Locating major PM10 source areas in Seoul using multivariate receptor modeling

Identifying the major sources contributing to air pollution is a problem of fundamental importance in developing effective air quality management plans. Multivariate receptor modeling aims to achieve this goal by unfolding the air pollution data into components associated with different sources based on factor analysis models. We analyze the PM₁₀ data obtained from 17 monitoring sites in Seoul to locate the major source regions using multivariate receptor modeling. The model uncertainty caused by the unknown number of sources and identifiability conditions is assessed by posterior probability of each model. The estimated source spatial profiles seem to be consistent with our prior expectation about the PM₁₀ sources in Seoul.     

World air particulate matter: sources,distribution and health effects

Particulate matter (PM) is both a major driver of climate change and a source of toxicity for health. In the upper atmosphere, particulate matter modifies the earth radiation budget, cloud formation and acts as a reaction center for air pollutants. In the lower atmosphere, particulate matter changes atmospheric visibility and alters biogeochemical cycles and meteorology. Most critical effects are observed in ambient air, where particulate matter degrades human health. Here we review the sources, spatial and temporal variability, and toxicity of PM₁₀, the particulate matter having particle sizes 10 micrometers or less in diameter, in world regions. For that we analyzed information from the world wide web and databases from government organizations after the year 2000. Findings show that PM₁₀ is a major risk in both developed and developing countries. This risk is more severe in Asian countries compared to Europe and USA, where decreasing trends are recorded during the last two decades. Meteorological factors modify particulate matter variations at local and regional levels. PM_2.5/PM₁₀ ratio provides information of particulate matter sources under different environment conditions. Crustal matter, road traffic and combustion of fuels are major sources of particulate matter pollution. Health studies indicate that long-term exposure to particulate matter has multiple health effects in people from all age groups. Identification of possible sources and their control with regular epidemiological monitoring could decrease the impact of particulate matter pollution.     

Air pollutant levels are 12 times higher than guidelines in Varanasi,India. Sources and transfer

Air quality in an urban atmosphere is regulated by both local and distant emission sources. For air quality management in urban areas, identification of sources and their relationships with local meteorology and air pollutants are essential. The critical condition of air quality in Indo-Gangetic plain is well known, but lack of data on both local and distant emission sources limits the scope of improving air quality in this region. Concentrations of particulate matter of size lower than 10 μm (PM₁₀) were assessed in the highly urbanized Varanasi city situated in middle Indo-Gangetic plain of India from 2014 to 2017, to identify the distant air pollution sources based on trajectory statistical models and local sources by conditional bivariate probability function. Modifying effects of meteorology and air pollutants on PM₁₀ were also explored. Mean PM₁₀ concentration for the study period was 244.8 ± 135.8 μg m^?3, which was 12 times higher than the WHO annual guideline. Several distinct sources of traffic as the major source of PM₁₀ were identified in the city. Trajectory statistical models like cluster analysis, potential source contribution function and concentration-weighted trajectory showed significant contributions from north-west and eastern directions in the transport of polluted air masses to the city. Dew point, wind speed, temperature and ventilation coefficient are the major factors in PM₁₀ formation and dispersion.     

Air pollution-oriented ecological risk assessment in Xiamen city,China

Urban energy consumption is one of the most important causes of air pollution. Air pollution-oriented ecological risk assessment is of great significance to the promotion of urban environmental protection. This paper focuses on ecological risk in Xiamen city caused by air pollutant discharge from urban energy consumption. The Long-range Energy Alternatives Planning model was used to establish two scenarios of energy consumption in Xiamen city, and based on different scenarios, we estimated urban energy consumption and discharge quantity of air pollutant (DQAP). A box model and an expert scoring method were used to calculate the air pollution burden (APB) of SO₂, NO₂, CO, PM₁₀ and PM_2.5 and to obtain the probabilities of different air pollution loads. An ecological risk assessment model was developed and utilized to predict Xiamen city’s ecological risks in 2020. The results showed that under an energy-saving scenario, the ecological risks for PM_2.5, SO₂ and NO₂ are high, whereas the ecological risks for CO and PM₁₀ are low. Under a baseline scenario, the ecological risks for PM_2.5, SO₂ and NO₂ are moderate, whereas the ecological risks for CO and PM₁₀ are low. In addition, the APB of SO₂, NO₂, CO, and PM_2.5, but not of PM₁₀, is predicted to rise. In the simulation, energy generation from coal is the main source of air pollution. Although the DQAP from automobiles is not high, it is predicted to rise year-on-year. In summary, the ecological risk due to pollution in Xiamen city is high, and the main pollutants are SO₂, NO₂ and PM_2.5.     

Modelling concentrations of airborne primary and secondary PM10 and PM2.5 with the BelEUROS-model in Belgium

The Eulerian Chemistry-Transport Model BelEUROS was used to calculate the concentrations of airborne PM₁₀ and PM_2.5 over Europe. Both primary as well as secondary particulate matter in the respirable size-range was taken into account. Especially PM_2.5 aerosols are often formed in the atmosphere from gaseous precursor compounds. Comprehensive computer codes for the calculation of gas phase chemical reactions and thermodynamic equilibria between compounds in the gas-phase and the particulate phase had been implemented into the BelEUROS-model. Calculated concentrations of PM₁₀ and PM_2.5 are compared to observations, including both the spatial and daily, temporal distribution of particulate matter in Belgium for certain monitoring locations and periods. The concentrations of the secondary compounds ammonium, nitrate and sulfate have also been compared to observed values. BelEUROS was found to reproduce the observed concentrations rather well. The model was applied to assess the contribution of emissions derived from the sector agriculture in Flanders, the northern part of Belgium, to PM₁₀- and PM_2.5-concentrations. The results demonstrate the importance of ammonia emissions in the formation of secondary particulate matter. Hence, future European emission abatement policy should consider more the role of ammonia in the formation of secondary particles.     

Source apportionment of PM<Subscript>2.5</Subscript> in Tangshan,China—Hybrid approaches for primary and secondary species apportionment

The objective of this paper is to propose a hybrid approach for the source apportionment of primary and secondary species of PM_2.5 in the city of Tangshan. The receptor-based PMF (Positive Matrix Factorization) is integrated with the emission inventory (EI) to form the first hybrid method for the source apportionment of the primary species. The hybrid CAMx-PSAT-CP (Comprehensive Air Quality Model with Extensions–Particulate Source Apportionment Technology–Chemical Profile) approach is then proposed and used for the source apportionment of the secondary species. The PM_2.5 sources identified for Tangshan included the soil dust, the metallurgical industry, power plants, coalfired boilers, vehicles, cement production, and other sources. It is indicated that the PM_2.5 pollution is a regional issue. Among all the identified sources, the metallurgy industry was the biggest contribution source to PM_2.5, followed by coal-fired boilers, vehicles and soil dust. The other-source category plays a crucial role for PM_2.5, particularly for the formation of secondary species and aerosols, and these other sources include non-specified sources such as agricultural activities, biomass combustion, residential emissions, etc. The source apportionment results could help the local authorities make sound policies and regulations to better protect the citizens from the local and regional PM_2.5 pollution. The study also highlights the strength of utilizing the proposed hybrid approaches in the identification of PM_2.5 sources. The techniques used in this study show considerable promise for further application to other regions as well as to identify other source categories of PM_2.5.

Open image in new window

     

Study on particulate matter air pollution,source origin,and human health risk based of PM10 metal content in Volos City,Greece

Investigations on the fluctuation in PM₁₀ air pollution in Volos, a medium-sized industrialized port city in the Mediterranean, are presented for the 5-year period between 2009 and 2014. The levels detected have been examined in relation to legislatively set limits, sampling year, and day of the week. A PM₁₀ spring sampling campaign has been performed in 2014 and metals and other elements in the PM₁₀ mass have been quantified. Source origin has been attempted for the latter sampling campaign and human health risk has been assessed. Results show compliance with the mean annual value of 40 μg m^?3 of 2008/50/EC for the city; however, exceedances of the daily quality standard of 50 μg m^?3 were frequently recorded. Shifts in PM₁₀ concentrations and in contributing sources have been recorded; nevertheless, longer duration data series are needed for safe deductions. Element measurements have enabled source identification for early summer of 2014, with Earth's crust minerals and anthropogenic sources being the main factors. Cumulative non-carcinogenic risk may exceed the threshold value of 1. Possible involvement of sea salt aerosol and desert dust long-range transport has also been assessed. These results may furnish databases on PM pollution of Greek cities as well as other Mediterranean urban centers with similar characteristics.     

复杂地形城市SO2扩散特征的模拟研究

利用中尺度气象模式RAMS和大气扩散模式HYPACT,结合甘肃省-中科院科技合作项目"兰州市大气污染及对策研究"于2000年12月在兰州市城区进行的大气污染物监测资料,通过资料分析与模拟计算,研究了兰州市冬季SO2的扩散特点。研究结果表明:大气扩散模式较好地模拟出了SO2时空分布特征,与同期监测资料的分析结果比较一致,模式模拟的SO2浓度分布的日变化与环流场的日变化紧密相关;模拟的SO2浓度的空间分布与污染源的排放方式有关,污染源的排放高度不同,造成污染的高度也不同,高架源对地面的影响比较小,而中、低架源对地面的影响比较大。     

Source apportionment of ambient PM10 in urban areas of Wuxi, China

A total of 168 PM₁₀ samples were collected during the year of 2005 at eight sites in the city of Wuxi in China. Fifteen chemical elements, three water-soluble ions, total carbon and organic carbon were analyzed. Six source categories were identified and their contributions to ambient PM₁₀ in Wuxi were estimated using a nested chemical mass balance method that reduces the effects of colinearity on the chemical mass balance model. In addition, the concentrations of secondary aerosols, such as secondary organic carbon, sulfate and nitrate, were quantified. The spatially averaged PM₁₀ was high in the spring and winter (123 ??g·m^?3 and low in the summer-fall (90 ??g·m^?3). According to the result of source apportionment, resuspended dust was the largest contributor to ambient PM₁₀, accounting for more than 50% of the PM₁₀ mass. Coal combustion (14.6%) and vehicle exhaust (9.4%) were also significant source categories of ambient PM₁₀. Construction and cement dust, sulfates, secondary organic carbon, and nitrates made contributions ranging between 4.1% and 4.9%. Other source categories such as steel manufacturing dust and soil dust made low contributions to ambient PM₁₀.     

Indoor and outdoor air pollution and lung cancer in New Hampshire and Vermont

Indoor and outdoor air pollution is known to contribute to increased lung cancer incidence. This study is the first to address the contribution of home heating fuel and geographical course particulate matter (PM₁₀) concentrations to lung cancer rates in New Hampshire, USA. First, Pearson correlation analysis and geographically weighted regression were used to investigate spatial relationships between outdoor PM₁₀ and lung cancer rates. While the aforementioned analyses did not indicate a significant contribution of PM₁₀ to lung cancer in the state, there was a trend towards a significant association in the northern and southwestern regions of the state. Second, case-control data were used to estimate the contributions of indoor pollution and secondhand smoke to the risk of lung cancer with adjustment for confounders. Increased risk was found among those who used wood or coal to heat their homes for more than 10 winters before the age of 18, with a significant increase in risk per winter. Resulting data suggest that further investigation of the relationship between heating-related air pollution levels and lung cancer risk is needed.     

大气颗粒物暴露与健康效应研究进展

大气颗粒物一直是影响我国大多数城市空气质量的首要污染物,且呈现出与欧美不同的煤烟、机动车尾气以及开放源复合型污染并存的高浓度污染态势,已有研究发现颗粒物的短期或长期暴露均会对人体产生不良的健康效应。本文从环境科学、暴露科学、环境流行病学和环境毒理学研究等方面系统综述了大气颗粒物健康效应研究的方法和进展,可为我国的大气颗粒物健康效应研究与大气颗粒物环境质量标准的修订提供方法学参考和经验借鉴。目前我国PM10污染尚未得到有效控制,细颗粒物(PM2.5)的污染也已引起关注,建议在不同区域开展空气污染健康效应的系统研究。     

电镀企业周边大气颗粒物PM_(2.5)、PM_(10)和TSP中重金属分布特征及健康风险评价

以东莞市5个镇区为研究对象,采集电镀企业周边大气样品,分析了样品中重金属(包括As、Co、Cd、Cr、Cu、Mn、Ni、Pb、Sb、V、Zn和Hg)的含量分布,使用富集因子(enrich factor)、地累积指数(index of geoaccumulation)、Hakanson法和美国国家环境保护局(US EPA)的人体暴露健康风险评价模型,对PM_(2.5)、PM_(10)、总悬浮颗粒物(TSP)中重金属进行人体健康风险评价。结果表明,PM_(2.5)、PM_(10)和TSP中As、Cd和Cr平均浓度皆超标。Cr、Ni和V元素在3种颗粒物中非富集,主要为自然源;As、Co、Cu、Pb和Zn,可能来源于自然源和叠加的工业污染。Cd、Hg和Sb浓度受人为污染影响严重。Cd、Sb、Cu、Zn、Pb为生物可利用元素(K>0.6),在环境中的可迁移性高且易于被生物体和人体吸收。Mn元素的非致癌风险值较其他重金属要高1~4个数量级,且儿童的非致癌暴露风险值HQ均高于成人的。3种颗粒物中重金属元素通过呼吸吸入途径产生的非致癌风险HI值均高于人体可接受的上限1.0,其主要贡献来源于Mn的影响,研究区非致癌风险较为严重。除PM_(10)中Co元素和TSP中Co、Cr的成人致癌风险CR值大于10-4之外,其余大部分重金属元素通过呼吸途径产生的致癌风险CR值均在可接受范围之内,此外,3种颗粒物中的成人的致癌暴露风险值CRT均高于儿童的CRT值,并且除了PM_(2.5)中儿童的重金属致癌暴露风险CRT值(4.70E-05)低于人体可接受范围的上限(10-4),其余CRT值均高于10-4,致癌风险较为严重。     

Estimating the effects of meteorology on PM2.5 reduction during the 2008 Summer Olympic Games in Beijing, China

Particulate pollution was a critical challenge to the promise of good air quality during the 2008 Beijing Olympic Games, which took place from August 8th to 24th. To ensure good air quality for the Games, several temporary emission control measures were implemented in Beijing and surrounding areas. Ambient particulate matter concentration decreased significantly during the Olympic period; however, it is difficult to distinguish the effectiveness of those control measures since meteorology also affects ambient PM_2.5 concentration. In this work, a multiple linear regression model based on continuous field monitoring at a roadside site was conducted to evaluate the effects of meteorology and emission control measures on the reduction of PM_2.5 during the 2008 Olympic Games. The hourly data set was divided into two time periods, the no control period, June 22nd to July 4th, and the control period, July 28th to August 21st. The response variable was PM_2.5 and the meteorology covariates used in the model were hourly temperature, dew point temperature, wind speed and precipitation. Wind direction was not a significant predictor of PM_2.5 levels in either the control or the no control period. Using the meteorologically-based regression coefficients from the two time periods, meteorology was found to contribute to at least a 16% reduction in PM_2.5 levels in the roadside microenvironment; while the pollution control measures contributed to at least a 43% reduction in PM_2.5 levels.     

The effect of pollution on crime: Evidence from data on particulate matter and ozone

We estimate the effect of short-term air pollution exposure (PM_2.5 and ozone) on several categories of crime, with a particular emphasis on aggressive behavior. To identify this relationship, we combine detailed daily data on crime, air pollution, and weather for an eight-year period across the United States. Our primary identification strategy employs extremely high dimensional fixed effects and we perform a series of robustness checks to address confounding variation between temperature and air pollution. We find a robust positive effect of increased air pollution on violent crimes, and specifically assaults, but no relationship between increases in air pollution and property crimes. The effects are present in and out of the home, at levels well below Ambient Air Pollution Standards, and PM_2.5 effects are strongest at lower temperatures. The results suggest that a 10% reduction in daily PM_2.5 and ozone could save $1.4 billion in crime costs per year, a previously overlooked cost associated with pollution.     

Metals and metalloids in PM10 in Nandan County,Guangxi, China,and the health risks posed

Intense mining, smelting, and tailing activities of polymetallic ore deposits have affected the environment in Nandan County, Guangxi, China. Samples of particulates with aerodynamic diameters low or equal 10 μm (PM₁₀) were collected in Nandan County to investigate the concentrations of and health risks posed by 17 metals and metalloids in the PM₁₀. The metal and metalloid concentrations were lower than those found in other industrial cities. The mean Cr concentration was 7.48 ng/m³. Significant higher metal and metalloid concentrations were found in PM₁₀ from mining areas (Dachang and Chehe) than from the control area (Liuzhai) (p < 0.05). Principal component analysis indicated that the main sources of Ba, Co, Cr, Fe, K, Mg, Mo, Na, and Sr were resuspension of the soil produced through mineral erosion, the main sources of As, Cd, Cu, Pb, Sb, and Zn were smelting and mining activities, and the main source of Ni was fossil fuel combustion. Higher non-carcinogenic and carcinogenic risks were posed in Dachang and Chehe than in Liuzhai. The non-carcinogenic risks posed to adults and children by individual metals and metalloids in PM₁₀ at all the sites were low, but the non-carcinogenic risks posed to children by all the metals and metalloids together exceeded the safe level (i.e., risk value > 1). The carcinogenic risks posed by Cd, Ni, and Pb were negligible at all sites, while As, Co, and Cr posed potential carcinogenic risks to the residents.

     

The effect of outdoor air pollutants and greenness on allergic rhinitis incidence rates: a cross-sectional study in Seoul,Korea

Air pollution poses a serious threat to human health in Asia. This study analyzes the association of air pollutants and greenness with incidence rates of allergic rhinitis in Seoul at the administrative district level to gain insight into district-level urban policies to improve public health. A spatial regression model is constructed to investigate the correlation between allergic rhinitis incidence rates and five air pollutants measured at 128 air pollution monitoring stations around Seoul: sulfur dioxide (SO₂), particulate matter less than 10 μm (PM₁₀), ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). The allergic rhinitis incidence data are derived from the National Health Insurance Service’s database that includes the number of allergic rhinitis-related clinic visits by the patients over 20 years of age and living in Seoul. A kriging geostatistical interpolation was used to estimate average air pollution level of 423 administrative districts. To assess pollen concentrations that can affect allergic rhinitis, the average normalized difference vegetation index (NDVI) is measured based on the urban greenness. The model, controlling for built environment and socio-economic attributes, identifies the possibility of a weak association between allergic rhinitis incidence rates and carbon monoxide levels. The NDVI value is negatively correlated with allergic rhinitis incidence rates, implying a complicated aspect in relation to the effect of urban greenness.     

Seasonal variations of transport pathways and potential sources of PM<Subscript>2.5</Subscript> in Chengdu,China (2012–2013)

Seasonal pattern of transport pathways and potential sources of PM_2.5 in Chengdu during 2012–2013 were investigated based on hourly PM_2.5 data, backward trajectories, clustering analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) method. The annual hourly mean PM_2.5 concentration in Chengdu was 97.4 mg·m^–3. 5, 5, 5 and 3 mean clusters were generated in four seasons, respectively. Short-distance air masses, which travelled within the Sichuan Basin with no specific source direction and relatively high PM_2.5 loadings (>80 mg·m^–3) appeared as important pathways in all seasons. These short pathways indicated that emissions from both local and surrounding regions of Chengdu contributed significantly to PM_2.5 pollution. The cities in southern Chengdu were major potential sources with PSCF>0.6 and CWT>90 mg·m^–3. The northeastern pathway prevailed throughout the year with higher frequency in autumn and winter and lower frequency in spring and summer. In spring, long-range transport from southern Xinjiang was a representative dust invasion path to Chengdu, and the CWT values along the path were 30-60 mg·m^–3. Long-range transport was also observed in autumn from southeastern Xinjiang along a northwesterly pathway, and in winter from the Tibetan Plateau along a westerly pathway. In summer, the potential source regions of Chengdu were smaller than those in other seasons, and no long-range transport pathway was observed. Results of PSCF and CWT indicated that regions in Qinghai and Tibet contributed to PM_2.5 pollution in Chengdu as well, and their CWT values increased to above 30 mg·m^–3 in winter.

Open image in new window

     

A 14-year measurement of toxic elements in atmospheric particulates in Hong Kong from 1995 to 2008

Toxic elements in the atmosphere can enter and accumulate in the human body, seriously impacting human health. In this study, we analyzed a 14-year （1995-2008） measurement of three toxic elements （As, Cd and Cr） in PMlo in Hong Kong, China. The pollution of these toxic elements in Hong Kong was not serious. The trend analysis showed that As and Cr in PM10 increased at a statistically significant level （p〈0.05） during the 14-year period, while the Cd in PM10 did not change significantly. Typical seasonal variations were observed for all three toxic elements, largely in relation to the Asian monsoon. Hourly 10-day backward trajectories were computed and cate- gorised into four groups. The continental air masses showed much higher concentrations of the three toxic elements than the marine air masses. The abundances of As and Cd in the PM10 were much higher in the continental air masses than those in the marine air masses, while the abundances of Cr showed an opposite pattern. The trends of the three toxic elements in East China＇s air mass were consistent with those in the overall data set ofHong Kong. Examination of the toxic element data recorded at urban sites and a roadside site also indicated a large contribution of external air masses to particulate As and Cd in Hong Kong. These results suggest that the long-range transport from the mainland of China is the dominant contributor to particulate As and Cd, while both local and long-distance sources determine the particulate Cr in Hong Kong.     

Analysis and prediction of the influence of energy utilization on air quality in Beijing

This work evaluates the influence of energy consumption on the future air quality in Beijing, using 2000 as the base year and 2008 as the target year. It establishes the emission inventory of primary PM₁₀, SO₂ and NO_x related to energy utilization in eight areas of Beijing. The air quality model was adopted to simulate the temporal and spatial distribution of each pollutant concentration in the eight urban areas. Their emission, concentration distribution, and sectoral share responsibility rate were analyzed, and air quality in 2008 was predicted. The industrial sector contributed above 40% of primary PM₁₀ and SO₂ resulting from energy consumption, while vehicles accounted for about 65% of NO_x. According to the current policy and development trend, air quality in the eight urban areas could become better in 2008 when the average concentrations of primary PM₁₀, SO₂ and NO₂ related to energy utilization at each monitored site are predicted to be about 25, 50 and 51 μg/m³, respectively.     

A flexible spatio-temporal model for air pollution with spatial and spatio-temporal covariates

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of \(\text {NO}_{x}\) in the Los Angeles area during a 10 year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated \(R^2\) of approximately \(0.7\) at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.