Ethylene industrial emitters seen from space.

Volatile organic compounds are emitted abundantly from a variety of natural and anthropogenic sources. However, in excess, they can severely degrade air quality. Their fluxes are currently poorly represented in inventories due to a lack of constraints from global measurements. Here, we track from space over 300 worldwide hotspots of ethylene, the most abundant industrially produced organic compound. We identify specific emitters associated with petrochemical clusters, steel plants, coal-related industries, and megacities. Satellite-derived fluxes reveal that the ethylene emissions of the industrial sources are underestimated or missing in the state-of-the-art Emission Database for Global Atmospheric Research (EDGAR) inventory. This work exposes global emission point-sources of a short-lived carbonated gas, complementing the ongoing large-scale efforts on the monitoring of inorganic pollutants.

On the weekly cycle of atmospheric ammonia over European agricultural hotspots.

The presence of a weekly cycle in the abundance of an atmospheric constituent is a typical fingerprint for the anthropogenic nature of its emission sources. However, while ammonia is mainly emitted as a consequence of human activities, a weekly cycle has never been detected in its abundances at large scale. We expose here for the first time the presence of a weekend effect in the NH3 total columns measured by the IASI satellite sounder over the main agricultural source regions in Europe: northwestern Europe (Belgium-the Netherlands-northwest Germany), the Po Valley, Brittany, and, to a lesser extent, the Ebro Valley. A decrease of 15% relative to the weekly mean is seen on Sunday-Monday observations in northwestern Europe, as a result of reduced NH3 emissions over the weekend. This is confirmed by in situ NH3 concentration data from the National Air Quality Monitoring Network in the Netherlands, where an average reduction of 10% is found around midnight on Sunday. The identified weekend effect presents a strong seasonal variability, with two peaks, one in spring and one in summer, coinciding with the two main (manure) fertilization periods. In spring, a reduction on Sunday-Monday up to 53 and 26% is found in the NH3 satellite columns and in situ concentrations, respectively, as fertilization largely drives atmospheric NH3 abundances at this time of the year.

Rapid rise in premature mortality due to anthropogenic air pollution in fast-growing tropical cities from 2005 to 2018.

Tropical cities are experiencing rapid growth but lack routine air pollution monitoring to develop prescient air quality policies. Here, we conduct targeted sampling of recent (2000s to 2010s) observations of air pollutants from space-based instruments over 46 fast-growing tropical cities. We quantify significant annual increases in nitrogen dioxide (NO2) (1 to 14%), ammonia (2 to 12%), and reactive volatile organic compounds (1 to 11%) in most cities, driven almost exclusively by emerging anthropogenic sources rather than traditional biomass burning. We estimate annual increases in urban population exposure to air pollutants of 1 to 18% for fine particles (PM2.5) and 2 to 23% for NO2 from 2005 to 2018 and attribute 180,000 (95% confidence interval: -230,000 to 590,000) additional premature deaths in 2018 (62% increase relative to 2005) to this increase in exposure. These cities are predicted to reach populations of up to 80 million people by 2100, so regulatory action targeting emerging anthropogenic sources is urgently needed.

IASI-Derived Sea Surface Temperature Data Set for Climate Studies.

Sea surface temperature (SST) is an essential climate variable, that is directly used in climate monitoring. Although satellite measurements can offer continuous global coverage, obtaining a long-term homogeneous satellite-derived SST data set suitable for climate studies based on a single instrument is still a challenge. In this work, we assess a homogeneous SST data set derived from reprocessed Infrared Atmospheric Sounding Interferometer (IASI) level-1 (L1C) radiance data. The SST is computed using Planck's Law and simple atmospheric corrections. We assess the data set using the ERA5 reanalysis and the EUMETSAT-released IASI level-2 SST product. Over the entire period, the reprocessed IASI SST shows a mean global difference with ERA5 close to zero, a mean absolute bias under 0.5°C, with a SD of difference around 0.3°C and a correlation coefficient over 0.99. In addition, the reprocessed data set shows a stable bias and SD, which is an advantage for climate studies. The interannual variability and trends were compared with other SST data sets: ERA5, Hadley Centre's SST (HadISST), and NOAA's Optimal Interpolation SST Analysis (OISSTv2). We found that the reprocessed SST data set is able to capture the patterns of interannual variability well, showing the same areas of high interannual variability (>1.5°C), including over the tropical Pacific in January corresponding to the El Niño Southern Oscillation. Although the period studied is relatively short, we demonstrate that the IASI data set reproduces the same trend patterns found in the other data sets (i.e., cooling trend in the North Atlantic, warming trend over the Mediterranean).

Monthly Patterns of Ammonia Over the Contiguous United States at 2-km Resolution.

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.

Complex refractive index of volcanic ash aerosol in the infrared, visible, and ultraviolet.

Very fine silicate-rich volcanic ash, generated by explosive volcanic eruptions, can efficiently be traced downwind with infrared satellite sounders. Their measurements can also be used to derive physical parameters, such as optical depths and effective radii. However, one of the key requirements for accurate retrievals is a good knowledge of the complex refractive index (CRI) of the ash under investigation. In the past, the vast majority of the studies used the CRIs from Pollack et al. [Icarus19, 372 (1973)ICRSA50019-103510.1016/0019-1035(73)90115-2], which are based on measurements of thin slices of volcanic rock, and therefore are not representative for airborne volcanic ash particles. Here, we report measurements of the CRI of volcanic ash in suspension, generated from samples collected from recent high-impact eruptions in Chile (Puyehue-Cordón Caulle, Calbuco, and Chaitén), Iceland (Eyjafjallajökull and Grímsvötn), and Italy (Etna). The samples cover a wide range of ${{\rm SiO}_2}$SiO2 content (46% to 76%) as confirmed by an X-ray fluorescence analysis. In the experimental setup, volcanic ash was suspended in nitrogen through mechanical agitation. Extinction spectra were recorded in the infrared, visible, and ultraviolet spectral regions. The particle size distribution within the airflow was also recorded. An iterative algorithm allowed us to obtain fully consistent CRIs for the six samples, compatible with the observed extinction spectra and the Kramers-Krönig relations. While a good agreement is found with other recently reported CRIs in the UV/Vis, larger differences are found in the longwave infrared spectral region.

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.

Industrial and agricultural ammonia point sources exposed.

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 ecosystems3-5 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 scales7-9. 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.

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.

Erratum: Strong constraints on aerosol-cloud interactions from volcanic eruptions.

This corrects the article DOI: 10.1038/nature22974.

Ammonia Emissions May Be Substantially Underestimated in China.

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.

Strong constraints on aerosol-cloud interactions from volcanic eruptions.

Aerosols have a potentially large effect on climate, particularly through their interactions with clouds, but the magnitude of this effect is highly uncertain. Large volcanic eruptions produce sulfur dioxide, which in turn produces aerosols; these eruptions thus represent a natural experiment through which to quantify aerosol-cloud interactions. Here we show that the massive 2014-2015 fissure eruption in Holuhraun, Iceland, reduced the size of liquid cloud droplets-consistent with expectations-but had no discernible effect on other cloud properties. The reduction in droplet size led to cloud brightening and global-mean radiative forcing of around -0.2 watts per square metre for September to October 2014. Changes in cloud amount or cloud liquid water path, however, were undetectable, indicating that these indirect effects, and cloud systems in general, are well buffered against aerosol changes. This result will reduce uncertainties in future climate projections, because we are now able to reject results from climate models with an excessive liquid-water-path response.

Remote sensing and in situ measurements of methane and ammonia emissions from a megacity dairy complex: Chino, CA.

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.

Towards a climate-dependent paradigm of ammonia emission and deposition.

Existing descriptions of bi-directional ammonia (NH3) 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 NH3 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 NH3 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 NH3 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 NH3 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 NH3 emissions may increase from 65 (45-85) Tg N in 2008 to reach 132 (89-179) Tg by 2100.

Retrieving radius, concentration, optical depth, and mass of different types of aerosols from high-resolution infrared nadir spectra.

We present a sophisticated radiative transfer code for modeling outgoing IR radiation from planetary atmospheres and, conversely, for retrieving atmospheric properties from high-resolution nadir-observed spectra. The forward model is built around a doubling-adding routine and calculates, in a spherical refractive geometry, the outgoing radiation emitted by the Earth and the atmosphere containing one layer of aerosol. The inverse model uses an optimal estimation approach and can simultaneously retrieve atmospheric trace gases, aerosol effective radius, and concentration. It is different from existing codes, as most forward codes dealing with multiple scattering assume a plane-parallel atmosphere, and as for the retrieval, it does not rely on precalculated spectra, the use of microwindows, or two-step retrievals. The simultaneous retrieval on a broad spectral range exploits the full potential of current state-of-the-art hyperspectral IR sounders, such as AIRS and IASI, and should be particularly useful in studying major pollution events. We present five example retrievals of IASI spectra observed in the range from 800 to 1200 cm(-1) above dust, volcanic ash, sulfuric acid, ice particles, and biomass burning aerosols.