Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.7
3.7
Journals
Environments
Special Issues
Air Quality Assessment: Environmental Impacts, Risks and Human Health Hazards
share announcement

Air Quality Assessment: Environmental Impacts, Risks and Human Health Hazards

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

Deadline for manuscript submissions: 30 October 2026 | Viewed by 4458

Special Issue Editors

Dr. Brindusa Sluser

E-Mail Website
Guest Editor
Department of Environmental Engineering and Management, “Gheorghe Asachi” Technical University of Iasi, 73 Blvd. D. Mangeron, 700050 Iasi, Romania
Interests: environmental health and safety; impact and risk assessment; environmental quality monitoring and sustainable management
Special Issues, Collections and Topics in MDPI journals
Dr. Marius M. Cazacu

E-Mail Website
Guest Editor
Department of Physics, Gheorghe Asachi Technical University of Iași, 700050 Iași, Romania
Interests: remote sensing techniques for environmental monitoring; long-range transport of aerosols; pollution; environmental engineering; atmospheric pollution; analytical microscopy; nanoscale imaging and spectroscopy; optical atmosphere; spectroscopy and lasers; physics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Air quality remains a top priority, as monitoring, characterisation, and assessment are challenging to perform accurately with little to no uncertainty. Modern methods employ AI tools for modelling, simulation, and impact and risk evaluation. New air quality assessment instruments are usually integrated with monitoring devices, enabling predictions of impacts and health risks. Meanwhile, traditional monitoring networks and modelling techniques have significantly advanced. Recently, there has been a notable boost in remote sensing capabilities (both passive and active) and data integration frameworks, which provide new opportunities for exposure assessment, risk quantification, and decision-making support.

The topics covered by this Special Issue address the assessment of air quality, environmental impacts, human health hazards, and related risks, emphasising the integration of remote sensing (passive and active) with traditional monitoring and modelling. This Special Issue addresses a variety of contributions from literature reviews and case studies to methodological developments and advanced data applications, covering, but not limited to, the following areas:

  • Passive remote sensing of atmospheric pollutants and aerosols (satellite AOD/AI/VI, ground-based photometer networks, sun–sky radiometry) and their relation to exposure and risk modelling.
  • Active remote sensing techniques (lidar, ceilometers, aerosol backscatter profiling, Raman lidar) for vertical distribution, mixing layer dynamics, and exposure assessment.
  • Decision support, mitigation strategies, and policy implications: how remote sensing and integrated monitoring can inform air-quality management, early warning systems, and planning.
  • Integrated methodologies for combining remote sensing data and ground measurements in the analysis of ecological and public health risks.
  • Human health hazard and risk assessment related to air quality, with novel exposure estimation methods (including remote sensing inputs, personal exposure modelling, epidemiology).

Thus, we invite contributions that explore the assessment of air quality, with a strong focus on environmental impacts, risks, and human health hazards, and on the integration of remote sensing technologies (passive and active). The aim is to bring together interdisciplinary research that spans from instrument/technique development, through exposure and impact assessment, to policy and mitigation strategies.

Dr. Brindusa Sluser
Dr. Marius M. Cazacu
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 250 words) can be sent to the Editorial Office for assessment.

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 monitoring
  • data fusion and integration
  • atmospheric aerosols
  • air quality assessment
  • pollutants exposure assessment
  • environmental risk assessment
  • human health hazards
  • risk modelling
  • environmental impact analysis

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.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 2266 KB  
Article
Towards Real-Time, High-Spatial-Resolution Air Pollution Exposure Estimation in Microenvironments Supported by Physics-Informed Machine Learning Approaches
by John G. Bartzis, Ioannis A. Sakellaris, Spyros Andronopoulos, Alexandros Venetsanos, Fernando Martín-Llorente and Stijn Janssen
Environments 2026, 13(5), 256; https://doi.org/10.3390/environments13050256 (registering DOI) - 2 May 2026
Abstract
Reliable and timely estimation of air pollution exposure at high spatial and temporal resolution remains challenging in complex urban environments, where pollutant concentrations vary due to traffic emissions, urban morphology, and meteorological conditions. This study presents a physics-informed machine learning framework for near-real-time [...] Read more.
Reliable and timely estimation of air pollution exposure at high spatial and temporal resolution remains challenging in complex urban environments, where pollutant concentrations vary due to traffic emissions, urban morphology, and meteorological conditions. This study presents a physics-informed machine learning framework for near-real-time estimation of NO2 concentrations at fine spatial scales. The approach combines a limited set of steady-state computational fluid dynamics (CFD) simulations with operational meteorological and air-quality data. CFD simulations under specific wind directions are first used to characterize site-specific dispersion patterns. These outputs are then scaled using hourly meteorological observations to generate physics-based concentration descriptors. A machine learning predictor, implemented using Random Forest and Extreme Gradient Boosting, is trained to refine these estimates by incorporating additional environmental and observational features. The method is applied to a 1 km × 1 km urban district in Antwerp, Belgium, within the FAIRMODE intercomparison framework. Validation against measurements from 105 passive samples collected over one month shows substantial improvement compared to standalone dispersion modeling, with coefficients of determination up to R2 = 0.965 and reduced bias across locations. These findings demonstrate that integrating physical modeling with machine learning enables accurate and computationally efficient high-resolution exposure assessment in urban settings. Full article
(This article belongs to the Special Issue Air Quality Assessment: Environmental Impacts, Risks and Human Health Hazards)
►▼ Show Figures

Figure 1

36 pages, 9939 KB  
Article
A National Emission Inventory of Major Air Pollutants and Greenhouse Gases in Thailand
by Agapol Junpen, Savitri Garivait, Pham Thi Bich Thao, Penwadee Cheewaphongphan, Orachorn Kamnoet, Athipthep Boonman and Jirataya Roemmontri
Environments 2026, 13(5), 244; https://doi.org/10.3390/environments13050244 - 23 Apr 2026
Viewed by 1035
Abstract
Accurate, high-resolution emission inventories are essential for air quality modeling and policy evaluation, yet national-scale inventories for Thailand remain limited in spatial and temporal detail. This study develops a comprehensive national emission inventory for Thailand in 2019 (EI–TH 2019), covering 12 major air [...] Read more.
Accurate, high-resolution emission inventories are essential for air quality modeling and policy evaluation, yet national-scale inventories for Thailand remain limited in spatial and temporal detail. This study develops a comprehensive national emission inventory for Thailand in 2019 (EI–TH 2019), covering 12 major air pollutants and greenhouse gases across key sectors, including energy, transport, industry, agriculture, waste, and residential activities. The inventory is constructed using country-specific activity data from official statistics and sectoral surveys, combined with GAINS-consistent emission factors and control assumptions. Emissions are resolved at 1 × 1 km spatial resolution and monthly temporal resolution to capture Thailand-specific emission dynamics. The results show that emissions across major pollutants are dominated by a limited number of source groups, with biomass burning and residential solid-fuel use driving particulate matter, transport dominating NOx and CO emissions, large-scale combustion and industry controlling SO2 emissions, and agriculture contributing the majority of NH3 emissions. Strong seasonal variability is observed in PM2.5, CO, and NH3, primarily driven by dry-season biomass burning, whereas NOx and SO2 exhibit relatively stable temporal patterns. The reliability of EI–TH 2019 is supported by a multi-dimensional evaluation framework. Temporal consistency is demonstrated through strong agreement between modeled PM2.5 emissions and ground-based observations, as well as between NOx emissions and satellite-derived TROPOMI NO2 (r = 0.93; ρ = 0.96). Biomass burning timing is further validated using satellite fire activity (VIIRS), showing consistent seasonal patterns. Comparisons with global inventories (EDGAR v8.1, HTAP v3.2, and GFED5.1) reveal systematic differences in sectoral contributions, temporal profiles, and emission magnitudes, particularly for biomass burning, reflecting the importance of country-specific data and assumptions. Overall, EI–TH 2019 provides a robust, high-resolution, and policy-relevant emission dataset that improves the representation of emission processes in Thailand. The results highlight key priority sectors—biomass burning, transport, industry, and agriculture—for targeted emission-reduction strategies and support applications in chemical transport modeling, exposure assessment, and integrated air-quality and climate-policy analysis. Full article
(This article belongs to the Special Issue Air Quality Assessment: Environmental Impacts, Risks and Human Health Hazards)
14 pages, 516 KB  
Article
Different Approaches, Same Indication: Using Plants as a Potentially Valuable Alternative to Assess the Genotoxicity of Urban Fine Particulate Matter
by Carlotta Alias, Claudia Zani, Ilaria Zerbini and Donatella Feretti
Environments 2026, 13(3), 170; https://doi.org/10.3390/environments13030170 - 19 Mar 2026
Viewed by 779
Abstract
The objective of this study was to use plant models, Allium cepa and Lepidium sativum, to assess the genotoxic effects of the urban particulate matter (PM) collected in a Northern Italian town. Aqueous extracts of different particle sizes (PM10–3, PM [...] Read more.
The objective of this study was to use plant models, Allium cepa and Lepidium sativum, to assess the genotoxic effects of the urban particulate matter (PM) collected in a Northern Italian town. Aqueous extracts of different particle sizes (PM10–3, PM3–0.5, PM0.5) were tested alongside the organic extracts through the standard Ames test. The organic particulate matter extracts were subjected to mutagenicity testing in the Salmonella typhimurium strains TA98 and TA100 (without and with metabolic activation), whereas the aqueous extracts were evaluated for genotoxicity in the emerging seedlings of L. sativum and in the root tips of A. cepa bulbs using the comet test to detect the primary DNA damage. Furthermore, the micronuclei frequency was assessed in the bulbs of A. cepa. As expected, the organic extracts of PM3–0.5 and PM0.5 induced point mutations in bacteria. The aqueous extracts of the finest fractions caused a significant increase in genotoxic damage in both plant models. These findings indicate that the two plant models (L. sativum seeds and A. cepa bulbs) are able to detect the genotoxicity of aqueous extracts of air pollutants, with many potential advantages as screening-level tools to complement Ames testing for an easier assessment of urban air quality in terms of DNA toxicity. Full article
(This article belongs to the Special Issue Air Quality Assessment: Environmental Impacts, Risks and Human Health Hazards)
►▼ Show Figures

Figure 1

19 pages, 1136 KB  
Article
Evaluation of the Role of Benzo(a)pyrene as Carcinogenic Index of PM10-Bound PAHs in Italian Urban Sites
by Catia Balducci, Serena Santoro, Mariantonia Bencardino, Francesco D’Amore, Marina Cerasa, Gianni Formenton and Cristina Leonardi
Environments 2026, 13(2), 75; https://doi.org/10.3390/environments13020075 - 1 Feb 2026
Viewed by 881
Abstract
The European Air Quality Directive defines benzo(a)pyrene as the chemical index for polycyclic aromatic hydrocarbon (PAH) carcinogenicity and sets a limit for its concentration in PM10 to address the exposure risk associated with the class. It also mandates monitoring six additional PAHs [...] Read more.
The European Air Quality Directive defines benzo(a)pyrene as the chemical index for polycyclic aromatic hydrocarbon (PAH) carcinogenicity and sets a limit for its concentration in PM10 to address the exposure risk associated with the class. It also mandates monitoring six additional PAHs at a limited number of selected sites to assess the benzo(a)pyrene’s contribution to the class in ambient air. For this aim, as part of the “Reti Speciali” project, benzo(a)pyrene and seven other PAHs were measured at 10 urban sites across Italy in 2016–2019, and the spatial and temporal pattern of these compounds were analyzed to evaluate benzo(a)pyrene’s effectiveness in representing the carcinogenicity of the entire PAH class. Results showed that in Italy, benzo(a)pyrene accounted for 61% ± 4.4% of total carcinogenicity when benzo(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, dibenzo(a-h)anthracene, and indenopyrene were considered, and about 1% less when chrysene and benzo(ghi)perylene were also added. This value varies by site (from 51% ± 11% in Taranto to 66% ± 7.5% in Cosenza) and decreases in summer due to benzo(a)pyrene’s strong photochemical degradation. In Europe, this percentage is generally similar or lower. For instance, in the United Kingdom, across 24 urban sites, it averages 56% ± 2.9%. These findings suggest that benzo(a)pyrene does not represent the overall carcinogenicity of PAHs nor a constant percentage, highlighting the need to further investigate the use of benzo(a)pyrene as the sole marker of PAH toxicity. Full article
(This article belongs to the Special Issue Air Quality Assessment: Environmental Impacts, Risks and Human Health Hazards)
►▼ Show Figures

Graphical abstract

49 pages, 6470 KB  
Article
National Inventory of Ammonia Emissions from Anthropogenic Sources in Thailand
by Agapol Junpen, Jirataya Roemmontri and Savitri Garivait
Environments 2026, 13(2), 72; https://doi.org/10.3390/environments13020072 - 27 Jan 2026
Viewed by 975
Abstract
Ammonia (NH3) is a key precursor to secondary particulate matter in Southeast Asia, yet Thailand has lacked a country-specific, policy-focused emission inventory. This study creates the first spatially gridded (12 × 12 km) and monthly resolved national NH3 inventory for [...] Read more.
Ammonia (NH3) is a key precursor to secondary particulate matter in Southeast Asia, yet Thailand has lacked a country-specific, policy-focused emission inventory. This study creates the first spatially gridded (12 × 12 km) and monthly resolved national NH3 inventory for 2019, using detailed agricultural activity data, survey-based livestock management practices, and crop-specific fertilizer application profiles. Satellite-derived burned-area data were included to constrain emissions from open burning. National NH3 emissions are estimated at 459.1 kt per year, with an overall uncertainty of ±15.3%. Agriculture accounts for 95.8% of total emissions. Livestock and manure management contribute 225.3 kt per year (49.1%), reflecting high densities of poultry, cattle, and pigs, as well as regional differences in manure handling and storage practices that enhance ammonia volatilization. Fertilizer-related emissions total 192.4 kt per year (41.9%), with seasonal peaks during primary planting cycles, in contrast to the more episodic biomass-burning emissions. Comparison with the global EDGARv8.1 inventory shows significant sectoral and temporal differences, including considerably higher livestock emissions and lower fertilizer emissions in this study, due to Thailand-specific emission factors and temporal emission allocation methods. These findings clarify the spatial and temporal drivers of NH3 emissions in Thailand and offer actionable insights for targeted mitigation—notably improved manure management and optimized nitrogen use in regions where dry-season emissions coincide with severe PM2.5 episodes. The THAI-NH3 Inventory provides a strong foundation for chemical-transport modeling and evidence-based policymaking to reduce ammonia-related haze in Thailand. Full article
(This article belongs to the Special Issue Air Quality Assessment: Environmental Impacts, Risks and Human Health Hazards)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop