Effects Evaluation of the Impact on Carbon Emission Intensity by Consumption of Main Types of Energy in China Based on LSDV Estimation
[1]Wei Ran.Effects Evaluation of the Impact on Carbon Emission Intensity by Consumption of Main Types of Energy in China Based on LSDV Estimation[J].Journal of Zhengzhou University (Engineering Science),2019,40(02):90-94.[doi:10.13705/j.issn.1671-6833.2019.02.010]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
40
Number of periods:
2019 02
Page number:
90-94
Column:
Public date:
2019-03-19
- Title:
- Effects Evaluation of the Impact on Carbon Emission Intensity by Consumption of Main Types of Energy in China Based on LSDV Estimation
- CLC:
- -
- DOI:
- 10.13705/j.issn.1671-6833.2019.02.010
- Abstract:
- Impact effects on carbon emissions intensity by population, per capita GDP, and main types of energy in China were evaluated with the fixed effect model based on LSDV estimation with reasons of the results of Likelihood Ratio Test and Hausman Test. The traditional model of STIRPAT was improved by adding Carbon Emission Intensity and Energy Consumption Variables, which included consumptions of coal, coke, crude oil, gasoline, kerosene, diesel oil, fuel oil, and natural gas, except population and per capita GDP. The results show that consumptions of different types of energy have different impacts on carbon emissions intensity from 2004 to 2016 in China. Five variables of energy consumption, which were corresponding to coal, coke, gasoline, diesel oil, and natural gas, had played positive effects on carbon emission intensity from the data of China Statistical Yearbook and China Energy Statistical Yearbook of 200 5 to 201 7. Other variables of crude oil consumption, fuel oil consumption, and kerosene consumption took opposite impact on carbon emission intensity. Moreover, change of population had the most significant favorable influence on carbon emission intensity in all studied variables. Unfortunately, per capita GDP and coal consumption contributed to the increasing of carbon emission intensity in China in the studied period.
- References:
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Last Update:
2019-03-24