Indoor air最新文献

The microbial contamination levels in the apartment transition spaces, frequently traversed by pedestrians, are closely related to resident health. This study analyzed the microbial distribution in these spaces and modeled and assessed the microbial exposure risk faced by residents following different flow paths. The results showed that the dominant genera of airborne microbes, settling microbes, wall microbes, and ground microbes were Staphylococcus, Bacillus, and Micrococcus, collectively accounting for over 70% of the total microbial population. The concentration of settling microbes in noncorridor spaces was 9.7 times higher than in corridor spaces, necessitating targeted disinfection of settling microbes in noncorridor spaces. The analysis of biodiversity indices elucidates the extent to which the biodiversity of different types of microbes is affected by variations in pedestrian flow, with airborne microbes being the most affected and ground microbes the least affected. This study also constructed a microbial exposure risk assessment model during residents’ mobility in the apartment transitional spaces. Based on this model, it was confirmed that nonfirst-floor residents using the elevator to enter and exit their homes face the highest exposure risk to airborne microbes and wall microbes, while those using the stairwell face the highest exposure risk to settling microbes and ground microbes. First-floor residents face the lowest microbial exposure risk when entering and exiting their homes. The research results not only establish a microbial exposure risk assessment system but also provide important theoretical reference for evaluating and improving the environmental quality of other similar scenarios.

Older people are more susceptible to health risks from indoor air pollution, even at low pollution levels. This study aimed to improve ventilation and air quality of densely occupied multipurpose rooms in elderly care centers (ECCs). The specific objectives were to investigate the impact of different ventilation types on ventilation performance and air quality in the ECC’s multipurpose room, including mixing (MV), displacement (DV), zone (ZV), stratum (SV), and underfloor ventilation (UV); analyze the influence of ventilation on CO₂ concentration; and discuss appropriate ventilation design comprehensively considering air velocity, CO₂ level, air change efficiency (ACE), mean age of air (MAA), contaminant removal effectiveness (CRE), and predicted mean vote (PMV). First, an experimental study was conducted, and then 11 potential optimization models were proposed based on the experiment’s results. Finally, quantitative results were obtained through computational fluid dynamics (CFD) analysis. Analysis revealed that model ZV2 with wall outlets at 1.1 m and ceiling inlets proved to be the optimal ventilation type. It had fewer air circulation and stagnation areas, and it maintained its effectiveness regardless of furniture configurations or occupant positioning (caregivers and elderly people), factors that could potentially compromise airflow in other models. Compared to model ZV2, CO₂ concentrations in the sitting breathing zone of other models increased from a minimal increase of 0.2% to a substantial increase of 38.9%. Analysis also showed that the seats in the first row consistently maintained low pollutant concentration environments. These new results offer valuable insights for ECC stakeholders by assessing ventilation and air quality in crowded spaces for older people at two different breathing heights (sitting and standing).

Awareness of how buildings interact with the occupant experience—especially human performance—is becoming more prevalent, as seen by increasing interest and investment in healthy built environments. However, there is a need to synthesize the wide array of existing indoor environmental assessment and performance research in a way that can translate directly to building design and operation. Existing research in this area typically focuses on a single isolated metric and has not focused on making the results utilizable by building practitioners. The aim of this research is to investigate existing office performance literature through meta-analyses and produce regression models for four indoor environmental quality (IEQ) metrics to support critical decision-making for building operation and renovation. To reach this aim, a literature review was conducted to identify studies that measure the impact of changing ventilation rate, temperature, horizontal illuminance, and noise level in offices on occupant task performance. This repository of field and laboratory studies was analyzed to visualize the trends between the selected IEQ metrics and task performance. The temperature, ventilation rate, and horizontal illuminance regression models showed clear improvement potential when modifying indoor conditions toward the defined high-performance range, while the regression model for noise level was inconclusive. The discussion notes the importance of designing holistically for all components of these IEQ categories to utilize the results, for example, good filtration on outdoor air for quantifying ventilation impact and uniform overhead lighting with low contrast for quantifying horizontal illuminance impact. The novelty of this work is in considering multiple facets of the indoor environment under a single, unified analysis schema and producing IEQ-based performance gains that can directly inform cost-benefit analyses of building design and renovation.

Providing high air quality is crucial to the health and well-being of older people living in nursing homes. A measurement study was undertaken in 22 communal rooms of five nursing homes in Spain to investigate the effects of heating, ventilation, and air-conditioning (HVAC) systems, room characteristics, and occupant activities on the indoor air quality. The study included 196 periods of data collection (equivalent to 5282 measurements). To the authors’ knowledge, this is the first study of indoor air quality in Spanish nursing homes. The study found that mean CO₂ concentrations were consistently below established standards, although notable peaks were evident due to specific activities. Natural and cross ventilation had a clear role in maintaining CO₂ concentrations below recommended levels. The findings indicate that lower occupancy density may be required in rooms where high-CO₂-generating activities take place, such as gym–physiotherapy rooms. The results showed that the older residents and staff were both more thermally comfortable at higher CO₂ concentrations. This suggests that striking a balance between air quality and thermal comfort is necessary. The study provides useful insights for the design of ventilation systems and spatial layouts of nursing homes, which can achieve higher levels of indoor air quality and occupant well-being.

Reports show that poor indoor air quality can be harmful to vulnerable groups and lead to various health problems. To address this problem, this work proposes a management architecture for enhancing indoor air quality by integrating the analytical learning models and regulation of indoor and outdoor pollutant concentrations, which coordinates the activation or deactivation of the pollutant control devices. The proposed system incorporates predictive and calibration functionalities to enhance overall system stability and effectiveness. This work tests the prediction accuracy of multilayer perceptron and recurrent neural network models. The experimental results show that the bidirectional long short-term memory (Bi-LSTM) with a land use regression (LUR)–based feature extraction model achieves the best predictive performance with a mean absolute error of 5.74 and a mean absolute percentage error of 15.7%, respectively. Comparing the existing Bi-LSTM work for PM2.5 prediction, the proposed Bi-LSTM model with feature selection delivers superior accuracy by about 14.58% in terms of the mean absolute error performance. To further assess the system feasibility, a self-designed air box with the Docker technology is developed to customize system parameters for various monitoring needs. The system has undergone validations through Ansys indoor airflow simulation software and scenario testing, demonstrating its effectiveness and great promise for the rapid removal of indoor pollutants.

This study focuses on the indoor radon gas monitoring in 30 residences in Campania to evaluate seasonal variability. Approximately 570 CR-39 solid-state detectors were employed. Measurements were taken monthly, quarterly, semiannually, and annually, starting in October 2022 and ending in September 2023. The seasonal variability was assessed using the Gini coefficient, with quarterly and semiannual values being comparable at 6% and 7%, respectively, while the monthly measurements exhibited a higher Gini coefficient, 13%. The measurements were conducted in accordance with the UNI ISO 11665-4:2021 standard. This preliminary study investigates the seasonal variability of radon concentration in Campania. The results obtained may support future research on a larger scale.

Currently, there is a substantial amount of research on the impact of long-term exposure to printing shop particles (PSPs) on worker health. However, the effects of short-term exposure to PSPs on consumer health and the appropriate exposure metric for assessing the health risks of PSPs remain unclear. In this study, a two-stage crossover experiment was conducted, in which 20 healthy adults were randomly exposed to different size distributions of PSPs during two separate experimental periods. Lung function of the participants was tested before and after PSP exposure, and blood samples were collected for analysis. The results indicated that, compared to traditional particle exposure metrics such as mass and number concentration, the ratio of PM₁₀ to PM₁ mass concentration (PMC₁₀/PMC₁) was a more suitable metric for evaluating PSP exposure risks. After exposure to PSPs, participants showed a decline in lung function. As the PMC₁₀/PMC₁ ratio increased in two experimental periods, lung function indicators associated with small airways, such as forced expiratory volume in 1 s (FEV₁), FEV₃, forced expiratory flow at 25% of FVC exhaled (FEF₂₅), FEF₇₅, and FEF_25-75%, significantly decreased. Blood biochemical test results revealed an increase in potassium levels in the serum of participants, potentially related to small airway damage caused by PSPs. In summary, this study proposes a more suitable exposure metric to evaluate the health impact of PSPs and other nanoparticles, offering epidemiological evidence on the health effects of short-term exposure to these substances.

This study thoroughly investigates thermal comfort conditions within an indoor swimming pool in a desert climate resembling the climatic conditions of regions like Qatar, known for its scorching summers and mild winters. The research focuses on a 17.6 × 11.7 m indoor swimming pool, assessing its response to extreme outdoor conditions: 43.3°C dry-bulb temperature and 33.3°C wet-bulb temperature for summer, and 17°C dry-bulb temperature and 10.6°C wet-bulb temperature for winter. Design considerations maintain indoor temperatures in the range of 24°C–29°C year-round, aligning with ASHRAE Handbook recommendations for indoor swimming pools. The study encompasses a comprehensive analysis, including the calculation of pool evaporation rates and the resulting latent heat load gain. Hourly Analysis Program (HAP 4.9), a specialized cooling load calculation program, was employed to determine the essential thermal load required to maintain optimum indoor conditions. Computational fluid dynamics (CFD) simulations, employing ANSYS Fluent 19.2 and incorporating standard turbulence and moisture content models following a meticulous grid independence study, were conducted. The results highlight distinct average indoor conditions for both summer and winter, encompassing parameters such as air temperature, air velocity, and relative humidity. The research outcomes, assessed using predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD), indicate comfort in summer and slight warmth in winter, serving as a valuable reference for future research on desert pool and greenhouse designs, ultimately enhancing indoor environmental quality.

Heavy metal contamination of street dust in the city of Morelia is well-documented; however, contamination of indoor dust remains largely unexplored, despite people spending most of their time indoors. Given the mobility restrictions during the COVID-19 pandemic, it was necessary to engage citizens in science; a total of 480 samples (60 houses, 4 weeks, two locations: indoor and outdoor) were collected by citizens, and general information was recorded in an app developed for this research. Heavy metal concentrations were measured by x-ray fluorescence. Contamination factor, pollution load index, and human health risk assessment were carried out. Contamination was moderate for Cu, Mn, Ni, Pb, and Zr and high for Zn. Contamination action limits were proposed based on local background values. Indoor concentrations of Cu (90 mg/kg), Pb (45 mg/kg), and Zn (731 mg/kg) were higher than outdoor concentrations, while outdoor concentrations of Fe (34217 mg/kg), Mn (838 mg/kg), and Sr (399 mg/kg) were higher than indoors. Mn, Fe, and Pb had the highest hazard indices (> 0.1) for children’s health; ailments can be expected due to Mn and Pb exposure to indoor and outdoor dust. In addition, the extreme values of Cu, Ni, and Zn were also higher than 0.1 and, therefore, these extreme values posed a risk to children’s health, both indoors and outdoors. This research was made possible through citizen science, and now, citizen participation is also essential for managing polluted dust exposure.

The COVID-19 pandemic, attributed to the highly infectious nature of the SARS-CoV-2 virus, has prompted the exigent need for the development and evaluation of effective countermeasures. Previous studies have found that antimicrobial technology and increased ventilation can dilute virus concentration in the air or destroy SARS-CoV-2 on indoor surfaces, reducing the risk of spreading COVID-19. However, evidence showing the efficacy of air purifiers equipped with high-efficiency filters in the direct removal of aerosolized SARS-CoV-2 is limited. To plug this research gap, a study was pursued in which aerosolized virology testing was conducted to evaluate the efficacy of a flow-through air purification device in removing aerosolized SARS-CoV-2 (Delta variant). The device was equipped with an internal fan, a high-efficiency particulate air (HEPA) filter, UVC-LEDs, and an ionizer for multipass large-volume air recirculation. TCID₅₀ assays were conducted to quantify and compare the infectious SARS-CoV-2 with and without the operation of the device. It was found that the air purifier was highly effective in removing aerosolized SARS-CoV-2 virus, achieving over four-log reduction within 36 s of operation and under 10 equivalent air changes in the test chamber. These findings suggest that the tested air purifier is a useful countermeasure against the spread of COVID-19 in enclosed spaces. Further research is warranted to evaluate the efficacy of air purifiers in real-world indoor environments to ascertain the wider implications of using such purifiers in safeguarding public health against COVID-19.