Modeling and Monitoring of Air Quality: From Data to Predictions

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 442

Special Issue Editor


E-Mail Website
Guest Editor
ATMO Hauts-de-France, 199 Rue Colbert, Lille, France
Interests: air quality modelling; analysis and interpretation of data comming from air quality modelling and monitoring; statistics; evaluation of models

Special Issue Information

Dear Colleagues,

Spatial modeling of air quality relies on diverse environmental and meteorological datasets to analyze and predict pollution levels across different regions. By integrating data from meteorological stations, remote sensing technologies, and sensor networks, these models evaluate the transport, transformation, and dispersion of pollutants such as nitrogen dioxide, sulfur dioxide, ozone, and particulate matter. Computational simulations provide insights into pollutant distribution and trends, facilitating early warning systems and policy interventions. Despite advancements in predictive modeling, challenges remain, including the need for more comprehensive data integration, the inclusion of emerging pollutants, and the expansion of models into underrepresented regions. Strengthening interdisciplinary approaches and leveraging artificial intelligence can further enhance the accuracy and applicability of air quality assessments, contributing to improved urban air quality management and public health outcomes.

Dr. Agnieszka Rorat
Guest Editor

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 quality modeling
  • dispersion modeling
  • air quality index
  • advanced statistic
  • urban air pollution
  • emission inventory
  • air quality standards
  • source apportionment

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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

Research

24 pages, 3083 KiB  
Article
Modelling of Nanoparticle Number Emissions from Road Transport—An Urban Scale Emission Inventory
by Said Munir, Haibo Chen and Richard Crowther
Atmosphere 2025, 16(4), 417; https://doi.org/10.3390/atmos16040417 - 3 Apr 2025
Viewed by 331
Abstract
Atmospheric nanoparticles, due to their tiny size up to 100 nanometres in diameter, have negligible mass and are better characterised by their particle number concentration. Atmospheric nanoparticle numbers are not regulated due to insufficient data availability, which emphasises the importance of this research. [...] Read more.
Atmospheric nanoparticles, due to their tiny size up to 100 nanometres in diameter, have negligible mass and are better characterised by their particle number concentration. Atmospheric nanoparticle numbers are not regulated due to insufficient data availability, which emphasises the importance of this research. In this paper, nanoparticle number emissions are estimated using nanoparticle number emission factors (NPNEF) and road traffic characteristics. Traffic flow and fleet composition were estimated using the Leeds Transport Model, which showed that the road traffic in Leeds consisted of 41% petrol cars, 43% diesel cars, 9% LGV, 2% HGV, and 4.5% buses and coaches. Two approaches were used for emission estimation: (a) a detailed model, which required detailed information on traffic flow and fleet composition and NPNEFs of various vehicle types; and (b) a simple model, which used total traffic flow and a single NPNEF of mixed fleet. The estimations of both models demonstrated a strong correlation with each other using the values of R, RMSE, FAC2, and MB, which were 1, 2.77 × 1017, 0.95, and −1.92 × 1017, respectively. Eastern and southern parts of the city experienced higher levels of emissions. Future work will include fine-tuning the road traffic emission inventory and quantifying other emission sources. Full article
(This article belongs to the Special Issue Modeling and Monitoring of Air Quality: From Data to Predictions)
Show Figures

Figure 1

Back to TopTop