Evaluation of the synergistic effect between air pollution control and carbon mitigation in China

  • Man Guo

Student thesis: PhD Thesis

Abstract

Achieving synergistic governance between air pollution control and carbon mitigation is critical for China's sustainable development, yet effective integrated governance strategies are still evolving. This study investigates this synergy using a framework that integrates two complementary perspectives: emission-based and concentration-based.

From the emission-based perspective, the analysis provides two distinct viewpoints. Firstly, an assessment of the coupling coordination degree reveals that China's overall synergistic performance has improved, exhibiting a clear spatial gradient, higher in the east and lower in the west, driven by factors like economic development and energy structure. Secondly, a pollutant-specific analysis using emission ratios offers a targeted view, showing that the potential for co-reducing SO2 with CO2 is significant in western and northern regions, while NOx stands out as the key species for synergistic reduction across the country, especially in the Chengyu Plain.

Complementarily, the concentration-based analysis, applied to the Yangtze River Delta Urban Agglomeration (YRDUA), evaluates the integrated environmental outcomes. This analysis reveals fluctuating synergistic governance performance at the city level, demonstrating that synergy from the perspective of concentration is strongly influenced by geographical locations, local industrial emissions, and meteorological conditions like wind speed, with drivers exhibiting nonlinear and spatial non-stationarity impacts.

Employing a life-cycle framework, this PhD project evaluates both policy outputs (emissions) and environmental outcomes (concentrations). By combining these two perspectives, it highlights the necessity of developing locally tailored strategies that address specific regional contexts and spatially varying drivers, which are essential to advance China’s path towards sustainability.
Date of Award15 Jan 2026
Original languageEnglish
Awarding Institution
  • University of Nottingham
SupervisorNicholas Hamm (Supervisor), Baozhang Chen (Supervisor) & Simon Gosling (Supervisor)

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