Satellite observations play a crucial role in quantifying ammonia sources by capturing large-scale variations of atmospheric NH3 concentrations. As the world's first geostationary hyperspectral infrared sounder, the Geostationary Interferometric Infrared Sounder (GIIRS) on board China's FengYun-4 satellite series provides a unique opportunity to monitor the diurnal cycle of NH3. Using NH3 retrievals from July 2022 to June 2025, this study investigates the spatio-temporal variability of NH3 columns over East Asia, with a focus on daytime variations (07:00-19:00 LT - local time) in major agricultural regions. Inter-comparison with polar-orbiting IASI and CrIS data shows that GIIRS NH3 retrievals are consistent in capturing spatial patterns and temporal dynamics. The NH3 peaks occur between March and July, with peak timing earlier in the south and later in the north, reflecting regional differences primarily driven by agricultural activities. Validation with ground-based FTIR measurements at Hefei in eastern China demonstrates the accuracy of GIIRS NH3, with a correlation coefficient of 0.77 and an RMSE of 9.67 & times;1015 moleccm-2, while reproducing daytime variations observed by FTIR. For major agricultural areas, the NH3 columns generally increase from early morning to late afternoon, reaching 1.10-1.56 times morning levels in summer and spring. Compared with GEOS-CF model simulations, the results reveal pronounced discrepancies in spatial distributions over the Sichuan Basin in southwestern China and daytime variations over northern India. These findings highlight the valuable capability of FY-4B/GIIRS in identifying and tracking daytime dynamics of NH3 sources over East Asia, offering new insights beyond current low-Earth orbit (LEO) instruments.

Although the concentrations of five basic ambient air pollutants in the Yangtze River Delta (YRD) have been reduced since the implementation of the "Air Pollution Prevention and Control Action Plan" in 2013, the ozone concentrations still increase. In order to explore the causes of ozone pollution in YRD, we use the GEOS-Chem and its adjoint model to study the sensitivities of ozone to its precursor emissions from different source regions and emission sectors during heavy ozone pollution events under typical circulation patterns. The Multi-resolution Emission Inventory for China (MEIC) of Tsinghua University and 0.25° × 0.3125° nested grids are adopted in the model. By using the T-mode principal component analysis (T-PCA), the circulation patterns of heavy ozone pollution days (observed MDA8 O3 concentrations ≥160 μg m-3) in Nanjing located in the center area of YRD from 2013 to 2019 are divided into four types, with the main features of Siberian Low, Lake Balkhash High, Northeast China Low, Yellow Sea High, and southeast wind at the surface. The adjoint results show that the contributions of emissions emitted from Jiangsu and Zhejiang are the largest to heavy ozone pollution in Nanjing. The 10 % reduction of anthropogenic NOx and NMVOCs emissions in Jiangsu, Zhejiang and Shanghai could reduce the ozone concentrations in Nanjing by up to 3.40 μg m-3 and 0.96 μg m-3, respectively. However, the reduction of local NMVOCs emissions has little effect on ozone concentrations in Nanjing, and the reduction of local NOx emissions would even increase ozone pollution. For different emissions sectors, industry emissions account for 31 %-74 % of ozone pollution in Nanjing, followed by transportation emissions (18 %-49 %). This study could provide the scientific basis for forecasting ozone pollution events and formulating accurate strategies of emission reduction.

We present a newly developed approach to characterize the sources of fine particulate matter (PM2.5)-related premature deaths in Europe using the chemical transport model GEOS-Chem and its adjoint. The contributions of emissions from each individual country, species, and sector are quantified and mapped out at km scale. In 2015, total PM2.5-related premature death is estimated to be 449,813 (257,846-722,138) in Europe, 59.0% of which were contributed by domestic anthropogenic emissions. The anthropogenic emissions of nitrogen oxides, ammonia, and organic carbon contributed most to the PM2.5-related health damages, making up 29.6%, 23.2%, and 16.8%, respectively of all domestic anthropogenic contributions. Residential, agricultural, and ground transport emissions are calculated to be the largest three sectoral sources of PM2.5-related health risks, accounting for 23.5%, 23.0%, and 19.4%, respectively, of total anthropogenic contributions within Europe. After excluding the influence of extra-regional sources, we find eastern European countries suffered from more premature deaths than their emissions caused; in contrast, the emissions from some central and western European regions contributed premature deaths exceeding three times the number of deaths that occurred locally. During 2005-2015, the first decade of PM2.5 regulation in Europe, emission controls reduced PM2.5-related health damages in nearly all European countries, resulting in 63,538 (46,092-91,082) fewer PM2.5-related premature deaths. However, our calculation suggests that efforts to reduce air pollution from key sectors in some countries can be offset by the lag in control of emissions in others. International cooperation is therefore vitally important for tackling air pollution and reducing corresponding detrimental effects on public health.

We aim to reduce uncertainties in CH2O and other volatile organic carbon (VOC) emissions through assimilation of remote sensing data. We first update a three-dimensional (3D) chemical transport model, GEOS-Chem with the KORUSv5 anthropogenic emission inventory and inclusion of chemistry for aromatics and C2H4, leading to modest improvements in simulation of CH2O (normalized mean bias (NMB): -0.57 to -0.51) and O-3 (NMB: -0.25 to -0.19) compared against DC-8 aircraft measurements during KORUS-AQ; the mixing ratio of most VOC species are still underestimated. We next constrain VOC emissions using CH2O observations from two satellites (OMI and OMPS) and the DC-8 aircraft during KORUS-AQ. To utilize data from multiple platforms in a consistent manner, we develop a two-step Hybrid Iterative Finite Difference Mass Balance and four-dimensional variational inversion system (Hybrid IFDMB-4DVar). The total VOC emissions throughout the domain increase by 47%. The a posteriori simulation reduces the low biases of simulated CH2O (NMB: -0.51 to -0.15), O-3 (NMB: -0.19 to -0.06), and VOCs. Alterations to the VOC speciation from the 4D-Var inversion include increases of biogenic isoprene emissions in Korea and anthropogenic emissions in Eastern China. We find that the IFDMB method alone is adequate for reducing the low biases of VOCs in general; however, 4D-Var provides additional refinement of high-resolution emissions and their speciation. Defining reasonable emission errors and choosing optimal regularization parameters are crucial parts of the inversion system. Our new hybrid inversion framework can be applied for future air quality campaigns, maximizing the value of integrating measurements from current and upcoming geostationary satellite instruments.

We conduct the first 4D-Var inversion of NH3 accounting for NH3 bi-directional flux, using CrIS satellite NH3 observations over Europe in 2016. We find posterior NH3 emissions peak more in springtime than prior emissions at continental to national scales, and annually they are generally smaller than the prior emissions over central Europe, but larger over most of the rest of Europe. Annual posterior anthropogenic NH3 emissions for 25 European Union members (EU25) are 25% higher than the prior emissions and very close (<2% difference) to other inventories. Our posterior annual anthropogenic emissions for EU25, the UK, the Netherlands, and Switzerland are generally 10%-20% smaller than when treating NH3 fluxes as uni-directional emissions, while the monthly regional difference can be up to 34% (Switzerland in July). Compared to monthly mean in-situ observations, our posterior NH3 emissions from both schemes generally improve the magnitude and seasonality of simulated surface NH3 and bulk NH x wet deposition throughout most of Europe, whereas evaluation against hourly measurements at a background site shows the bi-directional scheme better captures observed diurnal variability of surface NH3. This contrast highlights the need for accurately simulating diurnal variability of NH3 in assimilation of sun-synchronous observations and also the potential value of future geostationary satellite observations. Overall, our top-down ammonia emissions can help to examine the effectiveness of air pollution control policies to facilitate future air pollution management, as well as helping us understand the uncertainty in top-down NH3 emissions estimates associated with treatment of NH3 surface exchange.

CrIS-derived monthly NH3 emissions over the US for the year 2014

We present a novel source attribution approach that incorporates satellite data into GEOS-Chem adjoint simulations to characterize the species-specific, regional, and sectoral contributions of daily emissions for 3 air pollutants: fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2). This approach is implemented for Washington, DC, first for 2011, to identify urban pollution sources, and again for 2016, to examine the pollution response to changes in anthropogenic emissions. In 2011, anthropogenic emissions contributed an estimated 263 (uncertainty: 130–444) PM2.5and O3-attributable premature deaths and 1,120 (391–1795) NO2 attributable new pediatric asthma cases in DC. PM2.5 exposure was responsible for 90% of these premature deaths. On-road vehicle emissions contributed 51% of NO2-attributable new asthma cases and 23% of pollution-attributable premature deaths, making it the largest contributing individual sector to DC’s air pollution–related health burden. Regional emissions, originating from Maryland, Virginia, and Pennsylvania, were the most responsible for pollution-related health impacts in DC, contributing 57% of premature deaths impacts and 89% of asthma cases. Emissions from distant states contributed 34% more to PM2.5 exposure in the wintertime than in the summertime, occurring in parallel with strong wintertime westerlies and a reduced photochemical sink. Emission reductions between 2011 and 2016 resulted in health benefits of 76 (28–149) fewer pollution-attributable premature deaths and 227 (2–617) fewer NO2-attributable pediatric asthma cases. The largest sectors contributing to decreases in pollutionrelated premature deaths were energy generation units (26%) and on-road vehicles (20%). Decreases in NO2-attributable pediatric asthma cases were mostly due to emission reductions from on-road vehicles (63%). Emission reductions from energy generation units were found to impact PM2.5 more than O3, while on-road vehicle emission reductions impacted O3 proportionally more than PM2.5.This novel method is capable of capturing the sources of urban pollution at fine spatial and temporal scales and is applicable to many urban environments, globally.

We apply airborne measurements across three seasons (summer, winter and spring 2017–2018) in a multi-inversion framework to quantify methane emissions from the US Corn Belt and Upper Midwest, a key agricultural and wetland source region. Combing our seasonal results with prior fall values we find that wetlands are the largest regional methane source (32 %, 20 [16–23] Gg/d), while livestock (enteric/manure; 25 %, 15 [14–17] Gg/d) are the largest anthropogenic source. Natural gas/petroleum, waste/landfills, and coal mines collectively make up the remainder. Optimized fluxes improve model agreement with independent datasets within and beyond the study timeframe. Inversions reveal coherent and seasonally dependent spatial errors in the WetCHARTs ensemble mean wetland emissions, with an underestimate for the Prairie Pothole region but an overestimate for Great Lakes coastal wetlands. Wetland extent and emission temperature dependence have the largest influence on prediction accuracy; better representation of coupled soil temperature–hydrology effects is therefore needed. Our optimized regional livestock emissions agree well with the Gridded EPA estimates during spring (to within 7 %) but are ∼ 25 % higher during summer and winter. Spatial analysis further shows good top-down and bottom-up agreement for beef facilities (with mainly enteric emissions) but larger (∼ 30 %) seasonal discrepancies for dairies and hog farms (with > 40 % manure emissions). Findings thus support bottom-up enteric emission estimates but suggest errors for manure; we propose that the latter reflects inadequate treatment of management factors including field application. Overall, our results confirm the importance of intensive animal agriculture for regional methane emissions, implying substantial mitigation opportunities through improved management.

Effective mitigation of surface ozone pollution entails detailed knowledge of the contributing precursors' sources. We use the GEOS-Chem adjoint model to analyze the precursors contributing to surface ozone in the Beijing-Tianjin-Hebei area (BTH) of China on days of different ozone pollution severities in June 2019. We find that BTH ozone on heavily polluted days is sensitive to local emissions, as well as to precursors emitted from the provinces south of BTH (Shandong, Henan, and Jiangsu, collectively the SHJ area). Heavy ozone pollution in BTH can be mitigated effectively by reducing NOx (from industrial processes and transportation), ≥C3 alkenes (from on-road gasoline vehicles and industrial processes), and xylenes (from paint use) emitted from both BTH and SHJ, as well as by reducing CO (from industrial processes, transportation, and power generation) and ≥C4 alkanes (from industrial processes, paint and solvent use, and on-road gasoline vehicles) emissions from SHJ. In addition, reduction of NOx, xylene, and ≥C3 alkene emissions within BTH would effectively decrease the number of BTH ozone-exceedance days. Our analysis pinpoint the key areas and activities for locally and regionally coordinated emission control efforts to improve surface ozone air quality in BTH.

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NOx emissions. Second, the response of O3 to decreased NOx emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheri...

In situ measurements have suggested vehicle emissions may dominate agricultural sources of NH3 in many cities, which is alarming given the potential for urban NH3 to significantly increase human exposure to ambient particulate matter. However, confirmation of the prevalence of vehicle NH3 throughout a city has been challenging because of mixing with agricultural sources, and the latter are thus routinely assumed to dominate. Here we report vehicle NH3 emissions based on TROPOMI NO2 and CrIS NH3 (0.152 kg s-1) that are consistent with a model-based estimate (0.178 kg s-1) and show that COVID-19 lockdowns provide a unique opportunity for making the first satellite-based constraints on vehicle NH3 emissions for an entire urban region (western Los Angeles), which we find make up 60-95% of total NH3 emissions, substantially higher than the values of 13-22% in state and national inventories. This provides a new means of constraining a component of transportation emissions whose impacts may rival those of NOx yet which has been largely under-recognized and uncontrolled. © 2021 The Authors. Published by American Chemical Society.

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Earth's Future. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]Analysis of recent anthropogenic surface emissions from bottom-up inventories and top-down estimates: are future emission scenarios valid for the recent past?Authors Nellie Elguindi iD Claire Granier iD Trissevgeni Stavrakou iD Sabine Darras Maite Bauwens Hansen Cao iD Cheng Chen Hugo Denier van der Gon Oleg Dubovik iD Tzung-May Fu Daven K. Henze iD Zhe Jiang Jeroen Kuenen Jun-ichi Kurokawa iD Cathy Liousse Kazuyuki Miyazaki iD Jean-François Müller iD Zhen Qu iD Keita Sekou iD Fabien Solmon Bo Zheng iDSee all authors Nellie ElguindiiDCorresponding AuthorCentre national de la recherche scientifiqueiDhttps://orcid.org/0000-0002-9211-4173view email addressThe email was not providedcopy email addressClaire GranieriDUniversity of ToulouseiDhttps://orcid.org/0000-0002-3007-6044view email addressThe email was not providedcopy email addressTrissevgeni StavrakouiDRoyal Belgian Institute for Space AeronomyiDhttps://orcid.org/0000-0002-2952-8306view email addressThe email was not providedcopy email addressSabine DarrasObservatoire Midi-Pyreneesview email addressThe email was not providedcopy email addressMaite BauwensRoyal Belgium Institute for Space Aeronomyview email addressThe email was not providedcopy email addressHansen CaoiDUniversity of ColoradoiDhttps://orcid.org/0000-0003-2713-0430view email addressThe email was not providedcopy email addressCheng ChenLaboratoire d'Optique Atmosphériqueview email addressThe email was not providedcopy email addressHugo Denier van der GonTNOview email addressThe email was not providedcopy email addressOleg DubovikiDCNRS, Universite Lille-1iDhttps://orcid.org/0000-0003-3482-6460view email addressThe email was not providedcopy email addressTzung-May FuSchool of Environmental Science and Engineering, Southern University of Science and Technologyview email addressThe email was not providedcopy email addressDaven K. HenzeiDUniversity of Colorado BoulderiDhttps://orcid.org/0000-0001-6431-4963view email addressThe email was not providedcopy email addressZhe JiangUniversity of Science and Technology of Chinaview email addressThe email was not providedcopy email addressJeroen KuenenTNOview email addressThe email was not providedcopy email addressJun-ichi KurokawaiDAsia Center for Air Pollution ResearchiDhttps://orcid.org/0000-0001-5881-6377view email addressThe email was not providedcopy email addressCathy LiousseLaboratoire d'Aérologieview email addressThe email was not providedcopy email addressKazuyuki MiyazakiiDJet Propulsion LaboratoryiDhttps://orcid.org/0000-0002-1466-4655view email addressThe email was not providedcopy email addressJean-François MülleriDRoyal Belgian Institute for Space Aeronomy (BIRA-IASB)iDhttps://orcid.org/0000-0001-5335-2622view email addressThe email was not providedcopy email addressZhen QuiDUniversity of Colorado BoulderiDhttps://orcid.org/0000-0002-3766-9838view email addressThe email was not providedcopy email addressKeita SekouiDUniversity PGCiDhttps://orcid.org/0000-0002-7181-8382view email addressThe email was not providedcopy email addressFabien SolmonLaboratoire d'Aérologieview email addressThe email was not providedcopy email addressBo ZhengiDLaboratory of Climate Sciences and Environment (LSCE), Paris, FranceiDhttps://orcid.org/0000-0001-8344-3445view email addressThe email was not providedcopy email address

Spatiotemporal uncertainty in NH3 emissions in the US hinders prediction of environmental effects of atmospheric NH3. We conducted 4D-Var inversions using CrIS remote-sensing observations and GEOS-Chem to estimate monthly NH3 emissions over the contiguous US at the 0.25. x 0.3125. resolution in 2014, finding they are 33% higher than the prior emissions which likely underestimated most agricultural emissions, especially intense springtime fertilizer and livestock sources over the Central US. However, decreases were found in the Central Valley, southern Minnesota, northern Iowa and southeastern North Carolina during warm months. These updates increased the correlation coefficient between modeled monthly mean NH3 and surface observations from 0.53 to 0.84, and reduced the normalized mean bias of annual mean simulated NH3 and wet NH+ 4 by a factor of 1.3 to 12.7. Our satellite-based inversion approach thus holds promise for improving estimates of PM2.5 and reactive nitrogen deposition throughout the world where NH3 measurements are scarce.

The Beijing-Tianjin-Hebei (BTH) region in China has been frequently suffering from severe haze events (observed daily mean surface fine particulate matter PM2.5 concentrations larger than 150 mu g m(-3)) partially caused by certain types of large-scale synoptic patterns. Black carbon (BC), as an important PM2.5 component and a primarily emitted species, is a good tracer for investigating sources and formation mechanisms leading to severe haze pollutions. We apply GEOS-Chem model and its adjoint to quantify the source contributions to BC concentrations at the surface and at the top of the planetary boundary layer (PBL) during typical types of severe haze events for April 2013-2017 in BTH. Four types of severe haze events, mainly occurred in December-January-February (DJF, 62.3%) and in September-October-November (SON, 26.3%), are classified based on the associated synoptic weather patterns using principal component analysis. Model results reasonably capture the daily variations of BC measurements at three ground sites in BTH. The adjoint method attributes BC concentrations to emissions from different source sectors and from local versus regional transport at the model spatial and temporal resolutions. By source sectors, the adjoint method attributes the daily BC concentrations during typical severe haze events (in winter heating season) in Beijing largely to residential emissions (48.1-62.0%), followed by transportation (16.8-25.9%) and industry (19.1-29.5%) sectors. In terms of regionally aggregated source influences, local emissions in Beijing (59.6-79.5%) predominate the daily surface BC concentrations, while contributions of emissions from Beijing, Hebei, and outside BTH regions are comparable to the daily BC concentrations at the top of PBL (similar to 200-400m). Our adjoint analyses would provide a scientific support for joint regional and targeted control policies on effectively mitigating the particulate pollutions when the dominant synoptic weather patterns are predicted. (C) 2020 The Authors. Published by Elsevier B.V.