Impacts of different biomass burning emission inventories: Simulations of atmospheric CO2 concentrations based on GEOS-Chem

Mengqian Su; Yusheng Shi; Yongliang Yang; Wenyue Guo

doi:10.1016/j.scitotenv.2023.162825

Impacts of different biomass burning emission inventories: Simulations of atmospheric CO₂ concentrations based on GEOS-Chem

Sci Total Environ. 2023 Jun 10:876:162825. doi: 10.1016/j.scitotenv.2023.162825. Epub 2023 Mar 15.

Authors

Mengqian Su¹, Yusheng Shi², Yongliang Yang¹, Wenyue Guo¹

Affiliations

¹ State Environmental Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 101408, China.
² State Environmental Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China. Electronic address: shiys@aircas.ac.cn.

PMID: 36924969
DOI: 10.1016/j.scitotenv.2023.162825

Abstract

Biomass burning has substantial spatiotemporal variabilities. It contributes significantly to the dynamics of global CO₂ distributions and variances. Quantifying the impacts of biomass burning emissions on atmospheric CO₂ concentrations is essential for global and regional carbon cycles and budgets. In this study, we performed several numerical experiments by switching and replacing inventories to estimate the impacts of four biomass burning emission inventories on atmospheric CO₂ concentration simulations in 2006-2010 based on the global chemical transport model, GEOS-Chem. The results highlighted similarities and differences in the annual and seasonal variability of biomass burning emissions and simulated CO₂ concentrations at global and regional scales. Based on four different biomass burning emission inventories, we found that biomass burning emissions could lead to a global CO₂ concentration increase of 2.4 ppm annually. Africa contributed the largest global CO₂ emissions among all continental regions, where the maximum CO₂ concentration increase could reach 7.9-13.0 ppm in summer. Model evaluation results showed that simulation using the Quick Fire Emissions Database (QFED) as the model priori biomass burning emission inventory had the best performance compared with the satellite and surface observations. The sensitivity of simulated CO₂ concentrations to the uncertainties in different biomass burning emission inventories was high in southern South America and most areas of the Eurasian continent, and low in central Africa and Southeast Asia. This study furthers our understanding of the critical role of biomass burning in atmospheric CO₂ and indicates an urgent need to improve the accuracy of biomass burning emission estimates in CO₂ simulations.

Keywords: Biomass burning emission; CO(2) concentrations; Inventory switching and replacing; Model simulations; Spatiotemporal characteristics.