Fine particulate matter(PM_(2.5))and ozone(O_(3))double high pollution(DHP)events have occurred frequently over China in recent years,but their causes are not completely clear.In this study,the spatiotemporal distribu...Fine particulate matter(PM_(2.5))and ozone(O_(3))double high pollution(DHP)events have occurred frequently over China in recent years,but their causes are not completely clear.In this study,the spatiotemporal distribution of DHP events in China during 2013–20 is analyzed.The synoptic types affecting DHP events are identified with the Lamb–Jenkinson circulation classification method.The meteorological and chemical causes of DHP events controlled by the main synoptic types are further investigated.Results show that DHP events(1655 in total for China during 2013–20)mainly occur over the North China Plain,Yangtze River Delta,Pearl River Delta,Sichuan Basin,and Central China.The occurrence frequency increases by 5.1%during 2013–15,and then decreases by 56.1%during 2015–20.The main circulation types of DHP events are“cyclone”and“anticyclone”,accounting for over 40%of all DHP events over five main polluted regions in China,followed by southerly or easterly flat airflow types,like“southeast”,“southwest”,and“east”.Compared with non-DHP events,DHP events are characterized by static or weak wind,high temperature(20.9℃ versus 23.1℃)and low humidity(70.0%versus 64.9%).The diurnal cycles of meteorological conditions cause PM_(2.5)(0300–1200 LST,Local Standard Time=UTC+8 hours)and O_(3)(1500–2100 LST)to exceed the national standards at different periods of the DHP day.Three pollutant conversion indices further indicate the rapid secondary conversions during DHP events,and thus the concentrations of NO_(2),SO_(2) and volatile organic compounds decrease by 13.1%,4.7%and 4.4%,respectively.The results of this study can be informative for future decisions on the management of DHP events.展开更多
Aerosol ammonium(NH_(4)^(+)),mainly produced from the reactions of ammonia(NH_(3))with acids in the atmosphere,has significant impacts on air pollution,radiative forcing,and human health.Understanding the source and f...Aerosol ammonium(NH_(4)^(+)),mainly produced from the reactions of ammonia(NH_(3))with acids in the atmosphere,has significant impacts on air pollution,radiative forcing,and human health.Understanding the source and formation mechanism of NH_(4)^(+)can provide scientific insights into air quality improvements.However,the sources of NH_(3)in urban areas are not well understood,and few studies focus on NH_(3)/NH_(4)^(+)at different heights within the atmospheric boundary layer,which hinders a comprehensive understanding of aerosol NH_(4)^(+).In this study,we perform both field observation and modeling studies(the Community Multiscale Air Quality,CMAQ)to investigate regional NH_(3)emission sources and vertically resolved NH_(4)^(+)formation mechanisms during the winter in Beijing.Both stable nitrogen isotope analyses and CMAQ model suggest that combustion-related NH_(3)emissions,including fossil fuel sources,NH_(3)slip,and biomass burning,are important sources of aerosol NH_(4)^(+)with more than 60%contribution occurring on heavily polluted days.In contrast,volatilization-related NH_(3)sources(livestock breeding,N-fertilizer application,and human waste)are dominant on clean days.Combustion-related NH_(3)is mostly local from Beijing,and biomass burning is likely an important NH_(3)source(~15%–20%)that was previously overlooked.More effective control strategies such as the two-product(e.g.,reducing both SO_(2)and NH_(3))control policy should be considered to improve air quality.展开更多
Land use regression （LUR） model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regre...Land use regression （LUR） model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regression （MLR） equations were established based on the most significant variables for NO2 in heating season （R2 = 0.74）, and non-heating season （R2 = 0.61） in the whole study area; and PM10 in heating season （R2 = 0.72）, and non-heating season （R2 = 0.49）. Maps of spatial concentration distribution for NO2 and PM10 were obtained based on the MLR equations （resolution is 10 krn）. Intercepts of MLR equations were 0.050 （NOz, heating season）, 0.035 （NO2, non-heating season）, 0.068 （PM10, heating season）, and 0.092 （PM10, non-beating season） in the whole study area. In the central area of Tianjin region, the intercepts were 0.042 （NO2, heating season）, 0.043 （NO2, non-heating season）, 0.087 （PM10, heating season）, and 0.096 （PMl0, non-heating season）. These intercept values might imply an area＇s background concentrations. Predicted result derived from LUR model in the central area was better than that in the whole study area. Rz values increased 0.09 （heating season） and 0.18 （non-heating season） for NO2, and 0.08 （heating season） and 0.04 （non-heating season） for PMl0. In terms of R2, LUR model performed more effectively in heating season than non-heating season in the study area and gave a better result for NOz compared with PM10.展开更多
Concentrations of atmospheric PM10 and chemical components （including twenty-one elements, nine ions, organic carbon （OC） and elemental carbon （EC）） were measured at five sites in a heavily industrial region of ...Concentrations of atmospheric PM10 and chemical components （including twenty-one elements, nine ions, organic carbon （OC） and elemental carbon （EC）） were measured at five sites in a heavily industrial region of Shenzhen, China in 2005. Results showed that PM10 concentrations exhibited the highest values at 264 μg/m3 at the site near a harbor with the influence of harbor activities. Sulfur exhibited the highest concentrations （from 2419 to 3995 ng/m3） of all the studied elements, which may be related to the influence of coal used as fuel in this area for industrial plants. This was verified by the high mass percentages of SO42-, which accounted for 34.3%-39.7% of the total ions. NO3-/SO42- ratios varied from 0.64-0.71, which implies coal combustion was predominant compared with vehicle emission. The anion/cation ratios range was close to 0.95, indicating anion deficiency in this region. The harbor site showed the highest OC and EC concentrations, with the influence of emission from vessels. Secondary organic carbon accounted for about 22.6%-38.7% of OC, with the highest percentage occurring at the site adjacent to a coal-fired power plant and wood plant. The mass closure model performed well in this heavily industrial region, with significant correlation obtained between chemically determined and gravimetrically measured PM10 mass. The main constituents of PM10 were found to be organic materials （30.9%-69.5%）, followed by secondary inorganic aerosol （7.9%-25.0%）, crustal materials （6.7%-13.8%）, elemental carbon （3.5%-10.8%）, sea salt （2.4%-6.2%） and trace elements （2.0%-4.9%） in this heavily industrialized region. Principal component analysis indicated that the main sources for particulate matter in this industrial region were crustal materials and coal/wood combustion, oil combustion, secondary aerosols, industrial processes and vehicle emission.展开更多
Advancing the understanding of the spatial aspects of air pollution in the city regional environment is an area where improved methods can be of great benefit to exposure assessment and policy support. We created land...Advancing the understanding of the spatial aspects of air pollution in the city regional environment is an area where improved methods can be of great benefit to exposure assessment and policy support. We created land use regression （LUR） models for SO2, NO2 and PMI0 for Tianjin, China. Traffic volumes, road networks, land use data, population density, meteorological conditions, physical conditions and satellite-derived greenness, brightness and wetness were used for predicting SOa, NO2 and PMt0 concentrations. We incorporated data on industrial point sources to improve LUR model performance. In order to consider the impact of different sources, we calculated the PSIndex, LSIndex and area of different land use types （agricultural land, industrial land, commercial land, residential land, green space and water area） within different buffer radii （1 to 20 kin）. This method makes up for the lack of consideration of source impact based on the LUR model. Remote sensing-derived variables were significantly correlated with gaseous pollutant concentrations such as SO2 and NO2. R2 values of the multiple linear regression equations for SO2, NO2 and PM10 were 0.78, 0.89 and 0.84, respectively, and the RMSE values were 0.32, 0.18 and 0.21, respectively. Model predictions at validation monitoring sites went well with predictions generally within 15% of measured values. Compared to the relationship between dependent variables and simple variables （such as traffic variables or meteorological condition variables）, the relationship between dependent variables and integrated variables was more consistent with a linear relationship. Such integration has a discernable influence on both the overall model prediction and health effects assessment on the spatial distribution of air pollution in the city region.展开更多
To compare the inorganic chemical compositions of TSP（total suspended paniculate）,PM10（particulate matter with an aerodynamic diameter less than 10 μm） and PM2.5（particulate matter with an aerodynamic diameter l...To compare the inorganic chemical compositions of TSP（total suspended paniculate）,PM10（particulate matter with an aerodynamic diameter less than 10 μm） and PM2.5（particulate matter with an aerodynamic diameter less than 2.5 μm） in southern and northern cities in China,atmospheric particles were synchronously collected in Dalian（the northern city）and Xiamen（the southern city） in spring and autumn of 2004.The mass concentrations,twenty-three elements and nine soluble ions were assessed.The results show that in Dalian,the mass concentrations of Mg,Al,Ca,Mn and Fe in spring were 4.0-10.1,2.6-8.0,4.1-12,1.2-3.6 and 2.9-7.9 times higher,respectively,than those in Xiamen.The dust storm influence is more obvious in Dalian in spring.However,in Xiamen,heavy metals accounted for 13.9%-17.9%of TSP,while heavy metals contributed to 5.5%-9.3%of TSP in Dalian.These concentrations suggest that heavy metal pollution in Xiamen was more serious.In addition,the concentrations of Na＋,Cl-,Ca2＋ and Mg2＋ were higher in Dalian due to the influence of marine aerosol,construction activities and soil dust.The NO3-/SO42- ratios in Dalian（0.25-0.49） were lower than those in Xiamen（0.51-0.62）,indicating that the contributions of vehicle emission to particles in Xiamen were higher.Coefficient of divergence values was higher than 0.40,implying that the inorganic chemical composition profiles for the particles of Dalian and Xiamen were quite different from each other.展开更多
Light-absorbing organic carbon(OC),sometimes known as Brown Carbon(BrC),has been recognized as an important fraction of carbonaceous aerosols substantially affecting radiative forcing.This study firstly developed a bo...Light-absorbing organic carbon(OC),sometimes known as Brown Carbon(BrC),has been recognized as an important fraction of carbonaceous aerosols substantially affecting radiative forcing.This study firstly developed a bottom-up estimate of global primary BrC,and discussed its spatiotemporal distribution and source contributions from 1960 to 2010.The global total primary BrC emission from both natural and anthropogenic sources in 2010 was 7.26(5.98-8.93 as an interquartile range)Tg,with 43.5%from anthropogenic sources.High primary BrC emissions were in regions such as Africa,South America,South and East Asia with natural sources(wild fires and deforestation)contributing over 70%in the former two regions,while in East Asia,anthropogenic sources,especially residential solid fuel combustion,accounted for over 80%of the regional total BrC emissions.Globally,the historical trend was mainly driven by anthropogenic sources,which increased from 1960 to 1990 and then started to decline.Residential emissions significantly impacted on emissions and temporal trends that varied by region.In South and Southeast Asia,the emissions increased obviously due to population growth and a slow transition from solid fuels to clean modern energies in the residential sector.It is estimated that in primary OC,the global average was about 20%BrC,but this ratio varied from 13%to 47%,depending on sector and region.In areas with high residential solid fuel combustion emissions,the ratio was generally twice the value in other areas.Uncertainties in the work are associated with the concept of BrC and measurement technologies,pointing to the need for more studies on BrC analysis and quantification in both emissions and the air.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.41830965 and 41905112)the Key Program of the Ministry of Science and Technology of the People’s Republic of China(Grant No.2019YFC0214703)+2 种基金the Hubei Natural Science Foundation(Grant No.2022CFB027)supported by the State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry(Grant No.LAPC-KF-2023-07)the Key Laboratory of Atmospheric Chemistry,China Meteorological Administration(Grant No.2023B08).
文摘Fine particulate matter(PM_(2.5))and ozone(O_(3))double high pollution(DHP)events have occurred frequently over China in recent years,but their causes are not completely clear.In this study,the spatiotemporal distribution of DHP events in China during 2013–20 is analyzed.The synoptic types affecting DHP events are identified with the Lamb–Jenkinson circulation classification method.The meteorological and chemical causes of DHP events controlled by the main synoptic types are further investigated.Results show that DHP events(1655 in total for China during 2013–20)mainly occur over the North China Plain,Yangtze River Delta,Pearl River Delta,Sichuan Basin,and Central China.The occurrence frequency increases by 5.1%during 2013–15,and then decreases by 56.1%during 2015–20.The main circulation types of DHP events are“cyclone”and“anticyclone”,accounting for over 40%of all DHP events over five main polluted regions in China,followed by southerly or easterly flat airflow types,like“southeast”,“southwest”,and“east”.Compared with non-DHP events,DHP events are characterized by static or weak wind,high temperature(20.9℃ versus 23.1℃)and low humidity(70.0%versus 64.9%).The diurnal cycles of meteorological conditions cause PM_(2.5)(0300–1200 LST,Local Standard Time=UTC+8 hours)and O_(3)(1500–2100 LST)to exceed the national standards at different periods of the DHP day.Three pollutant conversion indices further indicate the rapid secondary conversions during DHP events,and thus the concentrations of NO_(2),SO_(2) and volatile organic compounds decrease by 13.1%,4.7%and 4.4%,respectively.The results of this study can be informative for future decisions on the management of DHP events.
基金supported by the National Natural Science Foundation of China(42130513,41905110,and 41961130384)the Royal Society Newton Advanced Fellowship,United Kingdom(NAFR1191220)the Research Grants Council of the Hong Kong Special Administrative Region,China(T24/504/17 and A-Poly U502/16)。
文摘Aerosol ammonium(NH_(4)^(+)),mainly produced from the reactions of ammonia(NH_(3))with acids in the atmosphere,has significant impacts on air pollution,radiative forcing,and human health.Understanding the source and formation mechanism of NH_(4)^(+)can provide scientific insights into air quality improvements.However,the sources of NH_(3)in urban areas are not well understood,and few studies focus on NH_(3)/NH_(4)^(+)at different heights within the atmospheric boundary layer,which hinders a comprehensive understanding of aerosol NH_(4)^(+).In this study,we perform both field observation and modeling studies(the Community Multiscale Air Quality,CMAQ)to investigate regional NH_(3)emission sources and vertically resolved NH_(4)^(+)formation mechanisms during the winter in Beijing.Both stable nitrogen isotope analyses and CMAQ model suggest that combustion-related NH_(3)emissions,including fossil fuel sources,NH_(3)slip,and biomass burning,are important sources of aerosol NH_(4)^(+)with more than 60%contribution occurring on heavily polluted days.In contrast,volatilization-related NH_(3)sources(livestock breeding,N-fertilizer application,and human waste)are dominant on clean days.Combustion-related NH_(3)is mostly local from Beijing,and biomass burning is likely an important NH_(3)source(~15%–20%)that was previously overlooked.More effective control strategies such as the two-product(e.g.,reducing both SO_(2)and NH_(3))control policy should be considered to improve air quality.
基金supported by the Special Environmental Research Funds for Public Welfare (No. 200709048,200909005)the National Natural Science Foundation of China (No. 20677030)
文摘Land use regression （LUR） model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regression （MLR） equations were established based on the most significant variables for NO2 in heating season （R2 = 0.74）, and non-heating season （R2 = 0.61） in the whole study area; and PM10 in heating season （R2 = 0.72）, and non-heating season （R2 = 0.49）. Maps of spatial concentration distribution for NO2 and PM10 were obtained based on the MLR equations （resolution is 10 krn）. Intercepts of MLR equations were 0.050 （NOz, heating season）, 0.035 （NO2, non-heating season）, 0.068 （PM10, heating season）, and 0.092 （PM10, non-beating season） in the whole study area. In the central area of Tianjin region, the intercepts were 0.042 （NO2, heating season）, 0.043 （NO2, non-heating season）, 0.087 （PM10, heating season）, and 0.096 （PMl0, non-heating season）. These intercept values might imply an area＇s background concentrations. Predicted result derived from LUR model in the central area was better than that in the whole study area. Rz values increased 0.09 （heating season） and 0.18 （non-heating season） for NO2, and 0.08 （heating season） and 0.04 （non-heating season） for PMl0. In terms of R2, LUR model performed more effectively in heating season than non-heating season in the study area and gave a better result for NOz compared with PM10.
基金supported by the Research and Applicationof Supported Technology for Ecologic Effect Assessment and Decision-Making of the Large Scale Energy Base Pattern (No. 2012BAC10B01)the National Natural Science Foundation of China (No. 21277132)
文摘Concentrations of atmospheric PM10 and chemical components （including twenty-one elements, nine ions, organic carbon （OC） and elemental carbon （EC）） were measured at five sites in a heavily industrial region of Shenzhen, China in 2005. Results showed that PM10 concentrations exhibited the highest values at 264 μg/m3 at the site near a harbor with the influence of harbor activities. Sulfur exhibited the highest concentrations （from 2419 to 3995 ng/m3） of all the studied elements, which may be related to the influence of coal used as fuel in this area for industrial plants. This was verified by the high mass percentages of SO42-, which accounted for 34.3%-39.7% of the total ions. NO3-/SO42- ratios varied from 0.64-0.71, which implies coal combustion was predominant compared with vehicle emission. The anion/cation ratios range was close to 0.95, indicating anion deficiency in this region. The harbor site showed the highest OC and EC concentrations, with the influence of emission from vessels. Secondary organic carbon accounted for about 22.6%-38.7% of OC, with the highest percentage occurring at the site adjacent to a coal-fired power plant and wood plant. The mass closure model performed well in this heavily industrial region, with significant correlation obtained between chemically determined and gravimetrically measured PM10 mass. The main constituents of PM10 were found to be organic materials （30.9%-69.5%）, followed by secondary inorganic aerosol （7.9%-25.0%）, crustal materials （6.7%-13.8%）, elemental carbon （3.5%-10.8%）, sea salt （2.4%-6.2%） and trace elements （2.0%-4.9%） in this heavily industrialized region. Principal component analysis indicated that the main sources for particulate matter in this industrial region were crustal materials and coal/wood combustion, oil combustion, secondary aerosols, industrial processes and vehicle emission.
基金supported by the Special Environmental Research Funds for Public Welfare (No. 200909005)the National Natural Science Foundation of China (No.20677030)the Doctor Funds of Tianjin Normal University (No. 52XB1110)
文摘Advancing the understanding of the spatial aspects of air pollution in the city regional environment is an area where improved methods can be of great benefit to exposure assessment and policy support. We created land use regression （LUR） models for SO2, NO2 and PMI0 for Tianjin, China. Traffic volumes, road networks, land use data, population density, meteorological conditions, physical conditions and satellite-derived greenness, brightness and wetness were used for predicting SOa, NO2 and PMt0 concentrations. We incorporated data on industrial point sources to improve LUR model performance. In order to consider the impact of different sources, we calculated the PSIndex, LSIndex and area of different land use types （agricultural land, industrial land, commercial land, residential land, green space and water area） within different buffer radii （1 to 20 kin）. This method makes up for the lack of consideration of source impact based on the LUR model. Remote sensing-derived variables were significantly correlated with gaseous pollutant concentrations such as SO2 and NO2. R2 values of the multiple linear regression equations for SO2, NO2 and PM10 were 0.78, 0.89 and 0.84, respectively, and the RMSE values were 0.32, 0.18 and 0.21, respectively. Model predictions at validation monitoring sites went well with predictions generally within 15% of measured values. Compared to the relationship between dependent variables and simple variables （such as traffic variables or meteorological condition variables）, the relationship between dependent variables and integrated variables was more consistent with a linear relationship. Such integration has a discernable influence on both the overall model prediction and health effects assessment on the spatial distribution of air pollution in the city region.
基金supported by the National Natural Science Foundation of China(No.41175111)
文摘To compare the inorganic chemical compositions of TSP（total suspended paniculate）,PM10（particulate matter with an aerodynamic diameter less than 10 μm） and PM2.5（particulate matter with an aerodynamic diameter less than 2.5 μm） in southern and northern cities in China,atmospheric particles were synchronously collected in Dalian（the northern city）and Xiamen（the southern city） in spring and autumn of 2004.The mass concentrations,twenty-three elements and nine soluble ions were assessed.The results show that in Dalian,the mass concentrations of Mg,Al,Ca,Mn and Fe in spring were 4.0-10.1,2.6-8.0,4.1-12,1.2-3.6 and 2.9-7.9 times higher,respectively,than those in Xiamen.The dust storm influence is more obvious in Dalian in spring.However,in Xiamen,heavy metals accounted for 13.9%-17.9%of TSP,while heavy metals contributed to 5.5%-9.3%of TSP in Dalian.These concentrations suggest that heavy metal pollution in Xiamen was more serious.In addition,the concentrations of Na＋,Cl-,Ca2＋ and Mg2＋ were higher in Dalian due to the influence of marine aerosol,construction activities and soil dust.The NO3-/SO42- ratios in Dalian（0.25-0.49） were lower than those in Xiamen（0.51-0.62）,indicating that the contributions of vehicle emission to particles in Xiamen were higher.Coefficient of divergence values was higher than 0.40,implying that the inorganic chemical composition profiles for the particles of Dalian and Xiamen were quite different from each other.
基金provided by the National Natural Science Foundation(42077328,41922057,41991312 and 41830641)the undergraduate student research training program of the Ministry of Education of People's Republic of China(B111).
文摘Light-absorbing organic carbon(OC),sometimes known as Brown Carbon(BrC),has been recognized as an important fraction of carbonaceous aerosols substantially affecting radiative forcing.This study firstly developed a bottom-up estimate of global primary BrC,and discussed its spatiotemporal distribution and source contributions from 1960 to 2010.The global total primary BrC emission from both natural and anthropogenic sources in 2010 was 7.26(5.98-8.93 as an interquartile range)Tg,with 43.5%from anthropogenic sources.High primary BrC emissions were in regions such as Africa,South America,South and East Asia with natural sources(wild fires and deforestation)contributing over 70%in the former two regions,while in East Asia,anthropogenic sources,especially residential solid fuel combustion,accounted for over 80%of the regional total BrC emissions.Globally,the historical trend was mainly driven by anthropogenic sources,which increased from 1960 to 1990 and then started to decline.Residential emissions significantly impacted on emissions and temporal trends that varied by region.In South and Southeast Asia,the emissions increased obviously due to population growth and a slow transition from solid fuels to clean modern energies in the residential sector.It is estimated that in primary OC,the global average was about 20%BrC,but this ratio varied from 13%to 47%,depending on sector and region.In areas with high residential solid fuel combustion emissions,the ratio was generally twice the value in other areas.Uncertainties in the work are associated with the concept of BrC and measurement technologies,pointing to the need for more studies on BrC analysis and quantification in both emissions and the air.
