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Environments
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Air Pollution in Urban and Industrial Areas III
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Air Pollution in Urban and Industrial Areas III

A special issue of Environments (ISSN 2076-3298).

Deadline for manuscript submissions: 25 August 2025 | Viewed by 4095

Special Issue Editors

Dr. Valerio Paolini

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Guest Editor
National Research Council of Italy, Institute of Atmospheric Pollution Research (CNR-IIA), Via Salaria 29,300, 00015 Monterotondo, Italy
Interests: air pollution; renewable energy; sustainability; environmental analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Francesco Petracchini

E-Mail Website
Guest Editor
Institute of Atmospheric Pollution Research (CNR-IIA), National Research Council, Via Salaria 29,300, 00015 Monterotondo, Italy
Interests: air pollution; renewable energy; atmosphere
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As guest editor of Environments, I invite you to submit a paper to the Special Issue, "Air Pollution in Urban and Industrial Areas III". Environments publishes articles and communications in the interdisciplinary area of environmental technologies and methodologies, environmental protection, and pollution prevention. Detailed information on the journal can be found at https://www.mdpi.com/journal/environments.

Airborne particle concentration levels in cities are mostly related to anthropic urban activities/sources, such as industrial and residential sectors (heating) and vehicular traffic, i.e., sources characterized by combustion processes mainly producing high levels of particulate matter (PM), sub-micrometric, and ultrafine particles. Recent epidemiological studies have demonstrated that exposure to these concentrations can lead to respiratory and circulatory health problems. The International Agency for Research on Cancer (IARC) has classified particulate matter, a major component of air pollution, as carcinogenic to humans (Group 1).

Different measures should be taken regarding vehicle technologies, distribution optimization, and regulations. Furthermore, some policies and interventions, such as the promotion of sustainable urban mobility actions (for example, different urban transport strategies ranging from carpooling and expanded electric vehicle (EV) use to bike sharing), are needed to improve urban air quality and reduce the impact of such sources on the urban environment in terms of human exposure.

Air pollution in industrial areas is still a great health and social relevance topic. In the last few decades, conventional industrial processes (e.g., concrete, steel, plastic production, waste incineration, and thermoelectric energy generation) have undergone several changes to mitigate their environmental burden. Nevertheless, such processes are still a major source of air pollutants. On the other hand, novel industrial processes related to a circular economy (waste recycling, biomaterials production, renewable energy generation, etc.) are experiencing rapid growth. At the same time, their global impact on climate change mitigation is well known, but little information is available on their local impact on air quality.

In this framework, new research is needed to provide updated information on air pollutant emissions in urban and industrial areas. Interest can be focused on regulated or emerging pollutants, including volatile organic compounds, polyaromatic, halogenated, flame retardants, siloxanes, greenhouse gases, biologically active molecules, and nanoparticles.

This Special Issue is open to the subject area of urban and industrial air pollution. The keywords listed below outline some of the possible areas of interest.

The publications in the first volume and the second volume, which we believe may be of interest to you, can be found at the following links: https://www.mdpi.com/journal/environments/special_issues/Air_Urban; https://www.mdpi.com/journal/environments/special_issues/10R20O310O.

Dr. Valerio Paolini
Dr. Francesco Petracchini
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. Environments 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 1800 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 pollution
  • NOx
  • particulate matter
  • residential heating
  • road traffic emissions
  • sustainable mobility
  • industrial emissions
  • pollutant dispersion
  • outdoor air quality
  • global health
  • population exposure

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Published Papers (6 papers)

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Research

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13 pages, 1253 KiB  
Article
Modeling Air Pollution in Metropolitan Lima: A Statistical and Artificial Neural Network Approach
by Miguel Angel Solis Teran, Felipe Leite Coelho da Silva, Elías A. Torres Armas, Natalí Carbo-Bustinza and Javier Linkolk López-Gonzales
Environments 2025, 12(6), 196; https://doi.org/10.3390/environments12060196 - 10 Jun 2025
Abstract
Particulate matter is a mixture of fine dust and tiny droplets of liquid suspended in the air. PM10 is a pollutant composed of particles smaller than 10 µm. These particles are harmful to the respiratory system. The air quality in the region [...] Read more.
Particulate matter is a mixture of fine dust and tiny droplets of liquid suspended in the air. PM10 is a pollutant composed of particles smaller than 10 µm. These particles are harmful to the respiratory system. The air quality in the region and capital Lima in the Republic of Peru has been investigated in recent years. In this context, statistical analyses of PM10 data with forecast models can contribute to planning actions that can improve air quality. The objective of this work is to perform a statistical analysis of the available PM10 data and evaluate the quality of time series classical models and neural networks for short-term forecasting. This study demonstrates that classical time series models, particularly ARIMA and SSA, achieve lower average forecast errors than LSTM across stations SMP, CRB, and ATE. This finding suggests that for data with seasonal patterns and relatively short time series, traditional models may be more efficient and robust. Although neural networks have the potential to capture more complex relationships and long-term dependencies, their performance may be limited by hyperparameter settings and intrinsic data characteristics. Full article
(This article belongs to the Special Issue Air Pollution in Urban and Industrial Areas III)
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25 pages, 4088 KiB  
Article
Urban Source Apportionment of Potentially Toxic Elements in Thessaloniki Using Syntrichia Moss Biomonitoring and PMF Modeling
by Themistoklis Sfetsas, Sopio Ghoghoberidze, Panagiotis Karnoutsos, Vassilis Tziakas, Marios Karagiovanidis and Dimitrios Katsantonis
Environments 2025, 12(6), 188; https://doi.org/10.3390/environments12060188 - 4 Jun 2025
Viewed by 205
Abstract
Urban air pollution from potentially toxic elements (PTEs) presents a critical threat to public health and environmental sustainability. The current study employed Syntrichia moss in a passive biomonitoring capacity to ascertain the levels of atmospheric PTE pollution in Thessaloniki, Greece. A comprehensive collection [...] Read more.
Urban air pollution from potentially toxic elements (PTEs) presents a critical threat to public health and environmental sustainability. The current study employed Syntrichia moss in a passive biomonitoring capacity to ascertain the levels of atmospheric PTE pollution in Thessaloniki, Greece. A comprehensive collection of 192 moss samples was undertaken at 16 urban sampling points over the March–July 2024 period. Concentrations of 21 PTEs were quantified using ICP-MS, and contamination levels were assessed through contamination factor (CF), enrichment factor (EF), and pollution load index (PLI). Positive matrix factorization (PMF) modeling and multivariate statistical analyses were used to identify pollution sources and spatiotemporal variations. Results revealed persistent hotspots with significant anthropogenic enrichments of elements, such as Fe, Mn, Sn in industrial zones and Tl, Ce, Pt in traffic corridors. PMF modeling attributed 48% of the measured PTE variance to traffic-related sources, 35% to industrial sources, and 17% to crustal material. Seasonal transitions showed a significant 3.5-fold increase in Tl during summer, indicating elevated traffic-related emissions. This integrated multi-index and source apportionment framework demonstrates the efficacy of Syntrichia moss for high-resolution urban air quality assessment. The approach offers a cost-effective, scalable, and environmentally friendly tool to support EU-aligned air quality management strategies. Full article
(This article belongs to the Special Issue Air Pollution in Urban and Industrial Areas III)
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13 pages, 2264 KiB  
Article
Ambient Air Quality and Hospital Admissions in Gjakova: A Time Series Analysis
by Antigona Ukëhaxhaj, Rita Xhiha, Faton T. Hoxha, Hasime Terziqi and Hanns Moshammer
Environments 2025, 12(5), 162; https://doi.org/10.3390/environments12050162 - 14 May 2025
Viewed by 368
Abstract
Even at historically low levels of air pollution, epidemiological time series studies carried out in cities across the globe have documented its substantial detrimental health effects. A time series analysis of counts of respiratory hospital admissions in Gjakova and outdoor air pollutants was [...] Read more.
Even at historically low levels of air pollution, epidemiological time series studies carried out in cities across the globe have documented its substantial detrimental health effects. A time series analysis of counts of respiratory hospital admissions in Gjakova and outdoor air pollutants was performed, applying a General Additive Model with a Poisson distribution, controlling for time trends and meteorological factors over a 4-year period (2020–2023) with different time lags (0–7 days). The effects were further analyzed per age group (children and adults). We found significant associations between gaseous pollutants, mainly NO2, and respiratory disease-related hospital admissions in the city. The strongest association between NO2 and total hospital admissions was observed after a lag of 6 days, with an increase of 0.14 cases per 10 μg/m3 increase in concentration. The effects were stronger in adults. An adverse effect was also seen with SO2, but not particulate pollution. Our findings call for greater awareness regarding environmental protection and the implementation of effective measures to improve air quality, which may reduce the risk of adverse health effects. Full article
(This article belongs to the Special Issue Air Pollution in Urban and Industrial Areas III)
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25 pages, 4478 KiB  
Article
Advancing Human Health Risk Assessment Through a Stochastic Methodology for Mobile Source Air Toxics
by Mohammad Munshed, Jesse Van Griensven Thé and Roydon Fraser
Environments 2025, 12(2), 54; https://doi.org/10.3390/environments12020054 - 6 Feb 2025
Cited by 1 | Viewed by 1022
Abstract
Mobile source air toxics (MSATs) are major contributors to urban air pollution, especially near high-traffic roadways, where populations face elevated pollutant exposures. Traditional human health risk assessments, based on deterministic methods, often overlook variability in exposure and the vulnerabilities of sensitive subpopulations. This [...] Read more.
Mobile source air toxics (MSATs) are major contributors to urban air pollution, especially near high-traffic roadways, where populations face elevated pollutant exposures. Traditional human health risk assessments, based on deterministic methods, often overlook variability in exposure and the vulnerabilities of sensitive subpopulations. This study introduces and applies a new stochastic modeling approach, utilizing Monte Carlo simulations to evaluate cumulative cancer risks from MSATs exposure through inhalation and ingestion pathways. This method captures variability in exposure scenarios, providing detailed health risk assessments, particularly for vulnerable groups such as children and the elderly. This approach was demonstrated in a case study conducted in Saint Paul, Minnesota, using 2019 traffic data. Deterministic models estimated cumulative cancer risks for adults at 6.24E-02 (unitless lifetime cancer risk), while stochastic modeling revealed a broader range, with the 95th percentile reaching 4.98E-02. The 95th percentile, used in regulatory evaluations, identifies high-risk scenarios overlooked by deterministic methods. This research advances the understanding of MSATs exposure risks by integrating spatiotemporal dynamics, identifying high-risk zones and vulnerable subpopulations, and supporting resource allocation for targeted pollution control measures. Future applications of this methodology include expanding stochastic modeling to evaluate ecological risks from mobile emissions. Full article
(This article belongs to the Special Issue Air Pollution in Urban and Industrial Areas III)
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Review

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31 pages, 1087 KiB  
Review
Global Trends in Air Pollution Modeling over Cities Under the Influence of Climate Variability: A Review
by William Camilo Enciso-Díaz, Carlos Alfonso Zafra-Mejía and Yolanda Teresa Hernández-Peña
Environments 2025, 12(6), 177; https://doi.org/10.3390/environments12060177 - 28 May 2025
Viewed by 480
Abstract
The objective of this article is to conduct a review to analyze global trends in the use of air pollution models under the influence of climate variability (CV) over urban areas. Five scientific databases were used (2013–2024): Scopus, ScienceDirect, SpringerLink, Web of Science, [...] Read more.
The objective of this article is to conduct a review to analyze global trends in the use of air pollution models under the influence of climate variability (CV) over urban areas. Five scientific databases were used (2013–2024): Scopus, ScienceDirect, SpringerLink, Web of Science, and Google Scholar. The frequency of citations of the variables of interest in the selected scientific databases was analyzed by means of an index using quartiles (Q). The results showed a hierarchy in the use of models: regional climate models/RCMs (Q3) > statistical models/SMs (Q3) > chemical transport models/CTMs (Q4) > machine learning models/MLMs (Q4) > atmospheric dispersion models/ADMs (Q4). RCMs, such as WRF, were essential for generating high-resolution projections of air pollution, crucial for local impact assessments. SMs, such as GAM, excelled in modeling nonlinear relationships between air pollutants and climate variables. CTMs, such as WRF-Chem, simulated detailed atmospheric chemical processes vital for understanding pollutant formation and transport. MLMs, such as ANNs, improved the accuracy of predictions and uncovered complex patterns. ADMs, such as HYSPLIT, evaluated air pollutant dispersion, informing regulatory strategies. The most studied pollutants globally were O3 (Q3) > PM (Q3) > VOCs (Q4) > NOx (Q4) > SO2 (Q4), with models adapting to their specific characteristics. Temperature emerged as the dominant climate variable, followed by wind, precipitation, humidity, and solar radiation. There was a clear differentiation in the selection of models and variables between high- and low-income countries. CTMs predominated in high-income countries, driven by their ability to simulate complex physicochemical processes, while SMs were preferred in low-income countries, due to their simplicity and lower resource requirements. Temperature was the main climate variable, and precipitation stood out in low-income countries for its impact on PM removal. VOCs were the most studied pollutant in high-income countries, and NOx in low-income countries, reflecting priorities and technical capabilities. The coupling between regional atmospheric models and city-scale air quality models was vital; future efforts should emphasize intra-urban models for finer urban pollution resolution. This study highlights how national resources and priorities influence air pollution research over cities under the influence of CV. Full article
(This article belongs to the Special Issue Air Pollution in Urban and Industrial Areas III)
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46 pages, 1183 KiB  
Review
Chemicals in European Residences—Part II: A Review of Emissions, Concentrations, and Health Effects of Semi-Volatile Organic Compounds (SVOCs)
by Charlotte Landeg-Cox, Alice Middleton, Christos Halios, Tim Marczylo and Sani Dimitroulopoulou
Environments 2025, 12(2), 40; https://doi.org/10.3390/environments12020040 - 30 Jan 2025
Viewed by 1183
Abstract
This comprehensive review reports on concentrations, sources, emissions, and potential health effects from Semi-Volatile Organic Compounds (SVOCs) identified in the internal home environment in European residences. A total of 84 studies were identified, and concentrations were collated for inhalation exposure from dust, air [...] Read more.
This comprehensive review reports on concentrations, sources, emissions, and potential health effects from Semi-Volatile Organic Compounds (SVOCs) identified in the internal home environment in European residences. A total of 84 studies were identified, and concentrations were collated for inhalation exposure from dust, air and aerosol. A total of 298 individual SVOCs were identified and 67 compounds belonging to eight chemical classes: phthalates, flame retardants, polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), per- and polyfluorinated alkyl substances (PFAS), biocides, bisphenols and musks were prioritised. Phthalates are the most abundant SVOCs with DEHP being the most abundant in both the dust and aerosol phases (WAGMs 426.4 μg g−1 and 52.2 ng m−3, respectively) followed by DBP for dust (WAGMs are 95.9 μg g−1). In the air, the most abundant SVOCs are DiBP (284.1 ng m−3), DBP (179.5 ng m−3), DEHP (106.2 ng m−3) and DMP (27.79 ng m−3). Chemicals from all SVOC categories are emitted from building and construction materials, furnishings and consumer products, especially phthalates. Both legacy chemicals and their alternatives were detected. Complexities of reporting on SVOCs included differing sampling methodologies, multiple standards in their definition, lack of industry data, and toxicological data focused primarily on ingestion not inhalation exposures. Further research is recommended to develop the evidence base for potential health effects including via inhalation, reporting of emission rates and undertaking future monitoring studies. Full article
(This article belongs to the Special Issue Air Pollution in Urban and Industrial Areas III)
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