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Atmosphere
Special Issues
Air Pollution in Chemical Industries
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Air Pollution in Chemical Industries

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

Deadline for manuscript submissions: 10 October 2024 | Viewed by 3393

Special Issue Editors

Prof. Dr. Jesse Van Griensven Thé

E-Mail Website
Guest Editor
Department of Mechanical & Mechatronics Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
Interests: numerical weather prediction; atmospheric physics; regional climate modeling; meteorology; air quality; climate dynamics; numerical modeling; atmospheric pollution; air pollution studies
Prof. Dr. Bahram Gharabaghi

E-Mail Website
Guest Editor
School of Engineering, University of Guelph, Guelph, ON NIG 2W1, Canada
Interests: hydrology; sediment transport; water quality
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to present recent developments in air pollution from chemical plants.  Innovations should be related to the methodology used to estimate emissions, the fate and transport of these hazardous air pollutants, and multi-pathway human and ecological risk assessments.  The decarbonization of the economy has caused a massive reduction in emissions from power plants. Therefore, chemical industrial operations remain a major source of human health and ecological deterioration from air pollution.

Currently, there are several limitations to estimating impacts.  These are characterized by the collection of atmospheric pollutant concentrations on a very limited number of contaminants and at point locations without knowledge of the substances’ origins.  This is the case, for example, for chemical plants emitting over 1200 chemicals of concern. Ambient air monitoring stations measure at most 30 of these contaminants. Furthermore, studies include only the direct inhalation pathway, while ignoring the accumulation of air toxics in the food web.  Public and ecological receptors only have restricted ambient air quality standards, which are established by environmental regulatory agencies.  The only acceptable approach to assess the impacts are by the use of mathematical models for the exposure estimations, along with data on the transport and end-point toxicity.  Final health and ecological impacts must be assessed with terms of risks.

The focus of this Special Issue is, therefore, to collate original research on novel models to monitor and estimate emissions, evaluate fate and transport in multimedia to receptors (humans and ecological), and assess of toxic risks coming from chemical industries.

Prof. Dr. Jesse Van Griensven Thé
Prof. Dr. Bahram Gharabaghi
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 2400 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.

Keywords

  • air toxics emissions
  • air toxic monitoring
  • fate and transport of air toxics
  • volatile compounds emissions estimations
  • innovative technologies to estimate air toxic emissions
  • innovative methodologies to conduct multi-pathway risk assessment

Published Papers (1 paper)

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Research

23 pages, 6760 KiB  
Article
Spatiotemporal Air Pollution Forecasting in Houston-TX: A Case Study for Ozone Using Deep Graph Neural Networks
by Victor Oliveira Santos, Paulo Alexandre Costa Rocha, John Scott, Jesse Van Griensven Thé and Bahram Gharabaghi
Atmosphere 2023, 14(2), 308; https://doi.org/10.3390/atmos14020308 - 03 Feb 2023
Cited by 10 | Viewed by 2618
Abstract
The presence of pollutants in our atmosphere has become one of humanity’s greatest challenges. These pollutants, produced primarily by burning fossil fuels, are detrimental to human health, our climate and agriculture. This work proposes the use of a spatiotemporal graph neural network, designed [...] Read more.
The presence of pollutants in our atmosphere has become one of humanity’s greatest challenges. These pollutants, produced primarily by burning fossil fuels, are detrimental to human health, our climate and agriculture. This work proposes the use of a spatiotemporal graph neural network, designed to forecast ozone concentration based on the GraphSAGE paradigm, to aid in our understanding of the dynamic nature of these pollutants’ production and proliferation in urban areas. This model was trained and tested using data from Houston, Texas, the United States, with varying numbers of time-lags, forecast horizons (1, 3, 6 h ahead), input data and nearby stations. The results show that the proposed GNN-SAGE model successfully recognized spatiotemporal patterns underlying these data, bolstering its forecasting performance when compared with a benchmarking persistence model by 33.7%, 48.7% and 57.1% for 1, 3 and 6 h forecast horizons, respectively. The proposed model produces error levels lower than we could find in the existing literature. The conclusions drawn from variable importance SHAP analysis also revealed that when predicting ozone, solar radiation becomes relevant as the forecast time horizon is raised. According to EPA regulation, the model also determined nonattainment conditions for the reference station. Full article
(This article belongs to the Special Issue Air Pollution in Chemical Industries)
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