Search Results (2,123)

In the western Hunan region, the fire pit serves as the primary space for heating, receiving guests, and sacrificial ceremonies. However, the prolonged use of wood as the main fuel for the fire pit poses a significant threat to indoor air quality and the health of residents. This study conducts field monitoring and evaluation of indoor air quality in traditional earthen residences in Western Hunan during winter. It employs software simulation to analyze the concentration of indoor pollutants in typical earthen dwellings. Three passive mitigation strategies—adjusting window size, installing interior partitions, and setting up passive smoke exhaust systems—are proposed, and their effectiveness is validated through simulation. The results indicate that the best air circulation performance occurs when the window sill height is between 0.9 and 1.5 m, and the window sill length is between 1.5 and 2.1 m. Installing partitions increases the average concentration of indoor pollutants in the fire pit and master bedroom areas by 2.33 and 3.05 times, respectively. Installing smoke exhaust systems above the fireplace can decrease indoor pollutant concentrations by more than 70%. The findings provide effective strategies for controlling health risks caused by indoor pollutants in winter without affecting local residents’ living habits and traditional customs. Full article

Battery-powered Internet of Things (IoT) sensor nodes for environmental monitoring face strict energy constraints, particularly when employing high-consumption sensors such as particulate matter sensors or gas analyzers. Extending operational lifetime without sacrificing measurement reliability remains a key challenge for large-scale air-quality monitoring deployments. This paper proposes a digital-twin-assisted adaptive sensing algorithm for reducing energy consumption by dynamically optimizing sensor usage for Indoor Air Quality (IAQ) monitoring system. The system consists of distributed sensing nodes and a central station that maintains digital twins to evaluate candidate sensing strategies based on historical data and environmental patterns. Strategies are assessed in terms of energy consumption and measurement fidelity and deployed only when a measurable improvement is achieved. The approach is evaluated across mobile and stationary sensor configurations used for monitoring indoor air quality in university laboratories while educational and research activities are carried out. For stationary nodes, clustering-based scheduling reduces the activation of high-power sensors, while for mobile nodes, variation-based triggering exploits correlations between equivalent and reference CO₂ measurements to limit energy-intensive sensing. Results demonstrate energy savings of up to approximately 70% while maintaining acceptable measurement fidelity. The findings show that reduced sensing can be used for system initialization, while digital twin evaluation enables reliable transition to adaptive sensing under suitable conditions. Full article

In megacities, where conventional mitigation strategies exhibit variable and environment-dependent performance, urban air pollution continues to be a significant public health concern. To methodically assess the operational reliability of urban smog mitigation systems under dynamic atmospheric conditions, this study proposes a data-driven failure analysis approach. A machine learning architecture based on Random Forest and XGBoost algorithms is developed using integrated meteorological and air quality metrics from Lahore, Pakistan, such as temperature, wind speed, and relative humidity. AQI is used as an integrated pollution indicator alongside meteorological variables to enhance the model’s ability to capture overall atmospheric pollution impact and improve the accuracy of smog mitigation failure prediction. This study presents a data-driven framework for predicting the failure of smog mitigation methods based on meteorological conditions. Unlike existing approaches that primarily focus only on air quality prediction, this work identifies specific environmental conditions, along with AQI as an input feature, to determine when mitigation strategies become ineffective. This enables proactive decision-making to maintain healthy indoor air quality. A threshold-controlled indoor air purification system that self-activates when the model predicts mitigation failure using real-time sensor inputs is introduced to address outdoor mitigation restrictions. PM_2.5 reduction efficiency, clean air delivery rate, and energy consumption indicators are used to evaluate the purifier’s optimized performance. Predicting mitigation failure rather than just pollution levels and connecting it with an intelligent interior reaction mechanism is what makes this research novel. In a comparative analysis, Random Forest outperforms XGBoost with an accuracy of 95.5% as opposed to 94.5%, as well as higher precision (96.9%), recall (96.1%), and F1-score (96.5%). The purifier lowered indoor AQI from dangerous to safe levels within 30–40 min. Full article

This study presents the design and performance evaluation of a hybrid solar-driven system (SOLIVE) that integrates tubular daylighting and buoyancy-driven natural ventilation within a single architectural component for industrial and large-scale buildings. While solar tubes and solar chimneys have been widely studied as independent passive technologies, their combined use in a unified system capable of delivering both daylight and ventilation remains largely unexplored. The proposed system utilizes solar tubes not only for transmitting natural daylight but also as thermal drivers that induce airflow through the stack effect generated by solar heating along the tube surface. A mathematical framework combining photometric daylight modeling and buoyancy-driven airflow analysis was developed to evaluate the system performance. Numerical simulations were conducted for three representative solar reference days (Equinox, Summer Solstice, and Winter Solstice). The influence of the key design parameters, including illuminated surface area (5–15 m²), solar tube diameter (0.1–0.3 m), and ventilated space volume (20–60 m³), was systematically analyzed. The results show that, under the adopted modelling assumptions, the system provides peak illuminance between 376 and 502 lux and ventilation rates up to 20.5 air changes per hour (ACH). These values are discussed as indicative benchmarks with respect to ISO 8995-1 and ASHRAE 62.1, rather than as proof of full real-building compliance, since glare, illuminance uniformity, thermal comfort, occupancy, wind effects and HVAC integration were not fully modelled. These findings demonstrate the potential of the proposed system as an effective passive solution for improving indoor environmental quality and reducing building energy demand in sunny climates. Full article

Previous research demonstrates that housing security and quality influence physical and mental health. Despite a rich literature on housing and health, less is known about the processes through which housing mobility programs directly affect family health. We use a single-case design to examine how the health of families with children is impacted by Families Flourish, a mobility program that combines three years of rental assistance with life coaching and placement in safe, well-resourced neighborhoods. Drawing on developmental and formative evaluation data, including longitudinally collected surveys, interviews, and administrative records, we trace families’ experiences over time. Our analysis identifies distinct pathways through which mobility improves mental and physical health—via improved indoor air quality, reduced environmental and parental stress, and enhanced access to resources. Initial health gains are subsequently leveraged to improve educational and economic outcomes. We observe a temporal sequence in outcomes, with early physical health gains and later mental health improvements as stability and safety increase. We conclude by situating these identified pathways within existing scholarship and discussing implications for planning and fair housing practice. Full article

Cooking oil fumes (COFs) are major pollutants generated during thermal food processing, with emissions rising rapidly due to urbanization and the expanding catering industry, posing significant risks to indoor air quality and human health. This review systematically examines the formation mechanisms, physicochemical properties, and environmental and health impacts of COFs. Their formation involves primary processes such as thermal oxidation, cracking, Maillard reactions, and water vaporization, alongside secondary reactions where volatile organic compounds (VOCs) contribute to ozone (O₃) and secondary organic aerosol (SOA) formation. COFs exhibit complex gas–liquid–solid coexistence and contain hazardous components including polycyclic aromatic hydrocarbons (PAHs), benzene compounds, aldehydes, and ultrafine particles (Dp ≤ 0.1 μm). Based on reported data, emission factors under typical cooking conditions range from 17.966 to 71.923 mg/(min·kg oil) for VOCs, 0.016 to 1.710 mg/(min·kg oil) for benzene compounds, and 0.458 to 1.820 mg/(min·kg oil) for formaldehyde. This highlights the variability in cooking fume emissions and associated health risks. Despite growing research attention, challenges remain in emission characterization and health risk assessment. By synthesizing current knowledge, this review provides a scientific basis for developing precise mitigation strategies and guiding future regulatory standards, with implications for improving food processing practices and indoor air quality management. Full article

Accurate and stable indoor occupancy information is essential for occupant-based intelligent ventilation control. Under a single-camera setting, existing indoor occupancy detection methods commonly suffer from missed detections caused by occlusion and blind zones, false detections caused by people outside the room, and cumulative entry–exit errors that are difficult to correct. These problems lead to false fluctuations in detected occupancy, affect control performance, and may further reduce indoor comfort or cause unnecessary energy use. To address the practical situation in which indoor spaces are commonly equipped with a single security camera, this study proposes an indoor occupancy detection method by fusing field-of-view information and entry–exit events with a single camera. The study covers method development, multi-scenario validation, parameter analysis, and a ventilation control application. The proposed method uses YOLOv8x and DeepSORT as front-end models and performs post-processing on their outputs to extract field-of-view occupancy information, entry–exit events, and blind-zone events. An occupancy confirmation and correction module is then constructed. The blind-zone event mechanism reduces the influence of missed entry–exit events and camera blind zones on occupancy judgment. The correction module integrates frame-by-frame ID counts, historical outputs, and multiple event signals to verify and suppress false occupancy changes caused by false detections, missed detections, and blind zones, thereby producing more stable indoor occupancy results. Experimental results show that the proposed method outperforms the baseline methods based on front-end object detection and tracking in terms of score, RMSE, and F1 score in three typical scenarios: an office, a home, and a classroom. In the office scenario, the proposed method achieved a score of 99.36%, an RMSE of 0.081, and an F1 score of 0.781. The detection stability was also improved in the home and classroom scenarios. In the high-density and strongly occluded classroom scenario, the absolute detection performance of the fusion-based detection method was limited by the front-end models, indicating that the method still has certain applicability boundaries in complex high-density scenes. Parameter sensitivity analysis shows that key parameters, including the entry–exit area depth, confidence threshold, and time threshold, affect the detection results of the fusion-based detection method. Under the test conditions of this study, the method performs well when the entry–exit area depth is approximately 1.5d, the YOLOv8x confidence threshold is 40%, and the time threshold is 5 × FPS. These results can provide a reference for initial parameter setting and on-site calibration in similar scenarios. Using the office scenario as a case study, the method was further applied to occupant-based ventilation control. The average CO₂ concentration during occupied periods under the proposed method was 622.43 ppm, which was closest to the result under ground-truth occupancy control, with a deviation of only 0.9 ppm. This indicates that the method can help improve indoor air quality. Compared with conventional schedule-based control, occupant-based ventilation control driven by the proposed fusion method reduced cumulative fan energy consumption by approximately 65.2%, showing good energy-saving potential at the ventilation-control level. In summary, the proposed method can effectively improve the accuracy and stability of indoor occupancy detection under a single-camera setting and provide more reliable input for occupant-based ventilation control. The framework is modular, and the front-end object detection and tracking models can be replaced according to actual deployment needs. However, the validation in this study is still mainly based on scenarios where existing security cameras can cover the main activity areas and all entry–exit passages. The applicability of the method under more complex camera arrangements, lighting variations, and automatic region configuration requires further investigation. Full article

People spend the majority of their time indoors; however, most previous studies on the health effects of particulate matter (PM) and ozone (O₃) have used outdoor concentrations as a proxy for personal exposure, which may introduce misclassification bias. Since indoor PM and O₃ originate primarily from outdoors, estimating their indoor infiltration levels provides a closer approximation of true personal exposure. This study used data on approximately four million deaths occurring over an eight-year period in Jiangsu Province, China. The infiltration factor method and time-series analysis were employed to assess the linear and nonlinear associations of short-term indoor exposure to outdoor-origin PM₁, PM_2.5, PM₁₀, and O₃ with all-cause, cardiovascular, and respiratory mortality. In addition, the interactions between indoor PM and O₃ were investigated. The results indicate that indoor exposure to outdoor-origin PM and O₃ was positively associated with mortality, and these associations were stronger than those observed for direct outdoor exposure. Each 10 μg/m³ increase in the 2-day moving average concentration of indoor PM₁, PM_2.5, PM₁₀, and O₃ was associated with a 1.82% (95% confidence interval [CI]: 1.64, 2.01), 1.02% (95% CI: 0.91, 1.13), 0.69% (95% CI: 0.62, 0.77), and 1.79% (95% CI: 1.60, 1.99) increase in all-cause mortality, respectively. No threshold was observed in the exposure-response associations. Furthermore, significant multiplicative and additive interactions were identified between infiltrated PM and O₃. Consequently, greater attention should be directed toward indoor air quality, particularly the coordinated management of combined exposure to indoor PM and O₃, in order to better protect public health. Full article

Climate change is expected to increase the overheating risk and cooling demand in buildings. This study investigates the thermal comfort and energy performance of a retrofitted glazed healthcare space using an integrated approach combining long-term field measurements with validated dynamic energy simulation. The analysed space, originally an external terrace later enclosed for medical use, is characterised by a high glazing ratio and substantial solar exposure. Continuous in situ measurements of indoor air temperature, relative humidity, and CO₂ concentration were conducted during winter and summer periods. Thermal comfort and indoor air quality were assessed according to international standards. A calibrated EnergyPlus model was used to evaluate performance under present (TMY) and future (2050, 2080) climate scenarios. The results show frequent overheating under current conditions, with peak operative temperatures exceeding 30 °C and comfort maintained for as little as 41% of the summertime in highly exposed zones. By 2080, overheating will intensify (up to 33 °C in simulations), while the cooling demand will nearly double (from 14 to 29 kWh/m²). Hybrid ventilation cooling strategies reduce cooling demand by up to 39% and maintain acceptable comfort for up to 78% of annual hours. The findings highlight the critical role of solar protection, hybrid control, and vegetation in improving the climate resilience of glazed healthcare spaces. Full article

Hurricanes cause severe impacts on lives, livelihoods, and essential systems. Hurricane Melissa impacted Jamaica as a Category 5 cyclone, resulting in estimated losses of approximately 41% of national GDP (US$8.8 billion) and eliciting widespread damage to housing, healthcare, agriculture, and urban infrastructure. Agriculture sustained heavy losses, with 41,000 hectares of damaged farmland and the loss of more than 1 million livestock animals. These impacts resulted in exposed animal closures with biological hazards. Using systems thinking, the PESTHEEL framework, and a One Health lens, we argue for viewing Hurricane Melissa as series of cascading inter-related One Health threats of waterborne and vector-borne diseases, zoonoses, antimicrobial resistance, degraded indoor and outdoor air quality, chemical pollution, and shifting migration and border dynamics. These each unfold at different timings. A structured synthesis for Jamaica and other Caribbean Small Island Developing States is provided by integrating systems thinking, One Health, and the PESTHEEL framework. Immediate and lagged risk pathways are identified, and practical risk reduction actions are proposed to support anticipatory, multisectoral recovery: enhanced syndromic, laboratory, wastewater, vector, and rodent surveillance; resilient WASH and shelter systems; non-insecticidal and integrated vector management; biosecure aid and border protocols; environmental toxicology monitoring; and climate–health intelligence. Full article

Ensuring the effective removal of airborne particles is essential for maintaining indoor air quality, particularly in environments with limited ventilation. This study examines how ion polarity regime, voltage, and relative humidity influence aerosol particle removal in a controlled, room-sized chamber (35.8 m³) using a custom-built air ionizer. Experiments were conducted under stagnant and ventilated conditions (0.5 h⁻¹) while varying ionizer polarity (positive, negative, bipolar, alternating), voltage (6 kV, 10 kV), humidity (40%, 70%), and aerosol type (incense smoke, nebulized KCl). Positive and negative unipolar ionization achieved over 90% removal within 60 min, with decay rates of 0.04–0.05 min⁻¹, half-lives of 13–17 min, and clean air delivery rates (CADR) of 60–90 m³ h⁻¹. Bipolar ionization was less efficient due to ion-ion recombination, yielding CADR values below 25 m³ h⁻¹, while alternating polarity improved deposition (40–70 m³ h⁻¹) by reducing recombination losses. Relative humidity had a minimal influence on unipolar performance but moderated efficiency in bipolar and alternating modes. Under low ventilation, unipolar negative ionization sustained high removal (96.7%), while ozone remained below the detection limits of the methods used. These findings indicate that ion polarity control and field strength strongly influence particle removal and that unipolar or alternating-polarity operation can provide effective particle removal under controlled chamber conditions, including a low-ventilation case of 0.5 h⁻¹. Full article

Poor indoor air quality (IAQ) in naturally ventilated school buildings remains a widespread problem, particularly during the heating season, when limited ventilation leads to elevated CO₂ concentrations. At the same time, increasing ventilation rates may significantly increase energy demand, creating a conflict between IAQ and energy efficiency. This study aims to evaluate whether CO₂-based demand-controlled mechanical ventilation, particularly with heat recovery (HRV), can improve IAQ while maintaining acceptable energy performance in existing school buildings. A previously validated CONTAM model of a Polish primary school classroom was used to simulate natural ventilation, mechanical exhaust ventilation, and balanced ventilation with heat recovery. In mechanical systems, CO₂-based demand-controlled ventilation (DCV) was applied. The resulting airflow rates were then used in EnergyPlus simulations to assess seasonal heating and primary energy demand under Kraków climatic conditions. Increasing the outdoor air supply rate significantly reduced indoor CO₂ concentration but led to higher heating demand in exhaust ventilation systems. In contrast, HRV reduced heating energy demand by more than 80% compared with exhaust ventilation while maintaining comparable indoor air quality. Although HRV required additional electricity for fan operation, the total primary energy consumption remained low. The results demonstrate that CO₂-based DCV systems with heat recovery provide an effective balance between indoor air quality and energy performance. These findings support the application of HRV as a practical retrofit solution for improving ventilation in existing school buildings. Full article

The construction sector must simultaneously meet rising global demand and cut embodied carbon deeply enough to satisfy European Green Deal and Bioeconomy Strategy targets—two pressures that conventional petrochemical-derived materials are poorly placed to resolve. Bio-based alternatives offer a credible path: they sequester carbon, carry lower embodied emissions, improve indoor air quality, and fit naturally within circular economy models. Yet they remain marginal in specification practice. This paper reviews the evidence on bio-based construction materials and maps the barriers that keep them there. The analysis organises these barriers into four levels—structural, economic, technical, and enabling—and traces the conditional relationships between them, with direct consequences for how policy interventions should be sequenced. The strategic case for this transition extends beyond environmental policy: the 2026 Strait of Hormuz disruption is used here as a scenario to show how dependent European construction is on fossil-derived material inputs, and how exposed that dependence leaves the sector to geopolitical supply shocks. The principal obstacles to adoption prove to be institutional and economic rather than technical—regulatory fragmentation, absent harmonised standards, fragile supply chains, and market structures that systematically undervalue bio-based solutions. The paper concludes that meaningful scaling requires coordinated action across governance, market design, and industrial policy, and that material and performance advances alone will not deliver it. Full article

Background: Indoor Environmental Quality (IEQ) in housing plays a critical role in supporting health, comfort, and daily well-being, yet research and practice often address thermal, visual, acoustic, and air quality conditions in isolation. Objective: This systematic review synthesizes findings from peer-reviewed studies to examine how residential IEQ is experienced and shaped through interactions among physical building factors, environmental conditions, occupant behaviors, and socio-economic contexts. Methods: A systematic literature review was conducted following PRISMA guidelines, including 110 peer-reviewed studies published between 2015 and 2025. Data were extracted and coded from 10,838 quotations and corresponding measured environmental parameters, enabling cross-domain thematic synthesis across eight IEQ domains and four analytical themes. Results: The results show persistent perception-to-measurement gaps, particularly in ventilation usability, low-frequency noise, nighttime thermal conditions, and moisture control. Demographic factors, including age, life stage, health sensitivity, and housing tenure, influence how IEQ conditions are perceived. Integrated IEQ assessments indicate that sleep-critical spaces, moisture robustness, and simple, quiet control systems exert disproportionate influence on overall environmental satisfaction. Conclusions: The findings highlight the need to prioritize preventive design strategies addressing moisture, thermal comfort, acoustics, and lighting, while improving usability of environmental controls. Future research should expand longitudinal and cross-context studies, particularly in low-income communities, and strengthen links between IEQ performance and health outcomes. Healthy residential environments require understanding IEQ not only as a technical performance metric but as a spatial and social condition. Full article

The perinatal period is a critical window of susceptibility for fetal development and awareness for women’s health. Pregnant women are highly motivated to reduce environmental health risks, yet often lack personalized, actionable guidance on mitigating endocrine-disrupting chemicals and other household hazards. Grounded in Motivational Interviewing theory, a digital assessment was developed to empower parents to identify and reduce exposures. The tool screens for home-based and environmental risks across several domains: air quality, lead, tobacco, cleaning agents, pesticides, and plastics (BPA/phthalates). Based on user inputs, a defined algorithm generates a positive index score paired with prioritized, low-cost behavioral recommendations designed to shift users from risk awareness to active mitigation. Since its launch in Spring 2024, the tool has had over 1900 views. Preliminary analytics suggest promising engagement, and feedback more so suggests that the motivational-interview-based framing, which emphasizes empowerment over fear, facilitates immediate behavioral changes, such as switching to safer personal care products and improving indoor ventilation. Digital health interventions that translate complex environmental data into a single, manageable score can bridge the gap between clinical knowledge and household practice. This article details the score’s calculation methodology and underlying datasets, and reports usage analytics and user feedback, discussing how digital screening can scale environmental health literacy and improve maternal and child health outcomes. Full article