High-resolution anthropogenic emission inventory for China (2015–2024): Spatiotemporal changes and environmental application

Abstract

Anthropogenic emission inventories serve not only as key inputs for chemical transport models but also as essential tools for evaluating the effectiveness of emission control measures. Here, this study employed the emission inventory from Chinese Unified Atmospheric Chemistry Environment model (CCES) to analyze the spatiotemporal characteristics of China's anthropogenic emissions from 2015 to 2024, and to evaluate its performance in simulating aerosols and their gaseous precursors. Furthermore, this study compared CCES with the Multi-resolution Emission Inventory for China (MEIC) and the Emissions Database for Global Atmospheric Research (EDGAR) to explore the emission discrepancies. National total anthropogenic emissions declined markedly over the decade: sulfur dioxide (SO₂) dropped by 60.8 %, while emissions of nitrogen oxides (NO_x), particulate matter with an aerodynamic diameter ≤10 μm (PM₁₀) and ≤2.5 μm (PM_2.5), carbon monoxide (CO) and ammonia (NH₃) decreased by 19.9–42.6 %. The three inventories exhibited decreases during 2015–2020, but the reduction rates for SO₂, PM_2.5 and PM₁₀ slowed after 2018. Although the inventories diverged substantially in absolute magnitude, they displayed nearly identical seasonal patterns. Relative to MEIC, EDGAR reported higher industrial SO₂ emissions, whereas CCES yielded higher traffic-related NO_x emissions. CCES-driven simulations reproduced spatiotemporal variability of SO₂, nitrogen dioxide (NO₂) and PM_2.5 concentrations, albeit with negative biases for SO₂ and PM_2.5 and a positive bias for NO₂ at most monitoring sites. Despite these remaining uncertainties, CCES can capture the dominant spatiotemporal patterns of China's emissions and thus provide valuable insights into their variability.