Dataset Information

Drivers of change in China's energy-related CO₂ emissions.

ABSTRACT: CO₂ emissions are of global concern because of climate change. China has become the largest CO₂ emitter in the world and presently accounts for 30% of global emissions. Here, we analyze the major drivers of energy-related CO₂ emissions in China from 1978 when the reform and opening-up policy was launched. We find that 1) there has been a 6-fold increase in energy-related CO₂ emissions, which was driven primarily (176%) by economic growth followed by population growth (16%), while the effects of energy intensity (-79%) and carbon intensity (-13%) slowed the growth of carbon emissions over most of this period; 2) energy-related CO₂ emissions are positively related to per capita gross domestic product (GDP), population growth rate, carbon intensity, and energy intensity; and 3) a portfolio of command-and-control policies affecting the drivers has altered the total emission trend. However, given the major role of China in global climate change mitigation, significant future reductions in China's CO₂ emissions will require transformation toward low-carbon energy systems.

SUBMITTER: Zheng X

PROVIDER: S-EPMC6955364 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Drivers of change in China's energy-related CO2 emissions.

Zheng Xiaoqi X Lu Yonglong Y Yuan Jingjing J Baninla Yvette Y Zhang Sheng S Stenseth Nils Chr NC Hessen Dag O DO Tian Hanqin H Obersteiner Michael M Chen Deliang D

Proceedings of the National Academy of Sciences of the United States of America 20191223 1

CO2 emissions are of global concern because of climate change. China has become the largest CO2 emitter in the world and presently accounts for 30% of global emissions. Here, we analyze the major drivers of energy-related CO2 emissions in China from 1978 when the reform and opening-up policy was launched. We find that 1) there has been a 6-fold increase in energy-related CO2 emissions, which was driven primarily (176%) by economic growth followed by po ...[more]

PMID: 31871172

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Project description:Iran has increased its CO2 emissions significantly during the past few decades. The household sector in Iran contributes one of the largest sectors of CO2 emissions. Despite this significant contribution, the existing policies have predominantly concentrated on large-scale initiatives while overlooking the regional role in shaping and implementing these plans. Therefore, this study investigates the relationship between CO2 emissions and the efficient factors in three major groups including energy, climate, and household socio-economic factors. This study aims to address regional carbon emissions and develop CO2 reduction policies tailored to each region's specific circumstances. It focuses on planning strategies at the regional level to effectively tackle CO2 emissions. Household panel data of 28 provinces of Iran are employed by using both static and dynamic panel models for the years 2001 to 2019. Static estimation includes Fixed Effect (FE), Random Effect (RE) and pooled Partial least squares (PLS), Dynamic estimation includes difference Generalized Method of Moments (GMM) and system Generalized Method of Moments (GMM). The empirical result of the static method showed positive dependence of household CO2 emissions on Heating Degree Days (HDD), Cooling Degree Days (CDD), precipitation level, oil consumption, gas consumption, household income, size of household, and also building stocks. In more detail, educational rate, dummy variable (removal of energy subsidy), and oil price reveal the greatest negative impact on the emissions with elasticities of - 0.428, - 0.31, and - 0.15; It represents 1% increase causes - 0.428, - 0.31, - 0.15, decrease CO2 emissions, respectively. however, household size, gas consumption, and oil consumption show the most significant positive effects on CO2 emissions with 1 percent increase causes CO2 emissions increases by 0.1, 0.044, and 0.026, respectively. Regarding the impact of climate factors, a 1% increase in Heating Degree Days, Cooling Degree Days, and precipitation level causes CO2 emissions increase by 0.024%, 0.004%, and 0.011% respectively, due to an increase in fossil energy demand. Results of the dynamic method of the system Generalized Method of Moments are similar to the static estimation results, except for that household size and urbanization are not significant. Also, removing the energy subsidy for fossil fuels due to substantial subsidy in fossil fuels in Iran or implementing a re-pricing energy policy can be a beneficial way to control carbon emissions from households within the provinces of the country. However, it is important to consider that this shift could potentially transfer subsidies to investments in the private sector for renewable energies.

Dataset Information

Drivers of change in China's energy-related CO₂ emissions.

Publications

Drivers of change in China's energy-related CO<sub>2</sub> emissions.

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