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.

Limited availability of ammonia (NH₃) observations is currently a barrier for effective monitoring of the nitrogen cycle. It prevents a full understanding of the atmospheric processes in which this trace gas is involved and therefore impedes determining its related budgets. Since the end of 2007, the Infrared Atmospheric Sounding Interferometer (IASI) satellite has been observing NH₃ from space at a high spatio-temporal resolution. This valuable data set, already used by models, still needs validation. We present here a first attempt to validate IASI-NH₃ measurements using existing independent ground-based and airborne data sets. The yearly distributions reveal similar patterns between ground-based and space-borne observations and highlight the scarcity of local NH₃ measurements as well as their spatial heterogeneity and lack of representativity. By comparison with monthly resolved data sets in Europe, China and Africa, we show that IASI-NH₃ observations are in fair agreement, but they are characterized by a smaller variation in concentrations. The use of hourly and airborne data sets to compare with IASI individual observations allows investigations of the impact of averaging as well as the representativity of independent observations for the satellite footprint. The importance of considering the latter and the added value of densely located airborne measurements at various altitudes to validate IASI-NH₃ columns are discussed. Perspectives and guidelines for future validation work on NH₃ satellite observations are presented.

We exploit 6 years of measurements from the Infrared Atmospheric Sounding Interferometer (IASI)/MetOp-A instrument to identify seasonal patterns and interannual variability of atmospheric NH₃. This is achieved by analyzing the time evolution of the monthly mean NH₃ columns in 12 subcontinental areas around the world, simultaneously considering measurements from IASI morning and evening overpasses. For most regions, IASI has a sufficient sensitivity throughout the years to capture the seasonal patterns of NH₃ columns, and we show that each region is characterized by a well-marked and distinctive cycle, with maxima mainly related to underlying emission processes. The largest column abundances and seasonal amplitudes throughout the years are found in southwestern Asia, with maxima twice as large as what is observed in southeastern China. The relation between emission sources and retrieved NH₃ columns is emphasized at a smaller regional scale by inferring a climatology of the month of maximum columns.

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.

Smoke from wildfires is a significant source of air pollution, which can adversely impact air quality and ecosystems downwind. With the recently increasing intensity and severity of wildfires, the threat to air quality is expected to increase. Satellite-derived biomass burning emissions can fill in gaps in the absence of aircraft or ground-based measurement campaigns and can help improve the online calculation of biomass burning emissions as well as the biomass burning emissions inventories that feed air quality models. This study focuses on satellite-derived NO_x emissions using the high-spatial-resolution TROPOspheric Monitoring Instrument (TROPOMI) NO₂ dataset. Advancements and improvements to the satellite-based determination of forest fire NO_x emissions are discussed, including information on plume height and effects of aerosol scattering and absorption on the satellite-retrieved vertical column densities. Two common top-down emission estimation methods, (1) an exponentially modified Gaussian (EMG) and (2) a flux method, are applied to synthetic data to determine the accuracy and the sensitivity to different parameters, including wind fields, satellite sampling, noise, lifetime, and plume spread. These tests show that emissions can be accurately estimated from single TROPOMI overpasses. The effect of smoke aerosols on TROPOMI NO₂ columns (via air mass factors, AMFs) is estimated, and these satellite columns and emission estimates are compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America. Our results indicate that applying an explicit aerosol correction to the TROPOMI NO₂ columns improves the agreement with the aircraft observations (by about 10 %–25 %). The aircraft- and satellite-derived emissions are in good agreement within the uncertainties. Both top-down emissions methods work well; however, the EMG method seems to output more consistent results and has better agreement with the aircraft-derived emissions. Assuming a Gaussian plume shape for various biomass burning plumes, we estimate an average NO_x e-folding time of 2 ±1 h from TROPOMI observations. Based on chemistry transport model simulations and aircraft observations, the net emissions of NO_x are 1.3 to 1.5 times greater than the satellite-derived NO₂ emissions. A correction factor of 1.3 to 1.5 should thus be used to infer net NO_x emissions from the satellite retrievals of NO₂.