SO2 Column Research Articles

Evaluating the assimilation of S5P/TROPOMI near real-time SO<sub>2</sub> columns and layer height data into the CAMS integrated forecasting system (CY47R1), based on a case study of the 2019 Raikoke eruption

Abstract. The Copernicus Atmosphere Monitoring Service (CAMS), operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission, provides daily analyses and 5 d forecasts of atmospheric composition, including forecasts of volcanic sulfur dioxide (SO2) in near real time. CAMS currently assimilates total column SO2 products from the GOME-2 instruments on MetOp-B and MetOp-C and the TROPOMI instrument on Sentinel-5P, which give information about the location and strength of volcanic plumes. However, the operational TROPOMI and GOME-2 data do not provide any information about the height of the volcanic plumes, and therefore some prior assumptions need to be made in the CAMS data assimilation system about where to place the resulting SO2 increments in the vertical. In the current operational CAMS configuration, the SO2 increments are placed in the mid-troposphere, around 550 hPa or 5 km. While this gives good results for the majority of volcanic emissions, it will clearly be wrong for eruptions that inject SO2 at very different altitudes, in particular exceptional events where part of the SO2 plume reaches the stratosphere. A new algorithm, developed by the German Aerospace Centre (DLR) for GOME-2 and TROPOMI, optimized in the frame of the ESA-funded Sentinel-5P Innovation–SO2 Layer Height Project, and known as the Full-Physics Inverse Learning Machine (FP_ILM) algorithm, retrieves SO2 layer height from TROPOMI in near real time (NRT) in addition to the SO2 column. CAMS is testing the assimilation of these products, making use of the NRT layer height information to place the SO2 increments at a retrieved altitude. Assimilation tests with the TROPOMI SO2 layer height data for the Raikoke eruption in June 2019 show that the resulting CAMS SO2 plume heights agree better with IASI plume height data than operational CAMS runs without the TROPOMI SO2 layer height information and show that making use of the additional layer height information leads to improved SO2 forecasts. Including the layer height information leads to higher modelled total column SO2 values in better agreement with the satellite observations. However, the plume area and SO2 burden are generally also overestimated in the CAMS analysis when layer height data are used. The main reason for this overestimation is the coarse horizontal resolution used in the minimizations. By assimilating the SO2 layer height data, the CAMS system can predict the overall location of the Raikoke SO2 plume up to 5 d in advance for about 20 d after the initial eruption, which is better than with the operational CAMS configuration (without prior knowledge of the plume height) where the forecast skill is much more reduced for longer forecast lead times.

Learnings from COVID-19 Forced Lockdown on Regional Air Quality and Mitigation Potential for South Asia

South Asia is a hotspot of air pollution with limited resilience and hence, understanding the mitigation potential of different sources is critically important. In this context the country lockdown initiated to combat the COVID-19 pandemic (during March and April 2020 that is the pre-monsoon season) provides an unique opportunity for studying the relative impacts of different emission sources in the region. Here, we analyze changes in levels of air quality species across the region during selected lockdown periods using satellite and in-situ datasets. This analysis compares air quality levels during the lockdown against pre-lockdown conditions as well as against regional long-term mean. Satellite derived AOD, NO2, and CO data indicates an increase of 9.5%, 2%, and 2.6%, respectively, during the 2020 lockdown period compared to pre-lockdown over the South Asia domain. However, individual country statistics, urban site data, and industrial grid analysis within the region indicate a more varied picture. Cities with high traffic loads reported a reduction of 12–39% in columnar NO2 during lockdown, in-situ PM2.5 measurements indicate a 23–56% percent reduction over the country capitals and columnar SO2 has an approximate reduction of 50% over industrial areas. In contrast, pollutant emissions from natural sources e.g., from biomass burning were observed to be adversely affecting the air quality in this period potentially masking expected lockdown related air quality improvements. This study demonstrates the need for a more nuanced and situation specific understanding of sources of air pollutants (anthropogenic and natural) and for these sources to be better understood from the local to the regional scale. Without this deeper understanding, mitigation strategies cannot be effectively targeted, wasting limited resources as well as risking unintended consequences both for the atmosphere and how mitigation action is perceived by the wider public.

Absorption spectra measurements at ~1 cm<sup>–1</sup> spectral resolution of <sup>32</sup>S, <sup>33</sup>S, <sup>34</sup>S, and <sup>36</sup>S sulfur dioxide for the 206–220 nm region and applications to modeling of the isotopic self-shielding

The sulfur isotope fractionation that occurs during SO2 photolysis is key to explaining the isotope signatures stored in ancient sedimentary rocks and understanding the atmospheric compositions of the early Earth and early Mars. Here, we report the photoabsorption cross-sections of 32SO2, 33SO2, 34SO2, and 36SO2 measured from 206 to 220 nm at 296 K. The wavelength resolution was set to 1 cm–1, 25 times higher than that of previous SO2 isotopologue absorption spectra measurements. The precision of ~10% is in agreement with previously reported SO2 absorption spectra. In comparison with previously reported high-resolution spectra of natural abundance, SO2 measurements demonstrate smaller cross-sectional magnitudes at absorption peaks and an offset wavelength by ~0.016 nm. Using the newly recorded isotopologue spectra, we calculated the sulfur isotope fractionation for self-shielding during SO2 photolysis. The calculated 34S fractionation (34ε) roughly reproduces the observed relationship between 34ε and the SO2 column density in previous photolysis experiments. Thus, the cross-section is useful for predicting 34S/32S isotope fractionation in an optically thick SO2 atmosphere. In contrast, for mass-independent fractionation (MIF-S, i.e., non-zero Δ33S), the measured spectra predicted a weakly negative Δ33S/δ34S slope of about –0.1. The small Δ33S/δ34S slope is consistent with the slopes of SO2 photolysis experiments under high-pressure atmospheres (i.e., the pressure broadened absorption line width will be comparable to the spectral resolution). Therefore, MIF-S during photolysis experiments was linked to spectroscopic measurements for the first time. We conclude that reasonable precision and high-resolution spectroscopic measurements are key to explaining the origin of MIF-S at column densities below 1018 cm–2. However, MIF-S production in chamber experiments or atmospheric conditions may require understanding pressure or temperature effects, such as linewidth broadening on the UV-absorption spectra, and how these effects manifest themselves on isotopologues.

Evaluation of SO<sub>2</sub>, SO<sub>4</sub><sup>2−</sup> and an updated SO<sub>2</sub> dry deposition parameterization in the United Kingdom Earth System Model

Abstract. In this study we evaluate simulated surface SO2 and sulfate (SO42-) concentrations from the United Kingdom Earth System Model (UKESM1) against observations from ground-based measurement networks in the USA and Europe for the period 1987–2014. We find that UKESM1 captures the historical trend for decreasing concentrations of atmospheric SO2 and SO42- in both Europe and the USA over the period 1987–2014. However, in the polluted regions of the eastern USA and Europe, UKESM1 over-predicts surface SO2 concentrations by a factor of 3 while under-predicting surface SO42- concentrations by 25 %–35 %. In the cleaner western USA, the model over-predicts both surface SO2 and SO42- concentrations by factors of 12 and 1.5 respectively. We find that UKESM1’s bias in surface SO2 and SO42- concentrations is variable according to region and season. We also evaluate UKESM1 against total column SO2 from the Ozone Monitoring Instrument (OMI) using an updated data product. This comparison provides information about the model's global performance, finding that UKESM1 over-predicts total column SO2 over much of the globe, including the large source regions of India, China, the USA, and Europe as well as over outflow regions. Finally, we assess the impact of a more realistic treatment of the model's SO2 dry deposition parameterization. This change increases SO2 dry deposition to the land and ocean surfaces, thus reducing the atmospheric loading of SO2 and SO42-. In comparison with the ground-based and satellite observations, we find that the modified parameterization reduces the model's over-prediction of surface SO2 concentrations and total column SO2. Relative to the ground-based observations, the simulated surface SO42- concentrations are also reduced, while the simulated SO2 dry deposition fluxes increase.

Tracking aerosols and SO<sub>2</sub> clouds from the Raikoke eruption: 3D view from satellite observations

Abstract. The 21 June 2019 eruption of the Raikoke volcano (Kuril Islands, Russia; 48∘ N, 153∘ E) produced significant amounts of volcanic aerosols (sulfate and ash) and sulfur dioxide (SO2) gas that penetrated into the lower stratosphere. The dispersed SO2 and sulfate aerosols in the stratosphere were still detectable by multiple satellite sensors for many months after the eruption. For this study of SO2 and aerosol clouds we use data obtained from two of the Ozone Mapping and Profiler Suite sensors on the Suomi National Polar-orbiting Partnership satellite: total column SO2 from the Nadir Mapper and aerosol extinction profiles from the Limb Profiler as well as other satellite data sets. We evaluated the limb viewing geometry effect (the “arch effect”) in the retrieval of the LP standard aerosol extinction product at 674 nm. It was shown that the amount of SO2 decreases with a characteristic period of 8–18 d and the peak of stratospheric aerosol optical depth recorded at a wavelength of 674 nm lags the initial peak of SO2 mass by 1.5 months. Using satellite observations and a trajectory model, we examined the dynamics of an unusual atmospheric feature that was observed, a stratospheric coherent circular cloud of SO2 and aerosol from 18 July to 22 September 2019.

A sulfur dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources

Abstract. Sensitive and accurate detection of sulfur dioxide (SO2) from space is important for monitoring and estimating global sulfur emissions. Inspired by detection methods applied in the thermal infrared, we present here a new scheme to retrieve SO2 columns from satellite observations of ultraviolet back-scattered radiances. The retrieval is based on a measurement error covariance matrix to fully represent the SO2-free radiance variability, so that the SO2 slant column density is the only retrieved parameter of the algorithm. We demonstrate this approach, named COBRA, on measurements from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S-5P) satellite. We show that the method reduces significantly both the noise and biases present in the current TROPOMI operational DOAS SO2 retrievals. The performance of this technique is also benchmarked against that of the principal component algorithm (PCA) approach. We find that the quality of the data is similar and even slightly better with the proposed COBRA approach. The ability of the algorithm to retrieve SO2 accurately is further supported by comparison with ground-based observations. We illustrate the great sensitivity of the method with a high-resolution global SO2 map, considering 2.5 years of TROPOMI data. In addition to the known sources, we detect many new SO2 emission hotspots worldwide. For the largest sources, we use the COBRA data to estimate SO2 emission rates. Results are comparable to other recently published TROPOMI-based SO2 emissions estimates, but the associated uncertainties are significantly lower than with the operational data. Next, for a limited number of weak sources, we demonstrate the potential of our data for quantifying SO2 emissions with a detection limit of about 8 kt yr−1, a factor of 4 better than the emissions derived from the Ozone Monitoring Instrument (OMI). We anticipate that the systematic use of our TROPOMI COBRA SO2 column data set at a global scale will allow missing sources to be identified and quantified and help improve SO2 emission inventories.

EUNADICS-AV early warning system dedicated to supporting aviation in the case of a crisis from natural airborne hazards and radionuclide clouds

Abstract. The purpose of the EUNADICS-AV (European Natural Airborne Disaster Information and Coordination System for Aviation) prototype early warning system (EWS) is to develop the combined use of harmonised data products from satellite, ground-based and in situ instruments to produce alerts of airborne hazards (volcanic, dust, smoke and radionuclide clouds), satisfying the requirement of aviation air traffic management (ATM) stakeholders (https://cordis.europa.eu/project/id/723986, last access: 5 November 2021). The alert products developed by the EUNADICS-AV EWS, i.e. near-real-time (NRT) observations, email notifications and netCDF (Network Common Data Form) alert data products (called NCAP files), have shown significant interest in using selective detection of natural airborne hazards from polar-orbiting satellites. The combination of several sensors inside a single global system demonstrates the advantage of using a triggered approach to obtain selective detection from observations, which cannot initially discriminate the different aerosol types. Satellite products from hyperspectral ultraviolet–visible (UV–vis) and infrared (IR) sensors (e.g. TROPOMI – TROPOspheric Monitoring Instrument – and IASI – Infrared Atmospheric Sounding Interferometer) and a broadband geostationary imager (Spinning Enhanced Visible and InfraRed Imager; SEVIRI) and retrievals from ground-based networks (e.g. EARLINET – European Aerosol Research Lidar Network, E-PROFILE and the regional network from volcano observatories) are combined by our system to create tailored alert products (e.g. selective ash detection, SO2 column and plume height, dust cloud, and smoke from wildfires). A total of 23 different alert products are implemented, using 1 geostationary and 13 polar-orbiting satellite platforms, 3 external existing service, and 2 EU and 2 regional ground-based networks. This allows for the identification and the tracking of extreme events. The EUNADICS-AV EWS has also shown the need to implement a future relay of radiological data (gamma dose rate and radionuclides concentrations in ground-level air) in the case of a nuclear accident. This highlights the interest of operating early warnings with the use of a homogenised dataset. For the four types of airborne hazard, the EUNADICS-AV EWS has demonstrated its capability to provide NRT alert data products to trigger data assimilation and dispersion modelling providing forecasts and inverse modelling for source term estimate. Not all of our alert data products (NCAP files) are publicly disseminated. Access to our alert products is currently restricted to key users (i.e. Volcanic Ash Advisory Centres, national meteorological services, the World Meteorological Organization, governments, volcano observatories and research collaborators), as these are considered pre-decisional products. On the other hand, thanks to the EUNADICS-AV–SACS (Support to Aviation Control Service) web interface (https://sacs.aeronomie.be, last access: 5 November 2021), the main part of the satellite observations used by the EUNADICS-AV EWS is shown in NRT, with public email notification of volcanic emission and delivery of tailored images and NCAP files. All of the ATM stakeholders (e.g. pilots, airlines and passengers) can access these alert products through this free channel.

Day–Night Monitoring of Volcanic SO2 and Ash Clouds for Aviation Avoidance at Northern Polar Latitudes

We describe NASA’s Applied Sciences Disasters Program, which is a collaborative project between the Direct Readout Laboratory (DRL), ozone processing team, Jet Propulsion Laboratory, Geographic Information Network of Alaska (GINA), and Finnish Meteorological Institute (FMI), to expedite the processing and delivery of direct readout (DR) volcanic ash and sulfur dioxide (SO2) satellite data. We developed low-latency quantitative retrievals of SO2 column density from the solar backscattered ultraviolet (UV) measurements using the Ozone Mapping and Profiler Suite (OMPS) spectrometers as well as the thermal infrared (TIR) SO2 and ash indices using Visible Infrared Imaging Radiometer Suite (VIIRS) instruments, all flying aboard US polar-orbiting meteorological satellites. The VIIRS TIR indices were developed to address the critical need for nighttime coverage over northern polar regions. Our UV and TIR SO2 and ash software packages were designed for the DRL’s International Planetary Observation Processing Package (IPOPP); IPOPP runs operationally at GINA and FMI stations in Fairbanks, Alaska, and Sodankylä, Finland. The data are produced within 30 min of satellite overpasses and are distributed to the Alaska Volcano Observatory and Anchorage Volcanic Ash Advisory Center. FMI receives DR data from GINA and posts composite Arctic maps for ozone, volcanic SO2, and UV aerosol index (UVAI, proxy for ash or smoke) on its public website and provides DR data to EUMETCast users. The IPOPP-based software packages are available through DRL to a broad DR user community worldwide.

Improved Anthropogenic SO2 Retrieval from High-Spatial-Resolution Satellite and its Application during the COVID-19 Pandemic.

Sulfur dioxide (SO2) measured by satellites is widely used to estimate anthropogenic emissions. The Sentinel-5 Precursor (S-5P) operational SO2 product is overestimated compared to the ground-based multiaxis differential optical absorption spectroscopy (MAX-DOAS) measurements in China and shows an opposite variation to the surface measurements, which limits the application of TROPOspheric monitoring instrument (TROPOMI) products in emissions research. Radiometric calibration, a priori profiles, and fitting windows might cause the overestimation of S-5P operational SO2 product. Here, we improve the optimal-estimation-based algorithm through several calibration methods. The improved retrieval agrees reasonably well with the ground-based measurements (R > 0.70, bias <13.7%) and has smaller biases (-28.9%) with surface measurements over China and India. It revealed that the SO2 column in March 2020 decreased by 51.6% compared to March 2019 due to the lockdown for curbing the spread of the COVID-19 pandemic, and there was a decrease of 50% during the lockdown than those after the lockdown, similar to the surface measurement trend, while S-5P operational SO2 product showed an unrealistic increase of 19%. In India, the improved retrieval identified obvious "hot spots" and observed a 30% decrease of SO2 columns during the lockdown.

An analysis of volcanic SO2 and ash emissions from Copahue volcano

During 2016, Copahue volcano (Neuquén, Argentina) made several eruptions and emitted ash and gases. This paper presents an analysis of the volcanic plume using dispersion models, remote sensor data, and analysis of sedimentary ash collected at the Caviahue Health Center from early October to 21st December 2016. Water-soluble elements contained in volcanic ash leachates were quantified. We have carried out a qualitative comparison of HYSPLIT dispersion simulations with SO2 and aerosol data obtained from OMI and OMPS sensor on board of AURA and SUOMI NPP satellites, as well as between modeled concentrations and sampled surface sediments. Good agreement was observed between gas dispersion plumes from HYSPLIT and total column SO2 values, as well as between volcanic ash plumes and satellite aerosol indices.The average SO2 emission rate in the analyzed events was 985.7 ± 492.9 t/d and the average emission rate of ash 2.6 103 kt/d (2.9 104 kg/s). In situ observations of ash deposition rates peaked at 0.23 g/h on 30th November. The average measured deposition rate from 1st October to 21st December was 0.12 g/h, consistent with modeled values. The geochemical analysis of ash leachate showed major content of sodium (Na), calcium (Ca) and magnesium (Mg) with 207.8 mg/kg, 209.5 mg/kg, and 195.3 mg/kg, respectively. Concentrations sulfate, chlorides, and fluoride anions were 990.7 mg/kg, 352.34 mg/kg, and 129.15 mg/kg, respectively. The SO2/HCl molar ratio was 1.05. In addition, traces of As, Cr, Hg, Mo, Pb, and Se were detected in concentrations ranging from 0.2 mg/kg to 6.0 mg/kg.

Io's SO2 atmosphere from HST Lyman-α images: 1997 to 2018

The atmosphere of Jupiter's volcanic moon Io consists of mainly sulfur dioxide (SO2), and this main constituent has been studied with a variety of observing techniques across many wavelengths over the years. Here we study absorption by SO2 at the hydrogen Ly-α line (1216 Å) in a large set of images taken by the Space Telescope Imaging Spectrograph (STIS) onboard the Hubble Space Telescope (HST) between 1997 and 2018. An advanced statistical analysis using a Monte-Carlo trial method is applied to derive the SO2 column density from the Ly-α intensity, which includes the uncertainties of the used variables such as solar and background flux. Our analysis produces a probability distribution function of the SO2 column density and highlights some short-comings of the observing technique. Most importantly, the HST/STIS images of the surface-reflected Ly-α flux are only sensitive to SO2 column densities between ~1015 cm−2 and ~5×1016 cm−2. Due to strong non-linearity in the relationship between the SO2 abundance and the Ly-α flux at the low and high values of detected flux, SO2 abundance directly retrieved from the STIS images will generally fall within these boundaries. This explains the relatively low equatorial column density of about 1016 cm−2 reported by previous studies using the Ly-α images (e.g., Feldman et al., 2000; Feaga et al., 2009) compared to other studies (e.g., Spencer et al., 2005; Tsang et al., 2013; Jessup and Spencer, 2015; Lellouch et al., 2015), where the obtained column density is often 1017 cm−2. By assuming a log-normal probability distribution function for the column density, a new estimate of the SO2 column density is then fitted, indirectly accounting for abundances beyond the detectability limits. This method suggests slightly higher equatorial SO2 abundances and much larger upper-limits, revealing that the Ly-α observations are in fact consistent with the higher abundances found in other studies. We then investigate the SO2 abundances at three volcanic sites (Loki, Marduk, Thor), where plumes were observed before and where the sensitivity in our images is comparably high. The observations did not reveal transient changes due to local outgassing at any of the three sites. Finally, the heliocentric distance of Io changed from 4.95 AU to 5.45 AU between the observation dates, potentially allowing us to investigate the influence of solar intensity changes on the SO2 column density via surface frost sublimation. However, the derived error bars are significantly larger than the derived variability, preventing any firm conclusion on seasonal changes and local volcanic outgassing.

Long-term ambient SO2 concentration and its exposure risk across China inferred from OMI observations from 2005 to 2018

Long-term trends in the ambient SO2 concentrations across China from 2005 to 2018 were estimated using Ozone Monitoring Instrument (OMI) SO2 columns and an atmospheric SO2 profile simulated by the Model for Ozone And Related Chemical Tracers (MOZART)-4. The estimated ground-level SO2 concentrations were in strong agreement with the ground observations (R = 0.86, root-mean-square error = 10.49 μg/m3, relative prediction error = 19%). From 2005 to 2018, the average ground-level SO2 concentration ranged from 0.97 to 106.41 μg/m3 across China, with higher values in eastern China than in western China. Considering the uneven distribution of SO2 concentration and population across China, the population-weighted SO2 concentration was estimated to be 20.30 μg/m3 on a national scale. The population-weighted SO2 levels showed decreasing trends, and the absolute values of the decreasing trend peaked in winter (1.41 μg/m3 per year), followed by those in autumn (0.92 μg/m3 per year), spring (0.74 μg/m3 per year) and summer (0.75 μg/m3 per year) from 2005 to 2018. Although the SO2 exposure risk in 2018 decreased significantly from 2005 on a national scale, 80% and 17% of people still faced a high SO2 exposure risk (higher than 20 μg/m3) in the North China Plain and Northwest China, respectively.

First Measurements of Gas Flux with a Low-Cost Smartphone Sensor-Based UV Camera on the Volcanoes of Northern Chile

UV cameras have been used for over a decade in order to remotely sense SO2 emission rates from active volcanoes, and to thereby enhance our understanding of processes related to active and passive degassing. Whilst SO2 column density retrievals can be more accurate/sophisticated using alternative techniques (e.g., Differential Optical Absorption Spectrometer (DOAS), Correlation Spectrometer (COSPEC)), due to their higher spectral resolutions, UV cameras provide the advantage of high time-resolution emission rates, a much greater spatial resolution, and the ability to simultaneously retrieve plume speeds. Nevertheless, the relatively high costs have limited their uptake to a limited number of research groups and volcanic observatories across the planet. One recent intervention in this regard has been the introduction of the PiCam UV camera, which has considerably lowered instrumental cost. Here we present the first data obtained with the PiCam system from seven persistently degassing volcanoes in northern Chile, demonstrating robust field operation in challenging conditions and over an extended period of time, hence adding credence to the potential of these units for more widespread dissemination to the international volcanic gas measurement community. Small and weak plumes, as well as strongly degassing plumes were measured at distances ranging 0.6–10.8 km from the sources, resulting in a wide range of SO2 emission rates, varying from 3.8 ± 1.8 to 361 ± 31.6 td−1. Our acquired data are discussed with reference to previously reported emission rates from other ground-based remotely sensed techniques at the same volcanoes, in particular considering: resolution of single plume emissions in multi-plume volcanoes, light dilution, plume geometry, seasonal effects, and the applied plume speed measurement methodology. The main internal/external factors that influence positive/negative PiCam measurements include camera shake, light dilution, and the performance of the OpenCV and control points post processing methods. A simple reprocessing method is presented in order to correct the camera shake. Finally, volcanoes were separated into two distinct groups: low and moderate SO2 emission rates systems. These groups correlate positively with their volcanological characteristics, especially with the fluid compositions from fumaroles.

An attempt to detect transient changes in Io’s SO[formula omitted] and NaCl atmosphere

Io’s atmosphere is predominately SO2 that is sustained by a combination of volcanic outgassing and sublimation. The loss from the atmosphere is the main mass source for Jupiter’s large magnetosphere. Numerous previous studies attributed various transient phenomena in Io’s environment and Jupiter’s magnetosphere to a sudden change in the mass loss from the atmosphere supposedly triggered by a change in volcanic activity. Since the gas in volcanic plumes does not escape directly, such causal correlation would require a transient volcano-induced change in atmospheric abundance, which has never been observed so far.Here we report four observations of atmospheric SO2 and NaCl from the same hemisphere of Io, obtained with the IRAM NOEMA interferometer on 11 December 2016, 14 March, 6 and 29 April 2017. These observations are compared to measurements of volcanic hot spots and Io’s neutral and plasma environment. We find a stable NaCl column density in Io’s atmosphere on the four dates. The SO2 column density derived for December 2016 is about 30% lower compared to the SO2 column density found in the period of March to April 2017. This increase in SO2 from December 2016 to March 2017 might be related to increasing volcanic activity observed at several sites in spring 2017, but the stability of the volcanic trace gas NaCl and resulting decrease in NaCl/SO2 ratio do not support this interpretation. Observed dimmings in both the sulfur ion torus and Na neutral cloud suggest rather a decrease in mass loading in the period of increasing SO2 abundance. The dimming Na brightness and stable atmospheric NaCl furthermore dispute an earlier suggested positive correlation of the sodium cloud and the hot spot activity at Loki Patara, which considerably increased in this period. The environment of Io overall appears to be in a rather quiescent state, preventing further conclusions. Only Jupiter’s aurora morphology underwent several short-term changes, which are apparently unrelated to Io’s quiescent environment or the relatively stable atmosphere.

Inverse modeling of SO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; and NO&amp;lt;sub&amp;gt;&amp;lt;i&amp;gt;x&amp;lt;/i&amp;gt;&amp;lt;/sub&amp;gt; emissions over China using multisensor satellite data – Part 1: Formulation and sensitivity analysis

Abstract. SO2 and NO2 observations from the Ozone Mapping and Profiler Suite (OMPS) sensor are used for the first time in conjunction with the GEOS-Chem adjoint model to optimize both SO2 and NOx emission estimates over China for October 2013. Separate and joint (simultaneous) optimizations of SO2 and NO2 emissions are both conducted and compared. Posterior emissions, compared to the prior, yield improvements in simulating columnar SO2 and NO2, in comparison to measurements from the Ozone Monitoring Instrument (OMI) and OMPS. The posterior SO2 and NOx emissions from separate inversions are 748 Gg S and 672 Gg N, which are 36 % and 6 % smaller than prior MIX emissions (valid for 2010), respectively. In spite of the large reduction of SO2 emissions over the North China Plain, the simulated sulfate–nitrate–ammonium aerosol optical depth (AOD) only decrease slightly, which can be attributed to (a) nitrate rather than sulfate as the dominant contributor to AOD and (b) replacement of ammonium sulfate with ammonium nitrate as SO2 emissions are reduced. For joint inversions, both data quality control and the weight given to SO2 relative to NO2 observations can affect the spatial distributions of the posterior emissions. When the latter is properly balanced, the posterior emissions from assimilating OMPS SO2 and NO2 jointly yield a difference of −3 % to 15 % with respect to the separate assimilations for total anthropogenic SO2 emissions and ±2 % for total anthropogenic NOx emissions; but the differences can be up to 100 % for SO2 and 40 % for NO2 in some grid cells. Improvements on SO2 and NO2 simulations from the joint inversions are overall consistent with those from separate inversions. Moreover, the joint assimilations save ∼ 50 % of the computational time compared to assimilating SO2 and NO2 separately in a sequential manner of computation. The sensitivity analysis shows that a perturbation of NH3 to 50 % (20 %) of the prior emission inventory can (a) have a negligible impact on the separate SO2 inversion but can lead to a decrease in posterior SO2 emissions over China by −2.4 % (−7.0 %) in total and up to −9.0 % (−27.7 %) in some grid cells in the joint inversion with NO2 and (b) yield posterior NOx emission decreases over China by −0.7 % (−2.8 %) for the separate NO2 inversion and by −2.7 % (−5.3 %) in total and up to −15.2 % (−29.4 %) in some grid cells for the joint inversion. The large reduction of SO2 between 2010 and 2013, however, only leads to ∼ 10 % decrease in AOD regionally; reducing surface aerosol concentration requires the reduction of emissions of NH3 as well.

Air quality impacts of the 2018 Mt. Kilauea Volcano eruption in Hawaii: A regional chemical transport model study with satellite-constrained emissions

Abstract Volcanic eruptions could bring a vast amount of sulfur dioxide (SO2) and ash into the air, often imposing substantial impacts on air quality and the ecosystem. Quantifying its impacts, however, is difficult due to the uncertainties in estimating the strength and variations of volcanic emissions. Here we developed and evaluated a new approach to combine satellite SO2 detection and chemical transport modeling to assess the impact of the 2018 Mt. Kilauea eruption on air quality over Hawaii. During the sustained eruption of the Kilauea Volcano in Hawaii's Big Island from May to July 2018, considerable SO2 and PM2.5 enhancements were observed both from the ground and from space. We studied this case using an experimental version of the NOAA National Air Quality Forecast Capability (NAQFC) modeling system. Daily emissions of SO2 and ash were estimated using a combination of SO2 column density retrieved by Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) aboard the Suomi-NPP satellite and the NAQFC model with an inverse emission modeling approach. We found that the volcanic SO2 emission rates peaked at 15,000 mol/s from the Kilauea's East Rift zone and Summit. The formation and transport of volcanic smog, or Vog, was highly dependent upon the vertical distribution of the volcanic emission, controlled by the heat flux of emission sources. We conducted four model simulations with various emission settings, and compared them to satellite data (CALIOP, OMPS and VIIRS) and in-situ measurements. All the runs tended to underpredict the peak values of surface SO2 and PM2.5 (particulate matter smaller than 2.5 μm in diameter). The “No Plume Rise” run underestimated the Vog plume rise and downstream transport. Using fixed emission rate or removing the temporal variations (”3-Day Mean”) led to miss peak Vog effects or inconsistent transport pattern compared to the observations. Therefore, the Base simulation with daily-varying emission and plume rise was used to quantify the air quality effects of the Kilauea eruption. We found that the volcanic eruption elevated surface PM2.5 concentration by 30–40 μg/m3 in the southeast part of the Big Island, with peak values up to 300 μg/m3. The Vog effect on trace gases, such as O3, NOx, and non-methane hydrocarbons, were much weaker (

Evaluation of the accuracy of the Sentinel-5 Precursor operational SO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; products over China

The Sentinel-5 Precursor (S-5P) was launched into low earth orbit with a single payload TROPOspheric Monitoring Instrument (TROPOMI) on 13 October, 2017. TROPOMI is able to provide atmospheric composition observations including sulfur dioxide (SO2) daily and globally. It has a higher spatial resolution, specifically with a ground resolution of 7 km ×3.5 km in the nadir, than previous satellite instruments such as Ozone Monitoring Instrument (OMI, 13 km ×24 km) and Ozone Mapping and Profiler Suite (OMPS, 50 km ×50 km). The three types of S-5P operational SO2 products (offline (OFFL), Reprocessing (RPRO) and Near Real Time (NRTI)) are on basis of the differential optical absorption spectroscopy (DOAS) algorithm, and available from the S-5P Pre-Operations Data Hub. To evaluate these data, the results of OFFL are compared to the measurements obtained by ground-based Multi-Axis DOAS (MAX-DOAS) and China National Environmental Monitoring Center (CNEMC). We find that the S-5P operational SO2 products significantly overestimate SO2 concentrations over Northern China. Compared with four ground-based MAX-DOAS measurements in terms of the weekly average SO2 vertical column densities (VCDs), the S-5P operational SO2 products exhibit an overestimation of 61%−140%, with the correlation coefficient less than 0.5. The a priori SO2 profiles in S-5P operational products are from daily Tracer Model (TM5) simulations. SO2 surface concentrations are converted by the S-5P operational SO2 products and a priori SO2 profiles used in the retrievals. The correlation coefficient between the SO2 surface concentrations measured by CNEMC over Northern China and those from the S-5P operational products is higher than 0.5, and the S-5P operational products at these CNEMC sites show an overestimation of about 54.6% on average. In this study, the SO2 products (TROPOMI USTC SO2 products) are retrieved by the University of Science and Technology of China (USTC) with the optimal estimation algorithm (OE) from TROPOMI measurements, with the a priori SO2 profiles from monthly average GEOS-Chem simulations. The mean biases between the TROPOMI USTC SO2 products and the ground-based MAX-DOAS measurements are reduced significantly (−4.8%−22%), together with an improvement in the correlation coefficients (0.72−0.89). TROPOMI USTC SO2 surface concentrations are transformed by the TROPOMI USTC SO2 products and a priori SO2 profiles in the retrievals. Based on the evaluation statistics of the S-5P operational SO2 products, a smaller mean bias of −25.8% is found between the TROPOMI USTC SO2 surface concentrations and CNEMC measurements over Northern China. Compared to the TROPOMI USTC SO2 products in the heavily polluted area (33°−45°N, 110°−122°E), the S-5P operational SO2 products have an overestimation of around 41.3%, with a correlation coefficient of 0.73. In addition, S-5P operational SO2 products show a larger area of heavy pollution than TROPOMI USTC SO2 products. Additionally, the sensitivity analysis indicates many influential factors of the SO2 retrievals using OE algorithm, such as radiative calibration, fitting window and a priori SO2 profiles. In the fitting window of 310.5−326.0 nm, the SO2 columns retrieved by the a priori profiles from monthly GEOS-Chem simulations show better agreement with the MAX-DOAS measurements than those from daily TM5 simulations. A possible reason is that the emission inventory used in GEOS-Chem is based on a Chinese power sector database for 31 provinces supported by CMEP (Chinese Ministry of Environmental Protection), resulting in a better performance of GEOS-Chem than that of TM5 over China in simulations. And the overestimation of the S-5P operational SO2 products over Northern China may be attributed to the fitting window used.

Variation of industrial air pollution emissions based on VIIRS thermal anomaly data

The Beijing-Tianjin-Hebei (BTH) region is the largest industrial cluster in northern China and its most prominent air pollution zone. Industrial emissions of PM2.5, SO2, NOx and other pollutants have a significant impact on regional air quality. Monitoring industrial pollution emissions is of great significance for the prevention and control of air pollution. The VIIRS Nightfire products can detect thermal anomalies in heavy industrial sectors, thus providing a new means for monitoring industrial activities. In this study, the VIIRS 375 product was selected to study the spatial and temporal changes of the heavy industrial thermal anomalies through spatial analysis and mathematical statistics methods. Furthermore, it is the first time to use thermal anomaly radiative power (CTRP) to evaluate the spatiotemporal pattern of industrial pollution emissions and its impact on air quality in the BTH region. We observed that the spatial distribution of CTRP was unbalanced and that Tangshan-Tianjin and Handan-Xingtai- Shijiazhuang were found to be high-density pollution areas. The CTRP in Tangshan and Handan were higher than in other cities, accounting for 72.41% of their area. From 2012 to 2018, CTRP in this region decreased by 17.2% per year while in Langfang decreased by 72.9% per year. The CTRP also showed a significantly positive correlation with industrial energy consumption. Emissions of SO2, NO2, and PM2.5 were high in the area of intense distribution of thermal anomalies. When compared to the density of tropospheric NO2 and SO2 columns and the monitored concentrations of SO2 and PM2.5, CTRP was consistent with the trend of interannual variations and spatial distributions. The energy-saving and emissions reduction measures taken by the industrial sector in the BTH contributed significantly to improving regional air quality. Remote sensing-based monitoring can provide regional industrial energy consumption in real-time and reflect pollution emissions, providing a basis for industrial pollution emissions regulation and reduction policy.

Effects of the socio-economic influencing factors on SO2 pollution in Chinese cities: A spatial econometric analysis based on satellite observed data

The research on SO2 pollution in China has been hotly debated over the past decades. Different from the existing studies, this work employs satellite observed SO2 columns from 2005 to 2016 and applies a spatial econometric approach to investigate the socio-economic influencing factors of SO2 pollution of 270 prefecture-level cities in China. The findings are as follows. (1) SO2 pollution over China exhibits a significant and positive spatial autocorrelation. (2) The most polluted area is concentrated on the North China Plain. However, SO2 pollution over China has been reduced gradually during the sample period, implying that overall environmental quality in China has been substantially improved. (3) Besides, the results of spatial econometric models are not in support of “pollution haven hypothesis”. On the contrary, the pollution halo effect of foreign direct investment works well and contributes to reducing SO2 pollution in China. Moreover, we find that urban economic levels and innovative capability are negatively correlated with SO2 pollution, indicating that economic growth and an increase in innovation can help improve environmental quality. On contrast, the share of the secondary industry, urbanization and transportation are found to have positive impacts, indicating that they are three main contributors to SO2 pollution in China.

Investigation of Aerosol Peak Height Effect on PBL and Volcanic Air Mass Factors for SO2 Column Retrieval from Space-Borne Hyperspectral UV Sensors

We investigate the effects of aerosol peak height (APH) and various parameters on the air mass factor (AMF) for SO2 retrieval. Increasing aerosol optical depth (AOD) leads to multiple scattering within the planetary boundary layer (PBL) and an increase in PBL SO2 AMF. However, under high AOD conditions, aerosol shielding effects dominate, which causes the PBL SO2 AMF to decrease with increasing AOD. The height of the SO2 layer and the APH are found to significantly influence the PBL SO2 AMF under high AOD conditions. When the SO2 and aerosol layers are of the same height, aerosol multiple scattering occurs dominantly within the PBL, which leads to an increase in the PBL SO2 AMF. When the APH is greater than the SO2 layer height, aerosol shielding effects dominate, which decreases the PBL SO2 AMF. When the SO2 and aerosol layers are of the same height under low AOD and solar zenith angle (SZA) conditions, increased surface reflectance is found to significantly increase the PBL SO2 AMF. However, high AOD dominates the surface reflectance contribution to PBL SO2 AMF. Under high SZA conditions, Rayleigh scattering contributes to a reduction in the light path length and PBL SO2 AMF. For volcanic SO2 AMF, high SZA enhances the light path length within the volcanic SO2 layer, as well as the volcanic SO2 AMF, because of the negligible photon loss by Rayleigh scattering at high altitudes. High aerosol loading and an APH that is greater than the SO2 peak height lead to aerosol shielding effects, which reduce the volcanic SO2 AMF. The SO2 AMF errors are also quantified as a function of uncertainty in the input data of AOD, APH, and surface reflectance. The SO2 AMF sensitivities and error analysis provided here can be used to develop effective error reduction strategies for satellite-based SO2 retrievals.