Preprints
https://doi.org/10.5194/egusphere-2026-4773
https://doi.org/10.5194/egusphere-2026-4773
08 Sep 2026
 | 08 Sep 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Improving bottom-up ammonia emission estimations in Guangdong combining ammonia measurements from a ground-based network and FY-4B satellite and GCHP model

Lingze Meng, Ni Lu, Yixin Guo, Ziru Lan, Zhao-Cheng Zeng, Zichong Chen, Yuanhong Zhao, Zhuangmin Zhong, Tao Zhang, Duohong Chen, Xuejun Liu, Lin Zhang, and Junyu Zheng

Abstract. Accurate ammonia (NH3) emission inventories are critical for PM2.5 mitigation, yet bottom-up estimates remain uncertain, particularly for sector-resolved estimates in humid subtropical regions such as Guangdong, where urban-industrial emissions in the Pearl River Delta (PRD) coexist with dispersed agricultural sources in surrounding non-PRD areas. Here we integrate a ground-based NH3 network, Fengyun-4B (FY-4B) geostationary NH3 retrievals, a localized 3 km × 3 km prior inventory, and stretched-grid GEOS-Chem High Performance (GCHP) simulations at 0.2° × 0.2° resolution to inversely constrain monthly agricultural and non-agricultural NH3 emissions in the PRD and non-PRD Guangdong in 2023. The posterior simulation improved agreement with observations, reducing NRMSE from 55.3 % to 48.4 % and changing NMB from −9.0 % to 4.6 %, with further support from independent NH3, NH4+, and deposition measurements. Provincial anthropogenic NH3 emissions decreased from 477.6 to 441.5 kt yr−1: agricultural emissions declined from 437.2 to 362.5 kt yr−1, mainly through warm-season reductions in non-PRD areas, whereas non-agricultural emissions increased from 40.4 to 79.0 kt yr−1, especially during the cool season. Hypothetically removing agricultural (non-agricultural) NH3 emissions in Guangdong provided provincial PM2.5 reductions of 3.7 ± 1.5 (0.7 ± 0.4) μg m−3 and avoided premature deaths of 3251 (1064), highlighting the need to combine dispersed agricultural source controls and targeted non-agricultural source controls over populated PRD.

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Lingze Meng, Ni Lu, Yixin Guo, Ziru Lan, Zhao-Cheng Zeng, Zichong Chen, Yuanhong Zhao, Zhuangmin Zhong, Tao Zhang, Duohong Chen, Xuejun Liu, Lin Zhang, and Junyu Zheng

Status: open (until 20 Oct 2026)

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Lingze Meng, Ni Lu, Yixin Guo, Ziru Lan, Zhao-Cheng Zeng, Zichong Chen, Yuanhong Zhao, Zhuangmin Zhong, Tao Zhang, Duohong Chen, Xuejun Liu, Lin Zhang, and Junyu Zheng
Lingze Meng, Ni Lu, Yixin Guo, Ziru Lan, Zhao-Cheng Zeng, Zichong Chen, Yuanhong Zhao, Zhuangmin Zhong, Tao Zhang, Duohong Chen, Xuejun Liu, Lin Zhang, and Junyu Zheng
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Latest update: 08 Sep 2026
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Short summary
Ammonia contributes to formation of health-damaging PM2.5 air pollution, but its emission estimations involve substantial uncertainties. Combining ground and satellite observations, a local inventory, and atmospheric modeling, we improved ammonia emissions in Guangdong, China. We found that current inventories overestimated agricultural emissions but underestimated non-agricultural emissions, especially in urban areas during the cool season, informing effective PM2.5 mitigation policy design.
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