{'fraction_non_alphanumeric': 0.022530329289428077, 'fraction_numerical': 0.008087810514153668, 'mean_word_length': 5.845849802371541, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Constraining U.S. ammonia emissions using TES remote sensing observations and the GEOS‐Chem adjoint model

Ammonia (NH3) has significant impacts on biodiversity, eutrophication, and acidification. Widespread uncertainty in the magnitude and seasonality of NH3 emissions hinders efforts to address these issues. In this work, we constrain U.S. NH3 sources using observations from the TES satellite instrument with the GEOS‐Chem model and its adjoint. The inversion framework is first validated using simulated observations. We then assimilate TES observations for April, July, and October of 2006 through 2009. The adjoint‐based inversion allows emissions to be adjusted heterogeneously; they are found to increase in California throughout the year, increase in different regions of the West depending upon season, and exhibit smaller increases and occasional decreases in the Eastern U.S. Evaluations of the inversion using independent surface measurements show reduced model underestimates of surface NH3 and wet deposited NHx in April and October; however, the constrained simulation in July leads to overestimates of these quantities, while TES observations are still under predicted. Modeled sulfate and nitrate aerosols concentrations do not change significantly, and persistent nitrate overestimation is noted, consistent with previous studies. Overall, while satellite‐based constraints on NH3 emissions improve model simulations in several aspects, additional assessment at higher horizontal resolution of spatial sampling bias, nitric acid formation, and diurnal variability and bi‐directionality of NH3 sources may be necessary to enhance year‐round model performance across the full range of gas and aerosol evaluations.