2000-2015年中国PM_(2.5)时空演化特征及驱动因素解析（英文）
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摘要
High concentrations of PM_(2.5) are universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM_(2.5) concentrations for regional air quality control and management. In this study, PM_(2.5) data from 2000 to 2015 was determined from an inversion of NASA atmospheric remote sensing images. Using geo-statistics, geographic detectors, and geo-spatial analysis methods, the spatio-temporal evolution patterns and driving factors of PM_(2.5) concentration in China were evaluated. The main results are as follows.(1) In general, the average concentration of PM_(2.5) in China increased quickly and reached its peak value in 2006; subsequently, concentrations remained between 21.84 and 35.08 μg/m3.(2) PM_(2.5) is strikingly heterogeneous in China, with higher concentrations in the north and east than in the south and west. In particular, areas with relatively high PM_(2.5) concentrations are primarily in four regions, the Huang-Huai-Hai Plain, Lower Yangtze River Delta Plain, Sichuan Basin, and Taklimakan Desert. Among them, Beijing-Tianjin-Hebei Region has the highest concentration of PM_(2.5).(3) The center of gravity of PM_(2.5) has generally moved northeastward, which indicates an increasingly serious haze in eastern China. High-value PM_(2.5) concentrations have moved eastward, while low-value PM_(2.5) has moved westward.(4) Spatial autocorrelation analysis indicates a significantly positive spatial correlation. The "High-High" PM_(2.5) agglomeration areas are distributed in the Huang-Huai-Hai Plain, Fenhe-Weihe River Basin, Sichuan Basin, and Jianghan Plain regions. The "Low-Low" PM_(2.5) agglomeration areas include Inner Mongolia and Heilongjiang, north of the Great Wall, Qinghai-Tibet Plateau, and Taiwan, Hainan, and Fujian and other southeast coastal cities and islands.(5) Geographic detection analysis indicates that both natural and anthropogenic factors account for spatial variations in PM_(2.5) concentration. Geographical location, population density, automobile quantity, industrial discharge, and straw burning are the main driving forces of PM_(2.5) concentration in China.
High concentrations of PM_(2.5) are universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM_(2.5) concentrations for regional air quality control and management. In this study, PM_(2.5) data from 2000 to 2015 was determined from an inversion of NASA atmospheric remote sensing images. Using geo-statistics, geographic detectors, and geo-spatial analysis methods, the spatio-temporal evolution patterns and driving factors of PM_(2.5) concentration in China were evaluated. The main results are as follows.(1) In general, the average concentration of PM_(2.5) in China increased quickly and reached its peak value in 2006; subsequently, concentrations remained between 21.84 and 35.08 μg/m3.(2) PM_(2.5) is strikingly heterogeneous in China, with higher concentrations in the north and east than in the south and west. In particular, areas with relatively high PM_(2.5) concentrations are primarily in four regions, the Huang-Huai-Hai Plain, Lower Yangtze River Delta Plain, Sichuan Basin, and Taklimakan Desert. Among them, Beijing-Tianjin-Hebei Region has the highest concentration of PM_(2.5).(3) The center of gravity of PM_(2.5) has generally moved northeastward, which indicates an increasingly serious haze in eastern China. High-value PM_(2.5) concentrations have moved eastward, while low-value PM_(2.5) has moved westward.(4) Spatial autocorrelation analysis indicates a significantly positive spatial correlation. The "High-High" PM_(2.5) agglomeration areas are distributed in the Huang-Huai-Hai Plain, Fenhe-Weihe River Basin, Sichuan Basin, and Jianghan Plain regions. The "Low-Low" PM_(2.5) agglomeration areas include Inner Mongolia and Heilongjiang, north of the Great Wall, Qinghai-Tibet Plateau, and Taiwan, Hainan, and Fujian and other southeast coastal cities and islands.(5) Geographic detection analysis indicates that both natural and anthropogenic factors account for spatial variations in PM_(2.5) concentration. Geographical location, population density, automobile quantity, industrial discharge, and straw burning are the main driving forces of PM_(2.5) concentration in China.
High concentrations of PM_(2.5) are universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM_(2.5) concentrations for regional air quality control and management. In this study, PM_(2.5) data from 2000 to 2015 was determined from an inversion of NASA atmospheric remote sensing images. Using geo-statistics, geographic detectors, and geo-spatial analysis methods, the spatio-temporal evolution patterns and driving factors of PM_(2.5) concentration in China were evaluated. The main results are as follows.(1) In general, the average concentration of PM_(2.5) in China increased quickly and reached its peak value in 2006; subsequently, concentrations remained between 21.84 and 35.08 μg/m3.(2) PM_(2.5) is strikingly heterogeneous in China, with higher concentrations in the north and east than in the south and west. In particular, areas with relatively high PM_(2.5) concentrations are primarily in four regions, the Huang-Huai-Hai Plain, Lower Yangtze River Delta Plain, Sichuan Basin, and Taklimakan Desert. Among them, Beijing-Tianjin-Hebei Region has the highest concentration of PM_(2.5).(3) The center of gravity of PM_(2.5) has generally moved northeastward, which indicates an increasingly serious haze in eastern China. High-value PM_(2.5) concentrations have moved eastward, while low-value PM_(2.5) has moved westward.(4) Spatial autocorrelation analysis indicates a significantly positive spatial correlation. The "High-High" PM_(2.5) agglomeration areas are distributed in the Huang-Huai-Hai Plain, Fenhe-Weihe River Basin, Sichuan Basin, and Jianghan Plain regions. The "Low-Low" PM_(2.5) agglomeration areas include Inner Mongolia and Heilongjiang, north of the Great Wall, Qinghai-Tibet Plateau, and Taiwan, Hainan, and Fujian and other southeast coastal cities and islands.(5) Geographic detection analysis indicates that both natural and anthropogenic factors account for spatial variations in PM_(2.5) concentration. Geographical location, population density, automobile quantity, industrial discharge, and straw burning are the main driving forces of PM_(2.5) concentration in China.
引文
Austin E,Coull B A,Zanobetti A et al.,2013.A framework to spatially cluster air pollution monitoring sites in US based on the PM2.5 composition.Environment International,59(3):244-254.
Beckerman B S,Jerrett M,Serre M et al.,2013.A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.Environmental Science&Technology,47(13):7233-7241.
Bell M L,Dominici F,Ebisu K et al.,2007.Spatial and temporal variation in PM2.5 chemical composition in the United States for health effects studies.Environmental Health Perspectives,115(7):989-995.
Cao G L,Zhang X Y,Gong S L et al.,2011.Emission inventories of primary particles and pollutant gases for China.Atmospheric Environment,45(37):6802-6811.(in Chinese)
Charron A,Harrison R M,2005.Fine(PM2.5)and coarse(PM2.5-10)particulate matter on a heavily trafficked London highway:?Sources and processes.Environmental Science&Technology,39(20):7768-7776.
Cheng S,Yang L X,Zhou X et al.,2011.Evaluating PM2.5 ionic components and source apportionment in Jinan,China from 2004 to 2008 using trajectory statistical methods.Journal of Environmental Monitoring,13(6):1662-1671.
Chow J C,Chen L W,Watson J G et al.,2006.PM2.5 chemical composition and spatiotemporal variability during the California regional PM10/PM2.5 air quality study(CRPAQS).Journal of Geophysical Research Atmospheres,111(D10):1-17.
Chu H J,Huang B,Lin C Y,2015.Modeling the spatio-temporal heterogeneity in the PM10-PM2.5 relationship.Atmospheric Environment,102(2):176-182.
Delfino R J,Sioutas C,Malik S,2005.Potential role of ultrafine particles in associations between airborne particle mass and cardiovascular health.Environmental Health Perspectives,113(8):934-946.
Dockery D W,Pope CA,Xu X et al.,1994.An association between air pollution and mortality in six US cities.New England Journal of Medicine,329(24):1753-1759.
Franklin M,Koutrakis P,Schwartz P,2008.The role of particle composition on the association between PM2.5 and mortality.Epidemiology,19(5):680-689.
Gao M,Cao J,Seto E.A,2015.A distributed network of low-cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi’an,China.Environmental Pollution,199(4):56-65.
Gelencsér A,May B,Simpson D et al.,2007.Source apportionment of PM2.5 organic aerosol over Europe:Primary/secondary,natural/anthropogenic,and fossil/biogenic origin.Journal of Geophysical Research Atmospheres,112(D23):1-12.
Gramsch E,Cereceda-Balic F,Oyola P et al.,2006.Examination of pollution trends in Santiago de Chile with cluster analysis of PM10 and ozone data.Atmospheric Environment,40(28):5464-5475.
Guo J P,Zhang X Y,Wu Y R et al.,2011.Spatio-temporal variation trends of satellite-based aerosol optical depth in China during 1980-2008.Atmospheric Environment,45(37):6802-6811.
Henderson S B,Beckerman B,Jerrett M et al.,2007.Application of land use regression to estimate long-term concentrations of traffic-related nitrogen oxides and fine particulate matter.Environmental Science&Technology,41(7):2422-2428.
Hoek G,Brunekreef B,Goldbohm S et al.,2002.Association between mortality and indicators of traffic-related air pollution in the Netherlands:A cohort study.The Lancet,360(9341):1203-1209.
Huang,Y,Yan Q,Zhang C,2018.Spatial-temporal distribution characteristics of PM2.5 in China in 2016,Journal of Geovisualization and Spatial Analysis,2(2):1-12.
Hueglin C,Gehrig R,Baltensperger U et al.,2005.Chemical characterisation of PM2.5,PM10 and coarse particles at urban,near-city and rural sites in Switzerland.Atmospheric Environment,39(4):637-651.
Jiang Y A,Chen Y,Zhao Y Z et al.,2013.Analysis on changes of basic climatic elements and extreme events in Xinjiang,China during 1961-2010.Advances in Climate Change Research,4(1):20-29.
Kioumourtzoglou M A,Schwartz J,Weisskopf M et al.,2016.Long-term PM2.5 exposure and neurological hospital admissions in the Northeastern United States.Environmental Health Perspectives,124(1):23-29.
Kloog I,Nordio F,Coull B et al.,2012.Incorporating local land use regression and satellite aerosol optical depth in a hybrid model of spatiotemporal PM2.5 exposures in the Mid-Atlantic states.Environmental Science&Technology,46(21):11913-11921.
Laden F,Neas L M,Dockery D W et al.,2000.Association of fine particulate matter from different sources with daily mortality in six US cities.Environmental Health Perspectives,108(10):941-947.
Laden F,Schwartz J,Speizer F E et al.,2006.Reduction in fine particulate air pollution and mortality.American Journal of Respiratory and Critical Care Medicine,173(6):667-672.
Lindner A,Pitombo C S,2018.A conjoint approach of spatial statistics and a traditional method for travel mode choice issues.Journal of Geovisualization and Spatial Analysis,2(1):1-13.
Lin G,Fu J,Jiang D et al.,2013.Spatio-temporal variation of PM2.5 concentrations and their relationship with geographic and socioeconomic factors in China.International Journal of Environmental Research and Public Health,11(1):173-186.
Liu Y,Paciorek C J,Koutrakis P et al.,2009.Estimating regional spatial and temporal variability of PM2.5 concentrations using satellite data,meteorology,and land use information.Environmental Health Perspectives,117(6):886-892.
Liu Y,Sarnat JA,Kilaru V et al.,2005.Estimating ground-level PM2.5 in the eastern using satellite remote sensing.Environmental Science&Technology,39(9):3269-3278.
Liu Y S,Yang R,2012.The spatial characteristics and formation mechanism of the county urbanization in China.Acta Geographica Sinica,67(8):1011-1020.(in Chinese)
Lu B,Kong S F,Han Bin,2011.Inventory of atmospheric pollutants discharged from biomass burning in China continent in 2007.China Environmental Science,31(2):186-194.(in Chinese)
Merbitz H,Buttst?dt M,Michael S et al.,2012.GIS-based identification of spatial variables enhancing heat and poor air quality in urban areas.Applied Geography,2012,33(4):94-106.
Pope C A,2000.Review:Epidemiological basis for particulate air pollution health standards.Aerosol Science&Technology,32(1):4-14.
Pope C A,Burnett R T,Thun M J et al.,2002.Lung cancer,cardiopulmonary mortality,and long-term exposure to fine particulate air pollution.Jama,287(9):1132-1141.
Pope C A,Dockery D W,Schwartz J,1995.Review of epidemiological evidence of health effects of particulate air pollution.Inhalation Toxicology,7(1):1-18.
Samet J M,Dominici F,Curriero F C et al.,2000.Fine particulate air pollution and mortality in 20 U.S cities,1987-1994.New England Journal of Medicine,343:(24):1742-1749.
Stone B,2008.Urban sprawl and air quality in large US cities.Journal of Environmental Management,86(4):688-698.
Wang H,Dwyer-Lindgren L,Lofgren K T et al.,2012.Age specific and sex-specific mortality in 187 countries,1970-2010:A systematic analysis for the global burden of disease study 2010.The Lancet,380(9859):2071-2094.
Wang J,Christopher S A,2003.Intercomparison between satellite-derived aerosol optical thickness and PM2.5mass:Implications for air quality studies.Geophysical Research Letters,30(21):1-4.
Wang J F,Li X H,George Christakos et al.,2010.Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region,China.International Journal of Geographical Information Science,24(1):107-127.
Wang Z B,Fang C L,Xu G et al.,2015.Spatial-temporal characteristics of the PM2.5 in China in 2014.Acta Geographica Sinica,70(11):1720-1734.(in Chinese)
Wu D,2012.Hazy weather research in China in the last decade:A review.Acta Scientiae Circumstantiae,32(2):257-269.
Xu W,He F,Li H et al.,2014.Spatial and temporal variations of PM2.5 in the Pearl River Delta.Research of Environmental Sciences,27(9):951-957.
Xue W,Wu W,Fu F et al.,2015.Satellite retrieval of a heavy pollution process in January 2013 in China.Environmental Science,36,(3):794-800.(in Chinese)
Xue W B,Fu F,Wang J N et al.,2014.Numerical study on the characteristics of regional transport of PM2.5 in China.China Environmental Science,34(6):1361-1368.(in Chinese)
Yi H,Hao J,Tang X L et al.,2007.Atmospheric environmental protection in China:Current status,developmental.Energy Policy,35(2):907-915.
Zhang Y,Cao F,2015.Fine particulate matter(PM2.5)in China at a city level.Scientific Reports,5:1-11.
Zhang Y,Zhang W,Wang J et al.,2015.Establishment and application of pollutant inventory-chemical mass balance(I-CMB)model for source apportionment of PM2.5.Transactions of Atmospheric Sciences,38(2):279-284.(in Chinese)
Beckerman B S,Jerrett M,Serre M et al.,2013.A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.Environmental Science&Technology,47(13):7233-7241.
Bell M L,Dominici F,Ebisu K et al.,2007.Spatial and temporal variation in PM2.5 chemical composition in the United States for health effects studies.Environmental Health Perspectives,115(7):989-995.
Cao G L,Zhang X Y,Gong S L et al.,2011.Emission inventories of primary particles and pollutant gases for China.Atmospheric Environment,45(37):6802-6811.(in Chinese)
Charron A,Harrison R M,2005.Fine(PM2.5)and coarse(PM2.5-10)particulate matter on a heavily trafficked London highway:?Sources and processes.Environmental Science&Technology,39(20):7768-7776.
Cheng S,Yang L X,Zhou X et al.,2011.Evaluating PM2.5 ionic components and source apportionment in Jinan,China from 2004 to 2008 using trajectory statistical methods.Journal of Environmental Monitoring,13(6):1662-1671.
Chow J C,Chen L W,Watson J G et al.,2006.PM2.5 chemical composition and spatiotemporal variability during the California regional PM10/PM2.5 air quality study(CRPAQS).Journal of Geophysical Research Atmospheres,111(D10):1-17.
Chu H J,Huang B,Lin C Y,2015.Modeling the spatio-temporal heterogeneity in the PM10-PM2.5 relationship.Atmospheric Environment,102(2):176-182.
Delfino R J,Sioutas C,Malik S,2005.Potential role of ultrafine particles in associations between airborne particle mass and cardiovascular health.Environmental Health Perspectives,113(8):934-946.
Dockery D W,Pope CA,Xu X et al.,1994.An association between air pollution and mortality in six US cities.New England Journal of Medicine,329(24):1753-1759.
Franklin M,Koutrakis P,Schwartz P,2008.The role of particle composition on the association between PM2.5 and mortality.Epidemiology,19(5):680-689.
Gao M,Cao J,Seto E.A,2015.A distributed network of low-cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi’an,China.Environmental Pollution,199(4):56-65.
Gelencsér A,May B,Simpson D et al.,2007.Source apportionment of PM2.5 organic aerosol over Europe:Primary/secondary,natural/anthropogenic,and fossil/biogenic origin.Journal of Geophysical Research Atmospheres,112(D23):1-12.
Gramsch E,Cereceda-Balic F,Oyola P et al.,2006.Examination of pollution trends in Santiago de Chile with cluster analysis of PM10 and ozone data.Atmospheric Environment,40(28):5464-5475.
Guo J P,Zhang X Y,Wu Y R et al.,2011.Spatio-temporal variation trends of satellite-based aerosol optical depth in China during 1980-2008.Atmospheric Environment,45(37):6802-6811.
Henderson S B,Beckerman B,Jerrett M et al.,2007.Application of land use regression to estimate long-term concentrations of traffic-related nitrogen oxides and fine particulate matter.Environmental Science&Technology,41(7):2422-2428.
Hoek G,Brunekreef B,Goldbohm S et al.,2002.Association between mortality and indicators of traffic-related air pollution in the Netherlands:A cohort study.The Lancet,360(9341):1203-1209.
Huang,Y,Yan Q,Zhang C,2018.Spatial-temporal distribution characteristics of PM2.5 in China in 2016,Journal of Geovisualization and Spatial Analysis,2(2):1-12.
Hueglin C,Gehrig R,Baltensperger U et al.,2005.Chemical characterisation of PM2.5,PM10 and coarse particles at urban,near-city and rural sites in Switzerland.Atmospheric Environment,39(4):637-651.
Jiang Y A,Chen Y,Zhao Y Z et al.,2013.Analysis on changes of basic climatic elements and extreme events in Xinjiang,China during 1961-2010.Advances in Climate Change Research,4(1):20-29.
Kioumourtzoglou M A,Schwartz J,Weisskopf M et al.,2016.Long-term PM2.5 exposure and neurological hospital admissions in the Northeastern United States.Environmental Health Perspectives,124(1):23-29.
Kloog I,Nordio F,Coull B et al.,2012.Incorporating local land use regression and satellite aerosol optical depth in a hybrid model of spatiotemporal PM2.5 exposures in the Mid-Atlantic states.Environmental Science&Technology,46(21):11913-11921.
Laden F,Neas L M,Dockery D W et al.,2000.Association of fine particulate matter from different sources with daily mortality in six US cities.Environmental Health Perspectives,108(10):941-947.
Laden F,Schwartz J,Speizer F E et al.,2006.Reduction in fine particulate air pollution and mortality.American Journal of Respiratory and Critical Care Medicine,173(6):667-672.
Lindner A,Pitombo C S,2018.A conjoint approach of spatial statistics and a traditional method for travel mode choice issues.Journal of Geovisualization and Spatial Analysis,2(1):1-13.
Lin G,Fu J,Jiang D et al.,2013.Spatio-temporal variation of PM2.5 concentrations and their relationship with geographic and socioeconomic factors in China.International Journal of Environmental Research and Public Health,11(1):173-186.
Liu Y,Paciorek C J,Koutrakis P et al.,2009.Estimating regional spatial and temporal variability of PM2.5 concentrations using satellite data,meteorology,and land use information.Environmental Health Perspectives,117(6):886-892.
Liu Y,Sarnat JA,Kilaru V et al.,2005.Estimating ground-level PM2.5 in the eastern using satellite remote sensing.Environmental Science&Technology,39(9):3269-3278.
Liu Y S,Yang R,2012.The spatial characteristics and formation mechanism of the county urbanization in China.Acta Geographica Sinica,67(8):1011-1020.(in Chinese)
Lu B,Kong S F,Han Bin,2011.Inventory of atmospheric pollutants discharged from biomass burning in China continent in 2007.China Environmental Science,31(2):186-194.(in Chinese)
Merbitz H,Buttst?dt M,Michael S et al.,2012.GIS-based identification of spatial variables enhancing heat and poor air quality in urban areas.Applied Geography,2012,33(4):94-106.
Pope C A,2000.Review:Epidemiological basis for particulate air pollution health standards.Aerosol Science&Technology,32(1):4-14.
Pope C A,Burnett R T,Thun M J et al.,2002.Lung cancer,cardiopulmonary mortality,and long-term exposure to fine particulate air pollution.Jama,287(9):1132-1141.
Pope C A,Dockery D W,Schwartz J,1995.Review of epidemiological evidence of health effects of particulate air pollution.Inhalation Toxicology,7(1):1-18.
Samet J M,Dominici F,Curriero F C et al.,2000.Fine particulate air pollution and mortality in 20 U.S cities,1987-1994.New England Journal of Medicine,343:(24):1742-1749.
Stone B,2008.Urban sprawl and air quality in large US cities.Journal of Environmental Management,86(4):688-698.
Wang H,Dwyer-Lindgren L,Lofgren K T et al.,2012.Age specific and sex-specific mortality in 187 countries,1970-2010:A systematic analysis for the global burden of disease study 2010.The Lancet,380(9859):2071-2094.
Wang J,Christopher S A,2003.Intercomparison between satellite-derived aerosol optical thickness and PM2.5mass:Implications for air quality studies.Geophysical Research Letters,30(21):1-4.
Wang J F,Li X H,George Christakos et al.,2010.Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun Region,China.International Journal of Geographical Information Science,24(1):107-127.
Wang Z B,Fang C L,Xu G et al.,2015.Spatial-temporal characteristics of the PM2.5 in China in 2014.Acta Geographica Sinica,70(11):1720-1734.(in Chinese)
Wu D,2012.Hazy weather research in China in the last decade:A review.Acta Scientiae Circumstantiae,32(2):257-269.
Xu W,He F,Li H et al.,2014.Spatial and temporal variations of PM2.5 in the Pearl River Delta.Research of Environmental Sciences,27(9):951-957.
Xue W,Wu W,Fu F et al.,2015.Satellite retrieval of a heavy pollution process in January 2013 in China.Environmental Science,36,(3):794-800.(in Chinese)
Xue W B,Fu F,Wang J N et al.,2014.Numerical study on the characteristics of regional transport of PM2.5 in China.China Environmental Science,34(6):1361-1368.(in Chinese)
Yi H,Hao J,Tang X L et al.,2007.Atmospheric environmental protection in China:Current status,developmental.Energy Policy,35(2):907-915.
Zhang Y,Cao F,2015.Fine particulate matter(PM2.5)in China at a city level.Scientific Reports,5:1-11.
Zhang Y,Zhang W,Wang J et al.,2015.Establishment and application of pollutant inventory-chemical mass balance(I-CMB)model for source apportionment of PM2.5.Transactions of Atmospheric Sciences,38(2):279-284.(in Chinese)