Abstract
Clean energy transition has been considered as an indispensable way to attain sustainable development for China, where the coal-to-gas initiative plays a vital role towards the goal. This paper takes Beijing, China’s political and economic center as well as a national pioneer in the energy transition, as a case to systematically analyze the co-mitigation of air pollution (PM2.5) and carbon emissions (CO2) achieved by the policy-driven natural gas-coal consumption substitution. Firstly, a qualitative analysis of the relationship of Beijing’s coal-to-gas policies and its air quality has been conducted. Then, VAR and ARDL models are employed to quantitatively analyze the impacts of coal-to-gas policies on PM2.5 and CO2, respectively. Results show that (i) an innovation of natural gas/coal consumption ratio will reduce PM2.5 concentrations, and the effect decreases over time; and (ii) an increase of 1% in natural gas/coal consumption ratio in Beijing will cause a decrease of 0.0784% in CO2 emissions in the long run. Therefore, the coal-to-gas policies do increase the usage of natural gas and improve Beijing’s air quality. The assessment methods and conclusions can be regarded as a reference for not only China’s policymakers, but also other countries, especially nowadays when air quality is becoming more valued and GHGs are being tightly controlled.
Similar content being viewed by others
References
BGGRI (2020) Beijing Gas Group Research Institute. http://www.bj-kys.com. Accessed 20 Apr 2020
BJMEMC (2020) BeijingMunicipal Ecological and Environmental Monitoring Center. http://www.bjmemc.com.cn/. Accessed 29 Feb 2020
Cao J-J, Shen Z-X, Chow JC, Watson JG, Lee SC, Tie XX, Ho KF, Wang GH, Han YM (2012) Winter and Summer PM2.5 chemical compositions in fourteen Chinese cities. J Air Waste Manage Assoc 62:1214–1226. https://doi.org/10.1080/10962247.2012.701193
Dong K, Sun R, Dong C, Li H, Zeng X, Ni G (2018a) Environmental Kuznets curve for PM2.5 emissions in Beijing, China: what role can natural gas consumption play? Ecol Indic 93:591–601. https://doi.org/10.1016/j.ecolind.2018.05.045
Dong K, Sun R, Dong X (2018b) CO2 emissions, natural gas and renewables, economic growth: assessing the evidence from China. Sci Total Environ 640–641:293–302. https://doi.org/10.1016/j.scitotenv.2018.05.322
Durbin J, Brown RL, Evans JM (1975) Techniques for testing the constancy of regression relationships over time. J R Stat Soc Ser B 37:149–192. https://doi.org/10.1111/j.2517-6161.1975.tb01532.x
Elser M, Huang R-J, Wolf R, Slowik JG, Wang Q, Canonaco F, Li G, Bozzetti C, Daellenbach KR, Huang Y, Zhang R, Li Z, Cao J, Baltensperger U, el-Haddad I, Prévôt ASH (2016) New insights into PM2.5 chemical composition and sources in two major cities in China during extreme haze events using aerosol mass spectrometry. Atmos Chem Phys 16:3207–3225. https://doi.org/10.5194/acp-16-3207-2016
Erdiwansyah, Mamat R, Sani MSM, Sudhakar K (2019) Renewable energy in Southeast Asia: policies and recommendations. Sci Total Environ 670:1095–1102. https://doi.org/10.1016/j.scitotenv.2019.03.273
Granier C, Darras S, van der Gon HD et al (2019) The Copernicus Atmosphere Monitoring Service global and regional emissions (April 2019 version). https://doi.org/10.24380/d0bn-kx16
Harris R, Sollis R (2005) Applied time series. Modeling and forecasting. Willey, Chichester
Hong Y-Y, Apolinario GFDG, Chung C-N, Lu TK, Chu CC (2020) Effect of Taiwan’s energy policy on unit commitment in 2025. Appl Energy 277:115585. https://doi.org/10.1016/j.apenergy.2020.115585
Kurokawa J, Ohara T (2019) Long-term historical trends in air pollutant emissions in Asia: regional Emission inventory in ASia (REAS) version 3.1. Atmos Chem Phys Discuss 2019:1–51. https://doi.org/10.5194/acp-2019-1122
Laes E, Gorissen L, Nevens F (2014) A comparison of energy transition governance in Germany, the Netherlands and the United Kingdom. Sustainability 6:1129–1152. https://doi.org/10.3390/su6031129
Li R, Su M (2017) The role of natural gas and renewable energy in curbing carbon emission: case study of the United States. Sustainability 9:600. https://doi.org/10.3390/su9040600
Li L, Taeihagh A (2020) An in-depth analysis of the evolution of the policy mix for the sustainable energy transition in China from 1981 to 2020. Appl Energy 263:114611. https://doi.org/10.1016/j.apenergy.2020.114611
Ma M, Cai W, Cai W (2018) Carbon abatement in China’s commercial building sector: a bottom-up measurement model based on Kaya-LMDI methods. Energy 165:350–368. https://doi.org/10.1016/j.energy.2018.09.070
Ma M, Ma X, Cai W, Cai W (2019) Carbon-dioxide mitigation in the residential building sector: a household scale-based assessment. Energy Convers Manag 198:111915. https://doi.org/10.1016/j.enconman.2019.111915
Ma M, Ma X, Cai W, Cai W (2020) Low carbon roadmap of residential building sector in China: historical mitigation and prospective peak. Appl Energy 273:115247. https://doi.org/10.1016/j.apenergy.2020.115247
Mirmirani S, Cheng Li H (2004) A comparison of var and neural networks with genetic algorithm in forecasting price of oil. In: Binner JM, Kendall G, Chen S-H (eds) . Emerald Group Publishing Limited, Applications of artificial intelligence in finance and economics, pp 203–223
Monstadt J, Wolff A (2015) Energy transition or incremental change? Green policy agendas and the adaptability of the urban energy regime in Los Angeles. Energy Policy 78:213–224. https://doi.org/10.1016/j.enpol.2014.10.022
Müller F, Claar S, Neumann M, Elsner C (2020) Is green a Pan-African colour? Mapping African renewable energy policies and transitions in 34 countries. Energy Res Soc Sci 68:101551. https://doi.org/10.1016/j.erss.2020.101551
National Bureau of Statistics of China (2021) China Statistical Yearbook 2020. China Statistics Press, Beijing
Ortega-Ruiz G, Mena-Nieto A, García-Ramos JE (2020) Is India on the right pathway to reduce CO2 emissions? Decomposing an enlarged Kaya identity using the LMDI method for the period 1990–2016. Sci Total Environ 737:139638. https://doi.org/10.1016/j.scitotenv.2020.139638
Pereira MA, Pereira M (2010) Is fuel-switching a no-regrets environmental policy? VAR evidence on carbon dioxide emissions, energy consumption and economic performance in Portugal. Energy Econ 32:227–242. https://doi.org/10.1016/j.eneco.2009.08.002
Pesaran H (1997) An autoregressive distributed lag modelling approach to cointegration analysis. Science 7825:371–413. https://doi.org/10.1017/CCOL0521633230.011
Pesaran H, Shin Y, Smith RJ (1996) Testing the existence of a long-run relationship
Rahman MM, Kashem MA (2017) Carbon emissions, energy consumption and industrial growth in Bangladesh: empirical evidence from ARDL cointegration and Granger causality analysis. Energy Policy 110:600–608. https://doi.org/10.1016/j.enpol.2017.09.006
Sack B (2000) Does the fed act gradually? A VAR analysis. J Monet Econ 46:229–256. https://doi.org/10.1016/S0304-3932(00)00019-2
Shen M (2013) Literature review about low-carbon energy and reduce carbon emission from energy research. J Low Carbon Econ 02:49–56. https://doi.org/10.12677/JLCE.2013.21008
Sims C (1980) Macroeconomics and Reality. Econometrica 48:1–48. https://doi.org/10.2307/1912017
Steinbacher K, Röhrkasten S (2019) An outlook on Germany’s international energy transition policy in the years to come: solid foundations and new challenges. Energy Res Soc Sci 49:204–208. https://doi.org/10.1016/j.erss.2018.10.013
Wu S (2020) The evolution of rural energy policies in China: a review. Renew Sust Energ Rev 119:109584. https://doi.org/10.1016/j.rser.2019.109584
Xu B, Lin B (2019) Can expanding natural gas consumption reduce China’s CO2 emissions? Energy Econ 81:393–407. https://doi.org/10.1016/j.eneco.2019.04.012
Yuan X, Zuo J (2011) Transition to low carbon energy policies in China—from the Five-Year Plan perspective. Energy Policy 39:3855–3859. https://doi.org/10.1016/j.enpol.2011.04.017
Zhang Y, Li W, Wu F (2020) Does energy transition improve air quality? Evidence derived from China’s Winter Clean Heating Pilot (WCHP) project. Energy 206:118130. https://doi.org/10.1016/j.energy.2020.118130
Zhou S, Matisoff DC, Kingsley GA, Brown MA (2019) Understanding renewable energy policy adoption and evolution in Europe: The impact of coercion, normative emulation, competition, and learning. Energy Res Soc Sci 51:1–11. https://doi.org/10.1016/j.erss.2018.12.011
Availability of data
The PM2.5 data analyzed during the current study are available in the Beijing Municipal Ecological and Environmental Monitoring Center repository, http://www.bjmemc.com.cn/. The CO2 dataset analyzed during the current study are available in the Beijing Municipal Ecological and Environmental Monitoring Center repository, http://www.bjmemc.com.cn/. The CO2 data analyzed during this study are included in this published article: Long-term historical trends in air pollutant emissions in Asia: Regional Emission inventory in ASia (REAS) version 3.1.
The daily consumption data that support the findings of this study are available from Beijing Gas Group Company Limited but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Beijing Gas Group Company Limited.
Funding
The relevant researches carried out in this paper are supported by the National Natural Science Foundation of China (No.71874201; 71871084; 71503264).
Author information
Authors and Affiliations
Contributions
Conceptualization: JLW. Data curation: JLW, ZHL, HKY, YDM, JXF. Methodology: ZHL, HKY. Formal analysis and investigation: JLW, ZHL, HKY. Writing—original draft preparation: ZHL, HKY, QL. Writing—review and editing: JLW, YDM. Visualization: ZHL, HKY. Funding acquisition: JLW. Supervision: JLW, YDM.
Corresponding author
Ethics declarations
Ethics approval
Not applicable.
Consent to participate
Not applicable.
Consent to publish
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Additional information
Responsible Editor: Baojing Gu
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Highlights
• Coal-to-gas policies in Beijing have been systematically reviewed and analyzed.
• The effect of policy implementation is analyzed qualitatively and quantitatively.
• Results show that coal-to-gas policies do improve Beijing’s air quality significantly.
• Impacts of policies on PM2.5 are significant in short term and stabilize in the long term.
• The dampening effect of policies on CO2 emissions is significant in the long run.
Rights and permissions
About this article
Cite this article
Wang, J., Li, Z., Ye, H. et al. Do China’s coal-to-gas policies improve regional environmental quality? A case of Beijing. Environ Sci Pollut Res 28, 57667–57685 (2021). https://doi.org/10.1007/s11356-021-14727-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-021-14727-3