In this paper, the spatial, temporal distribution, transformation and source simulation of NO3- were analyzed systematically based on the monitoring data, literature review and numerical simulation ( CMAQ4.7.1 ). An...In this paper, the spatial, temporal distribution, transformation and source simulation of NO3- were analyzed systematically based on the monitoring data, literature review and numerical simulation ( CMAQ4.7.1 ). Analysis results showed that annual average concentration of NO3- in Beijing was between 6.69 and 12.48 μg/m3 with an increasing trend in recent years; concentration of NO3- in Beijing in 2013 was higher in winter and autumn than that in spring and summer and diurnal variation of NO3- showed bimedal distribution and spatial distribution of NO3- showed significant north-south gradient distribution; annual average NOR in Beijing was between 0.12 and 0.17 while it was between 0.17 and 0.20 during heavy air pollution days in 2013; the average ratio of NO3-/SO42- was between 0.97 and 1.06 while it was between 1.00 and 1.07 during heavy air pollution days in 2013; the emission sources of Beijing was being changed from fixed source to both fixed and moving sources in feature development; simulated local, external transportation, background and boundary condition were 40%, 44% and 16% respectively to the annual average concentration of NO3- in Beijing in 2013 while they were 31%, 57% and 12% respectively in heavy air pollution days, which indicated that extemal source played an important role to the concentration of NO3- in Beijing. Key words NO3- ; Spatial and temporal distribution; Source; PM2.5; Beijing; CAMx展开更多
A total of 11 PM2.5 samples were collected from October 2003 to October 2004 at 8 sampling sites in Beijing city. The PM2.5 concentrations are all above the PM2.5 pollution standard (65 μg m^-3) established by Envi...A total of 11 PM2.5 samples were collected from October 2003 to October 2004 at 8 sampling sites in Beijing city. The PM2.5 concentrations are all above the PM2.5 pollution standard (65 μg m^-3) established by Environmental Protection Agency, USA (USEPA) in 1997 except for the Ming Tombs site. PM2.5 concentrations in winter are much higher than in summer. The 16 Polycyclic aromatic hydrocarbons (PAHs) listed as priority pollutants by USEPA in PM2.5 were completely identified and quantified by high performance liquid chromatography (HPLC) with variable wavelength detector (VWD) and fluorescence detector (FLD) employed. The PM2.5 concentrations indicate that the pollution situation is still serious in Beijing. The sum of 16 PAHs concentrations ranged from 22.17 to 5366 ng m^-3. The concentrations of the heavier molecular weight PAHs have a different pollution trend from the lower PAHs. Seasonal variations were mainly attributed to the difference in coal combustion emission and meteorological conditions. The source apportionment analysis suggests that PAHs from PM2.5 in Beijing city mainly come from coal combustion and vehicle exhaust emission. New measures about restricting coal combustion and vehicle exhaust must be established as soon as possible to improve the air pollution situation in Beijing city.展开更多
The increasing emission of primary and gaseous precursors of secondarily formed atmospheric particulate matter due to continuing industrial development and urbanization are leading to an increased public awareness of ...The increasing emission of primary and gaseous precursors of secondarily formed atmospheric particulate matter due to continuing industrial development and urbanization are leading to an increased public awareness of environmental issues and human health risks in China. As part of a pilot study, 12-h integrated fine fraction particulate matter (PM2.5) filter samples were collected to chemically characterize and investigate the sources of ambient particulate matter in Guiyang City, Guizhou Province, southwestern China. Results showed that the 12-h integrated PM2.5 concentrations exhibited a daytime average of 51 ± 22 μg m^-3 (mean -4- standard deviation) with a range of 17-128 μg m^-3 and a nighttime average of 55 ± 32 μg m^-3 with a range of 4-186 μg m^-3. The 24-h integrated PM2.5 concentrations varied from 15 to 157 μg m^-3, with amean value of 53 ± 25 μg m^-3, which exceeded the 24-h PM2.5 standard of 35μg m^-3 set by USEPA, but was below the standard of 75 μg m^-3, set by China Ministry of Environmental Protection. Energy-dispersive X-ray fluorescence spectrometry (XRF) was applied to determine PM2.5 chemical element concentrations. The order of concentrations of heavy metals in PM2.5 were iron (Fe) 〉 zinc (Zn) 〉 manganese (Mn) 〉 lead (Pb) 〉 arsenic (As)〉 chromium (Cr). The total concentration of 18 chemical elements was 13 ± 2 μg m^-3, accounting for 25% in PM2.5, which is comparable to other major cities in China, but much higher than cities outside of China.展开更多
In order to identify the day and night pollution sources of PM10 in ambient air in Longyan City,the authors analyzed the elemental composition of respirable particulate matters in the day and night ambient air samples...In order to identify the day and night pollution sources of PM10 in ambient air in Longyan City,the authors analyzed the elemental composition of respirable particulate matters in the day and night ambient air samples and various pollution sources which were collected in January 2010 in Longyan with inductivity coupled plasma-mass spectrometry(ICP-MS).Then chemical mass balance(CMB) model and factor analysis(FA) method were applied to comparatively study the inorganic components in the sources and receptor samples.The results of factor analysis show that the major sources were road dust,waste incineration and mixed sources which contained automobile exhaust,soil dust/secondary dust and coal dust during the daytime in Longyan City,China.There are two major sources of pollution which are soil dust and mixture sources of automobile exhaust and secondary dust during the night in Longyan.The results of CMB show that the major sources are secondary dust,automobile exhaust and road dust during the daytime in Longyan.The major sources are secondary dust,soil dust and automobile exhaust during the night in Longyan.The results of the two methods are similar to each other and the results will guide us to plan to control the PM10 pollution sources in Longyan.展开更多
A problem of the air pollution control in China is getting to know a regional contribution rate of internal and external source of PM2.5. In this paper,Set Pair Analysis( SPA) method is proposed to calculate the con...A problem of the air pollution control in China is getting to know a regional contribution rate of internal and external source of PM2.5. In this paper,Set Pair Analysis( SPA) method is proposed to calculate the contribution rate of PM2.5in Dongguan City. Due to geographic,meteorological factors and the low concentration of air pollutants in Qingxi area,the PM2.5in this place is mainly contributed by the regional transport of air pollutants from other inside areas of Dongguan,and less affected by the outside of Dongguan. So the concentration of PM2.5in Qingxi area can reflect the Dongguan's basic background concentration of PM2.5. On the basis of the basic background concentration,firstly the concentration of each pollutant components is divided into the internal part and the mixed part. Secondly using the source apportionment samples of five monitoring sites in Dongguan we can respectively construct a sample set A and an evaluation set B. Thirdly the SPA is operated onto the mixed part in terms of set B.At last the connection degree between the concentration of each pollutant components and external source and internal source will be calculated,that is the contribution rate. The research reveals that the contribution rate of internal source and external source of PM2.5in Dongguan City is 83%and 17% respectively,which roughly met expectations. This method is simple and effective and it can provide a reference for the government taking reduction measures to control PM2.5pollutants emission.展开更多
Adapting daily meteorological data provided by China International Exchange Station, and using principal component analysis of meteorological index for dimension reduction comprehensive, the regression analysis model ...Adapting daily meteorological data provided by China International Exchange Station, and using principal component analysis of meteorological index for dimension reduction comprehensive, the regression analysis model between PM2.5 and comprehensive index is established, by making use of Eviews time series modeling of the comprehensive principal component, finally puts forward opinions and suggestions aim at the regression analysis results of using artificial rainfall to ease haze.展开更多
Suspended particles in the air are pollutants formed by diverse materials and sizes. As determined in multiple studies, particulate matter equal to or less than 2.5 μrn also called breathable fraction is the one that...Suspended particles in the air are pollutants formed by diverse materials and sizes. As determined in multiple studies, particulate matter equal to or less than 2.5 μrn also called breathable fraction is the one that penetrates the inferior respiratory system. The present study shows the results of a sampling campaign of particulate matter PM25 through 12 months at 3 sites: C33 (Clinic 33), CIM (CIMAV) and A VA (Avalos) at Chihuahua, Mexico. The aim of this study was to determine the temporary concentrations of PM25, the concentration of metallic elements: Al, As, Co, Cu, Sb, Se, Fe, Mg, Mn, Ni, Pb and Zn, as well as their possible sources. The three sites had the same trend in the time, where in autumn and winter the higher concentrations were found. The yearly averages on sites C33, CIM, and AVA were 9.91, 12.74 and 21.67 μg·m^-3, respectively, finding that AVA site overpasses the standard of 15 μg·m^-3. The application of factor analysis to the data allowed to identify four source categories: crustal, related with Al-Co-Fe-Mg-Mn, vehicular, related with: As-Cu-Sb-Se; mixed, related with: As-Cu-Sb-Se-Pb-Zn and industrial related with Ni-Pb.展开更多
Exposure to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) may increase risk of lung cancer. The repetitive and broad-area coverage of satellites may allow atmospheric remote sensing to o...Exposure to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) may increase risk of lung cancer. The repetitive and broad-area coverage of satellites may allow atmospheric remote sensing to offer a unique opportunity to monitor air quality and help fill air pollution data gaps that hinder efforts to study air pollution and protect public health. This geographical study explores if there is an association between PM2.5 and lung cancer mortality rate in the conterminous USA. Lung cancer (ICD-10 codes C34- C34) death count and population at risk by county were extracted for the period from 2001 to 2010 from the U.S. CDC WONDER online database. The 2001-2010 Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset was used to calculate a 10 year average PM2.5 pollution. Exploratory spatial data analyses, spatial regression (a spatial lag and a spatial error model), and spatially extended Bayesian Monte Carlo Markov Chain simulation found that there is a significant positive association between lung cancer mortality rate and PM2.5. The association would justify the need of further toxicological investigation of the biological mechanism of the adverse effect of the PM2.5 pollution on lung cancer. The Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset provides a continuous surface of concentrations of PM2.5 and is a useful data source for environmental health research.展开更多
In this work, receptor models were used to identify the PM2.5 sources and its contribution to the air quality in residential, comercial and industrial sampling sites in the Metropolitan Area of Costa Rica. Principal c...In this work, receptor models were used to identify the PM2.5 sources and its contribution to the air quality in residential, comercial and industrial sampling sites in the Metropolitan Area of Costa Rica. Principal component analysis with absolute principal component scores (PCA-APCS), UNIMX and positive matrix factorization (PMF) was applied to analyze the data collected during 1 year of sampling campaign (2010-2011). The PM2.5 samples were characterized through its composition looking for trace elements, inorganic ions and organic and elemental carbon. These three models identified some common sources of PM2.5: marine aerosol, crustal material, traffic, secondary aerosols (secondary sulfate and secondary nitrate resolved by PMF), a mixed source of heavy fuels combustion and biomass burning, and industrial emissions. The three models predicted that the major sources of PM2.5 in the Metropolitan Area of Costa Rica were related to anthropogenic sources (73%, 65% and 69%, respectively, for PCA-APCS, Unmix and PMF) although natural sources also contributed to PM2.5 (21%, 24% and 26%). On average, PCA and PMF methods resolved 94% and 95% of the PM2.5 mass concentrations, respectively. The results were comparable to the estimate using UNMIX.展开更多
文摘In this paper, the spatial, temporal distribution, transformation and source simulation of NO3- were analyzed systematically based on the monitoring data, literature review and numerical simulation ( CMAQ4.7.1 ). Analysis results showed that annual average concentration of NO3- in Beijing was between 6.69 and 12.48 μg/m3 with an increasing trend in recent years; concentration of NO3- in Beijing in 2013 was higher in winter and autumn than that in spring and summer and diurnal variation of NO3- showed bimedal distribution and spatial distribution of NO3- showed significant north-south gradient distribution; annual average NOR in Beijing was between 0.12 and 0.17 while it was between 0.17 and 0.20 during heavy air pollution days in 2013; the average ratio of NO3-/SO42- was between 0.97 and 1.06 while it was between 1.00 and 1.07 during heavy air pollution days in 2013; the emission sources of Beijing was being changed from fixed source to both fixed and moving sources in feature development; simulated local, external transportation, background and boundary condition were 40%, 44% and 16% respectively to the annual average concentration of NO3- in Beijing in 2013 while they were 31%, 57% and 12% respectively in heavy air pollution days, which indicated that extemal source played an important role to the concentration of NO3- in Beijing. Key words NO3- ; Spatial and temporal distribution; Source; PM2.5; Beijing; CAMx
基金Financial support from the National Natural Science Foundation of China (Grant No. 40475049) the Natural Sciences Foundation of Beijing city (Grant No. 8032012) are acknowledged.
文摘A total of 11 PM2.5 samples were collected from October 2003 to October 2004 at 8 sampling sites in Beijing city. The PM2.5 concentrations are all above the PM2.5 pollution standard (65 μg m^-3) established by Environmental Protection Agency, USA (USEPA) in 1997 except for the Ming Tombs site. PM2.5 concentrations in winter are much higher than in summer. The 16 Polycyclic aromatic hydrocarbons (PAHs) listed as priority pollutants by USEPA in PM2.5 were completely identified and quantified by high performance liquid chromatography (HPLC) with variable wavelength detector (VWD) and fluorescence detector (FLD) employed. The PM2.5 concentrations indicate that the pollution situation is still serious in Beijing. The sum of 16 PAHs concentrations ranged from 22.17 to 5366 ng m^-3. The concentrations of the heavier molecular weight PAHs have a different pollution trend from the lower PAHs. Seasonal variations were mainly attributed to the difference in coal combustion emission and meteorological conditions. The source apportionment analysis suggests that PAHs from PM2.5 in Beijing city mainly come from coal combustion and vehicle exhaust emission. New measures about restricting coal combustion and vehicle exhaust must be established as soon as possible to improve the air pollution situation in Beijing city.
基金The U.S. Environmental Protection Agency (EPA), through its Office of Research and Development, partially funded and participated in the research described here through cooperative agreement CR-833232-01 through the U.S. National Science Foundation-National Research Council Research Associateship Awardfunded by the National Key Basic Research Program of China (2013CB430004)the National Natural Science Foundation of China (No. 40773067)
文摘The increasing emission of primary and gaseous precursors of secondarily formed atmospheric particulate matter due to continuing industrial development and urbanization are leading to an increased public awareness of environmental issues and human health risks in China. As part of a pilot study, 12-h integrated fine fraction particulate matter (PM2.5) filter samples were collected to chemically characterize and investigate the sources of ambient particulate matter in Guiyang City, Guizhou Province, southwestern China. Results showed that the 12-h integrated PM2.5 concentrations exhibited a daytime average of 51 ± 22 μg m^-3 (mean -4- standard deviation) with a range of 17-128 μg m^-3 and a nighttime average of 55 ± 32 μg m^-3 with a range of 4-186 μg m^-3. The 24-h integrated PM2.5 concentrations varied from 15 to 157 μg m^-3, with amean value of 53 ± 25 μg m^-3, which exceeded the 24-h PM2.5 standard of 35μg m^-3 set by USEPA, but was below the standard of 75 μg m^-3, set by China Ministry of Environmental Protection. Energy-dispersive X-ray fluorescence spectrometry (XRF) was applied to determine PM2.5 chemical element concentrations. The order of concentrations of heavy metals in PM2.5 were iron (Fe) 〉 zinc (Zn) 〉 manganese (Mn) 〉 lead (Pb) 〉 arsenic (As)〉 chromium (Cr). The total concentration of 18 chemical elements was 13 ± 2 μg m^-3, accounting for 25% in PM2.5, which is comparable to other major cities in China, but much higher than cities outside of China.
基金Supported by the Natural Basic Research Program of China(No.2005CB422207)the Fund of Eco-enviromental Impacts and Protection in Devoloping and Utilizing of Oil-shale Resources(No.OSR-01-06)
文摘In order to identify the day and night pollution sources of PM10 in ambient air in Longyan City,the authors analyzed the elemental composition of respirable particulate matters in the day and night ambient air samples and various pollution sources which were collected in January 2010 in Longyan with inductivity coupled plasma-mass spectrometry(ICP-MS).Then chemical mass balance(CMB) model and factor analysis(FA) method were applied to comparatively study the inorganic components in the sources and receptor samples.The results of factor analysis show that the major sources were road dust,waste incineration and mixed sources which contained automobile exhaust,soil dust/secondary dust and coal dust during the daytime in Longyan City,China.There are two major sources of pollution which are soil dust and mixture sources of automobile exhaust and secondary dust during the night in Longyan.The results of CMB show that the major sources are secondary dust,automobile exhaust and road dust during the daytime in Longyan.The major sources are secondary dust,soil dust and automobile exhaust during the night in Longyan.The results of the two methods are similar to each other and the results will guide us to plan to control the PM10 pollution sources in Longyan.
基金Supported by National Natural Science Foundation of China(71171089)Research for PM_(2.5) Contamination Characteristics and Prevention and Control Countermeasures in Dongguan City(Dongcaidan[2013]222)
文摘A problem of the air pollution control in China is getting to know a regional contribution rate of internal and external source of PM2.5. In this paper,Set Pair Analysis( SPA) method is proposed to calculate the contribution rate of PM2.5in Dongguan City. Due to geographic,meteorological factors and the low concentration of air pollutants in Qingxi area,the PM2.5in this place is mainly contributed by the regional transport of air pollutants from other inside areas of Dongguan,and less affected by the outside of Dongguan. So the concentration of PM2.5in Qingxi area can reflect the Dongguan's basic background concentration of PM2.5. On the basis of the basic background concentration,firstly the concentration of each pollutant components is divided into the internal part and the mixed part. Secondly using the source apportionment samples of five monitoring sites in Dongguan we can respectively construct a sample set A and an evaluation set B. Thirdly the SPA is operated onto the mixed part in terms of set B.At last the connection degree between the concentration of each pollutant components and external source and internal source will be calculated,that is the contribution rate. The research reveals that the contribution rate of internal source and external source of PM2.5in Dongguan City is 83%and 17% respectively,which roughly met expectations. This method is simple and effective and it can provide a reference for the government taking reduction measures to control PM2.5pollutants emission.
文摘Adapting daily meteorological data provided by China International Exchange Station, and using principal component analysis of meteorological index for dimension reduction comprehensive, the regression analysis model between PM2.5 and comprehensive index is established, by making use of Eviews time series modeling of the comprehensive principal component, finally puts forward opinions and suggestions aim at the regression analysis results of using artificial rainfall to ease haze.
文摘Suspended particles in the air are pollutants formed by diverse materials and sizes. As determined in multiple studies, particulate matter equal to or less than 2.5 μrn also called breathable fraction is the one that penetrates the inferior respiratory system. The present study shows the results of a sampling campaign of particulate matter PM25 through 12 months at 3 sites: C33 (Clinic 33), CIM (CIMAV) and A VA (Avalos) at Chihuahua, Mexico. The aim of this study was to determine the temporary concentrations of PM25, the concentration of metallic elements: Al, As, Co, Cu, Sb, Se, Fe, Mg, Mn, Ni, Pb and Zn, as well as their possible sources. The three sites had the same trend in the time, where in autumn and winter the higher concentrations were found. The yearly averages on sites C33, CIM, and AVA were 9.91, 12.74 and 21.67 μg·m^-3, respectively, finding that AVA site overpasses the standard of 15 μg·m^-3. The application of factor analysis to the data allowed to identify four source categories: crustal, related with Al-Co-Fe-Mg-Mn, vehicular, related with: As-Cu-Sb-Se; mixed, related with: As-Cu-Sb-Se-Pb-Zn and industrial related with Ni-Pb.
文摘Exposure to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) may increase risk of lung cancer. The repetitive and broad-area coverage of satellites may allow atmospheric remote sensing to offer a unique opportunity to monitor air quality and help fill air pollution data gaps that hinder efforts to study air pollution and protect public health. This geographical study explores if there is an association between PM2.5 and lung cancer mortality rate in the conterminous USA. Lung cancer (ICD-10 codes C34- C34) death count and population at risk by county were extracted for the period from 2001 to 2010 from the U.S. CDC WONDER online database. The 2001-2010 Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset was used to calculate a 10 year average PM2.5 pollution. Exploratory spatial data analyses, spatial regression (a spatial lag and a spatial error model), and spatially extended Bayesian Monte Carlo Markov Chain simulation found that there is a significant positive association between lung cancer mortality rate and PM2.5. The association would justify the need of further toxicological investigation of the biological mechanism of the adverse effect of the PM2.5 pollution on lung cancer. The Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset provides a continuous surface of concentrations of PM2.5 and is a useful data source for environmental health research.
文摘In this work, receptor models were used to identify the PM2.5 sources and its contribution to the air quality in residential, comercial and industrial sampling sites in the Metropolitan Area of Costa Rica. Principal component analysis with absolute principal component scores (PCA-APCS), UNIMX and positive matrix factorization (PMF) was applied to analyze the data collected during 1 year of sampling campaign (2010-2011). The PM2.5 samples were characterized through its composition looking for trace elements, inorganic ions and organic and elemental carbon. These three models identified some common sources of PM2.5: marine aerosol, crustal material, traffic, secondary aerosols (secondary sulfate and secondary nitrate resolved by PMF), a mixed source of heavy fuels combustion and biomass burning, and industrial emissions. The three models predicted that the major sources of PM2.5 in the Metropolitan Area of Costa Rica were related to anthropogenic sources (73%, 65% and 69%, respectively, for PCA-APCS, Unmix and PMF) although natural sources also contributed to PM2.5 (21%, 24% and 26%). On average, PCA and PMF methods resolved 94% and 95% of the PM2.5 mass concentrations, respectively. The results were comparable to the estimate using UNMIX.