Acta Geographica Sinica ›› 2021, Vol. 76 ›› Issue (12): 3103-3118.doi: 10.11821/dlxb202112016

• Regional Development and Carbon Emissions • Previous Articles     Next Articles

The spatiotemporal pattern evolution and influencing factors of CO2 emissions at the county level of China

WANG Shaojian(), XIE Zihan, WANG Zehong   

  1. Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
  • Received:2021-03-15 Revised:2021-08-17 Online:2021-12-25 Published:2022-02-25
  • Supported by:
    Ministry of Education Research in the Humanities and Social Sciences Planning Fund(21YJAZH087)

Abstract:

County is the pivotal platform and region unit to realize the new-type urbanization. The study of county-level CO2 emissions is of great significance to improve China's urbanization strategy, accelerate the achievement of ecological civilization and low-carbon transformation. Based on the data of China's county-level CO2 emissions from 2000 to 2017, this paper analyzed the overall tendency, regional differences, spatiotemporal pattern and agglomeration characteristics of per capita CO2 emissions. Meanwhile, under the STIRPAT model and EKC hypothesis, this study employed the panel quantile regressions to explain the dynamic impact of socio-economic development on per capita CO2 emissions. The main conclusions show that: (1) China's county-level CO2 emissions show an increasing trend of rapid growth followed by slow growth. The regional disparity of per capita CO2 emissions is distinct and shows a more uneven trend. (2) On the whole, China's county-level CO2 emissions present a spatial pattern of "high in the north and low in the south". The per capita CO2 emissions level in economically developed areas is much higher than that in other areas, thus brings about an obvious spatial polarization effect. (3) There is a significant positive spatial correlation of per capita CO2 emissions within counties. The number of counties with High-High concentration gradually increases and the distribution center gradually moves to Northwest China, while the number of Low-Low concentration counties decreases continuously and they were mainly distributed in the central and southern regions. The agglomeration type of county-level per capita CO2 emissions presents a spatial locking effect. (4) Population density and government expenditure have an inhibitory effect on county-level per capita CO2 emissions, while the scale of secondary industry output value and carbon emission intensity have significant promotive influence. And there is an inverted "N-shaped" relationship between economic development and per capita CO2 emissions in the counties with low- and middle-level emissions. The adjustment of socio-economic development structure plays a critical role in achieving China's total CO2 emission reduction target. Therefore, the policy makers of emission reduction strategy should consider the regional disparity to realize the development and transformation of backward counties. And the key urban agglomerations should play a leading role in carbon emission reduction simultaneously. In addition, improving energy use efficiency through technological innovation should be the key way to the reduction of carbon emissions in China's counties at the present stage.

Key words: per capita CO2 emissions at county level, spatiotemporal pattern, regional disparity, influencing factor, panel quantile regression