Estimation of Ammonia Emissions over China Using IASI Satellite-Derived Surface Observations

Abstract

An accurate ammonia (NH3) emission inventory is crucial for policymakers developing air pollution mitigation strategies. Both satellite observations and bottom-up estimates identify significant NH3 emission hotspots in China. However, bottom-up NH3 emission inventories are highly uncertain due to the lack of localized emission factors, while large and uncertain errors in IASI satellite NH3 columns have hindered their direct application in top-down emission inversion methods. In this study, we perform a top-down optimization of monthly NH3 emissions over China using IASI-derived surface NH3 concentrations with well-evaluated error estimates, combined with the CAMx model at a 36 km resolution. Our posterior NH3 emissions for 2020 (12.3 [10.9-13.6] Tg N yr-1) are significantly higher than prior estimates from the MEIC inventory (7.6 Tg N yr-1), which primarily underestimates emissions during the warm months in hotspot areas (e.g., NCP and MLYR). We employ multiple approaches to comprehensively evaluate our inversion results. Our study highlights that error estimates for low-value observations are a particularly critical factor in the inversion setup, significantly influencing the reliability of emission optimization.