不同经济发展路径下的能源需求与碳排放预测——基于河北省的分析

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (499 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract This study uses the cointegration test and the Markov chain method to project Hebei's future (2017~2035) energy demand and structure, and the associated CO₂ emissions by considering three distinct economic developing scenarios. The results show that the economic growth has strong pulling effect on energy demand. Under the low-growth scenario, Hebei's per capita energy consumption and total consumption will reach 5.261tce and 416.13million tce respectively. While these consumptions will be 7.618tce and 602.58million tce respectively under the high-growth scenario. Hebei's future energy consumption structure will maintain stable in the long term, unlikely to change the percentage of coal in total energy consumption. The coal consumption will reach 88.16% in Hebei's total energy consumption in 2035. The increasing trend of Hebei's CO₂ emissions will continue in the long run. Under the high-growth scenario, Hebei's total CO₂ emissions will increase from 876.99million ton in 2017 to 1 591.17million ton, 1.01times and 1.45times higher than the contemporaneous emissions in the low-growth scenario respectively. It's thus necessary to keep Hebei's economic growth within a rational range, optimize energy consumption structure, adjust industrial distribution, cultivate and develop new economy.

Key words： energy demand projection energy structure projection economic growth carbon emission Hebei province

Received: 27 February 2019

PACS:

X24

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	WENG Zhi-xiong
	MA Zhong-yu
	GE Cha-zhong
	CAI Song-feng
	CHENG Cui-yun
	DU Yan-Chun

Cite this article:

WENG Zhi-xiong,MA Zhong-yu,GE Cha-zhong等. Projection on energy demand and carbon emission in various economic developing pathways——A case study in Hebei province[J]. CHINA ENVIRONMENTAL SCIENCECE, 2019, 39(8): 3508-3517.

URL:

http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2019/V39/I8/3508

[1]	杜颖.河北省经济增长与大气污染关系研究[D]. 北京:中国地质大学(北京), 2016. Du Y. Study on relationship between economic growth and air pollution in Hebei province[D]. Beijing:China University of Geosciences (Beijing), 2016.
[2]	生态环境部.2017中国生态环境状况公报[R]. 北京:生态环境部, 2018:1-54. Ministry of Ecology and Environment (MEE). China's ecological and environmental bulletin in 2017[R]. Beijing:MEE, 2018:1-54.
[3]	闫云凤.京津冀碳足迹演变趋势与驱动机制研究[J]. 软科学, 2016, 30(8):10-14. Yan Y F. The carbon footprint's trends and its drivers in Beijing-Tianjin-Hebei region[J]. Soft Science, 2016,30(8):10-14.
[4]	伯鑫,徐峻,杜晓惠,等.京津冀地区钢铁企业大气污染影响评估[J]. 中国环境科学, 2017,37(5):1684-1692. Bo X, Xu J, Du X H, et al. Impacts assessment of steel plants on air quality over Beijing-Tianjin-Hebei[J]. China Environmental Science, 2017,37(5):1684-1692.
[5]	伯鑫,赵春丽,吴铁,等.京津冀地区钢铁行业高时空分辨率排放清单方法研究[J]. 中国环境科学, 2015,35(8):2554-2560. Bo X, Zhao C L, Wu T, et al. Emission inventory with high temporal and spatial resolution of steel industry in the Beijing-Tianjin-Hebei region[J]. China Environmental Science, 2015,35(8):2554-2560.
[6]	陈慧萍.基于供给侧改革的河北钢铁产能过剩研究[J]. 当代经济, 2017(29):141-143. Chen H P. Study on steel overcapacity in Hebei based on the supply-side reform[J]. Contemporary Economics, 2017,(29):141-143.
[7]	河北省统计局.河北经济年鉴2017[R]. 北京:中国统计出版社, 2017. Hebei Statistical Bureau. Hebei economic yearbook in 2017[R]. Beijing:China Statistical Press, 2017.
[8]	李云燕,殷晨曦.京津冀地区PM2.5减排实效与影响因素的门限效应[J]. 中国环境科学, 2017,37(4):1223-1230. Li Y Y, Yin C X. Threshold effect of socio-economic factors influencing PM2.5 in Beijing-Tianjin-Hebei[J] China Environmental Science, 2017,37(4):1223-1230.
[9]	Lee C C. Energy consumption and GDP in developing countries:a cointegrated panel analysis[J]. Energy economics, 2005,27(3):415-427.
[10]	林伯强.中国能源需求的经济计量分析[J]. 统计研究, 2001, 10(10):34-39. Lin B Q. Study on the energy demand in China based on econometric theory[J]. Statistical Research, 2001,10(10):34-39.
[11]	林伯强.结构变化、效率改进与能源需求预测-以中国电力行业为例[J]. 经济研究, 2003,(5):57-65. Lin B Q. Structural changes, efficiency improvement and electricity demand forecasting[J]. Economic Research, 2003(5):57-65.
[12]	何晓萍,刘希颖,林艳苹.中国城市化进程中的电力需求预测[J]. 经济研究, 2009,(1):118-130. He X P, Liu X Y, Lin Y P. China's electricity demand forecast under urbanization process[J]. Economic Research, 2009,(1):118-130.
[13]	刘兰凤,易行健.中国能源需求的估计与预测模拟[J]. 上海财经大学学报, 2008,4(10):84-91. Liu L F, Yi X J. An estimation on forecast of energy demand in China[J]. Journal of Shanghai University of Finance and Economics, 2008,4(10):84-91.
[14]	林伯强,吴微.中国现阶段经济发展中的煤炭需求[J]. 中国社会科学, 2018(2):141-161. Lin B Q, Wu W. Demand for coal in current Chinese economic development[J]. Social Science in China, 2018,(2):141-161.
[15]	Wang Y Y, Wang J Z, Zhao G, et al. Application of residual modification approach in seasonal ARIMA for electricity demand forecasting:A case study of China[J]. Energy Policy, 2012,48:284-294.
[16]	Lee C C, Chang C P. The impact of energy consumption on economic growth:evidence from linear and nonlinear models in Taiwan[J]. Energy, 2007,32(12):2282-2294.
[17]	Belke A, Dobnik F, Dreger C. Energy consumption and economic growth:New insights into the cointegration relationship[J]. Energy Economics, 2011,33(5):782-789.
[18]	王锋,冯根福.优化能源结构对实现中国碳强度目标的贡献潜力评估[J]. 中国工业经济, 2011(4):127-137. Wang F, Feng G F. Contribution of improving energy mix to carbon intensity target in China[J]. China Industrial Economics, 2011,(4):127-137.
[19]	刘金明.基于资源与环境约束的中国能源供需格局发展研究[D]. 北京:华北电力大学, 2013. Liu J M. Development of the energy supply and demand pattern of China under the constraints of resources and environment[D]. Beijing:North China Electric Power University, 2013.
[20]	王彩明,李健.一次能源消费结构调整对京津冀碳强度目标的贡献力分析[J]. 科技管理研究, 2017,(7):226-233. Wang C M, Li J. Potential contribution analysis of primary consumption structure adjustment to the carbon intensity coal of Beijing-Tianjin-Hebei region[J]. Science and Technology Management Research, 2017,(7):226-233.
[21]	Lin B Q, Ouyang X L. Energy demand in China:Comparison of characteristics between the US and China in rapid urbanization stage[J]. Energy conversion and management, 2014,79:128-139.
[22]	Yuan X C, Sun X, Zhao W G,et al. Forecasting China's regional energy demand by 2030:A Bayesian approach[J]. Resources, Conservation and Recycling, 2017,127:85-95.
[23]	周伟,米红.中国能源消费排放的CO2测算[J]. 中国环境科学, 2010,30(8):1142-1148. Zhou W, Mi H. Calculation on energy-related CO2 emissions in China[J]. China Environmental Science, 2010,30(8):1142-1148.
[24]	马晓君,董碧滢,于渊博,等.东北三省能源消费碳排放测度及影响因素[J]. 中国环境科学, 2018,38(8):3170-3179. Ma X J, Dong B Y, Yu Y B, et al. Measurement of carbon emissions from energy consumption in three Northeastern provinces and its driving factors[J]. China Environmental Science, 2018,38(8):3170-3179.
[25]	林伯强,李江龙.环境治理约束下的中国能源结构转变-基于煤炭和二氧化碳峰值的分析[J]. 中国社会科学, 2015,(9):84-107. Lin B Q, Li J L. Transformation of China's energy structure under environmental governance constraints:A peak value analysis of coal and carbon dioxide[J]. Social Science in China, 2015,(9):84-107.
[26]	马宏伟,刘思峰,袁潮清,等.基于生产函数的中国能源消费与经济增长的多变量协整关系的分析[J]. 资源科学, 2012,34(12):2374-2381. Ma H W, Liu S F, Yuan C Q,et al. Cointegration analysis of economic growth and energy consumption in China[J]. Resources Science, 2012, 34(12):2374-2381.
[27]	林伯强,蒋竺均.中国二氧化碳的环境库兹涅茨曲线预测及影响因素分许[J]. 管理世界, 2009,(4):27-36. Lin B Q, Jiang Z J. Projection and factor analysis on China's Environmental Kuznets Curve of carbon dioxide[J] Management World, 2009,(4):27-36.
[28]	孙广生,黄祎,田海峰,等.全要素生产率、投入替代与地区间的能源效率[J]. 经济研究, 2012,(9):99-112. Sun G S, Huang W, Tian H F, et al. Total factor productivity, inputs substitution and regional energy efficiency disparity[J]. Economic Research, 2012,(9):99-112.
[29]	MacKinnon J G. Numerical distribution functions for unit root and cointegration tests[J]. Journal of applied econometrics, 1996,11(6):601-618.
[30]	Maddala G S, Wu S. A comparative study of unit root tests with panel data and a new simple test[J]. Oxford Bulletin of Economics and statistics, 1999,61(S1):631-652.
[31]	河北省人民政府.河北省人口发展规划(2018~2035年)[R]. 河北:河北省人民政府, 2018. Hebei government. Hebei's pollution growth plan (2018~2035)[R]. Hebei:Hebei government, 2018.
[32]	国务院.国家人口发展规划(2016~2030年)[R]. 北京:国务院, 2016. State Council. National pollution growth plan (2016~2030)[R]. Beijing:State Council, 2016.
[33]	河北省统计局.河北省2017年国民经济和社会发展统计公报[R]. 河北:河北省统计局, 2018. Hebei Statistical Bureau. Hebei's economic and social development bulletin in 2017[R]. Hebei:Hebei Statistical Bureau, 2018.
[34]	李善同.2005~2020年中国经济增长前景分析[J]. 财经界, 2005,(11):10-15. Li S T. Projection on China's economic growth between 2005 and 2020[J]. Finance China, 2005,(11):10-15.
[35]	国家统计局.中国2017年国民经济和社会发展统计公报[R]. 北京:国家统计局, 2018. National Statistical Bureau. China's economic and social development bulletin in 2017[R]. Beijing:National Statistical Bureau, 2018.
[36]	河北省人民政府.河北省国民经济和社会发展第十三个五年规划纲要[R]. 河北:河北省人民政府, 2016. Hebei government. Hebei's economic and social development plan during the 13th five-year period[R]. Hebei:Hebei government, 2016.
[37]	白重恩,张琼.中国经济增长潜力预测:兼顾跨国生产率收敛与中国劳动力特征的供给侧分析[J]. 经济学报, 2017,4(4):1-27. Bai C E, Zhang Q. China's growth potential to 2050:A supply-side forecast based on cross-country productivity convergence and its featured labor force[J]. China Journal of Economics, 2017,4(4):1-27.
[38]	李志俊,原鹏飞.去产能战略的影响评价及建议-基于动态CGE模型的研究[J]. 中国软科学, 2018,(1):10-18. Li Z J, Yuan P F. Evaluation and route overcapacity cutting:Analysis based on dynamic computable general equilibrium model[J]. China Soft Science, 2018,(1):10-18.
[39]	国家统计局.中国2008年国民经济和社会发展统计公报[R]. 北京:国家统计局, 2009. National Statistical Bureau. China's economic and social development bulletin in 2008[R]. Beijing:National Statistical Bureau, 2009.