Indoor air最新文献

Ultraviolet germicidal irradiation (UVGI) as an engineering control against pathogenic microbes necessitates a clear understanding of operational parameters and environmental effects on inactivation rates. Here, we investigated the variation laws of ultraviolet-C (UV-C) irradiance under the influence of distance, ambient conditions of temperature, and relative humidity (RH) in a dark chamber using 30-W low-pressure mercury lamps, and all data were analyzed with curve fitting methods. UV-C irradiances in each plane were measured as the distance adjusting between 0.5 and 1.2 m, and a threshold of 70 μW/cm² was utilized to calculate the effective irradiation area. For the temperature and RH, UV-C irradiances were measured at 1 m perpendicular from the lamp axis at the lamp midpoint, with the ambient temperature increasing from 15.5°C to 40°C and RH adjusting from 10% to 97%. Results showed that the UV-C irradiance and effective irradiation area exhibited a notable decrease as the distance increased, both corresponded to polynomial 2nd order fits. The UV-C lamps operate at maximum efficiency at 20°C. Temperature above or below the optimum value will decrease UV output, especially when the ambient temperature exceeds 38°C and the irradiance decreases by 16% compared to the observed maximum. However, the impact of RH on radiant power is negligible with the UV-C irradiance maintaining an overall steady state (84–91 μW/cm²) in the 10%–97% RH range. The use of the measurement and modeling techniques demonstrated in this study may help understand various ambient conditions that influence the irradiance of UV-C and improve reliability and working performance of UVGI systems through better design.

Traffic-related air pollutants inside vehicle cabins are often extremely high compared to background pollution concentrations. The study of the determinants of these concentrations is particularly important for professional drivers and commuters who spend long periods in vehicles. This study is aimed at identifying and quantifying the effect of several exposure determinants on carbon monoxide (CO), equivalent black carbon (eBC), two particulate matter (PM) fractions (PM_0.3–1 and PM_1–2.5), and ultrafine particle (UFP) concentrations inside a passenger car cabin. The novelty of this work consists in examining the effects of the emissions of the first vehicle ahead (henceforth called “leading vehicle”) on pollutant concentrations inside the cabin of the following vehicle (i.e., the car that was equipped with the air monitoring devices), with particular emphasis on the role of the leading vehicle characteristics (e.g., emission reduction technologies). The real-time instrumentation was placed inside the cabin of a petrol passenger car, which was driven by the same operator two times per day on the same route in real driving conditions. The in-cabin ventilation settings were set as follows: windows closed, air conditioning and recirculation modes off, and the fanned ventilation system on. The measurements were conducted over a total of 10 weekdays during two different seasons (i.e., summer and autumn). A video camera fixed to the windscreen was used to retrieve information about traffic conditions and leading vehicle characteristics through careful video analysis. The associations among pollutant concentrations and their potential determinants were evaluated using generalized estimating equation univariate and multiple models. The results confirmed the significant impact of several well-known determinants such as seasonality, microclimatic parameters, traffic jam situations, and route characteristics. Moreover, the outcomes shed light on the key role of leading vehicle emissions as determinant factors of the pollutant concentrations inside car cabins. Indeed, in the tested cabin ventilation conditions, it was demonstrated that in-cabin pollutant concentrations were significantly higher with leading vehicles ahead (from +14.6% to +67.5%) compared to empty road conditions, even though the introduction of newer technologies with better emissions reduction helped mitigate their effect. Additionally, diesel-fuelled leading vehicles compared to petrol-fuelled leading vehicles were impactful on in-cabin CO (−7.2%) and eBC (+45.3%) concentrations. An important effect (+30.4%) on in-vehicle PM_1–2.5 concentrations was found with heavy-duty compared to light-duty leading vehicles. Finally, this research pointed out that road-scale factors are more important determinant factors of in-cabin concentrations than local pollution and meteorological conditions.

Aim: Environmental exposure constitutes a significant determinant in the pathogenesis of metabolic syndrome (MetS). Nevertheless, the contribution of environmental factors to MetS remains ambiguous. The present study was aimed at investigating the correlation between serum terpenes and the risk of MetS in the general population.

Methods: A cross-sectional study was conducted among 1266 individuals from the 2013–2014 National Health and Nutrition Examination Survey (NHANES). Serum terpenes and MetS risk were analyzed using a weighted logistic regression model. Weighted quantile sum (WQS) regression was utilized to explore the relationship between the mixture of serum terpenes and MetS. The restricted cubic spline (RCS) method was employed to assess the dose–response relationship between them. All data and analyses were conducted using the “Survey” package in R software (Version 4.3.2).

Results: The study population, with an average age of 46.82 ± 0.46 years and a body mass index (BMI) of 28.97 kg/m², consisted of 48.15% males and 67.99% Whites. Among the participants, 35.78% were diagnosed with MetS. The weighted logistic regression showed that tertiles of serum levels of α-pinene, β-pinene, and limonene were positively correlated with MetS risk with a OR value of 1.90 (1.14, 3.16), 2.02 (1.23, 3.31), and 2.35 (1.33, 4.13) and elevated triglycerides (TGs) with a OR of 2.36 (1.63, 3.43), 3.51 (2.30, 5.38), and 3.96 (2.55, 6.15) (all p_trend < 0.05). The WQS regression indicated a positive association between serum terpene mixture and MetS risk (OR = 1.65, 95% CI: 1.18–2.3), increased TG (OR = 2.69, 95% CI: 1.94–3.71), and reduced high-density lipoprotein cholesterol (HDL-C) (OR = 1.46, 95% CI: 1.03–2.07) (all p_trend < 0.01). The RCS analysis further supported the dose–response relationship.

Conclusion: This study suggested potential adverse effects of terpene exposure on human health, emphasizing the importance of environmental interventions in maintaining health.

Natural ventilation has become a focal point due to its positive impact on indoor air quality, expanding its role in addressing thermal comfort issues in schools. Despite previous studies exploring various approaches to enhance natural ventilation, factors such as classrooms facing non-windward directions and optimal window opening sizes have not been adequately considered. This lack of consideration poses challenges for implementation in school environments. To address this issue, this study employed response surface methodology, back-propagation neural network, and multiple linear regression to investigate the effects of different factors on natural ventilation. Experiments were conducted in classrooms facing nonwindward directions, measuring indoor air changes per hour (ACH) during peak noon temperatures. Thermal comfort was assessed using the predicted mean vote (PMV). The experimental results showed that single window openings provided better thermal comfort compared to cross window openings while maintaining indoor CO2 concentrations below 1000 ppm. Furthermore, subsequent analysis revealed that the opening size (open and open/gap) increases the range of ACH, suggesting avenues for future research to enhance natural ventilation practices. This underscores natural ventilation’s potential in maintaining indoor thermal comfort and CO2 levels under challenging conditions.

Carbon dioxide is an important parameter for indoor air quality (IAQ) monitoring and demand controlled ventilation (DCV). Usually, CO₂ sensors are wall-mounted at 0.9–1.8 m (3–6 ft) height as prescribed by LEED, although ASHRAE standards seemed to relax this requirement. In this work, we investigate whether positioning these sensors in the ceiling is effective and advantageous. We studied CO₂-level measurements for HVAC control in configurations with mixing ventilation and found that CO₂ from human exhalations experiences buoyancy from several factors. We calculated buoyancy from air properties, and we introduced the notion of “stratification temperature” for exhaled air. By simulation, we test the sensitivity to temperature, and we conducted in situ in vivo measurements to acquire more detailed insights in the feasibility of ceiling sensor positions. Buoyancy calculations show that in exhaled air, the positive buoyancy of H₂O approximately compensates for the negative buoyancy of CO₂, so that thermal buoyancy is the most dominant factor. Exhaled air, containing CO₂ to be measured, will rise towards a ceiling that has a temperature below the stratification temperature. Computational fluid dynamics (CFD) simulations of a small office space indicate that this can also be the case in the presence of air flows induced by a mechanical ventilation system. The measurement results support that using “properly mounted” CO₂ sensors in the ceiling gives lower variability in CO₂ measurements and faster response than wall-mounted sensors and yields slightly higher values than wall sensors. Our results highlight the need to update the standards and regulations for sensing CO₂ to include ceiling-mounted sensors.

This study addresses the critical issue of indoor air quality (IAQ) and pathogen transmission within enclosed spaces at high altitudes, focusing on university classrooms in Quito, an Andean city in South America. The aim is to establish safety thresholds for room occupancy and permissible durations of exposure, tailored to this unique environmental context. Through an experimental approach conducted at an elevation of 2900 m above sea level, various natural ventilation strategies were evaluated for their efficacy in mitigating pathogen transmission risks. The study employs the Concentration Decay Test Method to characterize air changes per hour (ACH) and utilizes the Bazant mathematical model to predict occupancy levels based on ventilation, dimensions of the room, respiratory activity, infectiousness rates, and other parameters. Findings highlight the significant impact of ventilation strategies on room occupancy. Notably, higher infectiousness rates and large exposure times drastically reduce permissible occupancy levels, underscoring the importance of effective ventilation in maintaining safety. This research contributes valuable insights for informed decision-making regarding classroom capacity and safety protocols in Andean higher education settings.

In order to explore the effects of constant and altered workload sequences on mental fatigue in a thermoneutral environment, experiments and surveys were carried out in this study. n-back tasks were used to design different workload sequences. Fifteen healthy right-handed males were required to experience three different workload sequences for 30 min, respectively, including a constant workload (2-back task) and 2 altered workload sequences that contained an elevating workload sequence (1-2-3-back tasks) and a reducing workload sequence (3-2-1-back tasks). The PANAS, VAS-F, and NASA-TLX scales were selected to investigate changes in the mood, the perceived fatigue, and the perceived workload. Meanwhile, the skin temperature during these three workload sequences was continuously collected. Results from the NASA-TLX scale indicated that no significant difference in total workload was observed among all three workload sequences. Meanwhile, results from the VAS-F scale showed that no significant changes in self-reported mental fatigue were observed among these three workload sequences, which meant that mental fatigue was only related to the total workload. However, self-reported “energy” from the VAS-F scale did not reduce significantly during the reducing workload sequence, which meant that the reducing workload sequence could conserve more “energy” than that of the elevating and constant workload sequences. Furthermore, both positive and negative moods changed significantly under the constant workload sequence (2-back task), but they did not show much changes under altered workloads, which meant that the altered workload sequence could attenuate the mood deterioration. What is more, the mental demand, physical demand, temporal demand, effort, and the total workload increased significantly after both the constant workload and elevating workload sequence, but no significant changes in all these six items of the NASA-TLX scale were observed under the reducing workload sequence. Finally, the mean skin temperature under the constant workload sequence was lower than that under the altered workload sequences (p > 0.05), but significant changes in skin temperature at the left hand and neck were only observed between the constant and reducing workload sequences. In conclusion, constant and altered workload sequences contributed equally to the mental fatigue in a thermoneutral environment, but the differences in workload sequence produced some differences in mood, energy, and mental demand, which would affect the working performance. Findings of this study provided implications for the proper planning, assignment, and management of tasks in real working settings.

Indoor air quality is becoming one of the most important factors for public health, as people tend to spend more time indoors, either at home or at work. This paper combines the use of calibrated low-cost particulate matter (PM) sensors with source apportionment algorithms to understand the factors that affect the indoor air quality within a typical UK school. Low-cost optical particle counter (OPC) sensors were placed in three different classrooms within the school, measuring PM concentrations during a typical school week and the subsequent holiday period, to understand the role of occupancy within schools for air quality. When students were in attendance during school hours (09:00–15:30), the classroom with the greatest average PM levels had PM_2.5 and PM₁₀ mass concentrations of 14.4 and 51.0 μg/m³, respectively. During school hours, when students were present, all classrooms had average PM_2.5 concentrations greater than 8.1 μg m⁻³ and average PM₁₀ concentrations greater than 13.1 μg m⁻³. Notably, the English studies classroom exceeded the 24-h WHO ambient PM₁₀ guideline (45 μg m⁻³). Employing the non-negative matrix factorization (NMF) algorithm for source apportionment revealed that between 93% and 98% of PM₁ observed within classrooms derived from outdoor sources. This contribution diminished as particle size increased, with outdoor sources accounting for 74%–89% of PM_2.5, and 19%–40% of PM₁₀, respectively. The differences in classroom PM concentration and source percentages are attributed to differences in lesson activities, lesson frequency, flooring (carpeted versus hard flooring), location within the school, and proximity to outdoor sources such as roads. The approach described within the paper is easily translated to other indoor locations and could also be straightforwardly scaled due to its relatively low cost. Thereby, it allows for air quality management in locations crucial for the public health and educational outcomes of children.

Understanding radon-prone areas is vital to prevent radon-related health problems, enhance public safety, and ensure adherence to regulations aimed at minimizing radon exposure. We conducted a comprehensive review of cross-sectional studies reporting on residential radon exposure in Iran. Our review encompassed studies published until February 13, 2022. Out of the 966 articles initially identified, 37 studies were included in our analysis, which measured indoor radon levels in a total of 3480 residential buildings in Iran. Notably, the highest residential radon levels (Bq.m⁻³) were found in Mazandaran province, with the most hazardous recorded levels in Talesh Mahalleh (3235), followed by Ramsar (1299). Conversely, Tehran, the capital city of Iran, had the lowest recorded levels of residential radon, at 11.0 Bq.m⁻³. Remarkably, indoor radon concentration exceeded both the reference levels recommended by the World Health Organization (WHO) and the standard levels set by the U.S. Environmental Protection Agency (US.EPA), with approximately 51% and 26%, respectively. The mean effective doses received by Iranian residents were 5.0 mSv.y⁻¹ (0.3–81.7). Moreover, the mean excess lifetime cancer risk (ELCR) associated with indoor radon exposure was determined to be two per 1000 people. The annual incidence of lung cancer cases (LCCs) per million people attributed to indoor radon exposure in Iranian residential buildings ranged from 5.00E − 06 to 1.47E − 03. The included studies addressed a wide range of variables affecting radon levels, but they did not cover all factors comprehensively. These factors encompass the meteorological parameters, geological characteristics, building construction materials, building type, window type, occupancy information, and ventilation rates in enclosed spaces. The potential health risks associated with indoor radon exposure necessitate the implementation of effective control measures. These should include raising public awareness, revising construction regulations, enhancing ventilation systems, identifying high-risk areas, and conducting more comprehensive studies to better understand the factors that influence radon concentration.

The cytotoxicity of PM_2.5 (fine particulate) derived from varying fuels burning in different microenvironments remains unclear. In this study, the toxicity of PM_2.5 collected from northern China in the winter on human cervical carcinoma (HeLa) cells was determined. The PM_2.5 from chunk coal (CC) combustion caused greater apoptosis (22.47%) than firewood (FW) burning (5.32%), while the effects on cell viability showed contrary patterns between FW (stimulation: 132.38%) and CC (inhibition: 87.05%). Furthermore, all the samples induced significant oxidative stress and inflammatory responses in cells. Intriguingly, PM_2.5 samples collected from FW burning upregulated the expression genes involved in pathways in cancer, whereas those from CC burning downregulated the levels. Accordingly, the health risks of different samples were assessed through a probabilistic model. The risk level of samples of CC burning from the living room (CC/L) was 0.752, followed by CC from the bedroom (CC/B, 0.736), and then CC from the kitchen (CC/K, 0.562), FW without a chimney (FW-C, 0.451), and FW with a chimney (FW+C, 0.446). Meanwhile, the survival curves established by gene expression indicated that PM_2.5 from FW might be positively correlated with cancer progression. This pilot investigation demonstrated that CC combustion in the living room posed the highest health risk, and improved cookstoves (with a chimney) markedly reduced the risk. This pilot study presents a novel model for assessing health risks associated with air pollution using the toxicology method and real-time PM_2.5 quantification.