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Spatiotemporal Dynamics of Direct Carbon Emission and Policy Implication of Energy Transition for China’s Residential Consumption Sector by the Methods of Social Network Analysis and Geographically Weighted Regression
by
Jia, Junsong
, Ju, Min
, Chen, Chundi
, Sun, Yuling
in
carbon
/ Carbon dioxide
/ Carbon dioxide emissions
/ China
/ Clean energy
/ Climate change
/ Clusters
/ coal
/ Consumption patterns
/ Economic development
/ Economic growth
/ Economics
/ Electricity
/ Emissions
/ Energy conservation
/ Energy consumption
/ Energy policy
/ Energy transition
/ geographically weighted regression
/ Investigations
/ issues and policy
/ land
/ Measurement techniques
/ Network analysis
/ people
/ Renewable energy
/ renewable energy sources
/ residential CO2 emissions (RCEs)
/ Residential energy
/ Social network analysis
/ Social networks
/ Social organization
/ spatial association network
/ Urbanization
2022
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Spatiotemporal Dynamics of Direct Carbon Emission and Policy Implication of Energy Transition for China’s Residential Consumption Sector by the Methods of Social Network Analysis and Geographically Weighted Regression
by
Jia, Junsong
, Ju, Min
, Chen, Chundi
, Sun, Yuling
in
carbon
/ Carbon dioxide
/ Carbon dioxide emissions
/ China
/ Clean energy
/ Climate change
/ Clusters
/ coal
/ Consumption patterns
/ Economic development
/ Economic growth
/ Economics
/ Electricity
/ Emissions
/ Energy conservation
/ Energy consumption
/ Energy policy
/ Energy transition
/ geographically weighted regression
/ Investigations
/ issues and policy
/ land
/ Measurement techniques
/ Network analysis
/ people
/ Renewable energy
/ renewable energy sources
/ residential CO2 emissions (RCEs)
/ Residential energy
/ Social network analysis
/ Social networks
/ Social organization
/ spatial association network
/ Urbanization
2022
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Spatiotemporal Dynamics of Direct Carbon Emission and Policy Implication of Energy Transition for China’s Residential Consumption Sector by the Methods of Social Network Analysis and Geographically Weighted Regression
by
Jia, Junsong
, Ju, Min
, Chen, Chundi
, Sun, Yuling
in
carbon
/ Carbon dioxide
/ Carbon dioxide emissions
/ China
/ Clean energy
/ Climate change
/ Clusters
/ coal
/ Consumption patterns
/ Economic development
/ Economic growth
/ Economics
/ Electricity
/ Emissions
/ Energy conservation
/ Energy consumption
/ Energy policy
/ Energy transition
/ geographically weighted regression
/ Investigations
/ issues and policy
/ land
/ Measurement techniques
/ Network analysis
/ people
/ Renewable energy
/ renewable energy sources
/ residential CO2 emissions (RCEs)
/ Residential energy
/ Social network analysis
/ Social networks
/ Social organization
/ spatial association network
/ Urbanization
2022
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Spatiotemporal Dynamics of Direct Carbon Emission and Policy Implication of Energy Transition for China’s Residential Consumption Sector by the Methods of Social Network Analysis and Geographically Weighted Regression
Journal Article
Spatiotemporal Dynamics of Direct Carbon Emission and Policy Implication of Energy Transition for China’s Residential Consumption Sector by the Methods of Social Network Analysis and Geographically Weighted Regression
2022
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Overview
As China’s second largest energy-use sector, residential consumption has a great potential for carbon dioxide (CO2) reduction and energy saving or transition. Thus, here, using the methods of social network analysis (SNA) and geographically weighted regression (GWR), we investigated the spatiotemporal evolution characteristics of China’s residential CO2 emissions (RCEs) from direct energy use and proposed some policy suggestions for regional energy transition. (1) From 2000 to 2019, the total direct RCEs rose from 396.32 Mt to 1411.69 Mt; the consumption of electricity and coal were the primary sources. Controlling coal consumption and increasing the proportion of electricity generated from renewable energy should be the effective way of energy transition. (2) The spatial associations of direct RCEs show an obvious spatial network structure and the number of associations is increasing. Provinces with a higher level of economic development (Beijing, Shanghai, and Jiangsu) were at the center of the network and classified as the net beneficiary cluster in 2019. These provinces should be the priority areas of energy transition. (3) The net spillover cluster (Yunnan, Shanxi, Xinjiang, Gansu, Qinghai, Guizhou) is an important area to develop clean energy. People in this cluster should be encouraged to use more renewable energy. (4) GDP and per capita energy consumption had a significant positive influence on the growth of direct RCEs. Therefore, the national economy should grow healthily and sustainably to provide a favorable economic environment for energy transition. Meanwhile, residential consumption patterns should be greener to promote the use of clean energy.
Publisher
MDPI AG
Subject
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