Improving Air Quality Predictions and Assessment across Scales
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".
Deadline for manuscript submissions: closed (20 May 2023) | Viewed by 4510
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Special Issue Editors
2. National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory Affiliate, College Park, MD, 20740, USA
Interests: atmospheric composition and deposition; multimedia surface fluxes and emissions; air quality predictions; coupled model development and applications; research and consulting
Special Issues, Collections and Topics in MDPI journals
Interests: atmospheric composition and deposition; severe weather induced; dust emissions; coupled model development and application; air quality predictions
Special Issue Information
Dear Colleagues,
The presence of air pollutants, such as ground-level ozone and fine particulate matter (PM2.5), has prominent impacts on human, ecosystem, and crop health, and thus it is critical to improve air quality assessments and predictions across scales. For example, the Global Burden of Disease Study 2019 attributes approximately 4.51 million deaths each year to outdoor air pollution. In response to this concern about air pollution, there have been significant reductions in anthropogenic emissions over the last decades in many parts of the world, thus leading to relatively “cleaner” atmospheric conditions in some regions. Consequently, more emphasis has been placed on understanding the roles of natural emissions, such as nitric oxide (NO), from soil and lightning; sulfur dioxide (SO2) and carbon dioxide (CO2), from volcanic eruptions; and biogenic volatile organic compounds (BVOCs) from vegetation, windblown dust, and biomass-burning sources. Numerous world regions have experienced events leading to significantly worsened air quality conditions, including extreme wildfires or windblown dust outbreaks.
To highlight such efforts in the scientific community, we are inviting the submission of research papers that investigate improved methods, applications, and evaluations of air quality assessments and predictions across scales. These papers may use either (or both) observations or models; new modeling approaches developed to improve predictions and forecasting of air quality through improved inputs, process development, or novel inline to postprocessing methods are also highly encouraged. Papers that delve into the interplay between anthropogenic and natural source emissions and how they affect atmospheric composition and air quality are also encouraged. Finally, papers using novel measurement techniques, observations, and analysis/statistical methods to evaluate air quality model predictions across scales are welcome.
Dr. Patrick C. Campbell
Dr. Barry D. Baker
Dr. Daiwen Kang
Guest Editors
Manuscript Submission Information
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Keywords
- ozone and PM2.5 Pollution
- air quality predictions and forecasting
- anthropogenic and natural emissions
- wildfire emissions
- windblown dust emissions
- lightning nitric oxide emissions
- model development and evaluation
- observational analysis
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