Satellite-Based Air Quality Monitoring

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".

Deadline for manuscript submissions: closed (25 November 2022) | Viewed by 3040

Special Issue Editors


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Guest Editor
Department of Environmental & Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA 98195, USA
Interests: air pollution modeling; air pollution health effects; machine learning; remote sensing; GIS

E-Mail Website
Guest Editor
Department of Environmental Health, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
Interests: air pollution modeling; environmental epidemiology; machine learning; remote sensing; GIS

Special Issue Information

Dear Colleagues,

Satellite remote sensing has revolutionized our observation systems of atmospheric composition over the past decades, providing an enormous amount of spatiotemporally continuous data for the entire planet. Earth science data and tools produced by research agencies around the world have great potential for offering unique information on air quality. Although there is a wide range of air pollutants that can be observed from space, including particulate matter, ozone, carbon monoxide, nitrogen dioxide, formaldehyde, ammonia, and methane, satellite-based air pollution monitoring is still in its infancy. As the abilities of satellite instruments and relevant algorithms/models improve with time, we will likely see a growth in new applications that will significantly advance our understanding of air quality at both urban and global scales.  This Special Issue focuses on (but is not limited to) using satellite remote sensing data to characterize emissions, concentration trends, human exposures, the attribution of exceptional events, long-range transport, as well as links to climate change with respect to air pollution. Particular attention is devoted to analyses of the interplay between air pollution and climate change (e.g., wildland fires, severe dust storm events, etc.), as well as applications of satellite-based air quality monitoring in low- or middle-income countries (LMICs) with limited ground-level, research-grade air monitors. The proposed studies will provide crucial insights into novel remote sensing techniques, approaches, and applications, showcasing satellite data as a promising supplement to ground-level air monitoring data to benefit air quality management and air pollution control.

Dr. Jianzhao Bi
Dr. Bryan N. Vu
Guest Editors

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Keywords

  • satellite retrievals
  • satellite instruments
  • atmospheric remote sensing
  • air quality monitoring
  • atmospheric composition
  • air quality management
  • air pollution control
  • climate change.

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Published Papers (1 paper)

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Research

19 pages, 4992 KiB  
Article
Anthropogenic NOx Emission Estimations over East China for 2015 and 2019 Using OMI Satellite Observations and the New Inverse Modeling System CIF-CHIMERE
by Dilek Savas, Gaëlle Dufour, Adriana Coman, Guillaume Siour, Audrey Fortems-Cheiney, Grégoire Broquet, Isabelle Pison, Antoine Berchet and Bertrand Bessagnet
Atmosphere 2023, 14(1), 154; https://doi.org/10.3390/atmos14010154 - 10 Jan 2023
Cited by 2 | Viewed by 2261
Abstract
The Chinese government introduced regulations to control emissions and reduce the level of NOx pollutants for the first time with the 12th Five-Year Plan in 2011. Since then, the changes in NOx emissions have been assessed using various approaches to evaluate [...] Read more.
The Chinese government introduced regulations to control emissions and reduce the level of NOx pollutants for the first time with the 12th Five-Year Plan in 2011. Since then, the changes in NOx emissions have been assessed using various approaches to evaluate the impact of the regulations. Complementary to the previous studies, this study estimates anthropogenic NOx emissions in 2015 and 2019 over Eastern China using as a reference the Hemispheric Transport of Air Pollution (HTAP) v2.2 emission inventory for 2010 and the new variational inversion system the Community Inversion Framework (CIF) interfaced with the CHIMERE regional chemistry transport model and OMI satellite observations. We also compared the estimated NOx emissions with the independent Multi-resolution Emission Inventory for China (MEIC) v1.3, from 2015. The inversions show a slight global decrease in NOx emissions (in 2015 and 2019 compared to 2010), mainly limited to the most urbanized and industrialized locations. In the locations such as Baotou, Pearl River Delta, and Wuhan, the estimations in 2015 compared to 2010 are consistent with the target reduction (10%) of the 12th Five-Year Plan. Comparisons between our emission estimates and MEIC emissions in 2015 suggest that our estimates likely underestimate the emission reductions between 2010 and 2015 in the most polluted locations of Eastern China. However, our estimates suggest that the MEIC inventory overestimates emissions in regions where MEIC indicates an increase of the emissions compared to 2010. Full article
(This article belongs to the Special Issue Satellite-Based Air Quality Monitoring)
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