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Potentialities Dataset of Carbon Emission Reduction based on per Capita and Efficiency in Provincial Level of China


ZHOU Di1HUA Shirun2
1Institute of Studies for the Great Bay Area,Guangdong University of Foreign Studies,Guangzhou 510006,China2School of Economics and Trade,Guangdong University of Foreign Studies,Guangzhou 510006,China

DOI:10.3974/geodb.2019.05.15.V1

Published:Nov. 2019

Visitors:160       Data Files Downloaded:19      
Data Downloaded:2.50 MB      Citations:

Key Words:

carbon reduction potential,per capita,efficiency,China,Journal of Natural Resources

Abstract:

Taking the carbon emissions per capita and efficiency to calculate the potentialities of regional carbon emission reduction is positive significance for the green and low-carbon economy. The potentialities dataset of carbon emission reduction based on per capita and efficiency in provincial level of China was developed based on the 29 provinces data from the China Statistical Yearbook, China Energy Statistical Yearbook, and China Stock Market & Accounting Research Databases from 1997 to 2015 (due to incomplete data, Hainan, Tibet, Hong Kong, Macao and Taiwan were not counted). According to the investment implied deflator of each province, the fixed capital formation amount over the years is uniformly converted into the value of the constant price in 1952, and then based on the set depreciation rate and the base period capital stock, the perpetual inventory method is used to estimate the annual capital stock to obtain the capital stock data; dividing the nominal GDP of the provinces from 1997-2015 by the 1952-based GDP deflator yields real GDP based on 1952; according to fossil fuel combustion and cement Consumption and the corresponding carbon emission coefficient are converted into total carbon emissions in each province, and then divided by the total population at the end of the year to calculate per capita carbon emissions data; using carbon dioxide emissions from the growth of each unit of GDP to characterize carbon Emission intensity; we measure the carbon reduction efficiency by the Super-SBM model, and measure the equity of regional carbon emissions by per capita carbon emissions. Then we calculate the carbon club convergence index of efficiency and fairness based on Markov model frame so as to analyze the importance of carbon reduction potential in China and the emphasis in carbon emissions. The dataset is consisted of 10 tables , they are covering the yearly provincial level data from 1997 to 2015 as following: (1) yearly capital stock data; (2) yearly GDP data according to the 1952 statistical specification;(3) yearly per capita carbon emissions data;(4) yearly carbon emissions intensity data;(5) carbon reduction efficiency data calculated by Super-SBM model;(6) energy consumption data;(7) the Markov Transfer Probability result of carbon emission per capita and efficiency in China;(8) Club convergence index model of pre capita and efficiency of regional carbon emission reduction under different durations; (9) curing degree difference test of per capita and efficiency of regional carbon emission; (10) estimation of carbon emission reduction potential in provinces of China based on the perspective of coordination of per capita and efficiency. The dataset is archived in one data file (.xlsx) with data size of 134 KB. The analysis paper based on this dataset was published in the Journal of Natural Resources, Vol.34, No.1, 2019.

Foundation Item:

Project of National Statistical Science Research (2017LY55); Guangdong Province (2018A030310044, 2015A070703019, 2016A070705058)

Data Citation:

ZHOU Di,HUA Shirun.Potentialities Dataset of Carbon Emission Reduction based on per Capita and Efficiency in Provincial Level of China[DB/OL].Global Change Research Data Publishing & Repository,2019.DOI:10.3974/geodb.2019.05.15.V1.

Data Product:

ID Data Name Data Size Operation
1 C_EmissionReduction_ProvChina.xlsx 134.64KB DownLoad
Co-Sponsors

Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences

The Geographical Society of China

Parteners

Committee on Data for Science and Technology (CODATA) Task Group on Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries (PASTD)

Jomo Kenyatta University of Agriculture and Technology

Digital Linchao GeoMuseum