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Assessing atmospheric CO2 concentrations and contributions from biogenic and anthropogenic sources in the Pearl River Delta region.

Authors :
Mai, B.
Diao, Y.
Yang, H.
Deng, T.
Zou, Y.
Wang, Y.
Lan, W.
Liu, X.
Deng, X.
Source :
Urban Climate; Mar2024, Vol. 54, pN.PAG-N.PAG, 1p
Publication Year :
2024

Abstract

The dynamics of atmospheric CO 2 concentrations in urban agglomerations have been a topic of interest in research on global climate change, yet there remain significant uncertainties within the estimates of CO 2 contributions from biogenic and anthropogenic sources. In this study, the Weather Research and Forecasting model coupled with the Vegetation Photosynthetic Respiration Model (WRF-VPRM) was implemented with local VPRM parameters to simulate the atmospheric CO 2 concentration in the Pearl River Delta (PRD) region of China during 2019–2021. The results show that (1) WRF-VPRM accurately simulates the distribution of the atmospheric CO 2 concentration in the PRD region from 36-km grids to 4-km grids, and the CO 2 concentrations within the simulated grids demonstrated good consistency. (2) Anthropogenic emissions were the main factor, accounting for 20.59% of the total CO 2 concentration in the region; by contrast, the contribution from vegetation emissions was only 1.57%. (3) High CO 2 concentration centers (CO 2 exceed 436 ppm) occur throughout the year in rural areas of the boundary between Yunfu and Zhaoqing, northeast Qingyuan, and southern Huizhou. CO 2 concentrations were below 426 ppm in the region around the Pearl River Estuary in summer and fall. • The WRF-VPRM can accurately capture atmospheric CO 2 in the PRD with an average bias of −1.27 ppm at a 4-km resolution. • Anthropogenic emissions account for 20.59% of the total CO 2 concentration, while the biogenic CO 2 contributions are small. • High CO 2 concentration centers occur in rural areas in the PRD. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22120955
Volume :
54
Database :
Supplemental Index
Journal :
Urban Climate
Publication Type :
Academic Journal
Accession number :
176224852
Full Text :
https://doi.org/10.1016/j.uclim.2024.101864