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Ammonia (NH3) is an essential reactive nitrogen species in the biosphere and through its use in agriculture in the form of fertilizer (important for sustaining humankind). The current emission levels, however, are up to 4 times higher than in the previous century and continue to grow with uncertain consequences to human health and the environment. While NH3 at its current levels is a hazard to environmental and human health, the atmospheric budget is still highly uncertain, which is a product of an overall lack of measurements. The capability to measure NH3 with satellites has opened up new ways to study the atmospheric NH3 budget. In this study, we present the first estimates of NH3 emissions, lifetimes and plume widths from large (>∼5 kt yr−1) agricultural and industrial point sources from Cross-track Infrared Sounder (CrIS) satellite observations across the globe with a consistent methodology. The same methodology is also applied to the Infrared Atmospheric Sounding Interferometer (IASI) (A and B) satellite observations, and we show that the satellites typically provide comparable results that are within the uncertainty of the estimates. The computed NH3 lifetime for large point sources is on average 2.35±1.16 h. For the 249 sources with emission levels detectable by the CrIS satellite, there are currently 55 locations missing (or underestimated by more than an order of magnitude) from the current Hemispheric Transport Atmospheric Pollution version 2 (HTAPv2) emission inventory and only 72 locations with emissions within a factor of 2 compared to the inventories. The CrIS emission estimates give a total of 5622 kt yr−1, for the sources analyzed in this study, which is around a factor of ∼2.5 higher than the emissions reported in HTAPv2. Furthermore, the study shows that it is possible to accurately detect short- and long-term changes in emissions, demonstrating the possibility of using satellite-observed NH3 to constrain emission inventories.

Ammonia (NH3) is the most important alkaline gas in the atmosphere, which has negative effects on biodiversity, ecosystems, soil acidification and human health. China has the largest NH3 emissions globally, mainly associated with agricultural sources including nitrogen fertilizer and livestock. However, there is still a limited number of ground monitoring sites in China, hindering our understanding of both surface NH3 concentrations and emissions. In this study, using the polar-orbiting satellite (Infrared Atmospheric Sounding Interferometer – IASI) and Fengyun-4A Geostationary Interferometric Infrared Sounder (GIIRS), we analyzed the changes in hourly NH3 concentrations and estimated surface NH3 concentrations and NH3 emissions in China. GIIRS-derived NH3 concentrations in the daytime were generally higher than those at night, with high values during 10:00–16:00 local time. Satellite-derived surface NH3 concentrations were generally consistent with the ground observations, with R-square at 0.72 and slope equal to 1.03. Satellite-based NH3 emissions ranged from 12.17 to 17.77 Tg N yr−1 during 2008–2019. Spatially, high values of NH3 emissions mainly occurred in the North China Plain, Northeast China and the Sichuan Basin, while low values were mainly distributed in West China (Qinghai–Tibet Plateau). Our study shows a high predictive power of using satellite data to estimate surface NH3 concentrations and NH3 emissions over multiple temporal and spatial scales, which provides an important reference for understanding NH3 changes over China.

Emissions of ammonia (NH3) to the atmosphere impact human health, climate, and ecosystems via their critical contributions to secondary aerosol formation. However, the estimation of NH3 emissions is associated with large uncertainties because of inadequate knowledge about agricultural sources. Here, we use satellite observations from the Infrared Atmospheric Sounding Interferometer (IASI) and simulations from the GEOS-Chem model to constrain global NH3 emissions over the period from 2008 to 2018. We update the prior NH3 emission fluxes with the ratio between biases in simulated NH3 concentrations and effective NH3 lifetimes against the loss of the NHx family. In contrast to the approximate factor of 2 discrepancies between top-down and bottom-up emissions found in previous studies, our method results in a global land NH3 emission of 78 (70–92) Tg a−1, which is ∼30 % higher than the bottom-up estimates. Regionally, we find that the bottom-up inventory underestimates NH3 emissions over South America and tropical Africa by 60 %–70 %, indicating underrepresentation of agricultural sources in these regions. We find a good agreement within 10 % between bottom-up and top-down estimates over the US, Europe, and eastern China. Our results also show significant increases in NH3 emissions over India (13 % per decade), tropical Africa (33 % per decade), and South America (18 % per decade) during our study period, which is consistent with the intensifying agricultural activity in these regions in the past decade. We find that the inclusion of the sulfur dioxide (SO2) column observed by satellite is crucial for more accurate inference of NH3 emission trends over important source regions such as India and China where SO2 emissions have changed rapidly in recent years.

The Hunga volcano violently erupted on 15 January 2022, producing the largest perturbation of the stratospheric aerosol layer since Pinatubo 1991, despite the initially estimated modest injection of SO2. This study presents novel SO2 and sulfate aerosol (SA) co‐retrievals from the Infrared Atmospheric Sounding Interferometer, and uses them to quantify the initial progression of the Hunga plume. These observations are consistent with rapid conversion of SO2 (e‐folding time: 17.1 ± 4.3 days) to SA, with an injected burden of >1.0 Tg SO2. This points at larger SO2 injections than previously thought. A long‐lasting SA plume was observed, with two separate build‐up phases, and with a meridional dispersion of marked anomalies from the tropics to the higher southern hemispheric latitudes. A limited (∼20%) SA removal was observed after 1‐year dispersion. The total injected SA mass burden was estimated at 1.6 ± 0.5 Tg in the total atmospheric column, with a build‐up e‐folding time of about 2 months. Plain Language Summary The eruption of the submarine Hunga volcano in January 2022 polluted the global stratosphere with a large amount of water vapor and significantly perturbed the stratospheric aerosol layer. In this paper, we present a 1‐year long aftermath study of the stratospheric sulfur pollution from this volcanic eruption using observations from the Infrared Atmospheric Sounding Interferometer (IASI) satellite‐borne instrument. Gaseous and aerosol sulfur emissions are observed simultaneously using the specific potential of this sensor. These observations provide unique capabilities to characterize the aerosol type in the Hunga plume and the sulfur cycle associated with the volcanic emissions. An extremely rapid conversion of gaseous sulfur emissions to aerosols is observed, leading to larger than expected and persistent anomalies of the stratospheric aerosol layer (compared with a consistent long‐term climatology), still noticeable in the Southern Hemisphere after 1 year. The total mass of the emitted sulfur in gas and aerosol state is also simultaneously estimated, for the first time. Key Points Novel co‐retrieval of SO2 and sulfate aerosol from Infrared Atmospheric Sounding Interferometer (IASI) used to study the dispersion of the Hunga plume over the entire year 2022 Rapid conversion of SO2 (2 weeks e‐folding time) and long‐lasting sulfate aerosol observed Larger SO2 injected mass burden (>1.0 Tg) than previously thought and a large sulfate aerosol total burden (1.6 Tg) estimated

We use a combination of spaceborne instruments to study the unprecedented stratospheric plume after the Tonga eruption of 15 January 2022. The aerosol plume was initially formed of two clouds at 30 and 28 km, mostly composed of submicron-sized sulfate particles, without ash, which is washed out within the first day following the eruption. The large amount of injected water vapour led to a fast conversion of SO2 to sulfate aerosols and induced a descent of the plume to 24–26 km over the first 3 weeks by radiative cooling. Whereas SO2 returned to background levels by the end of January, volcanic sulfates and water still persisted after 6 months, mainly confined between 35∘ S and 20∘ N until June due to the zonal symmetry of the summer stratospheric circulation at 22–26 km. Sulfate particles, undergoing hygroscopic growth and coagulation, sediment and gradually separate from the moisture anomaly entrained in the ascending branch Brewer–Dobson circulation. Sulfate aerosol optical depths derived from the IASI (Infrared Atmospheric Sounding Interferometer) infrared sounder show that during the first 2 months, the aerosol plume was not simply diluted and dispersed passively but rather organized in concentrated patches. Space-borne lidar winds suggest that those structures, generated by shear-induced instabilities, are associated with vorticity anomalies that may have enhanced the duration and impact of the plume.

Tropical tropospheric ozone (TTO) is important for the global radiation budget because the longwave radiative effect of tropospheric ozone is higher in the tropics than midlatitudes. In recent decades the TTO burden has increased, partly due to the ongoing shift of ozone precursor emissions from midlatitude regions toward the Equator. In this study, we assess the distribution and trends of TTO using ozone profiles measured by high-quality in situ instruments from the IAGOS (In-Service Aircraft for a Global Observing System) commercial aircraft, the SHADOZ (Southern Hemisphere ADditional OZonesondes) network, and the ATom (Atmospheric Tomographic Mission) aircraft campaign, as well as six satellite records reporting tropical tropospheric column ozone (TTCO): TROPOspheric Monitoring Instrument (TROPOMI), Ozone Monitoring Instrument (OMI), OMI/Microwave Limb Sounder (MLS), Ozone Mapping Profiler Suite (OMPS)/Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), Cross-track Infrared Sounder (CrIS), and Infrared Atmospheric Sounding Interferometer (IASI)/Global Ozone Monitoring Experiment 2 (GOME2). With greater availability of ozone profiles across the tropics we can now demonstrate that tropical India is among the most polluted regions (e.g., western Africa, tropical South Atlantic, Southeast Asia, Malaysia and Indonesia), with present-day 95th percentile ozone values reaching 80 nmol mol−1 in the lower free troposphere, comparable to midlatitude regions such as northeastern China and Korea. In situ observations show that TTO increased between 1994 and 2019, with the largest mid- and upper-tropospheric increases above India, Southeast Asia, and Malaysia and Indonesia (from 3.4 ± 0.8 to 6.8 ± 1.8 nmol mol−1 decade−1), reaching 11 ± 2.4 and 8 ± 0.8 nmol mol−1 decade−1 close to the surface (India and Malaysia–Indonesia, respectively). The longest continuous satellite records only span 2004–2019 but also show increasing ozone across the tropics when their full sampling is considered, with maximum trends over Southeast Asia of 2.31 ± 1.34 nmol mol−1 decade−1 (OMI) and 1.69 ± 0.89 nmol mol−1 decade−1 (OMI/MLS). In general, the sparsely sampled aircraft and ozonesonde records do not detect the 2004–2019 ozone increase, which could be due to the genuine trends on this timescale being masked by the additional uncertainty resulting from sparse sampling. The fact that the sign of the trends detected with satellite records changes above three IAGOS regions, when their sampling frequency is limited to that of the in situ observations, demonstrates the limitations of sparse in situ sampling strategies. This study exposes the need to maintain and develop high-frequency continuous observations (in situ and remote sensing) above the tropical Pacific Ocean, the Indian Ocean, western Africa, and South Asia in order to estimate accurate and precise ozone trends for these regions. In contrast, Southeast Asia and Malaysia–Indonesia are regions with such strong increases in ozone that the current in situ sampling frequency is adequate to detect the trends on a relatively short 15-year timescale.

Ammonia (NH3) has been detected in the upper troposphere by the analysis of averaged MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) infrared limb-emission spectra. We have found enhanced amounts of NH3 within the region of the Asian summer monsoon at 12–15 km altitude. Three-monthly, 10° longitude  ×  10° latitude average profiles reaching maximum mixing ratios of around 30 pptv in this altitude range have been retrieved, with a vertical resolution of 3–8 km and estimated errors of about 5 pptv. These observations show that loss processes during transport from the boundary layer to the upper troposphere within the Asian monsoon do not deplete the air entirely of NH3. Thus, ammonia might contribute to the so-called Asian tropopause aerosol layer by the formation of ammonium aerosol particles. On a global scale, outside the monsoon area and during different seasons, we could not detect enhanced values of NH3 above the actual detection limit of about 3–5 pptv. This upper bound helps to constrain global model simulations.

Recently, presented a neural-network-based algorithm for retrieving atmospheric ammonia (NH3) columns from Infrared Atmospheric Sounding Interferometer (IASI) satellite observations. In the past year, several improvements have been introduced, and the resulting new baseline version, Artificial Neural Network for IASI (ANNI)-NH3-v2.1, is documented here. One of the main changes to the algorithm is that separate neural networks were trained for land and sea observations, resulting in a better training performance for both groups. By reducing and transforming the input parameter space, performance is now also better for observations associated with favourable sounding conditions (i.e. enhanced thermal contrasts). Other changes relate to the introduction of a bias correction over land and sea and the treatment of the satellite zenith angle. In addition to these algorithmic changes, new recommendations for post-filtering the data and for averaging data in time or space are formulated. We also introduce a second dataset (ANNI-NH3-v2.1R-I) which relies on ERA-Interim ECMWF meteorological input data, along with surface temperature retrieved from a dedicated network, rather than the operationally provided Eumetsat IASI Level 2 (L2) data used for the standard near-real-time version. The need for such a dataset emerged after a series of sharp discontinuities were identified in the NH3 time series, which could be traced back to incremental changes in the IASI L2 algorithms for temperature and clouds. The reanalysed dataset is coherent in time and can therefore be used to study trends. Furthermore, both datasets agree reasonably well in the mean on recent data, after the date when the IASI meteorological L2 version 6 became operational (30 September 2014).

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models.

Ammonia has attracted significant attention due to its pivotal role in the ecosystem and its contribution to the formation of secondary aerosols. Developing an accurate ammonia emission inventory is crucial for simulating atmospheric ammonia levels and quantifying its impacts. However, current inventories are typically constructed via the bottom-up approach and are associated with substantial uncertainties. To address this issue, assimilating observations from satellite instruments for top-down emission inversion has emerged as an effective strategy for optimizing emission inventories. Despite the severity of ammonia pollution in South Asia, research in this context remains very limited. This study aims to estimate ammonia emissions in this region by integrating the prior emission inventory from the Community Emissions Data System (CEDS) and the columned ammonia concentration retrievals from the Infrared Atmospheric Sounder Interferometer (IASI). We employ a newly developed four-dimensional ensemble variational (4DEnVar)-based emission inversion system to conduct the calculations, resulting in monthly ammonia emissions for 2019 at a resolution of 0.5° × 0.625°. The annual total estimate for the posterior emission inventory is 12.61 Tg, compared to the prior inventory's 13.32 Tg. Our simulations, driven by the posterior emission inventory, demonstrate superior performance compared to those driven by the prior emission inventory. This performance is validated through comparisons against the IASI observations, the independent column concentration measurements from the advanced satellite instrument Cross-track Infrared Sounder (CrIS), and the ground concentration observations of ammonia and PM2.5. Additionally, the spatial and temporal characteristics of ammonia emissions in South Asia based on the posterior inventory are analyzed. Notably, emissions there exhibit a “double-peak” seasonal profile, with the maximum in July and the secondary peak in May. This observation differs from the “double-peak” trend suggested by the CEDS prior inventory, which identifies the maximum column concentration in May and a second peak in September. The differences may be attributed to a more accurate representation of regional agricultural practices, such as the timing of fertilizer application and meteorological influences like precipitation and temperature.