Dataset Information

Impact of Coronavirus Outbreak on NO₂ Pollution Assessed Using TROPOMI and OMI Observations.

ABSTRACT: Spaceborne NO₂ column observations from two high-resolution instruments, Tropospheric Monitoring Instrument (TROPOMI) on board Sentinel-5 Precursor and Ozone Monitoring Instrument (OMI) on Aura, reveal unprecedented NO₂ decreases over China, South Korea, western Europe, and the United States as a result of public health measures enforced to contain the coronavirus disease outbreak (Covid-19) in January-April 2020. The average NO₂ column drop over all Chinese cities amounts to -40% relative to the same period in 2019 and reaches up to a factor of ~2 at heavily hit cities, for example, Wuhan, Jinan, while the decreases in western Europe and the United States are also significant (-20% to -38%). In contrast with this, although Iran is also strongly affected by the disease, the observations do not show evidence of lower emissions, reflecting more limited health measures.

SUBMITTER: Bauwens M

PROVIDER: S-EPMC7261997 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Impact of Coronavirus Outbreak on NO2 Pollution Assessed Using TROPOMI and OMI Observations.

Bauwens M M Compernolle S S Stavrakou T T Müller J-F JF van Gent J J Eskes H H Levelt P F PF van der A R R Veefkind J P JP Vlietinck J J Yu H H Zehner C C

Geophysical research letters 20200605 11

Spaceborne NO2 column observations from two high-resolution instruments, Tropospheric Monitoring Instrument (TROPOMI) on board Sentinel-5 Precursor and Ozone Monitoring Instrument (OMI) on Aura, reveal unprecedented NO2 decreases over China, South Korea, western Europe, and the United States as a result of public health measures enforced to contain the coronavirus disease outbreak (Covid-19) in January-April 2020. The average NO2 column drop over all Chinese citi ...[more]

PMID: 32836515

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Project description:The production of nitrogen oxides (NO x = NO + NO 2 ) is substantial in urban areas and from fossil fuel-fired power plants, causing both local and regional pollution, with severe consequences for human health. To estimate their emissions and implement air quality policies, authorities often rely on reported emission inventories. The island of Cyprus is de facto divided into two different political entities, and as a result, such emissions inventories are not systematically available for the whole island. We map NO x emissions in Cyprus for two 6-month periods in 2021 and 2022 with a flux-divergence scheme, using spaceborne retrievals of nitrogen dioxide (NO 2 ) columns at high spatial resolution from the TROPOMI instrument, as well as horizontal wind data to derive advection and concentrations of OH, NO, and NO 2 to derive chemical processes. Emissions are estimated under three different sets of parameters using ECMWF data and WRF-Chem simulations. These sets are chosen for their differences in spatial resolution and representation of wind and air composition. Exploiting the low emissions in Cyprus, we show that the flux-divergence method is limited by the resolution of wind and hydroxyl radical, the signal-to-noise ratio of the observed tropospheric column densities, and the NO x :NO 2 ratio above the main pollution sources. Such limitations lead to large discrepancies in the emissions calculated with the three different sets of parameters, making it difficult to estimate NO x emissions for the five power plants of the island without high uncertainties. Nevertheless, the obtained emissions display a higher seasonality than reported or inventory emissions. For the two power plants in the south, the different mean daytime output estimates appear to be significantly higher than the bottom-up estimates. They are also higher than those from the power plants in the south combined, despite a much lower production capacity, illustrating the application of different environmental norms and the use of different technologies and fuels in the two parts of Cyprus.

Project description:Atmospheric pollutant data retrieved through satellite sensors are continually used to assess changes in air quality in the lower atmosphere. During the COVID-19 pandemic, several studies started to use satellite measurements to evaluate changes in air quality in many different regions worldwide. However, although satellite data is continuously validated, it is known that its accuracy may vary between monitored areas, requiring regionalized quality assessments. Thus, this study aimed to evaluate whether satellites could measure changes in the air quality of the state of São Paulo, Brazil, during the COVID-19 outbreak; and to verify the relationship between satellite-based data [Tropospheric NO2 column density and Aerosol Optical Depth (AOD)] and ground-based concentrations [NO2 and particulate material (PM; coarse: PM10 and fine: PM2.5)]. For this purpose, tropospheric NO2 obtained from the TROPOMI sensor and AOD retrieved from MODIS sensor data by using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm were compared with concentrations obtained from 50 automatic ground monitoring stations. The results showed low correlations between PM and AOD. For PM10, most stations showed correlations lower than 0.2, which were not significant. The results for PM2.5 were similar, but some stations showed good correlations for specific periods (before or during the COVID-19 outbreak). Satellite-based Tropospheric NO2 proved to be a good predictor for NO2 concentrations at ground level. Considering all stations with NO2 measurements, correlations >0.6 were observed, reaching 0.8 for specific stations and periods. In general, it was observed that regions with a more industrialized profile had the best correlations, in contrast with rural areas. In addition, it was observed about 57% reductions in tropospheric NO2 throughout the state of São Paulo during the COVID-19 outbreak. Variations in air pollutants were linked to the region economic vocation, since there were reductions in industrialized areas (at least 50% of the industrialized areas showed >20% decrease in NO2) and increases in areas with farming and livestock characteristics (about 70% of those areas showed increase in NO2). Our results demonstrate that Tropospheric NO2 column densities can serve as good predictors of NO2 concentrations at ground level. For MAIAC-AOD, a weak relationship was observed, requiring the evaluation of other possible predictors to describe the relationship with PM. Thus, it is concluded that regionalized assessment of satellite data accuracy is essential for assertive estimates on a regional/local level. Good quality information retrieved at specific polluted areas does not assure a worldwide use of remote sensor data.

Dataset Information

Impact of Coronavirus Outbreak on NO₂ Pollution Assessed Using TROPOMI and OMI Observations.

Publications

Impact of Coronavirus Outbreak on NO<sub>2</sub> Pollution Assessed Using TROPOMI and OMI Observations.

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