High-Resolution simulation of CO2 Concentrations Over Jiangsu Province in China Based on WRF-Chem-VPRM and Six Emission Inventories

Accurate simulation of regional carbon dioxide (CO₂) concentrations is essential for understanding carbon flux dynamics, refining emission inventories, and supporting climate mitigation policies. Using the WRF-Chem-VPRM model at 3 km resolution, this study simulated CO₂ concentrations in Jiangsu Province, China, with hourly outputs. Model verification against nine ground-based CO₂ monitoring stations confirmed its reliability.
Before integrating emission inventories into the model, we conducted a comprehensive analysis of six widely used emission inventories (ODIAC, EDGAR, MEIC, CHRED, GID, GRACED), revealing significant discrepancies in total emissions and spatial patterns in China. Provincial-scale annual carbon emissions discrepancies reached 52%, whereas urban-scale discrepancies averaged 137%, attributed to differences in emission proxies and spatial resolution. 
Sensitivity experiments for July and December 2022, representing summer and winter, assessed the impacts of spatial, temporal, and vertical allocation processes. Vertical allocation coefficients emerged as a critical factor, particularly under stable nighttime boundary layer conditions, where deviations exceeded 50 ppm. Their influence equaled or even surpassed that of emission inventory selection, underscoring the necessity of precise vertical parameterization.
Spatial allocation discrepancies primarily affected urban concentrations, where dense and diverse sources contributed to higher variability. Winter simulations exhibited increased uncertainties due to heightened heating emissions and limited vertical mixing.
These findings highlight the importance of refining vertical and spatial allocation in emission inventories to improve regional CO₂ modeling. The study provides insights for advancing carbon inversion methodologies and supporting robust Monitoring, Reporting, and Verification (MRV) systems in urbanizing regions.
Emission inventories analyzed include:
•    ODIAC: Open-source Data Inventory for Anthropogenic CO₂,
•    EDGAR: The Emissions Database for Global Atmospheric Research,
•    MEIC: The Multi-resolution Emission Inventory for China,
•    CHRED: China High-resolution Emission Database,
•    GID: Global Infrastructure emissions Detector,
•    GRACED: Global Gridded Daily CO₂ Emissions Dataset.