Dataset Information

Non-negligible impacts of clean air regulations on the reduction of tropospheric NO₂ over East China during the COVID-19 pandemic observed by OMI and TROPOMI.

ABSTRACT: We study the variation of tropospheric NO₂ vertical column densities (TropNO₂VCDs) over East China during the 2005-2020 lunar new year (LNY) holiday seasons to understand factors on the reduction of tropospheric NO₂ during the outbreak of COVID-19 in East China using Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) observations. TropNO₂VCDs from OMI and TROPOMI reveal sharp reductions of 33%-72% during 2020 LNY holiday season and the co-occurring outbreak of COVID-19 relative to the climatological mean of 2005-2019 LNY holiday seasons, and 22%-67% reduction relative to the 2019 LNY holiday season. These reductions of TropNO₂VCD occur majorly over highly polluted metropolitan areas with condensed industrial and transportation emission sources. COVID-19 control measures including lockdowns and shelter-in-place regulations are the primary reason for these tropospheric NO₂ reductions over most areas of East China in 2020 LNY holiday season relative to the 2019 LNY holiday season, as COVID-19 control measures may explain ~87%-90% of tropospheric NO₂ reduction in Wuhan as well as ~62%-89% in Beijing, Yangtze River Delta (YRD) and Sichuan Basin areas. The clean air regulation of China also contributes significantly to reductions of tropospheric NO₂ simultaneously and is the primary factor in the Pearl River Delta (PRD) area, by explaining ~56%-63% of the tropospheric NO₂ reduction there.

SUBMITTER: Huang G

PROVIDER: S-EPMC7372270 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Non-negligible impacts of clean air regulations on the reduction of tropospheric NO2 over East China during the COVID-19 pandemic observed by OMI and TROPOMI.

Huang Guanyu G Sun Kang K

The Science of the total environment 20200721

We study the variation of tropospheric NO2 vertical column densities (TropNO2VCDs) over East China during the 2005-2020 lunar new year (LNY) holiday seasons to understand factors on the reduction of tropospheric NO2 during the outbreak of COVID-19 in East China using Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) observations. TropNO2VCDs from OMI and TROPOMI reveal sharp reductions of 33%-72% during 2020 LNY holiday ...[more]

PMID: 32738690

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Project description:Airborne and ground-based Pandora spectrometer NO2 column measurements were collected during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region, which coincided with early observations from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOMI NO2 Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO2. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r 2 =0.92 and slope of 1.03), with the largest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representativity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representativity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250m×250m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r 2 = 0.96) than Pandora measurements are with TROPOMI (r 2 = 0.84). The largest outliers between TROPOMI and the reference measurements appear to stem from too spatially coarse a priori surface reflectivity (0.5°) over bright urban scenes. In this work, this results during cloud-free scenes that, at times, are affected by errors in the TROPOMI cloud pressure retrieval impacting the calculation of tropospheric air mass factors. This factor causes a high bias in TROPOMI TrVCs of 4%-11%. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19%-33% during the LISTOS timeframe of June-September 2018. Part of this low bias is caused by coarse a priori profile input from the TM5-MP model; replacing these profiles with those from a 12 km North American Model-Community Multiscale Air Quality (NAMCMAQ) analysis results in a 12%-14% increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7%-19% low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets.

Dataset Information

Non-negligible impacts of clean air regulations on the reduction of tropospheric NO₂ over East China during the COVID-19 pandemic observed by OMI and TROPOMI.

Publications

Non-negligible impacts of clean air regulations on the reduction of tropospheric NO<sub>2</sub> over East China during the COVID-19 pandemic observed by OMI and TROPOMI.

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