How does spatiotemporal variations and impact factors in CO_2 emissions differ across cities in China? Investigation on grid scale and geographic detection method

摘要

Timely and accurate assessments of the spatiotemporal variations and impact factors of CO2 emissions are crucial for developing effective and rational CO2 reduction policies. However, studies are still lacking that consider spatiotemporal variations in CO2 emissions at the grid scale and their impact factors in cities with different types of such emissions. This study proposes an improved estimation model to map the CO2 emissions of mainland China in 2000, 2005, 2010, 2015 and 2018 based on nighttime light data, land use data, and population data. The resulting maps of estimated CO2 emissions in different regions are examined and compared with Landsat data and with the results of linear regression, quadratic polynomial carbon emission models, carbon emission models based on land use and carbon emission models based on population. This comparison shows that the model proposed in this study is more accurate than ordinary models, such as the linear regression and quadratic polynomial models. Using the results of this model, 356 mainland cities in China are divided into serviceoriented, industrial, agricultural and comprehensive cities, and the impact factors of each city are analyzed. The results show that China's CO2 emissions are still concentrated in its smaller regions, but the intensity of this concentration is gradually decreasing. The spatial distribution characteristics of the carbon emissions of cities have an obvious circle-layer effect; however, the CO2 emissions of large cities present a "W"-shaped distribution, while the CO2 emissions of small cities present a power function curve. Although GDP is the main factor affecting the CO2 emissions in various cities, the factors affecting different types of cities based on their CO2 emissions vary greatly. These results could improve the current understanding of the patterns of variation and influencing factors of CO2 emissions in different cities and provide a scientific basis for formulating CO2 emission reduction policies in accordance with local conditions.