Spatiotemporal heterogeneity and varying associations of environmental pollution and carbon reduction synergy in a typical mountainous megacity: a county-level analysis from Chongqing, China

Understanding the spatiotemporal heterogeneity of the environmental pollution reduction and carbon reduction (EPRCR) synergy at the district and county level is essential for targeted urban policy. This study investigates the spatiotemporal evolution and influencing factors of EPRCR at the district and county levels in Chongqing, China, from 2017 to 2022. The analytical framework integrates Centroid-Standard Deviational Ellipse analysis, a coupling coordination degree (CCD) model, kernel density estimation, and a geographically and temporally weighted regression (GTWR) model. The results show that: (1) Major air pollutants (PM2.5, PM10, NO2) declined by about 30% but remained above WHO 2021 Air Quality Guidelines (AQGs). (2) Carbon emissions showed strengthening spatial agglomeration, with the centroid oscillating along a southwest-northeast axis; no significant diffusion of high‑carbon industries was detected. (3) The CCD of EPRCR increased overall from 0.54 to 0.61, with cold spots persistently located in the main urban industrial belt while hot spots shifted to lower-density peripheral districts. (4) Per capita GDP and technological innovation showed the strongest positive associations with EPRCR synergy, while industrial energy consumption showed the strongest negative association. These findings reveal spatially uneven EPRCR progress, where industrial zones remain locked in a high-emission paradigm and peripheral districts show positive synergy. Based on these results, this study proposes a zoning, classification, and time-based framework to inform targeted reduction policies for carbon and pollution in Chongqing. 1 1 EPRCR: Environmental pollution reduction and carbon reduction; CCD: Coupling coordination degree; GTWR: Geographically and temporally weighted regression; GWR: Geographical weighted regression; GDP: Gross domestic product; WHO: World Health Organization; AQGs: Air Quality Guidelines; CAQI: Comprehensive Air Quality Index; VIF: Variance inflation factor; OLSR: Ordinary Least Squares Regression.

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