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Identifying major influencing factors of CO2 emissions in China: Regional disparities analysis based on STIRPAT model from 1996 to 2015

Author:
Zhang, Sicong, Zhao, Tao
Source:
Atmospheric environment 2019 v.207 pp. 136-147
ISSN:
1352-2310
Subject:
atmospheric chemistry, carbon, carbon dioxide, cluster analysis, concrete, energy, factor analysis, greenhouse gas emissions, industry, models, regression analysis, research and development, urbanization, China
Abstract:
At present, there were countless documents and periodicals which have been paying more attention to the impact factors of carbon emissions at different levels. Nevertheless, in previous studies, regional classification methods are always based on geographical location or single factor which lack of comprehensive indicators for measurement. In this paper, 30 provinces are divided into three areas (advantageous area, potential area and backward area) from 1996 to 2015 by factor analysis and cluster analysis according to the different social development which is measured by urbanization, economy, energy utilization, industry and technology. An extented STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model containing with panel regression models are utilized to evaluate the influence of factors on CO2 emissions in China at national and diverse regional levels. The results indicate that the R&D investment and energy cleanliness play important roles in reducing CO2 emissions at advantageous area. Besides, the impact of demographic factor in potential area is higher than the other two areas. Meanwhile, improving the tertiary industry level is more essential in backward area than others. On the whole, the effect of economic growth has a greatest positive influence among three regions. Nevertheless, there exists EKC curve for three regions which shows a downward trend of CO2 emissions with increasing GDP per capita in the future. Finally, the concrete solution depends, of course, on the circumstances in three differentiated regions.
Agid:
6352348