摘要
在人均碳排放和效率协调基础上,计算区域碳减排潜力,对于更好地促进绿色低碳经济发展具有积极意义。《人均碳排放和效益协调视角下的中国分省碳减排潜力数据集》是基于《中国统计年鉴》、《中国能源统计年鉴》和"国泰安金融数据库"中1997–2015年中国29个省级地区(海南、西藏、香港、澳门、台湾因数据不全,没有统计)的数据开发得到。研发的流程包括:首先,按照各省的投资隐含平减指数将历年的固定资本形成额统一折算成1952年不变价的数值;然后,根据所设定的折旧率和基期资本存量,运用永续盘存法对历年资本存量进行估算,得到资本存量数据;将1997–2015年各省名义GDP除以1952年为基期的GDP平减指数得到以1952年为基期的实际GDP;根据化石燃料燃烧以及水泥的消耗量以及对应的碳排放系数折算得到各省碳排放总量,再除以年末总人口数计算得到人均碳排放量;利用每单位国民生产总值的增长所带来的二氧化碳排放量表征碳排放强度;通过Super-SBM模型测算碳排放效率;基于Markov链框架测算人均碳排放和效率的俱乐部趋同指数,以分析人均碳排放和效率原则在考察中国碳减排潜力中的重要性以及在制定碳减排政策时的侧重点,进而在人均碳排放与效率协调的视角下重新测算出各省份的碳减排潜力,得到人均碳排放与效率协调视角下的中国分省碳减排潜力数据集。该数据集包括:(1)1997–2015年中国29省资本存量;(2)1997–2015年中国29省以1952年为基期的实际GDP;(3)1997–2015年中国29省人均碳排放量;(4)1997–2015年中国29省碳排放强度;(5)1997–2015年中国29省碳排放效率(Super-SBM模型);(6)1997–2015年中国29省能源消费数据;(7)中国人均碳排放与效率的Markov转移概率结果;(8)不同时长下人均碳排放和效率的俱乐部趋同指数模型;(9)人均碳排放与效率的区域固化程度差异性检验;(10)人均碳排放与效率协调视角下中国分省碳减排潜力指数测算。数据集存储为.xlsx格式,由1个文件组成,数据量为134 KB。基于该数据集的分析研究成果发表在《自然资源学报》2019年第34卷第1期。
We developed a dataset on the potentialities of carbon emission reduction and the emissions efficiency metadata extracted for 29 provinces in China.The data were obtained from the China Statistical Yearbook,the China Energy Statistical Yearbook,and the China Stock Market&Accounting Research Databases for the period of 1997–2015.Hainan,Tibet,Hong Kong,Macao,and Taiwan were not included in the dataset because of incomplete data.Firstly,we converted the fixed capital generated over the study period into uniform values with reference to the constant price in 1952 using an implicit investment deflator in each province.Secondly,referring to the set depreciation rate and the base period capital stock,we applied the perpetual inventory method to estimate annual capital stocks.Actual GDPs,with reference to the 1952 baseline value,were calculated by dividing the nominal GDP values of the provinces for the period of 1997–2015 by the 1952-based GDP deflator.Total carbon emissions for each province were calculated from fossil fuel combustion and cement consumption values along with associated carbon emission coefficients.These values were then divided by the value for the total provincial population recorded at the end of the year to calculate per capita carbon emission values.In our study,carbon dioxide emissions resulted from the growth of each unit of GDP were considered to reflect the carbon emission intensity.Accordingly,we applied the Super-SBM model to measure carbon emission efficiency levels.We measured the equity of regional carbon emissions based on per capita carbon emissions.Finally,we used the Markov model to calculate the club convergence index of carbon emission efficiency and fairness to assess their importance in relation to China’s carbon reduction potential,with an emphasis on carbon emissions.The dataset contains 10 tables depicting the following categories of annual provincial-level data for the period of 1997–2015:(1)annual capital stocks;(2)annual GDP values with reference to baseline statistics for 1952;(3)annual per capita carbon emissions;(4)annual carbon emission intensity;(5)carbon emission efficiency calculated using the Super-SBM model;(6)energy consumption;(7)Markov transfer probability results for per capita carbon emissions and carbon emission efficiency in China;(8)a club convergence index model of per capita emissions and the efficiency of regional carbon emission reduction for different temporal durations;(9)difference test of regional solidification degree based on the results of regional per capita carbon emissions and carbon emission efficiency;and(10)estimation results for the carbon emission reduction potentials of provinces in China based on levels of coordination of per capita and efficiency.The dataset was archived in one data file in.xlsx format,with the data size of 134 KB.The research analysis related to the dataset was published in the Journal of Natural Resources(Vol.34,No.1,2019).
作者
周迪
华诗润
Zhou,D.;Hua,S.R.(Institute of Studies for the Great Bay Area,Guangdong University of Foreign Studies,Guangzhou 510006,China;School of Economics and Trade,Guangdong University of Foreign Studies,Guangzhou 510006,China)
出处
《全球变化数据学报(中英文)》
CSCD
2019年第4期356-363,463-470,共16页
Journal of Global Change Data & Discovery
基金
广东省自然科学基金(2018A030310044).
关键词
碳减排潜力
人均碳排放
碳排放效率
中国
自然资源学报
carbon reduction potential
per capita carbon emissions
carbon emission efficiency
China
Journal of Natural Resources