Quantifying differences in secondary organic aerosols(SOAs)between the preindustrial period and the present day is crucial to assess climate forcing and environmental effects resulting from anthropogenic activities.Th...Quantifying differences in secondary organic aerosols(SOAs)between the preindustrial period and the present day is crucial to assess climate forcing and environmental effects resulting from anthropogenic activities.The lack of vegetation information for the preindustrial period and the uncertainties in describing SOA formation are two leading factors preventing simulation of SOA.This study calculated the online emissions of biogenic volatile organic compounds(VOCs)in the Aerosol and Atmospheric Chemistry Model of the Institute of Atmospheric Physics(IAP-AACM)by coupling the Model of Emissions of Gases and Aerosols from Nature(MEGAN),where the input vegetation parameters were simulated by the IAP Dynamic Global Vegetation Model(IAP-DGVM).The volatility basis set(VBS)approach was adopted to simulate SOA formation from the nontraditional pathways,i.e.,the oxidation of intermediate VOCs and aging of primary organic aerosol.Although biogenic SOAs(BSOAs)were dominant in SOAs globally in the preindustrial period,the contribution of nontraditional anthropogenic SOAs(ASOAs)to the total SOAs was up to 35.7%.In the present day,the contribution of ASOAs was 2.8 times larger than that in the preindustrial period.The contribution of nontraditional sources of SOAs to SOA was as high as 53.1%.The influence of increased anthropogenic emissions in the present day on BSOA concentrations was greater than that of increased biogenic emission changes.The response of BSOA concentrations to anthropogenic emission changes in the present day was more sensitive than that in the preindustrial period.The nontraditional sources and the atmospheric oxidation capability greatly affect the global SOA change.展开更多
Although quality assurance and quality control procedures are routinely applied in most air quality networks, outliers can still occur due to instrument malfunctions, the influence of harsh environments and the limita...Although quality assurance and quality control procedures are routinely applied in most air quality networks, outliers can still occur due to instrument malfunctions, the influence of harsh environments and the limitation of measuring methods. Such outliers pose challenges for data-powered applications such as data assimilation, statistical analysis of pollution characteristics and ensemble forecasting. Here, a fully automatic outlier detection method was developed based on the probability of residuals, which are the discrepancies between the observed and the estimated concentration values. The estimation can be conducted using filtering—or regressions when appropriate—to discriminate four types of outliers characterized by temporal and spatial inconsistency, instrument-induced low variances, periodic calibration exceptions, and less PM_(10) than PM_(2.5) in concentration observations, respectively. This probabilistic method was applied to detect all four types of outliers in hourly surface measurements of six pollutants(PM_(2.5), PM_(10),SO_2,NO_2,CO and O_3) from 1436 stations of the China National Environmental Monitoring Network during 2014-16. Among the measurements, 0.65%-5.68% are marked as outliers. with PM_(10) and CO more prone to outliers. Our method successfully identifies a trend of decreasing outliers from 2014 to 2016,which corresponds to known improvements in the quality assurance and quality control procedures of the China National Environmental Monitoring Network. The outliers can have a significant impact on the annual mean concentrations of PM_(2.5),with differences exceeding 10 μg m^(-3) at 66 sites.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
基金supported by the National Key R&D Program of China(Grant No.2020YFA0607801)the National Natural Science Foundation of China(Grant Nos.42007199 and 42377105)the National Key Scientific and Technological Infrastructure project“Earth System Science Numerical Simulator Facility”.
文摘Quantifying differences in secondary organic aerosols(SOAs)between the preindustrial period and the present day is crucial to assess climate forcing and environmental effects resulting from anthropogenic activities.The lack of vegetation information for the preindustrial period and the uncertainties in describing SOA formation are two leading factors preventing simulation of SOA.This study calculated the online emissions of biogenic volatile organic compounds(VOCs)in the Aerosol and Atmospheric Chemistry Model of the Institute of Atmospheric Physics(IAP-AACM)by coupling the Model of Emissions of Gases and Aerosols from Nature(MEGAN),where the input vegetation parameters were simulated by the IAP Dynamic Global Vegetation Model(IAP-DGVM).The volatility basis set(VBS)approach was adopted to simulate SOA formation from the nontraditional pathways,i.e.,the oxidation of intermediate VOCs and aging of primary organic aerosol.Although biogenic SOAs(BSOAs)were dominant in SOAs globally in the preindustrial period,the contribution of nontraditional anthropogenic SOAs(ASOAs)to the total SOAs was up to 35.7%.In the present day,the contribution of ASOAs was 2.8 times larger than that in the preindustrial period.The contribution of nontraditional sources of SOAs to SOA was as high as 53.1%.The influence of increased anthropogenic emissions in the present day on BSOA concentrations was greater than that of increased biogenic emission changes.The response of BSOA concentrations to anthropogenic emission changes in the present day was more sensitive than that in the preindustrial period.The nontraditional sources and the atmospheric oxidation capability greatly affect the global SOA change.
基金supported by the National Natural Science Foundation (Grant Nos.91644216 and 41575128)the CAS Information Technology Program (Grant No.XXH13506-302)Guangdong Provincial Science and Technology Development Special Fund (No.2017B020216007)
文摘Although quality assurance and quality control procedures are routinely applied in most air quality networks, outliers can still occur due to instrument malfunctions, the influence of harsh environments and the limitation of measuring methods. Such outliers pose challenges for data-powered applications such as data assimilation, statistical analysis of pollution characteristics and ensemble forecasting. Here, a fully automatic outlier detection method was developed based on the probability of residuals, which are the discrepancies between the observed and the estimated concentration values. The estimation can be conducted using filtering—or regressions when appropriate—to discriminate four types of outliers characterized by temporal and spatial inconsistency, instrument-induced low variances, periodic calibration exceptions, and less PM_(10) than PM_(2.5) in concentration observations, respectively. This probabilistic method was applied to detect all four types of outliers in hourly surface measurements of six pollutants(PM_(2.5), PM_(10),SO_2,NO_2,CO and O_3) from 1436 stations of the China National Environmental Monitoring Network during 2014-16. Among the measurements, 0.65%-5.68% are marked as outliers. with PM_(10) and CO more prone to outliers. Our method successfully identifies a trend of decreasing outliers from 2014 to 2016,which corresponds to known improvements in the quality assurance and quality control procedures of the China National Environmental Monitoring Network. The outliers can have a significant impact on the annual mean concentrations of PM_(2.5),with differences exceeding 10 μg m^(-3) at 66 sites.
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.