Can expanding natural gas consumption reduce China's CO2 emissions?
China is now the world's largest emitter of carbon dioxide (CO2), thus leading to China facing enormous pressure on CO2 emission reduction. Natural gas is a high thermal and low-emission energy. Expanding natural gas consumption cannot only meet the growing demand for energy consumption but als...
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Published in | Energy economics Vol. 81; pp. 393 - 407 |
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Main Authors | , |
Format | Journal Article |
Language | English |
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Elsevier Science Ltd
01.06.2019
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Abstract | China is now the world's largest emitter of carbon dioxide (CO2), thus leading to China facing enormous pressure on CO2 emission reduction. Natural gas is a high thermal and low-emission energy. Expanding natural gas consumption cannot only meet the growing demand for energy consumption but also optimize energy consumption structure. Therefore, many scholars have investigated the effect of natural gas consumption on CO2 emissions. However, ignoring a large number of nonlinear relationships between economic variables, the vast majority of existing studies use traditional linear models to explore the relationships between natural gas consumption and CO2 emissions. In order to make up for the gap in existing research, this paper uses the nonparametric additive regression model with data-driven features to investigate the relationships between the two. The results show that natural gas consumption has an inverted "U-shaped" nonlinear effect on CO2 emissions in the eastern region, but a positive "U-shaped" nonlinear effect in the central and western regions. The linear impact of natural gas consumption on CO2 emissions in the eastern and central regions is higher than that in the western region, due to the differences in resource availability and energy prices, as well as natural gas consumption. Therefore, during the process of promoting natural gas consumption, the central and local governments should adopt heterogeneous measures at different stages of development. |
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AbstractList | China is now the world's largest emitter of carbon dioxide (CO2), thus leading to China facing enormous pressure on CO2 emission reduction. Natural gas is a high thermal and low-emission energy. Expanding natural gas consumption cannot only meet the growing demand for energy consumption but also optimize energy consumption structure. Therefore, many scholars have investigated the effect of natural gas consumption on CO2 emissions. However, ignoring a large number of nonlinear relationships between economic variables, the vast majority of existing studies use traditional linear models to explore the relationships between natural gas consumption and CO2 emissions. In order to make up for the gap in existing research, this paper uses the nonparametric additive regression model with data-driven features to investigate the relationships between the two. The results show that natural gas consumption has an inverted "U-shaped" nonlinear effect on CO2 emissions in the eastern region, but a positive "U-shaped" nonlinear effect in the central and western regions. The linear impact of natural gas consumption on CO2 emissions in the eastern and central regions is higher than that in the western region, due to the differences in resource availability and energy prices, as well as natural gas consumption. Therefore, during the process of promoting natural gas consumption, the central and local governments should adopt heterogeneous measures at different stages of development. |
Author | Xu, Bin Lin, Boqiang |
Author_xml | – sequence: 1 givenname: Bin surname: Xu fullname: Xu, Bin – sequence: 2 givenname: Boqiang surname: Lin fullname: Lin, Boqiang |
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Cites_doi | 10.1016/j.enpol.2017.03.027 10.1016/j.eneco.2017.11.015 10.1109/TSTE.2016.2615104 10.1016/S0304-4076(98)00009-8 10.1016/j.enpol.2014.05.035 10.3390/su9040600 10.1016/j.eneco.2015.01.005 10.1016/j.eneco.2018.12.005 10.1016/j.apenergy.2017.02.037 10.1016/j.enpol.2018.05.049 10.1016/j.enpol.2017.03.017 10.1016/j.jclepro.2017.08.052 10.1016/j.energy.2013.12.006 10.1016/j.enpol.2016.12.012 10.1016/j.apenergy.2016.07.077 10.1016/j.ecosta.2017.05.005 10.1016/j.energy.2017.02.042 10.1016/j.renene.2010.08.016 10.1016/j.jclepro.2017.12.022 10.1111/ecoj.12285 10.1016/j.jclepro.2017.03.142 10.1016/j.energy.2017.11.114 10.1016/j.eneco.2019.01.004 10.1016/j.jclepro.2017.08.107 10.1016/j.eneco.2017.02.001 10.1007/s10021-018-0264-y 10.1016/j.worlddev.2010.05.011 10.1016/j.eneco.2017.11.004 10.1016/j.rser.2017.05.006 10.1016/j.jclepro.2017.09.013 10.1016/j.eneco.2009.09.013 10.1016/j.serj.2016.10.001 10.1016/0304-4076(88)90045-0 10.1093/biomet/84.2.469 10.1016/j.apenergy.2016.10.127 10.2307/1913236 10.1016/j.compchemeng.2017.01.032 10.1016/j.eneco.2017.11.022 10.1016/j.energy.2019.02.114 10.1016/j.enpol.2017.09.033 10.1016/S0304-4076(01)00098-7 10.1016/j.jclepro.2016.04.095 10.1016/j.regsciurbeco.2017.04.001 10.1007/s12053-016-9488-x 10.1016/j.enpol.2017.06.041 10.1016/j.energy.2017.09.037 |
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References | Qin (10.1016/j.eneco.2019.04.012_bb0175) 2017; 185 Cesur (10.1016/j.eneco.2019.04.012_bb0055) 2017; 127 Linton (10.1016/j.eneco.2019.04.012_bb0155) 1997; 84 Tian (10.1016/j.eneco.2019.04.012_bb0200) 2017; 111 Li (10.1016/j.eneco.2019.04.012_bb0130) 2017; 9 He (10.1016/j.eneco.2019.04.012_bb0110) 2017; 8 Granger (10.1016/j.eneco.2019.04.012_bb0105) 1988; 139 Basso (10.1016/j.eneco.2019.04.012_bb0025) 2017; 123 Liddle (10.1016/j.eneco.2019.04.012_bb0140) 2018; 69 Engle (10.1016/j.eneco.2019.04.012_bb0070) 1987 Filloy (10.1016/j.eneco.2019.04.012_bb0085) 2019; 22 Liu (10.1016/j.eneco.2019.04.012_bb0160) 2017; 105 Xie (10.1016/j.eneco.2019.04.012_bb0215) 2014; 73 Xu (10.1016/j.eneco.2019.04.012_bb0235) 2017; 152 Lin (10.1016/j.eneco.2019.04.012_bb0150) 2017; 166 Li (10.1016/j.eneco.2019.04.012_bb0135) 2011; 39 Geniaux (10.1016/j.eneco.2019.04.012_bb0095) 2018; 72 Blundell (10.1016/j.eneco.2019.04.012_bb0040) 1998; 87 Xu (10.1016/j.eneco.2019.04.012_bb0225) 2018; 175 Agnolucci (10.1016/j.eneco.2019.04.012_bb0010) 2019; 78 Li (10.1016/j.eneco.2019.04.012_bb0125) 2017; 194 Wang (10.1016/j.eneco.2019.04.012_bb0210) 2017; 142 Kounetas (10.1016/j.eneco.2019.04.012_bb0115) 2018; 69 Fang (10.1016/j.eneco.2019.04.012_bb0075) 2018; 120 Yuan (10.1016/j.eneco.2019.04.012_bb0245) 2018; 69 Zheng (10.1016/j.eneco.2019.04.012_bb0250) 2019; 80 Meng (10.1016/j.eneco.2019.04.012_bb0165) 2017; 63 Su (10.1016/j.eneco.2019.04.012_bb0190) 2017; 105 Buja (10.1016/j.eneco.2019.04.012_bb0045) 1989; 17 Yeh (10.1016/j.eneco.2019.04.012_bb0240) 2017; 27 Wang (10.1016/j.eneco.2019.04.012_bb0205) 2017; 108 Sun (10.1016/j.eneco.2019.04.012_bb0195) 2019; 9 10.1016/j.eneco.2019.04.012_bb0015 Costantini (10.1016/j.eneco.2019.04.012_bb0065) 2010; 32 Shaikh (10.1016/j.eneco.2019.04.012_bb8000) 2017; 140 Bildirici (10.1016/j.eneco.2019.04.012_bb0035) 2014; 65 Cagno (10.1016/j.eneco.2019.04.012_bb0050) 2017; 10 Cong (10.1016/j.eneco.2019.04.012_bb0060) 2017; 193 Xu (10.1016/j.eneco.2019.04.012_bb0220) 2015; 48 Bélaïd (10.1016/j.eneco.2019.04.012_bb0030) 2017; 102 Granger (10.1016/j.eneco.2019.04.012_bb0100) 1993 Levin (10.1016/j.eneco.2019.04.012_bb0120) 2002; 108 Stone (10.1016/j.eneco.2019.04.012_bb0185) 1985; 113 Baltagi (10.1016/j.eneco.2019.04.012_bb0020) 2008 Gao (10.1016/j.eneco.2019.04.012_bb0090) 2017; 106 Miller (10.1016/j.eneco.2019.04.012_bb0170) 2011; 36 Feng (10.1016/j.eneco.2019.04.012_bb0080) 2017; 141 Xu (10.1016/j.eneco.2019.04.012_bb0230) 2017; 166 Lin (10.1016/j.eneco.2019.04.012_bb0145) 2017; 168 Abdallah (10.1016/j.eneco.2019.04.012_bb0005) 2017; 78 |
References_xml | – volume: 105 start-page: 484 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0190 article-title: Input-output and structural decomposition analysis of Singapore's carbon emissions publication-title: Energy Policy doi: 10.1016/j.enpol.2017.03.027 – volume: 69 start-page: 111 year: 2018 ident: 10.1016/j.eneco.2019.04.012_bb0115 article-title: Energy consumption and CO2 emissions convergence in European Union member countries. A tonneau des Danaides? publication-title: Energy Econ. doi: 10.1016/j.eneco.2017.11.015 – volume: 8 start-page: 658 issue: 2 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0110 article-title: Robust co-optimization scheduling of electricity and natural gas systems via ADMM publication-title: IEEE Transactions on Sustainable Energy doi: 10.1109/TSTE.2016.2615104 – volume: 87 start-page: 115 issue: 1 year: 1998 ident: 10.1016/j.eneco.2019.04.012_bb0040 article-title: Initial conditions and moment restrictions in dynamic panel data models publication-title: J. Econ. doi: 10.1016/S0304-4076(98)00009-8 – volume: 73 start-page: 401 year: 2014 ident: 10.1016/j.eneco.2019.04.012_bb0215 article-title: The driving forces of China' s energy use from 1992 to 2010: an empirical study of input-output and structural decomposition analysis publication-title: Energy Policy doi: 10.1016/j.enpol.2014.05.035 – volume: 9 start-page: 600 issue: 4 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0130 article-title: The role of natural gas and renewable energy in curbing carbon emission: case study of the United States publication-title: Sustainability doi: 10.3390/su9040600 – volume: 48 start-page: 188 year: 2015 ident: 10.1016/j.eneco.2019.04.012_bb0220 article-title: How industrialization and urbanization process impacts on CO2 emissions in China: evidence from nonparametric additive regression models publication-title: Energy Econ. doi: 10.1016/j.eneco.2015.01.005 – volume: 78 start-page: 546 year: 2019 ident: 10.1016/j.eneco.2019.04.012_bb0010 article-title: Industrial characteristics and air emissions: long-term determinants in the UK manufacturing sector publication-title: Energy Econ. doi: 10.1016/j.eneco.2018.12.005 – volume: 193 start-page: 414 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0060 article-title: Emission trading and carbon market performance in Shenzhen, China publication-title: Appl. Energy doi: 10.1016/j.apenergy.2017.02.037 – volume: 120 start-page: 250 year: 2018 ident: 10.1016/j.eneco.2019.04.012_bb0075 article-title: Estimating peak uranium production in China–based on a Stella model publication-title: Energy Policy doi: 10.1016/j.enpol.2018.05.049 – volume: 105 start-page: 398 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0160 article-title: Influencing factors of public support for modern coal-fired power plant projects: an empirical study from China publication-title: Energy Policy doi: 10.1016/j.enpol.2017.03.017 – volume: 166 start-page: 628 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0230 article-title: Geographical analysis of CO2 emissions in China's manufacturing industry: a geographically weighted regression model publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2017.08.052 – volume: 65 start-page: 134 year: 2014 ident: 10.1016/j.eneco.2019.04.012_bb0035 article-title: The relationship among oil, natural gas, and coal consumption and economic growth in BRICTS (Brazil, Russian, India, China, Turkey and South Africa) countries publication-title: Energy doi: 10.1016/j.energy.2013.12.006 – volume: 102 start-page: 277 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0030 article-title: Environmental degradation, renewable and non-renewable electricity consumption, and economic growth: assessing the evidence from Algeria publication-title: Energy Policy doi: 10.1016/j.enpol.2016.12.012 – volume: 194 start-page: 696 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0125 article-title: Security-constrained bi-level economic dispatch model for integrated natural gas and electricity systems considering wind power and power-to-gas process publication-title: Appl. Energy doi: 10.1016/j.apenergy.2016.07.077 – volume: 9 start-page: 140 year: 2019 ident: 10.1016/j.eneco.2019.04.012_bb0195 article-title: Estimation of a semiparametric varying-coefficient mixed regressive spatial autoregressive model publication-title: Econometrics and statistics doi: 10.1016/j.ecosta.2017.05.005 – volume: 123 start-page: 615 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0025 article-title: How to handle the hydrogen enriched natural gas blends in combustion efficiency measurement procedure of conventional and condensing boilers publication-title: Energy doi: 10.1016/j.energy.2017.02.042 – volume: 36 start-page: 1040 issue: 3 year: 2011 ident: 10.1016/j.eneco.2019.04.012_bb0170 article-title: A benchmark for life cycle air emissions and life cycle impact assessment of hydrokinetic energy extraction using life cycle assessment publication-title: Renew. Energy doi: 10.1016/j.renene.2010.08.016 – volume: 175 start-page: 109 year: 2018 ident: 10.1016/j.eneco.2019.04.012_bb0225 article-title: Investigating the differences in CO2 emissions in the transport sector across Chinese provinces: evidence from a quantile regression model publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2017.12.022 – volume: 127 start-page: 330 issue: 600 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0055 article-title: Air pollution and infant mortality: evidence from the expansion of natural gas infrastructure publication-title: Econ. J. doi: 10.1111/ecoj.12285 – volume: 152 start-page: 259 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0235 article-title: Assessing CO2 emissions in China's iron and steel industry: evidence from quantile regression approach publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2017.03.142 – volume: 141 start-page: 1869 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0080 article-title: The economy-wide energy efficiency in China's regional building industry publication-title: Energy doi: 10.1016/j.energy.2017.11.114 – volume: 80 start-page: 153 year: 2019 ident: 10.1016/j.eneco.2019.04.012_bb0250 article-title: Economic growth, urbanization and energy consumption—a provincial level analysis of China publication-title: Energy Econ. doi: 10.1016/j.eneco.2019.01.004 – volume: 166 start-page: 952 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0150 article-title: Impacts of urbanization and real economic development on CO2 emissions in non-high income countries: empirical research based on the extended STIRPAT model publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2017.08.107 – volume: 63 start-page: 161 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0165 article-title: Spatial spillover effects in determining China's regional CO2 emissions growth: 2007–2010 publication-title: Energy Econ. doi: 10.1016/j.eneco.2017.02.001 – volume: 22 start-page: 213 issue: 1 year: 2019 ident: 10.1016/j.eneco.2019.04.012_bb0085 article-title: Bird diversity in urban ecosystems: the role of the biome and land use along urbanization gradients publication-title: Ecosystems doi: 10.1007/s10021-018-0264-y – volume: 39 start-page: 1240 issue: 7 year: 2011 ident: 10.1016/j.eneco.2019.04.012_bb0135 article-title: Sources of external technology, absorptive capacity, and innovation capability in Chinese state-owned high-tech enterprises publication-title: World Dev. doi: 10.1016/j.worlddev.2010.05.011 – volume: 69 start-page: 71 year: 2018 ident: 10.1016/j.eneco.2019.04.012_bb0140 article-title: Consumption-based accounting and the trade-carbon emissions nexus publication-title: Energy Econ. doi: 10.1016/j.eneco.2017.11.004 – volume: 78 start-page: 1350 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0005 article-title: A semi-parametric panel data analysis on the urbanization-carbon emissions nexus for the MENA countries publication-title: Renew. Sust. Energ. Rev. doi: 10.1016/j.rser.2017.05.006 – volume: 168 start-page: 780 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0145 article-title: Energy and carbon intensity in China during the urbanization and industrialization process: a panel VAR approach publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2017.09.013 – volume: 32 start-page: 591 issue: 3 year: 2010 ident: 10.1016/j.eneco.2019.04.012_bb0065 article-title: The causality between energy consumption and economic growth: a multi-sectoral analysis using non-stationary cointegrated panel data publication-title: Energy Econ. doi: 10.1016/j.eneco.2009.09.013 – volume: 27 start-page: 41 issue: 1 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0240 article-title: Impact of population and economic growth on carbon emissions in Taiwan using an analytic tool STIRPAT publication-title: Sustainable Environment Research doi: 10.1016/j.serj.2016.10.001 – volume: 139 start-page: 199 issue: 1/2 year: 1988 ident: 10.1016/j.eneco.2019.04.012_bb0105 article-title: Some recent developments in a concept of causality publication-title: J. Econ. doi: 10.1016/0304-4076(88)90045-0 – volume: 84 start-page: 469 issue: 2 year: 1997 ident: 10.1016/j.eneco.2019.04.012_bb0155 article-title: Miscellanea efficient estimation of additive nonparametric regression models publication-title: Biometrika doi: 10.1093/biomet/84.2.469 – volume: 185 start-page: 604 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0175 article-title: Air emissions perspective on energy efficiency: an empirical analysis of China's coastal areas publication-title: Appl. Energy doi: 10.1016/j.apenergy.2016.10.127 – start-page: 251 year: 1987 ident: 10.1016/j.eneco.2019.04.012_bb0070 article-title: Co-integration and error correction: representation, estimation, and testing publication-title: Econometrica: Journal of the Econometric Society doi: 10.2307/1913236 – volume: 106 start-page: 699 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0090 article-title: Design and optimization of shale gas energy systems: overview, research challenges, and future directions publication-title: Comput. Chem. Eng. doi: 10.1016/j.compchemeng.2017.01.032 – volume: 69 start-page: 404 year: 2018 ident: 10.1016/j.eneco.2019.04.012_bb0245 article-title: The evolution of inter-sectoral linkages in China's energy-related CO2 emissions from 1997 to 2012 publication-title: Energy Econ. doi: 10.1016/j.eneco.2017.11.022 – ident: 10.1016/j.eneco.2019.04.012_bb0015 doi: 10.1016/j.energy.2019.02.114 – volume: 111 start-page: 394 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0200 article-title: Promoting green productivity growth for China's industrial exports: evidence from a hybrid input-output model publication-title: Energy Policy doi: 10.1016/j.enpol.2017.09.033 – year: 2008 ident: 10.1016/j.eneco.2019.04.012_bb0020 – volume: 17 start-page: 453 year: 1989 ident: 10.1016/j.eneco.2019.04.012_bb0045 article-title: Linear smoothers and additive models publication-title: Ann. Stat. – volume: 108 start-page: 1 issue: 1 year: 2002 ident: 10.1016/j.eneco.2019.04.012_bb0120 article-title: Unit root tests in panel data: asymptotic and finite-sample properties publication-title: J. Econ. doi: 10.1016/S0304-4076(01)00098-7 – volume: 142 start-page: 548 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0210 article-title: China's natural gas consumption peak and factors analysis: a regional perspective publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2016.04.095 – volume: 72 start-page: 74 year: 2018 ident: 10.1016/j.eneco.2019.04.012_bb0095 article-title: A new method for dealing simultaneously with spatial autocorrelation and spatial heterogeneity in regression models publication-title: Reg. Sci. Urban Econ. doi: 10.1016/j.regsciurbeco.2017.04.001 – volume: 113 start-page: 689 year: 1985 ident: 10.1016/j.eneco.2019.04.012_bb0185 article-title: Additive regression and other nonparametric models publication-title: Ann. Stat. – volume: 10 start-page: 855 issue: 4 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0050 article-title: Drivers for energy efficiency and their effect on barriers: empirical evidence from Italian manufacturing enterprises publication-title: Energy Efficiency doi: 10.1007/s12053-016-9488-x – volume: 108 start-page: 696 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb0205 article-title: Decline in China's coal consumption: an evidence of peak coal or a temporary blip? publication-title: Energy Policy doi: 10.1016/j.enpol.2017.06.041 – volume: 140 start-page: 941 year: 2017 ident: 10.1016/j.eneco.2019.04.012_bb8000 article-title: Forecasting China’s natural gas demand based on optimised nonlinear grey models. publication-title: Energy doi: 10.1016/j.energy.2017.09.037 – year: 1993 ident: 10.1016/j.eneco.2019.04.012_bb0100 |
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Title | Can expanding natural gas consumption reduce China's CO2 emissions? |
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