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As a precursor of atmospheric aerosols, ammonia (NH3) is one of the primary gaseous air pollutants. Given its short atmospheric lifetime, ambient NH3 concentrations are dominated by local sources. In a recent study, Van Damme et al. (2018) have highlighted the importance of NH3 point sources, especially those associated with feedlots and industrial ammonia production. Their emissions were shown to be largely underestimated in bottom-up emission inventories. The discovery was made possible thanks to the use of oversampling techniques applied to 9 years of global daily IASI NH3 satellite measurements. Oversampling allows one to increase the spatial resolution of averaged satellite data beyond what the satellites natively offer. Here we apply for the first time superresolution techniques, which are commonplace in many fields that rely on imaging, to measurements of an atmospheric sounder, whose images consist of just single pixels. We demonstrate the principle on synthetic data and on IASI measurements of a surface parameter. Superresolution is a priori less suitable to be applied on measurements of variable atmospheric constituents, in particular those affected by transport. However, by first applying the wind-rotation technique, which was introduced in the study of other primary pollutants, superresolution becomes highly effective in mapping NH3 at a very high spatial resolution. We show that plume transport can be revealed in greater detail than what was previously thought to be possible. Next, using this wind-adjusted superresolution technique, we introduce a new type of NH3 map that allows tracking down point sources more easily than the regular oversampled average. On a subset of known emitters, the source could be located within a median distance of 1.5 km. We subsequently present a new global point-source catalog consisting of more than 500 localized and categorized point sources. Compared to our previous catalog, the number of identified sources more than doubled. In addition, we refined the classification of industries into five categories – fertilizer, coking, soda ash, geothermal and explosives industries – and introduced a new urban category for isolated NH3 hotspots over cities. The latter mainly consists of African megacities, as clear isolation of such urban hotspots is almost never possible elsewhere due to the presence of a diffuse background with higher concentrations. The techniques presented in this paper can most likely be exploited in the study of point sources of other short-lived atmospheric pollutants such as SO2 and NO2.

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.

Air pollution reaching hazardous levels in many Chinese cities has been a major concern in China over the past decades. New policies have been applied to regulate anthropogenic pollutant emissions, leading to changes in atmospheric composition and in particulate matter ( PM ) production. Increasing levels of atmospheric ammonia columns have been observed by satellite during recent years. In particular, observations from the Infrared Atmospheric Sounding Interferometer (IASI) reveal an increase of these columns by 15 % and 65 % from 2011 to 2013 and 2015, respectively, over eastern China. In this paper we performed model simulations for 2011, 2013 and 2015 in order to understand the origin of this increase and to quantify the link between ammonia and the inorganic components of particles: NH 4 ( p ) + / SO 4 ( p ) 2 - / NO 3 ( p ) - . Interannual change of meteorology can be excluded as a reason: year 2015 meteorology leads to enhanced sulfate production over eastern China, which increases the ammonium and decreases the ammonia content, which is contrary to satellite observations. Reductions in SO2 and NOx emissions from 2011 to 2015 of 37.5 % and 21 % respectively, as constrained from satellite data, lead to decreased inorganic matter (by 14 % for NH 4 ( p ) + + SO 4 ( p ) 2 - + NO 3 ( p ) - ). This in turn leads to increased gaseous NH3(g) tropospheric columns by as much as 24 % and 49 % (sampled corresponding to IASI data availability) from 2011 to 2013 and 2015 respectively and thus can explain most of the observed increase.

Ammonia (NH3) is an important agent involved in atmospheric chemistry and nitrogen cycling. Current estimates of NH3 emissions from biomass burning (BB) differ by more than a factor of 2, impeding a reliable assessment of their environmental consequences. Combining highresolution satellite observations of NH3 columns with network measurements of the concentration and stable nitrogen isotope composition (δ15N) of NH3, we present coherent estimates of the amount of NH3 derived from BB in the heartland of Southeast Asia, a tropical monsoon environment. Our results reveal a strong variability in atmospheric NH3 levels in time and space across different landscapes. All of the evidence on hand suggests that anthropogenic activities are the most important modulating control with respect to the observed patterns of NH3 distribution in the study area. Nisotope balance considerations revealed that during the intensive fire period, the atmospheric input from BB accounts for no more than 21 ± 5 % (1s) of the ambient NH3, even at the rural sites and in the proximity of burning areas. Our N-isotope-based assessment of the variation in the relative contribution of BB-derived NH3 is further validated independently through the measurements of particulate KC, a chemical tracer of BB. Our findings underscore that BB-induced NH3 emissions in tropical monsoon environments can be much lower than previously anticipated, with important implications for future modeling studies to better constrain the climate and air quality effects of wildfires., SCOPUS: ar.j, info:eu-repo/semantics/published

Excess atmospheric ammonia (NH3) leads to deleterious effects on biodiversity, ecosystems, air quality and health, and it is therefore essential to monitor its budget and temporal evolution. Hyperspectral infrared satellite sounders provide daily NH3 observations at global scale for over a decade. Here we use the version 3 of the Infrared Atmospheric Sounding Interferometer (IASI) NH3 dataset to derive global, regional and national trends from 2008 to 2018. We find a worldwide increase of 12.8 ± 1.3 % over this 11-year period, driven by large increases in east Asia (5.80 ± 0.61% increase per year), western and central Africa (2.58 ± 0.23 % yr−1), North America (2.40 ± 0.45 % yr−1) and western and southern Europe (1.90 ± 0.43 % yr−1). These are also seen in the Indo-Gangetic Plain, while the southwestern part of India exhibits decreasing trends. Reported national trends are analyzed in the light of changing anthropogenic and pyrogenic NH3 emissions, meteorological conditions and the impact of sulfur and nitrogen oxides emissions, which alter the atmospheric lifetime of NH3. We end with a short case study dedicated to the Netherlands and the ‘Dutch Nitrogen crisis' of 2019., info:eu-repo/semantics/published

Monthly, high-resolution (∼2 km) ammonia (NH3) column maps from the Infrared Atmospheric Sounding Interferometer (IASI) were developed across the contiguous United States and adjacent areas. Ammonia hotspots (95th percentile of the column distribution) were highly localized with a characteristic length scale of 12 km and median area of 152 km2. Five seasonality clusters were identified with k-means++ clustering. The Midwest and eastern United States had a broad, spring maximum of NH3 (67% of hotspots in this cluster). The western United States, in contrast, showed a narrower midsummer peak (32% of hotspots). IASI spatiotemporal clustering was consistent with those from the Ammonia Monitoring Network. CMAQ and GFDL-AM3 modeled NH3 columns have some success replicating the seasonal patterns but did not capture the regional differences. The high spatial-resolution monthly NH3 maps serve as a constraint for model simulations and as a guide for the placement of future, ground-based network sites., SCOPUS: ar.j, info:eu-repo/semantics/published

During the COVID-19 pandemic, the lockdown reduced anthropogenic emissions of NO2 in Paris. NO2 concentrations recorded in 2020 were the lowest they have been in the past 5 years. Despite these low-NO2 levels, Paris experienced PM2.5 pollution episodes, which were investigated here based on multi-species and multi-platform measurements. Ammonia (NH3 ) measurements over Paris, derived from a mini-DOAS (differential optical absorption spectroscopy) instrument and the Infrared Atmospheric Sounding Interferometer (IASI) satellite, revealed simultaneous enhancements during the spring PM2.5 pollution episodes. Using the IASI maps and the FLEXPART model, we show that long-range transport had a statistically significant influence on the degradation of air quality in Paris. In addition, concentrations of ammonium (NH4+ ) and PM2.5 were strongly correlated for all episodes observed in springtime 2020, suggesting that transport of NH3 drove a large component of the PM2.5 pollution over Paris. We found that NH3 was not the limiting factor for the formation of ammonium nitrate (NH4 NO3 ), and we suggest that the conversion of ammonia to ammonium may have been the essential driver., SCOPUS: ar.j, info:eu-repo/semantics/published

In recent years, ammonia emissions have been continuously increasing, being almost 4 times higher than in the 20th century. Although an important species, as its use as a fertilizer sustains human living, ammonia has major consequences for both humans and the environment because of its reactive gas-phase chemistry that makes it easily convertible to particles. Despite its pronounced importance, ammonia emissions are highly uncertain in most emission inventories. However, the great development of satellite remote sensing nowadays provides the opportunity for more targeted research on constraining ammonia emissions. Here, we used satellite measurements to calculate global ammonia emissions over the period 2008 2017. Then, the calculated ammonia emissions were fed to a chemistry transport model, and ammonia concentrations were simulated for the period 2008 2017. The simulated concentrations of ammonia were compared with ground measurements from Europe, North America and Southeastern Asia, as well as with satellite measurements. The satellite-constrained ammonia emissions represent global concentrations more accurately than state-of-theart emissions. Calculated fluxes in the North China Plain were seen to be more increased after 2015, which is not due to emission changes but due to changes in sulfate emissions that resulted in less ammonia neutralization and hence in larger atmospheric loads. Emissions over Europe were also twice as much as those in traditional datasets with dominant sources being industrial and agricultural applications. Four hot-spot regions of high ammonia emissions were seen in North America, which are characterized by high agricultural activity, such as animal breeding, animal farms and agricultural practices. South America is dominated by ammonia emissions from biomass burning, which causes a strong seasonality. In Southeastern Asia, ammonia emissions from fertilizer plants in China, Pakistan, India and Indonesia are the most important, while a strong seasonality was observed with a spring and late summer peak due to rice and wheat cultivation. Measurements of ammonia surface concentrations were better reproduced with satellite-constrained emissions, such as measurements from CrIS (Cross-track Infrared Sounder)., SCOPUS: ar.j, info:eu-repo/semantics/published

International audience; The agricultural sector in Syria was heavily affected by the civil war that started in 2011. We investigate the war's impact on the country's atmospheric ammonia (NH 3) from 2008 to 2019, using measurements from the infrared atmospheric sounding interferometer instrument on board the Metop satellites. We examine the changes in NH 3 close to a fertilizer industry, whose activities were suspended due to conflict-related events. We also explore the effect of war-induced land use/land cover changes on agriculture-emitted ammonia in northeast Syria that has witnessed battles between different groups. The interpretation of the changes in NH 3 is supported by different datasets: visible satellite imagery to assess the effect on industrial activity, reanalysis data from the European center for medium-range weather forecasts to look at the effect of meteorology (temperature, wind speed, and precipitation), and land cover and burned area products from the moderate resolution imaging spectroradiometer (MODIS) to examine land use/land cover changes and fire events during the study period. We show that the NH 3 columns are directly affected by the war. Periods of intense conflict are reflected in lower values over the industry reaching-17%,-47%, and-32% in 2013, 2014, and 2016, respectively, compared to the [2008-2012] average, and a decrease reaching-14% and-15% in the croplands' area in northeast Syria during 2017 and 2018 (compared to 2011), respectively. Toward the end of the control of Islamic State in Iraq and Syria, an increase in atmospheric NH 3 was accompanied by an increase in croplands' area that reached up to þ35% in 2019 as compared to prewar (2011). This study shows the relevance of remote-sensing data of atmospheric composition in studying societal changes at a local and regional scale.

International audience; Satellite ammonia (NH3) observations provide unprecedented insights into NH3 emissions, spatiotemporal variabilities and trends, but validation with in‐situ measurements remains lacking. Here, total columns from the Infrared Atmospheric Sounding Interferometer (IASI) were intercompared to boundary layer NH3 profiles derived from aircraft‐ and surface‐based measurements primarily in Colorado, USA, in the summer of 2014. IASI‐NH3 version 3 near real‐time dataset compared well to in‐situ derived columns (windows ±15 km around centroid, ±1 hour around overpass time) with a correlation of 0.58, a slope of 0.78±0.14, and an intercept of 2.1×1015±1.5×1015 molecules cm‐2. Agreement degrades at larger spatiotemporal windows, consistent with the short atmospheric lifetime of NH3. We also examined IASI version 3R data, which relies on temperature retrievals from the ERA Reanalysis, and a third product generated using aircraft‐measured temperature profiles. The overall agreement improves slightly for both cases, and neither is biased within their combined measurement errors. Thus, spatiotemporal averaging of IASI over large windows can be used to reduce retrieval noise. Nonetheless, sampling artifacts of airborne NH3 instruments result in significant uncertainties of the in‐situ‐derived columns. For example, large validation differences exist between ascent and descent profiles, and the assumptions of the free tropospheric NH3 profiles used above the aircraft ceiling significantly impact the validation. Because short‐lived species like NH3 largely reside within the boundary layer with complex vertical structures, more comprehensive validation is needed across a wide range of environments. More accurate and widespread in‐situ NH3 datasets are therefore required for improved validations of satellite products.

Atmospheric ammonia (NH3) is a precursor to fine particulate matter and a source of nitrogen (N) deposition that can adversely affect ecosystem health. The main sources of NH3 – agriculture and biomass burning – are undergoing or expected to undergo substantial changes in Africa. Although evidence of increasing NH3 over parts of Africa has been observed, the mechanisms behind these trends are not well understood. Here we use observations of atmospheric NH3 vertical column densities (VCDs) from the Infrared Atmospheric Sounding Interferometer (IASI) along with other satellite observations of the land surface and atmosphere to evaluate how NH3 concentrations have changed over Africa from 2008 through 2017, and what has caused those changes. We find that NH3 VCDs have increased over several regions, including much of West Africa and parts of the Lake Victoria Basin. In West Africa NH3 VCDs are observed to increase during the late dry season, with increases of over 6 % yr−1 in Nigeria during February and March. These positive trends are associated with increasing burned area and CO trends during these months, likely related to agricultural preparation. Increases are also observed in the Lake Victoria Basin, where they are associated with expanding agricultural area. In contrast, South Sudan NH3 VCDs declined by over 2 % yr−1 during the February through May period, with the largest rates of change over the Sudd wetlands. Annual maxima in NH3 VCDs in South Sudan occur during February through May and are associated with drying of temporarily flooded wetland soils, which favor emissions of NH3. The change in mean NH3 VCDs over the Sudd and all of South Sudan during February through May is strongly correlated with variation in wetland extent in the Sudd: in years when more area remained flooded during the dry season, NH3 concentrations were higher (r = 0.69, p = 0.03). Relationships between agriculture and NH3 can be observed when evaluating national-scale statistics: countries with the largest declines in NH3 VCDs concentrations over time tended to have the smallest growth rates in crop productivity and livestock numbers as well as smaller negative changes in burned area than other countries. Fertilizer use in Africa is currently low but growing; implementing practices that can limit NH3 losses from fertilizer as agriculture is intensified may help mitigate impacts on health and ecosystems.

Ammonia (NH3) is a major source of nitrates in the atmosphere, and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, three years of surface in-situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the observational footprint of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.46 %/year from 2002 to 2018 in the FTIR columns, 8.88 ± 2.83 %/year from 2013 to 2017 in the surface in-situ data, and 8.38 ± 0.77 %/year from 2008 to 2018 in the IASI columns. To assess the observational footprint of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤ 25 km and ≤ 20 minutes, with r = 0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in-situ measurements were standardized and correlated. Comparison of 24-day averages and monthly averages resulted in correlation coefficients of r = 0.72 and r = 0.75, respectively, although correlation without resampling to reduce high-frequency variability led to a poorer correlation, with r = 0.39. The GEOS-Chem model, run at 2° × 2.5° resolution, was compared against FTIR and IASI to assess model performance and investigate correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35° N to 53° N, and 93.75° W to 63.75° W) resulted in r = 0.57, and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2 = 0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2 = 0.13, indicating that a finer spatial resolution is needed for modeling NH3.

Husbandry trace gases that have climate change implications such as carbon dioxide (CO2), methane (CH4) and ammonia (NH3) can be quantified through remote sensing; however, many husbandry gases with health implications such as hydrogen sulfide (H2S), cannot. This pilot study demonstrates an approach to derive H2S concentrations by coupling in situ and remote sensing data. Using AMOG (AutoMObile trace Gas) Surveyor, a mobile air quality and meteorology laboratory, we measured in situ concentrations of CH4, CO2, NH3, H2S, and wind at a southern California university research dairy. Emissions were 0.13, 1.93, 0.022 and 0.0064 Gg yr-1; emission factors (EF) were 422, 6333, 74, and 21 kg cow-1 yr-1, respectively, for the 306 head herd. Contributing to these strong EF were spillway emissions from a grate between the main cowshed and the waste lagoon identified in airborne remote sensing data acquired by the hyperspectral thermal infrared imager, Mako. NH3 emissions from the Chino Dairy Complex, also in southern California, were calculated from Infrared Atmospheric Sounding Interferometer (IASI) satellite data for 2008-2017 using average morning winds, yielding a flushing time of 2.7 h, and 8.9 Gg yr-1. The ratio of EF(H2S) to EF(NH3) for the research dairy from AMOG data were applied to IASI NH3 emissions to derive H2S exposure concentration maps for the Chino area, which ranged to 10-30 ppb H2S for many populated areas. Combining remote sensing with in situ concentrations of multiple emitted gases can allow derivation of emissions at the sub-facility, facility, and larger scales, providing spatial and temporal coverage that can translate into exposure estimates for use in epidemiology studies and regulation development. Furthermore, with high fidelity information at the sub-facility level we can identify best practices and opportunities to sustainably and holistically reduce husbandry emissions., info:eu-repo/semantics/published

Satellite remote sensing of the Earth's atmospheric composition usually samples irregularly in space and time, and many applications require spatially and temporally averaging the satellite observations (level 2) to a regular grid (level 3). When averaging level 2 data over a long period to a target level 3 grid that is significantly finer than the sizes of level 2 pixels, this process is referred to as. An agile, physics-based oversampling approach is developed to represent each satellite observation as a sensitivity distribution on the ground, instead of a point or a polygon as assumed in previous methods. This sensitivity distribution can be determined by the spatial response function of each satellite sensor. A generalized 2-D super Gaussian function is proposed to characterize the spatial response functions of both imaging grating spectrometers (e.g. OMI, OMPS, and TROPOMI) and scanning Fourier transform spectrometers (e.g. GOSAT, IASI, and CrIS). Synthetic OMI and IASI observations were generated to compare the errors due to simplifying satellite fields of view (FOVs) as polygons (tessellation error) and the errors due to discretizing the smooth spatial response function on a finite grid (discretization error). The balance between these two error sources depends on the target grid size, the ground size of the FOV, and the smoothness of spatial response functions. Explicit consideration of the spatial response function is favorable for fine-grid oversampling and smoother spatial response. For OMI, it is beneficial to oversample using the spatial response functions for grids finer than ∼ 16 km. The generalized 2-D super Gaussian function also enables smoothing of the level 3 results by decreasing the shape-determining exponents, which is useful for a high noise level or sparse satellite datasets. This physical oversampling approach is especially advantageous during smaller temporal windows and shows substantially improved visualization of trace gas distribution and local gradients when applied to OMI NO2 products and IASI NH3 products. There is no appreciable difference in the computational time when using the physical oversampling versus other oversampling methods., SCOPUS: ar.j, info:eu-repo/semantics/published

Recently, Whitburn et al.(2016) 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).

China is a global hotspot of atmospheric ammonia (NH3) emissions and, as a consequence, very high nitrogen (N) deposition levels are documented. However, previous estimates of total NH3 emissions in China were much lower than inference from observed deposition values would suggest, highlighting the need for further investigation. Here, we reevaluated NH3 emissions based on a mass balance approach, validated by N deposition monitoring and satellite observations, for China for the period of 2000 to 2015. Total NH3 emissions in China increased from 12.1±0.8 Tg N yr-1 in 2000 to 15.6±0.9 Tg N yr-1 in 2015 at an annual rate of 1.9%, which is approximately 40% higher than existing studies suggested. This difference is mainly due to more emission sources now having been included and NH3 emission rates from mineral fertilizer application and livestock having been underestimated previously. Our estimated NH3 emission levels are consistent with the measured deposition of NHx (including NH4+ and NH3) on land (11-14 Tg N yr-1) and the substantial increases in NH3 concentrations observed by satellite measurements over China. These findings substantially improve our understanding on NH3 emissions, implying that future air pollution control strategies have to consider the potentials of reducing NH3 emission in China.

Vegetation fires are a major source of ammonia (NH3) in the atmosphere. Their emissions are mainly estimated using bottom-up approaches that rely on uncertain emission factors. In this study, we derive new biome-specific NH3 enhancement ratios relative to carbon monoxide (CO), ERNH3 ∕ CO (directly related to the emission factors), from the measurements of the IASI sounder onboard the Metop-A satellite. This is achieved for large tropical regions and for an 8-year period (2008–2015). We find substantial differences in the ERNH3 ∕ CO ratios between the biomes studied, with calculated values ranging from 7 × 10−3 to 23 × 10−3. For evergreen broadleaf forest these are typically 50–75 % higher than for woody savanna and savanna biomes. This variability is attributed to differences in fuel types and size and is in line with previous studies. The analysis of the spatial and temporal distribution of the ERNH3 ∕ CO ratio also reveals a (sometimes large) within-biome variability. On a regional level, woody savanna shows, for example, a mean ERNH3 ∕ CO ratio for the region of Africa south of the Equator that is 40–75 % lower than in the other five regions studied, probably reflecting regional differences in fuel type and burning conditions. The same variability is also observed on a yearly basis, with a peak in the ERNH3 ∕ CO ratio observed for the year 2010 for all biomes. These results highlight the need for the development of dynamic emission factors that take into better account local variations in fuel type and fire conditions. We also compare the IASI-derived ERNH3 ∕ CO ratio with values reported in the literature, usually calculated from ground-based or airborne measurements. We find general good agreement in the referenced ERNH3 ∕ CO ratio except for cropland, for which the ERNH3 ∕ CO ratio shows an underestimation of about 2–2.5 times.

Concentrated agricultural activities and animal feeding operations in the northeastern plains of Colorado represent an important source of atmospheric ammonia (NH3). The NH3 from these sources contributes to regional fine particle formation and to nitrogen deposition to sensitive ecosystems in Rocky Mountain National Park (RMNP), located ∼80 km to the west. In order to better understand temporal and spatial differences in NH3 concentrations in this source region, weekly concentrations of NH3 were measured at 14 locations during the summers of 2010 to 2015 using Radiello passive NH3 samplers. Weekly (biweekly in 2015) average NH3 concentrations ranged from 2.66 to 42.7μ-3, with the highest concentrations near large concentrated animal feeding operations (CAFOs). The annual summertime mean NH3 concentrations were stable in this region from 2010 to 2015, providing a baseline against which concentration changes associated with future changes in regional NH3 emissions can be assessed. Vertical profiles of NH3 were also measured on the 300 m Boulder Atmospheric Observatory (BAO) tower throughout 2012. The highest NH3 concentration along the vertical profile was always observed at the 10 m height (annual average concentration of 4.63 μgm-3), decreasing toward the surface (4.35g μg-3) and toward higher altitudes (1.93g μg-3). The NH3 spatial distributions measured using the passive samplers are compared with NH3 columns retrieved by the Infrared Atmospheric Sounding Interferometer (IASI) satellite and concentrations simulated by the Comprehensive Air Quality Model with Extensions (CAMx). The satellite comparison adds to a growing body of evidence that IASI column retrievals of NH3 provide very useful insight into regional variability in atmospheric NH3, in this case even in a region with strong local sources and sharp spatial gradients. The CAMx comparison indicates that the model does a reasonable job simulating NH3 concentrations near sources but tends to underpredict concentrations at locations farther downwind. Excess NH3 deposition by the model is hypothesized as a possible explanation for this trend., SCOPUS: ar.j, info:eu-repo/semantics/published

Agriculture is the main source of ammonia (NH3) in France, an important gaseous precursor of atmospheric particulate matter (PM). National and global emission inventories are known to have difficulty representing the large spatial and temporal variability inherent to atmospheric NH3. In this study, we compare NH3 emissions in France during spring 2011 from one reference inventory, the TNO inventory, and two alternative inventories that account in different manners for both the spatial and temporal variabilities of the emissions: (i) the NH3SAT satellite-derived inventory based on IASI NH3 columns and (ii) the CADASTRE-CIT inventory that combines NH3 emissions due to nitrogen fertilization calculated with the mechanistic model VOLT'AIR on the database of the CADASTRE_NH3 framework and other source emissions from the CITEPA. The total spring budgets, from March to May 2011, at the national level are higher when calculated with both alternative inventories than with the reference, the difference being more marked with CADASTRE-CIT. NH3SAT and CADASTRE-CIT inventories both yield to large NH3 spring emissions due to fertilization on soils with high pH in the northeastern part of France (65 and 135 ktNH3, respectively, vs. 48 ktNH3 for TNO-GEN), while soil properties are not accounted for by the TNO-GEN methodology. For the other parts of France, the differences are smaller. The timing of fertilization and associated ammonia emissions is closely related to the nitrogen requirements and hence the phenological stage of the crops, and therefore to the crop year's specific weather conditions. Maximum emissions are observed in March for 2011 for some regions for both alternative inventories, while April is the period with maximum emissions for the reference inventory regardless of the region or the year. Comparing the inventories at finer temporal resolutions, typically at daily scale, large differences are found. The convergence of alternative, independent and complementary methods on the spatiotemporal representation of the spring NH3 emissions, particularly over areas where the contribution of mineral fertilizer spreading to the spring budget is strong, encourages further developments in both prospective complementary directions, as this will help improve national NH3 emission inventories., SCOPUS: ar.j, info:eu-repo/semantics/published

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 human kind. The current emission levels however, are up to four 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 the 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) agricultural and industrial point sources from CrIS satellite observations across the globe with a consistent methodology. The same methodology is also applied to the 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 hours. 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 HTAPv2 emission inventory, and only 72 locations with emissions within a factor 2 compared to the inventories. We find a total of 5622 kt/yr, for the sources analyzed in this study, which is equivalent to a factor ~ 2.5 between the CrIS estimated and HTAPv2 emissions. 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.

As a precursor of atmospheric aerosols, ammonia (NH3) is one the primary gaseous air pollutants. Given its short atmospheric lifetime, ambient NH3 concentrations are dominated by local sources. In a recent study, Van Damme et al. (2018) have highlighted the importance of NH3 point sources, especially those associated with feedlots and industrial ammonia production. Their emissions were shown to be largely underestimated in bottom-up emission inventories. The discovery was made possible thanks to the use of oversampling techniques applied on 9 years of global daily IASI NH3 satellite measurements. Oversampling allows to increase the spatial resolution of averaged satellite data, beyond what the satellites natively offer. Here, we apply for the first time the so-called superresolution techniques, which are commonplace in many fields that rely on imaging, to measurements of an atmospheric sounder, whose images consist of just single pixels. We demonstrate the principle on synthetic data and on IASI measurements of a surface parameter. Superresolution is a priori less suitable to be applied on measurements of variable atmospheric constituents, in particular those affected by transport. However, by first applying the so-called wind-rotation technique, which was introduced in the study of other primary pollutants, superresolution becomes highly effective to map NH3 at very high spatial resolution. We show in particular that it allows revealing plume transport in much greater detail than what was previously thought to be possible. Next, using this wind-adjusted superresolution technique, we introduce a new type of NH3 map that allows to track down point sources much more easily than the regular oversampled average. On a subset of known emitters, it allows to locate the source within a median distance of 1.5 km. We subsequently present a new global point source catalog consisting of more than 500 localized and categorized point sources. Compared to our previous catalog, the number of identified sources more than doubled. In addition, we refined the classification of industries into five categories: fertilizer, coking, soda ash, geothermal and explosive industry; and introduced a new urban category for isolated NH3 hotspots over cities. The latter mainly consists of African megacities, as clear isolation of such urban hotspots is almost never possible elsewhere due to the presence of a larger diffuse background. The techniques presented in this paper can most likely be exploited in the study of point sources of other short-lived atmospheric pollutants such as SO2 and NO2.

The Paris megacity experiences frequent particulate matter (PM2.5, PM with a diameter less than 2.5 μm) pollution episodes in springtime (March–April). At this time of the year, large parts of the particles consist of ammonium sulfate and nitrate which are formed from ammonia (NH3) released during fertilizer spreading practices and transported from the surrounding areas to Paris. There is still limited knowledge on the emission sources around Paris, their magnitude and seasonality. Using space-borne NH3 observation records of 10-years (2008–2017) and 5-years (2013–2017) provided by the Infrared Atmospheric Sounding Interferometer (IASI) and the Cross-Track Infrared Sounder (CrIS) instrument, regional pattern of NH3 variabilities (seasonal and inter-annual) are derived. Observations reveal identical high seasonal variabilities with three major NH3 hot spots found from March to August. The high inter-annual variability is discussed with respect to atmospheric total precipitation and temperature. A detailed analysis of the seasonal cycle is performed using both IASI and the CrIS instrument data, together with outputs from the CHIMERE atmospheric model. For months of high NH3 concentrations (March to August) the CHIMERE model shows good correspondence with correlation slopes of 0.98 and 0.71 when comparing with IASI and CrIS, respectively. It is found that the model is only able to reproduce half of the observed atmospheric temporal NH3 variability in the domain. In term of spatial variability, the CHIMERE monthly NH3 concentrations in springtime show a slight underrepresentation over Belgium and the United-Kingdom and overrepresentation in agricultural areas in the French Brittany/Pays de la Loire and Plateau du Jura region, as well as in the north part of Switzerland. Using HYSPLIT cluster analysis of back-trajectories, we show that NH3 total columns measured in spring over Paris are enhanced when air masses are originated from the Northeast (e. g., Netherlands and Belgium), highlighting the long-range transport importance on the NH3 budget over Paris. Finally, we quantify the key meteorological parameters driving the specific conditions important for the PM2.5 formation from NH3 in the Ile-de-France region in springtime. Data-driven results based on surface PM2.5 measurements from the Airparif network and IASI NH3 observations show that a combination of the factors, e. g. a low boundary layer of ~500 m, a relatively low temperature of 5 °C and a high relative humidity of 70 %, contributes to favor PM2.5 and NH3 correlation.

Global distributions of atmospheric ammonia (NH3) measured with satellite instruments such as the Infrared Atmospheric Sounding Interferometer (IASI) contain valuable information on NH3 concentrations and variability in regions not yet covered by ground-based instruments. Due to their large spatial coverage and (bi-)daily overpasses, the satellite observations have the potential to increase our knowledge of the distribution of NH3 emissions and associated seasonal cycles. However the observations remain poorly validated, with only a handful of available studies often using only surface measurements without any vertical information. In this study, we present the first validation of the IASI-NH3 product using ground-based Fourier transform infrared spectroscopy (FTIR) observations. Using a recently developed consistent retrieval strategy, NH3 concentration profiles have been retrieved using observations from nine Network for the Detection of Atmospheric Composition Change (NDACC) stations around the world between 2008 and 2015. We demonstrate the importance of strict spatio-temporal collocation criteria for the comparison. Large differences in the regression results are observed for changing intervals of spatial criteria, mostly due to terrain characteristics and the short lifetime of NH3 in the atmosphere. The seasonal variations of both datasets are consistent for most sites. Correlations are found to be high at sites in areas with considerable NH3 levels, whereas correlations are lower at sites with low atmospheric NH3 levels close to the detection limit of the IASI instrument. A combination of the observations from all sites (Nobs = 547) give a mean relative difference of −32.4 ± (56.3) %, a correlation r of 0.8 with a slope of 0.73. These results give an improved estimate of the IASI-NH3 product performance compared to the previous upper-bound estimates (−50 to +100 %).

From 17–22 August 2017 simultaneous enhancements of ammonia (NH3), carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) were detected from ground-based solar absorption Fourier transform infrared (FTIR) spectroscopic measurements at two high-Arctic sites: Eureka (80.05°N, 86.42°W) Nunavut, Canada, and Thule (76.53°N, 68.74°W), Greenland. These enhancements were attributed to wildfires in British Columbia and the Northwest Territories of Canada using FLEXPART back-trajectories and fire locations from Moderate Resolution Imaging Spectroradiometer (MODIS) and found to be the greatest observed enhancements in more than a decade of measurements at Eureka (2006–2017) and Thule (1999–2017). Observations of gas-phase NH3 from these wildfires illustrate that boreal wildfires may be a considerable episodic source of NH3 in the summertime high Arctic. Comparisons of GEOS-Chem model simulations using the Global Fire Assimilation System (GFASv1.2) biomass burning emissions to FTIR measurements and Infrared Atmospheric Sounding Interferometer (IASI) measurements showed that the transport of wildfire emissions to the Arctic was underestimated in GEOS-Chem. However, GEOS-Chem simulations showed that these wildfires contributed to surface layer NH3 and NH4 + enhancements of 0.01–0.11 ppbv and 0.05–1.07 ppbv, respectively, over the Canadian Archipelago from 15–23 August 2017., SCOPUS: ar.j, info:eu-repo/semantics/published

International audience; Through its important role in the formation of particulate matter, atmospheric ammonia affects air quality and has implications for human health and life expectancy1,2. Excess ammonia in the environment also contributes to the acidification and eutrophication of ecosystems3,4,5 and to climate change6. Anthropogenic emissions dominate natural ones and mostly originate from agricultural, domestic and industrial activities7. However, the total ammonia budget and the attribution of emissions to specific sources remain highly uncertain across different spatial scales7,8,9. Here we identify, categorize and quantify the world’s ammonia emission hotspots using a high-resolution map of atmospheric ammonia obtained from almost a decade of daily IASI satellite observations. We report 248 hotspots with diameters smaller than 50 kilometres, which we associate with either a single point source or a cluster of agricultural and industrial point sources—with the exception of one hotspot, which can be traced back to a natural source. The state-of-the-art EDGAR emission inventory10 mostly agrees with satellite-derived emission fluxes within a factor of three for larger regions. However, it does not adequately represent the majority of point sources that we identified and underestimates the emissions of two-thirds of them by at least one order of magnitude. Industrial emitters in particular are often found to be displaced or missing. Our results suggest that it is necessary to completely revisit the emission inventories of anthropogenic ammonia sources and to account for the rapid evolution of such sources over time. This will lead to better health and environmental impact assessments of atmospheric ammonia and the implementation of suitable nitrogen management strategies.

Air pollution, reaching hazardous levels in many Chinese cities has been a major concern in China over the past decades. New policies have been applied to regulate anthropogenic pollutant emissions, leading to changes in atmospheric composition and in particulate matter (PM) production. Increasing levels of atmospheric ammonia columns have been observed by satellite during the last years, in particular IASI observations reveal an increase of these columns by 15 % and 65 % from 2011 to 2013 and 2015, respectively, over Eastern China. In this paper we have performed model simulations for 2011, 2013 and 2015 in order to understand the origin of this increase, and in particular to quantify the link between ammonia and the inorganic components of particles: NH4(p)+ / SO4(p)2− / NO3(p)−. Interannual change of meteorology can be excluded as a reason: year 2015 meteorology leads to enhanced sulphate production over Eastern China which increases the ammonium and decreases the ammonia content which is contrary to satellite observations. Reductions in SO2 and NOX emission between 2011 and 2015 of respectively −37.5 and −21 %, as constrained from satellite data, lead to decreased inorganic matter (by 14 % for NH4(p)+ + SO4(p)2− + NO3(p)−). This in turn leads to increased gaseous NH3(g) tropospheric columns, by as much as 24 % and 49 % (sampled corresponding to IASI data availability) from 2011 to 2013 and 2015 respectively, and thus can explain most of the observed increase.

Mobile in situ concentration and meteorology data were collected for the Chino Dairy Complex in the Los Angeles Basin by AMOG (AutoMObile trace Gas) Surveyor on 25 June 2015 to characterize husbandry emissions in the near and far field in convoy mode with MISTIR (Mobile Infrared Sensor for Tactical Incident Response), a mobile upwards-looking, column remote sensing spectrometer. MISTIR reference flux validated AMOG plume inversions at different information levels including multiple gases, GoogleEarth imagery, and airborne trace gas remote sensing data. Long-term (9-yr.) Infrared Atmospheric Sounding Interferometer satellite data provided spatial and trace gas temporal context. For the Chino dairies, MISTIR-AMOG ammonia (NH3) agreement was within 5% (15.7 versus 14.9 Gg yr−1, respectively) using all information. Methane (CH4) emissions were 30 Gg yr−1 for a 45,200 herd size, indicating that Chino emission factors are greater than previously reported. Single dairy inversions were much less successful. AMOG-MISTIR agreement was 57% due to wind heterogeneity from downwind structures in these near-field measurements and emissions unsteadiness. AMOG CH4, NH3, and CO2 emissions were 91, 209, and 8200 Mg yr−1, implying 2480, 1870, and 1720 head using published emission factors. Plumes fingerprinting identified likely sources including manure storage, cowsheds, and a structure with likely natural gas combustion. NH3 downwind of Chino showed a seasonal variation of a factor of ten, three times larger than literature suggests. Chino husbandry practices and trends in herd size and production were reviewed and unlikely to add seasonality. Higher emission seasonality was proposed as legacy soil emissions, the results of a century of husbandry, supported by airborne remote sensing data showing widespread emissions from neighborhoods that were dairies 15 years prior, and AMOG and MISTIR observations. Seasonal variations provide insights into the implications of global climate change and must be considered when comparing surveys from different seasons. Where sufficient information from multiple gases and number of likely sources, high emissions accuracy can be achieved for in situ data plume inversion., SCOPUS: ar.j, info:eu-repo/semantics/published

In this paper we investigate a severe pollution episode that occurred in Beijing, Tianjin, and the Hebei province in January 2013. The episode was caused by the combination of anthropogenic emissions and a high-pressure system that trapped pollutants in the boundary layer. Using IASI (Infrared Atmospheric Sounding Interferometer) satellite measurements, high concentrations of key trace gases such as carbon monoxide (CO), sulfur dioxide (SO2), and ammonia (NH3) along with ammonium sulfate aerosol ((NH4)2SO4) are found. We show that IASI is able to detect boundary layer pollution in case of large negative thermal contrast combined with high levels of pollution. Our findings demonstrate that anthropogenic key pollutants, such as CO and SO2, can be monitored by IASI in the North China Plain during wintertime in support of air quality evaluation and management.

Part of the ISSI Scientific Report Series volume 16; International audience; In this chapter we describe what is achievable in terms of pollutant tracking from space using observations provided by thermal infrared remote sensors. After a general introduction on infrared remote sensing, we exploit the data provided by the Infrared Atmospheric Sounding Interferometer (IASI) missions onboard the Metop series of satellite to illustrate pollution detection at various spatial and temporal scales. Then, we focus on air pollution over China and discuss three case studies involving different pollutants. The first example discusses the geophysical conditions for detection of ammonia (NH3) and sulfur dioxide (SO2), both precursors of particulate matter (PM). The second case illustrates the seasonal variation of ozone (O3), in particular during the monsoon period. The third case shows the local accumulation of enhanced levels of carbon monoxide (CO) when pollution episodes occur.

Methane (CH4) and ammonia (NH3) directly and indirectly affect the atmospheric radiative balance with the latter leading to aerosol generation. Both have important spectral features in the Thermal InfraRed (TIR) that can be studied by remote sensing, with NH3 allowing discrimination of husbandry from other CH4 sources. Airborne hyperspectral imagery was collected for the Chino Dairy Complex in the Los Angeles Basin as well as in situ CH4, carbon dioxide (CO2) and NH3 data. TIR data showed good spatial agreement with in situ measurements and showed significant emissions heterogeneity between dairies. Airborne remote sensing mapped plume transport for ∼20 km downwind, documenting topographic effects on plume advection. Repeated multiple gas in situ measurements showed that emissions were persistent on half-year timescales. Inversion of one dairy plume found annual emissions of 4.1 × 105 kg CH4, 2.2 × 105 kg NH3, and 2.3 × 107 kg CO2, suggesting 2300, 4000, and 2100 head of cattle, respectively, and Chino Dairy Complex emissions of 42 Gg CH4 and 8.4 Gg NH3 implying ∼200k cows, ∼30% more than Peischl et al. (2013) estimated for June 2010. Far-field data showed chemical conversion and/or deposition of Chino NH3 occurs within the confines of the Los Angeles Basin on a four to six h timescale, faster than most published rates, and likely from higher Los Angeles oxidant loads. Satellite observations from 2011 to 2014 confirmed that observed in situ transport patterns were representative and suggests much of the Chino Dairy Complex emissions are driven towards eastern Orange County, with a lesser amount transported to Palm Springs, CA. Given interest in mitigating husbandry health impacts from air pollution emissions, this study highlights how satellite observations can be leveraged to understand exposure and how multiple gas in situ emissions studies can inform on best practices given that emissions reduction of one gas could increase those of others.

Global distributions of atmospheric ammonia (NH3) measured with satellite instruments such as the Infrared Atmospheric Sounding Interferometer (IASI) contain valuable information on NH3 concentrations and variability in regions not yet covered by ground based instruments. Due to their large spatial coverage and daily observations, the satellite observations have the potential to increase our knowledge of the distribution of NH3 emissions, and associated seasonal cycles. However the observations remain poorly validated, with only a handful of available studies often using only surface observations without any vertical information. In this study, we present the first validation of the IASI-NH3 product using ground-based Fourier Transform InfraRed (FTIR) observations. Using a recently developed consistent retrieval strategy, NH3 concentration profiles have been retrieved using observations from nine Network for the Detection of Atmospheric Composition Change (NDACC) stations around the world between 2008–2015. We demonstrate the importance of strict spatio-temporal collocation criteria for the comparison. Large differences in the regression results are observed for changing intervals of spatial criteria, mostly due to terrain characteristics and the short lifetime of NH3 in the atmosphere. The seasonal variations of both datasets are consistent for most sites. Correlations are found to be high at sites in areas with considerable NH3 levels, whereas correlations are lower at sites with low atmospheric NH3 levels close to the detection limit of the IASI instrument. A combination of the observations from all sites (Nobs = 547) give a MRD of −32.4 ± (56.3) %, a correlation r of 0.8 with a slope of 0.73. These results indicate that the IASI-NH3 product performs better than previous upper bound estimates (-50% – +100 %).

International audience; The IASI mission flying onboard the MetOp satellites has been providing global observations of the air composition twice a day since 2007. From the atmospheric spectra recorded by the instruments in the thermal infrared spectral range, concentrations of a series of trace gases can be monitored, enhanced levels of pollution can be detected, and particle types can be determined to some extent. This paper recalls the historical context for the IASI remote sensor, reviews its capability to observe some key species for global and regional pollution monitoring, and reports on information services that benefit from the mission.

Existing descriptions of bi-directional ammonia (NH 3 ) land–atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH 3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH 3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH 3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH 3 emission–deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28–67%). Together with increased anthropogenic activity, global NH 3 emissions may increase from 65 (45–85) Tg N in 2008 to reach 132 (89–179) Tg by 2100.

International audience; Atmospheric ammonia (NH3) has recently been observed with infrared sounders from space. Here we present 1 year of detailed bidaily satellite retrievals with the Infrared Atmospheric Sounding Interferometer and some retrievals of the Tropospheric Emission Spectrometer over the San Joaquin Valley, California, a highly polluted agricultural production region. Several sensitivity issues are discussed related to the sounding of ammonia, in terms of degrees of freedom, averaging kernels, and altitude of maximum sensitivity and in relation to thermal contrast and concentration. We also discuss their seasonal dependence and sources of errors. We demonstrate boundary layer sensitivity of infrared sounders when there is a large thermal contrast between the surface and the bottom of the atmosphere. For the San Joaquin Valley, large thermal contrast is the case for daytime measurements in spring, summer, and autumn and for nighttime measurements in autumn and winter when a large negative thermal contrast is amplified by temperature inversion.