Population growth and development patterns have a significant impact on the environmental performance.The issue of concern is whether population growth or the consumption/production patterns are responsible for enviro...Population growth and development patterns have a significant impact on the environmental performance.The issue of concern is whether population growth or the consumption/production patterns are responsible for environmental deterioration.This paper is an attempt to capture the impact of technological development,affluence,and population on environmental performance index,while previous stuthes had captured the impact of these three factors on environment only through CO_2emissions.The analysis reveals that technological development and population size have a negative impact on environmental performance,whereas measures to improve affluence have a positive impact.Technological development has increased the production of energy efficient products but at the same time consumption of these products has increased manifold leading to environmental deterioration.Demographic attributes need specific attention to improve environmental performance.This paper concludes on some policy reflections on slowing the population growth as well as persuades individuals and economies to relook to their consumption and production patterns and channelize their efforts to protect the environment.展开更多
我国能源活动碳排放占总碳排放85%以上,研究能源活动碳排放的变化规律对于实现碳达峰碳中和目标具有重要意义.首先,采用对数平均迪氏分解法(logarithmic mean Divisia index,LMDI)对1995—2017年我国能源消费碳排放变化的影响因素进行分...我国能源活动碳排放占总碳排放85%以上,研究能源活动碳排放的变化规律对于实现碳达峰碳中和目标具有重要意义.首先,采用对数平均迪氏分解法(logarithmic mean Divisia index,LMDI)对1995—2017年我国能源消费碳排放变化的影响因素进行分解,从经济规模、产业结构、能源强度、能源结构、能源价格、人均可支配收入、人口规模这7个方面,模型给出了相关因素对一、二、三产业和居民部门碳排放变化的贡献.结果表明,对于3个产业部门,经济增长是碳排放增长的首要驱动力,而技术进步带来的能源强度下降、产业结构优化和能源消费结构改善呈现负效应,且产业结构优化和能源结构清洁化的作用越来越显著.对于居民部门,人均可支配收入是居民部门碳排放增长的推动力,而能源价格呈现明显的负效应.其次,设计了3种情景,运用可拓展的随机性的环境影响评估模型(stochastic impacts by regression population,affluence and technology,STIRPAT)对2030年我国能源碳排放进行预测,在以实现碳达峰为目标的低碳情景中,我国能源碳排放有望于2025—2029年实现达峰,峰值水平为101亿~110亿t.最后,为实现碳达峰碳中和目标,建议以构建中国能源互联网为基础平台,实施"清洁替代"和"电能替代",推进能源转型.展开更多
“十四五”时期是中国实现碳达峰的关键时期,也是推动经济高质量发展和生态环境质量持续改善的重要阶段。可拓展的随机性环境影响评估(Stochastic Impacts by Regression on Population,Affluence,and Technology,STIRPAT)模型可以根据...“十四五”时期是中国实现碳达峰的关键时期,也是推动经济高质量发展和生态环境质量持续改善的重要阶段。可拓展的随机性环境影响评估(Stochastic Impacts by Regression on Population,Affluence,and Technology,STIRPAT)模型可以根据研究需要增加自变量,更好地分析相关因素对因变量的影响。以北京市为研究区,通过构建扩展的STIRPAT模型,分析人均地区生产总值(Gross Domestic Product,GDP)、人均汽车保有量、城市化率、第三产业GDP占比、能源消费强度与人均碳排放量的关系,并采用对数平均迪氏指数(Logarithmic Mean Divisia Index,LMDI)分解法分解能源消费强度。结果表明,产业结构和能源消费强度对人均碳排放量均有显著的正向影响。总体来看,要平衡经济发展与碳排放的关系,提高能源利用效率,推广可再生能源,降低能源消耗,减少碳排放。展开更多
In recent years,researchers have devoted considerable attention to identifying the causes of urban environmental pollution.To determine whether migrant populations significantly affect urban environments,we examined t...In recent years,researchers have devoted considerable attention to identifying the causes of urban environmental pollution.To determine whether migrant populations significantly affect urban environments,we examined the relationship between urban environmental pollutant emissions and migrant populations at the prefectural level using data obtained for 90 Chinese cities evidencing net in-migration.By dividing the permanent populations of these cities into natives and migrants in relation to the population structure,we constructed an improved Stochastic Impacts by Regression on Population,Affluence and Technology model(STIRPAT)that included not only environmental pollutant emission variables but also variables on the cities’attributes.We subsequently conducted detailed analyses of the results of the models to assess the impacts of natives and migrants on environmental pollutant emissions.The main findings of our study were as follows:1)Migrant populations have significant impacts on environmental emissions both in terms of their size and concentration.Specifically,migrant populations have negative impacts on Air Quality Index(AQI)as well as PM2.5 emissions and positive impacts on emissions of NO2 and CO2.2)The impacts of migrant populations on urban environmental pollutant emissions were 8 to 30 times weaker than that of local populations.3)Urban environmental pollutant emissions in different cities differ significantly according to variations in the industrial structures,public transportation facilities,and population densities.展开更多
Environmental infrastructure investment(EII)is an important environmental policy instrument on responding to greenhouse gas(GHG)emission and air pollution.This paper employs an improved stochastic impact by regression...Environmental infrastructure investment(EII)is an important environmental policy instrument on responding to greenhouse gas(GHG)emission and air pollution.This paper employs an improved stochastic impact by regression on population,affluence and technology(STRIPAT)model by using panel data from 30 Chinese provinces and municipalities for the period of 2003–2015 to investigate the effect of EII on CO2 emissions,SO2 emissions,and PM2.5 pollution.The results indicate that EII has a positive and significant effect on mitigating CO2 emission.However,the effect of EII on SO2 emission fluctuated although it still contributes to the reduction of PM2.5 pollution through technology innovations.Energy intensity has the largest impact on GHG emissions and air pollution,followed by GDP per capita and industrial structure.In addition,the effect of EII on environmental issues varies in different regions.Such findings suggest that policies on EII should be region-specific so that more appropriate mitigation policies can be raised by considering the local realities.展开更多
文摘Population growth and development patterns have a significant impact on the environmental performance.The issue of concern is whether population growth or the consumption/production patterns are responsible for environmental deterioration.This paper is an attempt to capture the impact of technological development,affluence,and population on environmental performance index,while previous stuthes had captured the impact of these three factors on environment only through CO_2emissions.The analysis reveals that technological development and population size have a negative impact on environmental performance,whereas measures to improve affluence have a positive impact.Technological development has increased the production of energy efficient products but at the same time consumption of these products has increased manifold leading to environmental deterioration.Demographic attributes need specific attention to improve environmental performance.This paper concludes on some policy reflections on slowing the population growth as well as persuades individuals and economies to relook to their consumption and production patterns and channelize their efforts to protect the environment.
文摘我国能源活动碳排放占总碳排放85%以上,研究能源活动碳排放的变化规律对于实现碳达峰碳中和目标具有重要意义.首先,采用对数平均迪氏分解法(logarithmic mean Divisia index,LMDI)对1995—2017年我国能源消费碳排放变化的影响因素进行分解,从经济规模、产业结构、能源强度、能源结构、能源价格、人均可支配收入、人口规模这7个方面,模型给出了相关因素对一、二、三产业和居民部门碳排放变化的贡献.结果表明,对于3个产业部门,经济增长是碳排放增长的首要驱动力,而技术进步带来的能源强度下降、产业结构优化和能源消费结构改善呈现负效应,且产业结构优化和能源结构清洁化的作用越来越显著.对于居民部门,人均可支配收入是居民部门碳排放增长的推动力,而能源价格呈现明显的负效应.其次,设计了3种情景,运用可拓展的随机性的环境影响评估模型(stochastic impacts by regression population,affluence and technology,STIRPAT)对2030年我国能源碳排放进行预测,在以实现碳达峰为目标的低碳情景中,我国能源碳排放有望于2025—2029年实现达峰,峰值水平为101亿~110亿t.最后,为实现碳达峰碳中和目标,建议以构建中国能源互联网为基础平台,实施"清洁替代"和"电能替代",推进能源转型.
文摘“十四五”时期是中国实现碳达峰的关键时期,也是推动经济高质量发展和生态环境质量持续改善的重要阶段。可拓展的随机性环境影响评估(Stochastic Impacts by Regression on Population,Affluence,and Technology,STIRPAT)模型可以根据研究需要增加自变量,更好地分析相关因素对因变量的影响。以北京市为研究区,通过构建扩展的STIRPAT模型,分析人均地区生产总值(Gross Domestic Product,GDP)、人均汽车保有量、城市化率、第三产业GDP占比、能源消费强度与人均碳排放量的关系,并采用对数平均迪氏指数(Logarithmic Mean Divisia Index,LMDI)分解法分解能源消费强度。结果表明,产业结构和能源消费强度对人均碳排放量均有显著的正向影响。总体来看,要平衡经济发展与碳排放的关系,提高能源利用效率,推广可再生能源,降低能源消耗,减少碳排放。
基金Under the auspices of Shanxi Scholarship Council of China(No.2017-003)
文摘In recent years,researchers have devoted considerable attention to identifying the causes of urban environmental pollution.To determine whether migrant populations significantly affect urban environments,we examined the relationship between urban environmental pollutant emissions and migrant populations at the prefectural level using data obtained for 90 Chinese cities evidencing net in-migration.By dividing the permanent populations of these cities into natives and migrants in relation to the population structure,we constructed an improved Stochastic Impacts by Regression on Population,Affluence and Technology model(STIRPAT)that included not only environmental pollutant emission variables but also variables on the cities’attributes.We subsequently conducted detailed analyses of the results of the models to assess the impacts of natives and migrants on environmental pollutant emissions.The main findings of our study were as follows:1)Migrant populations have significant impacts on environmental emissions both in terms of their size and concentration.Specifically,migrant populations have negative impacts on Air Quality Index(AQI)as well as PM2.5 emissions and positive impacts on emissions of NO2 and CO2.2)The impacts of migrant populations on urban environmental pollutant emissions were 8 to 30 times weaker than that of local populations.3)Urban environmental pollutant emissions in different cities differ significantly according to variations in the industrial structures,public transportation facilities,and population densities.
基金supported by the National Natural Science Foundation of China(Grant Nos.71810107001,71690241)the Natural Science Foundation of Shandong Province(ZR2017MG019)+3 种基金the Postdoctoral fund(No.18Z102060077)China Youth Foundation Project of Humanities and Social Sciences of the Ministry of Education(No.18YJC630148)Shandong Social Science Planning Project(No.15CGLG19)a Special Fund for Big Data of Shanghai Jiao Tong University(SJTU-2019UGBD-03).
文摘Environmental infrastructure investment(EII)is an important environmental policy instrument on responding to greenhouse gas(GHG)emission and air pollution.This paper employs an improved stochastic impact by regression on population,affluence and technology(STRIPAT)model by using panel data from 30 Chinese provinces and municipalities for the period of 2003–2015 to investigate the effect of EII on CO2 emissions,SO2 emissions,and PM2.5 pollution.The results indicate that EII has a positive and significant effect on mitigating CO2 emission.However,the effect of EII on SO2 emission fluctuated although it still contributes to the reduction of PM2.5 pollution through technology innovations.Energy intensity has the largest impact on GHG emissions and air pollution,followed by GDP per capita and industrial structure.In addition,the effect of EII on environmental issues varies in different regions.Such findings suggest that policies on EII should be region-specific so that more appropriate mitigation policies can be raised by considering the local realities.
