Search Results (1,231)

This study aimed to quantitatively evaluate the potential health effects of exposure to major air pollutants inside newly manufactured automobiles and to develop a grading system for automobile indoor air quality based on this assessment. To achieve this, the concentrations of 28 air pollutants were measured in five different automobile models. Among these, 18 substances were selected for health risk assessment based on the availability of acute and chronic toxicity data and the requirement that each substance had been detected at least once under one or more of the automobile test modes (AM, PM, and DM). Acute hazard quotients (HQ_acute), chronic non-carcinogenic hazard quotients (HQ), and excess lifetime cancer risks (ECR) were subsequently calculated. The results of acute and chronic health risk assessments showed significant variation depending on the automobile test mode, and some automobiles exceeded health-based reference values for certain pollutants. Based on these findings, this study developed a 10-level grading system for automobile indoor air quality by comprehensively integrating pollutant-specific health risk levels and exceedances of the recommended limits outlined in Ministry of Land, Infrastructure, and Transport’s “Indoor Air Quality Guidelines for Newly Manufactured Automobiles.” The grading scale ranges from Grade 1 (Excellent) to Grade 10 (Hazardous), reflecting both acute and chronic health risks as well as legal standards, thereby improving upon conventional concentration-based management approaches. The proposed grading system enables a quantitative interpretation of automobile indoor air quality from a health-based perspective and is expected to be applicable in various fields, including automobile manufacturers’ air quality control, consumer information disclosure, and policy development. Full article

Indoor sports facilities face distinctive indoor air quality (IAQ) challenges due to high occupant density, elevated metabolic emissions, and diverse pollutant sources associated with physical activity. This review presents a narrative synthesis of multidisciplinary evidence concerning IAQ in sports environments. It explores major pollutant categories, including carbon dioxide (CO₂), particulate matter (PM), volatile organic compounds (VOCs), and airborne microbial agents, highlighting their sources, behavior during exercise, and associated health risks. Research shows that physical activity can increase PM concentrations by up to 300%, and CO₂ levels frequently exceed 1000 ppm in inadequately ventilated spaces. The presence of semi-volatile organics and bioaerosols further complicates pollutant dynamics, especially in humid and densely occupied areas. Measurement technologies such as optical sensors, chromatographic methods, and molecular techniques are reviewed and compared for their applicability to dynamic indoor settings. Existing IAQ standards across China, the USA, the EU, the UK, and WHO are examined, revealing a lack of activity-specific thresholds and insufficient responsiveness to real-time conditions. Mitigation strategies (e.g., including demand-controlled ventilation, use of low-emission materials, liquid chalk substitutes, and integrated HEPA-UVGI purification systems) are evaluated, many demonstrating pollutant removal efficiencies over 80%. The integration of intelligent building management systems is emphasized for enabling real-time monitoring and adaptive control. This review concludes by identifying research priorities, including the development of activity-sensitive IAQ control frameworks and long-term health impact assessments for athletes and vulnerable users. Full article

In developing countries, indoor air pollution in rural areas is often attributed to the use of solid biomass fuels for cooking. Such fuels generate particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO₂), polyaromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). PM created from biomass combustion is a pollutant particularly damaging to health. This rigorous study employed a personal sampling device and multi-stage cascade impactor to collect airborne PM (including PM_2.5) and deposited ash from 20 real-world kitchen microenvironments. A robust analysis of the PM was undertaken using a range of morphological, physical, and chemical techniques, the results of which were then compared to a controlled burn experiment. Results revealed that airborne PM was predominantly carbon (~85%), with the OC/EC ratio varying between 1.17 and 11.5. Particles were primarily spherical nanoparticles (50–100 nm) capable of deep penetration into the human respiratory tract (HRT). This is the first systematic characterisation of biomass cooking emissions in authentic rural kitchen settings, linking particle morphology, chemistry and toxicology at health-relevant scales. Toxic heavy metals like Cr, Pb, Cd, Zn, and Hg were detected in PM, while ash was dominated by crustal elements such as Ca, Mg and P. VOCs comprised benzene derivatives, esters, ethers, ketones, tetramethysilanes (TMS), and nitrogen-, phosphorus- and sulphur-containing compounds. This research showcases a unique collection technique that gathered particles indicative of their potential for penetration and deposition in the HRT. Impact stems from the close link between the physico-chemical properties of particle emissions and their environmental and epidemiological effects. By providing a critical evidence base for exposure modelling, risk assessment and clean cooking interventions, this study delivers internationally significant insights. Our methodological innovation, capturing respirable nanoparticles under real-world conditions, offers a transferable framework for indoor air quality research across low- and middle-income countries. The findings therefore advance both fundamental understanding of combustion-derived nanoparticle behaviour and practical knowledge to inform public health, environmental policy, and the UN Sustainable Development Goals. Full article

Low-cost sensors have demonstrated their advances in acquiring hyper-localized data compared to traditional, high-maintenance air quality monitoring stations. The study aims to leverage the mobility of participants equipped with low-cost wearable monitors (LWMs) by comparing their exposure to particulate matter (PM) across indoor-home, outdoor-walking, and hybrid-commuting micro-environments. The LWMs would be calibrated first through field co-location and the multiple linear regression models. The coefficient of determination (R²) of PM_1.0 and PM_2.5 increased to over 0.85 after calibration, along with the reduced root mean square error of 2.25 and 3.46 μg/m³, respectively. The 26-day PM data collection with geographic locations could identify individual exposure patterns, local source contributions, and hotspot maps. Commuting constituted a small fraction of daily time (4–8%) but contributed a disproportionate impact, accounting for 11% of individual PM exposure. Indoor-home PM_2.5 exposure varied significantly among the urban districts. Based on the PM_2.5 hotspot map, the elevated concentration was mainly concentrated in dense residential areas and historical industrial areas, as well as interchanges of major roads and the highway system. LWMs acting as non-regulatory instruments can complement monitoring stations to provide missing short-term and hyper-localized air pollution data. Future studies should integrate long-term monitoring and citizen science across seasons and geographical regions to address pollutant spatiotemporal variability for building and city sustainability. Full article

Given the significant implications of indoor air pollution for physical and mental health, well-being and productivity, indoor air quality (IAQ) is of critical importance. CO₂ is a prevalent indoor air contaminant and represents a key determinant for IAQ characterization. This study collected sensed air pollution and climatic data from a hospital environment in Greece and employed Long Short-Term Memory (LSTM) neural network variants with progressively increased architectural complexity to predict indoor CO₂ concentration across future horizons ranging from 15 min up to 180 min. Among the examined variants, the attention-based LSTM exhibited the most consistent performance across the forecasting horizons. Incorporating additional predictors reflecting climatic conditions, air pollution and occupancy status within the hospital settings, the multivariate attention-based LSTM further enhanced its predictive performance with an MAE of 8.9 ppm, 16.7 ppm, 31.2 ppm, 38.9 and 39.5 ppm for 15 min, 30 min, 60 min, 120 min, and 180 min ahead, respectively. Full article

Traffic-induced noise pollution is a significant environmental issue, driving the development of advanced noise-reducing pavement materials. Semi-dense graded asphalt mixtures (SDAMs) present a promising compromise, offering enhanced acoustic properties compared to conventional dense-graded asphalt mixtures while maintaining superior durability to porous asphalt mixtures. However, the mechanism underlying the relationship between the energy dissipation characteristics and noise reduction effects of such mixtures remains unclear, which limits further optimization of their noise reduction performance. This study designed and prepared semi-dense graded noise-reducing asphalt mixtures SMA-6 TM, SMA-10 TM, and SMA-13 TM (SMA TM represents noise-reducing SMA mixture) based on traditional dense-graded asphalt mixtures SMA-6, SMA-10, and SMA-13, and conducted tests for water stability, high-temperature performance (60 °C), and low-temperature performance (−10 °C). Subsequently, energy loss parameters such as loss factor and damping ratio were calculated through dynamic modulus tests to characterize their energy dissipation properties. The mechanism linking the energy dissipation characteristics of semi-dense graded asphalt mixtures to noise reduction was investigated. Finally, the noise reduction effect was further verified through a tire free fall test and a close-proximity (CPX) method. The indoor test results indicate that the semi-dense mixtures exhibited a trade-off in performance: their dynamic stability was 11.1–11.3% lower and low-temperature performance decreased by 4.2% (SMA-13 TM) to 14.1% (SMA-6 TM), with moisture stability remaining comparable. Conversely, they demonstrated superior damping, with consistently higher loss factors and damping ratios. All mixtures reached peak damping at 20 °C, and the loss factor showed a strong positive correlation (R² > 0.91) with energy dissipation. Field results from a test section showed that the optimized SMA-10 TM mixture yielded a significant tire–road noise reduction of 3–5 dB(A) relative to the SMA-13, while concurrently meeting key performance criteria for anti-water ability and durability. This study establishes a link between the energy dissipation in SDAM and their noise reduction efficacy. The findings provide a theoretical framework for optimizing mixture designs and support the wider application of SDAM as a practical noise mitigation solution. Full article

Despite significant progress in controlling outdoor air pollution in Mexico City over the past three decades, indoor air pollution remains largely unaddressed. This is particularly concerning because health authorities advise people to stay indoors when outdoor pollution exceeds safe limits, yet indoor concentrations can be higher. Two optical particle counters were deployed simultaneously indoors and outdoors in 38 homes across all municipalities in Mexico City. The average indoor 24 h PM_2.5 concentration was 24.5 µg m⁻³, while PM₁₀ concentration averaged 78.6 µg m⁻³ compared to outdoor averages of 20.5 µg m⁻³ and 72.0 µg m⁻³. The PM_2.5/PM₁₀ ratio was 0.3 both indoors and outdoors. Only 20% of the homes exhibited maximum outdoor PM_2.5 concentrations 3.6 times higher than indoor; in 18%, indoor and outdoor levels were similar (0.8–1.2); and 60% of homes recorded indoor maxima up to nine times the outdoor peaks. Elevated indoor PM_2.5 was primarily linked with cooking and, to a lesser extent, cleaning activities. Peaks in PM_2.5 persisted for 4–8 h before returning to baseline. Ensuring adequate indoor ventilation is critical to maintain indoor air quality below outdoor levels and comply with WHO guidelines, highlighting the need for targeted strategies to reduce indoor exposure in urban homes. Full article

Particulate matter (PM) is a significant air pollutant in modern egg production. However, high-quality PM data from commercial egg farms are still very limited. A 6-month study, covering both cold and hot seasons, measured PM₁₀ concentrations and emissions in a 140,000-hen commercial laying hen house in the Midwest USA. An advanced measurement system was implemented for continuous and real-time monitoring, collecting data from 67 online instruments and sensors. The study generated 4318 h of valid PM₁₀ data, with 97.8% data completeness. The average daily mean (ADM) PM₁₀ concentration in the house exhaust air, standardized to 20 °C and 1 atm, was 236 ± 162 (ADM ± standard deviation) µg m⁻³. The ADM net PM₁₀ emission was 18.9 ± 2.2 mg d⁻¹ hen⁻¹. Increasing outdoor temperatures were correlated with decreased indoor PM₁₀ concentrations but increased overall emissions. Comparison with the ADM emission of 12.4 ± 13.3 mg d⁻¹ hen⁻¹ from the same house during a previous six-month study in 2004–2005 revealed that artificial hen molting in this study increased PM₁₀ concentrations and emissions. Extrapolating the ADM PM₁₀ emission from the house, the ADM PM₁₀ emission from the entire egg farm was estimated at 35.6 ± 31.1 kg d⁻¹ (or 35.6 ± 4.5 kg d⁻¹ with a 95% confidence interval). This study provides valuable insights into air quality in animal agriculture and contributes high-quality and real-world data for use in data-driven approaches such as artificial intelligence, machine learning, data mining, and big data analytics. Full article

Background: Exposure to indoor air pollution (IAP), including particulate matter of size 2.5 µm/m³ (PM_2.5) and carbon monoxide (CO) resulting from the combustion of biomass fuels in homes, is an important risk factor associated with growth and developmental delays in neonates. We investigated the association between exposure to HAP and adverse birth outcomes in a birth cohort study of 594 pregnant females in Sri Lanka. Methods: Pregnant females between the ages of 18 and 40 years were enrolled in their first trimester and followed until delivery. Baseline assessments of fuel used for cooking were used to categorize the females into high-exposure (wood and kerosene) or low-exposure (liquid petroleum gas and electricity) groups. Indoor air quality measurements of PM_2.5 (n = 303) and CO (n = 258) were conducted in a subgroup of households. The outcomes at birth included the neonates’ appearance, pulse, grimace, activity, respiration (APGAR) score, Brazelton Neonatal Behavioural Assessment Scale (BNBAS) score, and birth weight. Linear and logistic regressions were used to evaluate the association between household air pollution (HAP) and birth outcomes. Results: Of the 526 neonates assessed at delivery, 55.7% were born to mothers with high HAP exposure and 44.3% with low HAP exposure, respectively. The results of the linear regression found an inverse association between higher exposure to HAP and birthweight in the adjusted and unadjusted models; the birth weight of children in the high-exposure group was lower by 107 g compared to that of the low-exposure group after adjusting for other variables (β = −106.8; 95% confidence intervals: −197.6, −16.0). Exposure status was not associated with birth length, gestational age, or the APGAR score; however, the BNBAS motor score was significantly lower in the neonates of the high-exposure group (6.41 vs. 6.55, p = 0.04), though it was not significant when adjusted for other variables. No correlation was found between the measured indoor PM_2.5 levels and birth weight, birth length, gestational age, APGAR score, or BNBAS score. Conclusions: Exposure to IAP due to emissions from combustion products from biomass fuels adversely affects birth weight. These effects may be more pronounced in vulnerable populations in settings where primary healthcare for pregnant women is limited. Full article

Volatile organic compounds (VOCs) are common indoor air pollutants known to pose significant health risks, yet little is known about how internal exposure varies across populations and environments. This study investigated the associations between indoor air pollutants and urinary VOC biomarkers in a nationally representative sample. We analyzed data from 1880 adults in the eighth Korea National Health and Nutrition Examination Survey (2020–2021) who completed an indoor air quality (IAQ) survey and provided urine samples, assessing the influence of sociodemographic, behavioral, and environmental factors. Indoor concentrations of PM_2.5, CO₂, formaldehyde, total VOCs, benzene, ethylbenzene, toluene, xylene, and styrene were measured, alongside the urinary concentrations of nine VOC biomarkers. Associations between pollutants, sociodemographic variables, and biomarkers were evaluated using univariate and multivariable linear regression with Bonferroni correction. Older age, female, lower socioeconomic status (SES), and smoking were associated with higher urinary VOC biomarker concentrations, with smoking showing the strongest associations. Indoor ethylbenzene, styrene, benzene, and CO₂ were also associated with multiple metabolites. These findings indicated significant associations between household air pollutants and urinary VOC metabolites, with disparities by age, sex, SES, and smoking status, underscoring the importance of targeted IAQ interventions for vulnerable populations. Full article

Air pollution has a significant impact on the housing market, both in terms of property prices and buyer preferences, as well as urban development. Below, we present the main aspects of this impact. These may include a decline in property values in polluted areas, a change in buyer preferences (more buyers are taking environmental factors into account when choosing a home, including air quality—both outdoor and indoor—which translates into increased demand in ‘green’ neighborhoods), the development of energy-efficient and environmentally friendly buildings, the impact on spatial planning and urban policy, health effects, and the rental market. The study showed that air pollution has a significant negative impact on housing prices in Warsaw, particularly in relation to two pollutants: nitrogen dioxide (NO₂) and particulate matter (PM_2.5). As their concentrations decreased, housing prices increased, with the highest price sensitivity observed for smaller flats on the secondary market. The analysis used GRM and OLS statistical models, which confirmed the significance of the relationship between the concentrations of these pollutants and housing prices (per m²). NO₂ had a significant impact on prices in the primary market and on the largest flats in the secondary market, while PM_2.5 affected prices of smaller flats in the secondary market. No significant impact of other pollutants, meteorological factors, or their interaction on housing prices was detected. The study also showed that the primary and secondary markets differ significantly, requiring separate analyses. Attempts to combine them do not allow for the precise identification of key price-determining factors. Full article

This study presents real-time measurements of particulate matter (PM₁, PM_2.5, PM₁₀) and carbon dioxide (CO₂) concentrations across five university indoor environments with varying occupancy levels and natural ventilation conditions. CO₂ concentrations frequently exceeded the 1000 ppm guideline, with peak values reaching 3018 ppm and 2715 ppm in lecture spaces, whereas one workshop environment maintained levels well below limits (mean = 668 ppm). PM concentrations varied widely: PM₁₀ reached 541.5 µg/m³ in a carpeted amphitheater, significantly surpassing the 50 µg/m³ legal daily limit, while a well-ventilated classroom exhibited lower levels despite moderate occupancy (PM₁₀ max = 116.9 µg/m³). Elevated PM values were strongly associated with flooring type and occupant movement, not just activity type. Notably, window ventilation during breaks reduced CO₂ concentrations by up to 305 ppm (p < 1 × 10⁻⁴⁷) and PM₁₀ by over 20% in rooms with favorable layouts. These findings highlight the importance of ventilation strategy, spatial orientation, and surface materials in shaping indoor air quality. The study emphasizes the need for targeted, non-invasive interventions to reduce pollutant exposure in historic university buildings where mechanical ventilation upgrades are often restricted. Full article

Background: Outdoor and household PM_2.5 are established risk factors for chronic disease and early mortality. In China, high levels of outdoor PM_2.5 and solid fuel use for cooking and heating, especially in winter, pose large health risks to the country’s aging population. Hand grip strength is a validated biomarker of functional aging and strong predictor of disability and mortality in older adults. We investigated the effects of wintertime household and outdoor PM_2.5 on maximum grip strength in a rural cohort in Beijing. Methods: We analyzed data from 877 adults (mean age: 62 y) residing in 50 rural villages over three winter seasons (2018–2019, 2019–2020, and 2021–2022). Outdoor PM_2.5 was continuously measured in all villages, and household (indoor) PM_2.5 was monitored for at least two months in a randomly selected ~30% subsample of homes. Missing data were handled using multiple imputation. We applied multivariable mixed effects regression models to estimate within- and between-individual effects of PM_2.5 on grip strength, adjusting for demographic, behavioral, and health-related covariates. Results: Wintertime household and outdoor PM_2.5 concentrations ranged from 3 to 431 μg/m³ (mean = 80 μg/m³) and 8 to 100 μg/m³ (mean = 49 μg/m³), respectively. The effect of a 10 μg/m³ within-individual increase in household and outdoor PM_2.5 on maximum grip strength was 0.06 kg (95%CI: −0.01, 0.12 kg) and 1.51 kg (95%CI: 1.35, 1.68 kg), respectively. The household PM_2.5 effect attenuated after adjusting for outdoor PM_2.5, while outdoor PM_2.5 effects remained robust across sensitivity analyses. We found little evidence of between-individual effects. Conclusions: We did not find strong evidence of an adverse effect of household PM_2.5 on grip strength. The unexpected positive effects of outdoor PM_2.5 on grip strength may reflect transient physiological changes following short-term exposure. However, these findings should not be interpreted as evidence of protective effects of air pollution on aging. Rather, they highlight the complexity of air pollution’s health impacts and the value of longitudinal data in capturing time-sensitive effects. Further research is needed to better understand these patterns and their implications in high-exposure settings. Full article

Background/Objectives: As older adults spend increasing amounts of time indoors, concerns are rising about the neurological effects of indoor air pollution. This study examined associations between indoor air pollutants and structural brain changes in community-dwelling older adults in Seoul and Incheon, South Korea. A purposive sample of 23 individuals aged ≥65 years was recruited. Internet of Things (IoT)-based devices were installed in participants’ homes to continuously monitor indoor concentrations of PM₁₀, PM_2.5, and CO₂ for over two months. All participants underwent 3T brain magnetic resonance imaging (MRI), and brain structure metrics were analyzed using multiple linear regression models with and without adjustment for estimated total intracranial volume (eTIV). Hierarchical clustering was also performed based on exposure and neuroanatomical characteristics. Brain MRI indicators included cortical surface area, cortical thickness in six regions, and volumes of seven subcortical structures including the hippocampus and amygdala. Higher CO₂ concentrations were significantly associated with lower hippocampal volumes in both hemispheres (left: −2.83, −0.88, −1.02 mm³; right: −3.29, −0.86, −0.99 mm³; p ≤ 0.05). Elevated PM_2.5 levels were associated with reduced bilateral amygdala volume (−283.24 mm³ left; −292.37 mm³ right) and right hippocampal volume (−544.55 mm³; p ≤ 0.05). Cluster analysis showed that, before eTIV adjustment, Group C exhibited the lowest subcortical volumes. After adjustment, Group A showed the smallest cortical surface area, and Group D had the lowest subcortical volumes. These findings suggest that indoor air pollutants, including PM₁₀, PM_2.5, and CO₂, may be associated with structural brain alterations in older adults, supporting the need for age-specific indoor air quality standards and residential monitoring systems. Full article

Students and educators spend considerable time in indoor learning spaces on university campuses, where indoor air quality (IAQ), of which particulate matter (PM) is an important component, is a critical concern that architecture students must address. However, IAQ is seldom monitored and very rarely, if at all, reported in these spaces. We used a novel living lab approach to provide third-year students of building services with a hands-on learning activity. During a two-week monitoring period, students designed, assembled, and operated low-cost PM sensors using Arduino platforms. The data analysis showed hotspots where the IAQ was consistently compromised and showed repetitive patterns in time. Workshop and laboratory areas repeatedly recorded the highest PM levels in 15 min sampling events distributed over daily two-hour segments, averaging 43.3 and 47.9 μg/m³ PM₁₀, respectively, with maxima of 118.6 and 119.9 μg/m³ PM₁₀. These measurements would have qualified as ‘moderate’ IAQ if sustained over a full day. A distinct weekly pattern was discovered, with Mondays being worse. The results demonstrated a new practical approach to monitoring the building’s IAQ at minimal cost while obtaining reproducible data. This tool provided educators with a valuable teaching tool that provided students with a deeper understanding of indoor air pollution. Full article