Observations of atmospheric ammonia are important in understanding and modelling the impact of ammonia on both human health and the natural environment. We present a detailed description of a robust retrieval algorithm that demonstrates the capabilities of utilizing Cross-track Infrared Sounder (CrIS) satellite observations to globally retrieval ammonia concentrations. Initial ammonia retrieval results using both simulated and real observations show that (i) CrIS is sensitive to ammonia in the boundary layer with peak vertical sensitivity typically around ~ 850–750 hPa (~ 1.5 to 2.5 km), which can dip down close to the surface (~ 900 hPa) under ideal conditions, (ii) it has a minimum detection limit of ~ 1 ppbv (peak profile value typically at the surface), and (iii) the information content can vary significantly with maximum values of ~ 1 degree-of-freedom for signal. Comparisons of the retrieval with simulated "true" profiles show a small positive retrieval bias of 6% with a standard deviation of ~ ± 20% (ranging from ± 12 to ± 30% over the vertical profile). Note that these uncertainty estimates are considered as lower bound values as no potential systematic errors are included in the simulations. The CrIS NH₃ retrieval applied over the Central Valley in CA, USA, demonstrates that CrIS correlates well with the spatial variability of the boundary layer ammonia concentrations seen by the nearby Quantum Cascade-Laser (QCL) in situ surface and the Tropospheric Emission Spectrometer (TES) satellite observations as part of the DISCOVER-AQ campaign. The CrIS and TES ammonia observations show quantitatively similar retrieved boundary layer values that are often within the uncertainty of the two observations. Also demonstrated is CrIS's ability to capture the expected spatial distribution in the ammonia concentrations, from elevated values in the Central Valley from anthropogenic agriculture emissions, to much lower values in the unpolluted or clean surrounding mountainous regions. These initial results demonstrate the capabilities of the CrIS satellite to measure ammonia.

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 ($>\sim \mathrm{5}$ 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.

Despite its clear importance, the monitoring of atmospheric ammonia, including its sources, sinks, and links to the greater nitrogen cycle, remains limited. Satellite data are helping to fill the gap in monitoring from sporadic conventional ground- and aircraft-based observations to better inform policymakers and assess the impact of any ammonia-related policies. Presented is a description and survey that demonstrate the capabilities of the Cross-track Infrared Sounder (CrIS) ammonia product for monitoring, air quality forecast model evaluation, dry deposition estimates, and emission estimates from an agricultural hotspot. For model evaluation, while there is a general agreement in the spatial allocation of known major agricultural ammonia hotspots across North America, the satellite observations show some high-latitude regions during peak forest fire activity often have ammonia concentrations approaching those in agricultural hotspots. The CrIS annual ammonia dry depositions in Canada (excluding the territories) and the US have average and annual variability values of $\sim \mathrm{0.8}\pm \mathrm{0.08}$ and $\sim \mathrm{1.23}\pm \mathrm{0.09}$ Tg N yr⁻¹, respectively. These satellite-derived dry depositions of reactive nitrogen from NH₃ with NO₂ show an annual ratio of NH₃ compared to their sum (NH₃+NO₂) of ∼82 % and ∼55 % in Canada and the US, respectively. Furthermore, we show the use of CrIS satellite observations to estimate annual and seasonal emissions near Lethbridge, Alberta, Canada, a region dominated by high-emission concentrated animal feeding operations (CAFOs); the satellite annual emission estimate of 37.1±6.3 kt yr⁻¹ is at least double the value reported in current bottom-up emission inventories for this region.

Reactive nitrogen (N_r) is an essential nutrient to plants and a limiting element for growth in many ecosystems, but it can have harmful effects on ecosystems when in excess. Satellite‐derived surface observations are used together with a dry deposition model to estimate the dry deposition flux of the most abundant short‐lived nitrogen species, NH₃ and NO₂, over North America during the 2013 warm season. These fluxes demonstrate that the NH₃ contribution dominates over NO₂ for most regions (comprising ~85% of their sum in Canada and ~65% in the U.S.), with some regional exceptions (e.g. Alberta and northeastern U.S.). Nationwide, ~1.35 Tg of N from these species were dry deposited in the contiguous U.S., more than double the ~0.61 Tg in Canada (excluding territories) over this period. Forest fires are shown to be the major contributor of dry deposition of N_r from NH₃ in northern latitudes, leading to deposition fluxes 2–3 times greater than from expected amounts without fires.

Modern data assimilation algorithms depend on accurate infrared spectroscopy in order to make use of the information related to temperature, water vapor (H₂O), and other trace gases provided by satellite observations. Reducing the uncertainties in our knowledge of spectroscopic line parameters and continuum absorption is thus important to improve the application of satellite data to weather forecasting. Here we present the results of a rigorous validation of spectroscopic updates to an advanced radiative transfer model, the Line-By-Line Radiative Transfer Model (LBLRTM), against a global dataset of 120 near-nadir, over-ocean, nighttime spectra from the Infrared Atmospheric Sounding Interferometer (IASI). We compare calculations from the latest version of LBLRTM (v12.1) to those from a previous version (v9.4+) to determine the impact of spectroscopic updates to the model on spectral residuals as well as retrieved temperature and H₂O profiles. We show that the spectroscopy in the CO₂ ν₂ and ν₃ bands is significantly improved in LBLRTM v12.1 relative to v9.4+, and that these spectroscopic updates lead to mean changes of ~0.5 K in the retrieved vertical temperature profiles between the surface and 10 hPa, with the sign of the change and the variability among cases depending on altitude. We also find that temperature retrievals using each of these two CO₂ bands are remarkably consistent in LBLRTM v12.1, potentially allowing these bands to be used to retrieve atmospheric temperature simultaneously. The updated H₂O spectroscopy in LBLRTM v12.1 substantially improves the a posteriori residuals in the P-branch of the H₂O ν₂ band, while the improvements in the R-branch are more modest. The H₂O amounts retrieved with LBLRTM v12.1 are on average 14% lower between 100 and 200 hPa, 42% higher near 562 hPa, and 31% higher near the surface compared to the amounts retrieved with v9.4+ due to a combination of the different retrieved temperature profiles and the updated H₂O spectroscopy. We also find that the use of a fixed ratio of HDO to H₂O in LBLRTM may be responsible for a significant fraction of the remaining bias in the P-branch relative to the R-branch of the H₂O ν₂ band. There were no changes to O₃ spectroscopy between the two model versions, and so both versions give positive a posteriori residuals of ~ 0.3 K in the R-branch of the O₃ ν₃ band. While the updates to the H₂O self-continuum employed by LBLRTM v12.1 have clearly improved the match with observations near the CO₂ ν₃ band head, we find that these updates have significantly degraded the match with observations in the fundamental band of CO. Finally, significant systematic a posteriori residuals remain in the ν₄ band of CH₄, but the magnitude of the positive bias in the retrieved mixing ratios is reduced in LBLRTM v12.1, suggesting that the updated spectroscopy could improve retrievals of CH₄ from satellite observations.

Presented here is the validation of the CrIS (Cross-track Infrared Sounder) fast physical NH₃ retrieval (CFPR) column and profile measurements using ground-based Fourier transform infrared (FTIR) observations. We use the total columns and profiles from seven FTIR sites in the Network for the Detection of Atmospheric Composition Change (NDACC) to validate the satellite data products. The overall FTIR and CrIS total columns have a positive correlation of r = 0.77 (N = 218) with very little bias (a slope of 1.02). Binning the comparisons by total column amounts, for concentrations larger than 1.0 × 10¹⁶ molecules cm⁻², i.e. ranging from moderate to polluted conditions, the relative difference is on average ∼ 0–5 % with a standard deviation of 25–50 %, which is comparable to the estimated retrieval uncertainties in both CrIS and the FTIR. For the smallest total column range (< 1.0 × 10¹⁶ molecules cm⁻²) where there are a large number of observations at or near the CrIS noise level (detection limit) the absolute differences between CrIS and the FTIR total columns show a slight positive column bias. The CrIS and FTIR profile comparison differences are mostly within the range of the single-level retrieved profile values from estimated retrieval uncertainties, showing average differences in the range of ∼ 20 to 40 %. The CrIS retrievals typically show good vertical sensitivity down into the boundary layer which typically peaks at ∼ 850 hPa (∼ 1.5 km). At this level the median absolute difference is 0.87 (std = ±0.08) ppb, corresponding to a median relative difference of 39 % (std = ±2 %). Most of the absolute and relative profile comparison differences are in the range of the estimated retrieval uncertainties. At the surface, where CrIS typically has lower sensitivity, it tends to overestimate in low-concentration conditions and underestimate in higher atmospheric concentration conditions.