Asthma and PM10

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Gilmour M Ian

2000-07-01

Full Text Available Abstract PM10 (the mass of particles present in the air having a 50% cutoff for particles with an aerodynamic diameter of 10 μm is the standard measure of particulate air pollution used worldwide. Epidemiological studies suggest that asthma symptoms can be worsened by increases in the levels of PM10. Epidemiological evidence at present indicates that PM10 increases do not raise the chances of initial sensitisation and induction of disease, although further research is warranted. PM10 is a complex mixture of particle types and has many components and there is no general agreement regarding which component(s could lead to exacerbations of asthma. However pro-inflammatory effects of transition metals, hydrocarbons, ultrafine particles and endotoxin, all present to varying degrees in PM10, could be important. An understanding of the role of the different components of PM10 in exacerbating asthma is essential before proper risk assessment can be undertaken leading to advice on risk management for the many asthmatics who are exposed to air pollution particles.

Indoor air quality modeling for PM 10, PM 2.5, and PM 1.0 in naturally ventilated classrooms of an urban Indian school building.

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Goyal, Radha; Khare, Mukesh

2011-05-01

Assessment of indoor air quality (IAQ) in classrooms of school buildings is of prime concern due to its potential effects on student's health and performance as they spend a substantial amount of their time (6-7 h per day) in schools. A number of airborne contaminants may be present in urban school environment. However, respirable suspended particulate matter (RSPM) is of great significance as they may significantly affect occupants' health. The objectives of the present study are twofold, one, to measure the concentrations of PM(10) (building located near a heavy-traffic roadway (9,755 and 4,296 vehicles/hour during weekdays and weekends, respectively); and second, to develop single compartment mass balance-based IAQ models for PM(10) (NVIAQM(pm10)), PM(2.5) (NVIAQM(pm2.5)), and PM(1.0) (NVIAQM(pm1.0)) for predicting their indoor concentrations. Outdoor RSPM levels and classroom characteristics, such as size, occupancy level, temperature, relative humidity, and CO(2) concentrations have also been monitored during school hours. Predicted indoor PM(10) concentrations show poor correlations with observed indoor PM(10) concentrations (R (2) = 0.028 for weekdays, and 0.47 for weekends). However, a fair degree of agreement (d) has been found between observed and predicted concentrations, i.e., 0.42 for weekdays and 0.59 for weekends. Furthermore, NVIAQM(pm2.5) and NVIAQM(pm1.0) results show good correlations with observed concentrations of PM(2.5) (R(2) = 0.87 for weekdays and 0.9 for weekends) and PM(1.0) (R(2) = 0.86 for weekdays and 0.87 for weekends). NVIAQM(pm10) shows the tendency to underpredict indoor PM(10) concentrations during weekdays as it does not take into account the occupant's activities and its effects on the indoor concentrations during the class hours. Intense occupant's activities cause resuspension or delayed deposition of PM(10). The model results further suggests conductance of experimental and physical simulation studies on dispersion of

Diagnosis of Dust- and Pollution- Impacted PM10, PM2.5, and PM1 Aerosols Observed at Gosan Climate Observatory

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Shang, X.; Lee, M.; LIM, S.; Gustafsson, O.; Lee, G.; Chang, L.

2017-12-01

In East Asia, dust is prevalent and used to be mixed with various pollutants during transportation, causing a large uncertainty in estimating the climate forcing of aerosol and difficulty in making environmental policy. In order to diagnose the influence of dust particles on aerosol, we conducted a long-term measurement of PM10, PM2.5 and PM1 for mass, water-soluble ions, and carbonaceous compounds at Gosan Climate Observatory, South Korea from August 2007 to February 2012. The result of principle component analysis reveals that anthropogenic, typical soil dust, and saline dust impact explain 46 %, 16 %, and 9 % of the total variance for all samples, respectively. The mode analysis of mass distributions provides the criteria to distinguish these principle factors. The anthropogenic impact was most pronounced in PM1 and diagnosed by the PM1 mass higher than mean+σ. If PM10 mass was greater than mean+σ, it was highly likely to be affected by typical soil dust. This criterion is also applicable for PM2.5 mass, which was enhanced by both haze and dust particles, though. In the present study, saline dust was recognized by relatively high concentrations of Na and Cl ions in PM1.0. However, their existence was not manifested by increased mass in any of three PM types.

Modeling extreme PM10 concentration in Malaysia using generalized extreme value distribution

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Hasan, Husna; Mansor, Nadiah; Salleh, Nur Hanim Mohd

2015-05-01

Extreme PM10 concentration from the Air Pollutant Index (API) at thirteen monitoring stations in Malaysia is modeled using the Generalized Extreme Value (GEV) distribution. The data is blocked into monthly selection period. The Mann-Kendall (MK) test suggests a non-stationary model so two models are considered for the stations with trend. The likelihood ratio test is used to determine the best fitted model and the result shows that only two stations favor the non-stationary model (Model 2) while the other eleven stations favor stationary model (Model 1). The return level of PM10 concentration that is expected to exceed the maximum once within a selected period is obtained.

Modelling street level PM10 concentrations across Europe: source apportionment and possible futures

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G. Kiesewetter

2015-02-01

Full Text Available Despite increasing emission controls, particulate matter (PM has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter 10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

Predictability Analysis of PM10 Concentrations in Budapest

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Ferenczi, Zita

2013-04-01

Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.

Ambient endotoxin in PM10 and association with inflammatory activity, air pollutants, and meteorology, in Chitwan, Nepal.

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Mahapatra, Parth Sarathi; Jain, Sumeet; Shrestha, Sujan; Senapati, Shantibhusan; Puppala, Siva Praveen

2018-03-15

Endotoxin associated with ambient PM (particulate matter) has been linked to adverse respiratory symptoms, but there have been few studies of ambient endotoxin and its association with co-pollutants and inflammation. Our aim was to measure endotoxin associated with ambient PM 10 (particulate matter with aerodynamic diametermeteorology, co-pollutants, and inflammatory activity. PM 10 concentrations were recorded and filter paper samples were collected using E-samplers; PM 1, PM 2.5 , black carbon (BC), methane (CH 4 ), and carbon monoxide (CO) were also measured. The Limulus amebocyte lysate (LAL) assay was used for endotoxin quantification and the nuclear factor kappa B (NFκB) activation assay to assess inflammatory activity. The mean concentration of PM 10 at the different locations ranged from 136 to 189μg/m 3 , and of endotoxin from 0.29 to 0.53EU/m 3 . Pollutant presence was positively correlated with endotoxin. Apart from relative humidity, meteorological variations had no significant impact on endotoxin concentration. NF-κB activity was negatively correlated with endotoxin concentration. To the best of our knowledge, this study provides the first measurements of ambient endotoxin associated with PM 10 in Nepal. Endotoxin and co-pollutants were positively associated indicating a similar source. Endotoxin was negatively correlated with inflammatory activity as a result of a time-limited forest fire event during the sampling period. Studies of co-pollutants suggested that the higher levels of endotoxin related to biomass burning were accompanied by increased levels of anti-inflammatory agents, which suppressed the endotoxin inflammatory effect. Copyright © 2017. Published by Elsevier B.V.

Evaluation for Long Term PM10 Concentration Forecasting using Multi Linear Regression (MLR and Principal Component Regression (PCR Models

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Samsuri Abdullah

2016-07-01

Full Text Available Air pollution in Peninsular Malaysia is dominated by particulate matter which is demonstrated by having the highest Air Pollution Index (API value compared to the other pollutants at most part of the country. Particulate Matter (PM10 forecasting models development is crucial because it allows the authority and citizens of a community to take necessary actions to limit their exposure to harmful levels of particulates pollution and implement protection measures to significantly improve air quality on designated locations. This study aims in improving the ability of MLR using PCs inputs for PM10 concentrations forecasting. Daily observations for PM10 in Kuala Terengganu, Malaysia from January 2003 till December 2011 were utilized to forecast PM10 concentration levels. MLR and PCR (using PCs input models were developed and the performance was evaluated using RMSE, NAE and IA. Results revealed that PCR performed better than MLR due to the implementation of PCA which reduce intricacy and eliminate data multi-collinearity.

Impact of covariate models on the assessment of the air pollution-mortality association in a single- and multipollutant context.

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Sacks, Jason D; Ito, Kazuhiko; Wilson, William E; Neas, Lucas M

2012-10-01

With the advent of multicity studies, uniform statistical approaches have been developed to examine air pollution-mortality associations across cities. To assess the sensitivity of the air pollution-mortality association to different model specifications in a single and multipollutant context, the authors applied various regression models developed in previous multicity time-series studies of air pollution and mortality to data from Philadelphia, Pennsylvania (May 1992-September 1995). Single-pollutant analyses used daily cardiovascular mortality, fine particulate matter (particles with an aerodynamic diameter ≤2.5 µm; PM(2.5)), speciated PM(2.5), and gaseous pollutant data, while multipollutant analyses used source factors identified through principal component analysis. In single-pollutant analyses, risk estimates were relatively consistent across models for most PM(2.5) components and gaseous pollutants. However, risk estimates were inconsistent for ozone in all-year and warm-season analyses. Principal component analysis yielded factors with species associated with traffic, crustal material, residual oil, and coal. Risk estimates for these factors exhibited less sensitivity to alternative regression models compared with single-pollutant models. Factors associated with traffic and crustal material showed consistently positive associations in the warm season, while the coal combustion factor showed consistently positive associations in the cold season. Overall, mortality risk estimates examined using a source-oriented approach yielded more stable and precise risk estimates, compared with single-pollutant analyses.

Air Pollution Quality Index (AQI and Density of PM1, PM2.5 and PM10 in the Air of Qom

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M Azizifar

2012-05-01

Full Text Available

Background and Objectives: Air pollution has broad social, economical, political and technical aspects. one of the major issues in this regard is taking measures to prevent its increase. Since suspended particles are among the standard pollutants, the present study was carried out with the aim of measuring the amounts of these particles.

Methods: In the present study, the suspended particles ( PM₁, PM_2.5 and PM₁₀ were measured at two sites in Qom city. For each of them, 60 samples were selected with the Enviro Check during five consecutive months during summer (2 months and fall.

Results: During sampling, PM₁₀ in the period between October 22'th to November 22^nd 2007 had the maximum amount with the mean of 117µg/m³ and in the period between September 22'th to October 22^nd 2007 it had the minimum amount with the mean of 83µg/m³. PM_2.5 in the period between November 22^nd to December 22^nd 2007 with the mean of 33µg/m³ had the maximum amount and in the period  between July 22^nd to October 22^nd 2007 it had the minimum amount with the mean of 8µg/m³.

Conclusion: Based on the findings of this study, the densities of suspended particles PM₁, PM_2.5 and PM₁₀ were below the standard levels on most occasions. The amounts of AQI for them were normal and acceptable.

The role of perceived air pollution and health risk perception in health symptoms and disease: a population-based study combined with modelled levels of PM10.

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Orru, Kati; Nordin, Steven; Harzia, Hedi; Orru, Hans

2018-03-31

Adverse health impact of air pollution on health may not only be associated with the level of exposure, but rather mediated by perception of the pollution and by top-down processing (e.g. beliefs of the exposure being hazardous), especially in areas with relatively low levels of pollutants. The aim of this study was to test a model that describes interrelations between air pollution (particles pollution, health risk perception, health symptoms and diseases. A population-based questionnaire study was conducted among 1000 Estonian residents (sample was stratified by age, sex, and geographical location) about health risk perception and coping. The PM 10 levels were modelled in 1 × 1 km grids using a Eulerian air quality dispersion model. Respondents were ascribed their annual mean PM 10 exposure according to their home address. Path analysis was performed to test the validity of the model. The data refute the model proposing that exposure level significantly influences symptoms and disease. Instead, the perceived exposure influences symptoms and the effect of perceived exposure on disease is mediated by health risk perception. This relationship is more pronounced in large cities compared to smaller towns or rural areas. Perceived pollution and health risk perception, in particular in large cities, play important roles in understanding and predicting environmentally induced symptoms and diseases at relatively low levels of air pollution.

Investigation of air pollution of Shanghai subway stations in ventilation seasons in terms of PM2.5 and PM10.

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Guo, Erbao; Shen, Henggen; He, Lei; Zhang, Jiawen

2017-07-01

In November 2015, the PM 2.5 and PM 10 particulate matter (PM) levels in platforms, station halls, and rail areas of the Shangcheng and Jiashan Road Station were monitored to investigate air pollution in the Shanghai subway system. The results revealed that in subway stations, PM 2.5 and PM 10 concentrations were significantly higher than those in outdoor environments. In addition, particle concentrations in the platforms exceeded maximum levels that domestic safety standards allowed. Particularly on clear days, PM 2.5 and PM 10 concentrations in platforms were significantly higher than maximum standards levels. Owing to the piston effect, consistent time-varying trends were exhibited by PM 2.5 concentrations in platforms, station halls, and rail areas. Platform particle concentrations were higher than the amount in station halls, and they were higher on clear days than on rainy days. The time-varying trends of PM 10 and PM 2.5 concentrations in platforms and station halls were similar to each other. Activities within the station led to most of the inhalable particles within the station area. The mass concentration ratios of PM 2.5 and PM 10 in platforms were within 0.65-0.93, and fine particles were the dominant components.

Characteristics of PM1.0, PM2.5, and PM10, and Their Relation to Black Carbon in Wuhan, Central China

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Wei Gong

2015-09-01

Full Text Available Hourly average monitoring data for mass concentrations of PM1, PM2.5, PM10, and black carbon (BC were measured in Wuhan from December 2013 to December 2014, which has a flourishing steel industry, to analyze the characteristics of PM and their relation to BC, using statistical methods. The results indicate that variations in the monthly average mass concentrations of PM have similar concave parabolic shapes, with the highest values occurring in January and the lowest values appearing in August or September. The correlation coefficient of the linear regression model between PM1 and PM2.5 is quite high, reaching 0.99. Furthermore, the proportion of PM1 contained within PM2.5 is roughly 90%, directly proving that ultrafine particles whose diameter less than 1 μm may be a primary component of PM2.5 in Wuhan. Additionally, better seasonal correlation between PM and BC occurs only in summer and autumn, due to multiple factors such as topography, temperature, and the atmosphere in winter and spring. Finally, analysis of the diurnal variation of PM and BC demonstrates that the traffic emissions during rush hour, exogenous pollutants, and the shallow PBLH with stagnant atmosphere, all contribute to the severe pollution of Wuhan in winter.

PM(10) episodes in Greece: Local sources versus long-range transport-observations and model simulations.

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Matthaios, Vasileios N; Triantafyllou, Athanasios G; Koutrakis, Petros

2017-01-01

Periods of abnormally high concentrations of atmospheric pollutants, defined as air pollution episodes, can cause adverse health effects. Southern European countries experience high particulate matter (PM) levels originating from local and distant sources. In this study, we investigated the occurrence and nature of extreme PM 10 (PM with an aerodynamic diameter ≤10 μm) pollution episodes in Greece. We examined PM 10 concentration data from 18 monitoring stations located at five sites across the country: (1) an industrial area in northwestern Greece (Western Macedonia Lignite Area, WMLA), which includes sources such as lignite mining operations and lignite power plants that generate a high percentage of the energy in Greece; (2) the greater Athens area, the most populated area of the country; and (3) Thessaloniki, (4) Patra, and (5) Volos, three large cities in Greece. We defined extreme PM 10 pollution episodes (EEs) as days during which PM 10 concentrations at all five sites exceeded the European Union (EU) 24-hr PM 10 standards. For each EE, we identified the corresponding prevailing synoptic and local meteorological conditions, including wind surface data, for the period from January 2009 through December 2011. We also analyzed data from remote sensing and model simulations. We recorded 14 EEs that occurred over 49 days and could be grouped into two categories: (1) Local Source Impact (LSI; 26 days, 53%) and (2) African Dust Impact (ADI; 23 days, 47%). Our analysis suggested that the contribution of local sources to ADI EEs was relatively small. LSI EEs were observed only in the cold season, whereas ADI EEs occurred throughout the year, with a higher frequency during the cold season. The EEs with the highest intensity were recorded during African dust intrusions. ADI episodes were found to contribute more than local sources in Greece, with ADI and LSI fraction contribution ranging from 1.1 to 3.10. The EE contribution during ADI fluctuated from 41 to 83 �

Concentration distribution of NO{sub 2}, PM{sub 10} and PM{sub 2,5} in severe pollution episodes in Oslo, Drammen, Bergen and Trondheim; Konsentrasjonsfordelingen av NO{sub 2}, PM{sub 10} og PM{sub 2,5} i sterke forurensningsepisoder i Oslo, Drammen, Bergen og Trondheim

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Sloerdal, Leiv Haavard; Toennesen, Dag

1999-04-01

Based on hourly model calculations of NO{sub 2}, PM{sub 1}0 and PM{sub 2},5 through a 6 months winter season in the cities of Oslo, Drammen, Bergen and Trondheim, the 10 most severe pollution episodes have been analysed. Concentration distributions, calculated as the average of these episodes have been combined with the population distribution in order to reveal the exposure levels in such episodes. The model calculations have only been performed for the city background, i.e. on a km{sub 2} grid system. (author)

Indoor pollution: PM2.5 and PM10 from cigarette smoke

International Nuclear Information System (INIS)

Chianese, E.; Barone, G.; Castaldo, R.M.; Riccio, A.

2009-01-01

This work is aimed to establishing the temporal and spatial dispersion of PM 10 and PM 2.5 particulate matter fractions generated by cigarettes smoking in an indoor ambient. To this purpose, PM 10 and PM 2.5 concentrations were collected with a mobile instrument positioned in a room accommodating a smoking machine. [it

Spatiotemporal Characteristics of Air Pollutants (PM10, PM2.5, SO2, NO2, O3, and CO in the Inland Basin City of Chengdu, Southwest China

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Kuang Xiao

2018-02-01

Full Text Available Most cities in China are experiencing severe air pollution due to rapid economic development and accelerated urbanization. Long-term air pollution data with high temporal and spatial resolutions are needed to support research into physical and chemical processes that affect air quality, and the corresponding health risks. For the first time, data on PM10, PM2.5, SO2, NO2, O3 and CO concentrations in 23 ambient air quality automatic monitoring stations and routine meteorological were collected between January 2014 and December 2016 to determine the spatial and temporal variation in these pollutants and influencing factors in Chengdu. The annual mean concentrations of PM2.5 and PM10 exceeded the standard of Chinese Ambient Air Quality and World Health Organization guidelines standards at all of the stations. The concentrations of PM10, PM2.5, SO2 and CO decreased from 2014 to 2016, and the NO2 level was stable, whereas the O3 level increased markedly during this period. The air pollution characteristics in Chengdu showed simultaneously high PM concentrations and O3. High PM concentrations were mainly observed in the middle region of Chengdu and may have been due to the joint effects of industrial and vehicle emissions. Ozone pollution was mainly due to vehicle emissions in the downtown area, and industry had a more important effect on O3 in the northern area with fewer vehicles. The concentrations of PM10, PM2.5, NO2 and CO were highest in winter and lowest in summer; the highest SO2 concentration was also observed in winter and was lowest in autumn, whereas the O3 concentration peaked in summer. Haze pollution can easily form under the weather conditions of static wind, low temperature and relative humidity, and high surface pressure inside Chengdu. In contrast, severe ozone pollution is often associated with high temperature.

To what extent can aerosol water explain the discrepancy between model calculated and gravimetric PM10 and PM2.5?

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S. G. Tsyro

2005-01-01

Full Text Available Inter-comparisons of European air quality models show that regional transport models, including the EMEP (Co-operative Programme for monitoring and evaluation of the long-range transmission of air pollutants in Europe aerosol model, tend to underestimate the observed concentrations of PM10 and PM2.5. Obviously, an accurate representation of the individual aerosol constituents is a prerequisite for adequate calculation of PM concentrations. On the other hand, available measurements on the chemical characterization of ambient particles reveal that full chemical PM mass closure is rarely achieved. The fraction unaccounted for by chemical analysis can comprise as much as 30-40% of gravimetric PM10 or PM2.5 mass. The unaccounted PM mass can partly be due to non-C atoms in organic aerosols and/or due to sampling and measurement artefacts. Moreover, a part of the unaccounted PM mass is likely to consist of water associated with particles. Thus, the gravimetrically measured particle mass does not necessarily represent dry PM10 and PM2.5 mass. This is thought to be one of the reasons for models under-prediction of observed PM, if calculated dry PM10 and PM2.5 concentrations are compared with measurements. The EMEP aerosol model has been used to study to what extent particle-bound water can explain the chemically unidentified PM mass in filter-based particle samples. Water content of PM2.5 and PM10 has been estimated with the model for temperature 20°C and relative humidity 50%, which are conditions required for equilibration of dust-loaded filters according to the Reference method recommended by the European Committee for Standardization (CEN. Model calculations for Europe show that, depending on particle composition, particle-bound water constitutes 20-35% of the annual mean PM10 and PM2.5 concentrations, which is consistent with existing experimental estimates. At two Austrian sites, in Vienna and Streithofen, where daily measurements of PM2.5 mass

Receptor modeling studies for the characterization of PM10 pollution sources in Belgrade

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Mijić Zoran

2012-01-01

Full Text Available The objective of this study is to determine the major sources and potential source regions of PM10 over Belgrade, Serbia. The PM10 samples were collected from July 2003 to December 2006 in very urban area of Belgrade and concentrations of Al, V, Cr, Mn, Fe, Ni, Cu, Zn, Cd and Pb were analyzed by atomic absorption spectrometry. The analysis of seasonal variations of PM10 mass and some element concentrations reported relatively higher concentrations in winter, what underlined the importance of local emission sources. The Unmix model was used for source apportionment purpose and the four main source profiles (fossil fuel combustion; traffic exhaust/regional transport from industrial centers; traffic related particles/site specific sources and mineral/crustal matter were identified. Among the resolved factors the fossil fuel combustion was the highest contributor (34% followed by traffic/regional industry (26%. Conditional probability function (CPF results identified possible directions of local sources. The potential source contribution function (PSCF and concentration weighted trajectory (CWT receptor models were used to identify spatial source distribution and contribution of regional-scale transported aerosols. [Projekat Ministarstva nauke Republike Srbije, br. III43007 i br. III41011

Air Pollution and Suicide in 10 Cities in Northeast Asia: A Time-Stratified Case-Crossover Analysis.

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Kim, Yoonhee; Ng, Chris Fook Sheng; Chung, Yeonseung; Kim, Ho; Honda, Yasushi; Guo, Yue Leon; Lim, Youn-Hee; Chen, Bing-Yu; Page, Lisa A; Hashizume, Masahiro

2018-03-06

There is growing evidence suggesting an association between air pollution and suicide. However, previous findings varied depending on the type of air pollutant and study location. We examined the association between air pollutants and suicide in 10 large cities in South Korea, Japan, and Taiwan. We used a two-stage meta-analysis. First, we conducted a time-stratified case-crossover analysis to estimate the short-term association between nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), and particulate matter [aerodynamic diameter ≤10μm (PM 10 ), aerodynamic diameter ≤2.5μm (PM 2.5 ), and PM 10–2.5 ] and suicide, adjusted for weather factors, day-of-week, long-term time trends, and season. Then, we conducted a meta-analysis to combine the city-specific effect estimates for NO 2 , SO 2 , and PM 10 across 10 cities and for PM 2.5 and PM 10–2.5 across 3 cities. We first fitted single-pollutant models, followed by two-pollutant models to examine the robustness of the associations. Higher risk of suicide was associated with higher levels of NO 2 , SO 2 , PM 10 , and PM 10–2.5 over multiple days. The combined relative risks (RRs) were 1.019 for NO 2 (95% confidence interval [CI]: 0.999, 1.039), 1.020 for SO 2 (95% CI: 1.005, 1.036), 1.016 for PM 10 (95% CI: 1.004, 1.029), and 1.019 for PM 10–2.5 (95% CI: 1.005, 1.033) per interquartile range (IQR) increase in the 0-1 d average level of each pollutant. We found no evidence of an association for PM 2.5 . Some of the associations, particularly for SO 2 and NO 2 , were attenuated after adjusting for a second pollutant. Our findings suggest that higher levels of air pollution may be associated with suicide, and further research is merited to understand the underlying mechanisms. https://doi.org/10.1289/EHP2223.

Assessment of social losses of pollution's health caused by man-made pollution of atmospheric air with emissions of particulate matters (PM10

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Turos Ye.I.

2017-04-01

Full Text Available According to available estimates, about 3% of lethal outcomes from cardiac-pulmonary pathology and 5% from lung cancer are related to the impact of patriculate matters (PM. In the course of the study there were assessed social losses of population’s health (additional death cases caused by risk conditions of atmospheric air pollution with PM of various air-dynamic diameter (PM10, proper to emissions of various industrial enterprises. It was established that 90% of population of cities under study live under high exposures (≥50 µg/m3 health and risks for population (IRM=10-3÷10-4, caused by PM10 emissions. Results showed that metallurgical industry is responsible for 7,2 to 2193 additional mortality cases. The impact of machine building enterprises – from 0.06 to 21 cases; coke and chemical – from 1.5 to 36 cases; mining – from 1.1 to 14,6 cases. The findings revealed 0.6 % increase in lifetime mortality for each 10 µg/m3 in 24-hour average PM10 concentration. Based on research outcomes, a set of instruments was developed for implementation of air pollution risk management programs aimed at mitigation of health risks from (PM10 in highly exposed groups.

A simple method for the detection of PM2.5 air pollutions using MODIS data

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Kato, Yoshinobu

2016-05-01

In recent years, PM2.5 air pollution is a social and transboundary environmental issue with the rapid economic growth in many countries. As PM2.5 is small and includes various ingredients, the detection of PM2.5 air pollutions by using satellite data is difficult compared with the detection of dust and sandstorms. In this paper, we examine various images (i.e., single-band images, band-difference images, RGB composite color images) to find a good method for detecting PM2.5 air pollutions by using MODIS data. A good method for the detection of PM2.5 air pollution is {R, G, B = band10, band9, T11}, where T11 is the brightness temperature of band31. In this composite color image, PM2.5 air pollutions are represented by light purple or pink color. This proposed method is simpler than the method by Nagatani et al. (2013), and is useful to grasp the distribution of PM2.5 air pollutions in the wide area (e.g., from China and India to Japan). By comparing AVI image with the image by proposed method, DSS and PM2.5 air pollutions can be classified.

Preliminary PM2.5 and PM10 fractions source apportionment complemented by statistical accuracy determination

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Samek Lucyna

2016-03-01

Full Text Available Samples of PM10 and PM2.5 fractions were collected between the years 2010 and 2013 at the urban area of Krakow, Poland. Numerous types of air pollution sources are present at the site; these include steel and cement industries, traffic, municipal emission sources and biomass burning. Energy dispersive X-ray fluorescence was used to determine the concentrations of the following elements: Cl, K, Ca, Ti, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sr, As and Pb within the collected samples. Defining the elements as indicators, airborne particulate matter (APM source profiles were prepared by applying principal component analysis (PCA, factor analysis (FA and multiple linear regression (MLR. Four different factors identifying possible air pollution sources for both PM10 and PM2.5 fractions were attributed to municipal emissions, biomass burning, steel industry, traffic, cement and metal industry, Zn and Pb industry and secondary aerosols. The uncertainty associated with each loading was determined by a statistical simulation method that took into account the individual elemental concentrations and their corresponding uncertainties. It will be possible to identify two or more sources of air particulate matter pollution for a single factor in case it is extremely difficult to separate the sources.

Spatiotemporal estimation of historical PM2.5 concentrations using PM10, meteorological variables, and spatial effect

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Li, Lianfa; Wu, Anna H.; Cheng, Iona; Chen, Jiu-Chiuan; Wu, Jun

2017-10-01

Monitoring of fine particulate matter with diameter health outcomes such as cancer. In this study, we aimed to design a flexible approach to reliably estimate historical PM2.5 concentrations by incorporating spatial effect and the measurements of existing co-pollutants such as particulate matter with diameter additive non-linear model. The spatiotemporal model was evaluated, using leaving-one-site-month-out cross validation. Our final daily model had an R2 of 0.81, with PM10, meteorological variables, and spatial autocorrelation, explaining 55%, 10%, and 10% of the variance in PM2.5 concentrations, respectively. The model had a cross-validation R2 of 0.83 for monthly PM2.5 concentrations (N = 8170) and 0.79 for daily PM2.5 concentrations (N = 51,421) with few extreme values in prediction. Further, the incorporation of spatial effects reduced bias in predictions. Our approach achieved a cross validation R2 of 0.61 for the daily model when PM10 was replaced by total suspended particulate. Our model can robustly estimate historical PM2.5 concentrations in California when PM2.5 measurements were not available.

Short Term Prediction of PM10 Concentrations Using Seasonal Time Series Analysis

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Hamid Hazrul Abdul

2016-01-01

Full Text Available Air pollution modelling is one of an important tool that usually used to make short term and long term prediction. Since air pollution gives a big impact especially to human health, prediction of air pollutants concentration is needed to help the local authorities to give an early warning to people who are in risk of acute and chronic health effects from air pollution. Finding the best time series model would allow prediction to be made accurately. This research was carried out to find the best time series model to predict the PM10 concentrations in Nilai, Negeri Sembilan, Malaysia. By considering two seasons which is wet season (north east monsoon and dry season (south west monsoon, seasonal autoregressive integrated moving average model were used to find the most suitable model to predict the PM10 concentrations in Nilai, Negeri Sembilan by using three error measures. Based on AIC statistics, results show that ARIMA (1, 1, 1 × (1, 0, 012 is the most suitable model to predict PM10 concentrations in Nilai, Negeri Sembilan.

The Effects of Bus Ridership on Airborne Particulate Matter (PM10 Concentrations

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Jaeseok Her

2016-07-01

Full Text Available Air pollution caused by rapid urbanization and the increased use of private vehicles seriously affects citizens’ health. In order to alleviate air pollution, many cities have replaced diesel buses with compressed natural gas (CNG buses that emit less exhaust gas. Urban planning strategies such as transit-oriented development (TOD posit that reducing private vehicle use and increasing public transportation use would reduce air pollution levels. The present study examined the effects of bus ridership on airborne particulate matter (PM10 concentrations in the capital region of Korea. We interpolated the levels of PM10 from 128 air pollution monitoring stations, utilizing the Kriging method. Spatial regression models were used to estimate the impact of bus ridership on PM10 levels, controlling for physical environment attributes and socio-economic factors. The analysis identified that PM10 concentration levels tend to be lower in areas with greater bus ridership. This result implies that urban and transportation policies designed to promote public transportation may be effective strategies for reducing air pollution.

Comprehensive urban air quality studies of Islamabad: elemental characterization of PM10 and PM2.5, source apportionment and transboundary pollutant migration (abstract)

International Nuclear Information System (INIS)

Waheed, S.; Siddique, N.; Daud, M.

2011-01-01

Long term urban air quality of Islamabad, the capital city of Pakistan, has been investigated as a part of the joint UNDP/IAEA/RCA/RAS/7/015 project, entitled C haracterization and source identification of particulate air pollution in the Asian region (RCA) . Around 380 pairs of fine (PM2.5) and coarse (PM10-2.5) polycarbonate filters from the Nilore area were collected using GENT sampler. The average PM2.5 and PM2.5-10 masses at this site were found to be 15.02 and 37.01 g/m/sup 3/ respectively that are far below to the Pakistani limit for PM10 of 100 g/m/sup 3/. The average Black Carbon (BC) was found to be 2.58 and 1.22 g/m/sup 3/ corresponding to 20.7% and 4.54% of the fine and coarse mass respectively. The non destructive Ion Beam Analysis method, Proton induced X-ray emission (PIXE) and Proton induced gamma ray emission (PIGE) were employed to quantify more than 40 elements in both fine and coarse fractions. The acquired elemental data has been statistically treated and subjected to mass closure studies, principal component and factor analysis to calculate correlation matrices. The reconstructed mass (RCM) was calculated for both particle modes using soil, sulphate, smoke, sea salt and BC as pseudo sources. Data analysis performed using EPA-PMF3 shows that the fine and coarse data for the suburban site identifies 4 sources; biomass/ combustion, road dust, soil and automobile. Long range transport of pollutants was studied using HYSPLIT4 model. It was observed that high fine soil contributions in this area were mainly from dust storms arriving from west and North West of the country. (author)

Modelling street level PM10 concentrations across Europe: source apportionment and possible futures

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Kiesewetter, G.; Borken-Kleefeld, J.; Schöpp, W.; Heyes, C.; Thunis, P.; Bessagnet, B.; Terrenoire, E.; Fagerli, H.; Nyiri, A.; Amann, M.

2015-02-01

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000-2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are

Background Atmospheric Levels of Aldehydes, BTEX and PM10 Pollutants in a Medium-Sized City of Southern Italy

International Nuclear Information System (INIS)

Iovino, P.; Salvestrini, S.; Capasso, S.

2007-01-01

Background atmospheric levels of aldehydes, BTEX and PM10 pollutants were measured in the suburb of Caserta (Italy), 75 thousands inhabitants, 41 0 04' N, on rainless weekdays and weekends during 2005. On weekdays the average daily concentrations (μg m -3 ) were 41.6 PM10, 8.6 benzene, 25.2 toluene, 6.3 ethylbenzene, 14.0 (m+p)-xylene, 11.7 o-xylene, 6.5 formaldehyde, 3.3 acetaldehyde. All the pollutant concentrations were strictly correlated (mean correlation coefficients = 0.90). At weekends the concentrations were lower by about 1.6 times. Both on weekdays and at weekends the PM10 and benzene levels exceeded the limits set by the EU Directive 30/1999 and 69/2000, respectively

The Interaction between Ambient PM10 and NO₂ on Mortality in Guangzhou, China.

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Gu, Yuzhou; Lin, Hualiang; Liu, Tao; Xiao, Jianpeng; Zeng, Weilin; Li, Zhihao; Lv, Xiaojuan; Ma, Wenjun

2017-11-13

Air pollution is now a significant environmental issue in China. To better understand the health impacts of ambient air pollution, this study investigated the potential interaction between PM 10 and NO₂ on mortality in Guangzhou, China. Time series data of daily non-accidental mortality and concentrations of PM 10 and NO₂ from 2006 to 2010 were collected. Based on generalized additive model, we developed two models (bivariate model and stratified model) to explore the interaction both qualitatively and quantitatively. At lag of 0-2 days, greater interactive effects between PM 10 and NO₂ were presented in the graphs. Positive modified effects were also found between the two pollutants on total non-accidental death and cardiovascular death. When the NO₂ concentration was at a high level (>76.14 μg/m³), PM 10 showed the greatest excess relative risk percentage (ERR%) for total non-accidental mortality (0.46, 95% CI: 0.13-0.79) and cardiovascular disease mortality (0.61, 95% CI: 0.06-1.16) for each 10 μg/m³ increase. During the period of high PM 10 concentration (>89.82 μg/m³), NO₂ demonstrated its strongest effect for total non-accidental mortality (ERR%: 0.92, 95% CI: 0.42-1.42) and cardiovascular disease mortality (ERR%: 1.20, 95% CI: 0.38-2.03). Our results suggest a positive interaction between PM 10 and NO₂ on non-accidental mortality in Guangzhou.

Relationships of relative humidity with PM2.5 and PM10 in the Yangtze River Delta, China.

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Lou, Cairong; Liu, Hongyu; Li, Yufeng; Peng, Yan; Wang, Juan; Dai, Lingjun

2017-10-23

Severe particulate matter (PM, including PM 2.5 and PM 10 ) pollution frequently impacts many cities in the Yangtze River Delta (YRD) in China, which has aroused growing concern. In this study, we examined the associations between relative humidity (RH) and PM pollution using the equal step-size statistical method. Our results revealed that RH had an inverted U-shaped relationship with PM 2.5 concentrations (peaking at RH = 45-70%), and an inverted V-shaped relationship (peaking at RH = 40 ± 5%) with PM 10 , SO 2 , and NO 2 . The trends of polluted-day number significantly changed at RH = 70%. The very-dry (RH humidity (RH = 60-70%) conditions positively affected PM 2.5 and exerted an accumulation effect, while the mid-humidity (RH = 70-80%), high-humidity (RH = 80-90%), and extreme-humidity (RH = 90-100%) conditions played a significant role in reducing particle concentrations. For PM 10 , the accumulation and reduction effects of RH were split at RH = 45%. Moreover, an upward slope in the PM 2.5 /PM 10 ratio indicated that the accumulation effects from increasing RH were more intense on PM 2.5 than on PM 10 , while the opposite was noticed for the reduction effects. Secondary transformations from SO 2 and NO 2 to sulfate and nitrate were mainly responsible for PM 2.5 pollution, and thus, controlling these precursors is effective in mitigating the PM pollution in the YRD, especially during winter. The conclusions in this study will be helpful for regional air-quality management.

Ambient air pollutant PM10 and risk of pregnancy-induced hypertension in urban China

International Nuclear Information System (INIS)

Huang, Xin; Qiu, Jie; Qiu, Weitao; He, Xiaochun; Wang, Yixuan; Sun, Qingmei; Cui, Hongmei; Liu, Sufen; Tang, Zhongfeng; Chen, Ya; Yue, Li; Da, Zhenqiang; Lv, Ling; Lin, Xiaojuan; Zhang, Chong; Zhang, Honghong; Xu, Ruifeng; Zhu, Daling; Zhang, Yaqun; Zhao, Nan

2015-01-01

Background: The relationship between air borne particulate matter ≤10 μm (PM 10 ) exposure and pregnancy-induced hypertension (PIH) is inconclusive. Few studies have been conducted, and fewer were conducted in areas with high levels of PM 10 . Methods: To examine the association between PM 10 and PIH by different exposure time windows during pregnancy, we analyzed data from a birth cohort study conducted in Lanzhou, China including 8 745 pregnant women with available information on air pollution during pregnancy. A total of 333 PIH cases (127 gestational hypertension (GH) and 206 preeclampsia (PE)) were identified. PM 10 daily average concentrations of each subject were calculated according to the distance between home/work addresses and monitor stations using an inverse-distance weighting approach. Results: Average PM 10 concentration over the duration of entire pregnancy was significantly associated with PIH (OR = 1.12, 95%CI: 1.02, 1.23 per 10 μg m −3 increase), PE (OR = 1.16, 95%CI: 1.03, 1.30 per 10 μg m −3 increase), late onset PE (OR = 1.17, 95% CI: 1.03, 1.32 per10 μg m −3 increase), and severe PE (OR = 1.25, 95% CI: 1.06, 1.48 per 10 μg m −3 increase). Average PM 10 during the first 12 gestational weeks was associated with the risk of GH (OR = 1.10, 95% CI: 1.00, 1.21 per 10 μg m −3 increase), and PM 10 exposure before 20 gestational weeks was associated with the risk of severe PE (OR = 1.14, 95% CI: 1.01, 1.30 per 10 μg m −3 increase). Conclusions: We found that high level exposure to ambient PM 10 during pregnancy was associated with an increased risk of PIH, GH and PE and that the strength of the association varied by timing of exposure during pregnancy. (letter)

Investigation of Air Quality Index and PM10 and PM2.5 in Arak

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Fatemeh Fazelinia

2013-12-01

Full Text Available Background and purpose: In this study, the air quality index and concentration of particles such as PM10 and PM2.5 were investigated in Arak. Materials and Methods: To determine the concentration of PM10 and PM2.5, 60 samples were collected by laser TSI model 8520 in summer and winter 2012. The collection site was around Arak city center. Results: during the sampling period, as a matter of PM10, the cleanest and the most polluted month were December and June with the average of 34.33 µg m-3 and 100.1 µg m-3, respectively. The concentration of PM2.5 was 12.93 and 53.17 µg m-3 for December and June, respectively. Meanwhile, in terms of air quality index (AQI, in 98.3% and 70% of cases, the concentrations of PM10 and PM2.5, respectively were less than normal (AQI100. Conclusion: The concentration of PM10 in the study period was less than Environmental Protection Agency (EPA 2006 guideline. Meanwhile, the concentrations of PM2.5 in 30% of air samples were greater than EPA guideline. The average PM2.5/PM10 ratio during the sampling period was 0.41 compared to range 0.15 to 0.25 reported by EPA.

[Preliminary study of source apportionment of PM10 and PM2.5 in three cities of China during spring].

Science.gov (United States)

Gao, Shen; Pan, Xiao-chuan; Madaniyazi, Li-na; Xie, Juan; He, Ya-hui

2013-09-01

To study source apportionment of atmospheric PM10 (particle matter ≤ 10 µm in aerodynamic diameter) and PM2.5 (particle matter ≤ 2.5 µm in aerodynamic diameter) in Beijing,Urumqi and Qingdao, China. The atmospheric particle samples of PM10 and PM2.5 collected from Beijing between May 17th and June 18th, 2005, from Urumqi between April 20th and June 1st, 2006 and from Qingdao between April 4th and May 15th, 2005, were detected to trace the source apportionment by factor analysis and enrichment factor methods. In Beijing, the source apportionment results derived from factor analysis model for PM10 were construction dust and soil sand dust (contributing rate of variance at 45.35%), industry dust, coal-combusted smoke and vehicle emissions (contributing rate at 31.83%), and biomass burning dust (13.57%). The main pollution element was Pb, while the content (median (minimum value-maximum value)was 0.216 (0.040-0.795) µg/m(3)) . As for PM2.5, the sources were construction dust and soil sand dust (38.86%), industry dust, coal-combusted smoke and vehicle emissions (25.73%), biomass burning dust (13.10%) and burning oil dust (11.92%). The main pollution element was Zn (0.365(0.126-0.808) µg/m(3)).In Urumqi, source apportionment results for PM10 were soil sand dust and coal-combusted dust(49.75%), industry dust, vehicle emissions and secondary particles dust (30.65%). The main characteristic pollution element was Cd (0.463(0.033-1.351) ng/m(3)). As for PM2.5, the sources were soil sand dust and coal-combusted dust (43.26%), secondary particles dust (22.29%), industry dust and vehicle emissions (20.50%). The main characteristic pollution element was As (14.599 (1.696-36.741) µg/m(3)).In Qingdao, source apportionment results for PM10 were construction dust (30.91%), vehicle emissions and industry dust (29.65%) and secondary particles dust (28.99%). The main characteristic pollution element was Pb (64.071 (5.846-346.831) µg/m(3)). As for PM2.5, the sources were

PM10 modeling in the Oviedo urban area (Northern Spain) by using multivariate adaptive regression splines

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Nieto, Paulino José García; Antón, Juan Carlos Álvarez; Vilán, José Antonio Vilán; García-Gonzalo, Esperanza

2014-10-01

The aim of this research work is to build a regression model of the particulate matter up to 10 micrometers in size (PM10) by using the multivariate adaptive regression splines (MARS) technique in the Oviedo urban area (Northern Spain) at local scale. This research work explores the use of a nonparametric regression algorithm known as multivariate adaptive regression splines (MARS) which has the ability to approximate the relationship between the inputs and outputs, and express the relationship mathematically. In this sense, hazardous air pollutants or toxic air contaminants refer to any substance that may cause or contribute to an increase in mortality or serious illness, or that may pose a present or potential hazard to human health. To accomplish the objective of this study, the experimental dataset of nitrogen oxides (NOx), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3) and dust (PM10) were collected over 3 years (2006-2008) and they are used to create a highly nonlinear model of the PM10 in the Oviedo urban nucleus (Northern Spain) based on the MARS technique. One main objective of this model is to obtain a preliminary estimate of the dependence between PM10 pollutant in the Oviedo urban area at local scale. A second aim is to determine the factors with the greatest bearing on air quality with a view to proposing health and lifestyle improvements. The United States National Ambient Air Quality Standards (NAAQS) establishes the limit values of the main pollutants in the atmosphere in order to ensure the health of healthy people. Firstly, this MARS regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the main pollutants in the Oviedo urban area. Secondly, the main advantages of MARS are its capacity to produce simple, easy-to-interpret models, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, on the basis of

The Concentrations and Reduction of Airborne Particulate Matter (PM10, PM2.5, PM1 at Shelterbelt Site in Beijing

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Jungang Chen

2015-05-01

Full Text Available Particulate matter is a serious source of air pollution in urban areas, where it exerts adverse effects on human health. This article focuses on the study of subduction of shelterbelts for atmospheric particulates. The results suggest that (1 the PM mass concentration is higher in the morning or both morning and noon inside the shelterbelts and lower mass concentrations at other times; (2 the particle mass concentration inside shelterbelt is higher than outside; (3 the particle interception efficiency of the two forest belts over the three months in descending order was PM10 > PM1 > PM2.5; and (4 the two shelterbelts captured air pollutants at rates of 1496.285 and 909.075 kg/month and the major atmospheric pollutant in Beijing city is PM10. Future research directions are to study PM mass concentration variation of shelterbelt with different tree species and different configuration.

Modelling PM 10 concentrations and carrying capacity associated with woodheater emissions in Launceston, Tasmania

Science.gov (United States)

Luhar, Ashok K.; Galbally, Ian E.; Keywood, Melita

Launceston is one of the Australian cities most affected by particle pollution due to the use of woodheaters in the winter months, with frequent exceedences of the national standard, the National Environment Protection Measure for Ambient Air Quality (or Air NEPM in short), of 50 micrograms per cubic metre for daily PM 10 (particulate matter with an aerodynamic diameter of 10 μm or less). The main objective of the present study was to determine the woodheater carrying capacity for Launceston—the number of woodheaters that can operate in the city without exceeding the Air NEPM. For this purpose, a prognostic meteorological and air pollution model called TAPM is used, coupled to a gridded woodheater PM 10 emissions inventory. The latter was derived using information on dwelling density, the percentage of dwellings with woodheaters, woodheater emission rates and their diurnal and seasonal variations, and the proportions of compliant/non-compliant woodheaters and open fireplaces. The model simulations are performed for the year 1998, and the concentrations are scaled for previous and subsequent years using trends in woodheater numbers and types. The modelled number of exceedences of the Air NEPM for the period 1997-2004 is in good agreement with the observations. The modelling indicates that the PM 10 Air NEPM would be met in Launceston when the total number of woodheaters is 20% of the total number of dwellings, of which 76%, 18%, 6% would be compliant woodheaters, non-compliant woodheaters and open fireplaces, respectively. With the present trends in the regional woodheater profile, this should occur in the year 2007.

PM 10 Nonattainment Areas

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U.S. Environmental Protection Agency — This data layer identifies areas in the U.S. where air pollution levels have not met the National Ambient Air Quality Standards (NAAQS) for PM 10 and have been...

Comparison of Ground-Based PM2.5 and PM10 Concentrations in China, India, and the U.S.

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Xingchuan Yang

2018-07-01

Full Text Available Urbanization and industrialization have spurred air pollution, making it a global problem. An understanding of the spatiotemporal characteristics of PM2.5 and PM10 concentrations (particulate matter with an aerodynamic diameter of less than 2.5 μm and 10 μm, respectively is necessary to mitigate air pollution. We compared the characteristics of PM2.5 and PM10 concentrations and their trends of China, India, and the U.S. from 2014 to 2017. Particulate matter levels were lowest in the U.S., while China showed higher concentrations, and India showed the highest. Interestingly, significant declines in PM2.5 and PM10 concentrations were found in some of the most polluted regions in China as well as the U.S. No comparable decline was observed in India. A strong seasonal trend was observed in China and India, with the highest values occurring in winter and the lowest in summer. The opposite trend was noted for the U.S. PM2.5 was highly correlated with PM10 for both China and India, but the correlation was poor for the U.S. With regard to reducing particulate matter pollutant concentrations, developing countries can learn from the experiences of developed nations and benefit by establishing and implementing joint regional air pollution control programs.

Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area

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Alejandro Ivan Aguirre-Salado

2017-07-01

Full Text Available We implemented a spatial model for analysing PM 10 maxima across the Mexico City metropolitan area during the period 1995–2016. We assumed that these maxima follow a non-identical generalized extreme value (GEV distribution and modeled the trend by introducing multivariate smoothing spline functions into the probability GEV distribution. A flexible, three-stage hierarchical Bayesian approach was developed to analyse the distribution of the PM 10 maxima in space and time. We evaluated the statistical model’s performance by using a simulation study. The results showed strong evidence of a positive correlation between the PM 10 maxima and the longitude and latitude. The relationship between time and the PM 10 maxima was negative, indicating a decreasing trend over time. Finally, a high risk of PM 10 maxima presenting levels above 1000 μ g/m 3 (return period: 25 yr was observed in the northwestern region of the study area.

Human health risk due to variations in PM10-PM2.5 and associated PAHs levels

Science.gov (United States)

Sosa, Beatriz S.; Porta, Andrés; Colman Lerner, Jorge Esteban; Banda Noriega, Roxana; Massolo, Laura

2017-07-01

WHO (2012) reports that chronic exposure to air pollutants, including particulate matter (PM), causes the death of 7 million people, constituting the most important environmental risk for health in the world. IARC classifies contaminated outdoor air as carcinogenic, Group 1 category. However, in our countries there are few studies regarding air pollution levels and possible associated effects on public health. The current study determined PM and associated polycyclic aromatic hydrocarbons (PAHs) levels in outdoor air, identified their possible emission sources and analysed health risks in the city of Tandil (Argentina). PM10 and PM2.5 samples were collected using a low volume sampler (MiniVol TAS) in three areas: city centre, industrial and residential. Concentrations were determined by gravimetric methods and the content of the US EPA 16 priority PAHs was found by high performance liquid chromatography (HPLC). Description of the main emission sources and selection of monitoring sites resulted from spatial analysis and the IVE (International Vehicle Emissions) model was used in the characterisation of the traffic flow. Median values of 35.7 μgm-3 and 9.6 μgm-3 in PM10 and PM2.5 respectively and characteristic profiles were found for each area. Local values PAHs associated to PM10 and PM2.5, in general, were lower than 10ngm-3. The estimated Unit Risk for the three areas exceeds US EPA standards (9 × 10-5). The number of deaths attributable to short term exposure to outdoor PM10 was 4 cases in children under 5 years of age, and 21 cases in total population, for a relative risk of 1.037.

Estimation of health effects (morbidity and mortality attributed to PM10 and PM2.5 exposure using an Air Quality model in Bukan city, from 2015-2016 exposure using air quality model

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Bahram Kamarehie

2017-08-01

Full Text Available Background: Air Quality software is a useful tool for assessing the health risks associated with air pollutants. Quantifying the effects of exposure to air pollutants in terms of public health has become a critical component of policy discussion. The present study purposed to quantify the health effects of particulate matters on mortality and morbidity in a Bukan city hospital from 2015-2016. Methods: Information regarding coordinates, exposed population, number of stations used in profiling, mean and maximum concentrations (annual, winter, and summer, annual 98th percentile, baseline incidence (BI per 100 000 per year, and relative risk was needed for use with the software. Results: The average particulate matter concentration was higher in summer than in winter. The concentrations of PM10 in summer and winter were 84.37 and 74.86 μg m-3, respectively. The Air Quality model predicted that total mortality rates related to PM10 and PM2.5 were 33.3 and 49.8 deaths, respectively. As a result, 3.79% of the total mortality was due to PM10. In Bukan city, 2.004% of total deaths were due to cardiovascular mortality. The Air Quality model predicted that the deaths of 92.2 people were related to hospital admissions for respiratory disease. Conclusion: The continual evaluation of air quality data is necessary for investigating the effect of pollutants on human health.

Variations of PM2.5, PM10 mass concentration and health assessment in Islamabad, Pakistan

Science.gov (United States)

Memhood, Tariq; Tianle, Z.; Ahmad, I.; Li, X.; Shen, F.; Akram, W.; Dong, L.

2018-04-01

Sparse information appears in lack of awareness among the people regarding the linkage between particulate matter (PM) and mortality in Pakistan. The current study is aimed to investigate the seasonal mass concentration level of PM2.5 and PM10 in ambient air of Islamabad to assess the health risk of PM pollution. The sampling was carried out with two parallel medium volume air samplers on Whatman 47 mm quartz filter at a flow rate of 100L/min. Mass concentration was obtained by gravimetric analysis. A noticeable seasonal change in PM10 and PM2.5 mass concentration was observed. In case of PM2.5, the winter was a most polluted and spring was the cleanest season of 2017 in Islamabad with 69.97 and 40.44 μgm‑3 mean concentration. Contrary, highest (152.42 μgm‑3) and lowest (74.90 μgm‑3) PM10 mass concentration was observed in autumn and summer respectively. Air Quality index level for PM2.5 and PM10 was remained moderated to unhealthy and good to sensitive respectively. Regarding health risk assessment, using national data for mortality rates, the excess mortality due to PM2.5 and PM10 exposure has been calculated and amounts to over 198 and 98 deaths annually for Islamabad. Comparatively estimated lifetime risk for PM2.5 (1.16×10-6) was observed higher than PM10 (7.32×10-8).

Non-chemistry coupled PM10 modeling in Chiang Mai City, Northern Thailand: A fast operational approach for aerosol forecasts

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Macatangay, Ronald; Bagtasa, Gerry; Sonkaew, Thiranan

2017-09-01

The Weather Research and Forecasting (WRF v. 3.7) model was applied to model PM10 data in Chiang Mai city for 10-days during a high haze event utilizing updated land use categories from the Moderate Resolution Imaging Spectroradiometer (MODIS). A higher resolution meteorological lateral boundary condition (from 1 degree to 0.25 degree) was also used from the NCEP GDAS/FNL Global Tropospheric Analyses and Forecast Grid system. A 3-category urban canopy model was also added and the Thompson aerosol-aware microphysics parameterization scheme was used to model the aerosol number concentrations that were later converted to PM10 concentrations. Aerosol number concentration monthly climatology was firstly used as initial and lateral boundary conditions to model PM10 concentrations. These were compared to surface data obtained from two stations of the Pollution Control Department (PCD) of Thailand. The results from the modeled PM10 concentrations could not capture the variability (r = 0.29; 0.27 for each site) and underestimated a high PM10 spike during the period studied. The authors then added satellite data to the aerosol climatology that improved the comparison with observations (r = 0.45; 43). However, both model runs still were not able to capture the high PM10 concentration event. This requires further investigation.

Differentiating the effects of characteristics of PM pollution on mortality from ischemic and hemorrhagic strokes.

Science.gov (United States)

Lin, Hualiang; Tao, Jun; Du, Yaodong; Liu, Tao; Qian, Zhengmin; Tian, Linwei; Di, Qian; Zeng, Weilin; Xiao, Jianpeng; Guo, Lingchuan; Li, Xing; Xu, Yanjun; Ma, Wenjun

2016-03-01

Though increasing evidence supports significant association between particulate matter (PM) air pollution and stroke, it remains unclear what characteristics, such as particle size and chemical constituents, are responsible for this association. A time-series model with quasi-Poisson function was applied to assess the association of PM pollution with different particle sizes and chemical constituents with mortalities from ischemic and hemorrhagic strokes in Guangzhou, China, we controlled for potential confounding factors in the model, such as temporal trends, day of the week, public holidays, meteorological factors and influenza epidemic. We found significant association between stroke mortality and various PM fractions, such as PM10, PM2.5 and PM1, with generally larger magnitudes for smaller particles. For the PM2.5 chemical constituents, we found that organic carbon (OC), elemental carbon (EC), sulfate, nitrate and ammonium were significantly associated with stroke mortality. The analysis for specific types of stroke suggested that it was hemorrhagic stroke, rather than ischemic stroke, that was significantly associated with PM pollution. Our study shows that various PM pollution fractions are associated with stroke mortality, and constituents primarily from combustion and secondary aerosols might be the harmful components of PM2.5 in Guangzhou, and this study suggests that PM pollution is more relevant to hemorrhagic stroke in the study area, however, more studies are warranted due to the underlying limitations of this study. Copyright © 2015 Elsevier GmbH. All rights reserved.

ANALYSIS OF THE RESULTS OF MEASUREMENT OF CONCENTRATIONS OF AIR POLLUTION WITH PM10 AND PM2.5 MEASURING STATION SQUARE OF POZNAN IN BYDGOSZCZ

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Rafał Pasela

2017-02-01

Full Text Available The phenomenon of suspended particulate pollution PM10 and PM2.5 occurs in large urban areas where the main source of their presence is communication, which is primarily related to the combustion of liquid fuels. PM2.5 dust pollution is a major risk factor for diseases of the respiratory, cardiovascular, and allergy. Act regulating the standards and target dates for reducing concentrations of particulate matter in urban areas and in all the cities of over 100 thousand. residents of the Directive of the European Parliament and Council Directive 2008/50/EC of 21 May 2008. on ambient air quality and cleaner air for Europe (CAFE. The acceptable level of average daily concentration of PM10 is 50 μg/m3 and may be exceeded by not more than 35 times a year, while the level of allowable annual average concentration of 40 μg/m3. The aim of this study was to assess the state of air pollution of dust PM10 and PM2.5 for the selected area of the city of Bydgoszcz. The analysis was conducted using data from air monitoring stations located at Poznanska street. The station is owned by the Provincial Inspectorate for Environmental Protection (VIEP in Bydgoszcz. The studies have shown that the annual average concentration of particulate matter analyzed station in Bydgoszcz in the years 2013-2015 amounted to PM10 41 μg/m3 PM2.5 and 23 μg/m3. The results are on the borderline of acceptable levels of concentration resulting from the Regulation of the Minister of the Environment of 2 August 2012. The concentrations of particulate matter in ambient air are strongly associated with meteorological conditions. The definitely higher concentrations observed in the autumn-winter season. The decrease in temperature causes the combustion in the boiler house of fuels with a high emissions. The highest average daily concentration of suspended particulate matter was observed on Thursday and Friday in the winter months, and while the lowest concentration was recorded in the

Improvement of PM10 prediction in East Asia using inverse modeling

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Koo, Youn-Seo; Choi, Dae-Ryun; Kwon, Hi-Yong; Jang, Young-Kee; Han, Jin-Seok

2015-04-01

Aerosols from anthropogenic emissions in industrialized region in China as well as dust emissions from southern Mongolia and northern China that transport along prevailing northwestern wind have a large influence on the air quality in Korea. The emission inventory in the East Asia region is an important factor in chemical transport modeling (CTM) for PM10 (particulate matters less than 10 ㎛ in aerodynamic diameter) forecasts and air quality management in Korea. Most previous studies showed that predictions of PM10 mass concentration by the CTM were underestimated when comparing with observational data. In order to fill the gap in discrepancies between observations and CTM predictions, the inverse Bayesian approach with Comprehensive Air-quality Model with extension (CAMx) forward model was applied to obtain optimized a posteriori PM10 emissions in East Asia. The predicted PM10 concentrations with a priori emission were first compared with observations at monitoring sites in China and Korea for January and August 2008. The comparison showed that PM10 concentrations with a priori PM10 emissions for anthropogenic and dust sources were generally under-predicted. The result from the inverse modeling indicated that anthropogenic PM10 emissions in the industrialized and urbanized areas in China were underestimated while dust emissions from desert and barren soil in southern Mongolia and northern China were overestimated. A priori PM10 emissions from northeastern China regions including Shenyang, Changchun, and Harbin were underestimated by about 300% (i.e., the ratio of a posteriori to a priori PM10 emission was a factor of about 3). The predictions of PM10 concentrations with a posteriori emission showed better agreement with the observations, implying that the inverse modeling minimized the discrepancies in the model predictions by improving PM10 emissions in East Asia.

Revealing driving factors of China's PM2.5 pollution

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Zheng, Y.; Zhao, H.; Zhang, Q.; Geng, G.; Tong, D.; Peng, L.; He, K.

2017-12-01

China's rapid economic development and intensive energy consumption are deteriorating the air quality significantly. Understanding the key driving factors behind China's growing emissions of air pollutants and the accompanying PM2.5 pollution is critical for the development of China's clean air policies and also provides insight into how other emerging economies may develop a clear sky future. Here we reveal the socioeconomic drivers of the variations of China's PM2.5 concentrations during 2002-2012 by using an interdisciplinary framework that integrates an emission inventory model, an index decomposition analysis model, and a regional air quality model. The decomposition results demostrate that the improvements in emission efficiency and energy efficiency failed to offset the increased emissions of both primary PM2.5 and gaseous PM2.5 precursors (including SO2 NOx, and volatile organic compounds) triggered by the surging economic growth during 2002-2012. During the same time, the effects of energy structure, production structure and population growth were relatively less significant to all pollutants, which indicates the potential of large emission abatements through energy structure and production structure adjustment. Sensitivity simulations by the air quality model based on the provincial decomposition results also show that the economic growth have outpaced efficiency improvements in the increments of PM2.5 concentrations during the study years. As China continues to develop rapidly, future policies should promote further improvements in efficiency and accelerate the adjustments toward clean energy and production structures, which are critical for reducing China's emissions and alleviating the severe PM2.5 pollution.

A framework for delineating the regional boundaries of PM2.5 pollution: A case study of China.

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Liu, Jianzheng; Li, Weifeng; Wu, Jiansheng

2018-04-01

Fine particulate matter (PM 2.5 ) pollution has been a major issue in many countries. Considerable studies have demonstrated that PM 2.5 pollution is a regional issue, but little research has been done to investigate the regional extent of PM 2.5 pollution or to define areas in which PM 2.5 pollutants interact. To allow for a better understanding of the regional nature and spatial patterns of PM 2.5 pollution, This study proposes a novel framework for delineating regional boundaries of PM 2.5 pollution. The framework consists of four steps, including cross-correlation analysis, time-series clustering, generation of Voronoi polygons, and polygon smoothing using polynomial approximation with exponential kernel method. Using the framework, the regional PM 2.5 boundaries for China are produced and the boundaries define areas where the monthly PM 2.5 time series of any two cities show, on average, more than 50% similarity with each other. These areas demonstrate straightforwardly that PM 2.5 pollution is not limited to a single city or a single province. We also found that the PM 2.5 areas in China tend to be larger in cold months, but more fragmented in warm months, suggesting that, in cold months, the interactions between PM 2.5 concentrations in adjacent cities are stronger than in warmer months. The proposed framework provides a tool to delineate PM 2.5 boundaries and identify areas where PM 2.5 pollutants interact. It can help define air pollution management zones and assess impacts related to PM 2.5 pollution. It can also be used in analyses of other air pollutants. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulation And Forecasting of Daily Pm10 Concentrations Using Autoregressive Models In Kagithane Creek Valley, Istanbul

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Ağaç, Kübra; Koçak, Kasım; Deniz, Ali

2015-04-01

A time series approach using autoregressive model (AR), moving average model (MA) and seasonal autoregressive integrated moving average model (SARIMA) were used in this study to simulate and forecast daily PM10 concentrations in Kagithane Creek Valley, Istanbul. Hourly PM10 concentrations have been measured in Kagithane Creek Valley between 2010 and 2014 periods. Bosphorus divides the city in two parts as European and Asian parts. The historical part of the city takes place in Golden Horn. Our study area Kagithane Creek Valley is connected with this historical part. The study area is highly polluted because of its topographical structure and industrial activities. Also population density is extremely high in this site. The dispersion conditions are highly poor in this creek valley so it is necessary to calculate PM10 levels for air quality and human health. For given period there were some missing PM10 concentration values so to make an accurate calculations and to obtain exact results gap filling method was applied by Singular Spectrum Analysis (SSA). SSA is a new and efficient method for gap filling and it is an state-of-art modeling. SSA-MTM Toolkit was used for our study. SSA is considered as a noise reduction algorithm because it decomposes an original time series to trend (if exists), oscillatory and noise components by way of a singular value decomposition. The basic SSA algorithm has stages of decomposition and reconstruction. For given period daily and monthly PM10 concentrations were calculated and episodic periods are determined. Long term and short term PM10 concentrations were analyzed according to European Union (EU) standards. For simulation and forecasting of high level PM10 concentrations, meteorological data (wind speed, pressure and temperature) were used to see the relationship between daily PM10 concentrations. Fast Fourier Transformation (FFT) was also applied to the data to see the periodicity and according to these periods models were built

MUTAGENIC AND CYTOTOXIC FACTORS IN PM10 AND PM2.5 FRACTIONS IN ATMOSPHERE IN SOSNOWIEC

Directory of Open Access Journals (Sweden)

Agnieszka Kozłowska

2011-12-01

Full Text Available Air dust pollution enters human body via respiratory system. Its cytotoxic effect is surveyed using cell lines of mononuclear or pulmonary epithelial cell origins. Mutagenic properties are assessed using short-term assay on Salmonella typhimurium bacterial strains. Mutagenic and cytotoxic properties of air dust pollution – fractions PM10 and PM2.5, which were collected in autumn and in winter, were assessed using Ames test with Salmonella typhimurium strains and MTT cytoxicity assay on mononuclear cell line RAW 264.7, respectively. Samples of dust were collected on glass fiber filters by (Harvard impactor with air flow ca. 9 l/min, splitting samples to the fraction PM10 and PM2.5. Extraction of pollution was carried out using dichlorometane. Extracted samples were dissolved in dimethylsulfoxide (DMSO before analyses. The highest value of mutagenicity ratio (MR was observed in YG1041 strain with metabolic activation by S9 extract in the PM10 sample of dust collected in winter. The lowest one was observed in TA98 strain without activation in the PM2.5 sample of dust collected in autumn. Winter dust samples, both the fractions PM10 and PM2,5, were toxic for TA98 strain in both test conditions (5S9. MTT cytotoxicity assay using mononuclear cell line RAW 264.7 showed that fractions PM10 and PM2.5 collected in winter were of highest toxic properties. The viability of cells, which were treated with samples of 0,312 m3 air, were 1,7% and 1,6%, respectively, while for autumn samples for PM2,5 the viability was 63%.

Analysis of PM10, PM2.5, and PM2 5-10 concentrations in Santiago, Chile, from 1989 to 2001.

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Koutrakis, Petros; Sax, Sonja N; Sarnat, Jeremy A; Coull, Brent; Demokritou, Phil; Oyola, Pedro; Garcia, Javier; Gramsch, Ernesto

2005-03-01

Daily particle samples were collected in Santiago, Chile, at four urban locations from January 1, 1989, through December 31, 2001. Both fine PM with da Ambient Air Quality Standards and the European Union concentration limits. Mean PM2.5 levels during the cold season (April through September) were more than twice as high as those observed in the warm season (October through March); whereas coarse particle levels were similar in both seasons. PM concentration trends were investigated using regression models, controlling for site, weekday, month, wind speed, temperature, and RH. Results showed that PM2.5 concentrations decreased substantially, 52% over the 12-year period (1989-2000), whereas PM2.5-10 concentrations increased by approximately 50% in the first 5 years and then decreased by a similar percentage over the following 7 years. These decreases were evident even after controlling for significant climatic effects. These results suggest that the pollution reduction programs developed and implemented by the Comisión Nacional del Medio Ambiente (CONAMA) have been effective in reducing particle levels in the Santiago Metropolitan region. However, particle levels remain high and it is thus imperative that efforts to improve air quality continue.

To Investigate the Effects of Air Pollution (PM10 and SO2) on the Respiratory Diseases Asthma and Chronic Obstructive Pulmonary Disease.

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Saygın, Mustafa; Gonca, Taner; Öztürk, Önder; Has, Mehmet; Çalışkan, Sadettin; Has, Zehra Güliz; Akkaya, Ahmet

2017-04-01

Effects of air pollution parameters of sulfur dioxide (SO2) and particulate matter (PM10) values on the respiratory system were investigated. Data of SO 2 and PM10 were obtained daily for air pollution and classified into two groups: Group I (2006-2007), coal burning years and Group II (2008-2009), natural gas+ coal burning. Groups I and II were divided into two subgroups according to the months of combustion as combustible (November-April) and noncombustible (May-October). The number of patients with asthma and chronic obstructive pulmonary disorder (COPD) was recorded between 2006 and 2009. There was no statistically significant difference between Groups I and II for PM10 and SO 2 (p>0.05). Within the years, the values of SO 2 and PM10 were statistically different between the groups defined by month (p0.05). A correlation was found between SO 2 and COPD (p0.05). The number of visits for COPD and asthma was statistically different between combustible and noncombustible subgroups (X2:58.61, p=0.000; X2:34.55, p=0.000, respectively). The r2 values for SO 2 and PM10 for COPD patients were 17% and 24%, respectively, in contrast to 8% and 5%, respectivley for asthma patients. Air pollution is known to increase respiratory disease occurrences. With decrease in the usage of solid fuel, air pollution could be reduced and may be effective in preventing respiratory diseases.

Estimating the influence of different urban canopy cover types on atmospheric particulate matter (PM10) pollution abatement in London UK.

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Tallis, Matthew; Freer-Smith, Peter; Sinnett, Danielle; Aylott, Matthew; Taylor, Gail

2010-05-01

In the urban environment atmospheric pollution by PM10 (particulate matter with a diameter less than 10 x 10-6 m) is a problem that can have adverse effects on human health, particularly increasing rates of respiratory disease. The main contributors to atmospheric PM10 in the urban environment are road traffic, industry and power production. The urban tree canopy is a receptor for removing PM10s from the atmosphere due to the large surface areas generated by leaves and air turbulence created by the structure of the urban forest. In this context urban greening has long been known as a mechanism to contribute towards PM10 removal from the air, furthermore, tree canopy cover has a role in contributing towards a more sustainable urban environment. The work reported here has been carried out within the BRIDGE project (SustainaBle uRban plannIng Decision support accountinG for urban mEtabolism). The aim of this project is to assess the fluxes of energy, water, carbon dioxide and particulates within the urban environment and develope a DSS (Decision Support System) to aid urban planners in sustainable development. A combination of published urban canopy cover data from ground, airborne and satellite based surveys was used. For each of the 33 London boroughs the urban canopy was classified to three groups, urban woodland, street trees and garden trees and each group quantified in terms of ground cover. The total [PM10] for each borough was taken from the LAEI (London Atmospheric Emissions Inventory 2006) and the contribution to reducing [PM10] was assessed for each canopy type. Deposition to the urban canopy was assessed using the UFORE (Urban Forest Effects Model) approach. Deposition to the canopy, boundary layer height and percentage reduction of the [PM10] in the atmosphere was assessed using both hourly meterological data and [PM10] and seasonal data derived from annual models. Results from hourly and annual data were compared with measured values. The model was then

Disability-adjusted life years and economic cost assessment of the health effects related to PM2.5 and PM10 pollution in Mumbai and Delhi, in India from 1991 to 2015.

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Maji, Kamal Jyoti; Dikshit, Anil Kumar; Deshpande, Ashok

2017-02-01

Particulate air pollution is becoming a serious public health concern in urban cities in India due to air pollution-related health effects associated with disability-adjusted life years (DALYs) and economic loss. To obtain the quantitative result of health impact of particulate matter (PM) in most populated Mumbai City and most polluted Delhi City in India, an epidemiology-based exposure-response function has been used to calculate the attributable number of mortality and morbidity cases from 1991 to 2015 in a 5-year interval and the subsequent DALYs, and economic cost is estimated of the health damage based on unit values of the health outcomes. Here, we report the attributable number of mortality due to PM 10 in Mumbai and Delhi increased to 32,014 and 48,651 in 2015 compared with 19,291 and 19,716 in year 1995. And annual average mortality due to PM 2.5 in Mumbai and Delhi was 10,880 and 10,900. Premature cerebrovascular disease (CEV), ischemic heart disease (IHD), and chronic obstructive pulmonary disease (COPD) causes are about 35.3, 33.3, and 22.9% of PM 2.5 -attributable mortalities. Total DALYs due to PM10 increased from 0.34 million to 0.51 million in Mumbai and 0.34 million to 0.75 million in Delhi from average year 1995 to 2015. Among all health outcomes, mortality and chronic bronchitis shared about 95% of the total DALYs. Due to PM 10 , the estimated total economic cost at constant price year 2005 US$ increased from 2680.87 million to 4269.60 million for Mumbai City and 2714.10 million to 6394.74 million for Delhi City, from 1995 to 2015, and the total amount accounting about 1.01% of India's gross domestic product (GDP). A crucial presumption is that in 2030, PM 10 levels would have to decline by 44% (Mumbai) and 67% (Delhi) absolutely to maintain the same health outcomes in year 2015 levels. The results will help policy makers from pollution control board for further cost-benefit analyses of air pollution management programs in Mumbai and Delhi.

Study variation of PM-10 air pollution at Lang Meteorological Station, Hanoi Coded: CS/02/04-06

International Nuclear Information System (INIS)

Vuong Thu Bac; Dinh Thien Lam; Ngyen Thi Hong Thinh; Dang Duc Nhan; Nguyen Hao Quang; Pham Duy Hien

2003-01-01

577 air dust samples have been collected with two kinds of air samplers (2-SFU, 1-ASP) on every Wednesday and Sunday for 24 hours at both of monitoring stations (Lang - Hanoi and Lucnam - Bacgiang). PM(2.5), PM(2.5-10), PM(10) and BC concentrations in 452 air dust samples have been determined. 9032 data have been analyzed with many of different multi-elements analytical techniques (IC: 264 samples x 9 ions, PIXE: 388 samples x 15 elements, XRF: 48 samples x 8 elements, LR: 452 samples x 1 element). Over 6000 of meteorological parameters (T, Rain, WS, WD, RH...) have been collected and processed.Variations and levels of air dust concentrations and BC in Hanoi from 1998 to 2002 have been studied. PM(2.5), PM(2.5-10), PM(10) and BC concentrations and BC obviously periodically vary. They reach maximum in the winter season, especially in December and January, sometimes they reached 300-400 μg.m -3 , They reach minimum in the summer season, sometimes they went down 10 μg.m -3 on rainy days. These variations were affected by meteorological parameters. PM(2.5), PM(10) daily average concentrations in Hanoi are greater than the American air standards (PM(2.5): 65 μg.m -3 , PM(10): 150 μg.m -3 ) in many days and their yearly average concentrations are also far exceeded. Air dust pollution levels in Hanoi are higher than in developed countries and even countries in the region. BC (5.9 μg.m -3 ) concentration and Pb (0.11 μg.m -3 ) are also higher than in many countries. (VTB)

[Pollution characteristics and health risk assessment of heavy metals in PM(2.5) in Lanzhou].

Science.gov (United States)

Wei, Q Z; Li, S; Jia, Q; Luo, B; Su, L M; Liu, Q; Yuan, X R; Wang, Y H; Ruan, Y; Niu, J P

2018-06-06

Objective: To understand the pollution characteristics and assess the pollution health risks of heavy metals in atmospheric PM(2.5) in Lanzhou. Methods: According to the regional characteristics of air pollution and industrial distribution characteristics in Lanzhou, atmospheric PM(2.5) was sampled monthly in Chengguan and Xigu Districts from January, 2015 to December, 2016. Detected the concentration of PM(2.5) and 12 kinds of elements (Sb, Al, As, Be, Cd, Cr, Hg, Pb, Mn, Ni, Se and Tl) by weighing method and inductively coupled plasma mass spectrometry. Enrichment factor and geo-accumulation index were used to describe the pollution characteristics, while health risk assessment was conducted using the recommended United States Environmental Protection Agency (USA EPA) model. The health risks of non-carcinogens were evaluated by non-cancer hazard quotient (HQ), the non-carcinogenic risk was considered to be negligible when HQ1 meant a health risk. With a single contaminant cancer Risk value to evaluate the health risks of carcinogens, when the Risk value between 10(-6) to10(-4) as an acceptable level. Results: The daily average concentrations of PM(2.5) was 83.0 μg/m(3), 77.0 μg/m(3) in Chengguan and Xigu Districts, respectively, during the sampling periods, and the concentration of PM(2.5) in winter/spring was higher than summer/fall in both districts. The concentration of Al in PM(2.5) was the highest and other elements in descending order: Pb, Mn, As, Sb/Cd, Tl in both districts. Enrichment factor results showed that Al and Mn were mainly affected by natural factors, the rest of five elements were all typical man-made pollution elements and according to geo-accumulation index pollution level of Cd was the strongest in the winter. The results of health risk assessment showed that Mn had the highest non-cancer risks (HQ>1) and affected the health of the children seriously. HQ reached up to 2.44 and 1.79 in Chengguan and Xigu Districts, respectively. Pb, As, Sb

Environmental pollution: quantitative analysis of particulate matter (PM10) by SR-TXRF

International Nuclear Information System (INIS)

Moreira, Silvana; Melo Junior, Ariston da Silva; Zucchi, Orgheda Luiza Araujo Domingues; Vives, Ana Elisa Sirito de

2007-01-01

The atmospheric pollution is a concern in the great urban centers, due its association with man pathologies. The Campinas region is one of the most urbanized of the Sao Paulo State and an important industrial center. Thus, due to its location and importance were installed three samplers for particulate material (PM 10 ). One sampler was located in downtown of Campinas city, in an avenue with high vehicular flow. Another sampler was installed in the UNICAMP campus and the third one in Paulinia city, near to REPLAN. For downtown of Campinas city PM 10 concentrations higher than regular air quality established by CETESB (150 μg.m -3 ) was observed. The PM 10 values for Paulinia and downtown of Campinas were higher than Barao Geraldo location. Employing SR-TXRF was possible identify and quantify 19 elements in the particulate material samples. All the measurements were performed at Synchrotron Light Source Laboratory, Campinas, SP. After statistics analysis by principal components and cluster analysis was possible to assemble the elements according emission sources. The dusty soil for coarse fraction contributed with 62%, 51% and 46% for Barao Geraldo, Paulinia and downtown of Campinas, respectively. The vehicular emission was responsible for 16% at downtown Campinas city as expected due to high vehicular flow at sampling place. The vehicular and industrial emissions contributed with 20% and 25%, respectively at Paulinia sampling site. The industrial emissions observed for Barao Geraldo and downtown of Campinas city were 27% and 33%, respectively. (author)

Simultaneous monitoring and compositions analysis of PM1 and PM2.5 in Shanghai: Implications for characterization of haze pollution and source apportionment.

Science.gov (United States)

Qiao, Ting; Zhao, Mengfei; Xiu, Guangli; Yu, Jianzhen

2016-07-01

A year-long simultaneous observation of PM1 and PM2.5 were conducted at ECUST campus in Shanghai, the compositions were analyzed and compared. Results showed that PM2.5 was dominated by PM1 on clear days while the contribution of PM1-2.5 to PM2.5 increased on haze days, indicating that PM2.5 should be given priority to characterize or predict haze pollution. On haze days, accumulation of organic carbon (OC), elemental carbon (EC) and primary organic carbon (POC) in PM1-2.5 was faster than that in PM1. Humic-like substances carbon (Hulis-C) in both PM2.5 and PM1 formed faster than water soluble organic carbon (WSOC) on haze days, hence Hulis-C/WSOC increased with the intensification of haze pollution. In terms of water soluble ions, NO3(-)/SO4(2-) in PM1 increased with the aggravation of haze pollution, implying that mobile sources dominated on haze days, so is nitrogen oxidation ratio (NOR). Liquid water content (LWC) in both PM1 and PM2.5 had positive correlations with relative humidity (RH) but negative correlations with visibility, implying that hygroscopic growth might be a factor for visibility impairment, especially LWC in PM1. By comparison with multi-linear equations of LWC in PM1 and PM2.5, NO3(-) exerted a higher influence on hygroscopicity of PM1 than PM2.5, while RH, WSOC, SO4(2-) and NH4(+) had higher effects on PM2.5, especially WSOC. Source apportionment of PM2.5 was also investigated to provide reference for policy making. Cluster analysis by HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) model showed that PM2.5 originated from marine aerosols, middle-scale transportation and large-scale transportation. Furthermore, PM2.5 on haze days was dominated by middle-scale transportation. In line with source apportionment by positive matrix factorization (PMF) model, PM2.5 was attributed to secondary inorganics, aged sea salt, combustion emissions, hygroscopic growth and secondary organics. Secondary formation was the principle source of

Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study.

Science.gov (United States)

Fang, Xin; Li, Runkui; Kan, Haidong; Bottai, Matteo; Fang, Fang; Cao, Yang

2016-08-16

To demonstrate an application of Bayesian model averaging (BMA) with generalised additive mixed models (GAMM) and provide a novel modelling technique to assess the association between inhalable coarse particles (PM10) and respiratory mortality in time-series studies. A time-series study using regional death registry between 2009 and 2010. 8 districts in a large metropolitan area in Northern China. 9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010. Per cent increase in daily respiratory mortality rate (MR) per interquartile range (IQR) increase of PM10 concentration and corresponding 95% confidence interval (CI) in single-pollutant and multipollutant (including NOx, CO) models. The Bayesian model averaged GAMM (GAMM+BMA) and the optimal GAMM of PM10, multipollutants and principal components (PCs) of multipollutants showed comparable results for the effect of PM10 on daily respiratory MR, that is, one IQR increase in PM10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory MR. However, GAMM+BMA gave slightly but noticeable wider CIs for the single-pollutant model (-1.09 to 4.28 vs -1.08 to 3.93) and the PCs-based model (-2.23 to 4.07 vs -2.03 vs 3.88). The CIs of the multiple-pollutant model from two methods are similar, that is, -1.12 to 4.85 versus -1.11 versus 4.83. The BMA method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Inflammation response and cytotoxic effects in human THP-1 cells of size-fractionated PM10 extracts in a polluted urban site.

Science.gov (United States)

Schilirò, T; Alessandria, L; Bonetta, S; Carraro, E; Gilli, G

2016-02-01

To contribute to a greater characterization of the airborne particulate matter's toxicity, size-fractionated PM10 was sampled during different seasons in a polluted urban site in Torino, a northern Italian city. Three main size fractions (PM10 - 3 μm; PM3 - 0.95 μm; PM THP-1 cells to evaluate their effects on cell proliferation, LDH activity, TNFα, IL-8 and CYP1A1 expression. The mean PM10 concentrations were statistically different in summer and in winter and the finest fraction PMtest) that could be used in the context of the different monitoring programs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Household air pollution and personal inhalation exposure to particles (TSP/PM2.5/PM1.0/PM0.25) in rural Shanxi, North China

International Nuclear Information System (INIS)

Huang, Ye; Du, Wei; Chen, Yuanchen; Shen, Guofeng; Su, Shu; Lin, Nan; Shen, Huizhong; Zhu, Dan; Yuan, Chenyi; Duan, Yonghong; Liu, Junfeng; Li, Bengang; Tao, Shu

2017-01-01

Personal exposure to size-segregated particles among rural residents in Shanxi, China in summer, 2011 were investigated using portable carried samplers (N = 84). Household air pollution was simultaneously studied using stationary samplers in nine homes. Information on household fuel types, cooking activity, smoking behavior, kitchen ventilation conditions etc., were also collected and discussed. The study found that even in the summer period, the daily average concentrations of PM 2.5 and PM 1.0 in the kitchen were as high as 376 ± 573 and 288 ± 397 μg/m 3 (N = 6), that were nearly 3 times of 114 ± 81 and 97 ± 77 μg/m 3 in the bedroom (N = 8), and significantly higher than those of 64 ± 28 and 47 ± 21 μg/m 3 in the outdoor air (N = 6). The personal daily exposure to PM 2.5 and PM 1.0 were 98 ± 52 and 77 ± 47 μg/m 3 , respectively, that were lower than the concentrations in the kitchen but higher than the outdoor levels. The mass fractions of PM 2.5 in TSP were 90%, 72%, 65% and 68% on average in the kitchen, bedroom, outdoor air and personal inhalation exposure, respectively, and moreover, a majority of particles in PM 2.5 had diameters less than 1.0 μm. Calculated time-weighted average exposure based on indoor and outdoor air concentrations and time spent indoor and outdoor were positively correlated but, was ∼33% lower than the directly measured exposure. The daily exposure among those burning traditional solid fuels could be lower by ∼41% if the kitchen was equipped with an outdoor chimney, but was still 8–14% higher than those household using cleaning energies, like electricity and gas. With a ventilator in the kitchen, the exposure among the population using clean energies could be further reduced by 10–24%. - Highlights: • High inhalation exposure of fine PM 2.5 and PM 1.0 among rural residents. • Smoking prevails on cooking in increasing exposure to finer particles. • PM exposure could be reduced by �

Metallurgical source-contribution analysis of PM10 annual average concentration: A dispersion modeling approach in moravian-silesian region

Directory of Open Access Journals (Sweden)

P. Jančík

2013-10-01

Full Text Available The goal of the article is to present analysis of metallurgical industry contribution to annual average PM10 concentrations in Moravian-Silesian based on means of the air pollution modelling in accord with the Czech reference methodology SYMOS´97.

Characterization of short- and medium-chain chlorinated paraffins in outdoor/indoor PM10/PM2.5/PM1.0 in Beijing, China.

Science.gov (United States)

Huang, Huiting; Gao, Lirong; Xia, Dan; Qiao, Lin; Wang, Runhua; Su, Guijin; Liu, Wenbin; Liu, Guorui; Zheng, Minghui

2017-06-01

Persistent organic pollutants (POPs) were listed in the Stockholm Convention, because of their adverse health effects, persistence, bioaccumulation and ubiquitous presence in the environment. Short chain chlorinated paraffins (SCCPs), chlorinated derivatives of n-alkanes, have been listed as candidate POPs under Stockholm Convention. Inhalation uptake was an important exposure pathway for non-occupational adult human and the pollution of particle matter has caused great concern. There are some studies focused on POPs such as polychlorinated biphenyls, polychlorinated dibenzo-p-dioxins and dibenzofurans and polybrominated diphenyl ethers in different size particles. However, there were no studies that discussed CP concentrations in particulate matter (PM) with different sizes. In this study, a total of 30 PM samples were collected both outdoors and indoors at a sampling site in Beijing. These samples were used to investigate the concentrations and distributions of SCCPs and medium chain chlorinated paraffins (MCCPs) in PM fractions of different sizes, and to evaluate inhalation exposure risks. The results showed that the average SCCPs and MCCPs in the outdoor PM 10 were 23.9 and 3.6 ng m -3 , while the mean values in indoor were 61.1 and 6.9 ng m -3 , respectively. The levels of SCCPs and MCCPs in indoor and outdoor were relatively high. SCCP and MCCP concentrations in the indoor PM 10 /PM 2.5 /PM 1.0 samples were higher than the corresponding values in the outdoor, because of the using of some products containing CPs in the indoors, like paints and coatings, leather and rubber products. In both outdoor and indoor air, CPs are mainly associated with particles ≤2.5 μm in diameter. The main homolog groups for both SCCPs and MCCPs were C 10-11 Cl 7-8 . It is assumed that SCCPs in the outdoor and indoor PM samples may mainly derive from the production and use of CP-42 and CP-52. Copyright © 2017 Elsevier Ltd. All rights reserved.

Monitoring of 7Be in surface air of varying PM10 concentrations

International Nuclear Information System (INIS)

Chao, J.H.; Liu, C.C.; Cho, I.C.; Niu, H.

2014-01-01

In this study, beryllium-7 ( 7 Be) concentrations of surface air were monitored throughout a span of 23 years (1992–2012) in the Taiwanese cities Yilan, Taipei, Taichung, and Kaohsiung. During this period, particulate matter (PM) concentrations, in terms of PM 10 , were collected monthly from the nearest air-quality pollutant monitoring stations and compared against 7 Be concentrations. Seasonal monsoons influenced 7 Be concentrations in all cities, resulting in high winter and low summer concentrations. In addition, the meteorological conditions caused seasonal PM 10 variations, yielding distinct patterns among the cities. There was no correlation between 7 Be and PM 10 in the case cities. The average annual 7 Be concentrations varied little among the cities, ranging from 2.9 to 3.5 mBq/m 3 , while the PM 10 concentrations varied significantly from 38 μg/m 3 in Yilan to 92 μg/m 3 in Kaohsiung depending on the degree of air pollution and meteorological conditions. The correlation between the 7 Be concentration and gross-beta activities (A β ) in air implied that the 7 Be was mainly attached to crustal PM and its concentration varied little among the cities, regardless of the increase in anthropogenic PM in air-polluted areas. - Highlights: • Both 7 Be and PM 10 concentrations were monitored in four Taiwanese cities from 1992 to 2012. • Seasonal variations of 7 Be and PM 10 were explained based on on meteorological and pollution conditions. • The annual concentrations of 7 Be varied little among the four cities even in high PM environment. • 7 Be is believed to mainly attach to natural PM in the cities that exhibited varying PM 10 concentrations

Spatiotemporal variation of PM1 pollution in China

Science.gov (United States)

Chen, Gongbo; Morawska, Lidia; Zhang, Wenyi; Li, Shanshan; Cao, Wei; Ren, Hongyan; Wang, Boguang; Wang, Hao; Knibbs, Luke D.; Williams, Gail; Guo, Jianping; Guo, Yuming

2018-04-01

Understanding spatiotemporal variation of PM1 (mass concentrations of particles with aerodynamic diameter health, which is potentially more severe for its deeper penetrating capability into human bodies compared with larger particles. This study aimed to quantify the spatial and temporal distribution of PM1 across China as well as its ratio with PM2.5 (additive models were employed to examine the relationships between PM1 and meteorological parameters. We showed that PM1 concentrations were the lowest in summer and the highest in winter. Across China, the PM1/PM2.5 ratios ranged from 0.75-0.88, reaching higher levels in January and lower in August. For spatial distribution, higher PM1/PM2.5 ratios (>0.9) were observed in North-Eastern China, North China Plain, coastal areas of Eastern China and Sichuan Basin while lower ratios (<0.7) were present in remote areas in North-Western and Northern China (e.g., Xinjiang, Tibet and Inner Mongolia). Higher PM1/PM2.5 ratios were observed on heavily polluted days and lower ratios on clean days. The high PM1/PM2.5 ratios observed in China suggest that smaller particles, PM1 fraction, are key drivers of air pollution, and that they effectively account for the majority of PM2.5 concentrations. This emphasised the role of combustion process and secondary particle formation, the sources of PM1, and the significance of controlling them.

Assesment of PM10 pollution episodes in a ceramic cluster (NE Spain): proposal of a new quality index for PM10, As, Cd, Ni and Pb.

Science.gov (United States)

Vicente, A B; Sanfeliu, T; Jordan, M M

2012-10-15

Environmental pollution control is one of the most important goals in pollution risk assessment today. In this sense, modern and precise tools that allow scientists to evaluate, quantify and predict air pollution are of particular interest. Monitoring atmospheric particulate matter is a challenge faced by the European Union. Specific rules on this subject are being developed (Directive 2004/107/EC, Directive 2008/50/EC) in order to reduce the potential adverse effects on human health caused by air pollution. Air pollution has two sources: natural and anthropogenic. Contributions from natural sources can be assessed but cannot be controlled, while emissions from anthropogenic sources can be controlled; monitoring to reduce this latter type of pollution should therefore be carried out. In this paper, we describe an air quality evaluation in terms of levels of atmospheric particles (PM10), as outlined by European Union legislation, carried out in an industrialised Spanish coastal area over a five-year period with the purpose of comparing these values with those of other areas in the Mediterranean Basin with different weather conditions from North of Europe. The study area is in the province of Castellón. This province is a strategic area in the frame work of European Union (EU) pollution control. Approximately 80% of European ceramic tiles and ceramic frit manufacturers are concentrated in two areas, forming the so-called "ceramics clusters"; ones in Modena (Italy) and the other in Castellón. In this kind of areas, there are a lot of air pollutants from this industry then it is difficult to fulfill de European limits of PM10 so it is necessary to control the air quality in them. The seasonal differences in the number of days in which pollutant level limits were exceeded were evaluated and the sources of contamination were identified. Air quality indexes for each pollutant have been established to determine easily and clearly the quality of air breathed. Furthermore

Weekly cycle of magnetic characteristics of PM2.5 and PM2.5-10 in Beijing, China

Science.gov (United States)

SHI, M.; Wu, H.; Zhang, S.; Li, H.; Yang, T.

2013-12-01

In urban areas,fine particle matter with aerodynamic diameter between 2.5 um and 10 um (PM2.5-10), and 2.5 um (PM2.5), as an important source of urban particulate matter (PM) pollutants, have significant negative effects on health, atmospheric visibility and climate. PM has increasingly become a significant index of indicating the atmospheric pollution of city. In recent years, Beijing, China has been listed as one of the most serious air pollution city in the world. In order to investigate the sources of air pollutants, a total of 283 pairs of PM2.5 and PM2.5-10 samples were collected daily from July, 2010 to June, 2011 in Beijing. Mineral magnetic properties and Scanning electron microscope (SEM) observations and energy dispersive X-ray spectroscopy (EDS) analyses of PM2.5 and PM2.5-10 were measured to verify the magnetic materials. Magnetic measures for PM indicated that the major magnetic phase was coarse-grained magnetite-like material. The χlf, χarm, SIRM and χarm/SIRM series of the PM2.5 and PM2.5-10 show seasonal dependences: high values in winter and low values in summer. In additional the parameters analyzed by Time-series methods show a strong cycle about 7 days above 95% confidence level. Weekly cycle of magnetic characteristics of PM2.5 and PM2.5-10 show different pattern: the concentration of magnetic particles in PM2.5-10 show high values in mid-week, and particle sizes is steady, while the concentration of magnetic particles in PM2.5 show reverse a weekly cycle pattern, and particle sizes is smaller in the mid-week.Microscopy analyses reveal basically three morphologies of magnetic grains: aggregate, spherules and angular particles. The ultrafine carbonaceous particles which tend to form complex clusters and chain-like structures, most likely come from coal burning and motor vehicle exhaust. Spherical particles in PM2.5 are dominantly composed of Fe, O and C, grain-diameters of particles range from 0.3 to 2 um. Angular particles of Fe

Effect of the Apulia air quality plan on PM10 and benzo(apyrene exceedances

Directory of Open Access Journals (Sweden)

L. Trizio

2016-03-01

Full Text Available During the last years, several exceedances of PM10 and benzo(apyrene limit values exceedances were recorded in Taranto, a city in southern Italy included in so-called areas at high risk of environmental crisis because of the presence of a heavy industrial district including the largest steel factory in Europe. A study of these critical pollution events showed a close correlation with the wind coming from the industrial site to the adjacent urban area. During 2011, at monitoring sites closes to the industrial area, at least the 65% of PM10 exceedances were related to wind day conditions (characterized by at least 3 consecutive hours of wind coming from 270-360±2deg with an associated speed higher than 7 m/s. For this reason, in 2012 an integrated environmental permit and a regional air quality plan were enacted to reduce pollutant emissions from industrial plants. A study of PM10 levels registered during windy days was performed during critical episodes of pollution highlighting that the difference between windy days and no windy days’ concentrations reduces from 2012 to 2014 in industrial site. False negative events (verified ex-post by observed meteorological data not identified by the forecast model - did not show a significant influence on PM concentration: PM10 values were comparable and sometimes lower than windy days levels. It is reasonable that the new scenario with a relevant reduction emissions form Ilva plant reduced the pollutants contribution from industrial area, contributing to PM10 levels decrease, also in false negative events.

Composition and sources of particles in Mannerheimintie during exceedance days of PM{sub 10} limit value in 2009; Hiukkasten koostumus ja laehteet Mannerheimintiellae PM{sub 10}-raja-arvon ylityspaeivinae 2009

Energy Technology Data Exchange (ETDEWEB)

Kupiainen, K.; Stojiljkovic, A.; Ritola, R. (Nordic Envicon Oy, Helsinki (Finland))

2011-06-15

The purpose of the work was to determine sources of thoracic particles (PM{sub 10}) in the center of Helsinki, in Mannerheimintie, in 2009 during the days when the daily average concentration of PM{sub 10} exceeded 50 mug/m3. Work was commissioned by the Helsinki City Public Works department, the Helsinki Environment Centre and the Helsinki Region Environmental Services Authority HSY (formerly YTV). By the end of the year there were altogether 30 exceedance days. The allowed number of exceedance days per year is 35, so the limit value was not exceeded in 2009. HSY is responsible for monitoring the air quality in the Helsinki metropolitan area. The PM{sub 10} monitoring data in combination with electron microscopy based single particle compositional analysis and receptor modeling was used to evaluate dust source contributions on the exceedance days at HSY's air quality monitoring station in Mannerheimintie. Dust sources related to traction control (winter maintenance and pavement wear by studded tyres) contributed most to the PM{sub 10} concentrations in Mannerheimintie. On 12 exceeding days this group accounted for more than 50 % of PM{sub 10} particles, on 3 days the group alone was sufficient to cause the exceedance. On 3 of the exceedance days long-range transboundary air pollution or traffic exhaust emissions were on the same level with the traction control sources. On 11 days the most significant impact came from construction sites. (orig.)

A Comparison on Function of Kriging and Inverse Distance Weighting Models in PM10 Zoning in Urban Area

Directory of Open Access Journals (Sweden)

Mohammad Hassan Ehrampoush

2017-12-01

Conclusion: According to higher concentration of PM10 compared to WHO standard values particularly in spring, necessary actions and solutions should be taken for the pollution reduction. This study indicated that Kriging model has a better efficiency for spatial analysis of suspended particles, compared to IDW method.

Health benefits of PM10 reduction in Iran

Science.gov (United States)

Marzouni, Mohammad Bagherian; Moradi, Mahsa; Zarasvandi, Alireza; Akbaripoor, Shayan; Hassanvand, Mohammad Sadegh; Neisi, Abdolkazem; Goudarzi, Gholamreza; Mohammadi, Mohammad Javad; Sheikhi, Reza; Kermani, Majid; Shirmardi, Mohammad; Naimabadi, Abolfazl; Gholami, Moeen; Mozhdehi, Saeed Pourkarim; Esmaeili, Mehdi; Barari, Kian

2017-08-01

Air pollution contains a complex mixture of poisonous compounds including particulate matter (PM) which has wide spectrum of adverse health effects. The main purpose of this study was to estimate the potential health impacts or benefits due to any changes in annual PM10 level in four major megacities of Iran. The required data of PM10 for AirQ software was collected from air quality monitoring stations in four megacities of Iran. The preprocessing was carried out using macro coding in excel environment. The relationship between different presumptive scenarios and health impacts was determined. We also assessed the health benefits of reducing PM10 to WHO Air Quality Guidelines (WHO-AQGs) and National Ambient Air Quality Standards (NAAQSs) levels with regard to the rate of mortality and morbidity in studied cities. We found that the 10 μg/m3 increase in annual PM10 concentration is responsible for seven (95% CI 6-8) cases increase in total number of deaths per 2 × 105 person. We also found that 10.7, 7.2, 5.7, and 5.3% of total death is attributable to short-term exposure to air pollution for Ahvaz, Isfahan, Shiraz, and Tehran, respectively. We found that by attaining the WHO's proposed value for PM10, the potential health benefits of 89, 84, 79, and 78% were obtained in Ahvaz, Isfahan, Shiraz, and Tehran, respectively. The results also indicated that 27, 10, 3, and 1% of health impacts were attributed to dust storm days for Ahvaz, Isfahan, Shiraz, and Tehran, respectively.

Random forest meteorological normalisation models for Swiss PM10 trend analysis

Science.gov (United States)

Grange, Stuart K.; Carslaw, David C.; Lewis, Alastair C.; Boleti, Eirini; Hueglin, Christoph

2018-05-01

Meteorological normalisation is a technique which accounts for changes in meteorology over time in an air quality time series. Controlling for such changes helps support robust trend analysis because there is more certainty that the observed trends are due to changes in emissions or chemistry, not changes in meteorology. Predictive random forest models (RF; a decision tree machine learning technique) were grown for 31 air quality monitoring sites in Switzerland using surface meteorological, synoptic scale, boundary layer height, and time variables to explain daily PM10 concentrations. The RF models were used to calculate meteorologically normalised trends which were formally tested and evaluated using the Theil-Sen estimator. Between 1997 and 2016, significantly decreasing normalised PM10 trends ranged between -0.09 and -1.16 µg m-3 yr-1 with urban traffic sites experiencing the greatest mean decrease in PM10 concentrations at -0.77 µg m-3 yr-1. Similar magnitudes have been reported for normalised PM10 trends for earlier time periods in Switzerland which indicates PM10 concentrations are continuing to decrease at similar rates as in the past. The ability for RF models to be interpreted was leveraged using partial dependence plots to explain the observed trends and relevant physical and chemical processes influencing PM10 concentrations. Notably, two regimes were suggested by the models which cause elevated PM10 concentrations in Switzerland: one related to poor dispersion conditions and a second resulting from high rates of secondary PM generation in deep, photochemically active boundary layers. The RF meteorological normalisation process was found to be robust, user friendly and simple to implement, and readily interpretable which suggests the technique could be useful in many air quality exploratory data analysis situations.

PM10 source apportionment study in Pleasant Valley, Nevada

International Nuclear Information System (INIS)

Egami, R.T.; Chow, J.C.; Watson, J.G.; DeLong, T.

1990-01-01

A source apportionment study was conducted between March 18 and April 4, 1988, at Pleasant Valley, Nevada, to evaluate air pollutant concentrations to which community residents were exposed and the source contributions to those pollutants. Daily PM 10 samples were taken for chemical speciation of 40 trace elements, ions, and organic and elemental carbon. This paper reports that the objectives of this case study are: to determine the emissions source composition of the potential upwind source, a geothermal plant; to measure the ambient particulate concentration and its chemical characteristics in Pleasant Valley; and to estimate the contributions of different emissions sources to PM 10 . The study found that: particulate emissions from the geothermal cooling-tower plume consisted primarily of sulfate, ammonia, chloride, and trace elements; no significant quantities of toxic inorganic species were found in the ambient air; ambient PM 10 concentrations in Pleasant Valley were within Federal standards; and source contribution to PM 10 were approximately 60% geological material; 20% motor vehicle exhaust; and 10% cooling-tower plume

Household air pollution and personal inhalation exposure to particles (TSP/PM2.5/PM1.0/PM0.25) in rural Shanxi, North China.

Science.gov (United States)

Huang, Ye; Du, Wei; Chen, Yuanchen; Shen, Guofeng; Su, Shu; Lin, Nan; Shen, Huizhong; Zhu, Dan; Yuan, Chenyi; Duan, Yonghong; Liu, Junfeng; Li, Bengang; Tao, Shu

2017-12-01

Personal exposure to size-segregated particles among rural residents in Shanxi, China in summer, 2011 were investigated using portable carried samplers (N = 84). Household air pollution was simultaneously studied using stationary samplers in nine homes. Information on household fuel types, cooking activity, smoking behavior, kitchen ventilation conditions etc., were also collected and discussed. The study found that even in the summer period, the daily average concentrations of PM 2.5 and PM 1.0 in the kitchen were as high as 376 ± 573 and 288 ± 397 μg/m 3 (N = 6), that were nearly 3 times of 114 ± 81 and 97 ± 77 μg/m 3 in the bedroom (N = 8), and significantly higher than those of 64 ± 28 and 47 ± 21 μg/m 3 in the outdoor air (N = 6). The personal daily exposure to PM 2.5 and PM 1.0 were 98 ± 52 and 77 ± 47 μg/m 3 , respectively, that were lower than the concentrations in the kitchen but higher than the outdoor levels. The mass fractions of PM 2.5 in TSP were 90%, 72%, 65% and 68% on average in the kitchen, bedroom, outdoor air and personal inhalation exposure, respectively, and moreover, a majority of particles in PM 2.5 had diameters less than 1.0 μm. Calculated time-weighted average exposure based on indoor and outdoor air concentrations and time spent indoor and outdoor were positively correlated but, was ∼33% lower than the directly measured exposure. The daily exposure among those burning traditional solid fuels could be lower by ∼41% if the kitchen was equipped with an outdoor chimney, but was still 8-14% higher than those household using cleaning energies, like electricity and gas. With a ventilator in the kitchen, the exposure among the population using clean energies could be further reduced by 10-24%. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of annual air pollution levels with PM1, PM2.5, PM10 and associated heavy metals in Algiers, Algeria.

Science.gov (United States)

Talbi, Abdelhamid; Kerchich, Yacine; Kerbachi, Rabah; Boughedaoui, Ménouèr

2018-01-01

Concentrations of particulate matter less than 1  μm, 2.5  μm, 10 μm and their contents of heavy metals were investigated in two different stations, urban and roadside at Algiers (Algeria). Sampling was conducted during two years by a high volume samplers (HVS) equipped with a cascade impactor at four levels stage, for one year sampling. The characterization of the heavy metals associated to the particulate matter (PM) was carried out by X-Ray Fluorescence analysis (XRF). The annual average concentration of PM 1 , PM 2.5 and PM 10 in both stations were 18.24, 32.23 and 60.01 μg m -3 respectively. The PM 1 , PM 2.5 and PM 10 concentrations in roadside varied from 13.46 to 25.59 μg m -3 , 20.82-49.85 μg m -3 and 45.90-77.23 μg m -3 respectively. However in the urban station, the PM 1 , PM 2.5 and PM 10 concentrations varied from 10.45 to 26.24 μg m -3 , 18.53-47.58 μg m -3 and 43.8-91.62 μg m -3 . The heavy metals associated to the PM were confirmed by Scanning Electron Microscopy-Energy Dispersive X-Ray analyses (SEM-EDX). The different spots of PM 2.5 analysis by SEM-EDX shows the presence of nineteen elements with anthropogenic and natural origins, within the heavy metal detected, the lead was found with maximum of 5% (weight percent). In order to determine the source contributions of PM levels at the two sampling sites sampling, principal compound analysis (PCA) was applied to the collected data. Statistical analysis confirmed anthropogenic source with traffic being a significant source and high contribution of natural emissions. At both sites, the PM 2.5 /PM 10 ratio is lower than that usually recorded in developed countries. The study of the back-trajectories of the air masses starting from Sahara shows that desert dust influences the concentration and the composition of the PM measured in Algiers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Environmental pollution: quantitative analysis of particulate matter (PM{sub 10}) by SR-TXRF

Energy Technology Data Exchange (ETDEWEB)

Moreira, Silvana; Melo Junior, Ariston da Silva [Universidade Estadual de Campinas (UNICAMP), Campinas, SP (Brazil). Faculdade de Engenharia Civil, Arquitetura e Urbanismo]. E-mails: silvana@fec.unicamp.br; juniorariston@gmail.com; Zucchi, Orgheda Luiza Araujo Domingues [Universidade de Sao Paulo (USP), Ribeirao Preto, SP (Brazil). Faculdade de Ciencias Farmaceuticas]. E-mail: olzucchi@fcfrp.usp.br; Vives, Ana Elisa Sirito de [Universidade Metodista de Piracicaba (UNIMEP), Santa Barbara D' Oeste, SP (Brazil). Faculdade de Engenharia Civil, Arquitetura e Urbanismo]. E-mail: aesvives@unimep.br

2007-07-01

The atmospheric pollution is a concern in the great urban centers, due its association with man pathologies. The Campinas region is one of the most urbanized of the Sao Paulo State and an important industrial center. Thus, due to its location and importance were installed three samplers for particulate material (PM{sub 10}). One sampler was located in downtown of Campinas city, in an avenue with high vehicular flow. Another sampler was installed in the UNICAMP campus and the third one in Paulinia city, near to REPLAN. For downtown of Campinas city PM{sub 10} concentrations higher than regular air quality established by CETESB (150 {mu}g.m{sup -3}) was observed. The PM{sub 10} values for Paulinia and downtown of Campinas were higher than Barao Geraldo location. Employing SR-TXRF was possible identify and quantify 19 elements in the particulate material samples. All the measurements were performed at Synchrotron Light Source Laboratory, Campinas, SP. After statistics analysis by principal components and cluster analysis was possible to assemble the elements according emission sources. The dusty soil for coarse fraction contributed with 62%, 51% and 46% for Barao Geraldo, Paulinia and downtown of Campinas, respectively. The vehicular emission was responsible for 16% at downtown Campinas city as expected due to high vehicular flow at sampling place. The vehicular and industrial emissions contributed with 20% and 25%, respectively at Paulinia sampling site. The industrial emissions observed for Barao Geraldo and downtown of Campinas city were 27% and 33%, respectively. (author)

[Characterizing Beijing's Airborne Bacterial Communities in PM2.5 and PM1 Samples During Haze Pollution Episodes Using 16S rRNA Gene Analysis Method].

Science.gov (United States)

Wang, Bu-ying; Lang, Ji-dong; Zhang, Li-na; Fang, Jian-huo; Cao, Chen; Hao, Ji-ming; Zhu, Ting; Tian, Geng; Jiang, Jing-kun

2015-08-01

During 8th-14th Jan., 2013, severe particulate matter (PM) pollution episodes happened in Beijing. These air pollution events lead to high risks for public health. In addition to various PM chemical compositions, biological components in the air may also impose threaten. Little is known about airborne microbial community in such severe air pollution conditions. PM2.5 and PM10 samples were collected during that 7-day pollution period. The 16S rRNA gene V3 amplification and the MiSeq sequencing were performed for analyzing these samples. It is found that there is no significant difference at phylum level for PM2.5 bacterial communities during that 7-day pollution period both at phylum and at genus level. At genus level, Arthrobacter and Frankia are the major airborne microbes presented in Beijing winter.samples. At genus level, there are 39 common genera (combined by first 50 genera bacterial of the two analysis) between the 16S rRNA gene analysis and those are found by Metagenomic analysis on the same PM samples. Frankia and Paracoccus are relatively more abundant in 16S rRNA gene data, while Kocuria and Geodermatophilus are relatively more abundant in Meta-data. PM10 bacterial communities are similar to those of PM2.5 with some noticeable differences, i.e., at phylum level, more Firmicutes and less Actinobacteria present in PM10 samples than in PM2.5 samples, while at genus level, more Clostridium presents in PM10 samples. The findings in Beijing were compared with three 16S rRNA gene studies in other countries. Although the sampling locations and times are different from each other, compositions of bacterial community are similar for those sampled at the ground atmosphere. Airborne microbial communities near the ground surface are different from those sampled in the upper troposphere.

Using gravimetric measurement for determination of the mass fraction PM10

Directory of Open Access Journals (Sweden)

Nicolae Chirilă

2011-12-01

Full Text Available In this paper, we tried to determinate the air pollution level with mass fraction PM10 from Targu Mures area. For this purpose, determinations were made in University Petru Maior’s laboratory, using ADR 1200 S device and in Targu Mures Environmental Department’s laboratory. The results that we obtained show a low level of air pollution with mass fraction PM10 in Targu Mures area.

Efecto del tiempo de exposición a PM10 en las urgencias por bronquitis aguda Effect of exposure time to PM10 on emergency admissions for acute bronchitis

Directory of Open Access Journals (Sweden)

Franz Muñoz

2009-03-01

Full Text Available Este trabajo analiza el efecto de las horas de exposición a PM10 en las urgencias diarias por bronquitis aguda, controlando por temperatura y humedad. El estudio fue realizado en seis sectores de la ciudad de Santiago, Chile, durante el período de invierno de los años 2002 al 2004, para lactantes ( 65 años. Analizamos el retraso de la respuesta mediante una función polinomial distributiva (pdl, incluida en un modelo lineal generalizado (GLM-pdl, y la estructura del efecto de la exposición, mediante modelos aditivos generalizados (GAM, utilizando regresión spline como técnica de estimación. Los resultados mostraron que al cuarto día de retardo, el efecto de la exposición fue mayor, especialmente en lactantes, y varió en la medida que incrementó la concentración atmosférica de PM10. El efecto de las horas de exposición a PM10 mostró una variación significativa, según el sector geográfico. Al estimar linealmente este efecto en el sector Oeste, notamos que el incremento de consultas diarias en lactantes fue de 3% por cada hora de exposición sobre os 150µg/m³.To study the health effect of air pollution, measured as particulate matter greater than 10mm in diameter (PM10, we analyzed the effect of daily hours of exposure on the number of urgency admissions for acute bronchitis, adjusting for temperature and humidity on the same day. The study was conducted in six regions of Santiago, Chile, during the winter of years 2002 to 2004, for infants and elders. The delay between pollution time series and disease was modeled using a polynomial distributed lag (PDL function included in a generalized linear model. The linearity assumption was evaluated using a smooth-spline model approach. The highest effect for exposure to PM10 was detected with 4 days of delay. For both groups, the effect of temperature was linear, but that of humidity was not. Air pollution effect varied according to level of exposure and geographic region, increasing

Assesment of Pb concentration in PM{sub 2,5} and PM{sub 10} at Serpong area; Asesmen konsentrasi Pb pada PM{sub 2,5} dan PM{sub 10} di kawasan Serpong

Energy Technology Data Exchange (ETDEWEB)

Rita,; Hamonangan, Esrom; Halimah Syafrul, E-mail: ritaiim@yahoo.com [Pusat Sarana Pengendalian Dampak Lingkungan, Kemenneg Lingkungan Hidup, Kawasan Puspiptek Serpong, Tangerang 15314 (Indonesia); Santoso, Muhayatun; Lestian, Diah Dwiana [Pusat Tenaga Nuklir Bahan dan Radiometri (PTNBR) - BATAN, JI. Tamansari NO.71 Bandung 40132 (Indonesia)

2010-11-15

Ambient air pollution, especially Pb, in Serpong area has been detected since 1996. Pollution caused by heavy metals Pb deserve serious attention because of the impact is very influential on health such as reduced levels of intelligence, learning disability, symptoms of anemia, barriers to growth, poor cognitive development, weakened immune system, symptoms of autism, and even premature death. This study was conducted to determine Pb concentration of PM{sub 2,5} and PM{sub 10} in four residential locations in Serpong area as part of a series of comprehensive studies for the characterization and identification of sources pollution. Particulates were sampled using Gent Stacked Filter Unit Sampler at 3 housing locations and 1 office location in the period of August 25 to November 3, 2008, Samples were analyzed using nuclear analytical techniques, Proton Induced X-ray Emission. The results showed that the activity concentration of Pb in PM{sub 2,5} for the location of Setu, Pusarpedal, Batan Indah, and BSD were in the range of 33-388, 12-254, 6-282, and 5-332 ng/m{sup 3}, while for PM{sub 10} were 69-732, 59-647, 31-810, and 28718 ng/m{sup 3}, respectively, In general, Pb concentrations in Serpong area were higher than those in some other cities in Asia region. These results are expected to be used as scientific based reference in formulating, taking action, and appropriate policies to overcome environmental problems. (author)

Measurement of Ambient Air Particle (TSP, PM10, PM2,5) Around Candidate Location of PLTN Semenanjung Lemahabang

International Nuclear Information System (INIS)

AgusGindo S; Budi Hari H

2008-01-01

Measurement analysis of ambient air particle (TSP, PM 10 , PM 2,5 ) around location candidate of PLTN (Power Station of Nuclear Energy) Semenanjung Lemahabang has been carried out. The measurement was conducted in May 2007 with a purpose to providing information about concentration of ambient air particle (TSP, PM 10 , PM 2,5 ) and diameter distribution of its air particle. The measurement was conducted in three locations i.e. 1). Balong village 2). Bayuran 3). Bondo. Concentration of TSP, PM 10 , and PM 2,5 per 24 hours in all measured locations in area candidate of PLTN exceed quality standard of national ambient air is specified by government. All measurement locations for the TSP, PM 10 , and PM 2,5 was include category of ISPU (Standard Index of Air Pollution) moderate. (author)

Air pollution exposure in Oslo, Drammen, Bergen and Trondheim. Calculations of NO{sub 2}, PM{sub 10} and PM{sub 2,5} for the winter 1995 to 1996; Eksponering til luftforurensing i Oslo, Drammen, Bergen og Trondheim. Beregninger av NO{sub 2}, PM{sub 10} og PM{sub 2,5} for vinteren 1995-1996

Energy Technology Data Exchange (ETDEWEB)

Sloerdal, Leif Haavard

1998-07-01

The Norwegian Institute for Air Research (NILU) commissioned by the Norwegian Pollution Control Authority (Statens forurensningstilsyn), has calculated human exposure values to NO{sub 2}, PM{sub 1}0 and PM{sub 2},5 in the cities of Oslo, Drammen, Bergen and Trondheim. In Oslo, Drammen and Bergen the calculations are made for the winter 1995 to 1996. For Trondheim the necessary meteorological data were missing and the calculations are therefore made for the winter of 1994 to 1995. In the project only simplified exposure calculations are carried out where estimated ground concentrations and population distribution information at the km{sub 2} level are connected. The calculations are then made as if everyone have been outside at the home address during the entire estimation period, termed ''potential exposure''. The population exposure load is estimated for excesses of various air quality criteria and the results are presented. In addition values for the worst hour and/or the worst day of exposure for each of the four cities are presented. The term worst is defined as the hour or the day in the simulation period where the most number of people are exposed to concentrations exceeding the threshold values for air quality recommended by the Norwegian Pollution Control Authority. For NO{sub 2} these threshold figures are 100 microgram/m{sup 3} for hour values and 75 microgram/m{sup 3} for day values. For PM{sub 1}0 and PM{sub 2},5 criteria for hour values do not exist while day values are now stipulated as 35 microgram/m{sup 3} for PM{sub 1}0 and 20 microgram/m{sup 3} for PM{sub 2},5. The calculated maximum concentrations may not coincide with these values. The report gives results for exposure estimates for NO{sub 2}, PM{sub 1}0 and PM{sub 2},5 in the cities and evaluates the significance of regional background levels, traffic and heating emissions in contributions to the total population exposure load. The exposure to NO{sub 2} is largest in Bergen. The PM{sub 1}0 and

Vehicular pollution modeling using the operational street pollution model (OSPM) for Chembur, Mumbai (India).

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Kumar, Awkash; Ketzel, Matthias; Patil, Rashmi S; Dikshit, Anil Kumar; Hertel, Ole

2016-06-01

Megacities in India such as Mumbai and Delhi are among the most polluted places in the world. In the present study, the widely used operational street pollution model (OSPM) is applied for assessing pollutant loads in the street canyons of Chembur, a suburban area just outside Mumbai city. Chembur is both industrialized and highly congested with vehicles. There are six major street canyons in this area, for which modeling has been carried out for NOx and particulate matter (PM). The vehicle emission factors for Indian cities have been developed by Automotive Research Association of India (ARAI) for PM, not specifically for PM10 or PM2.5. The model has been applied for 4 days of winter season and for the whole year to see the difference of effect of meteorology. The urban background concentrations have been obtained from an air quality monitoring station. Results have been compared with measured concentrations from the routine monitoring performed in Mumbai. NOx emissions originate mainly from vehicles which are ground-level sources and are emitting close to where people live. Therefore, those emissions are highly relevant. The modeled NOx concentration compared satisfactorily with observed data. However, this was not the case for PM, most likely because the emission inventory did not contain emission terms due to resuspended particulate matter.

Temporal Variation of Ambient PM10 Concentration within an Urban-Industrial Environment

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Wong, Yoon-Keaw; Noor, Norazian Mohamed; Izzah Mohamad Hashim, Nur

2018-03-01

PM10 concentration in the ambient air has been reported to be the main pollutant affecting human health, particularly in the urban areas. This research is conducted to study the variation of PM10 concentration at the three urban-industrial areas in Malaysia, namely Shah Alam, Kuala Terengganu and Melaka. In addition, the association and correlation between PM10 concentration and other air pollutants will be distinguished. Five years interval dataset (2008-2012) consisting of PM10, SOX, NOX and O3 concentrations and other weather parameters such as wind speed, humidity and temperature were obtained from Department of Environment, Malaysia. Shah Alam shows the highest average of PM10 concentration with the value of 62.76 μg/m3 in June, whereas for Kuala Terengganu was 59.29 μg/m3 in February and 46.61 μg/m3 in August for Melaka. Two peaks were observed from the time series plot using the averaged monthly PM10 concentration. First peak occurs when PM10 concentration rises from January to February and the second peak is reached in June and remain high for the next two consecutive months for Shah Alam and Kuala Terengganu. Meanwhile the second peak for Melaka is only achieved in August as a result of the transboundary of smoke from forest fires in the Sumatra region during dry season from May to September. Both of the pollutants can be sourced from rapid industrial activities at Shah Alam. PM10 concentration is strongly correlated with carbon monoxide concentration in Kuala Terengganu and Melaka with value of r2 = 0.1725 and 0.2744 respectively. High carbon monoxide and PM10 concentration are associated with burning of fossil fuel from increased number of vehicles at these areas.

Assessment of the Possible Association of Air Pollutants PM10, O3, NO2 With an Increase in Cardiovascular, Respiratory, and Diabetes Mortality in Panama City: A 2003 to 2013 Data Analysis.

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Zúñiga, Julio; Tarajia, Musharaf; Herrera, Víctor; Urriola, Wilfredo; Gómez, Beatriz; Motta, Jorge

2016-01-01

In recent years, Panama has experienced a marked economic growth, and this, in turn, has been associated with rapid urban development and degradation of air quality. This study is the first evaluation done in Panama on the association between air pollution and mortality. Our objective was to assess the possible association between monthly levels of PM10, O3, and NO2, and cardiovascular, respiratory, and diabetes mortality, as well as the seasonal variation of mortality in Panama City, Panama.The study was conducted in Panama City, using air pollution data from January 2003 to December 2013. We utilized a Poisson regression model based on generalized linear models, to evaluate the association between PM10, NO2, and O3 exposure and mortality from diabetes, cardiovascular, and respiratory diseases. The sample size for PM10, NO2, and O2 was 132, 132, and 108 monthly averages, respectively.We found that levels of PM10, O3, and NO2 were associated with increases in cardiovascular, respiratory, and diabetes mortality. For PM10 levels ≥ 40 μg/m3, we found an increase in cardiovascular mortality of 9.7% (CI 5.8-13.6%), and an increase of 12.6% (CI 0.2-24.2%) in respiratory mortality. For O3 levels ≥ 20 μg/m3 we found an increase of 32.4% (IC 14.6-52.9) in respiratory mortality, after a 2-month lag period following exposure in the 65 to respiratory mortality of 11.2% (IC 1.9-21.3), after a 2-month lag period following exposure among those aged between 65 and pollution in Panama City and an increase in cardiovascular, respiratory, and diabetes mortality. This study confirms the urgent need to improve the measurement frequency of air pollutants in Panama.

Size distribution, directional source contributions and pollution status of PM from Chengdu, China during a long-term sampling campaign.

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Shi, Guo-Liang; Tian, Ying-Ze; Ma, Tong; Song, Dan-Lin; Zhou, Lai-Dong; Han, Bo; Feng, Yin-Chang; Russell, Armistead G

2017-06-01

Long-term and synchronous monitoring of PM 10 and PM 2.5 was conducted in Chengdu in China from 2007 to 2013. The levels, variations, compositions and size distributions were investigated. The sources were quantified by two-way and three-way receptor models (PMF2, ME2-2way and ME2-3way). Consistent results were found: the primary source categories contributed 63.4% (PMF2), 64.8% (ME2-2way) and 66.8% (ME2-3way) to PM 10 , and contributed 60.9% (PMF2), 65.5% (ME2-2way) and 61.0% (ME2-3way) to PM 2.5 . Secondary sources contributed 31.8% (PMF2), 32.9% (ME2-2way) and 31.7% (ME2-3way) to PM 10 , and 35.0% (PMF2), 33.8% (ME2-2way) and 36.0% (ME2-3way) to PM 2.5 . The size distribution of source categories was estimated better by the ME2-3way method. The three-way model can simultaneously consider chemical species, temporal variability and PM sizes, while a two-way model independently computes datasets of different sizes. A method called source directional apportionment (SDA) was employed to quantify the contributions from various directions for each source category. Crustal dust from east-north-east (ENE) contributed the highest to both PM 10 (12.7%) and PM 2.5 (9.7%) in Chengdu, followed by the crustal dust from south-east (SE) for PM 10 (9.8%) and secondary nitrate & secondary organic carbon from ENE for PM 2.5 (9.6%). Source contributions from different directions are associated with meteorological conditions, source locations and emission patterns during the sampling period. These findings and methods provide useful tools to better understand PM pollution status and to develop effective pollution control strategies. Copyright © 2016. Published by Elsevier B.V.

Assessing Model Characterization of Single Source ...

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Aircraft measurements made downwind from specific coal fired power plants during the 2013 Southeast Nexus field campaign provide a unique opportunity to evaluate single source photochemical model predictions of both O3 and secondary PM2.5 species. The model did well at predicting downwind plume placement. The model shows similar patterns of an increasing fraction of PM2.5 sulfate ion to the sum of SO2 and PM2.5 sulfate ion by distance from the source compared with ambient based estimates. The model was less consistent in capturing downwind ambient based trends in conversion of NOX to NOY from these sources. Source sensitivity approaches capture near-source O3 titration by fresh NO emissions, in particular subgrid plume treatment. However, capturing this near-source chemical feature did not translate into better downwind peak estimates of single source O3 impacts. The model estimated O3 production from these sources but often was lower than ambient based source production. The downwind transect ambient measurements, in particular secondary PM2.5 and O3, have some level of contribution from other sources which makes direct comparison with model source contribution challenging. Model source attribution results suggest contribution to secondary pollutants from multiple sources even where primary pollutants indicate the presence of a single source. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, deci

Evolution of air pollution source contributions over one decade, derived by PM10 and PM2.5 source apportionment in two metropolitan urban areas in Greece

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Diapouli, E.; Manousakas, M.; Vratolis, S.; Vasilatou, V.; Maggos, Th; Saraga, D.; Grigoratos, Th; Argyropoulos, G.; Voutsa, D.; Samara, C.; Eleftheriadis, K.

2017-09-01

Metropolitan Urban areas in Greece have been known to suffer from poor air quality, due to variety of emission sources, topography and climatic conditions favouring the accumulation of pollution. While a number of control measures have been implemented since the 1990s, resulting in reductions of atmospheric pollution and changes in emission source contributions, the financial crisis which started in 2009 has significantly altered this picture. The present study is the first effort to assess the contribution of emission sources to PM10 and PM2.5 concentration levels and their long-term variability (over 5-10 years), in the two largest metropolitan urban areas in Greece (Athens and Thessaloniki). Intensive measurement campaigns were conducted during 2011-2012 at suburban, urban background and urban traffic sites in these two cities. In addition, available datasets from previous measurements in Athens and Thessaloniki were used in order to assess the long-term variability of concentrations and sources. Chemical composition analysis of the 2011-2012 samples showed that carbonaceous matter was the most abundant component for both PM size fractions. Significant increase of carbonaceous particle concentrations and of OC/EC ratio during the cold period, especially in the residential urban background sites, pointed towards domestic heating and more particularly wood (biomass) burning as a significant source. PMF analysis further supported this finding. Biomass burning was the largest contributing source at the two urban background sites (with mean contributions for the two size fractions in the range of 24-46%). Secondary aerosol formation (sulphate, nitrate & organics) was also a major contributing source for both size fractions at the suburban and urban background sites. At the urban traffic site, vehicular traffic (exhaust and non-exhaust emissions) was the source with the highest contributions, accounting for 44% of PM10 and 37% of PM2.5, respectively. The long

Spatial distribution of particulate matter (PM10 and PM2.5) in Seoul Metropolitan Subway stations.

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Kim, Ki Youn; Kim, Yoon Shin; Roh, Young Man; Lee, Cheol Min; Kim, Chi Nyon

2008-06-15

The aims of this study are to examine the concentrations of PM10 and PM2.5 in areas within the Seoul Metropolitan Subway network and to provide fundamental data in order to protect respiratory health of subway workers and passengers from air pollutants. A total of 22 subway stations located on lines 1-4 were selected based on subway official's guidance. At these stations both subway worker areas (station offices, rest areas, ticket offices and driver compartments) and passengers areas (station precincts, subway carriages and platforms) were the sites used for measuring the levels of PM. The mean concentrations of PM10 and PM2.5 were relatively higher on platforms, inside subway carriages and in driver compartments than in the other areas monitored. The levels of PM10 and PM2.5 for station precincts and platforms exceeded the 24-h acceptable threshold limits of 150 microg/m3 for PM10 and 35 microg/m3 for PM2.5, which are regulated by the U.S. Environmental Protection Agency (EPA). However, levels measured in station and ticket offices fell below the respective threshold. The mean PM10 and PM2.5 concentrations on platforms located underground were significantly higher than those at ground level (p<0.05).

Levels of PM2.5/PM10 and associated metal(loid)s in rural households of Henan Province, China.

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Wu, Fuyong; Wang, Wei; Man, Yu Bon; Chan, Chuen Yu; Liu, Wenxin; Tao, Shu; Wong, Ming Hung

2015-04-15

Although a majority of China's rural residents use solid fuels (biomass and coal) for household cooking and heating, clean energy such as electricity and liquid petroleum gas is becoming more popular in the rural area. Unfortunately, both solid fuels and clean energy could result in indoor air pollution. Daily respirable particulate matter (PM≤10 μm) and inhalable particulate matter (PM≤2.5 μm) were investigated in kitchens, sitting rooms and outdoor area in rural Henan during autumn (Sep to Oct 2012) and winter (Jan 2013). The results showed that PM (PM2.5 and PM10) and associated metal(loid)s varied among the two seasons and the four types of domestic energy used. Mean concentrations of PM2.5 and PM10 in kitchens during winter were 59.2-140.4% and 30.5-145.1% higher than those during autumn, respectively. Similar with the trends of PM2.5 and PM10, concentrations of As, Pb, Zn, Cd, Cu, Ni and Mn in household PM2.5 and PM10 were apparently higher in winter than those in autumn. The highest mean concentrations of PM2.5 and PM10 (368.5 and 588.7 μg m(-3)) were recorded in sitting rooms in Baofeng during winter, which were 5.7 and 3.9 times of corresponding health based guidelines for PM2.5 and PM10, respectively. Using coal can result in severe indoor air pollutants including PM and associated metal(loid)s compared with using crop residues, electricity and gas in rural Henan Province. Rural residents' exposure to PM2.5 and PM10 would be roughly reduced by 13.5-22.2% and 8.9-37.7% via replacing coal or crop residues with electricity. The present study suggested that increased use of electricity as domestic energy would effectively improve indoor air quality in rural China. Copyright © 2015 Elsevier B.V. All rights reserved.

Twelve-Year Trends of PM10 and Visibility in the Hefei Metropolitan Area of China

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Lin Huang

2016-01-01

Full Text Available China has been experiencing severe air pollution and previous studies have mostly focused on megacities and a few hot spot regions. Hefei, the provincial capital city of Anhui province, has a population of near 5 million in its metropolitan area, but its air quality has not been reported in literature. In this study, daily PM10 and visibility data in 2001–2012 were analyzed to investigate the air quality status as well as the twelve-year pollution trends in Hefei. The results reveal that Hefei has been suffering high PM10 pollution and low visibility during the study period. The annual average PM10 concentrations are 2~3 times of the Chinese Ambient Air Quality Standard. PM10 shows fluctuating variation in 2001–2007 and has a slightly decreasing trend after 2008. The annual average visibility range is generally lower than 7 km and shows a worsening trend from 2001 to 2006 followed by an improving trend from 2007 to 2012. Wind speed, precipitation, and relative humidity have negative effects on PM10 concentrations in Hefei, while temperature could positively or negatively affect PM10. The results provide a general understanding of the status and long-term trends of PM10 pollution and visibility in a typical second-tier city in China.

Temporal multiscaling characteristics of particulate matter PM 10 and ground-level ozone O3 concentrations in Caribbean region

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Plocoste, Thomas; Calif, Rudy; Jacoby-Koaly, Sandra

2017-11-01

A good knowledge of the intermittency of atmospheric pollutants is crucial for air pollution management. We consider here particulate matter PM 10 and ground-level ozone O3 time series in Guadeloupe archipelago which experiments a tropical and humid climate in the Caribbean zone. The aim of this paper is to study their scaling statistics in the framework of fully developed turbulence and Kolmogorov's theory. Firstly, we estimate their Fourier power spectra and consider their scaling properties in the physical space. The power spectra computed follows a power law behavior for both considered pollutants. Thereafter we study the scaling behavior of PM 10 and O3 time series. Contrary to numerous studies where the multifractal detrended fluctuation analysis is frequently applied, here, the classical structure function analysis is used to extract the scaling exponent or multifractal spectrum ζ(q) ; this function provides a full characterization of a process at all intensities and all scales. The obtained results show that PM 10 and O3 possess intermittent and multifractal properties. The singularity spectrum MS(α) also confirms both pollutants multifractal features. The originality of this work comes from a statistical modeling performed on ζ(q) and MS(α) by a lognormal model to compute the intermittency parameter μ. By contrast with PM 10 which mainly depends on puffs of Saharan dust (synoptic-scale), O3 is more intermittent due to variability of its local precursors. The results presented in this paper can help to better understand the mechanisms governing the dynamics of PM 10 and O3 in Caribbean islands context.

Potential impact of particulate matter less than 10 micron (PM10) to ambient air quality of Jakarta and Palembang

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Agustine, I.; Yulinawati, H.; Gunawan, D.; Suswantoro, E.

2018-01-01

Particulate is a main urban air pollutant affects the environment and human wellbeing. The purpose of this study is to analyze the impact of particulate matter less than 10 micron (PM10) to ambient air quality of Jakarta and Palembang. The analysis is done with calendarPlot Function of openair model, which is based on the calculation of Pollutant Standards Index (PSI) or better known as Air Quality Index (AQI). The AQI category of “moderate” dominates Jakarta’s calendar from 2015 to 2016, which indicates the impact of PM10 is the visibility reduction. There was one day with category “unhealthy” that indicates the impact of dust exposure everywhere in Jakarta during 2015. Similar to Jakarta, the AQI category “moderate” also dominates Palembang’s calendar during 2015. However, the AQI category “hazardous” happened for few days in September and October 2015 during forest fires, which indicates the more harmful impacts of PM10, such as reduced visibility, dust exposure everywhere, increased sensitivity in patients with asthma and bronchitis to respiratory illness in all exposed populations. During 2016, AQI category of Jakarta mostly “moderate”, while in Palembang was “good”. Dominant AQI category from 2015 to 2016 shows higher PM10 concentration occurred in Jakarta compared to Palembang.

On the origin and variability of suspended particulate matter (PM1, PM2.5 and PM10) concentrations in Cyprus.

Science.gov (United States)

Pikridas, Michael; Vrekoussis, Mihalis; Mihalopoulos, Nikolaos; Kizas, Christos; Savvides, Chrysanthos; Sciare, Jean

2017-04-01

The Eastern Mediterranean (EM) lies at the crossroad of three different continents (Europe, Asia, and Africa). EM is a densely populated region including several cities with 3M inhabitants or more (e.g. Athens, Istanbul, Izmir, and Cairo). It has been identified as the most polluted area in Europe with respect to particulate matter (PM) mainly due to the combination of high photochemical activity, which causes pollutants to oxidize and partitioning in the particle phase, with the elevated pollutants emissions from neighboring regions. In addition, the proximity to Africa and the Middle East allows frequent transport of dust particles. At the center of the Eastern Mediterranean lies the island of Cyprus, which has received very little attention regarding its PM levels despite being the location in Europe most frequently impacted by air masses from the Middle East. Herewith, we present a historical PM archive that spans 2 decades. It involves ongoing monitoring on a daily basis of particulate matter with diameters smaller than 10 μm (PM10), 2.5 μm (PM2.5), and 1 μm (PM1) conducted in at least one, of the 12 currently existing air quality stations in Cyprus since 1997, 2005, and 2009, respectively. The most extended PM datasets correspond a) to the Agia Marina Xyliatou (AMX) monitoring station established at a remote area at the foothills of mount Troodos and b) that of the inland capital, Nicosia. Based on this long-term dataset, the diurnal, temporal and annual variability is assessed. Prior to 2010, PM10 concentration at all sites remained relatively constant, but at different levels, violating the annual EU legislated PM10 limit of 40 μg m-3. Since 2010, coarse mode levels have decreased at all sites. The reported decrease was equal to 30% at AMX. As a result, since 2010 the observed levels comply with the EU legislation threshold. Satellite observations of Aerosol Optical Thickness (AOT) Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA

Climatology of atmospheric PM10 concentration in the Po Valley

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Bigi, A.; Ghermandi, G.

2014-01-01

The limits to atmospheric pollutant concentration set by the European Commission provide a challenging target for the municipalities in the Po Valley, because of the characteristic climatic conditions and high population density of this region. In order to assess climatology and trends in the concentration of atmospheric particles in the Po Valley, a dataset of PM10 data from 41 sites across the Po Valley have been analysed, including both traffic and background sites (either urban, suburban or rural). Of these 41 sites, 18 with 10 yr or longer record have been analysed for long term trend in de-seasonalized monthly means, in annual quantiles and in monthly frequency distribution. A widespread significant decreasing trend has been observed at most sites, up to few percent per year, by Generalised Least Square and Theil-Sen method. All 41 sites have been tested for significant weekly periodicity by Kruskal-Wallis test for mean anomalies and by Wilcoxon test for weekend effect magnitude. A significant weekly periodicity has been observed for most PM10 series, particularly in summer and ascribed mainly to anthropic particulate emissions. A cluster analysis has been applied in order to highlight stations sharing similar pollution conditions over the reference period. Five clusters have been found, two gathering the metropolitan areas of Torino and Milano and their respective nearby sites and the other three clusters gathering north-east, north-west and central Po Valley sites respectively. Finally the observed trends in atmospheric PM10 have been compared to trends in provincial emissions of particulates and PM precursors, and analysed along with data on vehicular fleet age, composition and fuel sales. Significant basin-wide drop in emissions occurred for gaseous pollutants, contrarily to emissions of PM10 and PM2.5, whose drop resulted low and restricted to few provinces. It is not clear whether the decrease for only gaseous emissions is sufficient to explain the

Changes in gene expression in chronic allergy mouse model exposed to natural environmental PM2.5-rich ambient air pollution.

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Ouyang, Yuhui; Xu, Zhaojun; Fan, Erzhong; Li, Ying; Miyake, Kunio; Xu, Xianyan; Zhang, Luo

2018-04-20

Particulate matter (PM) air pollution has been associated with an increase in the incidence of chronic allergic diseases; however, the mechanisms underlying the effect of exposure to natural ambient air pollution in chronic allergic diseases have not been fully elucidated. In the present study, we aimed to investigate the cellular responses induced by exposure to natural ambient air pollution, employing a mouse model of chronic allergy. The results indicated that exposure to ambient air pollution significantly increased the number of eosinophils in the nasal mucosa. The modulation of gene expression profile identified a set of regulated genes, and the Triggering Receptor Expressed on Myeloid cells1(TREM1) signaling canonical pathway was increased after exposure to ambient air pollution. In vitro, PM2.5 increased Nucleotide-binding oligomerization domain-containing protein 1 (Nod1) and nuclear factor (NF)-κB signaling pathway activation in A549 and HEK293 cell cultures. These results suggest a novel mechanism by which, PM2.5 in ambient air pollution may stimulate the innate immune system through the PM2.5-Nod1-NF-κB axis in chronic allergic disease.

Economic Impacts from PM2.5 Pollution-Related Health Effects: A Case Study in Shanghai.

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Wu, Rui; Dai, Hancheng; Geng, Yong; Xie, Yang; Masui, Toshihiko; Liu, Zhiqing; Qian, Yiying

2017-05-02

PM 2.5 pollution-related diseases cause additional medical expenses and work time loss, leading to macroeconomic impact in high PM 2.5 concentration areas. Previous economic impact assessments of air pollution focused on benefits from environmental regulations while ignoring climate policies. In this study, we examine the health and economic impacts from PM 2.5 pollution under various air pollution control strategies and climate policies scenarios in the megacity of Shanghai. The estimation adopts an integrated model combining a Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model, exposure-response functions (ERFs), and a computable general equilibrium (CGE) model. The results show that without control measures, Shanghai's mortality caused by PM 2.5 pollution are estimated to be 192 400 cases in 2030 and the work time loss to be 72.1 h/cap annually. The corresponding GDP values and welfare losses would be approximately 2.26% and 3.14%, respectively. With an estimated control cost of 0.76% of local GDP, Shanghai would gain approximately 1.01% of local GDP through local air pollution control measures and climate policies. Furthermore, the application of multiregional integrated control strategies in neighboring provinces would be the most effective in reducing PM 2.5 concentration in Shanghai, leading to only 0.34% of GDP loss. At the sectoral level, labor-intensive sectors suffer more output loss from PM 2.5 pollution. Sectors with the highest control costs include power generation, iron and steel, and transport. The results indicate that the combination of multiregional integrated air pollution control strategies and climate policies would be cost-beneficial for Shanghai.

Tillage and straw management affect PM10 emission potential in subarctic Alaska

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Emission of PM10 (particulates =10 um in diameter regulated by many nations as an air pollutant) from agricultural soils can impact regional air quality. Little information exists that describes the potential for PM10 and airborne dust emissions from subarctic soils or agricultural soils subject to ...

Morphology changes in human lung epithelial cells after exposure to diesel exhaust micron sub particles (PM1.0) and pollen allergens

International Nuclear Information System (INIS)

Esposito, V.; Lucariello, A.; Savarese, L.; Cinelli, M.P.; Ferraraccio, F.; Bianco, A.; De Luca, A.; Mazzarella, G.

2012-01-01

In the recent literature there has been an increased interest in the effects of particulate matter on the respiratory tract. The objective of this study was to use an in vitro model of type II lung epithelium (A549) to evaluate the cell ability to take up sub-micron PM 1.0 particles (PM 1.0 ), Parietaria officinalis (ALL), and PM 1.0 + ALL together. Morphological analysis performed by Transmission Electron Microscope (TEM) showed that PM and ALL interacted with the cell surface, then penetrating into the cytoplasm. Each single treatment was able to point out a specific change in the morphology. The cells treated appear healthy and not apoptotic. The main effect was the increase of: multilamellar bodies, lysosomal enzymes, microvilli, and presence of vesicle/vacuoles containing particles. These observations demonstrate morphological and functional alterations related to the PM 1.0 and P. officinalis and confirm the induction of the inflammatory response in lung cells exposed to the inhalable particles. - Highlights: ► Cell ability to take up PM 1.0 particles, Parietaria officinalis (ALL), PM 1.0 + ALL. ► The cells treated appear healthy and not apoptotic. ► Each single treatment was able to point out a specific change in the morphology. ► Increase of multilamellar bodies lysosomal enzymes microvilli vesicle with particles. ► Induction of inflammatory response in lung cells exposed to the inhalable particles. - The urban environment with the combination of inhalable air pollution and particulate can damage the acinar lung units and activate cells of the immune system.

Enhanced PM10 bounded PAHs from shipping emissions

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Pongpiachan, S.; Hattayanone, M.; Choochuay, C.; Mekmok, R.; Wuttijak, N.; Ketratanakul, A.

2015-05-01

Earlier studies have highlighted the importance of maritime transport as a main contributor of air pollutants in port area. The authors intended to investigate the effects of shipping emissions on the enhancement of PM10 bounded polycyclic aromatic hydrocarbons (PAHs) and mutagenic substances in an industrial area of Rayong province, Thailand. Daily PM10 speciation data across two air quality observatory sites in Thailand during 2010-2013 were collected. Diagnostic binary ratios of PAH congeners, analysis of variances (ANOVA), and principal component analysis (PCA) were employed to evaluate the enhanced genotoxicity of PM10 during the docking period. Significant increase of PAHs and mutagenic index (MI) of PM10 were observed during the docking period in both sampling sites. Although stationary sources like coal combustions from power plants and vehicular exhausts from motorway can play a great role in enhancing PAH concentrations, regulating shipping emissions from diesel engine in the port area like Rayong is predominantly crucial.

Assesment of Pb concentration in PM_2_,_5 and PM_1_0 at Serpong area

International Nuclear Information System (INIS)

Rita; Esrom Hamonangan; Halimah Syafrul; Muhayatun Santoso; Diah Dwiana Lestian

2010-01-01

Ambient air pollution, especially Pb, in Serpong area has been detected since 1996. Pollution caused by heavy metals Pb deserve serious attention because of the impact is very influential on health such as reduced levels of intelligence, learning disability, symptoms of anemia, barriers to growth, poor cognitive development, weakened immune system, symptoms of autism, and even premature death. This study was conducted to determine Pb concentration of PM_2_,_5 and PM_1_0 in four residential locations in Serpong area as part of a series of comprehensive studies for the characterization and identification of sources pollution. Particulates were sampled using Gent Stacked Filter Unit Sampler at 3 housing locations and 1 office location in the period of August 25 to November 3, 2008, Samples were analyzed using nuclear analytical techniques, Proton Induced X-ray Emission. The results showed that the activity concentration of Pb in PM_2_,_5 for the location of Setu, Pusarpedal, Batan Indah, and BSD were in the range of 33-388, 12-254, 6-282, and 5-332 ng/m"3, while for PM_1_0 were 69-732, 59-647, 31-810, and 28718 ng/m"3, respectively, In general, Pb concentrations in Serpong area were higher than those in some other cities in Asia region. These results are expected to be used as scientific based reference in formulating, taking action, and appropriate policies to overcome environmental problems. (author)

Comparison of lidar-derived PM10 with regional modeling and ground-based observations in the frame of MEGAPOLI experiment

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J.-C. Raut

2011-10-01

Full Text Available An innovative approach using mobile lidar measurements was implemented to test the performances of chemistry-transport models in simulating mass concentrations (PM10 predicted by chemistry-transport models. A ground-based mobile lidar (GBML was deployed around Paris onboard a van during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation summer experiment in July 2009. The measurements performed with this Rayleigh-Mie lidar are converted into PM10 profiles using optical-to-mass relationships previously established from in situ measurements performed around Paris for urban and peri-urban aerosols. The method is described here and applied to the 10 measurements days (MD. MD of 1, 15, 16 and 26 July 2009, corresponding to different levels of pollution and atmospheric conditions, are analyzed here in more details. Lidar-derived PM10 are compared with results of simulations from POLYPHEMUS and CHIMERE chemistry-transport models (CTM and with ground-based observations from the AIRPARIF network. GBML-derived and AIRPARIF in situ measurements have been found to be in good agreement with a mean Root Mean Square Error RMSE (and a Mean Absolute Percentage Error MAPE of 7.2 μg m−3 (26.0% and 8.8 μg m−3 (25.2% with relationships assuming peri-urban and urban-type particles, respectively. The comparisons between CTMs and lidar at ~200 m height have shown that CTMs tend to underestimate wet PM10 concentrations as revealed by the mean wet PM10 observed during the 10 MD of 22.4, 20.0 and 17.5 μg m−3 for lidar with peri-urban relationship, and POLYPHEMUS and CHIMERE models, respectively. This leads to a RMSE (and a MAPE of 6.4 μg m−3 (29.6% and 6.4 μg m−3 (27.6% when considering POLYPHEMUS and CHIMERE CTMs, respectively. Wet integrated PM10 computed (between the ground and 1 km above the ground level from lidar, POLYPHEMUS and CHIMERE results

TSP, PM10, and PM2.5 emissions from a beef cattle feedlot using the flux-gradient technique

Science.gov (United States)

Emissions data on air pollutants from large open-lot beef cattle feedlots are limited. This research was conducted to determine emissions of total suspended particulates (TSP) and particulate matter (PM10 and PM2.5) from a commercial beef cattle feedlot in Kansas (USA). Vertical particulate concentr...

MLP based models to predict PM10, O3 concentrations, in Sines industrial area

Science.gov (United States)

Durao, R.; Pereira, M. J.

2012-04-01

Sines is an important Portuguese industrial area located southwest cost of Portugal with important nearby protected natural areas. The main economical activities are related with this industrial area, the deep-water port, petrochemical and thermo-electric industry. Nevertheless, tourism is also an important economic activity especially in summer time with potential to grow. The aim of this study is to develop prediction models of pollutant concentration categories (e.g. low concentration and high concentration) in order to provide early warnings to the competent authorities who are responsible for the air quality management. The knowledge in advanced of pollutant high concentrations occurrence will allow the implementation of mitigation actions and the release of precautionary alerts to population. The regional air quality monitoring network consists in three monitoring stations where a set of pollutants' concentrations are registered on a continuous basis. From this set stands out the tropospheric ozone (O3) and particulate matter (PM10) due to the high concentrations occurring in the region and their adverse effects on human health. Moreover, the major industrial plants of the region monitor SO2, NO2 and particles emitted flows at the principal chimneys (point sources), also on a continuous basis,. Therefore Artificial neuronal networks (ANN) were the applied methodology to predict next day pollutant concentrations; due to the ANNs structure they have the ability to capture the non-linear relationships between predictor variables. Hence the first step of this study was to apply multivariate exploratory techniques to select the best predictor variables. The classification trees methodology (CART) was revealed to be the most appropriate in this case.. Results shown that pollutants atmospheric concentrations are mainly dependent on industrial emissions and a complex combination of meteorological factors and the time of the year. In the second step, the Multi

Using support vector regression to predict PM10 and PM2.5

International Nuclear Information System (INIS)

Weizhen, Hou; Zhengqiang, Li; Yuhuan, Zhang; Hua, Xu; Ying, Zhang; Kaitao, Li; Donghui, Li; Peng, Wei; Yan, Ma

2014-01-01

Support vector machine (SVM), as a novel and powerful machine learning tool, can be used for the prediction of PM 10 and PM 2.5 (particulate matter less or equal than 10 and 2.5 micrometer) in the atmosphere. This paper describes the development of a successive over relaxation support vector regress (SOR-SVR) model for the PM 10 and PM 2.5 prediction, based on the daily average aerosol optical depth (AOD) and meteorological parameters (atmospheric pressure, relative humidity, air temperature, wind speed), which were all measured in Beijing during the year of 2010–2012. The Gaussian kernel function, as well as the k-fold crosses validation and grid search method, are used in SVR model to obtain the optimal parameters to get a better generalization capability. The result shows that predicted values by the SOR-SVR model agree well with the actual data and have a good generalization ability to predict PM 10 and PM 2.5 . In addition, AOD plays an important role in predicting particulate matter with SVR model, which should be included in the prediction model. If only considering the meteorological parameters and eliminating AOD from the SVR model, the prediction results of predict particulate matter will be not satisfying

Assessment of health risk due to PM 10 using fuzzy linear membership kriging with particle swarm optimization

International Nuclear Information System (INIS)

Singh, Jeetendra B.; Reddy, Vijay S.; Jana, Soumya; De, Swades

2013-01-01

Air quality is an important determinant of individual as well as broader well-being. Major pollutants include gasses as well as assorted suspended particulate matter (PM). In this paper, we focus on PM10, which are a collection of particles with median aerodynamic diameter less than 10 μm that remains suspended in the air for long periods. PM10, usually consist of smoke, dirt and dust particles, as well as spores and pollen, could easily be inhaled deep into lung. As a result, high outdoor PM10 concentration poses significant health hazard, and accurate modeling and prediction of health risk due to PM10 assume importance in pollution and public health management. In this backdrop, we propose an improved health risk assessment technique, and demonstrate its efficacy using widely used California PM10 database. At the heart of the proposed method lies indicator kriging, a well-known risk estimation technique. However, improved assessment of subjective health risk is achieved by posing the problem in a fuzzy setting, and optimizing the associated membership functions. In particular, we employ particle swarm optimization (PSO) algorithm, which has been motivated by natural behavior of organisms such as fish-schooling and bird flocking, and proven effective in various optimization contexts. We apply the fuzzy PSO membership grade kriging technique to predict the PM10 spatial distribution over the entire California state. (orig.)

Assessment of health risk due to PM 10 using fuzzy linear membership kriging with particle swarm optimization

Energy Technology Data Exchange (ETDEWEB)

Singh, Jeetendra B.; Reddy, Vijay S.; Jana, Soumya [Indian Institute of Technology, Hyderabad (India). Dept. of Electrical Engineering; De, Swades [Indian Institute of Technology, Delhi (India). Dept. of Electrical Engineering

2013-07-01

Air quality is an important determinant of individual as well as broader well-being. Major pollutants include gasses as well as assorted suspended particulate matter (PM). In this paper, we focus on PM10, which are a collection of particles with median aerodynamic diameter less than 10 {mu}m that remains suspended in the air for long periods. PM10, usually consist of smoke, dirt and dust particles, as well as spores and pollen, could easily be inhaled deep into lung. As a result, high outdoor PM10 concentration poses significant health hazard, and accurate modeling and prediction of health risk due to PM10 assume importance in pollution and public health management. In this backdrop, we propose an improved health risk assessment technique, and demonstrate its efficacy using widely used California PM10 database. At the heart of the proposed method lies indicator kriging, a well-known risk estimation technique. However, improved assessment of subjective health risk is achieved by posing the problem in a fuzzy setting, and optimizing the associated membership functions. In particular, we employ particle swarm optimization (PSO) algorithm, which has been motivated by natural behavior of organisms such as fish-schooling and bird flocking, and proven effective in various optimization contexts. We apply the fuzzy PSO membership grade kriging technique to predict the PM10 spatial distribution over the entire California state. (orig.)

Estimation of daily PM10 concentrations in Italy (2006-2012) using finely resolved satellite data, land use variables and meteorology.

Science.gov (United States)

Stafoggia, Massimo; Schwartz, Joel; Badaloni, Chiara; Bellander, Tom; Alessandrini, Ester; Cattani, Giorgio; De' Donato, Francesca; Gaeta, Alessandra; Leone, Gianluca; Lyapustin, Alexei; Sorek-Hamer, Meytar; de Hoogh, Kees; Di, Qian; Forastiere, Francesco; Kloog, Itai

2017-02-01

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM 10 measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM 10 concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM 10 =0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM 10 levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM 10 concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatio-temporal characteristics of PM10 concentration across Malaysia

Science.gov (United States)

Juneng, Liew; Latif, Mohd Talib; Tangang, Fredolin T.; Mansor, Haslina

The recurrence of forest fires in Southeast Asia and associated biomass burning, has contributed markedly to the problem of trans-boundary haze and the long-range movement of pollutants in the region. Air pollutants, specifically particulate matter in the atmosphere, have received extensive attention, mainly because of their adverse effect on people's health. In this study, the spatial and temporal variability of the PM10 concentration across Malaysia was analyzed by means of the rotated principal component analysis. The results suggest that the variability of the PM10 concentration can be decomposed into four dominant modes, each characterizing different spatial and temporal variations. The first mode characterizes the southwest coastal region of the Malaysian Peninsular with the PM10 showing a peak concentration during the summer monsoon i.e. when the winds are predominantly southerlies or southwesterlies, and a minimal concentration during the winter monsoon. The second mode features the region of western Borneo with the PM10 exhibiting a concentration surge in August-September, which is likely to be the result of the northward shift of the Inter Tropical Convergence Zone (ITCZ) and the subsequent rapid arrival of the rainy season. The third mode delineates the northern region of the Malaysian Peninsular with strong bimodality in the PM10 concentration. Seasonally, this component exhibits two concentration maxima during the late winter and summer monsoons, as well as two minima during the inter-monsoon periods. The fourth dominant mode characterizes the northern Borneo region which exhibits weaker seasonality of the PM10 concentration. Generally, the seasonal fluctuation of the PM10 concentration is largely associated with the seasonal variation of rainfall in the country. However, in addition to this, the PM10 concentration also fluctuates markedly in two timescale bands i.e. 10-20 days quasi-biweekly (QBW) and 30-60 days lower frequency (LF) band of the intra

Modelación de episodios críticos de contaminación por material particulado (PM10 en Santiago de Chile: Comparación de la eficiencia predictiva de los modelos paramétricos y no paramétricos Modeling critical episodes of air pollution by PM10 in Santiago, Chile: Comparison of the predictive efficiency of parametric and non-parametric statistical models

Directory of Open Access Journals (Sweden)

Sergio A. Alvarado

2010-12-01

Full Text Available Objetivo: Evaluar la eficiencia predictiva de modelos estadísticos paramétricos y no paramétricos para predecir episodios críticos de contaminación por material particulado PM10 del día siguiente, que superen en Santiago de Chile la norma de calidad diaria. Una predicción adecuada de tales episodios permite a la autoridad decretar medidas restrictivas que aminoren la gravedad del episodio, y consecuentemente proteger la salud de la comunidad. Método: Se trabajó con las concentraciones de material particulado PM10 registradas en una estación asociada a la red de monitorización de la calidad del aire MACAM-2, considerando 152 observaciones diarias de 14 variables, y con información meteorológica registrada durante los años 2001 a 2004. Se ajustaron modelos estadísticos paramétricos Gamma usando el paquete estadístico STATA v11, y no paramétricos usando una demo del software estadístico MARS v 2.0 distribuida por Salford-Systems. Resultados: Ambos métodos de modelación presentan una alta correlación entre los valores observados y los predichos. Los modelos Gamma presentan mejores aciertos que MARS para las concentraciones de PM10 con valores Objective: To evaluate the predictive efficiency of two statistical models (one parametric and the other non-parametric to predict critical episodes of air pollution exceeding daily air quality standards in Santiago, Chile by using the next day PM10 maximum 24h value. Accurate prediction of such episodes would allow restrictive measures to be applied by health authorities to reduce their seriousness and protect the community´s health. Methods: We used the PM10 concentrations registered by a station of the Air Quality Monitoring Network (152 daily observations of 14 variables and meteorological information gathered from 2001 to 2004. To construct predictive models, we fitted a parametric Gamma model using STATA v11 software and a non-parametric MARS model by using a demo version of Salford

Temporal variations and spatial distribution of ambient PM2.2 and PM10 concentrations in Dhaka, Bangladesh.

Science.gov (United States)

Begum, Bilkis A; Biswas, Swapan K; Hopke, Philip K

2006-04-01

Concentrations and characteristics of airborne particulate matter (PM(10), PM(2.2) and BC) on air quality have been studied at two air quality-monitoring stations in Dhaka, the capital of Bangladesh. One site is at the Farm Gate area, a hot spot with very high pollutant concentrations because of its proximity to major roadways. The other site is at a semi-residential area located at the Atomic Energy Centre, Dhaka Campus, (AECD) with relatively less traffic. The samples were collected using a 'Gent' stacked filter unit in two fractions of 0-2.2 mum and 2.2-10 mum sizes. Samples of fine (PM(2.2)) and coarse (PM(2.2-10)) airborne particulate matter fractions collected from 2000 to 2003 were studied. It has been observed that fine particulate matter has a decreasing trend, from prior year measurements, because of Government policy interventions like phase-wise plans to take two-stroke three-wheelers off the roads in Dhaka and finally banned from January 1, 2003. Other policy interventions were banning of old buses and trucks to ply on Dhaka city promotion of the using compressed natural gas (CNG), introducing air pollution control devices in vehicles, etc. It was found that both local (mostly from vehicular emissions) and possibly some regional emission sources are responsible for high PM(2.2) and BC concentrations in Dhaka. PM(2.2), PM(2.2-10) and black carbon concentration levels depend on the season, wind direction and wind speed. Transport related emissions are the major source of BC and long-range transportation from fossil fuel related sources and biomass burning could be another substantial source of BC.

External costs of PM2.5 pollution in Beijing, China

DEFF Research Database (Denmark)

Hao, Yin; Pizzol, Massimo; Xu, Linyu

2017-01-01

Some cities in China are facing serious air pollution problems including high concentrations of particles, SO2 and NOx. Exposure to PM2.5, one of the primary air pollutants in many cities in China, is highly correlated with various adverse health impacts and ultimately represents a cost for society....... The aim of this study is to assess health impacts and external costs related to PM2.5 pollution in Beijing, China with different baseline concentrations and valuation methods. The idea is to provide a reasonable estimate of the total health impacts and external cost due to PM2.5 pollution, as well...... as a quantification of the relevant uncertainty. PM2.5 concentrations were retrieved for the entire 2012 period in 16 districts of Beijing. The various PM2.5 related health impacts were identified and classified to avoid double counting. Exposure-response coefficients were then obtained from literature. Both...

Effects of PM10 on human health in the western half of Iran (Ahwaz, Bushehr and Kermanshah Cities

Directory of Open Access Journals (Sweden)

Sahar Geravandi

2015-10-01

Full Text Available Background & Aims of the Study: Particulate matter pollutants have harmful effects on human health and can intensify mortality and disease. The aim of this study is evaluate to adverse health effects caused by exposure to PM 10 in Ahwaz, Bushehr and Kermanshah Cities during 2011. Materials & Methods: In this study, the Air Q2.2.3 model was used for estimated adverse health effects of exposure to PM 10 . Air Q model provided by the WHO European Centre for Environment and Health (ECEH. Air Q software proved to be a valid and reliable tool to estimate the potential short term effects of air pollution. Daily concentrations of PM 10 were taken from Department of Environment (ADoE. Then processing data’s and finally the cardiovascular and respiratory disease attributable to this pollutant were calculated.   Results: Results show that the non hospitalized patients suffer from the cardiovascular and respiratory diseases attributable to Pm 10 . The patients from Ahwaz allocate the highest rate of hospital admittance to themselves with 19% respiratory and 20% cardiovascular charts those from Bushehr refer to hospitals 14% for respiratory illness and 15% for cardiac disease and the subjects from Kermanshah go to the hospitals 12% for respiratory complications and 14% for cardiac failures. Conclusions: The results indicate a direct relationship between the concentration of PM 10 and health effects resulting from exposure to them. The highest rate belongs to Ahwaz becomes it has greater concentration of dusty air. Therefore, the higher relative risk value can depict mismanagement in urban air quality.

Procedures for identifying reasonably available control technology for stationary sources of PM-10. Final report

International Nuclear Information System (INIS)

Fitzpatrick, M.J.; Ellefson, R.

1992-09-01

The guidance document sets forth procedures and identifies sources of information that will assist State and local air pollution control agencies in determining Reasonably Available Control Technology (RACT) for PM-10 (particulate matter having a nominal aerometric diameter of 10 microns or less) emission from existing stationary sources on a case-by-case basis. It provides an annotated bibliography of documents to aid in identifying the activities that cause PM-10 emissions as well as applicable air pollution control measures and their effectiveness in reducing emissions. The most stringent state total particulate matter (PM) emission limits are identified for several categories of PM-10 sources and compared to available emission test data. Finally, guidance is provided on procedures for estimating total capital investment and total annual cost of the control measures which are generally used to control PM-10 emissions

Secondary organic carbon quantification and source apportionment of PM10 in Kaifeng, China

Institute of Scientific and Technical Information of China (English)

WU Lin; FENG Yinchang; WU Jianhui; ZHU Tan; BI Xiaohui; HAN Bo; YANG Weihong; YANG Zhiqiang

2009-01-01

During 2005, the filter samples of ambient PM10 from five sites and the source samples of particulate matter were collected in Kaifeng, Henan province of China. Nineteen elements, water-soluble ions, total carbon (TC) and organic carbon (OC) contained in samples were analyzed. Seven contributive source types were identified and their contributions to ambient PM10 were estimated by chemical mass balance (CMB) receptor model. Weak associations between the concentrations of organic carbon and element carbon (EC) were observed during the sampling periods, indicating that there was secondary organic aerosol pollution in the urban atmosphere. An indirect method of "OC/EC minimum ratio" was applied to estimate the concentration of secondary organic carbon (SOC). The results showed that SOC contributed 26.2%, 32.4% and 18.0% of TC in spring, summer-fall and winter respectively, and the annual average SOC concentration was 7.07 μg/m3, accounting for 5.73% of the total mass in ambient PM10. The carbon species concentrations in ambient PM10 were recalculated by subtracting the SOC concentrations from measured concentrations of TC and OC to increase the compatibility of source and receptor measurements for CMB model.

A mouse dry eye model induced by topical administration of the air pollutant particulate matter 10.

Science.gov (United States)

Li, Juan; Tan, Gang; Ding, Xiaoyan; Wang, Yahong; Wu, Anhua; Yang, Qichen; Ye, Lei; Shao, Yi

2017-12-01

To introduce a novel dry eye mouse model induced by topical administration of the air pollutant particulate matter 10 (PM 10 ). A total of 60 male BALB/c mice were used in this study and divided into two groups: group A (PBS eye drops, n=30) and group B (PM 10 eye drop group, n=30). Each treatment was dosed four times a day, every time 50ul with the concentration of 5mg/ml PM10, for 14 consecutive days in the right eye. The clinical manifestations of dry eye were measured before therapy and 4, 7 and 14days post-treatment respectively, which included the tear volume, tear break-up (BUT) time, corneal fluorescein staining, rose bengal staining, Lissamine Green staining and inflammatory index. Eye samples were collected on D14 and examined by histologic light microscopy, transmission electron microscopy (TEM) and scanning electron microscopy (SEM), corneal cytokeration 10 (K10) immunnostaining, and tumor necrosis factor-α (TNF-α), NF-κB-p65 and NF-κB Western Blot analysis. At 0d, 7d and 14d, there were no statistical changes in tear volume, BUT after treatment (P>0.05) with PBS in group A. In group B, all items showed statistical differences at each time point (Plevels of K10 and reduced number of goblet cells in the conjunctival fornix in group B. PM 10 significantly increased the levels of TNF-α, NF-κB-p65 and NF-κB in the cornea. PM 10 can damage the tear film function and cause the destruction of the structural organization of ocular surface in mice. Topical administration of PM 10 in mice induces ocular surface changes that are similar to those of dry eye in humans, representing a novel model of DES. Copyright © 2017. Published by Elsevier Masson SAS.

Hospital indoor PM10/PM2.5 and associated trace elements in Guangzhou, China

International Nuclear Information System (INIS)

Wang Xinhua; Bi Xinhui; Sheng Guoying; Fu Jiamo

2006-01-01

PM10 and PM2.5 samples were collected in the indoor environments of four hospitals and their adjacent outdoor environments in Guangzhou, China during the summertime. The concentrations of 18 target elements in particles were also quantified. The results showed that indoor PM2.5 levels with an average of 99 μg m -3 were significantly higher than outdoor PM2.5 standard of 65 μg m -3 recommended by USEPA [United States Environmental Protection Agency. Office of Air and Radiation, Office of Air Quality Planning and Standards, Fact Sheet. EPA's Revised Particulate Matter Standards, 17, July 1997] and PM2.5 constituted a large fraction of indoor respirable particles (PM10) by an average of 78% in four hospitals. High correlation between PM2.5 and PM10 (R 2 of 0.87 for indoors and 0.90 for outdoors) suggested that PM2.5 and PM10 came from similar particulate emission sources. The indoor particulate levels were correlated with the corresponding outdoors (R 2 of 0.78 for PM2.5 and 0.67 for PM10), demonstrating that outdoor infiltration could lead to direct transportation into indoors. In addition to outdoor infiltration, human activities and ventilation types could also influence indoor particulate levels in four hospitals. Total target elements accounted for 3.18-5.56% of PM2.5 and 4.38-9.20% of PM10 by mass, respectively. Na, Al, Ca, Fe, Mg, Mn and Ti were found in the coarse particles, while K, V, Cr, Ni, Cu, Zn, Cd, Sn, Pb, As and Se existed more in the fine particles. The average indoor concentrations of total elements were lower than those measured outdoors, suggesting that indoor elements originated mainly from outdoor emission sources. Enrichment factors (EF) for trace element were calculated to show that elements of anthropogenic origins (Zn, Pb, As, Se, V, Ni, Cu and Cd) were highly enriched with respect to crustal composition (Al, Fe, Ca, Ti and Mn). Factor analysis was used to identify possible pollution source-types, namely street dust, road traffic and

Hospital indoor PM10/PM2.5 and associated trace elements in Guangzhou, China.

Science.gov (United States)

Wang, Xinhua; Bi, Xinhui; Sheng, Guoying; Fu, Jiamo

2006-07-31

PM10 and PM2.5 samples were collected in the indoor environments of four hospitals and their adjacent outdoor environments in Guangzhou, China during the summertime. The concentrations of 18 target elements in particles were also quantified. The results showed that indoor PM2.5 levels with an average of 99 microg m(-3) were significantly higher than outdoor PM2.5 standard of 65 microg m(-3) recommended by USEPA [United States Environmental Protection Agency. Office of Air and Radiation, Office of Air Quality Planning and Standards, Fact Sheet. EPA's Revised Particulate Matter Standards, 17, July 1997] and PM2.5 constituted a large fraction of indoor respirable particles (PM10) by an average of 78% in four hospitals. High correlation between PM2.5 and PM10 (R(2) of 0.87 for indoors and 0.90 for outdoors) suggested that PM2.5 and PM10 came from similar particulate emission sources. The indoor particulate levels were correlated with the corresponding outdoors (R(2) of 0.78 for PM2.5 and 0.67 for PM10), demonstrating that outdoor infiltration could lead to direct transportation into indoors. In addition to outdoor infiltration, human activities and ventilation types could also influence indoor particulate levels in four hospitals. Total target elements accounted for 3.18-5.56% of PM2.5 and 4.38-9.20% of PM10 by mass, respectively. Na, Al, Ca, Fe, Mg, Mn and Ti were found in the coarse particles, while K, V, Cr, Ni, Cu, Zn, Cd, Sn, Pb, As and Se existed more in the fine particles. The average indoor concentrations of total elements were lower than those measured outdoors, suggesting that indoor elements originated mainly from outdoor emission sources. Enrichment factors (EF) for trace element were calculated to show that elements of anthropogenic origins (Zn, Pb, As, Se, V, Ni, Cu and Cd) were highly enriched with respect to crustal composition (Al, Fe, Ca, Ti and Mn). Factor analysis was used to identify possible pollution source-types, namely street dust, road traffic

Metro Commuter Exposures to Particulate Air Pollution and PM2.5-Associated Elements in Three Canadian Cities: The Urban Transportation Exposure Study.

Science.gov (United States)

Van Ryswyk, Keith; Anastasopolos, Angelos T; Evans, Greg; Sun, Liu; Sabaliauskas, Kelly; Kulka, Ryan; Wallace, Lance; Weichenthal, Scott

2017-05-16

System-representative commuter air pollution exposure data were collected for the metro systems of Toronto, Montreal, and Vancouver, Canada. Pollutants measured included PM 2.5 (PM = particulate matter), PM 10 , ultrafine particles, black carbon, and the elemental composition of PM 2.5 . Sampling over three weeks was conducted in summer and winter for each city and covered each system on a daily basis. Mixed-effect linear regression models were used to identify system features related to particulate exposures. Ambient levels of PM 2.5 and its elemental components were compared to those of the metro in each city. A microenvironmental exposure model was used to estimate the contribution of a 70 min metro commute to daily mean exposure to PM 2.5 elemental and mass concentrations. Time spent in the metro was estimated to contribute the majority of daily exposure to several metallic elements of PM 2.5 and 21.2%, 11.3% and 11.5% of daily PM 2.5 exposure in Toronto, Montreal, and Vancouver, respectively. Findings suggest that particle air pollutant levels in Canadian metros are substantially impacted by the systems themselves, are highly enriched in steel-based elements, and can contribute a large portion of PM 2.5 and its elemental components to a metro commuter's daily exposure.

A Time-Series Study of the Effect of Air Pollution on Outpatient Visits for Acne Vulgaris in Beijing.

Science.gov (United States)

Liu, Wei; Pan, Xiaochuan; Vierkötter, Andrea; Guo, Qun; Wang, Xuying; Wang, Qiaowei; Seité, Sophie; Moyal, Dominique; Schikowski, Tamara; Krutmann, Jean

2018-01-01

There is increasing evidence that exposure to air pollutants, including particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2), might aggravate preexisting skin diseases such as eczema and urticaria. Here we investigated if a possible link exists between air pollution and acne vulgaris. We assessed the association between ambient air pollutant concentrations and the number of visits of patients for acne vulgaris to a dermatological outpatient clinic in Beijing, China, from April 1, 2012 to April 30, 2014. In this time period, 59,325 outpatient visits were recorded because of acne vulgaris. Daily air pollution parameters for PM10, PM2.5, SO2, and NO2 were obtained from the Beijing Municipal Environmental Monitoring Center. Increased concentrations of ambient PM2.5, PM10, and NO2 were significantly associated with increased numbers of outpatient visits for acne vulgaris over the 2 years. These effects could be observed for NO2 in a single-pollutant model and for PM2.5, PM10, and NO2 in 2-pollutant models, which are closer to real-life exposure. Of note, these effects were specific because they were not observed for increased SO2 concentrations, which even showed negative correlations in all test models. This study provides indirect evidence for a link between acne vulgaris and air pollution. © 2018 S. Karger AG, Basel.

Ambient levels and temporal variations of PM2.5 and PM10 at a residential site in the mega-city, Nanjing, in the western Yangtze River Delta, China.

Science.gov (United States)

Shen, Guo F; Yuan, Si Y; Xie, Yu N; Xia, Si J; Li, Li; Yao, Yu K; Qiao, Yue Z; Zhang, Jie; Zhao, Qiu Y; Ding, Ai J; Li, Bin; Wu, Hai S

2014-01-01

The deteriorating air quality in eastern China including the Yangtze River Delta is attracting growing public concern. In this study, we measured the ambient PM10 and fine PM2.5 in the mega-city, Nanjing at four different times. The 24-h average PM2.5 and PM10 mass concentrations were 0.033-0.234 and 0.042-0.328 mg/m(3), respectively. The daily PM10 and PM2.5 concentrations were 2.9 (2.7-3.2, at 95% confidence interval) and 4.2 (3.8-4.6) times the WHO air quality guidelines of 0.025 mg/m(3) for PM2.5 and 0.050 mg/m(3) for PM10, respectively, which indicated serious air pollution in the city. There was no obvious weekend effect. The highest PM10 pollution occurred in the wintertime, with higher PM2.5 loadings in the winter and summer. PM2.5 was correlated significantly with PM10 and the average mass fraction of PM2.5 in PM10 was about 72.5%. This fraction varied during different sampling periods, with the lowest PM2.5 fraction in the spring but minor differences among the other three seasons.

Quantifying PM2.5-Meteorology Sensitivities in a Global Climate Model

Science.gov (United States)

Westervelt, D. M.; Horowitz, L. W.; Naik, V.; Tai, A. P. K.; Fiore, A. M.; Mauzerall, D. L.

2016-01-01

Climate change can influence fine particulate matter concentrations (PM2.5) through changes in air pollution meteorology. Knowledge of the extent to which climate change can exacerbate or alleviate air pollution in the future is needed for robust climate and air pollution policy decision-making. To examine the influence of climate on PM2.5, we use the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 (GFDL CM3), a fully-coupled chemistry-climate model, combined with future emissions and concentrations provided by the four Representative Concentration Pathways (RCPs). For each of the RCPs, we conduct future simulations in which emissions of aerosols and their precursors are held at 2005 levels while other climate forcing agents evolve in time, such that only climate (and thus meteorology) can influence PM2.5 surface concentrations. We find a small increase in global, annual mean PM2.5 of about 0.21 micro-g/cu m3 (5%) for RCP8.5, a scenario with maximum warming. Changes in global mean PM2.5 are at a maximum in the fall and are mainly controlled by sulfate followed by organic aerosol with minimal influence of black carbon. RCP2.6 is the only scenario that projects a decrease in global PM2.5 with future climate changes, albeit only by -0.06 micro-g/cu m (1.5%) by the end of the 21st century. Regional and local changes in PM2.5 are larger, reaching upwards of 2 micro-g/cu m for polluted (eastern China) and dusty (western Africa) locations on an annually averaged basis in RCP8.5. Using multiple linear regression, we find that future PM2.5 concentrations are most sensitive to local temperature, followed by surface wind and precipitation. PM2.5 concentrations are robustly positively associated with temperature, while negatively related with precipitation and wind speed. Present-day (2006-2015) modeled sensitivities of PM2.5 to meteorological variables are evaluated against observations and found to agree reasonably well with observed sensitivities (within 10e50

Spatiotemporal patterns of particulate matter (PM and associations between PM and mortality in Shenzhen, China

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Fengying Zhang

2016-03-01

Full Text Available Abstract Background Most studies on air pollution exposure and its associations with human health in China have focused on the heavily polluted industrial areas and/or mega-cities, and studies on cities with comparatively low air pollutant concentrations are still rare. Only a few studies have attempted to analyse particulate matter (PM for the vibrant economic centre Shenzhen in the Pearl River Delta. So far no systematic investigation of PM spatiotemporal patterns in Shenzhen has been undertaken and the understanding of pollution exposure in urban agglomerations with comparatively low pollution is still limited. Methods We analyze daily and hourly particulate matter concentrations and all-cause mortality during 2013 in Shenzhen, China. Temporal patterns of PM (PM2.5 and PM10 with aerodynamic diameters of 2.5 (10 μm or less (or less (including particles with a diameter that equals to 2.5 (10 μm are studied, along with the ratio of PM2.5 to PM10. Spatial distributions of PM10 and PM2.5 are addressed and associations of PM10 or PM2.5 and all-cause mortality are analyzed. Results Annual average PM10 and PM2.5 concentrations were 61.3 and 39.6 μg/m3 in 2013. PM2.5 failed to meet the Class 2 annual limit of the National Ambient Air Quality Standard. PM2.5 was the primary air pollutant, with 8.8 % of days having heavy PM2.5 pollution. The daily PM2.5/PM10 ratios were high. Hourly PM2.5 concentrations in the tourist area were lower than downtown throughout the day. PM10 and PM2.5 concentrations were higher in western parts of Shenzhen than in eastern parts. Excess risks in the number of all-cause mortality with a 10 μg/m3 increase of PM were 0.61 % (95 % confidence interval [CI]: 0.50–0.72 for PM10, and 0.69 % (95 % CI: 0.55–0.83 for PM2.5, respectively. The greatest ERs of PM10 and PM2.5 were in 2-day cumulative measures for the all-cause mortality, 2-day lag for females and the young (0–65 years, and L02 for males and the elder (>65

Assessment of microbial communities in PM1 and PM10 of Urumqi during winter

International Nuclear Information System (INIS)

Gou, Huange; Lu, Jianjiang; Li, Shanman; Tong, Yanbin; Xie, Chunbin; Zheng, Xiaowu

2016-01-01

Recently, inhalable particulate matter has been reported to carry microorganisms responsible for human allergy and respiratory disease. The unique geographical environment and adverse weather conditions of Urumqi cause double pollution of dust and smog, but research on the microbial content of the atmosphere has not been commenced. In this study, 16S and 18S rRNA gene sequencing were conducted to investigate the microbial composition of Urumqi's PM 1 and PM 10 pollutants in winter. Results showed that the bacterial community is mainly composed of Proteobacteria, Firmicutes and Actinobacteria, Proteobacteria accounted for the most proportion which was significant difference in some aforementioned studies. Ascomycota and Basidiomycota constitute the main part of the fungal microbial community. The difference of bacterial relative abundance in sample point is greater than in particle sizes. The sequences of several pathogenic bacteria and opportunistic pathogens were also detected, such as Acinetobacter, Delftia, Serratia, Chryseobacterium, which may impact on immunocompromised populations (elderly, children and postoperative convalescence patients), and some fungal genera may cause several plant diseases. Our findings may serve an important reference value in the global air microbial propagation and air microbial research in desert. - Highlights: • Using 16 s rDNA double variable region (V3 + V4) sequencing to elucidate the bacterial communities. • Several potential microbial allergens and pathogens present in PM 1 and PM 10 were found. • Providing a great supplement to environmental science and human health assessment.

Receptor model-based source apportionment of particulate pollution in Hyderabad, India.

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Guttikunda, Sarath K; Kopakka, Ramani V; Dasari, Prasad; Gertler, Alan W

2013-07-01

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2 ± 24.6, 96.2 ± 12.1, and 64.3 ± 21.2 μg/m(3) of PM10, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m(3). In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM10 and PM2.5 size fractions for three seasons. The receptor modeling results indicated that the PM10 pollution is dominated by the direct vehicular exhaust and road dust (more than 60%). PM2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.

Long-term exposure to ambient air pollution (including PM1) and metabolic syndrome: The 33 Communities Chinese Health Study (33CCHS).

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Yang, Bo-Yi; Qian, Zhengmin Min; Li, Shanshan; Fan, Shujun; Chen, Gongbo; Syberg, Kevin M; Xian, Hong; Wang, Si-Quan; Ma, Huimin; Chen, Duo-Hong; Yang, Mo; Liu, Kang-Kang; Zeng, Xiao-Wen; Hu, Li-Wen; Guo, Yuming; Dong, Guang-Hui

2018-07-01

Little evidence exists about the effects of long-term exposure to ambient air pollution on metabolic syndrome (MetS). This study aimed to determine the association between long-term ambient air pollution and MetS in China. A total of 15,477 adults who participated in the 33 Communities Chinese Health Study (33CCHS) in 2009 were evaluated. MetS was defined based on the recommendation by the Joint Interim Societies. Exposure to air pollutants was assessed using data from monitoring stations and a spatial statistical model (including particles with diameters ≤ 1.0 µm (PM 1 ), ≤ 2.5 µm (PM 2.5 ), and ≤ 10 µm (PM 10 ), sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), and ozone (O 3 )). Two-level logistic regression analyses were utilized to assess the associations between air pollutants and MetS. The prevalence of MetS was 30.37%. The adjusted odds ratio of MetS per 10 µg/m 3 increase in PM 1 , PM 2.5 , PM 10 , SO 2 , NO 2 , and O 3 were 1.12 (95% CI = 1.00-1.24), 1.09 (95% CI = 1.00-1.18), 1.13 (95% CI = 1.08-1.19), 1.10 (95% CI = 1.02-1.18), 1.33 (95% CI = 1.12-1.57), and 1.10 (95% CI = 1.01-1.18), respectively. Stratified analyses indicated that the above associations were stronger in participants with the demographic variables of males, < 50 years of age, and higher income, as well as with the behavioral characteristics of smoking, drinking, and consuming sugar-sweetened soft drinks frequently. This study indicates that long-term exposure to ambient air pollutants may increase the risk of MetS, especially among males, the young to middle aged, those of low income, and those with unhealthy lifestyles. Copyright © 2018 Elsevier Inc. All rights reserved.

Multi-criteria Analysis of Air Pollution with SO(2) and PM(10) in Urban Area Around the Copper Smelter in Bor, Serbia.

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Nikolić, Djordje; Milošević, Novica; Mihajlović, Ivan; Zivković, Zivan; Tasić, Viša; Kovačević, Renata; Petrović, Nevenka

2010-02-01

This work presents the results of 4 years long monitoring of concentrations of SO(2) gas and PM(10) in the urban area around the copper smelter in Bor. The contents of heavy metals Pb, Cd, Cu, Ni, and As in PM(10) were determined and obtained values were compared to the limit values provided in EU Directives. Manifold excess concentrations of all the components in the atmosphere of the urban area of the townsite Bor were registered. Through application of a multi-criteria analysis by using PROMETHEE/GAIA method, the zones were ranked according to the level of pollution.

Seasonal variation, risk assessment and source estimation of PM 10 and PM10-bound PAHs in the ambient air of Chiang Mai and Lamphun, Thailand.

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Pengchai, Petch; Chantara, Somporn; Sopajaree, Khajornsak; Wangkarn, Sunanta; Tengcharoenkul, Urai; Rayanakorn, Mongkon

2009-07-01

Daily PM10 concentrations were measured at four sampling stations located in Chiang Mai and Lamphun provinces, Thailand. The sampling scheme was conducted during June 2005 to June 2006; every 3 days for 24 h in each sampling period. The result revealed that all stations shared the same pattern, in which the PM10 (particulate matters with diameter of less than 10 microm) concentration increased at the beginning of dry season (December) and reached its peak in March before decreasing by the end of April. The maximum PM10 concentration for each sampling station was in the range of 140-182 microg/m(3) which was 1.1-1.5 times higher than the Thai ambient air quality standard of 120 microg/m(3). This distinctly high concentration of PM10 in the dry season (Dec. 05-Mar. 06) was recognized as a unique seasonal pattern for the northern part of Thailand. PM10 concentration had a medium level of negative correlation (r = -0.696 to -0.635) with the visibility data. Comparing the maximum PM10 concentration detected at each sampling station to the permitted PM10 level of the national air quality standard, the warning visibility values for the PM10 pollution-watch system were determined as 10 km for Chiang Mai Province and 5 km for Lamphun Province. From the analysis of PM10 constituents, no component exceeded the national air quality standard. The total concentrations of PM10-bond polycyclic aromatic hydrocarbons (PAHs) are calculated in terms of total toxicity equivalent concentrations (TTECs) using the toxicity equivalent factors (TEFs) method. TTECs in Chiang Mai and Lamphun ambient air was found at a level comparable to those observed in Nagasaki, Bangkok and Rome and at a lower level than those reported at Copenhagen. The annual number of lung cancer cases for Chiang Mai and Lamphun Provinces was estimated at two cases/year which was lower than the number of cases in Bangkok (27 cases/year). The principal component analysis/absolute principal component scores (PCA

Economic Impacts from PM2.5 Pollution-Related Health Effects in China: A Provincial-Level Analysis.

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Xie, Yang; Dai, Hancheng; Dong, Huijuan; Hanaoka, Tatsuya; Masui, Toshihiko

2016-05-03

This study evaluates the PM2.5 pollution-related health impacts on the national and provincial economy of China using a computable general equilibrium (CGE) model and the latest nonlinear exposure-response functions. Results show that the health and economic impacts may be substantial in provinces with a high PM2.5 concentration. In the WoPol scenario without PM2.5 pollution control policy, we estimate that China experiences a 2.00% GDP loss and 25.2 billion USD in health expenditure from PM2.5 pollution in 2030. In contrast, with control policy in the WPol scenario, a control investment of 101.8 billion USD (0.79% of GDP) and a gain of 1.17% of China's GDP from improving PM2.5 pollution are projected. At the provincial level, GDP loss in 2030 in the WoPol scenario is high in Tianjin (3.08%), Shanghai (2.98%), Henan (2.32%), Beijing (2.75%), and Hebei (2.60%) and the top five provinces with the highest additional health expenditure are Henan, Sichuan, Shandong, Hebei, and Jiangsu. Controlling PM2.5 pollution could bring positive benefits in two-thirds of provinces. Tianjin, Shanghai, Beijing, Henan, Jiangsu, and Hebei experience most benefits from PM2.5 pollution control as a result of a higher PM2.5 pollution and dense population distribution. Conversely, the control investment is higher than GDP gain in some underdeveloped provinces, such as Ningxia, Guizhou, Shanxi, Gansu, and Yunnan.

Particulate Matter Dispersion (PM10, with interrelation of topographic and meteorological factors

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Alvaro Javier Arrieta-Fuentes

2016-07-01

Full Text Available Mining-industrial processes carried out by anthropic action, bring the generation of impacts to the environment. Between the impacts associated with mining is the involvement of the air quality produced by the release of atmospheric pollutants, being subject to study the behavior of the respirable fraction of particulate matter less than 10 microns (PM10 with respect to meteorological and topographical factors. The analyzed scenarios in the study involved daily and annual exposure times of PM10, in wich modeling with AERMOD View Software was made. The model was carried out in two topographic zones, a complex area, located in the municipality of Socha and a simple area located in the municipality of Sogamoso. It was used meteorological data type satellite, in format .SAM for modeled areas. Three types of emission sources were identified in the areas; considering that the disperse fixed emission sources predominate, followed by the mobile sources and point sources were found in low proportion. PM10 dispersion models made for the zones of simple and complex topography, gave as result that direction and the wind speed is conditioned by the type of zone. It allowed a free flow in the predominant direction in wind rose to the area of simple topography and a turbulent flow in the complex area. It was determined that the sources of emission of PM10 in both cases are local scale; They presented a critical radius of drag and deposition of particles of 200 m approximately.

2005-2014 trends of PM10 source contributions in an industrialized area of southern Spain.

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Li, Jiwei; Chen, Bing; de la Campa, Ana M Sánchez; Alastuey, Andrés; Querol, Xavier; de la Rosa, Jesus D

2018-05-01

Particulate matter with a diameter of 10 μm or less (PM10) using receptor modelling was determined at an urban (La Linea, LL) and an industrial area (Puente Mayorga, PMY) in Southern Spain with samples collected during 2005-2014. The concentrations of PM10 had been decreasing at both sites in three distinctive periods: 1) the initial PM10 levels approached or exceeded the Spain and EU PM10 annual guidelines of 40 μg/m 3 during 2005-2007 at LL and 2005-2009 at PMY; 2) then PM10 dropped by 25%-∼30 μg/m 3 during 2008-2011 at LL and during 2010-2011 at PMY; 3) since 2012, the PM10 concentrations gradually decreased to major elements. These PM components generally showed a decrease trend, in accord with the trend of PM10 reduction. A PMF model identified seven sources to PM10 contributions. Secondary sulfate, soil/urban/construction dust, and secondary nitrate showed significantly decreasing trends with reduction of 40-60% comparing to the initial levels. The road traffic contribution decreased by 14% from the first to third period. However, sea salt, oil combustion, and industrial metallurgical process had relative stable contributions. These source contribution changes are reasonably governed by the PM emission abatement actions implemented during the past decade, as well as the financial crisis, that accounted for a significant decrease of PM pollution in Southern Spain. We identified that the mitigation efforts on industry, fossil fuel combustion, and urban transportation during the past decade were successful for air quality improvement in a highly industrialized area in Southern Spain. Copyright © 2018 Elsevier Ltd. All rights reserved.

Source identification and long-term monitoring of airborne particulate matter (PM2.5/PM10) in an urban region of Korea

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Yong-Sam Chung; Sun-Ha Kim; Jong-Hwa Moon; Young-Jin Kim; Jong-Myoung Lim; Jin-Hong Lee

2006-01-01

For the identification of air pollution sources, about 500 airborne particulate matter (PM 2.5 and PM 10 ) samples were collected by using a Gent air sampler and a polycarbonate filter in an urban region in the middle of Korea from 2000 to 2003. The concentrations of 25 elements in the samples were measured by using instrumental neutron activation analysis (INAA). Receptor modeling was performed on the air monitoring data by using the positive matrix factorization (PMF2) method. According to this analysis, the existence of 6 to 10 PMF factors, such as metal-alloy, oil combustion, diesel exhaust, coal combustion, gasoline exhaust, incinerator, Cu-smelter, biomass burning, sea-salt, and soil dust were identified. (author)

Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering

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Elangasinghe, M. A.; Singhal, N.; Dirks, K. N.; Salmond, J. A.; Samarasinghe, S.

2014-09-01

This paper uses artificial neural networks (ANN), combined with k-means clustering, to understand the complex time series of PM10 and PM2.5 concentrations at a coastal location of New Zealand based on data from a single site. Out of available meteorological parameters from the network (wind speed, wind direction, solar radiation, temperature, relative humidity), key factors governing the pattern of the time series concentrations were identified through input sensitivity analysis performed on the trained neural network model. The transport pathways of particulate matter under these key meteorological parameters were further analysed through bivariate concentration polar plots and k-means clustering techniques. The analysis shows that the external sources such as marine aerosols and local sources such as traffic and biomass burning contribute equally to the particulate matter concentrations at the study site. These results are in agreement with the results of receptor modelling by the Auckland Council based on Positive Matrix Factorization (PMF). Our findings also show that contrasting concentration-wind speed relationships exist between marine aerosols and local traffic sources resulting in very noisy and seemingly large random PM10 concentrations. The inclusion of cluster rankings as an input parameter to the ANN model showed a statistically significant (p advanced air dispersion models.

Synoptic weather types and aeroallergens modify the effect of air pollution on hospitalisations for asthma hospitalisations in Canadian cities.

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Hebbern, Christopher; Cakmak, Sabit

2015-09-01

Pollution levels and the effect of air pollution on human health can be modified by synoptic weather type and aeroallergens. We investigated the effect modification of aeroallergens on the association between CO, O3, NO2, SO2, PM10, PM2.5 and asthma hospitalisation rates in seven synoptic weather types. We developed single air pollutant models, adjusted for the effect of aeroallergens and stratified by synoptic weather type, and pooled relative risk estimates for asthma hospitalisation in ten Canadian cities. Aeroallergens significantly modified the relative risk in 19 pollutant-weather type combinations, reducing the size and variance for each single pollutant model. However, aeroallergens did not significantly modify relative risk for any pollutant in the DT or MT weather types, or for PM10 in any weather type. Thus, there is a modifying effect of aeroallergens on the association between CO, O3, NO2, SO2, PM2.5 and asthma hospitalisations that differs under specific synoptic weather types. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Urban aerosol in Oporto, Portugal: Chemical characterization of PM10 and PM2.5

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Custódio, Danilo; Ferreira, Catarina; Alves, Célia; Duarte, Mácio; Nunes, Teresa; Cerqueira, Mário; Pio, Casimiro; Frosini, Daniele; Colombi, Cristina; Gianelle, Vorne; Karanasiou, Angeliki; Querol, Xavier

2014-05-01

Several urban and industrial areas in Southern Europe are not capable of meeting the implemented EU standards for particulate matter. Efficient air quality management is required in order to ensure that the legal limits are not exceeded and that the consequences of poor air quality are controlled and minimized. Many aspects of the direct and indirect effects of suspended particulate matter on climate and public health are not well understood. The temporal variation of the chemical composition is still demanded, since it enables to adopt off-set strategies and to better estimate the magnitude of anthropogenic forcing on climate. This study aims to provide detailed information on concentrations and chemical composition of aerosol from Oporto city, an urban center in Southern Europe. This city is located near the coast line in the North of Portugal, being the country's second largest urban area. Moreover, Oporto city economic prospects depend heavily on a diversified industrial park, which contribute to air quality degradation. Another strong source of air pollution is traffic. The main objectives of this study are: 1) to characterize the chemical composition of PM10 and PM2.5 by setting up an orchestra of aerosol sampling devices in a strategic place in Oporto; 2) to identify the sources of particles exploring parameters such as organic and inorganic markers (e.g. sugars as tracers for biomass burning; metals and elemental carbon for industrial and vehicular emissions); 3) to evaluate long range transport of pollutants using back trajectory analysis. Here we present data obtained between January 2013 and January 2014 in a heavy traffic roadside sampling site located in the city center. Different PM10 and PM2.5 samplers were operated simultaneously in order to collect enough mass on different filter matrixes and to fulfill the requirements of analytical methodologies. More than 100 aerosol samples were collected and then analysed for their mass concentration and

Modelling of PM10 concentration for industrialized area in Malaysia: A case study in Shah Alam

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N, Norazian Mohamed; Abdullah, M. M. A.; Tan, Cheng-yau; Ramli, N. A.; Yahaya, A. S.; Fitri, N. F. M. Y.

In Malaysia, the predominant air pollutants are suspended particulate matter (SPM) and nitrogen dioxide (NO2). This research is on PM10 as they may trigger harm to human health as well as environment. Six distributions, namely Weibull, log-normal, gamma, Rayleigh, Gumbel and Frechet were chosen to model the PM10 observations at the chosen industrial area i.e. Shah Alam. One-year period hourly average data for 2006 and 2007 were used for this research. For parameters estimation, method of maximum likelihood estimation (MLE) was selected. Four performance indicators that are mean absolute error (MAE), root mean squared error (RMSE), coefficient of determination (R2) and prediction accuracy (PA), were applied to determine the goodness-of-fit criteria of the distributions. The best distribution that fits with the PM10 observations in Shah Alamwas found to be log-normal distribution. The probabilities of the exceedences concentration were calculated and the return period for the coming year was predicted from the cumulative density function (cdf) obtained from the best-fit distributions. For the 2006 data, Shah Alam was predicted to exceed 150 μg/m3 for 5.9 days in 2007 with a return period of one occurrence per 62 days. For 2007, the studied area does not exceed the MAAQG of 150 μg/m3

Repeated intratracheal instillation of PM10 induces lipid reshaping in lung parenchyma and in extra-pulmonary tissues.

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Angela Maria Rizzo

Full Text Available Adverse health effects of air pollution attributed mainly to airborne particulate matter have been well documented in the last couple of decades. Short term exposure, referring to a few hours exposure, to high ambient PM10 concentration is linked to increased hospitalization rates for cardiovascular events, typically 24 h after air pollution peaks. Particulate matter exposure is related to pulmonary and cardiovascular diseases, with increased oxidative stress and inflammatory status. Previously, we have demonstrated that repeated intratracheal instillation of PM10sum in BALB/c mice leads to respiratory tract inflammation, creating in lung a condition which could potentially evolve in a systemic toxic reaction. Additionally, plasma membrane and tissue lipids are easily affected by oxidative stress and directly correlated with inflammatory products. With this aim, in the present investigation using the same model, we analyzed the toxic potential of PM10sum exposure on lipid plasma membrane composition, lipid peroxidation and the mechanisms of cells protection in multiple organs such as lung, heart, liver and brain. Obtained results indicated that PM10 exposure led to lung lipid reshaping, in particular phospholipid and cholesterol content increases; concomitantly, the generation of oxidative stress caused lipid peroxidation. In liver we found significant changes in lipid content, mainly due to an increase of phosphatidylcholine, and in total fatty acid composition with a more pronounced level of docosahexaenoic acid; these changes were statistically correlated to lung molecular markers. Heart and brain were similarly affected; heart was significantly enriched in triglycerides in half of the PM10sum treated mice. These results demonstrated a direct involvement of PM10sum in affecting lipid metabolism and oxidative stress in peripheral tissues that might be related to the serious systemic air-pollution effects on human health.

Correlation Analysis of PM10 and the Incidence of Lung Cancer in Nanchang, China.

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Zhou, Yi; Li, Lianshui; Hu, Lei

2017-10-19

Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are used to determine the pollution factors causing lung cancer among residents in Nanchang, China, and identify population segments which are more susceptible to air pollution. This study shows that particulate matter with particle sizes below 10 micron (PM 10 ) is most closely related to the incidence of lung cancer among air pollution factors including annual mean concentrations of SO₂, NO₂, PM 10 , annual haze days, and annual mean Air Pollution Index/Air Quality Index (API/AQI). Air pollution has a greater impact on urban inhabitants as compared to rural inhabitants. When gender differences are considered, women are more likely to develop lung cancer due to air pollution. Smokers are more likely to suffer from lung cancer. These results provide a reference for the government to formulate policies to reduce air pollutant emissions and strengthen anti-smoking measures.

AJUSTE DE CURVAS MEDIANTE MÉTODOS NO PARAMÉTRICOS PARA ESTUDIAR EL COMPORTAMIENTO DE CONTAMINACIÓN DEL AIRE POR MATERIAL PARTICULADO PM10 AJUSTE DE CURVAS MEDIANTE MÉTODOS NÃO PARAMÉTRICOS PARA ESTUDAR O COMPORTAMENTO DE CONTAMINAÇÃO DO AR POR MATERIAL PARTICULADO PM10 CURVE FITTING NONPARAMETRIC METHODS FOR STUDYING BEHAVIOR FROM AIR POLLUTION PM10

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Jhovana Reina

2012-12-01

comportamento do PM10 usando suavizadores kernel e spline. O processamento executa-se com o software estatístico de livre distribuição R. As curvas estimadas permitem observar um comportamento unimodal do PM10 durante as horas da manhã, diferenciado por dias da semana e por dias com chuva e sem chuva. Os modelos permitem caracterizar de maneira robusta o comportamento diário do PM10, tendo em conta observações heterocedásticas baixo um cenário de múltiplas respostas por ponto de desenho.One of the main air pollutants is the particulate matter whose aerodynamic diameter is less than 10 micrometers, usually referred as PM10. It is a fact that the PM10 behavior in the air varies in an irregular way, and also in a temporal way in the atmosphere, mainly due to human activities, to unstable atmospheric conditions, and to meteorological phenomena. Our main purpose is to characterize through a nonparametric smooth model the PM10 daily behavior, taking into account the day of the week, and the precipitation levels. We illustrate the model using records on PM10 contamination, as well as on data on rain precipitation in the north side of Cali, Colombia. We estimate daily typical curves of the PM10 behavior using kernel and spline estimators. We processed these data using the free distribution statistical software R. The estimated curves allow us to observe a PM10 unimodal behavior during the morning hours, which varies from one day to another and from rainy to non-rainy days. The fitted models allow a robust characterization of the PM10 daily behavior, considering heteroscedastic observations on a multiple response per design point scenario.

Assessment of PM10 in Aurangabad City of Central India

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Geetanjali Kaushik

2016-05-01

Full Text Available Almost 670 million people comprising 54.5% of our population reside in regions that do not meet the Indian NAAQS for fine particulate matter. Numerous studies have revealed a consistent correlation for particulate matter concentration with health than any other air pollutant. Aurangabad city a rapidly growing city with population of 1.5 million is home to five major industrial areas, the city is also known for its historical monuments which might also be adversely affected from air pollution. Therefore, this research aims at estimating PM10 concentrations at several locations across Aurangabad. The concentration of PM10 was highest at the Railway Station followed by Waluj (an industrial zone and City chowk is the centre of the city which has high population, tall buildings, few open spaces which causes high congestion and does not allow the particulates to disperse. Other locations with high concentrations of PM are Mill corner, Harsul T-point, Kranti Chowk, Seven Hill, TV centre and Beed Bye pass. All these locations have narrow roads, high traffic density, poor road condition with pot holes and few crossing points which cause congestion and vehicle idling which are responsible for high pollution. Therefore, it is evident that air pollution is a serious issue in the city which may be further aggravated if it is not brought under control. Hence, strategies have to be adopted for combating the menace of air pollution.INTERNATIONAL JOURNAL OF ENVIRONMENTVolume-5, Issue-2, March-May 2016, Page :61-74

Air pollution exposure in Oslo, Drammen, Bergen and Trondheim. Calculations of NO2, PM10 and PM2,5 for the winter 1995 to 1996

International Nuclear Information System (INIS)

Sloerdal, Leif Haavard

1998-07-01

The Norwegian Institute for Air Research (NILU) commissioned by the Norwegian Pollution Control Authority (Statens forurensningstilsyn), has calculated human exposure values to NO 2 , PM 1 0 and PM 2 ,5 in the cities of Oslo, Drammen, Bergen and Trondheim. In Oslo, Drammen and Bergen the calculations are made for the winter 1995 to 1996. For Trondheim the necessary meteorological data were missing and the calculations are therefore made for the winter of 1994 to 1995. In the project only simplified exposure calculations are carried out where estimated ground concentrations and population distribution information at the km 2 level are connected. The calculations are then made as if everyone have been outside at the home address during the entire estimation period, termed ''potential exposure''. The population exposure load is estimated for excesses of various air quality criteria and the results are presented. In addition values for the worst hour and/or the worst day of exposure for each of the four cities are presented. The term worst is defined as the hour or the day in the simulation period where the most number of people are exposed to concentrations exceeding the threshold values for air quality recommended by the Norwegian Pollution Control Authority. For NO 2 these threshold figures are 100 microgram/m 3 for hour values and 75 microgram/m 3 for day values. For PM 1 0 and PM 2 ,5 criteria for hour values do not exist while day values are now stipulated as 35 microgram/m 3 for PM 1 0 and 20 microgram/m 3 for PM 2 ,5. The calculated maximum concentrations may not coincide with these values. The report gives results for exposure estimates for NO 2 , PM 1 0 and PM 2 ,5 in the cities and evaluates the significance of regional background levels, traffic and heating emissions in contributions to the total population exposure load. The exposure to NO 2 is largest in Bergen. The PM 1 0 and PM 2 ,5 i.e. particle exposure, is greater than for NO 2 and is largest in Oslo

Synoptic weather types and aeroallergens modify the effect of air pollution on hospitalisations for asthma hospitalisations in Canadian cities

International Nuclear Information System (INIS)

Hebbern, Christopher; Cakmak, Sabit

2015-01-01

Pollution levels and the effect of air pollution on human health can be modified by synoptic weather type and aeroallergens. We investigated the effect modification of aeroallergens on the association between CO, O 3 , NO 2 , SO 2 , PM 10 , PM 2.5 and asthma hospitalisation rates in seven synoptic weather types. We developed single air pollutant models, adjusted for the effect of aeroallergens and stratified by synoptic weather type, and pooled relative risk estimates for asthma hospitalisation in ten Canadian cities. Aeroallergens significantly modified the relative risk in 19 pollutant-weather type combinations, reducing the size and variance for each single pollutant model. However, aeroallergens did not significantly modify relative risk for any pollutant in the DT or MT weather types, or for PM 10 in any weather type. Thus, there is a modifying effect of aeroallergens on the association between CO, O 3 , NO 2 , SO 2 , PM 2.5 and asthma hospitalisations that differs under specific synoptic weather types. - Highlights: • We model effect modification of aeroallergens on air pollutant–asthma association. • The air pollutant association was modelled in seven synoptic weather types. • Aeroallergens modify CO, O 3 , NO 2 , SO 2 , and PM 2.5 effect on asthma hospitalisations. • Synoptic weather types modify the air pollutant and asthma association. - We identify a modifying effect of aeroallergens on the relationship between air pollutants and hospitalisation rates for asthma, that differs under specific synoptic weather types

An integrated approach to identify the origin of PM10 exceedances.

Science.gov (United States)

Amodio, M; Andriani, E; de Gennaro, G; Demarinis Loiotile, A; Di Gilio, A; Placentino, M C

2012-09-01

This study was aimed to the development of an integrated approach for the characterization of particulate matter (PM) pollution events in the South of Italy. PM(10) and PM(2.5) daily samples were collected from June to November 2008 at an urban background site located in Bari (Puglia Region, South of Italy). Meteorological data, particle size distributions and atmospheric dispersion conditions were also monitored in order to provide information concerning the different features of PM sources. The collected data allowed suggesting four indicators to characterize different PM(10) exceedances. PM(2.5)/PM(10) ratio, natural radioactivity, aerosol maps and back-trajectory analysis and particle distributions were considered in order to evaluate the contribution of local anthropogenic sources and to determine the different origins of intrusive air mass coming from long-range transport, such as African dust outbreaks and aerosol particles from Central and Eastern Europe. The obtained results were confirmed by applying principal component analysis to the number particle concentration dataset and by the chemical characterization of the samples (PM(10) and PM(2.5)). The integrated approach for PM study suggested in this paper can be useful to support the air quality managers for the development of cost-effective control strategies and the application of more suitable risk management approaches.

Co-Mitigation of Ozone and PM2.5 Pollution over the Beijing-Tianjin-Hebei Region

Science.gov (United States)

Liu, J.; Xiang, S.; Yi, K.; Tao, W.

2017-12-01

With the rapid industrialization and urbanization, emissions of air pollutants in China were increasing rapidly during the past few decades, causing severe particulate matter and ozone pollution in many megacities. Facing these knotty environmental problems, China has released a series of pollution control policies to mitigate air pollution emissions and optimize energy supplement structure. Consequently, fine particulate matters (PM2.5) decrease recently. However, the concentrations of ambient ozone have been increasing, especially during summer time and over megacities. In this study, we focus on the opposite trends of ozone and PM2.5 over the Beijing-Tianjin-Hebei region. We use the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem) to simulate and analyze the best emission reduction strategies, and adopt the Empirical Kinetics Modeling Approach (EKMA) to depict the influences of mitigating NOx and VOCs. We also incorporate the abatement costs for NOx and VOCs in our analysis to explore the most cost-effective mitigation strategies for both ozone and PM2.5.

Potential Sources and Formations of the PM2.5 Pollution in Urban Hangzhou

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Jian Wu

2016-07-01

Full Text Available Continuous measurements of meteorological parameters, gaseous pollutants, particulate matters, and the major chemical species in PM2.5 were conducted in urban Hangzhou from 1 September to 30 November 2013 to study the potential sources and formations of PM2.5 pollution. The average PM2.5 concentration was 69 µg·m−3, ~97% higher than the annual concentration limit in the national ambient air quality standards (NAAQS of China. Relative humidity (RH and wind speed (WS were two important factors responsible for the increase of PM2.5 concentration, with the highest value observed under RH of 70%–90%. PM2.5 was in good correlation with both NO2 and CO, but not with SO2, and the potential source contribution function (PSCF results displayed that local emissions were important potential sources contributing to the elevated PM2.5 and NO2 in Hangzhou. Thus, local vehicle emission was suggested as a major contribution to the PM2.5 pollution. Concentrations of NO2 and CO significantly increased in pollution episodes, while the SO2 concentration even decreased, implying local emission rather than region transport was the major source contributing to the formation of pollution episodes. The sum of SO42−, NO3−, and NH4+ accounted for ~50% of PM2.5 in mass in pollution episodes and the NO3−/EC ratios were significantly elevated, revealing that the formation of secondary inorganic species, particularly NO3−, was an important contributor to the PM2.5 pollution in Hangzhou. This study highlights that controlling local pollution emissions was essential to reduce the PM2.5 pollution in Hangzhou, and the control of vehicle emission in particular should be further promoted in the future.

Evolution de la surveillance des PM10 en France : épisodes de pollution par les particules au printemps 2007

OpenAIRE

Aymoz , Gilles; Bessagnet , Bertrand; Rouil , Laurence; Le Bihan , Olivier

2008-01-01

National audience; Since the 1st January 2007, PM10 monitoring network in France has evolved, in order to account for volatile fraction of PM10. This evolution permitted the observation of high peaks of PM10 during spring 2007. Concentrations during these peaks would have been largely underestimated with measuring techniques used before 2007. A study, coupling chemical and modelling approach of the phenomenon has been launched by LCSQA (Laboratoire Central de Surveillance de la Qualité de l'A...

Monitoring of PM10 and PM2.5 around primary particulate anthropogenic emission sources

Science.gov (United States)

Querol, Xavier; Alastuey, Andrés; Rodriguez, Sergio; Plana, Felicià; Mantilla, Enrique; Ruiz, Carmen R.

Investigations on the monitoring of ambient air levels of atmospheric particulates were developed around a large source of primary anthropogenic particulate emissions: the industrial ceramic area in the province of Castelló (Eastern Spain). Although these primary particulate emissions have a coarse grain-size distribution, the atmospheric transport dominated by the breeze circulation accounts for a grain-size segregation, which results in ambient air particles occurring mainly in the 2.5-10 μm range. The chemical composition of the ceramic particulate emissions is very similar to the crustal end-member but the use of high Al, Ti and Fe as tracer elements as well as a peculiar grain-size distribution in the insoluble major phases allow us to identify the ceramic input in the bulk particulate matter. PM2.5 instead of PM10 monitoring may avoid the interference of crustal particles without a major reduction in the secondary anthropogenic load, with the exception of nitrate. However, a methodology based in PM2.5 measurement alone is not adequate for monitoring the impact of primary particulate emissions (such as ceramic emissions) on air quality, since the major ambient air particles derived from these emissions are mainly in the range of 2.5-10 μm. Consequently, in areas characterised by major secondary particulate emissions, PM2.5 monitoring should detect anthropogenic particulate pollutants without crustal particulate interference, whereas PM10 measurements should be used in areas with major primary anthropogenic particulate emissions.

Geographic variation in Chinese children' forced vital capacity and its association with long-term exposure to local PM10: a national cross-sectional study.

Science.gov (United States)

Wang, Hai-Jun; Li, Qin; Guo, Yuming; Song, Jie-Yun; Wang, Zhiqiang; Ma, Jun

2017-10-01

The purpose of this study was to estimate the association between Chinese children's forced vital capacity (FVC) and particulate matter with aerodynamic diameter ≤10 μm (PM 10 ). The FVC data of 71,763 children aged 7 to 18 was collected from 2010 Chinese National Survey on Students' Construction and Health (CNSSCH). The local annual average concentration of PM 10 , relative humidity, ambient temperature, and other air pollutant data of 30 cities was collected from China Meteorological Administration and Ministry of Environment Protection of China. Then, we used generalized additive model (GAM) to estimate the association between children's FVC and PM 10 . The obvious geographic variation in FVC was found in children of 30 Chinese cities ranging from 1647 ml in Xining to 2571 ml in Beijing. The annual average concentration of PM 10 was also different, ranging from 40 μg/m 3 in Haikou to 155 μg/m 3 in Lanzhou. After adjusted individual characteristics, socioeconomic conditions, ambient temperature, relative humidity, and other air pollutants (e.g., NO 2 and SO 2 ) in the generalized additive model, we found that the increase of PM 10 was associated with decrease of FVC in Chinese children. A 10-μg/m 3 increase of PM 10 was associated with 1.33-ml decrease in FVC (95% confidence interval: -2.18 to -0.47). We also found a larger effect estimate of PM 10 on FVC in boys than that in girls. Consistent associations were found in both physically inactive and active children. The increase of PM 10 was associated with decrease of children's FVC. We should develop proper public health policy to protect children's respiratory health during growth and development in polluted areas.

A modeling analysis of a heavy air pollution episode occurred in Beijing

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X. An

2007-06-01

Full Text Available The concentrations of fine particulate matter (PM and ozone in Beijing often exceed healthful levels in recent years, therefore China is to taking steps to improve Beijing's air quality for the 2008 Olympic Games. In this paper, the Models-3 Community Multiscale Air Quality (CMAQ Modeling System was used to investigate a heavy air pollution episode in Beijing during 3–7 April 2005 to obtain the basic information of how heavy air pollution formed and the contributions of local sources and surround emissions. The modeling domain covered from East Asia with four nested grids with 81 to 3 km horizontal resolution focusing on urban Beijing. This was coupled with a regional emissions inventory with a 10 km resolution and a local 1 km Beijing emissions database. The trend of predicted concentrations of various pollutants agreed reasonably well with the observations and captured the main features of this heavy pollution episode. The simulated column concentration distribution of PM was correlated well with the MODIS remote sensing products. Control runs with and without Beijing emissions were conducted to quantify the contributions of non-Beijing sources (NBS to the Beijing local air pollution. The contributions of NBS to each species differed spatially and temporally with the order of PM_2.5>PM₁₀>SO₂> soil for this episode. The percentage contribution of NBS to fine particle (PM_2.5 in Beijing was averaged about 39%, up to 53% at the northwest of urban Beijing and only 15% at southwest. The spatial distribution of NBS contributions for PM₁₀ was similar to that for PM_2.5, with a slightly less average percentage of about 30%. The average NBS contributions for SO₂ and soil (diameter between 2.5 μm and 10 μm were 18% and 10%. In addition, the pollutant transport flux was calculated and compared at different levels to investigate transport pathway and magnitude. It was found

[The effect of ambient PM(10) on sperm quality in Wuhan].

Science.gov (United States)

Wang, X C; Tian, X J; Ye, B; Ma, L; Zhang, Y; Yang, J

2018-01-06

Objective: To investigate the effect of exposure to particulate matter ≤10 μm in aerodynamic diameter (PM(10)) on sperm quality in different stages of sperm development. Methods: This cross-sectional study included 1 827 patients attending the reproductive medicine center in Renmin Hospital of Wuhan University during April 2013 to January 2015. Air pollution data from January 2013 to January 2015 was obtained from the database of Wuhan Municipal Environmental Protection Bureau. The generalized linear model was employed to assess the association between each exposure variables and sperm parameters for several exposure windows (0-9, 10-14, 15-69, 70-90, 0-90 days before sampling) . Results: The average levels of PM(10) was (116.2±71.6) μg/m(3) during the research period. Sperm volume was (75.4±49.1) ×10(6)/ml in sample population, (29.4±16.2) % in progressive motility and (51.8±21.6) % in total motility. Exposure to PM(10) was inversely associated with sperm concentration (β:-0.319; 95% CI: -0.529,-0.046) during 70-90 lag days. PM(10) exposure during the 0-90 lag days was significantly associated with progressive motility (β:-0.312; 95% CI: -0.527,-0.097) and total motility (β:-0.347; 95% CI: -0.636,-0.059) after adjusted for age, education level, BMI, smoking, abstinence time, temperature, humidity and season. Conclusion: Exposure to PM(10) was associated with statistically significant decrements in sperm concentration and motility, and the adverse impact on sperm concentration was significantly in early phases of spermatogenesis.

Temporal variations and spatial distribution of ambient PM{sub 2.2} and PM{sub 10} concentrations in Dhaka, Bangladesh

Energy Technology Data Exchange (ETDEWEB)

Begum, Bilkis A.; Biswas, Swapan K. [Chemistry Division, Atomic Energy Centre, P.O. Box-164, Dhaka (Bangladesh); Hopke, Philip K. [Department of Chemical Engineering, Clarkson University, Potsdam, NY 13699-5810 (United States)

2006-04-01

Concentrations and characteristics of airborne particulate matter (PM{sub 10}, PM{sub 2.2} and BC) on air quality have been studied at two air quality-monitoring stations in Dhaka, the capital of Bangladesh. One site is at the Farm Gate area, a hot spot with very high pollutant concentrations because of its proximity to major roadways. The other site is at a semi-residential area located at the Atomic Energy Centre, Dhaka Campus, (AECD) with relatively less traffic. The samples were collected using a 'Gent' stacked filter unit in two fractions of 0-2.2 {mu}m and 2.2-10 {mu}m sizes. Samples of fine (PM{sub 2.2}) and coarse (PM{sub 2.2-10}) airborne particulate matter fractions collected from 2000 to 2003 were studied. It has been observed that fine particulate matter has a decreasing trend, from prior year measurements, because of Government policy interventions like phase-wise plans to take two-stroke three-wheelers off the roads in Dhaka and finally banned from January 1, 2003. Other policy interventions were banning of old buses and trucks to ply on Dhaka city promotion of the using compressed natural gas (CNG), introducing air pollution control devices in vehicles, etc. It was found that both local (mostly from vehicular emissions) and possibly some regional emission sources are responsible for high PM{sub 2.2} and BC concentrations in Dhaka. PM{sub 2.2}, PM{sub 2.2-10} and black carbon concentration levels depend on the season, wind direction and wind speed. Transport related emissions are the major source of BC and long-range transportation from fossil fuel related sources and biomass burning could be another substantial source of BC. (author)

The use of total susceptibility in the analysis of long term PM10 (PM2.5) collected at Hungarian air quality monitoring stations

Science.gov (United States)

Márton, Emö; Domján, Ádám; Lautner, Péter; Szentmarjay, Tibor; Uram, János

2013-04-01

Air monitoring stations in Hungary are operated by Environmental, Nature Conservancy and Water Pollution Inspectorates, according to the CEN/TC 264 European Union standards. PM10 samples are collected on a 24-hour basis, for two weeks in February, in May, in August and in November. About 720m3 air is pumped through quartz filters daily. Mass measurements and toxic metal analysis (As, Pb, Cd, Ni) are made on each filter (Whatmann DHA-80 PAH, 150 mm diameter) by the inspectorates. We have carried out low field magnetic susceptibility measurements using a KLY-2 instrument on all PM10 samples collected at 9 stations from 2009 on (a total of more than 2000 filters). One station, located far from direct sources, monitors background pollution. Here PM2.5 was also collected in two-week runs, seven times during the period of 2009-2012 and made available for the non-destructive magnetic susceptibility measurements. Due to the rather weak magnetic signal, the susceptibility of each PM-10 sample was computed from 10, that of each PM2.5 sample from 20 measurements. Corrections were made for the susceptibility of the sample holder, for the unpolluted filter (provided with each of the two-week runs), and for the plastic bag containing the samples. The susceptibilities of the PM10 samples were analyzed from different aspects, like the degree of magnetic pollution at different stations, daily and seasonal variations of the total and mass susceptibilities compared to the mass of the pollutants and in relation to the concentrations of the toxic elements. As expected, the lowest total and mass susceptibilities characterize the background station (pollution arrives mostly from distant sources, Vienna, Bratislava or even the Sudeten), while the highest values were measured for an industrial town with heavy traffic. At the background station the mass of the PM10 and PM2.5, respectively for the same period are quite similar, while the magnetic susceptibilities are usually higher in the

Modeling spatial effects of PM{sub 2.5} on term low birth weight in Los Angeles County

Energy Technology Data Exchange (ETDEWEB)

Coker, Eric, E-mail: cokerer@onid.orst.edu [College of Public Health and Human Sciences, Oregon State University, Corvallis, OR (United States); Ghosh, Jokay [School of Public Health, University of California, Los Angeles, Los Angeles, CA (United States); Jerrett, Michael [School of Public Health, University of California, Berkeley, Berkeley, CA (United States); Gomez-Rubio, Virgilio [Department of Mathematics, Universidad De Castilla-La Mancha, Albacete (Spain); Beckerman, Bernardo [School of Public Health, University of California, Berkeley, Berkeley, CA (United States); Cockburn, Myles [Preventive Medicine and Spatial Sciences, University of Southern California, Los Angeles, CA (United States); Liverani, Silvia [Department of Mathematics, Brunel University, London (United Kingdom); Su, Jason [School of Public Health, University of California, Berkeley, Berkeley, CA (United States); Li, Arthur [Department of Information Science, City of Hope National Cancer Center, Duarte, CA (United States); Kile, Molly L [College of Public Health and Human Sciences, Oregon State University, Corvallis, OR (United States); Ritz, Beate [School of Public Health, University of California, Los Angeles, Los Angeles, CA (United States); Molitor, John [College of Public Health and Human Sciences, Oregon State University, Corvallis, OR (United States)

2015-10-15

Air pollution epidemiological studies suggest that elevated exposure to fine particulate matter (PM{sub 2.5}) is associated with higher prevalence of term low birth weight (TLBW). Previous studies have generally assumed the exposure–response of PM{sub 2.5} on TLBW to be the same throughout a large geographical area. Health effects related to PM{sub 2.5} exposures, however, may not be uniformly distributed spatially, creating a need for studies that explicitly investigate the spatial distribution of the exposure–response relationship between individual-level exposure to PM{sub 2.5} and TLBW. Here, we examine the overall and spatially varying exposure–response relationship between PM{sub 2.5} and TLBW throughout urban Los Angeles (LA) County, California. We estimated PM{sub 2.5} from a combination of land use regression (LUR), aerosol optical depth from remote sensing, and atmospheric modeling techniques. Exposures were assigned to LA County individual pregnancies identified from electronic birth certificates between the years 1995-2006 (N=1,359,284) provided by the California Department of Public Health. We used a single pollutant multivariate logistic regression model, with multilevel spatially structured and unstructured random effects set in a Bayesian framework to estimate global and spatially varying pollutant effects on TLBW at the census tract level. Overall, increased PM{sub 2.5} level was associated with higher prevalence of TLBW county-wide. The spatial random effects model, however, demonstrated that the exposure–response for PM{sub 2.5} and TLBW was not uniform across urban LA County. Rather, the magnitude and certainty of the exposure–response estimates for PM{sub 2.5} on log odds of TLBW were greatest in the urban core of Central and Southern LA County census tracts. These results suggest that the effects may be spatially patterned, and that simply estimating global pollutant effects obscures disparities suggested by spatial patterns of

Fugitive emission rates assessment of PM2.5 and PM10 from open storage piles in China

Science.gov (United States)

Cao, Yiqi; Liu, Tao; He, Jiao

2018-03-01

An assessment of the fugitive emission rates of PM2.5 and PM10 from an open static coal and mine storage piles. The experiment was conducted at a large union steel enterprises in the East China region to effectively control the fugitive particulate emissions pollution on daily work and extreme weather conditions. Wind tunnel experiments conducted on the surface of static storage piles, and it generated specific fugitive emission rates (SERs) at ground level of between ca.10-1 and ca.102 (mg/m2·s) for PM2.5 and between ca.101 and ca.103 (mg/m2·s) for PM10 under the u*(wind velocity) between ca.3.0 (m/s) and 10.0 (m/s). Research results show that SERs of different materials differ a lot. Material particulate that has lower surface moisture content generate higher SER and coal material generate higher SER than mine material. For material storage piles with good water infiltrating properties, aspersion is a very effective measure for control fugitive particulate emission.

KANDUNGAN TSP DAN PM-10 DI UDARA JAKARTA DAN SEKITARNYA

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Hendro Martono

2016-09-01

Full Text Available Abstract. A survey was performed to assess the quality of ambient air in Jakarta, Bogor,Depok,  Tangerang  and Bekasi.  Ambient air samples were collected from 33 sampling points at a distance of 0meter and 120 meters from each main roads respectively. The highest average content of TSP in ambientair at 0 meter was found in West Jakarta (652.02 p.g/cu.m and that of 120 meters from the main road was in Bekasi (445.46µg/cu.m . The highest difference of the TSP content between the two sampling pointswas in Kebon  Jeruk, West Jakarta (96.62 %,  and the lowest one was inCikarang, Bekasi (1.63 %.  Furthermore, the highest difference of the PM-10 content between the two sampling points was inJalan  Raya Bogor, Depok  (96.86 %,  and the lowest one was in Cikarang,  Bekasi (17.26%. In the whole areasof study, the average content of TSP  was 522.44.tg/cu.m  (0 meter, and178.09µg/cu.m (120 meters,  so the difference of the pollutant content between the two sampling points was 65.91%. Meanwhile, theaverage content of PM-10 was 326.25µg/cu.m  (0 meter, and97.09µg/cu.m (120 meters, so the difference of the pollutant content between the two sampling points was 70.24 %. The difference of the means ofboth TSP  and PM-10 content levels between the two sampling sites were significant. The percentages ofsampling points complying withTSP level standard were 9.52 %  (0 meter and 75.76% (120 meters from the road sides. While that of PM-10 were 18.18%  (road side sampling and 78.79% (120 meters from theroad sides.Crusial  measure for controlling theTSP  and PM-10 pollution should also be addressed tomobile sources, such as reducing diesel motorized-vehicles and providing proper mass transportation.

Correlation Analysis of PM10 and the Incidence of Lung Cancer in Nanchang, China

Science.gov (United States)

Zhou, Yi; Li, Lianshui; Hu, Lei

2017-01-01

Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are used to determine the pollution factors causing lung cancer among residents in Nanchang, China, and identify population segments which are more susceptible to air pollution. This study shows that particulate matter with particle sizes below 10 micron (PM10) is most closely related to the incidence of lung cancer among air pollution factors including annual mean concentrations of SO2, NO2, PM10, annual haze days, and annual mean Air Pollution Index/Air Quality Index (API/AQI). Air pollution has a greater impact on urban inhabitants as compared to rural inhabitants. When gender differences are considered, women are more likely to develop lung cancer due to air pollution. Smokers are more likely to suffer from lung cancer. These results provide a reference for the government to formulate policies to reduce air pollutant emissions and strengthen anti-smoking measures. PMID:29048397

Correlation Analysis of PM10 and the Incidence of Lung Cancer in Nanchang, China

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Yi Zhou

2017-10-01

Full Text Available Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are used to determine the pollution factors causing lung cancer among residents in Nanchang, China, and identify population segments which are more susceptible to air pollution. This study shows that particulate matter with particle sizes below 10 micron (PM10 is most closely related to the incidence of lung cancer among air pollution factors including annual mean concentrations of SO2, NO2, PM10, annual haze days, and annual mean Air Pollution Index/Air Quality Index (API/AQI. Air pollution has a greater impact on urban inhabitants as compared to rural inhabitants. When gender differences are considered, women are more likely to develop lung cancer due to air pollution. Smokers are more likely to suffer from lung cancer. These results provide a reference for the government to formulate policies to reduce air pollutant emissions and strengthen anti-smoking measures.

Effect of Exposure to PM10 on Cardiovascular Diseases Hospitalizations in Ahvaz, Khorramabad and Ilam, Iran During 2014

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Seyed Mohammad Daryanoosh

2016-01-01

Full Text Available Particulate matter with an aerodynamic diameter less than or equal to 10μm (PM10 has the great adverse endpoints on human health. The aim of this study was to assess the hospital admissions (HA due to cardiovascular diseases (CVD attributed to PM10 among people living in the cities of Ahvaz, Khorramabad and Ilam, during 2014. In this study, Air Quality Health Impact Assessment (AirQ2.2.3 software proposed by the World Health Organization (WHO to assess of health impacts of atmospheric pollutants was used. To evaluate human exposure and health outcome of PM10, 24-hour data was taken from the Departments of Environment of Ahvaz, Khorramabad and Ilam. We acquired an input file for the software from raw data and quantified PM10 by the AirQ2.2.3 model. The annual averages in three study areas illustrated that PM10 concentration in Ahvaz and Ilam with values of 534.77 and 60.45μg/m3, were the highest and lowest in 2014, respectively. The number of excess cases for HA due to CVD in Ahvaz, Khorramabad, and Ilam was estimated 508, 144 and 66 persons, respectively. The most percentage of person-days was attributable to the concentration interval of 130-139µg/m3 of PM10, whereas this was for Khorramabad and Ilam 60-69 and 40-49µg/m3, respectively. The comparison of PM10 concentrations with NAAQS standard was revealed the annual average of particulate matter concentrations in Ahvaz was higher than standard. Therefore, the efforts should be conducted in the governmental scale to prevent pollution and reduce PM10 emission from various sources, such as transport and industries and also control dust entering the country by spreading mulch and development of green space.

Elemental characterization of New Year's Day PM10 and PM2.2 particulates matter at several sites in Metro Manila

International Nuclear Information System (INIS)

Santos, Flora L.; Pabroa, Preciosa Corazon B.; Morco, Ryan P.; Racho, Joseph Michael D.

2007-01-01

In the Philippines, it has been a yearly tradition to welcome the coming of the New Year with the loudest noise as can be achieved. Firecrackers and fireworks have been a necessity for Filipinos during this time despite bans on the use of most of these and despite the Department of Health (DOH) campaign to use alternative safe practices to welcome the New Year. Data for PM 10 samples (fractionated as PM 10-2.2 or the course fraction and PM2.2 or the fine fraction) collected in four PNRI sampling sites in Metro Manila show the air pollution impacts of fireworks on New Year's Eve. Samples were collected from 1998 to 2006 using a Gent dichotomous sampler in connection with the PNRI project P articulate Matter Source Apportionment Using Nuclear and Related Analytical Techniques . Particulate mass was determined by gravimetry. Elemental analysis of the air filters was done using X-ray Fluorescence Spectrometry (X RF) or Particle induced X-ray Emission (PIXE), multielemental non-destructive nuclear analytical techniques. Black carbon was analyzed using reflectometry. PM 10 values increased by two to four times the usual averages (36.4 to 55.4 ug/cum) and in 2002 even exceeded the PNAAQ short-term guideline value of 150 ug/cum at the ADMU sampling station. PM2.2 values increased by two to six times the usual averages (15 to 28 ug/cum), even many times exceeding US EPA short-term guideline value of 65 ug/cum. The increase in the particulate mass of New Year's Day samples can be attributed more to an increase in the metal pollutants rather than the black carbon, with higher contribution to the fine fraction. Increase in the elemental concentrations of Al, S, Cl, K, Ba, Sr, Ti, V, Mn, Cu and Pb were observed with the highest contribution from K. Results show that the usual practices of burning firecrackers and fireworks during New Year's day celebration is a very strong source of air pollution which contributes significantly high amount of metal pollutants in the air

A Computational Fluid Dynamic (CFD) Simulation of PM10 Dispersion Caused by Rail Transit Construction Activity: A Real Urban Street Canyon Model

Science.gov (United States)

Wang, Yang; Zhou, Ying; Zuo, Jian

2018-01-01

Particle emissions derived from construction activities have a significant impact on the local air quality, while the canyon effect with reduced natural ventilation contributes to the highest particulate pollution in urban environments. This study attempted to examine the effect of PM10 emissions derived from the construction of a rail transit system in an urban street canyon. Using a 3D computational fluid dynamic (CFD) model based on a real street canyon with different height ratios, this study formulates the impact of height ratio and wind directions on the dispersion and concentration of PM10. The results indicate that parallel flow would cause the concentration of PM10 at the end of the street canyons in all height ratios, and the trends in horizontal, vertical and lateral planes in all street canyons are similar. While in the condition of perpendicular flow, double-eddy circulations occur and lead to the concentration of PM10 in the middle part of the street canyon and leeward of backwind buildings in all height ratios. Furthermore, perpendicular flow will cause the concentration of PM10 to increase if the upwind buildings are higher than the backwind ones. This study also shows that the dispersion of PM10 is strongly associated with wind direction in and the height ratios of the street canyons. Certain measures could, therefore, be taken to prevent the impact on people in terms of the PM10 concentration and the heights of street canyons identified in this research. Potential mitigation strategies are suggested, include measurements below 4 m according to governmental regulations, dust shields, and atomized water. PMID:29522495

A Computational Fluid Dynamic (CFD) Simulation of PM10 Dispersion Caused by Rail Transit Construction Activity: A Real Urban Street Canyon Model.

Science.gov (United States)

Wang, Yang; Zhou, Ying; Zuo, Jian; Rameezdeen, Raufdeen

2018-03-09

Particle emissions derived from construction activities have a significant impact on the local air quality, while the canyon effect with reduced natural ventilation contributes to the highest particulate pollution in urban environments. This study attempted to examine the effect of PM 10 emissions derived from the construction of a rail transit system in an urban street canyon. Using a 3D computational fluid dynamic (CFD) model based on a real street canyon with different height ratios, this study formulates the impact of height ratio and wind directions on the dispersion and concentration of PM 10 . The results indicate that parallel flow would cause the concentration of PM 10 at the end of the street canyons in all height ratios, and the trends in horizontal, vertical and lateral planes in all street canyons are similar. While in the condition of perpendicular flow, double-eddy circulations occur and lead to the concentration of PM 10 in the middle part of the street canyon and leeward of backwind buildings in all height ratios. Furthermore, perpendicular flow will cause the concentration of PM 10 to increase if the upwind buildings are higher than the backwind ones. This study also shows that the dispersion of PM 10 is strongly associated with wind direction in and the height ratios of the street canyons. Certain measures could, therefore, be taken to prevent the impact on people in terms of the PM 10 concentration and the heights of street canyons identified in this research. Potential mitigation strategies are suggested, include measurements below 4 m according to governmental regulations, dust shields, and atomized water.

A Computational Fluid Dynamic (CFD Simulation of PM10 Dispersion Caused by Rail Transit Construction Activity: A Real Urban Street Canyon Model

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Yang Wang

2018-03-01

Full Text Available Particle emissions derived from construction activities have a significant impact on the local air quality, while the canyon effect with reduced natural ventilation contributes to the highest particulate pollution in urban environments. This study attempted to examine the effect of PM10 emissions derived from the construction of a rail transit system in an urban street canyon. Using a 3D computational fluid dynamic (CFD model based on a real street canyon with different height ratios, this study formulates the impact of height ratio and wind directions on the dispersion and concentration of PM10. The results indicate that parallel flow would cause the concentration of PM10 at the end of the street canyons in all height ratios, and the trends in horizontal, vertical and lateral planes in all street canyons are similar. While in the condition of perpendicular flow, double-eddy circulations occur and lead to the concentration of PM10 in the middle part of the street canyon and leeward of backwind buildings in all height ratios. Furthermore, perpendicular flow will cause the concentration of PM10 to increase if the upwind buildings are higher than the backwind ones. This study also shows that the dispersion of PM10 is strongly associated with wind direction in and the height ratios of the street canyons. Certain measures could, therefore, be taken to prevent the impact on people in terms of the PM10 concentration and the heights of street canyons identified in this research. Potential mitigation strategies are suggested, include measurements below 4 m according to governmental regulations, dust shields, and atomized water.

Composition and sources of particles in Mannerheimintie during exceedance days of PM{sub 10} limit value in 2010; Hiukkasten koostumus ja laehteet Mannerheimintiellae PM{sub 10}-raja-arvon ylityspaeivinae 2010

Energy Technology Data Exchange (ETDEWEB)

Kupiainen, K.; Niemi, J.; Ritola, R.; Stojiljkovic, A.

2012-02-15

The purpose of the work was to determine sources of respirable particles (PM{sub 10}) in the center of Helsinki, at the measurement station in Mannerheimintie traffic site, in 2010 during the days when the daily average concentration of PM{sub 10} exceeded 50 mug/m3. By the end of the year (2010) the number of this kind of days was 24. The allowed number of exceedance days per year is 35, so the limit value was not exceeded in 2010. Similar work has been carried out in 2008 and 2009 and this report also summarizes results from all three years. HSY is responsible for monitoring the air quality in the Helsinki metropolitan area. The PM{sub 10} monitoring data in combination with electron microscopy based single particle compositional analysis and receptor modeling was used to evaluate dust source contributions on the exceedance days at HSY's air quality monitoring station in Mannerheimintie. According to the study the most significant source of PM{sub 10} particles in Mannerheimintie in 2010 was the dust sources related to traction control (winter-sanding and -salting of streets, pavement wear by studded tyres). Results from 2008 and 2009 show similar tendency. Also dust from construction sites contribute to airborne particle concentrations, timing of this source varies depending on the year. In 2010 particles from construction sites contributed to the exceedances that took place in late spring and early summer. Long-range transboundary air pollution also caused high concentrations of particles and contributed to some of the exceedances in 2008-2010. In late July and early August in 2010, long-range transboundary particles from the forest fires in Russia caused high particle concentrations in Helsinki metropolitan area and elsewhere in Southern Finland. Based on the results, the most significant means to reduce the airborne concentrations and to prevent the exceedance of the limit value are those that aim at mitigating street dust. In Helsinki, the means to

Determinants of perceived air pollution annoyance and association between annoyance scores and air pollution (PM 2.5, NO 2) concentrations in the European EXPOLIS study

Science.gov (United States)

Rotko, Tuulia; Oglesby, Lucy; Künzli, Nino; Carrer, Paolo; Nieuwenhuijsen, Mark J.; Jantunen, Matti

Apart from its traditionally considered objective impacts on health, air pollution can also have perceived effects, such as annoyance. The psychological effects of air pollution may often be more important to well-being than the biophysical effects. Health effects of perceived annoyance from air pollution are so far unknown. More knowledge of air pollution annoyance levels, determinants and also associations with different air pollution components is needed. In the European air pollution exposure study, EXPOLIS, the air pollution annoyance as perceived at home, workplace and in traffic were surveyed among other study objectives. Overall 1736 randomly drawn 25-55-yr-old subjects participated in six cities (Athens, Basel, Milan, Oxford, Prague and Helsinki). Levels and predictors of individual perceived annoyances from air pollution were assessed. Instead of the usual air pollution concentrations at fixed monitoring sites, this paper compares the measured microenvironment concentrations and personal exposures of PM 2.5 and NO 2 to the perceived annoyance levels. A considerable proportion of the adults surveyed was annoyed by air pollution. Female gender, self-reported respiratory symptoms, downtown living and self-reported sensitivity to air pollution were directly associated with high air pollution annoyance score while in traffic, but smoking status, age or education level were not significantly associated. Population level annoyance averages correlated with the city average exposure levels of PM 2.5 and NO 2. A high correlation was observed between the personal 48-h PM 2.5 exposure and perceived annoyance at home as well as between the mean annoyance at work and both the average work indoor PM 2.5 and the personal work time PM 2.5 exposure. With the other significant determinants (gender, city code, home location) and home outdoor levels the model explained 14% (PM 2.5) and 19% (NO 2) of the variation in perceived air pollution annoyance in traffic. Compared to

Update on the development of cotton gin PM10 emission factors for EPA's AP-42

Science.gov (United States)

A cotton ginning industry-supported project was initiated in 2008 to update the U.S. Environmental Protection Agency’s (EPA) Compilation of Air Pollution Emission Factors (AP-42) to include PM10 emission factors. This study develops emission factors from the PM10 emission factor data collected from ...

Modeled PM2.5 removal by trees in ten US cities and associated health effects

Science.gov (United States)

David J. Nowak; Satoshi Hirabayashi; Allison Bodine; Robert. Hoehn

2013-01-01

Urban particulate air pollution is a serious health issue. Trees within cities can remove fine particles from the atmosphere and consequently improve air quality and human health. Tree effects on PM2.5 concentrations and human health are modeled for 10 U.S. cities. The total amount of PM2.5 removed annually by...

Assessment of PM10 enhancement by yellow sand on the air quality of Taipei, Taiwan in 2001.

Science.gov (United States)

Chang, Shuenn-Chin; Lee, Chung-Te

2007-09-01

The impact of long-range transport of yellow sand from Asian Continent to the Taipei Metropolitan Area (Taipei) not only deteriorates air quality but also poses health risks to all, especially the children and the elderly. As such, it is important to assess the enhancement of PM(10) during yellow sand periods. In order to estimate PM(10) enhancement, we adopted factor analysis to distinguish the yellow-sand (YS) periods from non-yellow-sand (NYS) periods based on air quality monitoring records. Eight YS events were identified using factor analysis coupling with an independent validation procedure by checking background site values, examining meteorological conditions, and modeling air mass trajectory from January 2001 to May 2001. The duration of each event varied from 11 to 132 h, which was identified from the time when the PM(10) level was high, and the CO and NOx levels were low. Subsequently, we used the artificial neural network (ANN) to simulate local PM(10) levels from related parameters including local gas pollutants and meteorological factors during the NYS periods. The PM(10) enhancement during the YS periods is then calculated by subtracting the simulated PM(10) from the observed PM(10) levels. Based on our calculations, the PM(10) enhancement in the maximum hour of each event ranged from 51 to 82%. Moreover, in the eight events identified in 2001, it was estimated that a total amount of 7,210 tons of PM(10) were transported by yellow sand to Taipei. Thus, in this study, we demonstrate that an integration of factor analysis with ANN model could provide a very useful method in identifying YS periods and in determining PM(10) enhancement caused by yellow sand.

Multicontaminant air pollution in Chinese cities.

Science.gov (United States)

Han, Lijian; Zhou, Weiqi; Pickett, Steward Ta; Li, Weifeng; Qian, Yuguo

2018-04-01

To investigate multicontaminant air pollution in Chinese cities, to quantify the urban population affected and to explore the relationship between air pollution and urban population size. We obtained data for 155 cities with 276 million inhabitants for 2014 from China's air quality monitoring network on concentrations of fine particulate matter measuring under 2.5 μm (PM 2.5 ), coarse particulate matter measuring 2.5 to 10 μm (PM 10 ), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ) and ozone (O 3 ). Concentrations were considered as high, if they exceeded World Health Organization (WHO) guideline limits. Overall, 51% (142 million) of the study population was exposed to mean annual multicontaminant concentrations above WHO limits - east China and the megacities were worst affected. High daily levels of four-contaminant mixtures of PM 2.5 , PM 10 , SO 2 and O 3 and PM 2.5 , PM 10 , SO 2 and NO 2 occurred on up to 110 days in 2014 in many cities, mainly in Shandong and Hebei Provinces. High daily levels of PM 2.5 , PM 10 and SO 2 occurred on over  146 days in 110 cities, mainly in east and central China. High daily levels of mixtures of PM 2.5 and PM 10 , PM 2.5 and SO 2 , and PM 10 and SO 2 occurred on over  146 days in 145 cities, mainly in east China. Surprisingly, multicontaminant air pollution was less frequent in cities with populations over 10 million than in smaller cities. Multicontaminant air pollution was common in Chinese cities. A shift from single-contaminant to multicontaminant evaluations of the health effects of air pollution is needed. China should implement protective measures during future urbanization.

PIXE characterization of PM10 and PM2.5 particulate matter collected during the winter season in Shanghai city

International Nuclear Information System (INIS)

Zhang Yuanxun; Wang Yingsong; Li Delu; Li Aiguo; Li Yan; Zhang Guilin

2006-01-01

The samples of PM2.5 and PM10 inhalable particulate matter had been collected during the period of December 2002-January 2003 at nineteen representative sites of Shanghai urban and suburb area in order to investigate the chemical characterization of aerosol particle in winter. The samples were analyzed to determine the average concentrations for up to twenty elements by means of particle induced X-ray emission (PIXE). It was found that the average elemental concentrations in the urban center are higher than those in the suburb, except for Ti and P. The particulate mass data demonstrate that the ratio range of PM2.5/PM10 is from 0.32 to 0.85 and its average ratio is 0.6. The result of the enrichment factor shows that the inhalable particles may be divided into two categories, i.e., soil elements from the earth crust and anthropogenic pollution elements. It is noticed that toxic or harmful elements such as S, As, Pb, Ni, Mn and Se are enriched mainly in fine particles with diameter less than 2.5 μm. The fingerprints of major pollution sources such as coal (or oil) burning, vehicle exhaust emission and industry are also presented and discussed. (author)

Association between air pollution and cardiovascular mortality in Hefei, China: A time-series analysis.

Science.gov (United States)

Zhang, Chao; Ding, Rui; Xiao, Changchun; Xu, Yachun; Cheng, Han; Zhu, Furong; Lei, Ruoqian; Di, Dongsheng; Zhao, Qihong; Cao, Jiyu

2017-10-01

In recent years, air pollution has become an alarming problem in China. However, evidence on the effects of air pollution on cardiovascular mortality is still not conclusive to date. This research aimed to assess the short-term effects of air pollution on cardiovascular morbidity in Hefei, China. Data of air pollution, cardiovascular mortality, and meteorological characteristics in Hefei between 2010 and 2015 were collected. Time-series analysis in generalized additive model was applied to evaluate the association between air pollution and daily cardiovascular mortality. During the study period, the annual average concentration of PM 10, SO 2 , and NO 2 was 105.91, 20.58, and 30.93 μg/m 3 , respectively. 21,816 people (including 11,876 man, and 14,494 people over 75 years of age) died of cardiovascular diseases. In single pollutant model, the effects of multi-day exposure were greater than single-day exposure of the air pollution. For every increase of 10 μg/m 3 in SO 2 , NO 2 , and PM 10 levels, CVD mortality increased by 5.26% (95%CI: 3.31%-7.23%), 2.71% (95%CI: 1.23%-4.22%), and 0.68% (95%CI: 0.33%-1.04%) at a lag03, respectively. The multi-pollutant models showed that PM 10 and SO 2 remained associated with CVD mortality, although the effect estimates attenuated. However, the effect of NO 2 on CVD mortality decreased to statistically insignificant. Subgroup analyses further showed that women were more vulnerable than man upon air pollution exposure. These findings showed that air pollution could significantly increase the CVD mortality. Copyright © 2017 Elsevier Ltd. All rights reserved.

Temporal and spatial analyses of particulate matter (PM10 and PM2.5) and its relationship with meteorological parameters over an urban city in northeast China

Science.gov (United States)

Li, Xiaolan; Ma, Yanjun; Wang, Yangfeng; Liu, Ningwei; Hong, Ye

2017-12-01

Temporal and spatial characteristics of atmospheric particulate matter (PM10 and PM2.5) and its relationship with meteorology over Shenyang, a city in northeast China, were statistically analyzed using hourly and daily averaged PM mass concentrations measured at 11 locations and surface meteorological parameters, from January 2014 to May 2016. Using averaged data from 11 stations in Shenyang, it was found that the monthly mean PM2.5 mass concentrations were higher in winter (97.2 ± 11.2 μg m- 3) and autumn (85.5 ± 42.9 μg m- 3), and lower in spring (62.0 ± 14.0 μg m- 3) and summer (42.5 ± 8.4 μg m- 3), similar to the seasonal variation in PM10 concentrations. The monthly ratios of PM2.5/PM10 ranged from 0.41 to 0.87, and were larger in autumn and winter but lowest in spring due to dust activities. PM pollution was concentrated mainly in the central, northern, and western areas of Shenyang in most seasons mainly due to anthropogenic activities such as traffic and residential emission and construction activity as well as natural dust emission. PM concentrations observed over different areas in all seasons generally exhibited two peaks, at 08:00-10:00 local time (LT) and 21:00-23:00 LT, with the exception of PM2.5 in summer, which showed only one peak during the daytime. In addition, PM10 concentrations peaked around 14:00 LT during spring in the western area of Shenyang because of strong thermal and dynamic turbulence, resulting in elevated dust emissions from adjacent dust sources. The relationship between daily PM concentrations and meteorological parameters showed both seasonal and annual variation. Overall, both PM2.5 and PM10 concentrations were negatively correlated with atmospheric visibility, with correlation coefficients (R) of 0.71 and 0.56, respectively. In most seasons, PM concentrations also exhibited negative correlations with wind speed, but showed positive correlations with air pressure, air temperature, and relative humidity. Strong wind

EVALUATION OF AIR POLLUTION FROM ROVINARI (GORJ WITH SUBSTANCES IN SOSPENSION (PM10 AS A RESULT OF AUTO TRAFFIC

Directory of Open Access Journals (Sweden)

Emil Cătălin ŞCHIOPU

2016-12-01

Full Text Available The paper presents a short introduction of the impact that auto transportation has on air quality and on the main pollutants resulting from fuel burning in the engines with internal combustion. Also here are presented the results obtained as a result of monitoring substances in suspension, fraction PM10, realized in the proximity of the most important auto traffic roads of Rovinari. The comparison of the results obtained was realized according to Law 104/2011 on the protection of ambient air quality

Does maternal exposure to benzene and PM10 during pregnancy increase the risk of congenital anomalies? A population-based case-control study

Science.gov (United States)

Vinceti, Marco; Malagoli, Carlotta; Malavolti, Marcella; Cherubini, Andrea; Maffeis, Giuseppe; Rodolfi, Rossella; Heck, Julia E.; Astolfi, Gianni; Calzolari, Elisa; Nicolini, Fausto

2015-01-01

A few studies have suggested an association between maternal exposure to ambient air pollution from vehicular traffic and risk of congenital anomalies in the offspring, but epidemiologic evidence is neither strong nor entirely consistent. In a population-based case-control study in a Northern Italy community encompassing 228 cases of birth defects and 228 referent newborns, we investigated if maternal exposure to PM10 and benzene from vehicular traffic during early pregnancy, as estimated through a dispersion model, was associated with excess teratogenic risk. In conditional logistic regression analysis, and with adjustment for the other pollutant, we found that higher exposure to PM10 but not benzene was associated with increased risk of birth defects overall. Anomaly categories showing the strongest dose-response relation with PM10 exposure were musculoskeletal and chromosomal abnormalities but not cardiovascular defects, with Down syndrome being among the specific abnormalities showing the strongest association, though risk estimates particularly for the less frequent defects were statistically very unstable. Further adjustment in the regression model for potential confounders did not considerably alter the results. All the associations were stronger for average levels of PM10 than for their maximal level. Findings of this study give some support for an excess teratogenic risk following maternal exposure during pregnancy to PM10, but not benzene. Such association appears to be limited to some birth defect categories. PMID:26410719

The classification of PM10 concentrations in Johor Based on Seasonal Monsoons

Science.gov (United States)

Hamid, Hazrul Abdul; Hanafi Rahmat, Muhamad; Aisyah Sapani, Siti

2018-04-01

Air is the most important living resource in life. Contaminated air could adversely affect human health and the environment, especially during the monsoon season. Contamination occurs as a result of human action and haze. There are several pollutants present in the air where one of them is PM10. Secondary data was obtained from the Department of Environment from 2010 until 2014 and was analyzed using the hourly average of PM10 concentrations. This paper examined the relation between PM10 concentrations and the monsoon seasons (Northeast Monsoon and Southwest Monsoon) in Larkin and Pasir Gudang. It was expected that the concentration of PM10 would be higher during the Southwest Monsoon as it is a dry season. The data revealed that the highest PM10 concentrations were recorded between 2010 to 2014 during this particular monsoon season. The characteristics of PM10 concentration were compared using descriptive statistics based on the monsoon seasons and classified using the hierarchical cluster analysis (Ward Methods). The annual average of PM10 concentration during the Southwest Monsoon had exceeded the standard set by the Malaysia Ambient Air Quality Guidelines (50 μg/m3) while the PM10 concentration during the Northeast Monsoon was below the acceptable level for both stations. The dendrogram displayed showed two clusters for each monsoon season for both stations excepted for the PM10 concentration during the Northeast Monsoon in Larkin which was classified into three clusters due to the haze in 2010. Overall, the concentration of PM10 in 2013 was higher based on the clustering shown for every monsoon season at both stations according to the characteristics in the descriptive statistics.

Pulmonary toxicity study in rats with PM 10 and PM 2.5: Differential responses related to scale and composition

Science.gov (United States)

Zhang, Wei; Lei, Tian; Lin, Zhi-Qing; Zhang, Hua-Shan; Yang, Dan-Feng; Xi, Zhu-Ge; Chen, Jian-Hua; Wang, Wei

2011-02-01

ObjectionTo study the pollution of atmospheric particles at winter in Beijing and compare the lung toxicity which induced by particle samples from different sampling sites. MethodWe collected samples from two sampling points during the winter for toxicity testing and chemical analysis. Wistar rats were administered with particles by intratracheal instillation. After exposure, biochemically index, esimmunity indexes, histopathology and DNA damage were detected in rat pulmonary cells. ResultThe elements with enrichment factors (EF) larger than 10 were As, Cd, Cu, Zn, S and Pb in the four experiment groups. The priority control of the total concentration of polycyclic aromatic hydrocarbons (PAHs) in PM 10 and PM 2.5 of Near-traffic source was much higher than that of Far-traffic source, it demonstrated that near the traffic source of PAHs pollution was heavier than that of Far-traffic source, as it was close to main roads Beiyuan Road, motor vehicle emissions were much higher. The pathology of lung showed that the degree of inflammation was increased with the particle diameter minished, it was the same as the detection of biochemical parameters such as lactate dehydrogenase (LDH), Total antioxidant status(T-AOC) and total protein (TP) in BALF and inflammation cytokine(interleukin-1, interleukin-6 and tumor necrosis factor-alpha) in lung homogenate. The indexes of DNA damage including the content of DNA and Olive empennage of PM 2.5 were significant higher than that of PM 10 at the same surveillance point ( P < 0.05), near-traffic particles were higher than the far-traffic particles at the same diameter, ( P < 0.05). ConclusionNear-traffic area particles had certain pollution at winter in Beijing. Meanwhile, atmospheric particulate matters on lung toxicity were related to the particles size and distance related sites which were exposed: smaller size, more toxicity; nearer from traffic, more toxicity.

Seasonal variation of benzo(a)pyrene in the Spanish airborne PM10. Multivariate linear regression model applied to estimate BaP concentrations.

Science.gov (United States)

Callén, M S; López, J M; Mastral, A M

2010-08-15

The estimation of benzo(a)pyrene (BaP) concentrations in ambient air is very important from an environmental point of view especially with the introduction of the Directive 2004/107/EC and due to the carcinogenic character of this pollutant. A sampling campaign of particulate matter less or equal than 10 microns (PM10) carried out during 2008-2009 in four locations of Spain was collected to determine experimentally BaP concentrations by gas chromatography mass-spectrometry mass-spectrometry (GC-MS-MS). Multivariate linear regression models (MLRM) were used to predict BaP air concentrations in two sampling places, taking PM10 and meteorological variables as possible predictors. The model obtained with data from two sampling sites (all sites model) (R(2)=0.817, PRESS/SSY=0.183) included the significant variables like PM10, temperature, solar radiation and wind speed and was internally and externally validated. The first validation was performed by cross validation and the last one by BaP concentrations from previous campaigns carried out in Zaragoza from 2001-2004. The proposed model constitutes a first approximation to estimate BaP concentrations in urban atmospheres with very good internal prediction (Q(CV)(2)=0.813, PRESS/SSY=0.187) and with the maximal external prediction for the 2001-2002 campaign (Q(ext)(2)=0.679 and PRESS/SSY=0.321) versus the 2001-2004 campaign (Q(ext)(2)=0.551, PRESS/SSY=0.449). Copyright 2010 Elsevier B.V. All rights reserved.

Seasonal variation of benzo(a)pyrene in the Spanish airborne PM10. Multivariate linear regression model applied to estimate BaP concentrations

International Nuclear Information System (INIS)

Callen, M.S.; Lopez, J.M.; Mastral, A.M.

2010-01-01

The estimation of benzo(a)pyrene (BaP) concentrations in ambient air is very important from an environmental point of view especially with the introduction of the Directive 2004/107/EC and due to the carcinogenic character of this pollutant. A sampling campaign of particulate matter less or equal than 10 microns (PM10) carried out during 2008-2009 in four locations of Spain was collected to determine experimentally BaP concentrations by gas chromatography mass-spectrometry mass-spectrometry (GC-MS-MS). Multivariate linear regression models (MLRM) were used to predict BaP air concentrations in two sampling places, taking PM10 and meteorological variables as possible predictors. The model obtained with data from two sampling sites (all sites model) (R 2 = 0.817, PRESS/SSY = 0.183) included the significant variables like PM10, temperature, solar radiation and wind speed and was internally and externally validated. The first validation was performed by cross validation and the last one by BaP concentrations from previous campaigns carried out in Zaragoza from 2001-2004. The proposed model constitutes a first approximation to estimate BaP concentrations in urban atmospheres with very good internal prediction (Q CV 2 =0.813, PRESS/SSY = 0.187) and with the maximal external prediction for the 2001-2002 campaign (Q ext 2 =0.679 and PRESS/SSY = 0.321) versus the 2001-2004 campaign (Q ext 2 =0.551, PRESS/SSY = 0.449).

Temporal and Spatial Simulation of Atmospheric Pollutant PM2.5 Changes and Risk Assessment of Population Exposure to Pollution Using Optimization Algorithms of the Back Propagation-Artificial Neural Network Model and GIS.

Science.gov (United States)

Zhang, Ping; Hong, Bo; He, Liang; Cheng, Fei; Zhao, Peng; Wei, Cailiang; Liu, Yunhui

2015-09-29

PM2.5 pollution has become of increasing public concern because of its relative importance and sensitivity to population health risks. Accurate predictions of PM2.5 pollution and population exposure risks are crucial to developing effective air pollution control strategies. We simulated and predicted the temporal and spatial changes of PM2.5 concentration and population exposure risks, by coupling optimization algorithms of the Back Propagation-Artificial Neural Network (BP-ANN) model and a geographical information system (GIS) in Xi'an, China, for 2013, 2020, and 2025. Results indicated that PM2.5 concentration was positively correlated with GDP, SO₂, and NO₂, while it was negatively correlated with population density, average temperature, precipitation, and wind speed. Principal component analysis of the PM2.5 concentration and its influencing factors' variables extracted four components that accounted for 86.39% of the total variance. Correlation coefficients of the Levenberg-Marquardt (trainlm) and elastic (trainrp) algorithms were more than 0.8, the index of agreement (IA) ranged from 0.541 to 0.863 and from 0.502 to 0.803 by trainrp and trainlm algorithms, respectively; mean bias error (MBE) and Root Mean Square Error (RMSE) indicated that the predicted values were very close to the observed values, and the accuracy of trainlm algorithm was better than the trainrp. Compared to 2013, temporal and spatial variation of PM2.5 concentration and risk of population exposure to pollution decreased in 2020 and 2025. The high-risk areas of population exposure to PM2.5 were mainly distributed in the northern region, where there is downtown traffic, abundant commercial activity, and more exhaust emissions. A moderate risk zone was located in the southern region associated with some industrial pollution sources, and there were mainly low-risk areas in the western and eastern regions, which are predominantly residential and educational areas.

Estimating representative background PM2.5 concentration in heavily polluted areas using baseline separation technique and chemical mass balance model

Science.gov (United States)

Gao, Shuang; Yang, Wen; Zhang, Hui; Sun, Yanling; Mao, Jian; Ma, Zhenxing; Cong, Zhiyuan; Zhang, Xian; Tian, Shasha; Azzi, Merched; Chen, Li; Bai, Zhipeng

2018-02-01

The determination of background concentration of PM2.5 is important to understand the contribution of local emission sources to total PM2.5 concentration. The purpose of this study was to exam the performance of baseline separation techniques to estimate PM2.5 background concentration. Five separation methods, which included recursive digital filters (Lyne-Hollick, one-parameter algorithm, and Boughton two-parameter algorithm), sliding interval and smoothed minima, were applied to one-year PM2.5 time-series data in two heavily polluted cities, Tianjin and Jinan. To obtain the proper filter parameters and recession constants for the separation techniques, we conducted regression analysis at a background site during the emission reduction period enforced by the Government for the 2014 Asia-Pacific Economic Cooperation (APEC) meeting in Beijing. Background concentrations in Tianjin and Jinan were then estimated by applying the determined filter parameters and recession constants. The chemical mass balance (CMB) model was also applied to ascertain the effectiveness of the new approach. Our results showed that the contribution of background PM concentration to ambient pollution was at a comparable level to the contribution obtained from the previous study. The best performance was achieved using the Boughton two-parameter algorithm. The background concentrations were estimated at (27 ± 2) μg/m3 for the whole year, (34 ± 4) μg/m3 for the heating period (winter), (21 ± 2) μg/m3 for the non-heating period (summer), and (25 ± 2) μg/m3 for the sandstorm period in Tianjin. The corresponding values in Jinan were (30 ± 3) μg/m3, (40 ± 4) μg/m3, (24 ± 5) μg/m3, and (26 ± 2) μg/m3, respectively. The study revealed that these baseline separation techniques are valid for estimating levels of PM2.5 air pollution, and that our proposed method has great potential for estimating the background level of other air pollutants.

WRF modeling of PM2.5 remediation by SALSCS and its clean air flow over Beijing terrain.

Science.gov (United States)

Cao, Qingfeng; Shen, Lian; Chen, Sheng-Chieh; Pui, David Y H

2018-06-01

Atmospheric simulations were carried out over the terrain of entire Beijing, China, to investigate the effectiveness of an air-pollution cleaning system named Solar-Assisted Large-Scale Cleaning System (SALSCS) for PM 2.5 mitigation by using the Weather Research and Forecasting (WRF) model. SALSCS was proposed to utilize solar energy to generate airflow therefrom the airborne particulate pollution of atmosphere was separated by filtration elements. Our model used a derived tendency term in the potential temperature equation to simulate the buoyancy effect of SALSCS created with solar radiation on its nearby atmosphere. PM 2.5 pollutant and SALSCS clean air were simulated in the model domain by passive tracer scalars. Simulation conditions with two system flow rates of 2.64 × 10 5  m 3 /s and 3.80 × 10 5  m 3 /s were tested for seven air pollution episodes of Beijing during the winters of 2015-2017. The numerical results showed that with eight SALSCSs installed along the 6 th Ring Road of the city, 11.2% and 14.6% of PM 2.5 concentrations were reduced under the two flow-rate simulation conditions, respectively. Copyright © 2018 Elsevier B.V. All rights reserved.

Elemental characterization of New Year's Day PM10 and PM2.2 particulates matter at several sites in Metro Manila

Energy Technology Data Exchange (ETDEWEB)

Santos, Flora L; Pabroa, Preciosa Corazon B; Morco, Ryan P; Racho, Joseph Michael D [Analytical Measurements Research Group, Philippine Nuclear Research Institute, Commonwealth Ave., Diliman, Quezon City (Philippines)

2007-07-01

In the Philippines, it has been a yearly tradition to welcome the coming of the New Year with the loudest noise as can be achieved. Firecrackers and fireworks have been a necessity for Filipinos during this time despite bans on the use of most of these and despite the Department of Health (DOH) campaign to use alternative safe practices to welcome the New Year. Data for PM 10 samples (fractionated as PM 10-2.2 or the course fraction and PM2.2 or the fine fraction) collected in four PNRI sampling sites in Metro Manila show the air pollution impacts of fireworks on New Year's Eve. Samples were collected from 1998 to 2006 using a Gent dichotomous sampler in connection with the PNRI project {sup P}articulate Matter Source Apportionment Using Nuclear and Related Analytical Techniques{sup .} Particulate mass was determined by gravimetry. Elemental analysis of the air filters was done using X-ray Fluorescence Spectrometry (X RF) or Particle induced X-ray Emission (PIXE), multielemental non-destructive nuclear analytical techniques. Black carbon was analyzed using reflectometry. PM 10 values increased by two to four times the usual averages (36.4 to 55.4 ug/cum) and in 2002 even exceeded the PNAAQ short-term guideline value of 150 ug/cum at the ADMU sampling station. PM2.2 values increased by two to six times the usual averages (15 to 28 ug/cum), even many times exceeding US EPA short-term guideline value of 65 ug/cum. The increase in the particulate mass of New Year's Day samples can be attributed more to an increase in the metal pollutants rather than the black carbon, with higher contribution to the fine fraction. Increase in the elemental concentrations of Al, S, Cl, K, Ba, Sr, Ti, V, Mn, Cu and Pb were observed with the highest contribution from K. Results show that the usual practices of burning firecrackers and fireworks during New Year's day celebration is a very strong source of air pollution which contributes significantly high amount of metal pollutants in the

Particulate matter air pollution components and risk for lung cancer

DEFF Research Database (Denmark)

Raaschou-Nielsen, O.; Beelen, Rob; Wang, M.

2016-01-01

geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models...... was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01-1.53 per 5ng/m(3)), PM10 Zn (1.28; 1.02-1.59 per 20ng/m(3)), PM10 S (1.58; 1.03-2.44 per 200ng/m(3)), PM10 Ni (1.......59; 1.12-2.26 per 2ng/m(3)) and PM10 K (1.17; 1.02-1.33 per 100ng/m(3)). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S. CONCLUSIONS: This study indicates that the association between PM in air pollution and lung cancer can be attributed...

Regional contribution to PM1 pollution during winter haze in Yangtze River Delta, China.

Science.gov (United States)

Tang, Lili; Yu, Hongxia; Ding, Aijun; Zhang, Yunjiang; Qin, Wei; Wang, Zhuang; Chen, Wentai; Hua, Yan; Yang, Xiaoxiao

2016-01-15

To quantify regional sources contributing to submicron particulate matter (PM1) pollution in haze episodes, on-line measurements combining two modeling methods, namely, positive matrix factorization (PMF) and backward Lagrangian particle dispersion modeling (LPDM), were conducted for the period of one month in urban Nanjing, a city located in the western part of Yangtze River Delta (YRD) region of China. Several multi-day haze episodes were observed in December 2013. Long-range transport of biomass burning from the southwestern YRD region largely contributed to PM1 pollution with more than 25% of total organics mass in a lasting heavy haze. The LPDM analysis indicates that regional transport is a main source contributing to secondary low-volatility production. The high-potential source regions of secondary low-volatility production are mainly located in areas to the northeast of the city. High aerosol pollution was mainly contributed by regional transport associated with northeastern air masses. Such regional transport on average accounts for 46% of total NR-PM1 with sulfate and aged low-volatility organics being the largest fractions (>65%). Copyright © 2015 Elsevier B.V. All rights reserved.

Assessment of health and economic effects by PM2.5 pollution in Beijing: a combined exposure-response and computable general equilibrium analysis.

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Wang, Guizhi; Gu, SaiJu; Chen, Jibo; Wu, Xianhua; Yu, Jun

2016-12-01

Assessment of the health and economic impacts of PM2.5 pollution is of great importance for urban air pollution prevention and control. In this study, we evaluate the damage of PM2.5 pollution using Beijing as an example. First, we use exposure-response functions to estimate the adverse health effects due to PM2.5 pollution. Then, the corresponding labour loss and excess medical expenditure are computed as two conducting variables. Finally, different from the conventional valuation methods, this paper introduces the two conducting variables into the computable general equilibrium (CGE) model to assess the impacts on sectors and the whole economic system caused by PM2.5 pollution. The results show that, substantial health effects of the residents in Beijing from PM2.5 pollution occurred in 2013, including 20,043 premature deaths and about one million other related medical cases. Correspondingly, using the 2010 social accounting data, Beijing gross domestic product loss due to the health impact of PM2.5 pollution is estimated as 1286.97 (95% CI: 488.58-1936.33) million RMB. This demonstrates that PM2.5 pollution not only has adverse health effects, but also brings huge economic loss.

Displaced calibration of PM10 measurements using spatio-temporal models

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Daniela Cocchi

2007-12-01

Full Text Available PM10 monitoring networks are equipped with heterogeneous samplers. Some of these samplers are known to underestimate true levels of concentrations (non-reference samplers. In this paper we propose a hierarchical spatio-temporal Bayesian model for the calibration of measurements recorded using non-reference samplers, by borrowing strength from non co-located reference sampler measurements.

Household Cooking with Solid Fuels Contributes to Ambient PM2.5 Air Pollution and the Burden of Disease

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Chafe, Zoë A.; Brauer, Michael; Klimont, Zbigniew; Van Dingenen, Rita; Mehta, Sumi; Rao, Shilpa; Riahi, Keywan; Dentener, Frank

2014-01-01

Background: Approximately 2.8 billion people cook with solid fuels. Research has focused on the health impacts of indoor exposure to fine particulate pollution. Here, for the 2010 Global Burden of Disease project (GBD 2010), we evaluated the impact of household cooking with solid fuels on regional population-weighted ambient PM2.5 (particulate matter ≤ 2.5 μm) pollution (APM2.5). Objectives: We estimated the proportion and concentrations of APM2.5 attributable to household cooking with solid fuels (PM2.5-cook) for the years 1990, 2005, and 2010 in 170 countries, and associated ill health. Methods: We used an energy supply–driven emissions model (GAINS; Greenhouse Gas and Air Pollution Interactions and Synergies) and source-receptor model (TM5-FASST) to estimate the proportion of APM2.5 produced by households and the proportion of household PM2.5 emissions from cooking with solid fuels. We estimated health effects using GBD 2010 data on ill health from APM2.5 exposure. Results: In 2010, household cooking with solid fuels accounted for 12% of APM2.5 globally, varying from 0% of APM2.5 in five higher-income regions to 37% (2.8 μg/m3 of 6.9 μg/m3 total) in southern sub-Saharan Africa. PM2.5-cook constituted > 10% of APM2.5 in seven regions housing 4.4 billion people. South Asia showed the highest regional concentration of APM2.5 from household cooking (8.6 μg/m3). On the basis of GBD 2010, we estimate that exposure to APM2.5 from cooking with solid fuels caused the loss of 370,000 lives and 9.9 million disability-adjusted life years globally in 2010. Conclusions: PM2.5 emissions from household cooking constitute an important portion of APM2.5 concentrations in many places, including India and China. Efforts to improve ambient air quality will be hindered if household cooking conditions are not addressed. Citation: Chafe ZA, Brauer M, Klimont Z, Van Dingenen R, Mehta S, Rao S, Riahi K, Dentener F, Smith KR. 2014. Household cooking with solid fuels contributes to

Assessment of PM10 concentrations from domestic biomass fuel combustion in two rural Bolivian highland villages

International Nuclear Information System (INIS)

Albalak, R.; Haber, M.

1999-01-01

PM 10 concentrations were measured in two contrasting rural Bolivian villages that cook with biomass fuels. In one of the villages, cooking was done exclusively indoors, and in the other, it was done primarily outdoors. Concentrations in all potential microenvironments of exposure (i.e., home, kitchen, and outdoors) were measured for a total of 621 samples. Geometric mean kitchen PM 10 concentrations were 1830 and 280 microg/m 3 and geometric mean home concentrations were 280 and 440 microg/m 3 for the indoor and outdoor cooking villages, respectively. An analysis of pollutant concentrations using generalized estimating equation techniques showed significant effects of village location, and interaction of village and location on log-transformed PM 10 concentrations. Pollutant concentrations and activity pattern data were used to estimate total exposure using the indirect method of exposure assessment. Daily exposure for women during the nonwork season was 15 120 and 6240 microg h -1 m -3 for the indoor and outdoor cooking villages, respectively. Differences in exposure to pollution between the villages were not as great as might be expected based on kitchen concentration alone. This study underscores the importance of measuring pollutant concentrations in all microenvironments where people spend time and of shifting the focus of air pollution studies to include rural populations in developing countries

Long-term trend and variability of atmospheric PM10 concentration in the Po Valley

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Bigi, A.; Ghermandi, G.

2014-05-01

The limits to atmospheric pollutant concentration set by the European Commission provide a challenging target for the municipalities in the Po Valley, because of the characteristic climatic conditions and high population density of this region. In order to assess climatology and trends in the concentration of atmospheric particles in the Po Valley, a data set of PM10 data from 41 sites across the Po Valley have been analysed, including both traffic and background sites (either urban, suburban or rural). Of these 41 sites, 18 with 10 yr or longer record have been analysed for long-term trend in deseasonalized monthly means, in annual quantiles and in monthly frequency distribution. A widespread significant decreasing trend has been observed at most sites, up to a few percent per year, by a generalized least squares and Theil-Sen method. All 41 sites have been tested for significant weekly periodicity by Kruskal-Wallis test for mean anomalies and by Wilcoxon test for weekend effect magnitude. A significant weekly periodicity has been observed for most PM10 series, particularly in summer and ascribed mainly to anthropic particulate emissions. A cluster analysis has been applied in order to highlight stations sharing similar pollution conditions over the reference period. Five clusters have been found, two encompassing the metropolitan areas of Turin and Milan and their respective nearby sites and the other three clusters gathering northeast, northwest and central Po Valley sites respectively. Finally, the observed trends in atmospheric PM10 have been compared to trends in provincial emissions of particulates and PM precursors, and analysed along with data on vehicular fleet age, composition and fuel sales. A significant basin-wide drop in emissions occurred for gaseous pollutants, contrarily to emissions of PM10 and PM2.5, whose drop was low and restricted to a few provinces. It is not clear whether the decrease for only gaseous emissions is sufficient to explain the

Analysis of Influence Factors of PM2.5 in Chengdu Based on VAR Model

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Mingzhi, Luo

2017-05-01

Air pollution and smog are the serious harms to public health and has attracted public attention. Based on the vector auto-regressive (VAR) model, we analysed the influence factors of PM2.5 in Chengdu, investigated the effect of other kinds of air pollutants and meteorological factors onthe PM2.5 by using the methods of generalized impulse response function, variance decomposition analysis, Granger causality test and therelated daily data from December 1, 2013 to November 14, 2016 in Chengdu city to the empirical study. The resultsshow that the influence factors of PM2.5 were stable;the increase of nitrogen dioxide, ozone,precipitation and temperature difference led to the increase of PM2.5 concentration while the increase ofthe wind speed, PM10, sulphur dioxide and carbon monoxide resulted in the decrease of PM2.5 concentration.Climate conditions,nitrogen dioxide and ozone are Granger causes for PM2.5.It is suggestedthat the key for the control of PM2.5 must be based on the cause and formation rules of PM2.5.A further study on nitrogen dioxide and ozone may play an important role in finding out the real source and formation reasons of PM2.5.

Source apportionment of PM10 and PM2.5 in a desert region in northern Chile

International Nuclear Information System (INIS)

Jorquera, Héctor; Barraza, Francisco

2013-01-01

Estimating contributions of anthropogenic sources to ambient particulate matter (PM) in desert regions is a challenging issue because wind erosion contributions are ubiquitous, significant and difficult to quantify by using source-oriented, dispersion models. A receptor modeling analysis has been applied to ambient PM 10 and PM 2.5 measured in an industrial zone ∼ 20 km SE of Antofagasta (23.63°S, 70.39°W), a midsize coastal city in northern Chile; the monitoring site is within a desert region that extends from northern Chile to southern Perú. Integrated 24-hour ambient samples of PM 10 and PM 2.5 were taken with Harvard Impactors; samples were analyzed by X Ray Fluorescence, ionic chromatography (NO 3 − and SO 4 = ), atomic absorption (Na + , K + ) and thermal optical transmission for elemental and organic carbon determination. Receptor modeling was carried out using Positive Matrix Factorization (US EPA Version 3.0); sources were identified by looking at specific tracers, tracer ratios, local winds and wind trajectories computed from NOAA's HYSPLIT model. For the PM 2.5 fraction, six contributions were found — cement plant, 33.7 ± 1.3%; soil dust, 22.4 ± 1.6%; sulfates, 17.8 ± 1.7%; mineral stockpiles and brine plant, 12.4 ± 1.2%; Antofagasta, 8.5 ± 1.3% and copper smelter, 5.3 ± 0.8%. For the PM 10 fraction five sources were identified — cement plant, 38.2 ± 1.5%; soil dust, 31.2 ± 2.3%; mineral stockpiles and brine plant, 12.7 ± 1.7%; copper smelter, 11.5 ± 1.6% and marine aerosol, 6.5 ± 2.4%. Therefore local sources contribute to ambient PM concentrations more than distant sources (Antofagasta, marine aerosol) do. Soil dust is enriched with deposition of marine aerosol and calcium, sulfates and heavy metals from surrounding industrial activities. The mean contribution of suspended soil dust to PM 10 is 50 μg/m 3 and the peak daily value is 104 μg/m 3 . For the PM 2.5 fraction, suspended soil dust contributes with an average of 9.3 �

Short-Term Health Impact Assessment of Urban PM10 in Bejaia City (Algeria

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Fatima Benaissa

2016-01-01

Full Text Available We used Health Impact Assessment (HIA to analyze the impact on a given population’s health outcomes in terms of all-causes mortality and respiratory and cardiovascular hospitalizations attributable to short-term exposure to particulate matter less than 10 μm diameter (PM10 in Bejaia city, for which health effects of air pollution have never been investigated. Two scenarios of PM10 reduction were considered: first, a scenario where the PM10 annual mean is decreased by 5 µg/m3, and then a scenario where this PM10 mean is decreased to 20 µg/m3 (World Health Organization annual air quality guideline (WHO-AQG. Annual mean level of PM10 (81.7 µg/m3 was calculated from objective measurements assessed in situ. Each year, about 4 and 55 deaths could be postponed with the first and the second scenarios successfully. Furthermore, decreasing PM10 annual mean by 5 µg/m3 would avoid 5 and 3 respiratory and cardiac hospitalizations, respectively, and not exceeding the PM10 WHO-AQG (20 µg/m3 would result in a potential gain of 36 and 23 per 100000 respiratory and cardiac hospitalizations, respectively. Lowering in current levels of PM10 has a nonnegligible impact in terms of public health that it is expected to be higher in the case of long-term effects.

The relation between air pollution and respiratory deaths in Tehran, Iran- using generalized additive models.

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Dehghan, Azizallah; Khanjani, Narges; Bahrampour, Abbas; Goudarzi, Gholamreza; Yunesian, Masoud

2018-03-20

Some epidemiological evidence has shown a relation between ambient air pollution and adverse health outcomes. The aim of this study was to investigate the effect of air pollution on mortality from respiratory diseases in Tehran, Iran. In this ecological study, air pollution data was inquired from the Tehran Province Environmental Protection Agency and the Tehran Air Quality Control Company. Meteorological data was collected from the Tehran Meteorology Organization and mortality data from the Tehran Cemetery Mortality Registration. Generalized Additive Models (GAM) was used for data analysis with different lags, up to 15 days. A 10-unit increase in all pollutants except CO (1-unit) was used to compute the Relative Risk of deaths. During 2005 until 2014, 37,967 respiratory deaths occurred in Tehran in which 21,913 (57.7%) were male. The strongest relationship between NO 2 and PM 10 and respiratory death was seen on the same day (lag 0), and was respectively (RR = 1.04, 95% CI: 1.02-1.07) and (RR = 1.03, 95% CI: 1.02-1.04). O 3 and PM 2.5 had the strongest relationship with respiratory deaths on lag 2 and 1 respectively, and the RR was equal to 1.03, 95% CI: 1.01-1.05 and 1.06, 95% CI: 1.02-1.10 respectively. NO 2 , O 3 , PM 10 and PM 2.5 also showed significant relations with respiratory deaths in the older age groups. The findings of this study showed that O 3 , NO 2 , PM 10 and PM 2.5 air pollutants were related to respiratory deaths in Tehran. Reducing ambient air pollution can save lives in Tehran.

Application Study of Comprehensive Forecasting Model Based on Entropy Weighting Method on Trend of PM2.5 Concentration in Guangzhou, China

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Liu, Dong-jun; Li, Li

2015-01-01

For the issue of haze-fog, PM2.5 is the main influence factor of haze-fog pollution in China. The trend of PM2.5 concentration was analyzed from a qualitative point of view based on mathematical models and simulation in this study. The comprehensive forecasting model (CFM) was developed based on the combination forecasting ideas. Autoregressive Integrated Moving Average Model (ARIMA), Artificial Neural Networks (ANNs) model and Exponential Smoothing Method (ESM) were used to predict the time series data of PM2.5 concentration. The results of the comprehensive forecasting model were obtained by combining the results of three methods based on the weights from the Entropy Weighting Method. The trend of PM2.5 concentration in Guangzhou China was quantitatively forecasted based on the comprehensive forecasting model. The results were compared with those of three single models, and PM2.5 concentration values in the next ten days were predicted. The comprehensive forecasting model balanced the deviation of each single prediction method, and had better applicability. It broadens a new prediction method for the air quality forecasting field. PMID:26110332

Environmental Pollution by Benzene and PM10 and Clinical Manifestations of Systemic Sclerosis: A Correlation Study.

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Borghini, Alice; Poscia, Andrea; Bosello, Silvia; Teleman, Adele Anna; Bocci, Mario; Iodice, Lanfranco; Ferraccioli, Gianfranco; La Milìa, Daniele Ignazio; Moscato, Umberto

2017-10-26

Atmospheric air pollution has been associated with a range of adverse health effects. The environment plays a causative role in the development of Systemic Sclerosis (SSc). The aim of the present study is to explore the association between particulate (PM 10 ) and benzene (B) exposure in Italian patients with systemic sclerosis and their clinical characteristics of the disease. A correlation study was conducted by enrolling 88 patients who suffer from SSc at the Fondazione Policlinico "A. Gemelli" in Rome (Italy) in the period from January 2013 to January 2014. The average mean concentrations of B (in 11 monitoring sites) and PM 10 (in 14 sites) were calculated using data from the Regional Environmental Protection Agency's monitoring stations located throughout the Lazio region (Italy) and then correlated with the clinical characteristics of the SSc patients. Of the study sample, 92.5% were female. The mean age was 55 ± 12.9 years old and the mean disease duration from the onset of Raynaud's phenomenon was 13.0 ± 9.4 years. The Spearman's correlation showed that concentrations of B correlate directly with the skin score (R = 0.3; p ≤ 0.05) and inversely with Diffusing Lung Carbon Monoxide (DLCO) results (R = -0.36; p = 0.04). This study suggests a possible role of B in the development of diffuse skin disease and in a worse progression of the lung manifestations of SSc.

Assessment of microbial communities in PM1 and PM10 of Urumqi during winter.

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Gou, Huange; Lu, Jianjiang; Li, Shanman; Tong, Yanbin; Xie, Chunbin; Zheng, Xiaowu

2016-07-01

Recently, inhalable particulate matter has been reported to carry microorganisms responsible for human allergy and respiratory disease. The unique geographical environment and adverse weather conditions of Urumqi cause double pollution of dust and smog, but research on the microbial content of the atmosphere has not been commenced. In this study, 16S and 18S rRNA gene sequencing were conducted to investigate the microbial composition of Urumqi's PM1 and PM10 pollutants in winter. Results showed that the bacterial community is mainly composed of Proteobacteria, Firmicutes and Actinobacteria, Proteobacteria accounted for the most proportion which was significant difference in some aforementioned studies. Ascomycota and Basidiomycota constitute the main part of the fungal microbial community. The difference of bacterial relative abundance in sample point is greater than in particle sizes. The sequences of several pathogenic bacteria and opportunistic pathogens were also detected, such as Acinetobacter, Delftia, Serratia, Chryseobacterium, which may impact on immunocompromised populations (elderly, children and postoperative convalescence patients), and some fungal genera may cause several plant diseases. Our findings may serve an important reference value in the global air microbial propagation and air microbial research in desert. Copyright © 2016 Elsevier Ltd. All rights reserved.

Temporal and Spatial Simulation of Atmospheric Pollutant PM2.5 Changes and Risk Assessment of Population Exposure to Pollution Using Optimization Algorithms of the Back Propagation-Artificial Neural Network Model and GIS

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Ping Zhang

2015-09-01

Full Text Available PM2.5 pollution has become of increasing public concern because of its relative importance and sensitivity to population health risks. Accurate predictions of PM2.5 pollution and population exposure risks are crucial to developing effective air pollution control strategies. We simulated and predicted the temporal and spatial changes of PM2.5 concentration and population exposure risks, by coupling optimization algorithms of the Back Propagation-Artificial Neural Network (BP-ANN model and a geographical information system (GIS in Xi’an, China, for 2013, 2020, and 2025. Results indicated that PM2.5 concentration was positively correlated with GDP, SO2, and NO2, while it was negatively correlated with population density, average temperature, precipitation, and wind speed. Principal component analysis of the PM2.5 concentration and its influencing factors’ variables extracted four components that accounted for 86.39% of the total variance. Correlation coefficients of the Levenberg-Marquardt (trainlm and elastic (trainrp algorithms were more than 0.8, the index of agreement (IA ranged from 0.541 to 0.863 and from 0.502 to 0.803 by trainrp and trainlm algorithms, respectively; mean bias error (MBE and Root Mean Square Error (RMSE indicated that the predicted values were very close to the observed values, and the accuracy of trainlm algorithm was better than the trainrp. Compared to 2013, temporal and spatial variation of PM2.5 concentration and risk of population exposure to pollution decreased in 2020 and 2025. The high-risk areas of population exposure to PM2.5 were mainly distributed in the northern region, where there is downtown traffic, abundant commercial activity, and more exhaust emissions. A moderate risk zone was located in the southern region associated with some industrial pollution sources, and there were mainly low-risk areas in the western and eastern regions, which are predominantly residential and educational areas.

What Causes Haze Pollution? An Empirical Study of PM2.5 Concentrations in Chinese Cities

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Jiannan Wu

2016-01-01

Full Text Available In recent years, many areas of China have suffered from serious haze pollution, which greatly affects human health and daily life. It is of policy importance to understand the factors that influence the spatial concentration of PM2.5. Based on data from 74 cities with PM2.5 monitoring stations in 2013 and 2014, this study presents the overall haze situation in China and explores the determinants of PM2.5 using a random-effects model, as well as a set of OLS regressions. The results indicate that PM2.5 is significantly correlated with the industrial proportion, the number of motor vehicles, and household gas consumption, while public financial expenditure on energy saving and environmental protection does not show statistically significant effects. The analysis implies that China should adjust its economic structure and optimizes environmental governance to effectively respond to haze pollution.

Pulmonary Function and Incidence of Selected Respiratory Diseases Depending on the Exposure to Ambient PM10

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Artur Badyda

2016-11-01

Full Text Available It is essential in pulmonary disease research to take into account traffic-related air pollutant exposure among urban inhabitants. In our study, 4985 people were examined for spirometric parameters in the presented research which was conducted in the years 2008–2012. The research group was divided into urban and rural residents. Traffic density, traffic structure and velocity, as well as concentrations of selected air pollutants (CO, NO2 and PM10 were measured at selected areas. Among people who live in the city, lower percentages of predicted values of spirometric parameters were noticed in comparison to residents of rural areas. Taking into account that the difference in the five-year mean concentration of PM10 in the considered city and rural areas was over 17 μg/m3, each increase of PM10 by 10 μg/m3 is associated with the decline in FEV1 (forced expiratory volume during the first second of expiration by 1.68%. These findings demonstrate that traffic-related air pollutants may have a significant influence on the decline of pulmonary function and the growing rate of respiratory diseases.

Indoor PM1, PM2.5, PM10 and outdoor PM2.5 concentrations in primary schools in Sari, Iran.

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Mohammadyan, Mahmoud; Shabankhani, Bijan

2013-09-01

This study was carried out to determine the distribution of particles in classrooms in primary schools located in the centre of the city of Sari, Iran and identify the relationship between indoor classroom particle levels and outdoor PM2.5 concentrations. Outdoor PM2.5 and indoor PM1, PM2.5, and PM10 were monitored using a real-time Micro Dust Pro monitor and a GRIMM monitor, respectively. Both monitors were calibrated by gravimetric method using filters. The Kolmogorov-Smirnov test showed that all indoor and outdoor data fitted normal distribution. Mean indoor PM1, PM2.5, PM10 and outdoor PM2.5 concentrations for all of the classrooms were 17.6 μg m(-3), 46.6 μg m(-3), 400.9 μg m(-3), and 36.9 μg m(-3), respectively. The highest levels of indoor and outdoor PM2.5 concentrations were measured at the Shahed Boys School (69.1 μg m(-3) and 115.8 μg m(-3), respectively). The Kazemi school had the lowest levels of indoor and outdoor PM2.5 (29.1 μg m(-3) and 15.5 μg m(-3), respectively). In schools located near both main and small roads, the association between indoor fine particle (PM2.5 and PM1) and outdoor PM2.5 levels was stronger than that between indoor PM10 and outdoor PM2.5 levels. Mean indoor PM2.5 and PM10 and outdoor PM2.5 were higher than the standards for PM2.5 and PM10, and there was a good correlation between indoor and outdoor fine particle concentrations.

PM10 and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set

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2014-01-01

Background The chemical composition of aerosols and particle size distributions are the most significant factors affecting air quality. In particular, the exposure to finer particles can cause short and long-term effects on human health. In the present paper PM10 (particulate matter with aerodynamic diameter lower than 10 μm), CO, NOx (NO and NO2), Benzene and Toluene trends monitored in six monitoring stations of Bari province are shown. The data set used was composed by bi-hourly means for all parameters (12 bi-hourly means per day for each parameter) and it’s referred to the period of time from January 2005 and May 2007. The main aim of the paper is to provide a clear illustration of how large data sets from monitoring stations can give information about the number and nature of the pollutant sources, and mainly to assess the contribution of the traffic source to PM10 concentration level by using multivariate statistical techniques such as Principal Component Analysis (PCA) and Absolute Principal Component Scores (APCS). Results Comparing the night and day mean concentrations (per day) for each parameter it has been pointed out that there is a different night and day behavior for some parameters such as CO, Benzene and Toluene than PM10. This suggests that CO, Benzene and Toluene concentrations are mainly connected with transport systems, whereas PM10 is mostly influenced by different factors. The statistical techniques identified three recurrent sources, associated with vehicular traffic and particulate transport, covering over 90% of variance. The contemporaneous analysis of gas and PM10 has allowed underlining the differences between the sources of these pollutants. Conclusions The analysis of the pollutant trends from large data set and the application of multivariate statistical techniques such as PCA and APCS can give useful information about air quality and pollutant’s sources. These knowledge can provide useful advices to environmental policies in

Source Apportionment and Elemental Composition of PM2.5 and PM10 in Jeddah City, Saudi Arabia.

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Khodeir, Mamdouh; Shamy, Magdy; Alghamdi, Mansour; Zhong, Mianhua; Sun, Hong; Costa, Max; Chen, Lung-Chi; Maciejczyk, Polina

2012-07-01

This paper presents the first comprehensive investigation of PM2.5 and PM10 composition and sources in Saudi Arabia. We conducted a multi-week multiple sites sampling campaign in Jeddah between June and September, 2011, and analyzed samples by XRF. The overall mean mass concentration was 28.4 ± 25.4 μg/m 3 for PM2.5 and 87.3 ± 47.3 μg/m 3 for PM10, with significant temporal and spatial variability. The average ratio of PM2.5/PM10 was 0.33. Chemical composition data were modeled using factor analysis with varimax orthogonal rotation to determine five and four particle source categories contributing significant amount of for PM2.5 and PM10 mass, respectively. In both PM2.5 and PM10 sources were (1) heavy oil combustion characterized by high Ni and V; (2) resuspended soil characterized by high concentrations of Ca, Fe, Al, and Si; and (3) marine aerosol. The two other sources in PM2.5 were (4) Cu/Zn source; (5) traffic source identified by presence of Pb, Br, and Se; while in PM10 it was a mixed industrial source. To estimate the mass contributions of each individual source category, the CAPs mass concentration was regressed against the factor scores. Cumulatively, resuspended soil and oil combustion contributed 77 and 82% mass of PM2.5 and PM10, respectively.

Air pollution and cardiovascular mortality with over 25years follow-up: A combined analysis of two British cohorts.

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Dehbi, Hakim-Moulay; Blangiardo, Marta; Gulliver, John; Fecht, Daniela; de Hoogh, Kees; Al-Kanaani, Zaina; Tillin, Therese; Hardy, Rebecca; Chaturvedi, Nish; Hansell, Anna L

2017-02-01

Adverse effects of air pollution on cardiovascular disease (CVD) mortality are well established. There are comparatively fewer studies in Europe, and in the UK particularly, than in North America. We examined associations in two British cohorts with >25years of follow-up. Annual average NO 2 , SO 2 and black smoke (BS) air pollution exposure estimates for 1991 were obtained from land use regression models using contemporaneous monitoring data. From the European Study of Cohorts and Air Pollution (ESCAPE), air pollution estimates in 2010-11 were obtained for NO 2 , NO x , PM 10 , PM coarse and PM 2.5 . The exposure estimates were assigned to place of residence 1989 for participants in a national birth cohort born in 1946, the MRC National Study of Health and Development (NSHD), and an adult multi-ethnic London cohort, Southall and Brent Revisited (SABRE) recruited 1988-91. The combined median follow-up was 26years. Single-pollutant competing risk models were employed, adjusting for individual risk factors. Elevated non-significant hazard ratios for CVD mortality were seen with 1991 BS and SO 2 and with ESCAPE PM 10 and PM 2.5 in fully adjusted linear models. Per 10μg/m 3 increase HRs were 1.11 [95% CI: 0.76-1.61] for BS, 1.05 [95% CI: 0.91-1.22] for SO 2 , 1.16 [95% CI: 0.70-1.92] for PM 10 and 1.30 [95% CI: 0.39-4.34] for PM 2.5 , with largest effects seen in the fourth quartile of BS and PM 2.5 compared to the first with HR 1.24 [95% CI: 0.91-1.61] and 1.21 [95% CI: 0.88-1.66] respectively. There were no consistent associations with other ESCAPE pollutants, or with 1991 NO 2 . Modelling using Cox regression led to similar results. Our results support a detrimental long-term effect for air pollutants on cardiovascular mortality. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Generalized additive model of air pollution to daily mortality

International Nuclear Information System (INIS)

Kim, J.; Yang, H.E.

2005-01-01

The association of air pollution with daily mortality due to cardiovascular disease, respiratory disease, and old age (65 or older) in Seoul, Korea was investigated in 1999 using daily values of TSP, PM10, O 3 , SO 2 , NO 2 , and CO. Generalized additive Poisson models were applied to allow for the highly flexible fitting of daily trends in air pollution as well as nonlinear association with meteorological variables such as temperature, humidity, and wind speed. To estimate the effect of air pollution and weather on mortality, LOESS smoothing was used in generalized additive models. The findings suggest that air pollution levels affect significantly the daily mortality. (orig.)

Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5

Science.gov (United States)

Ausati, Shadi; Amanollahi, Jamil

2016-10-01

Since Sanandaj is considered one of polluted cities of Iran, prediction of any type of pollution especially prediction of suspended particles of PM2.5, which are the cause of many diseases, could contribute to health of society by timely announcements and prior to increase of PM2.5. In order to predict PM2.5 concentration in the Sanandaj air the hybrid models consisting of an ensemble empirical mode decomposition and general regression neural network (EEMD-GRNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), principal component regression (PCR), and linear model such as multiple liner regression (MLR) model were used. In these models the data of suspended particles of PM2.5 were the dependent variable and the data related to air quality including PM2.5, PM10, SO2, NO2, CO, O3 and meteorological data including average minimum temperature (Min T), average maximum temperature (Max T), average atmospheric pressure (AP), daily total precipitation (TP), daily relative humidity level of the air (RH) and daily wind speed (WS) for the year 2014 in Sanandaj were the independent variables. Among the used models, EEMD-GRNN model with values of R2 = 0.90, root mean square error (RMSE) = 4.9218 and mean absolute error (MAE) = 3.4644 in the training phase and with values of R2 = 0.79, RMSE = 5.0324 and MAE = 3.2565 in the testing phase, exhibited the best function in predicting this phenomenon. It can be concluded that hybrid models have accurate results to predict PM2.5 concentration compared with linear model.

Characterization of the GENT PM10 sampler. Appendix 18

International Nuclear Information System (INIS)

Hopke, Philip K.; Xie Ying; Raunemaa, Taisto; Biegalski, Steven; Landsberger, Sheldon

1995-01-01

An integral part of the Co-ordinated Research Programme: Applied Research on Air Pollution using Nuclear-Related Analytical Techniques is the PM 10 sampler that was designed by Dr. W. Maenhaut of the University of Gent. Each participant was provided with such a sampler so that comparable samples will be obtained by each of the participating groups. Thus, in order to understand the characteristics of this sampler, we have undertaken several characterization studies in which we have examine the aerodynamic collection characteristics of the impactor inlet and the reproducibility of the sample mass collection. The sampler does provide a collection efficiency that follows the guidelines for a PM 10 sampler. Comparing one of the original samplers built at the University of Gent with a unit built from the same plans at Clarkson University showed good reproducibility in mass collection. (author)

Comparisons of urban and rural PM10−2.5 and PM2.5 mass concentrations and semi-volatile fractions in northeastern Colorado

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N. Clements

2016-06-01

Full Text Available Coarse (PM10−2.5 and fine (PM2.5 particulate matter in the atmosphere adversely affect human health and influence climate. While PM2.5 is relatively well studied, less is known about the sources and fate of PM10−2.5. The Colorado Coarse Rural-Urban Sources and Health (CCRUSH study measured PM10−2.5 and PM2.5 mass concentrations, as well as the fraction of semi-volatile material (SVM in each size regime (SVM2.5, SVM10−2.5, from 2009 to early 2012 in Denver and comparatively rural Greeley, Colorado. Agricultural operations east of Greeley appear to have contributed to the peak PM10−2.5 concentrations there, but concentrations were generally lower in Greeley than in Denver. Traffic-influenced sites in Denver had PM10−2.5 concentrations that averaged from 14.6 to 19.7 µg m−3 and mean PM10−2.5 ∕ PM10 ratios of 0.56 to 0.70, higher than at residential sites in Denver or Greeley. PM10−2.5 concentrations were more temporally variable than PM2.5 concentrations. Concentrations of the two pollutants were not correlated. Spatial correlations of daily averaged PM10−2.5 concentrations ranged from 0.59 to 0.62 for pairs of sites in Denver and from 0.47 to 0.70 between Denver and Greeley. Compared to PM10−2.5, concentrations of PM2.5 were more correlated across sites within Denver and less correlated between Denver and Greeley. PM10−2.5 concentrations were highest during the summer and early fall, while PM2.5 and SVM2.5 concentrations peaked in winter during periodic multi-day inversions. SVM10−2.5 concentrations were low at all sites. Diurnal peaks in PM10−2.5 and PM2.5 concentrations corresponded to morning and afternoon peaks of traffic activity, and were enhanced by boundary layer dynamics. SVM2.5 concentrations peaked around noon on both weekdays and weekends. PM10−2.5 concentrations at sites located near highways generally increased with wind speeds above about 3 m s−1. Little wind speed dependence was

Air pollution studies in terms of PM2.5, PM2.5-10, PM10, lead and black carbon in urban areas of Antananarivo-Madagascar

International Nuclear Information System (INIS)

Rasoazanany, E. O.; Andriamahenina, N. N.; Ravoson, H. N.; Raoelina Andriambololona; Randriamanivo, L. V.; Ramaherison, H.; Ahmed, H.; Harinoely, M.

2011-01-01

Atmospheric aerosols or particulate matters are chemically complex and dynamic mixtures of solid and liquid particles. Sources of particulate matters include both natural and anthropogenic processes. The present work consists in determining the concentrations of existing elements in the aerosols collected in Andravoahangy and in Ambodin Isotry in Antananarivo city (Madagascar). The size distribution of these elements and their main sources are also studied.The Total Reflection X-Ray Fluorescence spectrometer is used for the qualitative and quantitative analyses. The results show that the concentrations of the airborne particulate matters PM 2.5-10 are higher than those of PM 2.5 .The identified elements in the aerosol samples are Ti, Cr, Mn, Fe, Ni, Cu, Zn, Br, Sr and Pb. The average concentrations of these elements are also higher in the coarse particles than in the fine particles. The calculation of the enrichment factors by Mason's model shows that Cr, Ni, Cu, Zn, Br and Pb are of anthropogenic origins. The average concentrations of lead (2.8 ng.m -3 , 31.3 ng.m -3 and 19.6 ng.m -3 respectively in aerosols collected in Andravoahangy in 2007 and in 2008 and in Ambodin Isotry in 2008) are largely lower than the average concentration of 1.8 μg.m -3 obtained in 2000 in the Antananarivo urban areas. The concentration of black carbon is higher in the fine particles. The Air Quality Index category is variable in the two sites.

Globalization and pollution: tele-connecting local primary PM2.5 emissions to global consumption.

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Meng, Jing; Liu, Junfeng; Xu, Yuan; Guan, Dabo; Liu, Zhu; Huang, Ye; Tao, Shu

2016-11-01

Globalization pushes production and consumption to geographically diverse locations and generates a variety of sizeable opportunities and challenges. The distribution and associated effects of short-lived primary fine particulate matter (PM 2.5 ), a representative of local pollution, are significantly affected by the consumption through global supply chain. Tele-connection is used here to represent the link between production and consumption activity at large distances. In this study, we develop a global consumption-based primary PM 2.5 emission inventory to track primary PM 2.5 emissions embodied in the supply chain and evaluate the extent to which local PM 2.5 emissions are triggered by international trade. We further adopt consumption-based accounting and identify the global original source that produced the emissions. We find that anthropogenic PM 2.5 emissions from industrial sectors accounted for 24 Tg globally in 2007; approximately 30% (7.2 Tg) of these emissions were embodied in export of products principally from Brazil, South Africa, India and China (3.8 Tg) to developed countries. Large differences (up to 10 times) in the embodied emissions intensity between net importers and exporters greatly increased total global PM 2.5 emissions. Tele-connecting production and consumption activity provides valuable insights with respect to mitigating long-range transboundary air pollution and prompts concerted efforts aiming at more environmentally conscious globalization.

Globalization and pollution: tele-connecting local primary PM2.5 emissions to global consumption

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Meng, Jing; Xu, Yuan; Guan, Dabo; Liu, Zhu; Huang, Ye; Tao, Shu

2016-01-01

Globalization pushes production and consumption to geographically diverse locations and generates a variety of sizeable opportunities and challenges. The distribution and associated effects of short-lived primary fine particulate matter (PM2.5), a representative of local pollution, are significantly affected by the consumption through global supply chain. Tele-connection is used here to represent the link between production and consumption activity at large distances. In this study, we develop a global consumption-based primary PM2.5 emission inventory to track primary PM2.5 emissions embodied in the supply chain and evaluate the extent to which local PM2.5 emissions are triggered by international trade. We further adopt consumption-based accounting and identify the global original source that produced the emissions. We find that anthropogenic PM2.5 emissions from industrial sectors accounted for 24 Tg globally in 2007; approximately 30% (7.2 Tg) of these emissions were embodied in export of products principally from Brazil, South Africa, India and China (3.8 Tg) to developed countries. Large differences (up to 10 times) in the embodied emissions intensity between net importers and exporters greatly increased total global PM2.5 emissions. Tele-connecting production and consumption activity provides valuable insights with respect to mitigating long-range transboundary air pollution and prompts concerted efforts aiming at more environmentally conscious globalization. PMID:27956874

Globalization and pollution: tele-connecting local primary PM2.5 emissions to global consumption

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Meng, Jing; Liu, Junfeng; Xu, Yuan; Guan, Dabo; Liu, Zhu; Huang, Ye; Tao, Shu

2016-11-01

Globalization pushes production and consumption to geographically diverse locations and generates a variety of sizeable opportunities and challenges. The distribution and associated effects of short-lived primary fine particulate matter (PM2.5), a representative of local pollution, are significantly affected by the consumption through global supply chain. Tele-connection is used here to represent the link between production and consumption activity at large distances. In this study, we develop a global consumption-based primary PM2.5 emission inventory to track primary PM2.5 emissions embodied in the supply chain and evaluate the extent to which local PM2.5 emissions are triggered by international trade. We further adopt consumption-based accounting and identify the global original source that produced the emissions. We find that anthropogenic PM2.5 emissions from industrial sectors accounted for 24 Tg globally in 2007; approximately 30% (7.2 Tg) of these emissions were embodied in export of products principally from Brazil, South Africa, India and China (3.8 Tg) to developed countries. Large differences (up to 10 times) in the embodied emissions intensity between net importers and exporters greatly increased total global PM2.5 emissions. Tele-connecting production and consumption activity provides valuable insights with respect to mitigating long-range transboundary air pollution and prompts concerted efforts aiming at more environmentally conscious globalization.

Assessment of PM10 and heavy metals concentration in a Ceramic Cluster (NE Spain)

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Belen Vicente, Ana; Pardo, Francisco; Sanfeliu, Teofilo; Bech, Joan

2013-04-01

Environmental pollution control is one of the most important goals in pollution risk assessment today. The aim of this study is conducting a retrospective view of the evolution of particulate matter (PM10) and heavy metals (As, Cd, Ni and Pb) at different localities in the Spanish cluster ceramic in the period between January 2007 and December 2011. The study area is in the province of Castellón. This province is a strategical area in the framework of European Union Pollution control. Approximately 80% of European ceramic tiles and ceramic frits manufacturers are concentrated in two areas, forming the so-called "Ceramics Clusters"; one is in Modena (Italy) and the other in Castellón (Spain). In this kind of areas, there are a lot of pollutants from this industry that represent an important contribution to soil contamination so it is necessary to control the air quality in them. These atmospheric particles are deposited in the ground through both dry and wet deposition. Soil is a major sink for heavy metals released into the environment. The level of pollution of soils by heavy metals depends on the retention capacity of the soil, especially on physical-chemical properties (mineralogy, grain size, organic matter) affecting soil particle surfaces and also on the chemical properties of the metal. The most direct consequences on the ground of air pollutants are acidification, salinization and the pollutions that can cause heavy metals as components of suspended particulate matter. For this purpose the levels of PM10 in ambient air and the corresponding annual and weekly trend were calculated. The results of the study show that the PM10 and heavy metals concentrations are below the limit values recommended by European Union Legislation for the protection of human health and ecosystems in the study period. There is an important reduction of them from 2009 in all control stations due to the economic crisis. References Moral, R., Gilkes, R.J., Jordán, M.M., 2005

External costs of PM2.5 pollution in Beijing, China: Uncertainty analysis of multiple health impacts and costs

International Nuclear Information System (INIS)

Yin, Hao; Pizzol, Massimo; Xu, Linyu

2017-01-01

Some cities in China are facing serious air pollution problems including high concentrations of particles, SO 2 and NO x . Exposure to PM2.5, one of the primary air pollutants in many cities in China, is highly correlated with various adverse health impacts and ultimately represents a cost for society. The aim of this study is to assess health impacts and external costs related to PM2.5 pollution in Beijing, China with different baseline concentrations and valuation methods. The idea is to provide a reasonable estimate of the total health impacts and external cost due to PM2.5 pollution, as well as a quantification of the relevant uncertainty. PM2.5 concentrations were retrieved for the entire 2012 period in 16 districts of Beijing. The various PM2.5 related health impacts were identified and classified to avoid double counting. Exposure-response coefficients were then obtained from literature. Both the value of statistical life (VSL) and the amended human capital (AHC) approach were applied for external costs estimation, which could provide the upper and lower bound of the external costs due to PM2.5. To fully understand the uncertainty levels, the external cost distribution was determined via Monte Carlo simulation based on the uncertainty of the parameters such as PM2.5 concentration, exposure-response coefficients, and economic cost per case. The results showed that the external costs were equivalent to around 0.3% (AHC, China's guideline: C 0  = 35 μg/m 3 ) to 0.9% (VSL, WHO guideline: C 0  = 10 μg/m 3 ) of regional GDP depending on the valuation method and on the assumed baseline PM2.5 concentration (C 0 ). Among all the health impacts, the economic loss due to premature deaths accounted for more than 80% of the overall external costs. The results of this study could help policymakers prioritizing the PM2.5 pollution control interventions and internalize the external costs through the application of economic policy instruments. - Highlights: �

Chemical characteristics and influence of continental outflow on PM1.0, PM2.5 and PM10 measured at Tuoji island in the Bohai Sea.

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Zhang, Junmei; Yang, Lingxiao; Mellouki, Abdelwahid; Wen, Liang; Yang, Yumeng; Gao, Ying; Jiang, Pan; Li, Yanyan; Wang, Wenxing

2016-12-15

To investigate the chemical characteristics and sources of size-segregated particles in the background region, PM 1.0 , PM 2.5 and PM 10 samples were collected in Tuoji Island (TI) during the winter of 2014. Water-soluble inorganic ions (WSIIs) including Na + , NH 4 + , K + , Mg 2+ , Ca 2+ , Cl - , NO 3 - and SO 4 2- , organic carbon (OC) and elemental carbon (EC) and water-soluble organic carbon (WSOC) were analysed. The average mass concentrations of PM 1.0 , PM 2.5 and PM 10 were 44.5μg/m 3 , 62.0μg/m 3 and 94.4μg/m 3 , respectively, and particles were importantly enriched in PM 1.0 . Secondary WSIIs (NH 4 + , NO 3 - and SO 4 2- ) were the most abundant species, and their contribution was highest in PM 1.0 . The average values of NOR and SOR were more than 0.1 in PM 1.0 , suggesting that secondary formation of SO 4 2- and NO 3 - from the gas precursors SO 2 and NO 2 occurred in PM 1.0 . Secondary organic carbon accounted for 62.3% in PM 1.0 , 61.9% in PM 1.0-2.5 and 48.9% in PM 2.5-10 of OC, formed mainly in the fine mode. The particles concentrations were mainly affected by air mass from the North China Plain, especially the air mass from the southwest of Shandong province, which had low speed and altitude. Copyright © 2016 Elsevier B.V. All rights reserved.

Receptor modeling of PM2.5, PM10 and TSP in different seasons and long-range transport analysis at a coastal site of Tianjin, China.

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Kong, Shaofei; Han, Bin; Bai, Zhipeng; Chen, Li; Shi, Jianwu; Xu, Zhun

2010-09-15

Atmospheric particulate matter (PM(2.5), PM(10) and TSP) were sampled synchronously during three monitoring campaigns from June 2007 to February 2008 at a coastal site in TEDA of Tianjin, China. Chemical compositions including 19 elements, 6 water-solubility ions, organic and elemental carbon were determined. principle components analysis (PCA) and chemical mass balance modeling (CMB) were applied to determine the PM sources and their contributions with the assistance of NSS SO(4)(2)(-), the mass ratios of NO(3)(-) to SO(4)(2)(-) and OC to EC. Air mass backward trajectory model was compared with source apportionment results to evaluate the origin of PM. Results showed that NSS SO(4)(2)(-) values for PM(2.5) were 2147.38, 1701.26 and 239.80 ng/m(3) in summer, autumn and winter, reflecting the influence of sources from local emissions. Most of it was below zero in summer for PM(10) indicating the influence of sea salt. The ratios of NO(3)(-) to SO(4)(2)(-) was 0.19 for PM(2.5), 0.18 for PM(10) and 0.19 for TSP in winter indicating high amounts of coal consumed for heating purpose. Higher OC/EC values (mostly larger than 2.5) demonstrated that secondary organic aerosol was abundant at this site. The major sources were construction activities, road dust, vehicle emissions, marine aerosol, metal manufacturing, secondary sulfate aerosols, soil dust, biomass burning, some pharmaceutics industries and fuel-oil combustion according to PCA. Coal combustion, marine aerosol, vehicular emission and soil dust explained 5-31%, 1-13%, 13-44% and 3-46% for PM(2.5), PM(10) and TSP, respectively. Backward trajectory analysis showed air parcels originating from sea accounted for 39% in summer, while in autumn and winter the air parcels were mainly related to continental origin. Copyright 2010 Elsevier B.V. All rights reserved.

Characterization and source apportionment of health risks from ambient PM10 in Hong Kong over 2000-2011

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Li, Zhiyuan; Yuan, Zibing; Li, Ying; Lau, Alexis K. H.; Louie, Peter K. K.

2015-12-01

Atmospheric particulate matter (PM) pollution is a major public health concern in Hong Kong. In this study, the spatiotemporal variations of health risks from ambient PM10 from seven air quality monitoring stations between 2000 and 2011 were analyzed. Positive matrix factorization (PMF) was adopted to identify major source categories of ambient PM10 and quantify their contributions. Afterwards, a point-estimated risk model was used to identify the inhalation cancer and non-cancer risks of PM10 sources. The long-term trends of the health risks from classified local and non-local sources were explored. Furthermore, the reason for the increase of health risks during high PM10 days was discussed. Results show that vehicle exhaust source was the dominant inhalation cancer risk (ICR) contributor (72%), whereas trace metals and vehicle exhaust sources contributed approximately 27% and 21% of PM10 inhalation non-cancer risk (INCR), respectively. The identified local sources accounted for approximately 80% of the ICR in Hong Kong, while contribution percentages of the non-local and local sources for INCR are comparable. The clear increase of ICR at high PM days was mainly attributed to the increase of contributions from coal combustion/biomass burning and secondary sulfate, while the increase of INCR at high PM days was attributed to the increase of contributions from the sources coal combustion/biomass burning, secondary nitrate, and trace metals. This study highlights the importance of health risk-based source apportionment in air quality management with protecting human health as the ultimate target.

The Effect of PM10 on Allergy Symptoms in Allergic Rhinitis Patients During Spring Season

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Il Gyu Kang

2015-01-01

Full Text Available Background: Asian sand dust (ASD that originates in the Mongolian Desert in the spring induces serious respiratory health problems throughout East Asia (China, Korea, Japan. PM10 (particulate matter with an aerodynamic diameter <10 μm is a major air pollutant component in ASD. We studied the effects of PM10 on allergy symptoms in patients with allergic rhinitis during the spring season, when ASD frequently develops. Methods: We investigated the changes in allergic symptoms in 108 allergic patients and 47 healthy subjects by comparing their 120-day symptom scores from February to May 2012. At the same time, the contributions of pollen count and PM10 concentration were also assessed. We also compared symptom scores before and 2 days after the daily PM10 concentration was >100 μg/m3. Results: The PM10 concentration during the 120 days was <150 μg/m3. No significant correlations were observed between changes in the PM10 concentration and allergic symptom scores (p > 0.05. However, allergic symptoms were significantly correlated with outdoor activity time (p < 0.001. Conclusions: These results demonstrate that a PM10 concentration <150 μg/m3 did not influence allergy symptoms in patients with allergic rhinitis during the 2012 ASD season.

Análisis del origen de PM10 y PM2.5 en Bogotá usando gráficos polares (Analysis of the origin of PM10 and PM2.5 in Bogota by using polar plots

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Pedro Alejandro García Ávila

2016-09-01

Full Text Available Determinar la procedencia de los contaminantes del aire registrados por una red de monitoreo es fundamental para diseñar acciones de prevención y control de la contaminación. Con este fin, se analizaron, mediante la aplicación Openair®, los registros de material particulado (PM10 y PM2.5, velocidad y dirección de los vientos, en 10 estaciones de monitoreo de calidad del aire en Bogotá para el período 2009-2011, encontrándose la influencia de fuentes locales y regionales. Se determinaron altas concentraciones de material particulado relacionadas con velocidades de viento superiores a 5 m/s procedentes del occidente, lo cual sugiere un transporte regional de contaminantes desde los municipios vecinos del occidente de la ciudad (Soacha, Funza, Mosquera, Madrid, hacia su centro geográfico. Estos municipios concentran actividad industrial y transporte pesado de bienes desde y hacia Bogotá. Las fuentes localizadas al interior de la ciudad, en particular aquellas que emplean carbón como combustible y las fuentes móviles que transitan sobre las vías principales, contribuyen a generar altos niveles de material particulado cuando los vientos son débiles, pero en menor magnitud que las fuentes externas. (Abstract. The design of pollution prevention strategies and plans requires information about the origin of the pollutants. In this work, particulate matter (PM10 and PM2.5, wind speed and wind direction records from 10 air quality monitoring stations in Bogota between 2009 and 2011 were analyzed using Openair®. The influence of local and regional sources was established. High concentrations of particulate matter associated with wind speeds exceeding 5 m/s from the West were found, suggesting regional transport from the neighboring municipalities of Soacha, Funza, Mosquera and Madrid, towards its geographic center. These municipalities have a significant industrial activity and heavy transport of goods to and from Bogota. Sources located

Winter mass concentrations of carbon species in PM10, PM 2.5 and PM1 in Zagreb air, Croatia.

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Godec, Ranka; Čačković, Mirjana; Šega, Krešimir; Bešlić, Ivan

2012-11-01

The purpose of our investigation was to examine the mass concentrations of EC, OC and TC (EC + OC) in PM(10), PM(2.5) and PM(1) particle fractions. Daily PM(10), PM(2.5) and PM(1) samples were collected at an urban background monitoring site in Zagreb during winter 2009. Average OC and EC mass concentrations were 11.9 and 1.8 μg m(-3) in PM(10), 9.0 and 1.4 μg m(-3) in PM(2.5), and 5.5 and 1.1 μg m(-3) in PM(1). Average OC/EC ratios in PM(10), PM(2.5), and PM(1) were 7.4, 6.9 and 5.4, respectively.

40 CFR Table C-4 to Subpart C of... - Test Specifications for PM10, PM2.5 and PM10-2.5 Candidate Equivalent Methods

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2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Test Specifications for PM10, PM2.5 and PM10-2.5 Candidate Equivalent Methods C Table C-4 to Subpart C of Part 53 Protection of Environment... Pt. 53, Subpt. C, Table C-4 Table C-4 to Subpart C of Part 53—Test Specifications for PM10, PM2.5 and...

The impact of the "Air Pollution Prevention and Control Action Plan" on PM2.5 concentrations in Jing-Jin-Ji region during 2012-2020.

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Cai, Siyi; Wang, Yangjun; Zhao, Bin; Wang, Shuxiao; Chang, Xing; Hao, Jiming

2017-02-15

In order to cope with heavy haze pollution in China, the Air Pollution Prevention and Control Action Plan including phased goals of the fine particulate matter (PM 2.5 ) was issued in 2013. In this study, China's emission inventories in the baseline 2012 and the future scenarios of 2017 and 2020 have been developed based on this Action Plan. Beijing-Tianjin-Hebei (Jing-Jin-Ji) region, one of the most polluted regions in China, was taken as a case to assess the impact of phased emission control measures on PM 2.5 concentration reduction using WRF-CMAQ model system. With the implementation of the Action Plan, the emissions of sulfur dioxide (SO 2 ), nitrogen oxides (NO X ) , PM 2.5 , non-methane volatile organic compound (NMVOC), and ammonia (NH 3 ) in 2017 will decrease by36%, 31%, 30%,12%, and -10% from the 2012 levels in Jing-Jin-Ji, respectively. In 2020, the emissions of SO 2 , NO X, PM 2.5 , NMVOC, and NH 3 will decrease by 40%, 44%, 40%, 22%, and -3% from the 2012 levels in Jing-Jin-Ji, respectively. Consequently, the ambient annual PM 2.5 concentration under the scenarios of 2017 and 2020 will be 28.3% and 37.8% lower than those in 2012, respectively. The Action Plan provided an effective approach to alleviate PM 2.5 pollution level in Jing-Jin-Ji region. However, emission control of NMVOC and NH 3 should be paid more attention and be strengthened in future. Meanwhile, emission control of NO x , SO 2 , NH 3 and NMVOC synergistically are highly needed in the future because multiple pollutants impact on PM 2.5 and O 3 concentrations nonlinearly. Copyright © 2016 Elsevier B.V. All rights reserved.

Effects of air pollution on infant and children respiratory mortality in four large Latin-American cities

International Nuclear Information System (INIS)

Gouveia, Nelson; Junger, Washington Leite; Romieu, Isabelle; Cifuentes, Luis A.; Ponce de Leon, Antonio; Vera, Jeanette; Strappa, Valentina; Hurtado-Díaz, Magali; Miranda-Soberanis, Victor; Rojas-Bracho, Leonora; Carbajal-Arroyo, Luz; Tzintzun-Cervantes, Guadalupe

2018-01-01

Objectives: Air pollution is an important public health concern especially for children who are particularly susceptible. Latin America has a large children population, is highly urbanized and levels of pollution are substantially high, making the potential health impact of air pollution quite large. We evaluated the effect of air pollution on children respiratory mortality in four large urban centers: Mexico City, Santiago, Chile, and Sao Paulo and Rio de Janeiro in Brazil. Methods: Generalized Additive Models in Poisson regression was used to fit daily time-series of mortality due to respiratory diseases in infants and children, and levels of PM 10 and O 3 . Single lag and constrained polynomial distributed lag models were explored. Analyses were carried out per cause for each age group and each city. Fixed- and random-effects meta-analysis was conducted in order to combine the city-specific results in a single summary estimate. Results: These cities host nearly 43 million people and pollution levels were above the WHO guidelines. For PM 10 the percentage increase in risk of death due to respiratory diseases in infants in a fixed effect model was 0.47% (0.09–0.85). For respiratory deaths in children 1–5 years old, the increase in risk was 0.58% (0.08–1.08) while a higher effect was observed for lower respiratory infections (LRI) in children 1–14 years old [1.38% (0.91–1.85)]. For O 3 , the only summarized estimate statistically significant was for LRI in infants. Analysis by season showed effects of O 3 in the warm season for respiratory diseases in infants, while negative effects were observed for respiratory and LRI deaths in children. Discussion: We provided comparable mortality impact estimates of air pollutants across these cities and age groups. This information is important because many public policies aimed at preventing the adverse effects of pollution on health consider children as the population group that deserves the highest protection

Exposure to hazardous volatile organic compounds, PM 10 and CO while walking along streets in urban Guangzhou, China

Science.gov (United States)

Zhao, Lirong; Wang, Xinming; He, Qiusheng; Wang, Hao; Sheng, Guoying; Chan, L. Y.; Fu, Jiamo; Blake, D. R.

Toxic air pollutants in street canyons are important issues concerning public health especially in some large Asian cities like Guangzhou. In 1998 Guangzhou citizens used public transportation modes, with a majority commuting on foot (42%) or by bicycle (22%). Of the pedestrians, 57% were either senior citizens or students. In the present study, we measured toxic air pollutants while walking along urban streets in Guangzhou to evaluate pedestrian exposure. Volatile organic compounds (VOCs) were collected with sorbent tubes, and PM 10 and CO were measured simultaneously with portable analyzers. Our results showed that pedestrian exposure to PM 10 (with an average of 303 μg m -3 for all samples) and some toxic VOCs (for example, benzene) was relatively high. Monocyclic aromatic hydrocarbons were found to be the most abundant VOCs, and 71% of the samples had benzene levels higher than 30 μg m -3. Benzene, PM 10 and CO in walk-only streets were significantly lower ( ptransportation modes (bus and subway). The good correlations between BTEX, PM 10 and CO in the streets indicated that automotive emission might be their major source. Our study also showed that the risk to pedestrians due to air pollution was misinterpreted by the reported air quality index based on measurement of SO 2, NO x and PM 10 in the government monitoring stations. An urban roadside monitoring station might be needed by air quality monitoring networks in large Asian cities like Guangzhou, in order to survey exposure to air toxics in urban roadside microenvironments.

Household cooking with solid fuels contributes to ambient PM2.5 air pollution and the burden of disease.

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Chafe, Zoë A; Brauer, Michael; Klimont, Zbigniew; Van Dingenen, Rita; Mehta, Sumi; Rao, Shilpa; Riahi, Keywan; Dentener, Frank; Smith, Kirk R

2014-12-01

Approximately 2.8 billion people cook with solid fuels. Research has focused on the health impacts of indoor exposure to fine particulate pollution. Here, for the 2010 Global Burden of Disease project (GBD 2010), we evaluated the impact of household cooking with solid fuels on regional population-weighted ambient PM2.5 (particulate matter ≤ 2.5 μm) pollution (APM2.5). We estimated the proportion and concentrations of APM2.5 attributable to household cooking with solid fuels (PM2.5-cook) for the years 1990, 2005, and 2010 in 170 countries, and associated ill health. We used an energy supply-driven emissions model (GAINS; Greenhouse Gas and Air Pollution Interactions and Synergies) and source-receptor model (TM5-FASST) to estimate the proportion of APM2.5 produced by households and the proportion of household PM2.5 emissions from cooking with solid fuels. We estimated health effects using GBD 2010 data on ill health from APM2.5 exposure. In 2010, household cooking with solid fuels accounted for 12% of APM2.5 globally, varying from 0% of APM2.5 in five higher-income regions to 37% (2.8 μg/m3 of 6.9 μg/m3 total) in southern sub-Saharan Africa. PM2.5-cook constituted > 10% of APM2.5 in seven regions housing 4.4 billion people. South Asia showed the highest regional concentration of APM2.5 from household cooking (8.6 μg/m3). On the basis of GBD 2010, we estimate that exposure to APM2.5 from cooking with solid fuels caused the loss of 370,000 lives and 9.9 million disability-adjusted life years globally in 2010. PM2.5 emissions from household cooking constitute an important portion of APM2.5 concentrations in many places, including India and China. Efforts to improve ambient air quality will be hindered if household cooking conditions are not addressed.

PM10 Analysis for Three Industrialized Areas using Extreme Value

International Nuclear Information System (INIS)

Hasfazilah Ahmat; Ahmad Shukri Yahaya; Nor Azam Ramli; Hasfazilah Ahmat

2015-01-01

One of the concerns of the air pollution studies is to compute the concentrations of one or more pollutants' species in space and time in relation to the independent variables, for instance emissions into the atmosphere, meteorological factors and parameters. One of the most significant statistical disciplines developed for the applied sciences and many other disciplines for the last few decades is the extreme value theory (EVT). This study assesses the use of extreme value distributions of the two-parameter Gumbel, two and three-parameter Weibull, Generalized Extreme Value (GEV) and two and three-parameter Generalized Pareto Distribution (GPD) on the maximum concentration of daily PM10 data recorded in the year 2010 - 2012 in Pasir Gudang, Johor; Bukit Rambai, Melaka; and Nilai, Negeri Sembilan. Parameters for all distributions are estimated using the Method of Moments (MOM) and Maximum Likelihood Estimator (MLE). Six performance indicators namely; the accuracy measures which include predictive accuracy (PA), Coefficient of Determination (R2), Index of Agreement (IA) and error measures that consist of Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Normalized Absolute Error (NAE) are used to find the goodness-of-fit of the distribution. The best distribution is selected based on the highest accuracy measures and the smallest error measures. The results showed that the GEV is the best fit for daily maximum concentration for PM10 for all monitoring stations. The analysis also demonstrates that the estimated numbers of days in which the concentration of PM10 exceeded the Malaysian Ambient Air Quality Guidelines (MAAQG) of 150 mg/ m"3 are between 1/2 and 11/2 days. (author)

A system dynamics model of China's electric power structure adjustment with constraints of PM10 emission reduction.

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Guo, Xiaopeng; Ren, Dongfang; Guo, Xiaodan

2018-06-01

Recently, Chinese state environmental protection administration has brought out several PM10 reduction policies to control the coal consumption strictly and promote the adjustment of power structure. Under this new policy environment, a suitable analysis method is required to simulate the upcoming major shift of China's electric power structure. Firstly, a complete system dynamics model is built to simulate China's evolution path of power structure with constraints of PM10 reduction considering both technical and economical factors. Secondly, scenario analyses are conducted under different clean-power capacity growth rates to seek applicable policy guidance for PM10 reduction. The results suggest the following conclusions. (1) The proportion of thermal power installed capacity will decrease to 67% in 2018 with a dropping speed, and there will be an accelerated decline in 2023-2032. (2) The system dynamics model can effectively simulate the implementation of the policy, for example, the proportion of coal consumption in the forecast model is 63.3% (the accuracy rate is 95.2%), below policy target 65% in 2017. (3) China should promote clean power generation such as nuclear power to meet PM10 reduction target.

PM 10, PM 2.5 and PM 1.0—Emissions from industrial plants—Results from measurement programmes in Germany

Science.gov (United States)

Ehrlich, C.; Noll, G.; Kalkoff, W.-D.; Baumbach, G.; Dreiseidler, A.

Emission measurement programmes were carried out at industrial plants in several regions of Germany to determine the fine dust in the waste gases; the PM 10, PM 2.5 and PM 1.0 fractions were sampled using a cascade impactor technique. The installations tested included plants used for: combustion (brown coal, heavy fuel oil, wood), cement production, glass production, asphalt mixing, and processing plants for natural stones and sand, ceramics, metallurgy, chemical production, spray painting, wood processing/chip drying, poultry farming and waste treatment. In addition waste gas samples were taken from small-scale combustion units, like domestic stoves, firing lignite briquettes or wood. In total 303 individual measurement results were obtained during 106 different measurement campaigns. In the study it was found that in more than 70% of the individual emission measurement results from industrial plants and domestic stoves the PM 10 portion amounted to more than 90% and the PM 2.5 portion between 50% and 90% of the total PM (particulate matter) emission. For thermal industrial processes the PM 1.0 portion constituted between 20% and 60% of the total PM emission. Typical particle size distributions for different processes were presented as cumulative frequency distributions and as frequency distributions. The particle size distributions determined for the different plant types show interesting similarities and differences depending on whether the processes are thermal, mechanical, chemical or mixed. Consequently, for the groups of plant investigated, a major finding of this study has been that the particle size distribution is a characteristic of the industrial process. Attempts to correlate particle size distributions of different plants to different gas cleaning technologies did not lead to usable results.

Modeled PM2.5 removal by trees in ten U.S. cities and associated health effects

International Nuclear Information System (INIS)

Nowak, David J.; Hirabayashi, Satoshi; Bodine, Allison; Hoehn, Robert

2013-01-01

Urban particulate air pollution is a serious health issue. Trees within cities can remove fine particles from the atmosphere and consequently improve air quality and human health. Tree effects on PM 2.5 concentrations and human health are modeled for 10 U.S. cities. The total amount of PM 2.5 removed annually by trees varied from 4.7 tonnes in Syracuse to 64.5 tonnes in Atlanta, with annual values varying from $1.1 million in Syracuse to $60.1 million in New York City. Most of these values were from the effects of reducing human mortality. Mortality reductions were typically around 1 person yr −1 per city, but were as high as 7.6 people yr −1 in New York City. Average annual percent air quality improvement ranged between 0.05% in San Francisco and 0.24% in Atlanta. Understanding the impact of urban trees on air quality can lead to improved urban forest management strategies to sustain human health in cities. -- Highlights: •Paper provides the first broad-scale estimates of city-wide tree impacts on PM 2.5 . •Trees improve overall air quality by intercepting particulate matter. •Particle resuspension can lead to short-term increases in pollutant concentrations. •Urban trees produce substantial health improvements and values. -- Air pollution modeling reveals broad-scale impacts of pollution removal by urban trees on PM 2.5 concentrations and human health

Strong signatures of high-latitude blocks and subtropical ridges in winter PM10 over Europe

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Ordonez, C.; Garrido-Perez, J. M.; Garcia-Herrera, R.

2017-12-01

Atmospheric blocking is associated with persistent, slow-moving high pressure systems that interrupt the eastward progress of extratropical storm systems at middle and high latitudes. Subtropical ridges are low latitude structures manifested as bands of positive geopotential height anomalies extending from sub-tropical latitudes towards extra-tropical regions. We have quantified the impact of blocks and ridges on daily PM10 (particulate matter ≤ 10 µm) observations obtained from the European Environment Agency's air quality database (AirBase) for the winter period of 2000-2010. For this purpose, the response of the PM10 concentrations to the location of blocks and ridges with centres in two main longitudinal sectors (Atlantic, ATL, 30˚-0˚ W; European, EUR, 0˚-30˚ E) is examined. EUR blocking is associated with a collapse of the boundary layer as well as reduced wind speeds and precipitation occurrence, yielding large positive anomalies which average 12 µg m-3 over the whole continent. Conversely, the enhanced zonal flow around 50˚-60˚ N and the increased occurrence of precipitation over northern-central Europe on days with ATL ridges favour the ventilation of the boundary layer and the impact of washout processes, reducing PM10 concentrations on average by around 8 µg m-3. The presence of EUR blocks is also concurrent with an increased probability of exceeding the European air quality target (50 µg m-3 for 24-h averaged PM10) and the local 90th percentiles for this pollutant at many sites, while the opposite effect is found for ridges. In addition, the effect of synoptic persistence on the PM10 concentrations is particularly strong for EUR blocks. Finally, we have found that the effect of both synoptic patterns can partly control the interannual variability of winter mean PM10 at many sites of north-western and central Europe, with coefficients of determination (R2) exceeding 0.80 for southern Germany. These results indicate that the response of the

The local contribution of wood burning to PM10 and PM2.5; De lokale bijdrage van houtverbranding aan PM10 en PM2,5

Energy Technology Data Exchange (ETDEWEB)

Kos, G.; Weijers, E. [ECN Biomassa, Kolen en Milieuonderzoek, Petten (Netherlands)

2011-04-15

In January 2009, the concentrations of wood smoke in Schoorl, the Netherlands, were established by means of levoglucosan measurements (a hydrocarbon compound that is characteristic for wood smoke). Local wood smoke contributes significantly to the concentration of particulate matter: between 9% and 27% for PM10 and between 30% and 29% for PM2.5. [Dutch] In februari 2009 zijn in Schoorl in Noord-Holland concentraties houtrook bepaald door levoglucosanmetingen (een voor houtrook kenmerkende koolwaterstofverbinding). Lokale houtrook draagt daar significant bij aan de concentratie fijn stof: tussen 9% en 27% voor PM10 en tussen 30% en 39% voor PM2,5.

Development of Land Use Regression models for particulate matter and associated components in a low air pollutant concentration airshed

NARCIS (Netherlands)

Dirgawati, Mila; Heyworth, Jane S.; Wheeler, Amanda J.; McCaul, Kieran A.; Blake, David; Boeyen, Jonathon; Cope, Martin; Yeap, Bu Beng; Nieuwenhuijsen, Mark; Brunekreef, Bert|info:eu-repo/dai/nl/067548180; Hinwood, Andrea

2016-01-01

Perth, Western Australia represents an area where pollutant concentrations are considered low compared with international locations. Land Use Regression (LUR) models for PM10, PM2.5 and PM2.5 Absorbance (PM2.5Abs) along with their elemental components: Fe, K, Mn, V, S, Zn and Si were developed for

Bioaccessibility of selected trace metals in urban PM{sub 2.5} and PM{sub 10} samples: a model study

Energy Technology Data Exchange (ETDEWEB)

Falta, Thomas; Koellensperger, Gunda; Hann, Stephan [University of Natural Resources and Applied Life Sciences, Division of Analytical Chemistry, Vienna (Austria); Limbeck, Andreas [Vienna University of Technology, Institute of Chemical Technologies and Analytics, Vienna (Austria)

2008-02-15

Bioaccessibility of trace metals originating from urban particulate matter was assessed in a worst case scenario to evaluate the uptake and thus the hazardous potential of these metals via gastric juice. Sampling was performed over a period of about two months at the Getreidemarkt in downtown Vienna. Concentrations of the assayed trace metals (Ti, Cr, Mn, Co, Ni, Cu, Zn, Mo, Ag, Cd, Sn, Sb, Tl and Pb) were determined in PM{sub 2.5} and PM{sub 10} samples by ICP-MS. The metal concentrations in sampled air were in the low picogram to high nanogram per cubic metre range. The concentrations in PM{sub 2.5} samples were generally lower than those in PM{sub 10} samples. The average daily intake of these metals by inhalation for a healthy adult was estimated to be in the range of <1 ng (Tl) to >1,000 ng (Zn). To estimate the accessibility of the inhaled and subsequently ingested metals (i.e. after lung clearance had taken place) in the size range from 2.5- to 10-{mu}m aerodynamic equivalent diameter, a batch-extraction with synthetic gastric juice was performed. The data were used to calculate the bioaccessibility of the investigated trace metals. Extractable fractions ranged from 2.10% (Ti in PM{sub 2.5}) to 91.0% (Cd in PM{sub 2.5}), thus yielding bioaccessible fractions (PM{sub 2.5-10}) from 0.16 ng (Ag) to 178 ng (Cu). (orig.)

Preliminary analysis of variability in concentration of fine particulate matter - PM1.0, PM2.5 and PM10 in area of Poznań city

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Sówka Izabela

2018-01-01

Full Text Available It is commonly known, that suspended particulate matter pose a threat to human life and health, negatively influence the flora, climate and also materials. Especially dangerous is the presence of high concentration of particulate matter in the area of cities, where density of population is high. The research aimed at determining the variability of suspended particulate matter concentration (PM1.0, PM2.5 and PM10 in two different thermal seasons, in the area of Poznań city. As a part of carried out work we analyzed the variability of concentrations and also performed a preliminary analysis of their correlation. Measured concentrations of particulate matter were contained within following ranges: PM10 – 8.7-69.6 μg/m3, PM2.5 – 2.2-88.5 μg/m3, PM1.0 – 2.5-22.9 μg/m3 in the winter season and 1.0-42.8 μg/m3 (PM10, 1.2-40.3 μg/m3 (PM2.5 and 2.7-10.4 (PM1.0 in the summer season. Preliminary correlative analysis indicated interdependence between the temperature of air, the speed of wind and concentration of particulate matter in selected measurement points. The values of correlation coefficients between the air temperature, speed of wind and concentrations of particulate matter were respectively equal to: for PM10: -0.59 and -0.55 (Jana Pawła II Street, -0.53 and -0.53 (Szymanowskiego Street, for PM2.5: -0.60 and -0.53 (Jana Pawła II Street and for PM1.0 -0.40 and -0.59 (Jana Pawła II Street.

Composition of PM2.5 and PM1 on high and low pollution event days and its relation to indoor air quality in a home for the elderly.

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Buczyńska, Anna J; Krata, Agnieszka; Van Grieken, Rene; Brown, Andrew; Polezer, Gabriela; De Wael, Karolien; Potgieter-Vermaak, Sanja

2014-08-15

Many studies probing the link between air quality and health have pointed towards associations between particulate matter (PM) exposure and decreased lung function, aggravation of respiratory diseases like asthma, premature death and increased hospitalisation admissions for the elderly and individuals with cardiopulmonary diseases. Of recent, it is believed that the chemical composition and physical properties of PM may contribute significantly to these adverse health effects. As part of a Belgian Science Policy project ("Health effects of particulate matter in relation to physical-chemical characteristics and meteorology"), the chemical composition (elemental and ionic compositions) and physical properties (PM mass concentrations) of PM were investigated, indoors and outdoors of old age homes in Antwerp. The case reported here specifically relates to high versus normal/low pollution event periods. PM mass concentrations for PM1 and PM2.5 fractions were determined gravimetrically after collection via impaction. These same samples were hence analysed by EDXRF spectrometry and IC for their elemental and ionic compositions, respectively. During high pollution event days, PM mass concentrations inside the old age home reached 53 μg m(-3) and 32 μg m(-3) whilst outside concentrations were 101 μg m(-3) and 46 μg m(-3) for PM2.5 and PM1, respectively. The sum of nss-sulphate, nitrate and ammonium, dominate the composition of PM, and contribute the most towards an increase in the PM during the episode days constituting 64% of ambient PM2.5 (52 μg m(-3)) compared to 39% on non-episode days (10 μg m(-3)). Other PM components, such as mineral dust, sea salt or heavy metals were found to be considerably higher during PM episodes but relatively less important. Amongst heavy metals Zn and Pb were found at the highest concentrations in both PM2.5 and PM1. Acid-base ionic balance equations were calculated and point to acidic aerosols during event days and acidic to alkaline

Association between PM10 concentrations and school absences in proximity of a cement plant in northern Italy.

Science.gov (United States)

Marcon, Alessandro; Pesce, Giancarlo; Girardi, Paolo; Marchetti, Pierpaolo; Blengio, Gianstefano; de Zolt Sappadina, Simona; Falcone, Salvatore; Frapporti, Guglielmo; Predicatori, Francesca; de Marco, Roberto

2014-03-01

Dusts are one of the main air pollutants emitted during cement manufacturing. A substantial part of these are breathable particles that are less than 10 μm in diameter (PM10), which represent a potential threat for the health of the exposed population. This study aimed at evaluating the short-term effects of PM10 concentrations on the health of children, aged 6-14 years, who attended the schools in Fumane (Italy), in proximity (1.2 km) to a large cement plant. School absenteeism was used as a proxy indicator of child morbidity. Time series of daily school absences and PM10 concentrations were collected for 3 school-years from 2007 to 2010 (541 school-days, 462 children on average). The associations between PM10 concentrations and school absence rates in the same day (lag0) and in the following 4 days (lag1 to lag4) were evaluated using generalised additive models, smoothed for medium/long term trends and adjusted for day of the week, influenza outbreaks, daily temperature and rain precipitations. The average concentration of PM10 in the period was 34 (range: 4-183) μg/m(3). An average 10 μg/m(3) increase of PM10 concentration in the previous days (lag0-4) was associated with a statistically significant 2.5% (95%CI: 1.1-4.0%) increase in the rate of school absences. The highest increase in the absence rates (2.4%; 95%CI: 1.2-3.5%) was found 2 days after exposure (lag2). These findings provide epidemiological evidence of the acute health effects of PM10 in areas with annual concentrations that are lower than the legal European Union limit of 40 μg/m(3), and support the need to establish more restrictive legislative standards. Copyright © 2013 Elsevier GmbH. All rights reserved.

Milano summer particulate matter (PM10 triggers lung inflammation and extra pulmonary adverse events in mice.

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Francesca Farina

Full Text Available Recent studies have suggested a link between particulate matter (PM exposure and increased mortality and morbidity associated with pulmonary and cardiovascular diseases; accumulating evidences point to a new role for air pollution in CNS diseases. The purpose of our study is to investigate PM10sum effects on lungs and extra pulmonary tissues. Milano PM10sum has been intratracheally instilled into BALB/c mice. Broncho Alveolar Lavage fluid, lung parenchyma, heart and brain were screened for markers of inflammation (cell counts, cytokines, ET-1, HO-1, MPO, iNOS, cytotoxicity (LDH, ALP, Hsp70, Caspase8-p18, Caspase3-p17 for a putative pro-carcinogenic marker (Cyp1B1 and for TLR4 pathway activation. Brain was also investigated for CD68, TNF-α, GFAP. In blood, cell counts were performed while plasma was screened for endothelial activation (sP-selectin, ET-1 and for inflammation markers (TNF-α, MIP-2, IL-1β, MPO. Genes up-regulation (HMOX1, Cyp1B1, IL-1β, MIP-2, MPO and miR-21 have been investigated in lungs and blood. Inflammation in the respiratory tract of PM10sum-treated mice has been confirmed in BALf and lung parenchyma by increased PMNs percentage, increased ET-1, MPO and cytokines levels. A systemic spreading of lung inflammation in PM10sum-treated mice has been related to the increased blood total cell count and neutrophils percentage, as well as to increased blood MPO. The blood-endothelium interface activation has been confirmed by significant increases of plasma ET-1 and sP-selectin. Furthermore PM10sum induced heart endothelial activation and PAHs metabolism, proved by increased ET-1 and Cyp1B1 levels. Moreover, PM10sum causes an increase in brain HO-1 and ET-1. These results state the translocation of inflammation mediators, ultrafine particles, LPS, metals associated to PM10sum, from lungs to bloodstream, thus triggering a systemic reaction, mainly involving heart and brain. Our results provided additional insight into the toxicity

Is ozone, rather than PM2.5, actually the largest contributor to premature deaths associated with trans-continental transport of air pollution?

Science.gov (United States)

Henze, D. K.; Davila, Y.; Anenberg, S.; Malley, C.; Kuylenstierna, J. C. I.; Vallack, H.; Ashmore, M. R.; Turner, M.; Sudo, K.; Jonson, J. E.; Chin, M.; Doherty, R. M.

2017-12-01

While both ozone and PM2.5 contribute to a range of deleterious human health impacts, evaluations of regional and global burdens of disease associated with exposure to these pollutants have concluded that PM2.5 is the larger driver of premature deaths from degraded air quality. This is owing to both high PM2.5 concentrations in heavily populated areas and stronger concentration-response relationships between PM2.5 exposure and increased mortality risk. Meanwhile, both PM2.5 and O3 are formed and/or advected far downwind of their sources and contribute to long-range (trans-continental) pollution transport. Ozone most often makes greater contributions to long-range pollution transport in terms of percent changes in surface-level concentrations given its longer tropospheric lifetime than PM2.5. Combining these factors, previous works have identified PM2.5 as more frequently being the dominant long-range source of air pollution related premature deaths, closely followed by O3. Here we re-evaluate this question using several updates, drawing from ensembles of model simulations performed as part of Phase 2 of the Hemispheric Transport of Air Pollutants (HTAP) project. Most importantly, we use recently revised concentration-response relationships for respiratory (and, less confidently, cardiovascular) disease associated with long-term O3 exposure, which we have shown increases estimates of premature death owing to O3 several-fold, and integrated exposure response (IER) functions for PM2.5. Further, we attempt to overcome well-recognized biases in estimating PM2.5 exposure with global-scale models via assimilation of high resolution (0.1 x 0.1) maps of surface PM2.5 derived from satellite observations. Overall, we find that our revised estimates of long-range O3 and PM2.5 related premature deaths are most often dominated by O3. These findings provide additional incentives for considering the global-scale consequences of regional emissions controls of O3 precursors.

Air pollution exposure, cause-specific deaths and hospitalizations in a highly polluted Italian region.

Science.gov (United States)

Carugno, Michele; Consonni, Dario; Randi, Giorgia; Catelan, Dolores; Grisotto, Laura; Bertazzi, Pier Alberto; Biggeri, Annibale; Baccini, Michela

2016-05-01

The Lombardy region in northern Italy ranks among the most air polluted areas of Europe. Previous studies showed air pollution short-term effects on all-cause mortality. We examine here the effects of particulate matter with aerodynamic diameter ≤10µm (PM10) and nitrogen dioxide (NO2) exposure on deaths and hospitalizations from specific causes, including cardiac, cerebrovascular and respiratory diseases. We considered air pollution, mortality and hospitalization data for a non-opportunistic sample of 18 highly polluted and most densely populated areas of the region in the years 2003-2006. We obtained area-specific effect estimates for PM10 and NO2 from a Poisson regression model on the daily number of total deaths or cause-specific hospitalizations and then combined them in a Bayesian random-effects meta-analysis. For cause-specific mortality, we applied a case-crossover analysis. Age- and season-specific analyses were also performed. Effect estimates were expressed as percent variation in mortality or hospitalizations associated with a 10µg/m(3) increase in PM10 or NO2 concentration. Natural mortality was positively associated with both pollutants (0.30%, 90% Credibility Interval [CrI]: -0.31; 0.78 for PM10; 0.70%, 90%CrI: 0.10; 1.27 for NO2). Cardiovascular deaths showed a higher percent variation in association with NO2 (1.12%, 90% Confidence Interval [CI]: 0.14; 2.11), while the percent variation for respiratory mortality was highest in association with PM10 (1.64%, 90%CI: 0.35; 2.93). The effect of both pollutants was more evident in the summer season. Air pollution was also associated to hospitalizations, the highest variations being 0.77% (90%CrI: 0.22; 1.43) for PM10 and respiratory diseases, and 1.70% (90%CrI: 0.39; 2.84) for NO2 and cerebrovascular diseases. The effect of PM10 on respiratory hospital admissions appeared to increase with age. For both pollutants, effects on cerebrovascular hospitalizations were more evident in subjects aged less than

Mortality and morbidity due to exposure to outdoor air pollution in Mashhad metropolis, Iran. The AirQ model approach.

Science.gov (United States)

Miri, Mohammad; Derakhshan, Zahra; Allahabadi, Ahmad; Ahmadi, Ehsan; Oliveri Conti, Gea; Ferrante, Margherita; Aval, Hamideh Ebrahimi

2016-11-01

In the past two decades, epidemiological studies have shown that air pollution is one of the causes of morbidity and mortality. In this study the effect of PM10, PM2.5, NO2, SO2 and O3 pollutants on human health among the inhabitants of Mashhad has been evaluated. To evaluate the health effects due to air pollution, the AirQ model software 3.3.2, developed by WHO European Centre for Environment and Health, was used. The daily data related to the pollutants listed above has been used for the short term health effects (total mortality, cardiovascular and respiratory mortality, hospitalization due to cardiovascular and respiratory diseases, chronic obstructive pulmonary disease and acute myocardial infarction). PM2.5 had the most health effects on Mashhad inhabitants. With increasing in each 10μg/m3, relative risk rate of pollutant concentration for total mortality due to PM10, PM2.5, SO 2 , NO 2 and O 3 was increased of 0.6%, 1.5%, 0.4%, 0.3% and 0.46% respectively and, the attributable proportion of total mortality attributed to these pollutants was respectively equal to 4.24%, 4.57%, 0.99%, 2.21%, 2.08%, and 1.61% (CI 95%) of the total mortality (correct for the non-accident) occurred in the year of study. The results of this study have a good compatibly with other studies conducted on the effects of air pollution on humans. The AirQ software model can be used in decision-makings as a useful and easy tool. Copyright © 2016 Elsevier Inc. All rights reserved.

External costs of PM2.5 pollution in Beijing, China: Uncertainty analysis of multiple health impacts and costs.

Science.gov (United States)

Yin, Hao; Pizzol, Massimo; Xu, Linyu

2017-07-01

Some cities in China are facing serious air pollution problems including high concentrations of particles, SO 2 and NO x . Exposure to PM2.5, one of the primary air pollutants in many cities in China, is highly correlated with various adverse health impacts and ultimately represents a cost for society. The aim of this study is to assess health impacts and external costs related to PM2.5 pollution in Beijing, China with different baseline concentrations and valuation methods. The idea is to provide a reasonable estimate of the total health impacts and external cost due to PM2.5 pollution, as well as a quantification of the relevant uncertainty. PM2.5 concentrations were retrieved for the entire 2012 period in 16 districts of Beijing. The various PM2.5 related health impacts were identified and classified to avoid double counting. Exposure-response coefficients were then obtained from literature. Both the value of statistical life (VSL) and the amended human capital (AHC) approach were applied for external costs estimation, which could provide the upper and lower bound of the external costs due to PM2.5. To fully understand the uncertainty levels, the external cost distribution was determined via Monte Carlo simulation based on the uncertainty of the parameters such as PM2.5 concentration, exposure-response coefficients, and economic cost per case. The results showed that the external costs were equivalent to around 0.3% (AHC, China's guideline: C 0  = 35 μg/m 3 ) to 0.9% (VSL, WHO guideline: C 0  = 10 μg/m 3 ) of regional GDP depending on the valuation method and on the assumed baseline PM2.5 concentration (C 0 ). Among all the health impacts, the economic loss due to premature deaths accounted for more than 80% of the overall external costs. The results of this study could help policymakers prioritizing the PM2.5 pollution control interventions and internalize the external costs through the application of economic policy instruments. Copyright © 2017

Characterization of PM10 sources in the central Mediterranean

Science.gov (United States)

Calzolai, G.; Nava, S.; Lucarelli, F.; Chiari, M.; Giannoni, M.; Becagli, S.; Traversi, R.; Marconi, M.; Frosini, D.; Severi, M.; Udisti, R.; di Sarra, A.; Pace, G.; Meloni, D.; Bommarito, C.; Monteleone, F.; Anello, F.; Sferlazzo, D. M.

2015-12-01

The Mediterranean Basin atmosphere is influenced by both strong natural and anthropogenic aerosol emissions and is also subject to important climatic forcings. Several programs have addressed the study of the Mediterranean basin; nevertheless important pieces of information are still missing. In this framework, PM10 samples were collected on a daily basis on the island of Lampedusa (35.5° N, 12.6° E; 45 m a.s.l.), which is far from continental pollution sources (the nearest coast, in Tunisia, is more than 100 km away). After mass gravimetric measurements, different portions of the samples were analyzed to determine the ionic content by ion chromatography (IC), the soluble metals by inductively coupled plasma atomic emission spectrometry (ICP-AES), and the total (soluble + insoluble) elemental composition by particle-induced x-ray emission (PIXE). Data from 2007 and 2008 are used in this study. The Positive Matrix Factorization (PMF) model was applied to the 2-year long data set of PM10 mass concentration and chemical composition to assess the aerosol sources affecting the central Mediterranean basin. Seven sources were resolved: sea salt, mineral dust, biogenic emissions, primary particulate ship emissions, secondary sulfate, secondary nitrate, and combustion emissions. Source contributions to the total PM10 mass were estimated to be about 40 % for sea salt, around 25 % for mineral dust, 10 % each for secondary nitrate and secondary sulfate, and 5 % each for primary particulate ship emissions, biogenic emissions, and combustion emissions. Large variations in absolute and relative contributions are found and appear to depend on the season and on transport episodes. In addition, the secondary sulfate due to ship emissions was estimated and found to contribute by about one-third to the total sulfate mass. Results for the sea-salt and mineral dust sources were compared with estimates of the same contributions obtained from independent approaches, leading to an

Air Pollution and Deaths among Elderly Residents of São Paulo, Brazil: An Analysis of Mortality Displacement.

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Costa, Amine Farias; Hoek, Gerard; Brunekreef, Bert; Ponce de Leon, Antônio C M

2017-03-01

Evaluation of short-term mortality displacement is essential to accurately estimate the impact of short-term air pollution exposure on public health. We quantified mortality displacement by estimating single-day lag effects and cumulative effects of air pollutants on mortality using distributed lag models. We performed a daily time series of nonaccidental and cause-specific mortality among elderly residents of São Paulo, Brazil, between 2000 and 2011. Effects of particulate matter smaller than 10 μm (PM 10 ), nitrogen dioxide (NO 2 ) and carbon monoxide (CO) were estimated in Poisson generalized additive models. Single-day lag effects of air pollutant exposure were estimated for 0-, 1- and 2-day lags. Distributed lag models with lags of 0-10, 0-20 and 0-30 days were used to assess mortality displacement and potential cumulative exposure effects. PM 10 , NO 2 and CO were significantly associated with nonaccidental and cause-specific deaths in both single-day lag and cumulative lag models. Cumulative effect estimates for 0-10 days were larger than estimates for single-day lags. Cumulative effect estimates for 0-30 days were essentially zero for nonaccidental and circulatory deaths but remained elevated for respiratory and cancer deaths. We found evidence of mortality displacement within 30 days for nonaccidental and circulatory deaths in elderly residents of São Paulo. We did not find evidence of mortality displacement within 30 days for respiratory or cancer deaths. Citation: Costa AF, Hoek G, Brunekreef B, Ponce de Leon AC. 2017. Air pollution and deaths among elderly residents of São Paulo, Brazil: an analysis of mortality displacement. Environ Health Perspect 125:349-354; http://dx.doi.org/10.1289/EHP98.

Analysis of Particulate matter (PM 10 and PM 2.5 concentration in Khorramabad city

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Seyed Hamed Mirhosseini

2013-01-01

Full Text Available Aims: In this study, the concentration of PM10 and PM2.5 in eight station of Khorramabad city was analyzed. Materials and Methods: For this study, the data were taken from April 2010 to March 2011. The eight sampling point were chosen in account to Khorramabad maps. During this period, 240 daily PM samples including coarse particle (PM 10 and fine particle (PM 2.5 were collected. A two-part sampler was used to collect samples of PM. According to one-way ANOVA, multiple comparisons Scheffe, the obtained data were analyzed and then compared with the Environment protection organization standard rates. Khorramabad Results: The results revealed that during measuring the maximum concentration of PM 10 and PM 2.5 was respectively 120.9 and 101.09 μ/m 3 at Shamshirabad station. There was a significant difference between the mean values of PM 10 concentration (μg/m 3 in the seasons of summer. In addition, the mean concentrations of PM 10 in warmer months exceeded to the maximum permissible concentration. Conclusions: Year comparison of PM 10 and PM 2.5 concentration with standard were revealed particle matter concentration in summer season was higher than standard. Although total mean of particle matter was less than standard concentration.

Study and evaluation of atmospheric pollution in Spain: necessary measures arising from the EC Directive on PM10 and PM2.5 particles in the Ceramic industry

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Rodríguez, S.

2000-02-01

Full Text Available The European Commission Directive, 1999/30/EC, approved on the 22nd of April 1999, on atmospheric particles establishes a standard that is more stringent than the current one. This Directive proposes the monitoring of particles lower than 10 μm (PM10, thoracic particles based on health impact criteria. The proposed EC limits are 40 μgPM10.m-3 and 20 μgPM10.m-3 as annual means in 2005 and 2010, respectively. In accordance with the European Commission (EC, the future PM10 limits will be revised in 2003 if the European States can demonstrate that the exceedances of the new limits are attributed to natural inputs. The exceedances due to natural inputs are more frequent in Mediterranean countries due to the re-suspension of natural soil particles and to the higher frequency of Saharan air mass intrusions. This study summarises the preliminary results obtained from two research projects in Spain focused on: 1 establishing the criteria for the discrimination of natural/anthropogenic inputs of PM10; 2 identifying the events when the proposed limits are exceeded by natural inputs and 3 determining the most suitable monitoring parameter, PM10 or PM2.5, in order to avoid natural interference. Given the importance of the ceramic industry in Castelló, special attention will be placed on the preliminary results obtained this area.La Directiva de la comisión Europea, 1999/30/CE, aprobada el 22 de Abril de 1999, referida a partículas atmosféricas en suspensión, establece una normativa más estricta que la vigente. Esta normativa propone el control de las partículas inferiores a 10 μm (PM10, partículas torácicas basándose en criterios de impacto en la salud. Según esta directiva no se podrán superar medias diarias anuales de 40 μgPM10.m-3 en el 2005 y de 20 μgPM10.m-3 en el 2010. La directiva contempla la revisión de los límites normativos y de los parámetros de control en el 2003, pudiendo variar estos en el caso de que los Estados miembros

Characteristics and classification of PM2.5 pollution episodes in Beijing from 2013 to 2015.

Science.gov (United States)

Wang, Xiaoqi; Wei, Wei; Cheng, Shuiyuan; Li, Jianbing; Zhang, Hanyu; Lv, Zhe

2018-01-15

During the period of 2013-2015, a total of 34 PM 2.5 pollution episodes occurred in Beijing, each of which remained for at least 2days. Among that, 28 times occurred in winter half year with the average concentration of 243.1μg/m 3 and summer half year with the average concentration of 194.1μg/m 3 . These episodes were mainly associated with lower wind speed and lower visibility as well as higher relative humidity, indicating that they belonged to heavy pollution under static stability. The PM 2.5 pollution was classified into two categories according to the back trajectory analysis and meteorological background field. Category I, accounting for 22 times among all the pollution episodes, was due to air mass transport from Beijing's southern regions with north-south direction pressure gradient and sparse isopiestic. And category II was mainly led by northwestern air masses accompanied with a large area of uniform pressure field. Then, a typical case study was conducted for each category to recognize the sub-region contribution to Beijing's PM 2.5 pollution based on WRF-CAMx modeling system, and the simulation results indicated that local emission source contribution decreased significantly during the accumulation phase for category I, but increased during that of category II, with an average contribution of 47.3% and 77.1% during the entire pollution period of each category, respectively. Two red alerts of air pollution occurred in December 2015 were also analyzed based on the episode classification. It was found that the second red alert pollution episode belonged to category II. The emission control measures in Beijing worked more obviously with the reduction effect ratio of 15.4% compared to the first red alert period (9.7%). Copyright © 2017 Elsevier B.V. All rights reserved.

Adverse health effects of air pollutants in a nonsmoking population.

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Pope, C A

1996-07-17

Utah Valley has provided an interesting and unique opportunity to evaluate the health effects of respirable particulate air pollution (PM10). Residents of this valley are predominantly nonsmoking members of the Church of Jesus Christ of Latter-day Saints (Mormons). The area has moderately high average PM10 levels with periods of highly elevated PM10 concentrations due to local emissions being trapped in a stagnant air mass near the valley floor during low-level temperature inversion episodes. Due to a labor dispute, there was intermittent operation of the single largest pollution source, an old integrated steel mill. Levels of other common pollutants including sulfur dioxide, ozone, and acidic aerosol are relatively low. Studies specific to Utah Valley have observed that elevated PM10 concentrations are associated with: (1) decreased lung function; (2) increased incidence of respiratory symptoms; (3) increased school absenteeism; (4) increased respiratory hospital admissions; and (5) increased mortality, especially respiratory and cardiovascular mortality.

Mapping and Assessment of PM10 and O3 Removal by Woody Vegetation at Urban and Regional Level

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Lina Fusaro

2017-08-01

Full Text Available This study is the follow up of the URBAN-MAES pilot implemented in the framework of the EnRoute project. The study aims at mapping and assessing the process of particulate matter (PM10 and tropospheric ozone (O3 removal by various forest and shrub ecosystems. Different policy levels and environmental contexts were considered, namely the Metropolitan city of Rome and, at a wider level, the Latium region. The approach involves characterization of the main land cover and ecosystems using Sentinel-2 images, enabling a detailed assessment of Ecosystem Service (ES, and monetary valuation based on externality values. The results showed spatial variations in the pattern of PM10 and O3 removal inside the Municipality and in the more rural Latium hinterland, reflecting the spatial dynamics of the two pollutants. Evergreen species displayed higher PM10 removal efficiency, whereas deciduous species showed higher O3 absorption in both rural and urban areas. The overall pollution removal accounted for 5123 and 19,074 Mg of PM10 and O3, respectively, with a relative monetary benefit of 161 and 149 Million Euro for PM10 and O3, respectively. Our results provide spatially explicit evidence that may assist policymakers in land-oriented decisions towards improving Green Infrastructure and maximizing ES provision at different governance levels.

Local contribution of wood combustion to PM10 and PM2.5; Lokale bijdrage van houtverbranding aan PM10 en PM2,5

Energy Technology Data Exchange (ETDEWEB)

Kos, G.; Weijers, E. [ECN Biomassa, Kolen en Milieuonderzoek, Petten (Netherlands)

2011-04-15

In February 2009 the concentration of wood smoke in a residential area in Schoorl (Noord-Holland, Netherlands) was investigated over a period of three weeks. The aim was to assess the effect of local particulate matter (PM) emissions - caused by heating with wood stoves in this area - on local PM concentration. [Dutch] In februari 2009 zijn in Schoorl in Noord-Holland concentraties houtrook bepaald door levoglucosanmetingen (een voor houtrook kenmerkende koolwaterstofverbinding). Lokale houtrook draagt daar significant bij aan de concentratie fijn stof: tussen 9% en 27% voor PM10 en tussen 30% en 39% voor PM2,5.

Effects of Urban Landscape Pattern on PM2.5 Pollution--A Beijing Case Study.

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Wu, Jiansheng; Xie, Wudan; Li, Weifeng; Li, Jiacheng

2015-01-01

PM2.5 refers to particulate matter (PM) in air that is less than 2.5 μm in aerodynamic diameter, which has negative effects on air quality and human health. PM2.5 is the main pollutant source in haze occurring in Beijing, and it also has caused many problems in other cities. Previous studies have focused mostly on the relationship between land use and air quality, but less research has specifically explored the effects of urban landscape patterns on PM2.5. This study considered the rapidly growing and heavily polluted Beijing, China. To better understand the impact of urban landscape pattern on PM2.5 pollution, five landscape metrics including PLAND, PD, ED, SHEI, and CONTAG were applied in the study. Further, other data, such as street networks, population density, and elevation considered as factors influencing PM2.5, were obtained through RS and GIS. By means of correlation analysis and stepwise multiple regression, the effects of landscape pattern on PM2.5 concentration was explored. The results showed that (1) at class-level, vegetation and water were significant landscape components in reducing PM2.5 concentration, while cropland played a special role in PM2.5 concentration; (2) landscape configuration (ED and PD) features at class-level had obvious effects on particulate matter; and (3) at the landscape-level, the evenness (SHEI) and fragmentation (CONTAG) of the whole landscape related closely with PM2.5 concentration. Results of this study could expand our understanding of the role of urban landscape pattern on PM2.5 and provide useful information for urban planning.

Effect of particulate matter less than 10μm (PM10 on mortality in Bogota, Colombia: a time-series analysis, 1998-2006

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Luis Camilo Blanco-Becerra

2014-07-01

Full Text Available Objective. To analyze the association between daily mortality from different causes and acute exposure to particulate matter less than 10 microns in aerodynamic diameter (PM10, in Bogota, Colombia. Materials and methods. A time-series ecological study was conducted from 1998 to 2006. The association between mortality (due to different causes and exposure was analyzed using single and distributed lag models and adjusting for potential confounders. Results. For all ages, the cumulative effect of acute mortality from all causes and respiratory causes increased 0.71% (95%CI 0.46-0.96 and 1.43% (95%CI 0.85-2.00, respectively, per 10μg/m3 increment in daily average PM10 with a lag of three days before death. Cumulative effect of mortality from cardiovascular causes was -0.03% (95%CI -0.49-0.44% with the same lag. Conclusions. The results suggest an association between an increase in PM10 concentrations and acute mortality from all causes and respiratory causes.

Multi-scale dynamic modeling of atmospheric pollution in urban environment

International Nuclear Information System (INIS)

Thouron, Laetitia

2017-01-01

Urban air pollution has been identified as an important cause of health impacts, including premature deaths. In particular, ambient concentrations of gaseous pollutants such as nitrogen dioxide (NO 2 ) and particulate matter (PM10 and PM2.5) are regulated, which means that emission reduction strategies must be put in place to reduce these concentrations in places where the corresponding regulations are not respected. Besides, air pollution can contribute to the contamination of other media, for example through the contribution of atmospheric deposition to runoff contamination. The multifactorial and multi-scale aspects of urban make the pollution sources difficult to identify. Indeed, the urban environment is a heterogeneous space characterized by complex architectural structures (old buildings alongside a more modern building, residential, commercial, industrial zones, roads, etc.), non-uniform atmospheric pollutant emissions and therefore the population exposure to pollution is variable in space and time. The modeling of urban air pollution aims to understand the origin of pollutants, their spatial extent and their concentration/deposition levels. Some pollutants have long residence times and can stay several weeks in the atmosphere (PM2.5) and therefore be transported over long distances, while others are more local (NO x in the vicinity of traffic). The spatial distribution of a pollutant will therefore depend on several factors, and in particular on the surfaces encountered. Air quality depends strongly on weather, buildings (canyon-street) and emissions. The aim of this thesis is to address some of these aspects by modeling: (1) urban background pollution with a transport-chemical model (Polyphemus / POLAIR3D), which makes it possible to estimate atmospheric pollutants by type of urban surfaces (roofs, walls and roadways), (2) street-level pollution by explicitly integrating the effects of the building in a three-dimensional way with a multi-scale model of

Determination of benzo(apyrene content in PM10 using regression methods

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Jacek Gębicki

2015-12-01

Full Text Available The paper presents an attempt of application of multidimensional linear regression to estimation of an empirical model describing the factors influencing on B(aP content in suspended dust PM10 in Olsztyn and Elbląg city regions between 2010 and 2013. During this period annual average concentration of B(aP in PM10 exceeded the admissible level 1.5-3 times. Conducted investigations confirm that the reasons of B(aP concentration increase are low-efficiency individual home heat stations or low-temperature heat sources, which are responsible for so-called low emission during heating period. Dependences between the following quantities were analysed: concentration of PM10 dust in air, air temperature, wind velocity, air humidity. A measure of model fitting to actual B(aP concentration in PM10 was the coefficient of determination of the model. Application of multidimensional linear regression yielded the equations characterized by high values of the coefficient of determination of the model, especially during heating season. This parameter ranged from 0.54 to 0.80 during the analyzed period.

Estimating premature mortality attributable to PM2.5 exposure and benefit of air pollution control policies in China for 2020.

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Maji, Kamal Jyoti; Dikshit, Anil Kumar; Arora, Mohit; Deshpande, Ashok

2018-01-15

In past decade of rapid industrial development and urbanization, China has witnessed increasingly persistent severe haze and smog episodes, posing serious health hazards to the Chinese population, especially in densely populated cities. Quantification of health impacts attributable to PM 2.5 (particulates with aerodynamic diameter≤2.5μm) has important policy implications to tackle air pollution. The Chinese national monitoring network has recently included direct measurements of ground level PM 2.5 , providing a potentially more reliable source for exposure assessment. This study reports PM 2.5 -related long-term mortality of year 2015 in 161 cities of nine regions across China using integrated exposure risk (IER) model for PM 2.5 exposure-response functions (ERF). It further provides an estimate of the potential health benefits by year 2020 with a realization of the goals of Air Pollution Prevention and Control Action Plan (APPCAP) and the three interim targets (ITs) and Air Quality Guidelines (AQG) for PM 2.5 by the World Health Organization (WHO). PM 2.5 -related premature mortality in 161 cities was 652 thousand, about 6.92% of total deaths in China during year 2015. Among all premature deaths, contributions of cerebrovascular disease (stroke), ischemic heart disease (IHD), chronic obstructive pulmonary disease (COPD), lung cancer (LC) and acute lower respiratory infections (ALRIs) were 51.70, 26.26, 11.77, 9.45 and 0.82%, respectively. The premature mortality in densely populated cities is very high, such as Tianjin (12,533/year), Beijing (18,817/year), Baoding (10,932/year), Shanghai (18,679/year), Chongqing (23,561/year), Chengdu (11,809/year), Harbin (9037/year) and Linyi (9141/year). The potential health benefits will be 4.4, 16.2, 34.5, 63.6 and 81.5% of the total present premature mortality when PM 2.5 concentrations in China meet the APPCAP, WHO IT-1, IT-2, IT-3 and AQG respectively, by the year 2020. In the current situation, by the end of year 2030