In recent years,the issue of PM_(2.5)-O_(3)compound pollution has become a significant global environmental concern.This study examines the spatial and temporal patterns of global PM_(2.5)-O_(3)compound pollution and ...In recent years,the issue of PM_(2.5)-O_(3)compound pollution has become a significant global environmental concern.This study examines the spatial and temporal patterns of global PM_(2.5)-O_(3)compound pollution and exposure risks,firstly at the global and urban scale,using spatial statistical regression,exposure risk assessment,and trend analyses based on the datasets of daily PM_(2.5)and surface O_(3)concentrations monitored in 120 cities around the world from 2019 to 2022.Additionally,on the basis of the common emission sources,spatial heterogeneity,interacting chemical mechanisms,and synergistic exposure risk levels between PM_(2.5)and O_(3)pollution,we proposed a synergistic PM_(2.5)-O_(3)control framework for the joint control of PM_(2.5)and O3.The results indicated that:(1)Nearly 50%of cities worldwide were affected by PM_(2.5)-O_(3)compound pollution,with China,South Korea,Japan,and India being the global hotspots for PM2.5-O3 compound pollution;(2)Cities with PM_(2.5)-O_(3)compound pollution have exposure risk levels dominated by ST t ST(Stabilization)and ST t HR(High Risk).Exposure risk levels of compound pollution in developing countries are significantly higher than those in developed countries,with unequal exposure characteristics;(3)The selected cities showed significant positive spatial correlations between PM_(2.5)and O_(3)concentrations,which were consistent with the spatial distribution of the precursors NOx and VOCs;(4)During the study period,52.5%of cities worldwide achieved synergistic reductions in annual average PM_(2.5)and O_(3)concentrations.The average PM_(2.5)concentration in these cities decreased by 13.97%,while the average O_(3)concentration decreased by 19.18%.This new solution offers the opportunity to construct intelligent and healthy cities in the upcoming low–carbon transition.展开更多
Recently,air pollution especially fine particulate matters(PM_(2.5))and ozone(O_(3))has become a severe issue in China.In this study,we first characterized the temporal trends of PM_(2.5) and O_(3) for Beijing,Guangzh...Recently,air pollution especially fine particulate matters(PM_(2.5))and ozone(O_(3))has become a severe issue in China.In this study,we first characterized the temporal trends of PM_(2.5) and O_(3) for Beijing,Guangzhou,Shanghai,andWuhan respectively during 2018-2020.The annual mean PM2.5 has decreased by 7.82%-33.92%,while O_(3) concentration showed insignificant variations by-6.77%-4.65%during 2018-2020.The generalized additive models(GAMs)were implemented to quantify the contribution of individual meteorological factors and their gas precursors on PM_(2.5) and O_(3).On a short-term perspective,GAMs modeling shows that the daily variability of PM_(2.5) concentration is largely related to the variation of precursor gases(R=0.67-0.90),while meteorological conditions mainly affect the daily variability of O_(3) concentration(R=0.65-0.80)during 2018-2020.The impact of COVID-19 lockdown on PM_(2.5) and O_(3) concentrations were also quantified by using GAMs.During the 2020 lockdown,PM_(2.5) decreased significantly for these megacities,yet the ozone concentration showed an increasing trend compared to 2019.The GAMs analysis indicated that the contribution of precursor gases to PM_(2.5) and O_(3) changes is 3-8 times higher than that of meteorological factors.In general,GAMsmodeling on air quality is helpful to the understanding and control of PM2.5 and O3 pollution in China.展开更多
文摘In recent years,the issue of PM_(2.5)-O_(3)compound pollution has become a significant global environmental concern.This study examines the spatial and temporal patterns of global PM_(2.5)-O_(3)compound pollution and exposure risks,firstly at the global and urban scale,using spatial statistical regression,exposure risk assessment,and trend analyses based on the datasets of daily PM_(2.5)and surface O_(3)concentrations monitored in 120 cities around the world from 2019 to 2022.Additionally,on the basis of the common emission sources,spatial heterogeneity,interacting chemical mechanisms,and synergistic exposure risk levels between PM_(2.5)and O_(3)pollution,we proposed a synergistic PM_(2.5)-O_(3)control framework for the joint control of PM_(2.5)and O3.The results indicated that:(1)Nearly 50%of cities worldwide were affected by PM_(2.5)-O_(3)compound pollution,with China,South Korea,Japan,and India being the global hotspots for PM2.5-O3 compound pollution;(2)Cities with PM_(2.5)-O_(3)compound pollution have exposure risk levels dominated by ST t ST(Stabilization)and ST t HR(High Risk).Exposure risk levels of compound pollution in developing countries are significantly higher than those in developed countries,with unequal exposure characteristics;(3)The selected cities showed significant positive spatial correlations between PM_(2.5)and O_(3)concentrations,which were consistent with the spatial distribution of the precursors NOx and VOCs;(4)During the study period,52.5%of cities worldwide achieved synergistic reductions in annual average PM_(2.5)and O_(3)concentrations.The average PM_(2.5)concentration in these cities decreased by 13.97%,while the average O_(3)concentration decreased by 19.18%.This new solution offers the opportunity to construct intelligent and healthy cities in the upcoming low–carbon transition.
基金supported by the National Key Research and Development Program of China(Nos.2018YFC0213104 and 2017YFC0210002)the National Natural Science Foundation of China(Nos.41977184,41941011,and 51778596)+5 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA23020301)the Major Projects of High Resolution Earth Observation Systems of National Science and Technology(No.05-Y30B01-9001-19/20-3)the Youth Innovation Promotion Association of CAS(No.2021443),the Young Talent Project of the Center for Excellence in Regional Atmospheric Environment,CAS(CERAE202004)the China Postdoctoral Science Foundation(Nos.2020TQ0320 and 2021M693068)Anhui Provincial Natural Science Foundation(No.2108085QD178)the Fundamental Research Funds for the Central Universities.
文摘Recently,air pollution especially fine particulate matters(PM_(2.5))and ozone(O_(3))has become a severe issue in China.In this study,we first characterized the temporal trends of PM_(2.5) and O_(3) for Beijing,Guangzhou,Shanghai,andWuhan respectively during 2018-2020.The annual mean PM2.5 has decreased by 7.82%-33.92%,while O_(3) concentration showed insignificant variations by-6.77%-4.65%during 2018-2020.The generalized additive models(GAMs)were implemented to quantify the contribution of individual meteorological factors and their gas precursors on PM_(2.5) and O_(3).On a short-term perspective,GAMs modeling shows that the daily variability of PM_(2.5) concentration is largely related to the variation of precursor gases(R=0.67-0.90),while meteorological conditions mainly affect the daily variability of O_(3) concentration(R=0.65-0.80)during 2018-2020.The impact of COVID-19 lockdown on PM_(2.5) and O_(3) concentrations were also quantified by using GAMs.During the 2020 lockdown,PM_(2.5) decreased significantly for these megacities,yet the ozone concentration showed an increasing trend compared to 2019.The GAMs analysis indicated that the contribution of precursor gases to PM_(2.5) and O_(3) changes is 3-8 times higher than that of meteorological factors.In general,GAMsmodeling on air quality is helpful to the understanding and control of PM2.5 and O3 pollution in China.
