This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China...This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China over the span of 2000-2019.This study also analyzes cross-sectional dependence tests,panel unit root tests,Westerlund panel cointegration tests,Dumitrescu-Hurlin(D-H)causality tests.According to the test results,there is an inverted U-shaped association between EG and SE,and the assumption of the Environmental Kuznets Curve(EKC)is verified.The signs of EG and EC in the fixed effect(FE)and random effect(RE)methods are in line with those in the dynamic ordinary least squares(DOLS),fully modified ordinary least squares(FMOLS)and autoregressive distributed lag(ARDL)estimators.Moreover,the results verified that EC can obviously positive impact the SE.To reduce SE in China,government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency.This requires the comprehensive use of policies,regulations,economic incentives,and public participation to promote sustainable development.展开更多
Coal-fired power plants are a major carbon source in China. In order to assess the evaluation of China's carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon ...Coal-fired power plants are a major carbon source in China. In order to assess the evaluation of China's carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon flux intensity from coal-fired power plants. Previous studies have calculated CO_(2) emissions from point sources based on Orbiting Carbon Observatory-2 and-3(OCO-2 and OCO-3) satellite measurements, but the factors affecting CO_(2) flux estimations are uncertain. In this study, we employ a Gaussian Plume Model to estimate CO_(2) emissions from three power plants in China based on OCO-3 XCO_(2) measurements. Moreover, flux uncertainties resulting from wind information, background values,satellite CO_(2) measurements, and atmospheric stability are discussed. This study highlights the CO_(2) flux uncertainty derived from the satellite measurements. Finally, satellite-based CO_(2) emission estimates are compared to bottom-up inventories.The satellite-based CO_(2) emission estimates at the Tuoketuo and Nongliushi power plants are ~30 and ~10 kt d^(-1) smaller than the Open-Data Inventory for Anthropogenic Carbon dioxide(ODIAC) respectively, but ~10 kt d^(-1) larger than the ODIAC at Baotou.展开更多
Investing in projects that support environmental benefits,such as tree harvesting,has the potential to reduce air pollution levels in the atmosphere in the future.However,this kind of investment may increase the curre...Investing in projects that support environmental benefits,such as tree harvesting,has the potential to reduce air pollution levels in the atmosphere in the future.However,this kind of investment may increase the current level of emissions.Therefore,it is necessary to estimate how much the policy affects the current level of CO_(2) emissions.This makes sure the policy doesn’t increase the level of CO_(2) emis-sions.This study aims to analyze the effect of the One Bil-lion Trees program on CO_(2) emissions in New Zealand by employing the 2020 input–output table analysis.This inves-tigation examines the direct and indirect effects of policy on both the demand and supply sides across six regions of New Zealand.The results of this study for the first year of plantation suggest that the policy increases the level of CO_(2) emissions in all regions,especially in the Waikato region.The direct and indirect impact of the policy leads to 64 kt of CO_(2) emissions on the demand side and 270 kt of CO_(2) emis-sions on the supply side.These lead to 0.19 and 0.74%of total CO_(2) emissions being attributed to investment shocks.Continuing the policy is recommended,as it has a low effect on CO_(2) emissions.However,it is crucial to prioritize the use of low-carbon machinery that uses fossil fuels during the plantation process.展开更多
This paper analyzes Chinese household CO_2 emissions in 1994-2012 based on the Logarithmic Mean Divisia Index(LMDI) structure decomposition model, and discusses the relationship between household CO_2 emissions and ec...This paper analyzes Chinese household CO_2 emissions in 1994-2012 based on the Logarithmic Mean Divisia Index(LMDI) structure decomposition model, and discusses the relationship between household CO_2 emissions and economic growth based on a decoupling indicator.The results show that in 1994-2012, household CO_2 emissions grew in general and displayed an accelerated growth trend during the early 21 st century. Economic growth leading to an increase in energy consumption is the main driving factor of CO_2 emission growth(an increase of 1.078 Gt CO_2) with cumulative contribution rate of 55.92%, while the decline in energy intensity is the main cause of CO_2 emission growth inhibition(0.723 Gt CO_2 emission reduction) with cumulative contribution rate of 38.27%. Meanwhile, household CO_2 emissions are in a weak state of decoupling in general. The change in CO_2 emissions caused by population and economic growth shows a weak decoupling and expansive decoupling state, respectively. The CO_2 emission change caused by energy intensity is in a state of strong decoupling, and the change caused by energy consumption structure ?uctuates between a weak and a strong decoupling state.展开更多
Co-integration theory has been employed in this paper and Granger causes are found between urbanization rate and GDP, between capital stock and GDP. Scenario analysis of GDP is performed using the GDP model establishe...Co-integration theory has been employed in this paper and Granger causes are found between urbanization rate and GDP, between capital stock and GDP. Scenario analysis of GDP is performed using the GDP model established in the paper. The energy consumptions in Germany, Japan and other developed countries are analyzed and compared with the energy consumption in China. Environmental friendly scenario of energy demand and CO2 emissions for sustainable China has been formed based on the results of comparison. Under environmental friendly scenario, the primary energy consumption will be 4.31 billion ton coal equivalence （tee） and CO2 emissions will be 1.854 billion t-c in 2050; energy per capital will be 3.06 tee that is 1.8 times of energy consumed in 2005 in China and 51% of consumed energy per capital in Japan in 2003. In 2050, the energy requirement of unit GDP will be 20% lower than that of Germany in 2003, but will be still 37% higher than that in Japan in 2003. It is certain that to fulfill the environmental friendly Scenario of energy demand and CO2 emissions is a difficult task and it needs long term efforts of the whole society, not only in production sectors but also in service and household sectors,展开更多
Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also ...Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO_(2)emissions.Therefore,using logarithmic mean Divisia index(LMDI)model to analysis the influence degree of different influencing factors on CO_(2)emissions from final energy consumption in Sichuan Province,so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors.Based on the data of final energy consumption in Sichuan Province from 2010 to 2019,we calculated CO_(2)emission by the indirect emission calculation method.The influencing factors of CO_(2)emissions originating from final energy consumption in Sichuan Province were decomposed into population size,economic development,industrial structure,energy consumption intensity,and energy consumption structure by the Kaya-logarithmic mean Divisia index(LMDI)decomposition model.At the same time,grey correlation analysis was used to identify the correlation between CO_(2)emissions originating from final energy consumption and the influencing factors in Sichuan Province.The results showed that population size,economic development and energy consumption structure have positive contributions to CO_(2)emissions from final energy consumption in Sichuan Province,and economic development has a significant contribution to CO_(2)emissions from final energy consumption,with a contribution rate of 519.11%.The industrial structure and energy consumption intensity have negative contributions to CO_(2)emissions in Sichuan Province,and both of them have significant contributions,among which the contribution rate of energy consumption structure was 325.96%.From the perspective of industrial structure,secondary industry makes significant contributions and will maintain a restraining effect;from the perspective of energy consumption structure,industry sector has a significant contribution.The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.展开更多
文摘This study aims to analysis the influence of economic growth(EG)and energy consumption(EC)on sulfur dioxide emissions(SE)in China.Accordingly,this study explores the link between EG,EC,and SE for 30 provinces in China over the span of 2000-2019.This study also analyzes cross-sectional dependence tests,panel unit root tests,Westerlund panel cointegration tests,Dumitrescu-Hurlin(D-H)causality tests.According to the test results,there is an inverted U-shaped association between EG and SE,and the assumption of the Environmental Kuznets Curve(EKC)is verified.The signs of EG and EC in the fixed effect(FE)and random effect(RE)methods are in line with those in the dynamic ordinary least squares(DOLS),fully modified ordinary least squares(FMOLS)and autoregressive distributed lag(ARDL)estimators.Moreover,the results verified that EC can obviously positive impact the SE.To reduce SE in China,government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency.This requires the comprehensive use of policies,regulations,economic incentives,and public participation to promote sustainable development.
基金supported by the Shanghai Sailing Program (Grant No. 22YF1442000)the Key Laboratory of Middle Atmosphere and Global Environment Observation(Grant No. LAGEO-2021-07)+1 种基金the National Natural Science Foundation of China (Grant No. 41975035)Jiaxing University (Grant Nos. 00323027AL and CD70522035)。
文摘Coal-fired power plants are a major carbon source in China. In order to assess the evaluation of China's carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon flux intensity from coal-fired power plants. Previous studies have calculated CO_(2) emissions from point sources based on Orbiting Carbon Observatory-2 and-3(OCO-2 and OCO-3) satellite measurements, but the factors affecting CO_(2) flux estimations are uncertain. In this study, we employ a Gaussian Plume Model to estimate CO_(2) emissions from three power plants in China based on OCO-3 XCO_(2) measurements. Moreover, flux uncertainties resulting from wind information, background values,satellite CO_(2) measurements, and atmospheric stability are discussed. This study highlights the CO_(2) flux uncertainty derived from the satellite measurements. Finally, satellite-based CO_(2) emission estimates are compared to bottom-up inventories.The satellite-based CO_(2) emission estimates at the Tuoketuo and Nongliushi power plants are ~30 and ~10 kt d^(-1) smaller than the Open-Data Inventory for Anthropogenic Carbon dioxide(ODIAC) respectively, but ~10 kt d^(-1) larger than the ODIAC at Baotou.
基金Open Access funding enabled and organized by CAUL and its Member Institutions
文摘Investing in projects that support environmental benefits,such as tree harvesting,has the potential to reduce air pollution levels in the atmosphere in the future.However,this kind of investment may increase the current level of emissions.Therefore,it is necessary to estimate how much the policy affects the current level of CO_(2) emissions.This makes sure the policy doesn’t increase the level of CO_(2) emis-sions.This study aims to analyze the effect of the One Bil-lion Trees program on CO_(2) emissions in New Zealand by employing the 2020 input–output table analysis.This inves-tigation examines the direct and indirect effects of policy on both the demand and supply sides across six regions of New Zealand.The results of this study for the first year of plantation suggest that the policy increases the level of CO_(2) emissions in all regions,especially in the Waikato region.The direct and indirect impact of the policy leads to 64 kt of CO_(2) emissions on the demand side and 270 kt of CO_(2) emis-sions on the supply side.These lead to 0.19 and 0.74%of total CO_(2) emissions being attributed to investment shocks.Continuing the policy is recommended,as it has a low effect on CO_(2) emissions.However,it is crucial to prioritize the use of low-carbon machinery that uses fossil fuels during the plantation process.
基金supported by the National Natural Science Foundation of China (NSFC) under Grant No. 71573015, 71303019, 71173206, and 71521002
文摘This paper analyzes Chinese household CO_2 emissions in 1994-2012 based on the Logarithmic Mean Divisia Index(LMDI) structure decomposition model, and discusses the relationship between household CO_2 emissions and economic growth based on a decoupling indicator.The results show that in 1994-2012, household CO_2 emissions grew in general and displayed an accelerated growth trend during the early 21 st century. Economic growth leading to an increase in energy consumption is the main driving factor of CO_2 emission growth(an increase of 1.078 Gt CO_2) with cumulative contribution rate of 55.92%, while the decline in energy intensity is the main cause of CO_2 emission growth inhibition(0.723 Gt CO_2 emission reduction) with cumulative contribution rate of 38.27%. Meanwhile, household CO_2 emissions are in a weak state of decoupling in general. The change in CO_2 emissions caused by population and economic growth shows a weak decoupling and expansive decoupling state, respectively. The CO_2 emission change caused by energy intensity is in a state of strong decoupling, and the change caused by energy consumption structure ?uctuates between a weak and a strong decoupling state.
文摘Co-integration theory has been employed in this paper and Granger causes are found between urbanization rate and GDP, between capital stock and GDP. Scenario analysis of GDP is performed using the GDP model established in the paper. The energy consumptions in Germany, Japan and other developed countries are analyzed and compared with the energy consumption in China. Environmental friendly scenario of energy demand and CO2 emissions for sustainable China has been formed based on the results of comparison. Under environmental friendly scenario, the primary energy consumption will be 4.31 billion ton coal equivalence （tee） and CO2 emissions will be 1.854 billion t-c in 2050; energy per capital will be 3.06 tee that is 1.8 times of energy consumed in 2005 in China and 51% of consumed energy per capital in Japan in 2003. In 2050, the energy requirement of unit GDP will be 20% lower than that of Germany in 2003, but will be still 37% higher than that in Japan in 2003. It is certain that to fulfill the environmental friendly Scenario of energy demand and CO2 emissions is a difficult task and it needs long term efforts of the whole society, not only in production sectors but also in service and household sectors,
基金financially supported by the National Natural Science Foundation of China(41771535)the National Social Science Foundation Major Project(20&ZD092)。
文摘Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO_(2)emissions.Therefore,using logarithmic mean Divisia index(LMDI)model to analysis the influence degree of different influencing factors on CO_(2)emissions from final energy consumption in Sichuan Province,so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors.Based on the data of final energy consumption in Sichuan Province from 2010 to 2019,we calculated CO_(2)emission by the indirect emission calculation method.The influencing factors of CO_(2)emissions originating from final energy consumption in Sichuan Province were decomposed into population size,economic development,industrial structure,energy consumption intensity,and energy consumption structure by the Kaya-logarithmic mean Divisia index(LMDI)decomposition model.At the same time,grey correlation analysis was used to identify the correlation between CO_(2)emissions originating from final energy consumption and the influencing factors in Sichuan Province.The results showed that population size,economic development and energy consumption structure have positive contributions to CO_(2)emissions from final energy consumption in Sichuan Province,and economic development has a significant contribution to CO_(2)emissions from final energy consumption,with a contribution rate of 519.11%.The industrial structure and energy consumption intensity have negative contributions to CO_(2)emissions in Sichuan Province,and both of them have significant contributions,among which the contribution rate of energy consumption structure was 325.96%.From the perspective of industrial structure,secondary industry makes significant contributions and will maintain a restraining effect;from the perspective of energy consumption structure,industry sector has a significant contribution.The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.
