Special Issue "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: 2 December 2022 | Viewed by 624

Special Issue Editors

Dr. Patrick C. Campbell
E-Mail Website1 Website2
Guest Editor
1. Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, 22030, USA
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
Dr. Barry D. Baker
E-Mail Website
Guest Editor
National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory, College Park, MD, 20740, USA
Interests: atmospheric composition and deposition; severe weather induced; dust emissions; coupled model development and application; air quality predictions
Dr. Daiwen Kang
E-Mail Website
Guest Editor
United States Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
Interests: atmospheric composition and process modeling; air quality predictions; model evaluation and applications; natural and biogenic emissions; data assimilation

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

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • 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

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:


Particulate Matter and Ammonia Pollution in the Animal Agricultural-Producing Regions of North Carolina: Integrated Ground-Based Measurements and Satellite Analysis
Atmosphere 2022, 13(5), 821; https://doi.org/10.3390/atmos13050821 - 17 May 2022
Viewed by 384
Intensive animal agriculture is an important part of the US and North Carolina’s (NC’s) economy. Large emissions of ammonia (NH3) gas emanate from the handling of animal wastes at these operations contributing to the formation of fine particulate matter (PM2.5 [...] Read more.
Intensive animal agriculture is an important part of the US and North Carolina’s (NC’s) economy. Large emissions of ammonia (NH3) gas emanate from the handling of animal wastes at these operations contributing to the formation of fine particulate matter (PM2.5) around the state causing a variety of human health and environmental effects. The objective of this research is to provide the relationship between ammonia, aerosol optical depth and meteorology and its effect on PM2.5 concentrations using satellite observations (column ammonia and aerosol optical depth (AOD)) and ground-based meteorological observations. An observational-based multiple linear regression model was derived to predict ground-level PM2.5 during the summer months (JJA) from 2008–2017 in New Hanover County, Catawba County and Sampson County. A combination of the Cumberland and Johnston County models for the summer was chosen and validated for Duplin County, NC, then used to predict Sampson County, NC, PM2.5 concentrations. The model predicted a total of six 24 h exceedances over the nine-year period. This indicates that there are rural areas of the state that may have air quality issues that are not captured for a lack of measurements. Moreover, PM2.5 chemical composition analysis suggests that ammonium is a major component of the PM2.5 aerosol. Full article
(This article belongs to the Special Issue Improving Air Quality Predictions and Assessment across Scales)
Show Figures

Figure 1

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Tentative title: Application of Lightning Flash Data from WWLLN for Lightning NOx Production in the WRF-CMAQ Modeling System
Author: Daiwen Kang

Tentative title: Updating  Anthropogenic Emissions in NOAA’s Global Ensemble Forecast System with Aerosols (GEFS-Aerosols): Application of a Bias Scaling Method
Author: Gill-Ran Jeong

Back to TopTop