Spatiotemporal evolution of the Co-reduction of carbon emissions and air pollutants and the drivers of carbon mitigation: Evidence from a city-sector-industry perspective in China.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a comprehensive spatiotemporal analysis framework and empirical results on co-reduction of carbon and air pollutants across sectors and cities in China.

🏢実務担当者:Offers insights for corporate sustainability teams on sector-specific co-reduction dynamics, helpful for setting emission reduction targets aligned with local air quality goals.

🏛政策担当者:Highlights the importance of coordinated sectoral policies and spatial targeting for maximizing co-benefits of carbon and air pollution reduction.

Existing studies have primarily focused on the co-reduction of carbon dioxide and air pollutants (CDAP) at the provincial level, in key regions, or within single sectors, while systematic analyses at the city scale, across multiple sectors, and at the disaggregated industry level remain limited. Based on all-sector data and data for four major sectors (power generation, industry, transportation, and residential use) at the city scale, together with data for 11 disaggregated industries at the provincial scale, this study applies the co-control effects coordinate system (CCECS) method and the coupling coordination degree (CCD) model to measure the level of co-reduction between carbon dioxide and major air pollutants (SO2, NOx, PM2.5 and CO). By integrating ArcGIS-based spatial analysis, LMDI decomposition, and econometric regression models, this study reveals the spatiotemporal evolution characteristics of co-reduction and the drivers of carbon mitigation. The results show that: (1) during the period 2006-2020, the overall level of co-reduction of CDAP in China increased significantly, with the spatial pattern exhibiting a diffusion trend from eastern to western regions and a gradual narrowing of inter-city disparities in coordination; (2) the CCD of the co-reduction of CDAP in the industrial, power generation, transportation, and residential sectors respectively exhibits inverted U-shaped, N-shaped, Z-shaped, and oscillatory variation patterns; and (3) the energy structure intensity effect and the energy consumption intensity effect are the primary driving factors of carbon mitigation, while the co-reduction effects of CDAP display significant heterogeneity across different sectors and industries.

• semanticscholar https://doi.org/10.1016/j.jenvman.2026.129891first seen 2026-07-25 06:04:23