In the construction of resilient cities,regional air pollution prevention plays a pivotal role.Building on the previous research experience,the relationship between air pollution concentration and urban size exhibits ...In the construction of resilient cities,regional air pollution prevention plays a pivotal role.Building on the previous research experience,the relationship between air pollution concentration and urban size exhibits a sublinear allometric growth pattern.To identify effective strategies for mitigating particulate matter air pollution,this study quantitatively explored 6 variables influencing urbanization in China’s cities and established an allometry model.Empirical analysis was conducted using data from 293 prefecturelevel cities and 1,827 county-level cities to examine the relationship between annual concentrations of fine particulate matter PM_(2.5) and PM_(10) in the atmosphere.①The findings of this study provided partial validation for the Kuznets curve and demonstrated a reverse‘U’-shaped association between urbanization and levels of PM_(2.5) and PM_(10) pollution.②By partitioning the Hu Huanyong line,this study identified the spatial distribution pattern of PM_(2.5) and PM_(10).In central and western regions,as urban size expands,inhalable particle concentrations tended to increase further;whereas in the southeast region,inhalable particle concentrations gradually decreased and stabilized after a certain threshold of urban scale expansion was reached.Among the factors influencing urban size,green coverage within built-up areas exerted the most significant impact on both PM_(2.5) and PM_(10) concentrations,followed by the extent of built-up areas and the scale of secondary industries.This study presented an effective strategy for reconciling conflicts between urban expansion and air pollution management,while concurrently promoting resilient cities characterized by high levels of modernization and superior quality.展开更多
This study constructs a quasi-natural experiment based on the expansion of the Yangtze River Delta urban agglomeration(YRDUA) of China in 2010 to investigate the impact and inner mechanism of urban agglomeration expan...This study constructs a quasi-natural experiment based on the expansion of the Yangtze River Delta urban agglomeration(YRDUA) of China in 2010 to investigate the impact and inner mechanism of urban agglomeration expansion on fine particulate matter(PM_(2.5)) concentrations through propensity scores in difference-in-differences models(PSM-DID) using panel data from 286 prefecturelevel cities in China from 2003 to 2016. The results show that 1) urban agglomeration expansion contributes to an overall decrease in PM_(2.5)concentration, which is mainly achieved from the original cities. For the new cities, on the other hand, the expansion significantly increases the local PM_(2.5)concentration. 2) In the long term, the significant influence of urban agglomeration expansion on PM_(2.5)concentration lasts for three years and gradually decreases. A series of robustness tests confirm the applicability of the PSM-DID model.3) Cities with weaker government regulation, a better educated population and higher per capita income present stronger PM_(2.5)reduction effects. 4) Urban agglomeration expansion affects the PM_(2.5)concentration mainly through industrial transfer and population migration, which cause a decrease in the PM_(2.5)concentration in the original cities and an increase in the PM_(2.5)concentration in the new cities.Corresponding policy suggestions are proposed based on the conclusions.展开更多
Objective To estimate the frequency of daily average PM10 concentrations exceeding the air quality standard （AQS） and the reduction of particulate matter emission to meet the AQS from the statistical properties （pr...Objective To estimate the frequency of daily average PM10 concentrations exceeding the air quality standard （AQS） and the reduction of particulate matter emission to meet the AQS from the statistical properties （probability density functions） of air pollutant concentration. Methods The daily PM10 average concentration in Beijing, Shanghai, Guangzhou, Wuhan, and Xi＇an was measured from 1 January 2004 to 31 December 2008. The PM10 concentration distribution was simulated by using the Iognormal, Weibull and Gamma distributions and the best statistical distribution of PM10 concentration in the 5 cities was detected using to the maximum likelihood method. Results The daily PM10 average concentration in the 5 cities was fitted using the Iognormal distribution. The exceeding duration was predicted, and the estimated PMlo emission source reductions in the 5 cities need to be 56.58%, 93.40%, 80.17%, 82.40%, and 79.80%, respectively to meet the AO, S. Conclusion Air pollutant concentration can be predicted by using the PM10 concentration distribution, which can be further applied in air quality management and related policy making.展开更多
文摘In the construction of resilient cities,regional air pollution prevention plays a pivotal role.Building on the previous research experience,the relationship between air pollution concentration and urban size exhibits a sublinear allometric growth pattern.To identify effective strategies for mitigating particulate matter air pollution,this study quantitatively explored 6 variables influencing urbanization in China’s cities and established an allometry model.Empirical analysis was conducted using data from 293 prefecturelevel cities and 1,827 county-level cities to examine the relationship between annual concentrations of fine particulate matter PM_(2.5) and PM_(10) in the atmosphere.①The findings of this study provided partial validation for the Kuznets curve and demonstrated a reverse‘U’-shaped association between urbanization and levels of PM_(2.5) and PM_(10) pollution.②By partitioning the Hu Huanyong line,this study identified the spatial distribution pattern of PM_(2.5) and PM_(10).In central and western regions,as urban size expands,inhalable particle concentrations tended to increase further;whereas in the southeast region,inhalable particle concentrations gradually decreased and stabilized after a certain threshold of urban scale expansion was reached.Among the factors influencing urban size,green coverage within built-up areas exerted the most significant impact on both PM_(2.5) and PM_(10) concentrations,followed by the extent of built-up areas and the scale of secondary industries.This study presented an effective strategy for reconciling conflicts between urban expansion and air pollution management,while concurrently promoting resilient cities characterized by high levels of modernization and superior quality.
基金Under the auspices of Chinese National Funding of Social Sciences (No.17AGL005)Institute of Socialism with Chinese Characteristics of Southeast University (No.DDZTZK2021C11)。
文摘This study constructs a quasi-natural experiment based on the expansion of the Yangtze River Delta urban agglomeration(YRDUA) of China in 2010 to investigate the impact and inner mechanism of urban agglomeration expansion on fine particulate matter(PM_(2.5)) concentrations through propensity scores in difference-in-differences models(PSM-DID) using panel data from 286 prefecturelevel cities in China from 2003 to 2016. The results show that 1) urban agglomeration expansion contributes to an overall decrease in PM_(2.5)concentration, which is mainly achieved from the original cities. For the new cities, on the other hand, the expansion significantly increases the local PM_(2.5)concentration. 2) In the long term, the significant influence of urban agglomeration expansion on PM_(2.5)concentration lasts for three years and gradually decreases. A series of robustness tests confirm the applicability of the PSM-DID model.3) Cities with weaker government regulation, a better educated population and higher per capita income present stronger PM_(2.5)reduction effects. 4) Urban agglomeration expansion affects the PM_(2.5)concentration mainly through industrial transfer and population migration, which cause a decrease in the PM_(2.5)concentration in the original cities and an increase in the PM_(2.5)concentration in the new cities.Corresponding policy suggestions are proposed based on the conclusions.
基金supported by the National Basic Research Program (973 program) of China (2011CB503802)Gong-Yi Program of China Ministry of Environmental Protection (201209008)the Program for New Century Excellent Talents in University (NCET-09-0314)
文摘Objective To estimate the frequency of daily average PM10 concentrations exceeding the air quality standard （AQS） and the reduction of particulate matter emission to meet the AQS from the statistical properties （probability density functions） of air pollutant concentration. Methods The daily PM10 average concentration in Beijing, Shanghai, Guangzhou, Wuhan, and Xi＇an was measured from 1 January 2004 to 31 December 2008. The PM10 concentration distribution was simulated by using the Iognormal, Weibull and Gamma distributions and the best statistical distribution of PM10 concentration in the 5 cities was detected using to the maximum likelihood method. Results The daily PM10 average concentration in the 5 cities was fitted using the Iognormal distribution. The exceeding duration was predicted, and the estimated PMlo emission source reductions in the 5 cities need to be 56.58%, 93.40%, 80.17%, 82.40%, and 79.80%, respectively to meet the AO, S. Conclusion Air pollutant concentration can be predicted by using the PM10 concentration distribution, which can be further applied in air quality management and related policy making.
