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The dependence of county industry on high CO 2 emission industries makes it difficult to balance the development of county economy and CO 2 emission reduction. Therefore, this article attempts to study on the spatial-temporal evolution and influencing factor on land use-related CO 2 emissions at region-county level to promote county economy from CO 2 source to CO 2 sink. 9 regions and 38 counties in Chongqing of China were thus selected as study objects. Based on land use data, land use-related CO 2 emissions were estimated using direct and indirect CO 2 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 CO 2 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, CO 2 emissions of different regions all greatly improve in which southeastern ecological protection and development area showed the largest increase. Increases in per capita CO 2 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 CO 2 emissions fluctuate. The effect of population shows an insignificant influence on CO 2 emissions. Economic development greatly influences CO 2 emissions. Additionally, energy consumption shows a significant inhibitory effect on CO 2 emissions while energy mix exhibits significant hysteresis. 3) at county scale, heavy CO 2 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 CO 2 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. [ABSTRACT FROM AUTHOR]