中国物质资源消费区域差异的测度及分析

傅一珂, 陈定江, 朱兵, 胡山鹰

清华大学学报（自然科学版） ›› 2020, Vol. 60 ›› Issue (7) : 611-616.

PDF(943 KB)
横山亮次奖  |  百年刊庆  |  中文  |  English
PDF(943 KB)
清华大学学报（自然科学版） ›› 2020, Vol. 60 ›› Issue (7) : 611-616. DOI: 10.16511/j.cnki.qhdxxb.2019.22.031
化学与化学工程

中国物质资源消费区域差异的测度及分析

  • 傅一珂1, 陈定江1,2, 朱兵1,2, 胡山鹰1,2
作者信息 +

Measurement and analyses of regional differences in material consumption in China

  • FU Yike1, CHEN Dingjiang1,2, ZHU Bing1,2, HU Shanying1,2
Author information +
文章历史 +

摘要

区域资源环境不平衡是中国发展面临的突出问题之一。该文基于修正的原始资源消耗当量的测算结果和Gini系数法，对2010-2015年中国人均物质资源消耗的区域不平衡进行了测度和空间分解，并比较了物质资源消耗、温室气体排放和GDP在区域分布、不平衡模式上的异同。结果表明：中国人均物质资源消耗和温室气体排放的区域不平衡模式有一定相似性，组内差异和组间差异对Gini系数的贡献率均为25%~30%；但与中国GDP和全球温室气体的不平衡模式有显著差异。

Abstract

The inequality of regional resources and environments is one of the most pressing problems for China's development. The adjusted raw material consumption method and the Gini coefficient were used to measure and spatially decompose the inequality in per capita material consumption, greenhouse gas emissions and GDP at the regional scale in China during 2010 to 2015. The paper also compared the material consumption with the greenhouse gas emissions and GDP at the regional level to identify inequality patterns. The results show that the inequality pattern of the per capita material consumption in China's provinces is similar to the per capita greenhouse gas emissions in China, where inter-regional and intra-regional components both contribute 25%-30% to the Gini coefficient. The results also show significant differences between China's GDP and global greenhouse gas emissions.

关键词

物质资源消耗 / 区域差异 / Gini系数

Key words

material consumption / regional difference / Gini coefficient

引用本文

EndNote

Ris (Procite)

Bibtex

导出引用
傅一珂, 陈定江, 朱兵, 胡山鹰. 中国物质资源消费区域差异的测度及分析[J]. 清华大学学报（自然科学版）. 2020, 60(7): 611-616 https://doi.org/10.16511/j.cnki.qhdxxb.2019.22.031
FU Yike, CHEN Dingjiang, ZHU Bing, HU Shanying. Measurement and analyses of regional differences in material consumption in China[J]. Journal of Tsinghua University(Science and Technology). 2020, 60(7): 611-616 https://doi.org/10.16511/j.cnki.qhdxxb.2019.22.031

参考文献

[1] XIE Y, ZHOU X. Income inequality in today's China[J]. Proceedings of the National Academy of Sciences of the United States of America, 2014, 111(19):6928-6933.
[2] PIKETTY T, YANG L, ZUCMAN G. Capital accumulation, private property and rising inequality in China, 1978-2015[R]. Cambridge, USA:National Bureau of Economic Research, 2017.
[3] CHAKRAVARTY S, CHIKKATUR A, DE CONINCK H, et al. Sharing global CO2 emission reductions among one billion high emitters[J]. Proceedings of the National Academy of Sciences of the United States of America, 2009, 106(29):11884-11888.
[4] ROGELJ J, DEN ELZEN M, HÖHNE N, et al. Paris Agreement climate proposals need a boost to keep warming well below 2℃[J]. Nature, 2016, 534(7609):631-639.
[5] FISCHER C, FOX A K. Comparing policies to combat emissions leakage:Border carbon adjustments versus rebates[J]. Journal of Environmental Economics and Management, 2012, 64(2):199-216.
[6] RODRIK D. Green industrial policy[J]. Oxford Review of Economic Policy, 2014, 30(3):469-491.
[7] METCALF G E, WEISBACH D. The design of a carbon tax[J]. Harvard Environmental Law Review, 2009, 33(2):499-556.
[8] ZHANG X P, CHENG X M. Energy consumption, carbon emissions, and economic growth in China[J]. Ecological Economics, 2009, 68(10):2706-2712.
[9] KUIK O, HOFKES M. Border adjustment for European emissions trading:Competitiveness and carbon leakage[J]. Energy Policy, 2010, 38(4):1741-1748.
[10] OBERLE B, BRINGEZE S, HATFIELD-DODDS S, et al. Global resource outlook 2019:Natural resources for the future we want[M]. Nairobi, Kenya:United Nations Environment Programme, 2019.
[11] LUTTER S, GILJUM S, BRUCKNER M. A review and comparative assessment of existing approaches to calculate material footprints[J]. Ecological Economics, 2016, 127:1-10.
[12] EISENMENGER N, WIEDENHOFER D, SCHAFFARTZIK A, et al. Consumption-based material flow indicators:Comparing six ways of calculating the Austrian raw material consumption providing six results[J]. Ecological Economics, 2016, 128:177-186.
[13] WANG H M, HASHIMOTO S, MORIGUCHI Y, et al. Resource use in growing China:Past trends, influence factors, and future demand[J]. Journal of Industrial Ecology, 2012, 16(4):481-492.
[14] HU Y, WEN Z G, LEE J C K, et al. Assessing resource productivity for industrial parks using adjusted raw material consumption (ARMC)[J]. Resources, Conservation and Recycling, 2017, 124:42-49.
[15] 张音波, 陈新庚, 彭晓春, 等. 广东省环境经济系统的物质流分析[J]. 环境科学学报, 2008, 28(5):1021-1031.ZHANG Y B, CHEN X G, PENG X C, et al. Material flow analysis (MFA) of the environment and the economy in Guangdong Province[J]. Acta Scientiae Circumstantiae, 2008, 28(5):1021-1031. (in Chinese)
[16] BARLES S. Urban metabolism of Paris and its region[J]. Journal of Industrial Ecology, 2009, 13(6):898-913.
[17] DURO J A. On the automatic application of inequality indexes in the analysis of the international distribution of environmental indicators[J]. Ecological Economics, 2012, 76:1-7.
[18] PADILLA E, SERRANO A. Inequality in CO2 emissions across countries and its relationship with income inequality:A distributive approach[J]. Energy Policy, 2006, 34(14):1762-1772.
[19] CANTORE N, PADILLA E. Equality and CO2 emissions distribution in climate change integrated assessment modelling[J]. Energy, 2010, 35(1):298-313.
[20] GROOT L. Carbon Lorenz curves[J]. Resource and Energy Economics, 2010, 32(1):45-64.
[21] TENG F, HE J K, PAN X Z, et al. Metric of carbon equity:Carbon Gini index based on historical cumulative emission per capita[J]. Advances in Climate Change Research, 2011, 2(3):134-140.
[22] WIEDENHOFER D, GUAN D B, LIU Z, et al. Unequal household carbon footprints in China[J]. Nature Climate Change, 2017, 7(1):75-80.
[23] XU X K, HAN L Y, LV X F. Household carbon inequality in urban China, its sources and determinants[J]. Ecological Economics, 2016, 128:77-86.
[24] DURO J A, PADILLA E. International inequalities in per capita CO2 emissions:A decomposition methodology by Kaya factors[J]. Energy Economics, 2006, 28(2):170-187.
[25] CLARKE-SATHER A, QU J S, WANG Q, et al. Carbon inequality at the sub-national scale:A case study of provincial-level inequality in CO2 emissions in China 1997-2007[J]. Energy Policy, 2011, 39(9):5420-5428.
[26] 洪丽云. 基于ARMC的省域层面资源生产率研究[D]. 北京:清华大学, 2011. HONG L Y. Analysis of provincial resource productivity based on ARMC[D]. Beijing:Tsinghua University, 2011. (in Chinese)
[27] 国家统计局能源统计司. 资源产出率统计试点调查培训资料[M]. 北京:国家统计局能源统计司, 2012. Energy Statistics Division of National Bureau of Statistics. Training materials for pilot survey of resource productivity[M]. Beijing:Energy Statistics Division of National Bureau of Statistics of the People's Republic of China, 2012. (in Chinese)
[28] YITZHAKI S, LERMAN R I. Income stratification and income inequality[J]. Review of Income and Wealth, 1991, 37(3):313-329.
[29] SHAN Y L, GUAN D B, ZHENG H R, et al. China CO2 emission accounts 1997-2015[J]. Scientific Data, 2018, 5:170-201.
[30] LIU Z, GUAN D B, WEI W, et al. Reduced carbon emission estimates from fossil fuel combustion and cement production in China[J]. Nature, 2015, 524(7565):335-338.
[31] MUSSINI M, GROSSI L. Decomposing changes in CO2 emission inequality over time:The roles of re-ranking and changes in per capita CO2 emission disparities[J]. Energy Economics, 2015, 49:274-281.
[32] SAUTER C, GRETHER J M, MATHYS N A. Geographical spread of global emissions:Within-country inequalities are large and increasing[J]. Energy Policy, 2016, 89:138-149.

基金

陈定江,副教授,E-mail:chendj@tsinghua.edu.cn

PDF(943 KB)

Accesses

Citation

Detail
段落导航
相关文章
扫码关注，本刊微信公众号
地址：清华大学东门外学研大厦B座908室　
邮编：100084
电话：010-62788108/62771385/62792976/62792994　
E-mail：xuebaost@tsinghua.edu.cn
访问统计
    总访问量
    今日访问
    在线人数
　
版权所有 © 《清华大学学报（自然科学版）》编辑部

/

〈 〉