Interferometer Satellite Research Articles

Interannual variability of atmospheric ammonia over the Sichuan Basin, southwestern China: Trend, sources, and implications on particle matter control

Atmospheric ammonia (NH3) is an important constituent of biogeochemical cycle and excessive NH3 in the environment results in detrimental effects on ecosystems, air quality, and human health. However, interannual variability and emission changes of NH3 remain highly uncertain, particularly for NH3 hotspot areas. Here, we identify the emission hotspots of NH3 and reveal the trend of NH3 emissions over the Sichuan Basin (SCB) based on a high-resolution map from infrared Atmospheric Sounding Interferometer (IASI) satellite observations in combination with the MEIC inventory from 2008 to 2019. IASI observations indicate that NH3 columns persistent increase over time while MEIC inventory suggests that the past increase in NH3 emissions has indeed ended in 2017 and exhibit decreasing trend afterwards. The NH3 hotspots derived from IASI mainly concentrate in the Chengdu Plain and southern SCB city cluster, which mostly agrees with MEIC emission inventory. CMAQ model simulations well reproduce PM2.5 and ammonia loading and capture observed patterns of NH3. We find that ammonium makes up 15–35% of inorganic fine PM2.5 mass in winter over the SCB. Regulation efforts focused on joint reducing 30% of NOx, SO2, and NH3 emissions could lead to basin-wide wintertime PM2.5 reduce by 10.0 μg/m3, while cutting 30% emissions of NH3 or NOx alone only yield PM2.5 reduced by 0.8 and 5.0 μg/m3, respectively. This work contributes insights on the trend and spatial pattern of NH3 source over the SCB and reveals the critical role of regulating NH3 emissions in mitigating PM2.5 pollution, shedding insights on nitrogen management strategies

Exceptional Wildfire Enhancements of PAN, C2H4, CH3OH, and HCOOH Over the Canadian High Arctic During August 2017

AbstractExtreme enhancements in the total columns of carbon monoxide (CO), peroxyacetyl nitrate (PAN), ethylene (C2H4), methanol (CH3OH), and formic acid (HCOOH) were observed over the Canadian high Arctic during the period of 17–22 August 2017 by a ground‐based Fourier transform infrared (FTIR) spectrometer at Eureka, Nunavut (80.05°N, 86.42°W), and by the Infrared Atmospheric Sounding Interferometer (IASI) satellite instruments. These enhancements have been attributed to wildfires in British Columbia (BC) and the Northwest Territories (NWT) of Canada, and represent the largest short‐term perturbations of PAN, C2H4, and HCOOH above ambient concentrations over the 14‐year (2006–2020) Eureka time‐series. Enhancement ratios, emission ratios, and emission factors relative to CO were calculated for all species for both FTIR and IASI observations. The C2H4 and HCOOH emission factors are significantly larger than previous studies, suggesting unusually high emissions from these fires. The wildfire plumes were also simulated using the GEOS‐Chem model. Initial GEOS‐Chem simulations displayed a severe under‐estimation relative to observations for these fire plumes resulting from the injection height scheme of the model. Sensitivity tests highlighted that injection heights of 12.5 km for BC (based on previous studies) and 10 km for the NWT fires yielded the strongest correlations with ground‐based measurements. Applying these injection heights to the model significantly improves the simulated plume transport and agreement with ground‐ and space‐based observations. GEOS‐Chem was also used to estimate the magnitude of secondary in‐plume production of CH3OH and HCOOH; it was found to be an important component (∼18%) of the enhanced HCOOH columns at Eureka.

Atmospheric ammonia in China: Long-term spatiotemporal variation, urban-rural gradient, and influencing factors

In recent years, atmospheric ammonia (NH3) concentrations have increased in China. Ammonia control has become one of the next hot topics in air pollution mitigation with the increasing cost of acid gas emission reduction. In this study, using Infrared Atmospheric Sounding Interferometer (IASI) satellite observations, we analyzed the spatiotemporal distribution, the urban-rural gradient of the vertical column densities (VCDs) of NH3 and the contribution of influencing factors (meteorology, social, atmospheric acid gases, and NH3 emissions) in China from 2008 to 2019 using hotspot analysis, circular gradient analysis, geographical and temporal weighted regression, and some other methods. Our results showed that NH3 VCDs in China have significantly increased (31.88 %) from 2008 to 2019, with the highest occurring in North China Plain. The average NH3 VCDs in urban areas were significantly higher than those in rural areas, and the urban-rural gap in NH3 VCDs was widening. The results of circular gradient analysis showed an overall decreasing trend in NH3 VCDs along the urban-rural gradient. We used a geographically and temporally weighted regression model to analyze the contribution of various influencing factors to NH3 VCDs: meteorology (30.13 %), social (27.40 %), atmospheric acid gases (23.20 %), and NH3 emissions (19.28 %) factors. The results showed substantial spatiotemporal differences in the influencing factors. Atmospheric acid gas was the main reason for the increase in NH3 VCDs from 2008 to 2019. A more thorough understanding of the spatiotemporal distribution, urban-rural variations, and factors influencing NH3 in China will aid in developing control strategies to reduce PM2.5.

Vehicle-based in situ observations of the water vapor isotopic composition across China: spatial and seasonal distributions and controls

Abstract. Stable water isotopes are natural tracers in the hydrological cycle and have been applied in hydrology, atmospheric science, ecology, and paleoclimatology. However, the factors controlling the isotopic distribution, both at spatial and temporal scales, are debated in low and middle latitude regions, due to the significant influence of large-scale atmospheric circulation and complex sources of water vapor. For the first time, we made in situ observations of near-surface vapor isotopes over a large region (over 10 000 km) across China in both pre-monsoon and monsoon seasons, using a newly designed vehicle-based vapor isotope monitoring system. Combined with daily and multiyear monthly mean outputs from the isotope-incorporated global spectral model (Iso-GSM) and infrared atmospheric sounding interferometer (IASI) satellite to calculate the relative contribution, we found that the observed spatial variations in both periods represent mainly seasonal mean spatial variations, but are influenced by more significant synoptic-scale variations during the monsoon period. The spatial variations of vapor δ18O are mainly controlled by Rayleigh distillation along air mass trajectories during the pre-monsoon period, but are significantly influenced by different moisture sources, continental recycling processes, and convection during moisture transport in the monsoon period. Thus, the North–South gradient observed during the pre-monsoon period is counteracted during the monsoon period. The seasonal variation of vapor δ18O reflects the influence of the summer monsoon convective precipitation in southern China and a dependence on temperature in the North. The spatial and seasonal variations in d-excess reflect the different moisture sources and the influence of continental recycling. Iso-GSM successfully captures the spatial distribution of vapor δ18O during the pre-monsoon period, but the performance is weaker during the monsoon period, maybe due to the underestimation of local or short-term high-frequency synoptic variations. These results provide an overview of the spatial distribution and seasonal variability of water isotopic composition in East Asia and their controlling factors, and they emphasize the need to interpret proxy records in the context of the regional system.

Measurement report: Evolution and distribution of NH3 over Mexico City from ground-based and satellite infrared spectroscopic measurements

Abstract. Ammonia (NH3) is the most abundant alkaline compound in the atmosphere, with consequences for the environment, human health, and radiative forcing. In urban environments, it is known to play a key role in the formation of secondary aerosols through its reactions with nitric and sulfuric acids. However, there are only a few studies about NH3 in Mexico City. In this work, atmospheric NH3 was measured over Mexico City between 2012 and 2020 by means of ground-based solar absorption spectroscopy using Fourier transform infrared (FTIR) spectrometers at two sites (urban and remote). Total columns of NH3 were retrieved from the FTIR spectra and compared with data obtained from the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument. The diurnal variability of NH3 differs between the two FTIR stations and is strongly influenced by the urban sources. Most of the NH3 measured at the urban station is from local sources, while the NH3 observed at the remote site is most likely transported from the city and surrounding areas. The evolution of the boundary layer and the temperature play a significant role in the recorded seasonal and diurnal patterns of NH3. Although the vertical columns of NH3 are much larger at the urban station, the observed annual cycles are similar for both stations, with the largest values in the warm months, such as April and May. The IASI measurements underestimate the FTIR NH3 total columns by an average of 32.2±27.5 % but exhibit similar temporal variability. The NH3 spatial distribution from IASI shows the largest columns in the northeast part of the city. In general, NH3 total columns over Mexico City measured at the FTIR stations exhibited an average annual increase of 92±3.9×1013 molecules cm−2 yr−1 (urban, from 2012 to 2019) and 8.4±1.4×1013 molecules cm−2 yr−1 (remote, from 2012 to 2020), while IASI data within 20 km of the urban station exhibited an average annual increase of 38±7.6×1013 molecules cm−2 yr−1 from 2008 to 2018.

Understanding the Simulated Ammonia Increasing Trend from 2008 to 2015 over Europe with CHIMERE and Comparison with IASI Observations

The objective of this study is to assess and understand the NH3 recent trends and to identify the key components driving its concentrations. We have simulated the seasonal cycle, the interannual variability, and the trends in NH3 vertical column densities (VCD) from 2008 to 2015 over Europe, with the CHIMERE regional chemistry–transport model. We have also confronted the simulations against the Infrared Atmospheric Sounding Interferometer (IASI) satellite observations. IASI often shows a strong maximum in summer in addition to the spring peak, whereas CHIMERE only shows a slight peak in summer some years. This result could point to a misrepresentation of the temporal profile of the NH3 emissions, i.e., to missing emission sources during summertime either due to more than expected fertilizer use or to increased volatilization under warmer conditions. The simulated NH3 VCDs present an increasing trend over continental Europe (+2.7 ± 1.0 %/yr) but also at the national scale for Spain, Germany, UK, France, and Poland. Sensitivity tests indicate that these simulated positive trends are mainly due to (i) the trends in NH3 emissions, found heterogeneous in the EMEP NH3 emissions with strong disparities depending on the country, and (ii) the negative trends in NOx and SOx emissions. The impact of reductions in NO2 and SO2 emissions on NH3 concentrations should therefore be taken into account in future policies. This simulated NH3 VCD increase at the European scale is confirmed by IASI-v3R satellite observations in spring and summer, when ammonia emissions strongly contribute to the annual budget in accordance with crop requirements. Nevertheless, there are remaining differences about the significance and magnitude between the simulated and observed trends at the national scale, and it warrants further investigation.

The 2019 Raikoke volcanic eruption – Part 1: Dispersion model simulations and satellite retrievals of volcanic sulfur dioxide

Abstract. Volcanic eruptions can cause significant disruption to society, and numerical models are crucial for forecasting the dispersion of erupted material. Here we assess the skill and limitations of the Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) in simulating the dispersion of the sulfur dioxide (SO2) cloud from the 21–22 June 2019 eruption of the Raikoke volcano (48.3∘ N, 153.2∘ E). The eruption emitted around 1.5±0.2 Tg of SO2, which represents the largest volcanic emission of SO2 into the stratosphere since the 2011 Nabro eruption. We simulate the temporal evolution of the volcanic SO2 cloud across the Northern Hemisphere (NH) and compare our model simulations to high-resolution SO2 measurements from the TROPOspheric Monitoring Instrument (TROPOMI) and the Infrared Atmospheric Sounding Interferometer (IASI) satellite SO2 products. We show that NAME accurately simulates the observed location and horizontal extent of the SO2 cloud during the first 2–3 weeks after the eruption but is unable, in its standard configuration, to capture the extent and precise location of the highest magnitude vertical column density (VCD) regions within the observed volcanic cloud. Using the structure–amplitude–location (SAL) score and the fractional skill score (FSS) as metrics for model skill, NAME shows skill in simulating the horizontal extent of the cloud for 12–17 d after the eruption where VCDs of SO2 (in Dobson units, DU) are above 1 DU. For SO2 VCDs above 20 DU, which are predominantly observed as small-scale features within the SO2 cloud, the model shows skill on the order of 2–4 d only. The lower skill for these high-SO2-VCD regions is partly explained by the model-simulated SO2 cloud in NAME being too diffuse compared to TROPOMI retrievals. Reducing the standard horizontal diffusion parameters used in NAME by a factor of 4 results in a slightly increased model skill during the first 5 d of the simulation, but on longer timescales the simulated SO2 cloud remains too diffuse when compared to TROPOMI measurements. The skill of NAME to simulate high SO2 VCDs and the temporal evolution of the NH-mean SO2 mass burden is dominated by the fraction of SO2 mass emitted into the lower stratosphere, which is uncertain for the 2019 Raikoke eruption. When emitting 0.9–1.1 Tg of SO2 into the lower stratosphere (11–18 km) and 0.4–0.7 Tg into the upper troposphere (8–11 km), the NAME simulations show a similar peak in SO2 mass burden to that derived from TROPOMI (1.4–1.6 Tg of SO2) with an average SO2 e-folding time of 14–15 d in the NH. Our work illustrates how the synergy between high-resolution satellite retrievals and dispersion models can identify potential limitations of dispersion models like NAME, which will ultimately help to improve dispersion modelling efforts of volcanic SO2 clouds.

Analysis of atmospheric ammonia over South and East Asia based on the MOZART-4 model and its comparison with satellite and surface observations

Abstract. Limited availability of atmospheric ammonia (NH3) observations limits our understanding of controls on its spatial and temporal variability and its interactions with the ecosystem. Here we used the Model for Ozone and Related chemical Tracers version 4 (MOZART-4) global chemistry transport model and the Hemispheric Transport of Air Pollution version 2 (HTAP-v2) emission inventory to simulate global NH3 distribution for the year 2010. We presented a first comparison of the model with monthly averaged satellite distributions and limited ground-based observations available across South Asia. The MOZART-4 simulations over South Asia and East Asia were evaluated with the NH3 retrievals obtained from the Infrared Atmospheric Sounding Interferometer (IASI) satellite and 69 ground-based monitoring stations for air quality across South Asia and 32 ground-based monitoring stations from the Nationwide Nitrogen Deposition Monitoring Network (NNDMN) of China. We identified the northern region of India (Indo-Gangetic Plain, IGP) as a hotspot for NH3 in Asia, both using the model and satellite observations. In general, a close agreement was found between yearly averaged NH3 total columns simulated by the model and IASI satellite measurements over the IGP, South Asia (r=0.81), and the North China Plain (NCP), East Asia (r=0.90). However, the MOZART-4-simulated NH3 column was substantially higher over South Asia than East Asia, as compared with the IASI retrievals, which show smaller differences. Model-simulated surface NH3 concentrations indicated smaller concentrations in all seasons than surface NH3 measured by the ground-based observations over South and East Asia, although uncertainties remain in the available surface NH3 measurements. Overall, the comparison of East Asia and South Asia using both MOZART-4 model and satellite observations showed smaller NH3 columns in East Asia compared with South Asia for comparable emissions, indicating rapid dissipation of NH3 due to secondary aerosol formation, which can be explained by larger emissions of acidic precursor gases in East Asia.

Carbon monoxide emissions assessment by using satellite and modeling data: Central Mexico case study

This paper quantifies and reduces the differences in emissions from the 2008 inventory with respect to the real ones through the use of satellite observations and modeling. Carbon monoxide column comparisons from the Infrared Atmospheric Sounding Interferometer (IASI) satellite data were made against columns obtained from the WRF-Chem model, during February 2011. The analysis was carried out at the satellite passage local time (approximately 10:00 LT) over Mexico City. The 2008 National Emissions Inventory generated by the Mexican Ministry of Environment and Natural Resources was utilized. An inversion method was applied to the modeled and observed column data. With the above, scaling factors were obtained for five regions and the concentration from the model domain boundaries, which were used to update the emissions. These were used in modeling and the result was compared with surface measurements. For Mexico City and the Metropolitan Area, a scaling factor equal to 0.43 was obtained when using the 2008 emissions inventory; for Toluca, Morelos and Puebla, a less than one factor was estimated, while for Hidalgo and the concentration from model boundaries it was close to two. The model performance was improved by an increment in the agreement index and a reduction on the mean square error when the updated CO emissions were used.

Ammonia and PM2.5 Air Pollution in Paris during the 2020 COVID Lockdown

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 (NH4NO3), and we suggest that the conversion of ammonia to ammonium may have been the essential driver.

Air Quality Degradation by Mineral Dust over Beijing, Chengdu and Shanghai Chinese Megacities

Air pollution in Chinese megacities has reached extremely hazardous levels, and human activities are responsible for the emission or production of large amounts of particulate matter (PM). In addition to PM from anthropogenic sources, natural phenomena, such as dust storms over Asian deserts, may also emit large amounts of PM, which lead episodically to poor air quality over Chinese megacities. In this paper, we quantify the degradation of air quality by dust over Beijing, Chengdu and Shanghai megacities using the three dimensions (3D) chemistry transport model CHIMERE, which simulates dust emission and transport online. In the first part of our work, we evaluate dust emissions using Moderate Resolution Imaging Spectroradiometer (MODIS) and Infrared Atmospheric Sounding Interferometer (IASI) satellite observations of aerosol optical depth, respectively, in the visible and the thermal infrared over source areas. PM simulations were also evaluated compared to surface monitoring stations. Then, mineral dust emissions and their impacts on particle composition of several Chinese megacities were analyzed. Dust emissions and transport over China were simulated during three years (2011, 2013 and 2015). Annual dust contributions to the PM 10 budget over Beijing, Chengdu and Shanghai were evaluated respectively as 6.6%, 9.5% and 9.3%. Dust outbreaks largely contribute to poor air quality events during springtime. Indeed it was found that dust significantly contribute for 22%, 52% and 43% of spring PM 10 events (for Beijing, Chengdu and Shanghai respectively).

Three‐dimensional pathways of dust over the Sahara during summer 2011 as revealed by new Infrared Atmospheric Sounding Interferometer observations

AbstractWe present a new characterisation of the three‐dimensional (3D) distribution of dust over the Sahara during summer, exemplified for June 2011. Our approach, called AEROIASI, is based on the innovative retrieval of vertical profiles of the dust extinction coefficient from daily cloud‐free hyperspectral Infrared Atmospheric Sounder Interferometer (IASI) satellite observations. AEROIASI observations clearly agree with other widely used measurements (from lidar and radiometers). The 3D characterisation is focused on the dust maximum in June 2011, located in the central Sahara (17–23°N, 1–7°E) and linked to the major atmospheric dynamical drivers associated with the West African Monsoon (WAM) system. AEROIASI shows the near‐surface dust load to be dominated by five major emission events occurring every 3–4 days. These all occur when the study region is under the influence of northward bursts of the WAM and convection‐related cold pools, likely associated with orographic forcing by the Aïr Mountains. During the earliest (June 10) and the dustiest (June 17) cases, northward advection of moisture over the hotspot is favoured by the superposition of cyclonic circulations related to an extratropical disturbance northwest of the Sahara and to the Saharan heat low over Mauritania, respectively. Convection over the hotspot also triggers wave‐like disturbances that travel westwards. The three dustiest events are characterised by elongated dust fronts moving northwards, with a leading edge spanning 200–300 km horizontally and extending from the surface up to 2 km of altitude. Further south, the dust layer progressively elevates to 3.5 km along the slanted isentropes at the interface of the monsoon and the harmattan, increasingly losing contact with the ground. When northerlies blow over the study region, elevated dust layers at 3–5 km are observed, which are transported southwards within the Saharan air layer and westwards along the northern edge of the African easterly jet (after June 13).

Constraints on eruption processes and event masses for the 2016–2017 eruption of Bogoslof volcano, Alaska, through evaluation of IASI satellite SO2 masses and complementary datasets

Bogoslof volcano, Alaska, experienced at least 70 explosive eruptions between 12 December 2016 and 31 August 2017. Due to its remote location and limited local monitoring network, this eruption was monitored and characterized primarily using remote geophysical and satellite techniques. SO2 emissions from Bogoslof were persistently detected by the Infrared Atmospheric Sounding Interferometer (IASI) satellite sensors. Of Bogoslof’s 70 explosive events, 50% produced measurable SO2 masses ranging from 0.1 to 21.5 kt, with a median and standard deviation of 0.7 ± 4.0 kt SO2, respectively. Here, we compare IASI-derived SO2 masses from Bogoslof events to complementary geophysical datasets to provide insights into eruption source processes, namely the degree of seawater scrubbing of water-soluble SO2 and variations in magma flux. Correlations with the number of lightning strokes and infrasound energy are expected to indicate magma-flux as a controlling process, while correlations with infrasound frequency index are expected to indicate variations in vent-water content as a controlling factor. These comparisons suggest that the measured SO2 masses are primarily a function of eruption magnitude (degassed magma mass) and that scrubbing of SO2 emissions by vent seawater may have exerted a minor effect on the observed SO2 masses. SO2 masses were combined with petrologic constraints on melt inclusion and matrix glass S concentrations to calculate degassed magma masses and volumes. The cumulative SO2-derived degassed magma mass and estimated volume (dense-rock equivalent) for the full Bogoslof eruption were found to be 2.8 × 1010 kg and 9.3 × 106 m3, respectively. When individual event masses are compared against event masses calculated using an empirical plume-height method, a strong correlation is found (R2 = 0.83), with better than order-of-magnitude agreement in most cases. These estimates of eruption masses provide useful information on the magnitude, behavior, and associated hazards of the 2016–2017 eruption, and potentially future unrest at Bogoslof volcano.

Estimating exposure to hydrogen sulfide from animal husbandry operations using satellite ammonia as a proxy: Methodology demonstration

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.

A New Parameterization of Volcanic Ash Complex Refractive Index Based on NBO/T and SiO2 Content

AbstractRadiative transfer models used in remote sensing and hazard assessment of volcanic ash require knowledge of ash optical parameters. Here we characterize the bulk and glass compositions of a representative suite of volcanic ash samples with known complex refractive indices (n + ik, where n is the real part and k is the imaginary part). Using a linear regression model, we develop a new parameterization allowing the complex refractive index of volcanic ash to be estimated from ash SiO2 content or ratio of nonbridging oxygens to tetrahedrally coordinated cations (NBO/T). At visible wavelengths, n correlates better with bulk than with glass composition (both SiO2 and NBO/T), and k correlates better with SiO2 content than with NBO/T. Over a broader spectral range (0.4–19 μm), bulk correlates better than glass composition, and NBO/T generally correlates better than SiO2 content for both parts of the refractive index. In order to understand the impacts of our new parameterization on satellite retrievals, we compared Infrared Atmospheric Sounding Interferometer satellite (wavelengths 3.62–15.5 μm) mass loading retrievals using our new approach with retrievals that assumed a generic (Eyjafjallajökull) ash refractive index. There are significant differences in mass loading using our calculated indices specific to ash type rather than a generic index. Where mass loadings increase, there is often improvement in retrieval quality (corresponding to cost function decrease). This new parameterization of refractive index variation with ash composition will help to improve remote‐sensing retrievals for the rapid identification of ash and quantitative analysis of mass loadings from satellite data on operational timescales.

Validation of mobile in situ measurements of dairy husbandry emissions by fusion of airborne/surface remote sensing with seasonal context from the Chino Dairy Complex

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.

Version 2 of the IASI NH<sub>3</sub> neural network retrieval algorithm: near-real-time and reanalysed datasets

Abstract. 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).

Temporal and spatial variability of ammonia in urban and agricultural regions of northern Colorado, United States

Abstract. 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 42.7 µg m−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 µg m−3), decreasing toward the surface (4.35 µg m−3) and toward higher altitudes (1.93 µg m−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.

Ground Ammonia Concentrations over China Derived from Satellite and Atmospheric Transport Modeling

As a primary basic gas in the atmosphere, atmospheric ammonia (NH3) plays an important role in determining air quality, environmental degradation, and climate change. However, the limited ground observation currently presents a barrier to estimating ground NH3 concentrations on a regional scale, thus preventing a full understanding of the atmospheric processes in which this trace gas is involved. This study estimated the ground NH3 concentrations over China, combining the Infrared Atmospheric Sounding Interferometer (IASI) satellite NH3 columns and NH3 profiles from an atmospheric chemistry transport model (CTM). The estimated ground NH3 concentrations showed agreement with the variability in annual ground NH3 measurements from the Chinese Nationwide Nitrogen Deposition Monitoring Network (NNDMN). Great spatial heterogeneity of ground NH3 concentrations was found across China, and high ground NH3 concentrations were found in Northern China, Southeastern China, and some areas in Xinjiang Province. The maximum ground NH3 concentrations over China occurred in summer, followed by spring, autumn, and winter seasons, which were in agreement with the seasonal patterns of NH3 emissions in China. This study suggested that a combination of NH3 profiles from CTMs and NH3 columns from satellite obtained reliable ground NH3 concentrations over China.

Balloon-borne measurement of the aerosol size distribution from an Icelandic flood basalt eruption

We present in situ balloon-borne measurements of aerosols in a volcanic plume made during the Holuhraun eruption (Iceland) in January 2015. The balloon flight intercepted a young plume at 8 km distance downwind from the crater, where the plume is ∼15 min of age. The balloon carried a novel miniature optical particle counter LOAC (Light Optical Aerosol Counter) which measures particle number concentration and size distribution in the plume, alongside a meteorological payload. We discuss the possibility of calculating particle flux by combining LOAC data with measurements of sulfur dioxide flux by ground-based UV spectrometer (DOAS).The balloon passed through the plume at altitude range of 2.0–3.1 km above sea level (a.s.l.). The plume top height was determined as 2.7–3.1 km a.s.l., which is in good agreement with data from Infrared Atmospheric Sounding Interferometer (IASI) satellite. Two distinct plume layers were detected, a non-condensed lower layer (300 m thickness) and a condensed upper layer (800 m thickness). The lower layer was characterized by a lognormal size distribution of fine particles (0.2 μm diameter) and a secondary, coarser mode (2.3 μm diameter), with a total particle number concentration of around 100 cm−3 in the 0.2–100 μm detection range. The upper layer was dominated by particle centered on 20 μm in diameter as well as containing a finer mode (2 μm diameter). The total particle number concentration in the upper plume layer was an order of magnitude higher than in the lower layer.We demonstrate that intercepting a volcanic plume with a meteorological balloon carrying LOAC is an efficient method to characterize volcanic aerosol properties. During future volcanic eruptions, balloon-borne measurements could be carried out easily and rapidly over a large spatial area in order to better characterize the evolution of the particle size distribution and particle number concentrations in a volcanic plume.