Spatiotemporal Characteristic and Driving Factors of Synergy on Carbon Dioxide Emission and Pollutants Reductions in the Guangdong–Hong Kong–Macao Greater Bay Area, China

As an economically active region, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) faces dual challenges of carbon and air pollution reduction. Existing studies predominantly focus on single pollutants or engineering pathways, lacking systematic analyses of multi-scale synergistic effects. This study investigates the spatiotemporal distributions, driving factors, and synergistic effects of CO 2 and volatile organic compounds (VOCs) at the multi-scale of urban agglomerations, cities, and industries, using global Moran’s index, standard deviational ellipse, logarithmic mean divisa index decomposition model, and Tapio decoupling model. The results show that the average annual growth rate of CO 2 (7.4%) was significantly higher than that of VOCs (4.5%) from 2000 to 2020, and the industrial sector contributed more than 70% of CO 2 and VOC emissions, with the center of gravity of emissions migrating to Dongguan. Industrial energy intensity improvement emerged as the primary mitigation driver, with Guangzhou and Shenzhen demonstrating the highest contribution rates. Additionally, CO 2 and VOC reduction show two-way positive synergy, and the path of “energy intensity enhancement–carbon and pollution reduction” in the industrial sector is effective. Notably, the number of strong decouplings of the economy from CO 2 (11 times) is much higher than the number of strong decouplings of VOCs (3 times), suggesting that the synergy between VOC management and economic transformation needs to be strengthened. This study provides scientific foundations for phased co-reduction targets and energy–industrial structure optimization, proposing regional joint prevention and control policy frameworks.