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.

SO2 and HCHO over the major cities of Kazakhstan from 2005 to 2016: influence of political, economic and industrial changes

Satellite observations of the Ozone Monitoring Instrument (OMI) for tropospheric sulfur dioxide (SO2) and formaldehyde (HCHO) column mass densities (CMD) are analyzed for the period 2005-2016 over the atmosphere of Kazakhstan. Regarding SO2 the major hot spots relate to regions with high population and large industrial facilities. Such an example is the city of Ekibastuz that hosts the biggest thermal power plants in the country and exhibits the higher SO2 CMD at national level. The annual average CMD in Ekibastuz reaches 2.5 × 10-5 kg/m2, whereas for the rest of the country respective values are 6 times lower. Other hotspots, mostly urban conglomerates such as Almaty and Nur-Sultan, experience high CMDs of SO2 in particular years, such as 2008. One of the main reasons for this behavior is the financial crisis of 2008, forcing the application of alternate heating sources based on cheap low-quality coal. Regarding HCHO, an oxygenated Volatile Organic Compound (VOC), the main hot spot is noticed over the city Atyrau, the oil capital of the country where two massive oil fields are located. The highest HCHO CMD (9 × 1015 molecules/cm2) appears in the summertime due to secondary production as a result of the photo-oxidation of VOCs emitted by industrial sectors, oil refinery plants and vehicles. Strongly elevated HCHO amounts are also observed in Nur-Sultan in 2012 that could be due to the residential coal combustion and vehicle exhaust under poor winter dispersion conditions. Significant reductions in HCHO observed between 2012 and 2015 can be attributed to two significant measures implemented in the country in 2013 that aimed at the improvement of air quality: the introduction of the emission trading system (ETS) for greenhouse gases and Euro-4 standards for new vehicles entering the national vehicle fleet.

Assessment of satellite-estimated near-surface sulfate and nitrate concentrations and their precursor emissions over China from 2006 to 2014

China is the largest anthropogenic aerosol-generating country worldwide; however, few studies have analyzed the PM_2.5 chemical components and their underlying precursor emissions over long periods and across the national domain. First, global 3-D tropospheric chemistry and transport model (GEOS-Chem)-integrated satellite-retrieved aerosol optical depth (AOD) and vertical profiles were used to estimate near-surface sulfate and nitrate levels at 10-km resolution over China from 2006 to 2014. Ground measurement validation of our satellite model yielded correlation coefficients (r) of 0.7 and 0.73 and normalized mean bias (NMB) values of -37.96% and - 32.73% for sulfate and nitrate, respectively. Second, analyses of the spatiotemporal distributions of sulfate and nitrate as well as the vertical density Ozone Monitoring Instrument (OMI)-measured SO₂ (PBL_SO₂) and NO₂ (TVCD_NO₂) indicated that the highest nitrate and sulfate levels occurred in the North China Plain (~25 μg/m³) and Sichuan Basin (SCB) (~30 μg/m³), respectively. The long-term variations in the estimated components and precursor gases indicated that the large sulfate decline was positively correlated with the SO₂ emission reduction due to the mandatory desulfurization implemented in 2007. The annual growth rate of sulfate relative to the national mean was -6.19%/yr, and the concentration decreased by 17.10% from 2011 to 2014. Energy consumption increases and a lack of control measures for NO₂ resulted in persistent increases in NO₂ emissions and nitrate concentrations from 2006 to 2010, particularly in the SCB. With energy consumption structure advancements, reductions in NO₂ emissions and corresponding nitrate levels over three typical regions were prominent after 2012. Third, the estimated national-scale uncertainties of satellite datasets at 0.1° × 0.1° were 26.88% for sulfate and 25.55% for nitrate. Differences in the spatial distributions and temporal trends between our estimated components and precursor gases were mainly attributed to the dataset accuracy, the data pre-processing strategy, inconsistent column density and near-surface mass concentration, meteorological variables and complex chemical reactions.

Ozone monitoring instrument observations of interannual increases in SO2 emissions from Indian coal-fired power plants during 2005-2012

Due to the rapid growth of electricity demand and the absence of regulations, sulfur dioxide (SO2) emissions from coal-fired power plants in India have increased notably in the past decade. In this study, we present the first interannual comparison of SO2 emissions and the satellite SO2 observations from the Ozone Monitoring Instrument (OMI) for Indian coal-fired power plants during the OMI era of 2005-2012. A detailed unit-based inventory is developed for the Indian coal-fired power sector, and results show that its SO2 emissions increased dramatically by 71% during 2005-2012. Using the oversampling technique, yearly high-resolution OMI maps for the whole domain of India are created, and they reveal a continuous increase in SO2 columns over India. Power plant regions with annual SO2 emissions greater than 50 Gg year(-1) produce statistically significant OMI signals, and a high correlation (R = 0.93) is found between SO2 emissions and OMI-observed SO2 burdens. Contrary to the decreasing trend of national mean SO2 concentrations reported by the Indian Government, both the total OMI-observed SO2 and annual average SO2 concentrations in coal-fired power plant regions increased by >60% during 2005-2012, implying the air quality monitoring network needs to be optimized to reflect the true SO2 situation in India.

Measuring global volcanic degassing with the Ozone Monitoring Instrument (OMI)

The ultraviolet (UV) Ozone Monitoring Instrument (OMI), launched on NASA's Aura satellite in July 2004, was the first space-based sensor to provide operational sulphur dioxide (SO2) measurements (OMSO2) for use by the scientific community. Herein, we discuss the application of OMSO2 data for the monitoring of global volcanic SO2 emissions, with an emphasis on lower tropospheric volcanic plumes. We review the algorithms used to produce OMSO2 data and highlight some key measurement sensitivity issues. The data processing scheme used to generate web-based OMSO2 data subsets for volcanic regions and estimate SO2 burdens in volcanic plumes is outlined. We describe three techniques to derive SO2 emission rates from the OMSO2 measurements, and employ one method (using single OMI pixels to estimate SO2 fluxes) to elucidate SO2 flux detection thresholds on a global scale. Applications of OMSO2 data to volcanic degassing studies are demonstrated using four case studies. These examples show how OMSO2 measurements correlate with changes in eruptive activity at Kilauea volcano (Hawaii), constrain small, potentially significant SO2 releases from reawakening, historically inactive volcanoes, track long-term changes in SO2 degassing from Nyiragongo volcano (D.R. Congo), and detect SO2 emissions from the remote Lastarria Volcano (Chile), in the actively deforming Lazufre region.