Search Results (188)

Accurate forecasting of energy consumption in buildings is essential for achieving energy efficiency and reducing carbon emissions. However, many existing models rely on limited input variables and overlook the complex influence of indoor environmental quality (IEQ). In this study, we assess the performance of hybrid machine learning ensembles for predicting hourly energy demand in a smart office environment using high-frequency IEQ sensor data. Environmental variables including carbon dioxide concentration (CO₂), particulate matter (PM_2.5), total volatile organic compounds (TVOCs), noise levels, humidity, and temperature were recorded over a four-month period. We evaluated two ensemble configurations combining support vector regression (SVR) with either Random Forest or LightGBM as base learners and Ridge regression as a meta-learner, alongside single-model baselines such as SVR and artificial neural networks (ANN). The SVR combined with Random Forest and Ridge regression demonstrated the highest predictive performance, achieving a mean absolute error (MAE) of 1.20, a mean absolute percentage error (MAPE) of 8.92%, and a coefficient of determination (R²) of 0.82. Feature importance analysis using SHAP values, together with non-parametric statistical testing, identified TVOCs, humidity, and PM_2.5 as the most influential predictors of energy use. These findings highlight the value of integrating high-resolution IEQ data into predictive frameworks and demonstrate that such data can significantly improve forecasting accuracy. This effect is attributed to the direct link between these IEQ variables and the activation of energy-intensive systems; fluctuations in humidity drive HVAC energy use for dehumidification, while elevated pollutant levels (TVOCs, PM_2.5) trigger increased ventilation to maintain indoor air quality, thus raising the total energy load. Full article

Analysis of changes in TVOC and VOCs chemical composition or odor characteristics of particleboard before and after decoration treatment with resin-impregnated paper (RIP), polypropylene (PP) film and polyvinyl chloride (PVC) film were studied. The effects of these three decoration treatments on masking or suppressing the release of VOCs and odorants from particleboard were explored. The substances that were covered or suppressed and newly introduced before and after processing were identified to provide a basis for reducing the odor emissions of PVC-, PP- and RIP-decorated particleboard. Taking undecorated particleboard and particleboard treated by three types of decorative materials as research subjects, the air permeability of the three decorative materials was tested using the Gurley Permeability Tester. TVOC emissions from the boards were evaluated using the 1 m³ environmental chamber method. Qualitative and quantitative analyses of the samples were conducted via thermal desorption–gas chromatography–mass spectrometry (TD-GCMS). The contribution of odor substances was determined using odor activity value (OAV). The results indicated that the permeability from high to low was PVC film, PP film and RIP. Compared with undecorated particleboard, the TVOC emissions of PVC-decorated boards decreased by 93%, PP-decorated particleboard by 83% but the TVOC emissions of RIP-decorated particleboard increased by 67%. PP decoration treatment masked or suppressed the release of 20 odor substances but introduced xylene, which can increase potentially the health risks for PP-decorated particleboard. PVC decoration treatment masked or suppressed 19 odor substances, but it introduced 12 new compounds, resulting in an overall increase in TVOC emissions. RIP treatment did not introduce new odor substances. After PP film and RIP treatments, both the variety of VOCs released and the number of key odor-contributing compounds and modifying odorants decreased. In contrast, the number of modifying odorants and potential odorants increased after PVC treatment. VOC emissions were effectively masked or suppressed by three decoration treatments, same as the release of substances contributing to overall odor of particleboard was reduced. Among them, PP and RIP decorative materials demonstrate better effects. Full article

Despite spending a substantial proportion of their time indoors, the mental health effects of indoor air pollution on children and adolescents remain inadequately explored. This study aimed to elucidate the spatiotemporal variations and sociodemographic inequalities in exposure to multiple indoor pollutants and to assess their potential associations with depressive symptoms among school-aged children in Beijing. Using real-time portable monitors, concentrations of fine particulate matter (PM_2.5), coarse particulate matter (PM₁₀), carbon dioxide (CO₂), formaldehyde (HCHO), total volatile organic compounds (TVOC), temperature, and humidity in classrooms and bedrooms were measured during both weekdays and weekends. Moreover, substantial spatiotemporal heterogeneity was observed. It was found that concentrations of PM_2.5, PM₁₀, and TVOC peaked in classrooms during weekday daytime, while CO₂ levels were highest in bedrooms on weekend nights. Exposure levels were notably higher among children whose mothers had lower educational attainment and those living in recently renovated homes, indicating marked socio-demographic disparities. In multivariable logistic regression models, indoor exposure to CO₂ and TVOC was significantly associated with increased odds of depressive symptoms. These findings highlight the critical need to improve indoor air quality through enhanced ventilation and the mitigation of emissions from indoor sources, particularly within school and residential settings. The results offer valuable empirical evidence to guide the development of targeted environmental interventions and public health policies designed to support and enhance the psychological well-being of children. Full article

The acceleration of industrialization and urbanization worldwide has dramatically improved living standards but has also introduced serious environmental and public health challenges. One of the most critical challenges is air pollution, particularly indoors, where individuals typically spend over 90% of their time. Ensuring good Indoor Air Quality (IAQ) is essential, especially in heavily frequented public spaces such as shopping malls. This study focuses on assessing IAQ in a large shopping mall located in Tabuk, Saudi Arabia, covering retail zones as well as an attached underground parking area. Monitoring is conducted over a continuous two-month period using calibrated instruments placed at representative locations to capture variations in pollutant levels. The investigation targets key contaminants, including carbon monoxide (CO), carbon dioxide (CO₂), fine particulate matter (PM_2.5), total volatile organic compounds (TVOCs), and formaldehyde (HCHO). The data are analyzed and compared against international and national guidelines, including World Health Organization (WHO) standards and Saudi environmental regulations. The results show that concentrations of CO, CO₂, and PM_2.5 in the shopping mall are generally within acceptable limits, with values ranging from approximately 7 to 15 ppm, suggesting that ventilation systems are effective in most areas. However, the study identifies high levels of TVOCs and HCHO, particularly in zones characterized by poor ventilation and high human occupancy. Peak concentrations reach 1.48 mg/m³ for TVOCs and 1.43 mg/m³ for HCHO, exceeding recommended exposure thresholds. These findings emphasize the urgent need for enhancing ventilation designs, prioritizing the use of low-emission materials, and establishing continuous air quality monitoring protocols within commercial buildings. Improving IAQ is not only crucial for protecting public health but also for enhancing occupant comfort, satisfaction, and overall building sustainability. This study offers practical recommendations to policymakers, building managers, and designers striving to create healthier indoor environments in rapidly expanding urban centers. Full article

Prolonged conflicts in Iraq over the past four decades have profoundly disrupted environmental systems, not only through immediate post-conflict emissions—such as residues from munitions and explosives—but also via long-term infrastructural collapse, population displacement, and unsustainable resource practices. Despite growing concern over air quality in conflict-affected regions, comprehensive assessments integrating long-term data and localized measurements remain scarce. This study addresses this gap by analyzing the environmental consequences of sustained instability in Mosul, focusing on air pollution trends using both remote sensing data (1983–2023) and in situ monitoring of key pollutants—including PM_2.5, PM₁₀, TVOCs, NO₂, SO₂, and formaldehyde—at six urban sites during 2022–2023. The results indicate marked seasonal variations, with winter peaks in combustion-related pollutants (NO₂, SO₂) and elevated particulate concentrations in summer driven by sandstorm activity. Annual average concentrations of all six pollutants increased by 14–51%, frequently exceeding WHO air quality guidelines. These patterns coincide with worsening meteorological conditions, including higher temperatures, reduced rainfall, and more frequent storms, suggesting synergistic effects between climate stress and pollution. The findings highlight severe public health risks and emphasize the urgent need for integrated urban recovery strategies that promote sustainable infrastructure, environmental restoration, and resilience to climate change. Full article

This study was conducted in an urban park in a temperate-continental city of Europe (Timișoara, Romania) and aimed to investigate the contribution of urban vegetation in maintaining air quality and mitigating the heat in the analyzed city. The following air parameters were monitored: fine particulate matter PM_2.5, coarse particulate matter PM₁₀, AQI (Air Quality Index) (resulted from PM_2.5 and PM₁₀), particle number, air temperature, relative air humidity, TVOC (total volatile organic compounds), and HCHO (formaldehyde). The results of this study show that urban vegetation remains a reliable factor in reducing PM_2.5 and PM₁₀ in city air and in keeping the AQI within the limits corresponding to good air quality, but also that relative air humidity counteracts the contribution of vegetation in achieving this goal. Inside the park, the HCHO concentration increased by up to 4–5 times compared to the outside, and this increase was not caused by vehicle traffic but rather by the photochemical reactions generating HCHO. Regarding the cooling effect on air temperature, the studied green space did not exhibit this effect, as the air temperature inside it increased by up to 1–6 °C compared to the outside. Our results contrast with the general perception that urban parks and green spaces are cooler islands within the cities and draw attention to the fact that having a green space in a city does not necessarily mean achieving environmental goals, such as reducing the heat risk of cities. Based on the results, we consider that the main limitations in achieving these objectives were the park’s small size (88 hectares) and its morphology and architecture resulting from the integration of the species that compose it. It follows from these data that it is not enough for an urban green space to be established, but its design must be combined with urban morphology strategies if the heat mitigation effect is to be achieved and the cooling benefits are to be maximized in cities. Full article

In this research, we present the development and validation of a compact, resource-efficient (low-cost, low-energy), distributed, real-time traffic and air quality monitoring system. Deployed since November 2023 in a small town that relies on burning various fuels and waste for winter heating, the system comprises three IoT units that integrate image processing and environmental sensing for sustainable urban and environmental management. Each unit uses an embedded camera and sensors to process live data locally, which are then transmitted to a central database. The image processing algorithm counts vehicles by type with over 95% daylight accuracy, while air quality sensors measure pollutants including particulate matter (PM), equivalent carbon dioxide (eCO₂), and total volatile organic compounds (TVOCs). Data analysis revealed fluctuations in pollutant concentrations across monitored areas, correlating with traffic variations and enabling the identification of pollution sources and their relative impacts. Recorded PM10 daily average levels even reached eight times above the safe 24 h limits in winter, when traffic values were low, indicating a strong link to household heating. This work provides a scalable, cost-effective approach to traffic and air quality monitoring, offering actionable insights for urban planning and sustainable development. Full article

Particulate matter (PM) is recognized as a leading health risk factor worldwide, causing adverse effects for people in living and working environments. During the COVID-19 pandemic, it was shown that ultrafine particles (UFP) and PM concentrations, may have played an important role in the transmission of SARS-CoV-2. This study aims to investigate whether the mechanical ventilation system installed as a COVID-19 mitigation measure in a university dining hall can be effectively and sustainably used to improve indoor UFP exposure levels, integrated with a continuous low-cost sensor monitoring system. Measurements of particle number concentration (PNC), average diameter (D_avg), and Lung Deposited Surface Area (LDSA) were performed over three working days divided into ten homogeneous daily time slots (from 12:00 am to 11:59 pm) using high-frequency (1 Hz) real-time devices. PM and other indoor pollutants (CO₂ and TVOC) were monitored using low-cost handheld sensors. Indoor PNC (Dp < 700 nm) increased and showed great variability related to dining activities, reaching a maximum average PNC level of 30,000 part/cm³ (st. dev. 16,900). D_avg (Dp < 300 nm) increased during lunch and dinner times, from 22 nm at night to 48 nm during post-dinner recovery activities. Plasma-based filter technology reduced average PNC (Dp < 700 nm) by up to three times, effectively mitigating UFP concentrations in indoor environments, especially during dining hall access periods. It could be successfully adopted also after the pandemic emergency, as a sustainable health and safety control measure to improve UFPs exposure levels. Full article

Indoor environmental quality (IEQ), encompassing thermal comfort and indoor air quality (IAQ), plays a crucial role in occupant well-being and operational performance. Although widely studied individually, integrating thermal comfort and IAQ assessments remains limited, particularly in large-scale tropical commercial settings. Hypermarkets, characterised by spatial heterogeneity and fluctuating occupancy, present challenges that conventional HVAC systems often fail to manage effectively. This study investigates thermal comfort and IAQ variability in a hypermarket located in Gombak, Malaysia, under tropical rainforest conditions based on the Köppen–Geiger climate classification, a widely used system for classifying the world’s climates. Environmental parameters were monitored using a network of IoT-enabled sensors across five functional zones during actual operations. Thermal indices (PMV, PPD) and IAQ metrics (CO₂, TVOC, PM2.5, PM10) were analysed and benchmarked against ASHRAE 55 standards to assess spatial variations and occupant exposure. Results revealed substantial heterogeneity, with the cafeteria zone recording critical discomfort (PPD 93%, CO₂ 900 ppm, TVOC 1500 ppb) due to localised heat and insufficient ventilation. Meanwhile, the intermediate retail zone maintained near-optimal conditions (PPD 12%). Although findings are specific to this hypermarket, the integrated zone-based monitoring provides empirical insights that support the enhancement of IEQ assessment approaches in tropical commercial spaces. By characterising zone-specific thermal comfort and IAQ profiles, this study contributes valuable knowledge toward developing adaptive, occupant-centred HVAC strategies for complex retail environments in hot-humid climates. Full article

Crude oil spills create environmental hazards, leading to air pollution and respiratory health risks in under-five children due to their developing organs. This study compares ambient air quality (AAQ) and the respiratory health (RH) of under-five children in crude oil-impacted and less-impacted communities. The study involved 450 under-five children (mean age: 3 years) from three Niger Delta communities: Bodo, K-Dere, and Beeri. AAQ was measured using sensors, and RH was assessed through interviewer-administered questionnaires between July and October 2022. Mean concentrations of pollutants, including PM_2.5, PM₁₀, TVOCs, and HCHO, were consistently higher in Bodo and K-Dere (oil-impacted communities) compared to Beeri (less-impacted community), with levels frequently exceeding both WHO and national standards. These concentrations were highest near spill sites and during evening periods, highlighting localized and temporal factors influencing air pollution. Respiratory symptoms such as cough, difficulty breathing, and persistent nasal congestion were significantly more prevalent among children in oil-impacted communities. Logistic regression analysis indicated a higher likelihood of respiratory issues in these communities, with odds ratios ranging from 2.53 to 14.18 for various symptoms. Elevated air pollution from crude oil spills correlates with a higher prevalence of respiratory conditions in children from impacted communities, underscoring the need for public health interventions in these areas. Full article

Ensuring rapid and efficient evacuation in high-density environments, such as stadiums, is critical for public safety during fire emergencies. Traditional fire alarm systems rely on reactive detection mechanisms, often resulting in delayed response times, increased panic, and overcrowding. This study introduces an AI-driven predictive fire alarm and evacuation model that leverages machine learning algorithms and real-time environmental sensor data to anticipate fire hazards before ignition, improving emergency response efficiency. To detect early fire risk indicators, the system processes data from 62,630 sensor measurements across 15 ecological parameters, including temperature, humidity, total volatile organic compounds (TVOC), CO₂ levels, and particulate matter. A comparative analysis of six machine learning models—Logistic Regression, Support Vector Machines (SVM), Random Forest, and proposed EvacuNet—demonstrates that EvacuNet outperforms all other models, achieving an accuracy of 99.99%, precision of 1.00, recall of 1.00, and an AUC-ROC score close to 1.00. The predictive alarm system significantly reduces false alarm rates and enhances fire detection speed, allowing emergency responders to take preemptive action. Moreover, integrating AI-driven evacuation optimization minimizes bottlenecks and congestion, reduces evacuation times, and improves structured crowd movement. These findings underscore the necessity of intelligent fire detection systems in high-occupancy venues, demonstrating that AI-based predictive modeling can drastically improve fire response and evacuation efficiency. Future research should focus on integrating IoT-enabled emergency navigation, reinforcement learning algorithms, and real-time crowd management systems to further enhance predictive accuracy and minimize casualties. By adopting such advanced technologies, large-scale venues can significantly improve emergency preparedness, reduce evacuation delays, and enhance public safety. Full article

Eucalyptus wood particleboard (EPB), commonly used in indoor decoration, releases volatile organic compounds (VOCs) that can adversely affect indoor air quality and human health. This study systematically examined the VOC emission characteristics of EPB using headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography mass spectrometry (GC-MS). A total of 65 VOCs were identified, with medium-volatility organic compounds (MVOCs) accounting for 28 compounds, low-volatility organic compounds (LVOCs) for 26, and high-volatility organic compounds (HVOCs) for 11. Terpenoids dominated the VOCs, comprising 78.46%, followed by aldehydes (10.77%) and alkanes (7.69%). Key odorant compounds (KOCs) were identified using the relative odor activity value (ROAV), with hexanal (ROAV = 100) and o-cymene (ROAV = 76.90) emerging as the most significant contributors to the overall odor profile. Thermal post-treatment at temperatures of 50–60 °C for durations of 6–12 h was found to be an effective method for reducing the residual VOCs and KOCs in the EPB, leading to a marked decrease in the peak areas of key odorants. The findings suggest several strategies for minimizing VOC emissions and eliminating residual odor, including reducing the use of miscellaneous wood materials, controlling the production of o-cymene, and employing thermal post-treatment at moderate temperatures. These measures provide a promising approach to reducing VOC and odor emissions from EPB and similar composite wood products, thereby enhancing their suitability for indoor applications. This study innovatively establishes an evaluation system for VOC emission characteristics in wood-based panels based on the ROAV. It elucidates the contribution mechanisms of key odor-active substances (e.g., hexanal and pentanal) and presents a thermal post-treatment process for source control, achieving simultaneous VOCs and odor elimination. A ROAV-guided hierarchical management strategy is proposed, providing scientific guidelines for the industrial production of high-quality particleboards with ultralow emissions (TVOC < 50 μg/m³) and minimal odor intensity (OI < Grade 3). Full article

In order to study the characteristics of the thermal runaway process of a full-size prefabricated cabin energy storage system, a full-scale prefabricated cabin energy storage physical fire test platform was designed using 100% SOC energy storage battery packs as the thermal runaway object, and full-scale prefabricated cabin energy storage system physical fire experiments were conducted. This experiment analyzes the early change rules of parameters such as temperature, voltage, CO, and VOC after the energy storage system enters thermal runaway and explores the technical methods to improve the fire protection of electrochemical energy storage systems. The results show that the time when the surface temperature of the runaway cell undergoes a sudden change is 37 s later than the time when the voltage undergoes a sudden change; the CO at the bottom and middle of the runaway cluster reaches the alarm threshold 25 s and 39 s earlier than that at the top of the cluster, respectively, and the peak concentration of CO at the bottom and middle of the cluster is more than three times that at the top of the cluster. The opening of the fan causes the CO concentration on the left side of the thermal runaway cluster to be higher than that of the runaway cluster; before the battery thermal runaway, the VOC concentration at the middle and top of the runaway cluster is generally higher than that at the bottom of the cluster. After thermal runaway occurs, the VOC concentration at the bottom of the thermal runaway cluster exceeds that at other positions of the runaway cluster and the adjacent cluster; the t_VOC at the top, middle, and bottom of the thermal runaway cluster is 2296 s, 1681 s, and 1464 s earlier than the t_CO, respectively, but the initial detection value of VOC fluctuates more than that of CO. Full article

Recently, the only UNESCO river in Nigeria has become polluted, with its color turning dark brown. Osun River serves not only domestic purposes in the city of Osogbo, but also spiritual purposes during the annual Osun Osogbo Festival (OOF). This study examines the physicochemical properties and presence of heavy metals in Osun River, and the air quality at the heritage site before, during, and after the festival. Water samples from Osun River at the UNESCO site were collected before, during, and after the 2024 festival. The water was analyzed at the Department of Environmental Health Sciences of Osun State University, Nigeria, to determine the quantity of heavy metals present in the river. Additionally, an air quality detector was used to assess the quantity of pollutants (CO₂, CO, PM_2.5, PM₁₀, TVOC, and HCHO) in the air before, during, and after the festival. In Osun River, the quantities of arsenic and copper were within the permissible levels set by the World Health Organization (WHO) for drinking water, while those of lead, chromium, and cadmium were far above the safety standards set by the WHO. The pollution rate of the river was in the order of festival day > before the festival > after the festival. The air quality on the festival day was hazardous to human health, as particulate matter (PM_2.5 and PM₁₀) and carbon dioxide were found to be far above the permissible levels set by the WHO. The implications of the findings of this study are discussed, and measures to ensure the future sustainability of this important UNESCO site in the city of Osogbo are recommended. Full article

This study focuses on the olfactometric and chemical characterisation of gaseous and vapour emissions from different crude oils. To investigate this topic, laboratory experiments were set up to obtain comparable gaseous samples: they were estimated in terms of odour concentration (C_od), via dynamic olfactometry, and chemical-specific characterisation. It was found that, even if considered similar in regard to physical properties and chemical composition, the gaseous emissions of different crude oils are significantly different in terms of odorous potential. The observed discrepancy appears to be associated with the presence of volatile organic sulphur compounds (VOSCs), and the highest values of C_od were found in samples containing mercaptans and sulphides. In addition, from the conducted comparison, it appeared that crude odorous potential, in terms of C_od, is not strictly linked to the quantity of the volatile organic compounds (VOCs), H₂S concentration, or a priori knowledge of the percentage of elemental sulphur in the crude; on the contrary, the presence of volatile organic sulphur compounds in the gaseous emissions is the most influential parameter for the odour potential of this matrix. Full article