Spatio-Temporal Dynamics and Driving Forces of Multi-Scale CO2 Emissions by Integrating DMSP-OLS and NPP-VIIRS Data: A Case Study in Beijing-Tianjin-Hebei, China

The emission of greenhouse gases, especially CO2, is the main factor causing global warming. Due to incomplete statistical data on energy consumption at and below urban scale Beijing-Tianjin-Hebei (BTH), in this study, Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) were combined, a neural network model weighted average method based DN (Digital Number) value used obtain CO2 emissions municipal county scales with resolution 1 km × from 2000–2019. Next, spatial-temporal analysis spatial econometric study different BTH. This also solved problem that STIRPAT cannot be carried out due insufficient data. results show BTH present distribution pattern “East greater than West”, trend first rising then slowing down. Moreover, rapid growth areas are mainly located Chengde Tianjin. degree regional aggregation decreased year by Population, affluence technology factors positively correlated Tianjin Hebei. For Beijing, addition foreign investment, such as urbanization rate, intensity, construction transportation all contributed increase emissions. Among them, population reason for Finally, research specific situation cities, corresponding policies measures proposed future low-carbon development cities.