<p>Optimizing collaborative carbon reduction, pollution abatement, green development, and sustainable growth (C-P-G-S) is essential for Chinese cities to address environmental degradation, mitigate climate change, and achieve sustainable development. However, relevant research on this integrated framework remains limited. This study constructs a comprehensive evaluation framework by integrating the Coupled coordination model, Dagum Gini coefficient, Spatial auto-correlation analysis, Optimal parameters-based geographical detector, and a CatBoost-SHAP model to assess the coupling coordination degree (CCD) of C-P-G-S and its driving factors across 274 Chinese cities from 2005 to 2020. The findings reveal that: (1) The CCD for the overall, eastern, central, and western regions showed an upward trend, with a substantial decrease in extremely incoordinated cities and a substantial increase in moderately incoordinated cities. (2) There was heterogeneity in the spatial distribution of CCD, with obvious spatial aggregation features and low-low clustering predominating. The overall spatial difference showed a decreasing and then increasing trend, and the intersection and overlap between different regions were the core source of the differences in the spatial distribution of CCD. (3) The explanatory power of the internal drivers was better than that of the external drivers in different regions, with carbon reduction being the dominant factor influencing the spatial distribution of CCD and green development having the most pronounced effect on changes in CCD values. The two-factor interaction significantly improved the explanatory power, especially for the external drivers. These findings can inform the design of differentiated policies for C-P-G-S and help reduce regional disparities in achieving sustainable development.</p>