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Environments
Special Issues
Ambient Air Pollution, Built Environment, and Public Health
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Ambient Air Pollution, Built Environment, and Public Health

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

Deadline for manuscript submissions: 15 January 2026 | Viewed by 3036

Special Issue Editors

Dr. Pei Yu

E-Mail Website
Guest Editor
Climate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
Interests: ambient air pollution; cancer epidemiology; public health
Dr. Weiju Zhou

E-Mail Website
Guest Editor
Vanke School of Public Health, Tsinghua University, Beijing 100084, China
Interests: building environment; green space; public health

Special Issue Information

Dear Colleagues,

We are organizing a Special Issue on ambient air pollution, built environment, and public health. Extensive research has demonstrated that exposure to outdoor air pollution—both short- and long-term—poses significant health risks. However, key uncertainties persist, particularly regarding exposure–response relationships for specific diseases, the vulnerability of certain populations, and regional disparities. The increasing prevalence of natural disasters, such as wildfires, has further altered air pollution composition and exposure dynamics, adding complexity to this Special Issue. In addition to concerns over air quality, increasing attention has been given to the built environment’s role in public health, with factors such as building height, population density, and access to green spaces influencing well-being. These issues are not only scientific but also social, guiding policies that shape urban living environments.

This Special Issue will address key topics, including the following:

  • Health impact of outdoor air pollution;
  • Effects of combined environmental exposures on health;
  • Impact of the built environment on health outcomes;
  • Interaction between air pollution and the built environment;
  • Novel methodologies for environmental health assessment;
  • Other related research topics.

Dr. Pei Yu
Dr. Weiju Zhou
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

  • ambient air pollution
  • built envrionment
  • green space
  • natural disaster
  • public health
  • environmental epidemiology
  • vulnerable population

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

Published Papers (4 papers)

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Research

23 pages, 5315 KB  
Article
Results of a Comprehensive Study on Atmospheric Pollution at the Tankhoi Observation Point (Southeastern Coast of Lake Baikal, Russia): Temporal Variability and Identification of Sources
by Yelena Molozhnikova, Maxim Shikhovtsev and Tamara Khodzher
Environments 2025, 12(12), 462; https://doi.org/10.3390/environments12120462 - 1 Dec 2025
Viewed by 231
Abstract
This study is based on data obtained as part of continuous monitoring of small gas impurities (SO2, NO2, NO), mass concentration of aerosol particles PM2.5 and meteorological parameters, which was first implemented at the Tankhoi observation point (southeastern [...] Read more.
This study is based on data obtained as part of continuous monitoring of small gas impurities (SO2, NO2, NO), mass concentration of aerosol particles PM2.5 and meteorological parameters, which was first implemented at the Tankhoi observation point (southeastern coast of Lake Baikal, Russia) from October 2023 to May 2025. Statistical methods and the non-parametric wind regression receptor model (NWR) were used to analyze temporal variability and identify sources of pollution. It was found that the concentrations of gas impurities have a clearly pronounced winter maximum: the median values for sulfur dioxide and nitrogen in winter reached 9.2 μg/m3 and 13.8 μg/m3, respectively, which is associated with emissions from coal-fired thermal power plants and unfavorable meteorological conditions (inversions, low boundary layer height). In contrast to gases, PM2.5 demonstrated a summer peak up to 43.5 μg/m3 in July–August 2024 due to abnormally hot weather and forest fires. The daily course of sulfur dioxide was characterized by an atypical daily maximum caused by the convective transport of polluted air masses from the upper layers of the boundary layer. During this period, higher concentrations of sulfur dioxide caused by long-range high-altitude transport of emissions from regional thermal power plants can reach the ground surface, leading to an increase in their concentration in the near-surface layer. Using the NWR model, the influence of regional thermal power plants located 100–150 km northwest of the station on the levels of SO2 and NO2 was confirmed. The results also highlight the contribution of local sources, such as vehicles, stoves, and shipping, to the formation of NO and PM2.5. Full article
(This article belongs to the Special Issue Ambient Air Pollution, Built Environment, and Public Health)
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11 pages, 675 KB  
Article
Predicting Minute Ventilation from Heart Rate in Adolescents: A Tool for Environmental Health Studies
by Celia Cacho, Meghana Giri, Kyung Hwa Jung, Ruskin Del Mundo, Aimee Layton and Stephanie Lovinsky-Desir
Environments 2025, 12(12), 448; https://doi.org/10.3390/environments12120448 - 21 Nov 2025
Viewed by 611
Abstract
Minute ventilation (VE) is central to understanding the interplay between air pollution and exercise. However, real-time measurement of VE in environmental health research is often limited by access to equipment and technical expertise. We aimed to (1) develop predictive equations for VE based [...] Read more.
Minute ventilation (VE) is central to understanding the interplay between air pollution and exercise. However, real-time measurement of VE in environmental health research is often limited by access to equipment and technical expertise. We aimed to (1) develop predictive equations for VE based on heart rate (HR) in adolescents using metabolic exercise testing data, (2) evaluate which demographic factors influenced model accuracy, and (3) compare our equations to previously published equations applied to our sample. We analyzed cardiopulmonary exercise test (CPET) data from 41 patients. VE was log-transformed, and generalized estimating equations (GEE) were used to model associations between HR and VE, adjusting for age, sex, race, ethnicity, and BMI. In the fully adjusted model, HR was a strong predictor of VE (p-value < 0.001); only sex was a significant covariate (p = 0.003). Stratification revealed a higher predicted VE at a given HR for males compared to females (ymale = 0.020x + 0.813 vs. yfemale = 0.019x + 0.708, where y = lnVE and x = HR) with a pseudo-R2 of 0.80 for males and pseudo-R2 of 0.82 for females. Our predictive equations had the lowest average percent difference between measured and predicted VE, whereas prior models under- or overestimated VE in our sample. Overall, sex-specific GEEs provide a practical method to estimate VE from HR in adolescents and can serve as tools to support exposure assessment and future applications in environmental health research. Full article
(This article belongs to the Special Issue Ambient Air Pollution, Built Environment, and Public Health)
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17 pages, 643 KB  
Article
Particulate Matter Pollution in an Agricultural Setting: A Community-Engaged Research Study
by Bonnie N. Young, Jessica Tryner, Luis Hernandez Ramirez, Sherry WeMott, Grant Erlandson, Xiaoying Li, Grace Kuiper, Daniel Alan Dean, Nayamin Martinez, Mollie Phillips, John Volckens and Sheryl Magzamen
Environments 2025, 12(10), 348; https://doi.org/10.3390/environments12100348 - 26 Sep 2025
Viewed by 963
Abstract
California’s San Joaquin Valley experiences some of the worst particulate matter (PM) air pollution in the U.S., but PM2.5 and PM10 exposures in agricultural communities are understudied. We collaborated with rural residents living adjacent to large-scale agricultural production and processing activities [...] Read more.
California’s San Joaquin Valley experiences some of the worst particulate matter (PM) air pollution in the U.S., but PM2.5 and PM10 exposures in agricultural communities are understudied. We collaborated with rural residents living adjacent to large-scale agricultural production and processing activities to assess 24-h-average personal and indoor PM2.5 and PM10 concentrations during different seasons. We visited 35 participants from 18 households during December 2023, May 2024, and the September 2024 harvest season to collect PM samples and survey data. Mixed effects linear regression models (with random effects for participant or household) assessed associations between natural log-transformed PM concentrations and regional ambient PM, harvest season, as well as participant/household characteristics. Participants were mostly female (69%) and Hispanic/Latino(a) (100%). Median household distance to processing facility silos was 633 m. Median personal exposures to PM2.5 and PM10 were 11.1 and 45.5 µg m−3. Median indoor PM2.5 and PM10 levels were 12.9 and 24.3 µg m−3. Overall, 29% of personal and indoor PM2.5 samples and 33% of personal and indoor PM10 samples exceeded WHO 24-h air quality guidelines (15 µg m−3 PM2.5, 45 µg m−3 PM10). The factors most strongly associated with personal and indoor PM were household members working in agriculture and regional ambient PM measures. Full article
(This article belongs to the Special Issue Ambient Air Pollution, Built Environment, and Public Health)
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19 pages, 4914 KB  
Article
Development of a Portable Calibration Chamber for PM Sensors Equipped with Wireless Connectivity Controlled by a Graphical Interface in Python
by Daniel Cuevas-González, Martín Aarón Sánchez-Barajas, Marco A. Reyna, Juan Pablo García-Vázquez, Eladio Altamira-Colado and Roberto L. Avitia
Environments 2025, 12(9), 338; https://doi.org/10.3390/environments12090338 - 21 Sep 2025
Viewed by 785
Abstract
The health impact of air pollutants has generated a trend in the design and manufacture of portable, personal and fixed PM monitoring systems to help reduce exposure to air pollutants. However, these devices still need to be improved and properly evaluated to compete [...] Read more.
The health impact of air pollutants has generated a trend in the design and manufacture of portable, personal and fixed PM monitoring systems to help reduce exposure to air pollutants. However, these devices still need to be improved and properly evaluated to compete with environmental monitors in the market. In this work, a test chamber with controlled environmental conditions and wireless connectivity is developed for the evaluation of low-cost portable and personal PM sensors. The developed system ensures rapid evaluation tests ranging from seconds to hours to corroborate prolonged operation and correct calibration. The system is controlled by a Python-based graphical user interface (GUI) and monitors PM concentration, altitude, relative humidity, atmospheric pressure, illuminance, and temperature measurements. Fifty measurement tests with a duration of 10 min each were conducted to ensure robust performance and data transfer. Subsequently, four calibration tests were conducted using two SENSIRION SPS30 (SPS A and SPS B) personal PM sensors and two PMS5003 (PMS A and PMS B) personal PM sensors. The Prana Air PAS-OUT-01 sensor served as the reference to calculate the correlations and the descriptive statistics between each sensor to be calibrated. A contamination source was employed utilizing a monodispersed aerosol generator for 0.46 µm latex polystyrene particle atomization. Linear regression was applied during the calibration to determine the calibration coefficients, which were then used to adjust the sensor readings in the respective code and descriptive statistics of the sensor calibration tests were calculated. For the PMS5003 sensors, the Pearson correlation coefficients (r) after calibration were PMS A: 0.9870 and PMS B: 0.9898 compared to their uncalibrated values of PMS A: 0.9828 and PMS B: 0.9863. In contrast, the uncalibrated SPS A sensor initially had a correlation of 0.9939, which slightly decreased to 0.9917 after calibration. Meanwhile, the uncalibrated SPS B sensor showed a correlation of 0.9422, which improved to 0.9715 after calibration. Full article
(This article belongs to the Special Issue Ambient Air Pollution, Built Environment, and Public Health)
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