Abstract

The dependence of county industry on high CO2 emission industries makes it difficult to balance the development of county economy and CO2 emission reduction. Therefore, this article attempts to study on the spatial-temporal evolution and influencing factor on land use-related CO2 emissions at region-county level to promote county economy from CO2 source to CO2 sink. 9 regions and 38 counties in Chongqing of China were thus selected as study objects. Based on land use data, land use-related CO2 emissions were estimated using direct and indirect CO2 emission models for the period 1997–2015. On this basis, the space-time patterns were revealed from two scales of region and county. And the main factors influencing CO2 emissions according to land use were revealed based on Logarithmic Mean Divisia Index (LMDI) and geographic detector analysis (GDA), respectively. The results show that: 1) at regional scale, CO2 emissions of different regions all greatly improve in which southeastern ecological protection and development area showed the largest increase. Increases in per capita CO2 emissions in two-wing (suburban) areas are higher than those in downtown and surrounding-downtown areas. 2) at regional scale, the influences of various decomposed factors on the change of CO2 emissions fluctuate. The effect of population shows an insignificant influence on CO2 emissions. Economic development greatly influences CO2 emissions. Additionally, energy consumption shows a significant inhibitory effect on CO2 emissions while energy mix exhibits significant hysteresis. 3) at county scale, heavy CO2 emissions are concentrated in core urban areas; moderate and mild emissions occur mainly in the main urban expansion area, the region around the main urban areas, and in regional hub cities; low emissions are mainly concentrated in the Wuling mountainous area in southeast Chongqing and the Three Gorges Reservoir area in northeast Chongqing. 4) at county scale, the main influences on land use-related CO2 emissions are total energy consumption, per capita GDP, and urbanization rate. Minor influences include population size, proportion of secondary and tertiary industries, and proportion of land used for construction.

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