关键词: 粤港澳大湾区、碳排放、莫兰指数、STIRPAT、情景预测

Abstract:

It is of great significance to scientifically identify the factors influencing the growth of carbon emissions and accurately predict the peak of carbon emissions and the time to reach the peak of carbon emissions, so that China can realize the goal of “double carbon” as scheduled. This paper selects Guangdong, Hong Kong and Macao Greater Bay Area as the research object and analyzes it based on the NPP-VIIRS nighttime lighting data from 2010 to 2022. Firstly, it estimates the carbon emissions of the 11 cities in Guangdong, Hong Kong and Macao Greater Bay Area, and adopts the Moran index to characterize the spatial and temporal heterogeneity of the carbon emissions among the cities; secondly, it constructs the extended STIRPAT model based on the regional characteristics and thoroughly analyzes the carbon emissions and their influencing factors; finally, it constructs the extended STIRPAT model based on the regional characteristics. In-depth analysis of carbon emissions and its influencing factors; finally, and set three scenarios to predict the changes of carbon emissions from 2022 to 2050. The results show that: (1) the overall carbon emissions in the Guangdong-Hong Kong-Macao Greater Bay Area show a fluctuating upward trend; (2) carbon emissions show significant spatial clustering characteristics; (3) population size, urbanization and R&D investment are positive influences on carbon emissions in the region; GDP per capita, industrial structure and the level of openness to the outside world negatively influence carbon emissions; (4) in the baseline scenario and the fast-growth scenario, carbon emissions cannot be effectively controlled, while in the carbon peak scenario, carbon emissions are not effectively controlled, while in the carbon peak scenario, carbon emissions are not effectively controlled. (4) Carbon emissions cannot be effectively controlled under the baseline and rapid growth scenarios, while carbon emissions can be effectively controlled under the peak carbon scenario. This paper is of great significance in promoting the low-carbon transition of the Guangdong-Hong Kong-Macao Greater Bay Area and realizing the goals of carbon peaking and carbon neutrality.

Key words: Guangdong, Hong Kong and Macao Greater Bay Area, carbon emission, Moran Index, STIRPAT, scenario prediction