The increasing concentration of atmospheric CO2 is one of the major causes of global warming. Accurate estimation of anthropogenic carbon emissions is significant for the government to monitor CO2 emissions timely and formulate emission reduction policies. To explore the application potential of interannual carbon emission distribution estimated by remotely-sensed data in monitoring carbon-related indicators of SDGs, this study constructed 0.2° grid-scale and municipal-scale anthropogenic CO2 emission models in mainland China and calculated carbon intensity and total CO2 emissions from 2015 to 2020. SDG indicator 9.4.1 and 13.2.2 were used as model indicators to evaluate the achievement of cities in each province. The experimental results show that all cities in Shanxi, Jiangsu, Zhejiang, and Guizhou Province, as well as Beijing, Chongqing, and Shanghai City, have reached the indicator 9.4.1. For the indicator 13.2.2, 15.6% of the cities have successfully controlled the growth of total carbon emissions, among which the Yangtze River Delta controlled well while that in the western region were slowly decreasing. Other cities still have a certain distance to reach the indicator 9.4.1 and 13.2.2. Using remote sensing data to quantify anthropogenic CO2 emissions at different scales can assist local governments in monitoring key energy-using units according to the emission distribution results and can also effectively solve the problems of lagging, absent and opacity of carbon emission statistics. It can provide indirect evidences for assessing local SDG indicators and technical support for relevant institutions to make decisions based on local conditions.