SO2 Vertical Column Densities Research Articles

Measuring The Spatio-Temporal Distribution of Sulfur Dioxide (SO2) with Copernicus Sentinel-5P Near Real Time in Medan City

This study aims to monitor the impact of sulfur dioxide (SO2), a significant contributor to atmospheric corrosion and associated with air pollution, in urban and industrial areas through empirical models of spatial distribution and temporal estimation in Medan. Datasets of Sentinel 5P NRTI are worth using to monitor the formation of sulfate aerosols or SO2 emissions from natural sources and anthropogenic origin in near real-time from 2019 until 2023 on the local scale, Medan. The source dataset covers 1,11 km of spatial image resolution on orbital in daily revisit time with a spectral bound between the ultraviolet and the shortwave infrared. The measurement of atmospheric SO2 concentrations is generated by enumerating the SO2 vertical column density technique at the soil surface with the cloud-based platform The Earth Engine (EE) Code Editor to handle large data sizes and produce interactive mapping. Based on the availability of auxiliary results, the number of spreading SO2 concentrations fell from 0,92 mmol/m2 in 2019 to 0,41 mmol/m2 in 2023, a reduction of 49.98 percent. The average of SO2 concentrations has decreased substantially over the years. Consequently, these pollutants have recorded long-term health and meteorological parameters impact that substances can rise or reduce acid rain.Keywords: Air pollution, Meteorological parameters, Sentinel 5P NRTI, SO2

The effectiveness of emission control policies in regulating air pollution over coastal ports of China: Spatiotemporal variations of NO2 and SO2

Air pollution over coastal port areas has become a major concern of today's world. As one of the largest shipping countries, China has issued a series of emission control policies to regulate air pollution in these areas. This study investigated the effectiveness of these policies by exploring the spatiotemporal variations of NO2 and SO2 in the five coastal port clusters i.e., Bohai Rim Area (BRA), Yangtze River Delta (YRD), Pearl River Delta (PRD), Southeast Coast (SEC) and Southwest Coast (SWC) of China from 2005 to 2020 using tropospheric NO2 and planetary boundary layer SO2 Vertical Column Densities (VCDs) retrieved from Ozone Monitoring Instrument (OMI). The NO2 levels were found to be the highest around 2011, whereas the SO2 levels showed decreasing trends after 2007, with rebounds found around 2011. BRA exhibited the highest average air pollution level compared to the other port clusters. PRD has implemented emission control policies earlier than the other port clusters, whereas YRD and BRA have controlled the NO2 and SO2 levels more effectively during 2010–2020. SWC saw an increase in the NO2 level during 2015–2020. As for individual ports, air pollution in Guangzhou port has been controlled most effectively during the entire study period; Qinhuangdao, Tangshan, Tianjin, Lianyungang, Qingdao and Rizhao have made great strides in reducing air pollution during 2010–2020. However, Beibu Gulf and Haikou showed clear increases in NO2 levels during 2018–2020 which may be attributed to strong growth in cargo throughput. Findings from this study can potentially help different authorities evaluate their effectiveness of air pollution control actions and support their future decision making.

Exploiting Sentinel-5P TROPOMI and Ground Sensor Data for the Detection of Volcanic SO2 Plumes and Activity in 2018-2021 at Stromboli, Italy.

Sulfur dioxide (SO2) degassing at Strombolian volcanoes is directly associated with magmatic activity, thus its monitoring can inform about the style and intensity of eruptions. The Stromboli volcano in southern Italy is used as a test case to demonstrate that the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (Sentinel-5P) satellite has the suitable spatial resolution and sensitivity to carry out local-scale SO2 monitoring of relatively small-size, nearly point-wise volcanic sources, and distinguish periods of different activity intensity. The entire dataset consisting of TROPOMI Level 2 SO2 geophysical products from UV sensor data collected over Stromboli from 6 May 2018 to 31 May 2021 is processed with purposely adapted Python scripts. A methodological workflow is developed to encompass the extraction of total SO2 Vertical Column Density (VCD) at given coordinates (including conditional VCD for three different hypothetical peaks at 0–1, 7 and 15 km), as well as filtering by quality in compliance with the Sentinel-5P Validation Team’s recommendations. The comparison of total SO2 VCD time series for the main crater and across different averaging windows (3 × 3, 5 × 5 and 4 × 2) proves the correctness of the adopted spatial sampling criterion, and practical recommendations are proposed for further implementation in similar volcanic environments. An approach for detecting SO2 VCD peaks at the volcano is trialed, and the detections are compared with the level of SO2 flux measured at ground-based instrumentation. SO2 time series analysis is complemented with information provided by contextual Sentinel-2 multispectral (in the visible, near and short-wave infrared) and Suomi NPP VIIRS observations. The aim is to correctly interpret SO2 total VCD peaks when they either (i) coincide with medium to very high SO2 emissions as measured in situ and known from volcanological observatory bulletins, or (ii) occur outside periods of significant emissions despite signs of activity visible in Sentinel-2 data. Finally, SO2 VCD peaks in the time series are further investigated through daily time lapses during the paroxysms in July–August 2019, major explosions in August 2020 and a more recent period of activity in May 2021. Hourly wind records from ECMWF Reanalysis v5 (ERA5) data are used to identify local wind direction and SO2 plume drift during the time lapses. The proposed analysis approach is successful in showing the SO2 degassing associated with these events, and warning whenever the SO2 VCD at Stromboli may be overestimated due to clustering with the plume of the Mount Etna volcano.

Investigation of the Influence of Water Vapor on Heavy Pollution and Its Relationship With AOD Using MAX‐DOAS on the Coast of the Yellow Sea

AbstractMulti‐AXis Differential Optical Absorption Spectroscopy (MAX‐DOAS) observations were carried out from March 1, 2019 to February 29, 2020 in Qingdao, China, on the coast of the Yellow Sea (120.67°E, 36.35°N). Atmospheric parameters retrieved from the MAX‐DOAS instrument included vertical profiles of aerosol extinction, gaseous aerosol precursors (NO2, SO2), and H2O. First, the seasonal relationship between aerosol optical depth (AOD) and the H2O vertical column density (VCD) was analyzed. The correlation coefficients (r) between AOD and H2O VCD were largest in the winter, followed by spring, autumn, and summer. In addition, the correlation during heavily polluted weather was much higher than that during clean weather or slightly polluted weather. Then, an analysis of the wind speed and direction, and trace gas VCDs during the months with frequent pollution (December 2019 and January 2020) found that heavy pollution episodes easily occurred in Qingdao due to a combination of high H2O concentrations and low wind speeds. Out of four pollution events (P1, P2, P3, P4), both the H2O concentration and pollution were highest during the first event (P1). The H2O VCD, AOD, sulfate AOD, and total column HNO3 simultaneously increased during P1, while the NO2 and SO2 VCDs decreased. These trends are consistent with liquid phase reactions. Finally, the 1,000 m backward trajectory for the wind and the gas profiles during P1 revealed that the pollutants increased in Qingdao due to the influence of a polluted air mass from the western inland regions.

Effect of Error in SO2 Slant Column Density on the Accuracy of SO2 Transport Flow Rate Estimates Based on GEMS Synthetic Radiances

This study investigates the uncertainties associated with estimates of the long-range transport SO2 (LRT-SO2) flow rate calculated hourly using Geostationary Environment Monitoring Spectrometer (GEMS) synthetic radiances. These radiances were simulated over the Korean Peninsula and the surrounding regions using inputs from the GEOS-Chem model for January, April, July, and October 2016. The LRT-SO2 calculation method, which requires SO2 vertical column densities, wind data, and planetary boundary layer information, was used to quantify the effects of the SO2 slant column density (SCD) retrieval error and uncertainties in wind data on the accuracy of the LRT-SO2 estimates. The effects were estimated for simulations of three anthropogenic and three volcanic SO2 transport events. When there were no errors in the GEMS SO2 SCD and wind data, the average true LRT-SO2 flow rates (standard deviation) and those calculated for these events were 1.17 (± 0.44) and 1.21 (±0.44) Mg/h, respectively. However, the averages of the true LRT-SO2 flow rates and those calculated for the three anthropogenic (volcanic) SO2 events were 0.61 (1.17) and 0.64 (1.20) Mg/h, respectively, in the presence of GEMS SO2 SCD errors. In the presence of both errors in the GEMS SO2 SCD and wind data, the averages of the true LRT-SO2 flow rates and those calculated for the three anthropogenic (volcanic) SO2 events were 0.61 (1.17) and 0.61 (1.04) Mg/h, respectively. This corresponds to differences of 2.1% to 23.1% between the simulated and true mean LRT-SO2 flow rates. The mean correlation coefficient (R), intercept, and slope between the true and simulated LRT-SO2 flow rates were 0.51, 0.43, and 0.45 for the six simulated events, respectively. This study demonstrates that SO2 SCD accuracy is an important factor in improving estimates of LRT-SO2 flow rates.

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.

Recommendations for HCHO and SO2 Retrieval Settings from MAX-DOAS Observations under Different Meteorological Conditions

Recently, the occurrence of fog and haze over China has increased. The retrieval of trace gases from the multi-axis differential optical absorption spectroscopy (MAX-DOAS) is challenging under these conditions. In this study, various reported retrieval settings for formaldehyde (HCHO) and sulfur dioxide (SO2) are compared to evaluate the performance of these settings under different meteorological conditions (clear day, haze, and fog). The dataset from 1st December 2019 to 31st March 2020 over Nanjing, China, is used in this study. The results indicated that for HCHO, the optimal settings were in the 324.5–359 nm wavelength window with a polynomial order of five. At these settings, the fitting and root mean squared (RMS) errors for column density were considerably improved for haze and fog conditions, and the differential slant column densities (DSCDs) showed more accurate values compared to the DSCDs between 336.5 and 359 nm. For SO2, the optimal settings for retrieval were found to be at 307–328 nm with a polynomial order of five. Here, root mean square (RMS) and fitting errors were significantly lower under all conditions. The observed HCHO and SO2 vertical column densities were significantly lower on fog days compared to clear days, reflecting a decreased chemical production of HCHO and aqueous phase oxidation of SO2 in fog droplets.

SO2 mitigation in China's coal-fired power plants: A satellite-based assessment on compliance and enforcement

Compliance monitoring plays an indispensable role in enforcing environmental policies for achieving compliance. This study examines the compliance and enforcement of SO2 mitigation policies in China's coal-fired power plants from both temporal and spatial perspectives with Aura Ozone Monitoring Instrument (OMI) level 2 sulfur dioxide total column product (OMSO2 v003). We apply a pixel-averaging method with the pixel size being 0.02 × 0.02°, the time range being one year, and the averaging radius being 18 km. Results show that SO2 Vertical Column Density (VCD) enhancements of coal-fired power plants decreased by 94.3% from January 2006 to April 2020. Most of the reduction took place in two compliance episodes, being in 2008 and after 2014. They can be related to the “desulfurized electricity tariff” and the “ultra-low emission” policies that entered into effect in July 2007 and from September 2013, respectively. Furthermore, the SO2 VCD enhancements rebounded in 2006 and 2011, the first years of 11th and 12th Five-Year Plans to reflect likely more relaxed enforcement and compliance. Policy enforcement differed significantly across provinces as indicated by when their coal-fired power plants complied and how much reduction was made. Environmental supervision and inspection could target those provinces with poorer compliance statuses for more effective and efficient enforcement.

Impact of COVID-19 Pandemic on Air Pollution in Poland Based on Surface Measurements and Satellite Data

Since its first detection in December 2019 in the Chinese city of Wuhan, the virus has become a global pandemic within just three months. The Polish government declared a state of emergency on March 14, 2020, which was connected with the adoption of a number of measures aimed to prevent the spread of the virus. These restrictive measures have led to improvements in air quality throughout the country. Therefore, evaluation of the reduction in anthropogenic emissions due to COVID-19 and related government measures to constrain its spread is crucial to define its impact on air pollution. During this study, aerosol optical depth (AOD) observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used along with tropospheric NO2 and SO2 vertical column densities from TROPOspheric Monitoring Instrument (TROPOMI). The data on ground-based concentrations of pollutants (PM2.5, PM10, NO2 and SO2) obtained from air quality monitoring stations were also considered to assess changes in aerosols and air pollutants connected with the cessation of various kinds of anthropogenic and industrial activities due to preventive measures for COVID-19. In large cities of the country, the concentrations of PM2.5, PM10 and NO2 were reduced in the range from –5.1% to –35.5%, from –8.3% to –33.1% and from –0.4% to –18.8%. In addition, satellite data for NO2 and SO2 also indicate a decrease in concentration across the country by –10.8% and –25.6% during the COVID-19 restrictions period. The lockdown events may play a vital role as a potential solution to reduce air pollution in future as it may not be uncommon for governments to introduce deliberately selective hotspot lockdowns to control pollution levels.

A multi-sensor satellite-based archive of the largest SO<sub>2</sub> volcanic eruptions since 2006

Abstract. We present a multi-sensor archive collecting spatial and temporal information about volcanic SO2 clouds generated by the 11 largest eruptions of this century. The detection and monitoring of volcanic clouds are an important topic for aviation management, climate issues and weather forecasts. Several studies focusing on single eruptive events exist, but no archive available at the moment combines quantitative data from as many instruments. We archived and collocated the SO2 vertical column density estimations from three different satellite instruments (AIRS, IASI and GOME-2), atmospheric parameters as vertical profiles from the Global Navigation Satellite Systems (GNSS) Radio Occultations (RO), and the cloud-top height and aerosol type from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Additionally, we provide information about the cloud-top height from three different algorithms and the atmospheric anomaly due to the presence of the cloud. The dataset is gathering 206 d of SO2 data, collocated with 44 180 backscatter profiles and 64 764 radio occultation profiles. The modular structure of the archive allows an easy collocation of the datasets according to the users' needs, and the cross-comparison of the datasets shows different consistency of the parameters estimated with different sensors and algorithms, according to the sensitivity and resolution of the instruments. The data described here are published with a DOI at https://doi.org/10.5880/fidgeo.2020.016 (Tournigand et al., 2020a).

Version 2 Ozone Monitoring Instrument SO<sub>2</sub> product (OMSO2 V2): new anthropogenic SO<sub>2</sub> vertical column density dataset

Abstract. The Ozone Monitoring Instrument (OMI) has been providing global observations of SO2 pollution since 2004. Here we introduce the new anthropogenic SO2 vertical column density (VCD) dataset in the version 2 OMI SO2 product (OMSO2 V2). As with the previous version (OMSO2 V1.3), the new dataset is generated with an algorithm based on principal component analysis of OMI radiances but features several updates. The most important among those is the use of expanded lookup tables and model a priori profiles to estimate SO2 Jacobians for individual OMI pixels, in order to better characterize pixel-to-pixel variations in SO2 sensitivity including over snow and ice. Additionally, new data screening and spectral fitting schemes have been implemented to improve the quality of the spectral fit. As compared with the planetary boundary layer SO2 dataset in OMSO2 V1.3, the new dataset has substantially better data quality, especially over areas that are relatively clean or affected by the South Atlantic Anomaly. The updated retrievals over snow/ice yield more realistic seasonal changes in SO2 at high latitudes and offer enhanced sensitivity to sources during wintertime. An error analysis has been conducted to assess uncertainties in SO2 VCDs from both the spectral fit and Jacobian calculations. The uncertainties from spectral fitting are reflected in SO2 slant column densities (SCDs) and largely depend on the signal-to-noise ratio of the measured radiances, as implied by the generally smaller SCD uncertainties over clouds or for smaller solar zenith angles. The SCD uncertainties for individual pixels are estimated to be ∼ 0.15–0.3 DU (Dobson units) between ∼ 40∘ S and ∼ 40∘ N and to be ∼ 0.2–0.5 DU at higher latitudes. The uncertainties from the Jacobians are approximately ∼ 50 %–100 % over polluted areas and are primarily attributed to errors in SO2 a priori profiles and cloud pressures, as well as the lack of explicit treatment for aerosols. Finally, the daily mean and median SCDs over the presumably SO2-free equatorial east Pacific have increased by only ∼ 0.0035 DU and ∼ 0.003 DU respectively over the entire 15-year OMI record, while the standard deviation of SCDs has grown by only ∼ 0.02 DU or ∼ 10%. Such remarkable long-term stability makes the new dataset particularly suitable for detecting regional changes in SO2 pollution.

Probabilistic retrieval of volcanic SO<sub>2</sub> layer height and partial column density using the Cross-track Infrared Sounder (CrIS)

Abstract. During most volcanic eruptions and many periods of volcanic unrest, detectable quantities of sulfur dioxide (SO2) are injected into the atmosphere at a wide range of altitudes, from ground level to the lower stratosphere. Because the fine ash fraction of a volcanic plume is, at times, colocated with SO2 emissions, global tracking of volcanic SO2 is useful in tracking the hazard long after ash detection becomes dominated by noise. Typically, retrievals of SO2 vertical column density (VCD) have relied heavily on hyperspectral ultraviolet measurements. More recently, infrared sounders have provided additional VCD measurements and estimates of the SO2 layer altitude, adding significant value to real-time monitoring of volcanic emissions and climatological analyses. These methods can provide fast and accurate physics-based retrievals of VCD and altitude without regard to solar irradiance, meaning that they are effective day and night and can observe high-latitude SO2 even in the winter. In this study, we detail a probabilistic enhancement of an infrared SO2 retrieval method, based on a modified trace gas retrieval, to estimate SO2 VCD and altitude probabilistically using the Cross-track Infrared Sounder (CrIS) on the Joint Polar Satellite System (JPSS) series of satellites. The methodology requires the characterization of real SO2-free spectra aggregated seasonally and spatially. The probabilistic approach replaces altitude and VCD estimates with probability density functions for the layer height and the partial VCD at multiple heights, fully quantifying the retrieval uncertainty and allowing the estimation of SO2 partitioning by layer. This framework adds significant value over basic VCD and altitude retrieval because it can be used to assign probabilities of SO2 occurrence to different atmospheric intervals. We highlight analyses of several recent significant eruptions, including the 22 June 2019 eruption of Raikoke volcano, in the Kuril Islands; the mid-December 2016 eruption of Bogoslof volcano, in the Aleutian Islands; and the 26 June 2018 eruption of Sierra Negra volcano, in the Galapagos Islands. This retrieval method is currently being implemented in the VOLcanic Cloud Analysis Toolkit (VOLCAT), where it will be used to generate additional cloud object properties for real-time detection, probabilistic characterization, and tracking of volcanic clouds in support of aviation safety.

Evaluation of the accuracy of the Sentinel-5 Precursor operational SO<sub>2</sub> 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.

Impact of natural gas production on nitrogen dioxide and sulphur dioxide over Northeast British Columbia, Canada

Northeast British Columbia (BC) Canada, is a region in which natural gas production has undergone rapid development since 2007. We used nitrogen dioxide (NO2) and sulphur dioxide (SO2) data products of the Ozone Monitoring Instrument (OMI) to assess the impact of natural gas development activity on air quality in this region from 2005 to 2018. We noticed that values of both pollutants were elevated in the immediate vicinity of large emission sources within the Montney formation and Horn River Basin – regions, which have experienced an increase in unconventional natural gas activities. Places with elevated NO2 Vertical Column Densities (VCDs) are Fort St. John, Taylor, and Dawson Creek located in the Montney formation, and higher SO2 VCDs are found near the Fort Nelson gas plant situated in the Horn River and Liard Basin areas. Although all the OMI data products consistently reported relatively high NO2 VCDs in the same areas, VCD values vary substantially with data products largely due to differences in Air Mass Factor (AMF) calculations. The rate of increase in NO2 VCDs and mass between 2005 and 2018 in the Dawson Creek area was assessed at 2.34% yr−1 and 4.32% yr−1, respectively, and these rates of change are statistically significant. Although we obtained an overall increasing trend for NO2 in Northeast BC, we also noticed a decreasing trend in the period of 2011–2013, which may be attributed, in part, to compliance and enforcement of regulations concerning flaring activities from oil and gas activities in Northeast BC, or due to less development activities. From our analysis, we suggest that the current air quality monitoring network in Northeast BC should be expanded to capture the spatial distribution of SO2 by deploying one additional station near Fort Nelson equipped with meteorology and SO2 monitoring systems.

A new discrete wavelength backscattered ultraviolet algorithm for consistent volcanic SO<sub>2</sub> retrievals from multiple satellite missions

Abstract. This paper describes a new discrete wavelength algorithm developed for retrieving volcanic sulfur dioxide (SO2) vertical column density (VCD) from UV observing satellites. The Multi-Satellite SO2 algorithm (MS_SO2) simultaneously retrieves column densities of sulfur dioxide, ozone, and Lambertian effective reflectivity (LER) and its spectral dependence. It is used operationally to process measurements from the heritage Total Ozone Mapping Spectrometer (TOMS) onboard NASA's Nimbus-7 satellite (N7/TOMS: 1978–1993) and from the current Earth Polychromatic Imaging Camera (EPIC) onboard Deep Space Climate Observatory (DSCOVR: 2015–ongoing) from the Earth–Sun Lagrange (L1) orbit. Results from MS_SO2 algorithm for several volcanic cases were assessed using the more sensitive principal component analysis (PCA) algorithm. The PCA is an operational algorithm used by NASA to retrieve SO2 from hyperspectral UV spectrometers, such as the Ozone Monitoring Instrument (OMI) onboard NASA's Earth Observing System Aura satellite and Ozone Mapping and Profiling Suite (OMPS) onboard NASA–NOAA Suomi National Polar Partnership (SNPP) satellite. For this comparative study, the PCA algorithm was modified to use the discrete wavelengths of the Nimbus-7/TOMS instrument, described in Sect. S1 of the Supplement. Our results demonstrate good agreement between the two retrievals for the largest volcanic eruptions of the satellite era, such as the 1991 Pinatubo eruption. To estimate SO2 retrieval systematic uncertainties, we use radiative transfer simulations explicitly accounting for volcanic sulfate and ash aerosols. Our results suggest that the discrete-wavelength MS_SO2 algorithm, although less sensitive than hyperspectral PCA algorithm, can be adapted to retrieve volcanic SO2 VCDs from contemporary hyperspectral UV instruments, such as OMI and OMPS, to create consistent, multi-satellite, long-term volcanic SO2 climate data records.

Natural and anthropogenic contributions to long-term variations of SO2, NO2, CO, and AOD over East China

Concentrations of atmospheric pollutants over East China have varied considerably during the past decades. These variations are partly due to variations of human activities, e.g., increasing energy consumption and implementation of government emission control policies, and partly to natural fluctuations. This study aims to separate the effects of natural processes and anthropogenic activities on the increase/decrease of the concentrations of some of the most important pollutants (SO2, NO2, CO and aerosols) over East China in the last decade. This was achieved by the comparison of the temporal variations in long-term time series of satellite-retrieved aerosol optical depth (AOD) and vertical column densities (VCDs) of SO2, NO2, and CO, with those in model-simulated time series of the natural variations only. The latter were created by the use of the same anthropogenic emissions throughout the whole simulation, while using re-analysis data (MERRA) to describe meteorological processes and natural emissions. Thus, the comparison between observed and simulated temporal variations reveals the effects due to anthropogenic emissions only, assuming that the atmospheric processes affect natural and anthropogenic species in the same way. In the analysis, a Kolmogorov–Zurbenko (KZ) filter is used to extract long-term components from both the observed and simulated data and normalization to the situation at a certain reference point is used to eliminate bias between observations and simulations. By this new method, natural and anthropogenic contributions to long-term variations of trace gases and AOD are quantitatively estimated. The results show that NO2 VCDs increased from 2004 to 2011 by 76% and of the overall increase in this period only 1% ± 1% was attributed to natural factors, 99% ± 1% attributed to anthropogenic factors. AOD increased by 24% between 2001 and 2011 and of the overall increase 24% ± 32% was due to natural factors and 76% ± 32% was due to anthropogenic factors. SO2 VCDs decreased by 15% from 2007 to 2013, natural and anthropogenic factors contributed respectively 16% ± 14% and 84% ± 14% to the overall decrease in this period. CO decreased since 2003 with 13% and of the overall decrease 6% ± 6% was due to natural factors and 94% ± 6% was due to anthropogenic factors.

Ship-based MAX-DOAS measurements of tropospheric NO<sub>2</sub>, SO<sub>2</sub>, and HCHO distribution along the Yangtze River

Abstract. In this paper, we present ship-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of tropospheric trace gases' distribution along the Yangtze River during winter 2015. The measurements were performed along the Yangtze River between Shanghai and Wuhan, covering major industrial areas in eastern China. Tropospheric vertical column densities (VCDs) of nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) were retrieved using the air mass factor calculated by the radiative transfer model. Enhanced tropospheric NO2 and SO2 VCDs were detected over downwind areas of industrial zones over the Yangtze River. In addition, spatial distributions of atmospheric pollutants are strongly affected by meteorological conditions; i.e., positive correlations were found between concentration of pollutants and wind speed over these areas, indicating strong influence of transportation of pollutants from high-emission upwind areas along the Yangtze River. Comparison of tropospheric NO2 VCDs between ship-based MAX-DOAS and Ozone Monitoring Instrument (OMI) satellite observations shows good agreement with each other, with a Pearson correlation coefficient (R) of 0.82. In this study, the NO2 ∕ SO2 ratio was used to estimate the relative contributions of industrial sources and vehicle emissions to ambient NO2 levels. Analysis results of the NO2 ∕ SO2 ratio show a higher contribution of industrial NO2 emissions in Jiangsu Province, while NO2 levels in Jiangxi and Hubei provinces are mainly related to vehicle emissions. These results indicate that different pollution control strategies should be applied in different provinces. In addition, multiple linear regression analysis of ambient carbon monoxide (CO) and odd oxygen (Ox) indicated that the primary emission and secondary formation of HCHO contribute 54.4 ± 3.7 % and 39.3 ± 4.3 % to the ambient HCHO, respectively. The largest contribution from primary emissions in winter suggested that photochemically induced secondary formation of HCHO is reduced due to lower solar irradiance in winter. Our findings provide an improved understanding of major pollution sources along the eastern part of the Yangtze River which are useful for designing specific air pollution control policies.

Multi-source SO<sub>2</sub> emission retrievals and consistency of satellite and surface measurements with reported emissions

Abstract. Reported sulfur dioxide (SO2) emissions from US and Canadian sources have declined dramatically since the 1990s as a result of emission control measures. Observations from the Ozone Monitoring Instrument (OMI) on NASA's Aura satellite and ground-based in situ measurements are examined to verify whether the observed changes from SO2 abundance measurements are quantitatively consistent with the reported changes in emissions. To make this connection, a new method to link SO2 emissions and satellite SO2 measurements was developed. The method is based on fitting satellite SO2 vertical column densities (VCDs) to a set of functions of OMI pixel coordinates and wind speeds, where each function represents a statistical model of a plume from a single point source. The concept is first demonstrated using sources in North America and then applied to Europe. The correlation coefficient between OMI-measured VCDs (with a local bias removed) and SO2 VCDs derived here using reported emissions for 1° by 1° gridded data is 0.91 and the best-fit line has a slope near unity, confirming a very good agreement between observed SO2 VCDs and reported emissions. Having demonstrated their consistency, seasonal and annual mean SO2 VCD distributions are calculated, based on reported point-source emissions for the period 1980–2015, as would have been seen by OMI. This consistency is further substantiated as the emission-derived VCDs also show a high correlation with annual mean SO2 surface concentrations at 50 regional monitoring stations.

OMI-measured increasing SO<sub>2</sub> emissions due to energy industry expansion and relocation in northwestern China

Abstract. The rapid growth of economy makes China the largest energy consumer and sulfur dioxide (SO2) emitter in the world. In this study, we estimated the trends and step changes in the planetary boundary layer (PBL) vertical column density (VCD) of SO2 from 2005 to 2015 over China measured by the Ozone Monitoring Instrument (OMI). We show that these trends and step change years coincide with the effective date and period of the national strategy for energy development and relocation in northwestern China and the regulations in the reduction of SO2 emissions. Under the national regulations for the reduction of SO2 emissions in eastern and southern China, SO2 VCD in the Pearl River Delta (PRD) of southern China exhibited the largest decline during 2005–2015 at a rate of −7 % yr−1, followed by the North China Plain (NCP) (−6.7 % yr−1), Sichuan Basin (−6.3 % yr−1), and Yangtze River Delta (YRD) (−6 % yr−1). The Mann–Kendall (MK) test reveals the step change points of declining SO2 VCD in 2009 for the PRD and 2012–2013 for eastern China responding to the implementation of SO2 control regulation in these regions. In contrast, the MK test and regression analysis also revealed increasing trends of SO2 VCD in northwestern China, particularly for several hot spots featured by growing SO2 VCD in those large-scale energy industry bases in northwestern China. The enhanced SO2 VCD is potentially attributable to increasing SO2 emissions due to the development of large-scale energy industry bases in energy-abundant northwestern China under the national strategy for the energy safety of China in the 21st century. We show that these large-scale energy industry bases could overwhelm the trends and changes in provincial total SO2 emissions in northwestern China and contribute increasingly to the national total SO2 emissions in China. Given that northwestern China is more ecologically fragile and uniquely susceptible to atmospheric pollution than the rest of China, increasing SO2 emissions in this part of China should not be overlooked and merit scientific research.

Validation of OMI, GOME-2A and GOME-2B tropospheric NO<sub>2</sub>, SO<sub>2</sub> and HCHO products using MAX-DOAS observations from 2011 to 2014 in Wuxi, China: investigation of the effects of priori profiles and aerosols on the satellite products

Abstract. Tropospheric vertical column densities (VCDs) of NO2, SO2 and HCHO derived from the Ozone Monitoring Instrument (OMI) on AURA and the Global Ozone Monitoring Experiment 2 aboard METOP-A (GOME-2A) and METOP-B (GOME-2B) are widely used to characterize the global distributions, trends and dominating sources of these trace gases. They are also useful for the comparison with chemical transport models (CTMs). We use tropospheric VCDs and vertical profiles of NO2, SO2 and HCHO derived from MAX-DOAS measurements from 2011 to 2014 in Wuxi, China, to validate the corresponding products (daily and bi-monthly-averaged data) derived from OMI and GOME-2A/B by different scientific teams. Prior to the comparison, the spatial and temporal coincidence criteria for MAX-DOAS and satellite data are determined by a sensitivity study using different spatial and temporal averaging conditions. Cloud effects on both MAX-DOAS and satellite observations are also investigated. Our results indicate that the discrepancies between satellite and MAX-DOAS results increase with increasing effective cloud fraction and are dominated by the effects of clouds on the satellite products. In comparison with MAX-DOAS, we found a systematic underestimation of all SO2 (40 to 57 %) and HCHO products (about 20 %), and an overestimation of the GOME-2A/B NO2 products (about 30 %), but good consistency with the DOMINO version 2 NO2 product. To better understand the reasons for these differences, we evaluated the a priori profile shapes used in the OMI retrievals (derived from CTM) by comparison with those derived from the MAX-DOAS observations. Significant differences are found for the SO2 and HCHO profile shapes derived from the IMAGES model, whereas on average good agreement is found for the NO2 profile shapes derived from the TM4 model. We also applied the MAX-DOAS profile shapes to the satellite retrievals and found that these modified satellite VCDs agree better with the MAX-DOAS VCDs than the VCDs from the original data sets by up to 10, 47 and 35 % for NO2, SO2 and HCHO, respectively. Furthermore, we investigated the effect of aerosols on the satellite retrievals. For OMI observations of NO2, a systematic underestimation is found for large AOD, which is mainly attributed to effect of the aerosols on the cloud retrieval and the subsequent application of a cloud correction scheme (implicit aerosol correction). In contrast, the effect of aerosols on the clear-sky air mass factor (explicit aerosol correction) has a smaller effect. For SO2 and HCHO observations selected in the same way, no clear aerosol effect is found, probably because for the considered data sets no cloud correction is applied (and also because of the larger scatter). From our findings we conclude that for satellite observations with cloud top pressure (CTP) > 900 hPa and effective cloud fraction (eCF) < 10 % the application of a clear-sky air mass factor might be a good option if accurate aerosol information is not available. Another finding of our study is that the ratio of morning-to-afternoon NO2 VCDs can be considerably overestimated if results from different sensors and/or retrievals (e.g. OMI and GOME-2) are used, whereas fewer deviations for HCHO and SO2 VCDs are found.