Indoor air最新文献

Given the concerns surrounding the possibility of crosscontamination caused by the airborne transmission of respiratory aerosols (> 5 μm in diameter) and droplets (> 5 μm in diameter) containing infectious viruses, there is a great need for simulations that reliably characterize the behaviour of these particles in real-world scenarios. This study performs a comprehensive transient CFD analysis to investigate the transmission of virus-carrying aerosols and droplets released through coughing by a mobile patient within a typical room equipped with a ventilation system. This computational study elaborately examines how particle size and relative humidity impact the dispersion of aerosols and droplets carrying virus in both mobile and stationary conditions of patients. To enhance the accuracy of this study, effective factors such as evaporation of liquid content within aerosols and droplets and random distribution of the particles, along with considerations for buoyancy, drag, lift, Brownian motion, and gravitational forces, are taken into account. To investigate the influence of aerosol and droplet size, this study considers uniform size distributions of 1, 10, and 100 μm in diameter, comprising 98.2% liquid water and 1.8% solid content. Additionally, different relative humidity levels, 0%, 50%, and 90%, are incorporated to indicate their impact on the dispersion pattern and residence time of the particles in both stationary and dynamic scenarios. According to the results, high levels of relative humidity and individuals’ movement significantly affect the turbulence intensity, airflow pattern, travelling distance, residence time and trajectory of particles, air pressure, and density distributions in such environments.

Cooking activities are responsible for substantial emissions of both particulate matter (PM) and volatile organic compounds (VOCs), two key indoor air pollutants, which can lead to numerous adverse health effects, including premature mortality. Chicken breast was prepared following tightly constrained cooking procedures with contrasting cooking methods in a well-controlled research kitchen to investigate the PM and VOC emissions by simultaneous measurements with reference instruments (an optical aerosol spectrometer measuring light scattering of single particles for continuous PM monitoring and a proton-transfer-reaction time-of-flight mass spectrometer [PTR-ToF-MS] for VOCs). Peak concentrations of PM_2.5 ranked in the order (median [μg m⁻³]) pan-frying (92.9), stir-frying (26.7), deep-frying (7.7), boiling (0.7), and air-frying (0.6). Peak concentrations of VOCs ranked in the order (median [ppb]) pan-frying (260), deep-frying (230), stir-frying (110), boiling (30), and air-frying (20). Key VOCs from different frying methods were identified in a detailed principal component analysis (PCA), including aldehydes, ketones, furans, aromatic hydrocarbons, alkenes, pyrazines, and alkanes. The cooking temperature was found to be the key factor that positively correlated with both PM and VOC emission strength, while the oil weight was negatively correlated with the PM levels. We also determined PM emission rates (varying over a wide range, e.g., for PM_2.5 from 0.1 to 2931 μg min⁻¹) and PM exposures (ranging, e.g., for PM_2.5 from approximately 2 to more than 1000 μg m⁻³ min). In addition, by using EPR spectroscopy, we measured environmentally persistent free radicals (EPFRs) that formed from heating and cooking processes at levels of approximately 10⁹ spins μg⁻¹ of PM mass. These EPFR concentrations were shown to be unaffected by ozone exposure.

The thermal perception of the human body changes with seasons. The seasonal variation of subjective thermal responses and the separation of thermal sensation and thermal comfort were studied in this paper. A new evaluation index of thermal comfort was proposed. The study was based on field surveys of 32 university students in Jiaozuo city in the cold climate zone of China. Totally, 854 valid datasets were obtained. Results indicated that the environmental parameters, clothing insulation, subjective responses and mean skin temperature were all affected by seasonal variations. The mean skin temperature increased with the rise of indoor air temperature. The influence of season changes on the difference between mean skin temperature and indoor air temperature (T_dif) was obvious. The separation of thermal comfort and thermal sensation was obvious in the four seasons. TSVs deviated 0.76, 1.13, 0.83, and 1.37 units from the thermal neutrality when TCVs were the lowest in the four seasons, respectively. The separations were more obvious in seasons with extreme climates (summer and winter) than in transition seasons with mild climates (spring and autumn). People’s emotion was affected by the thermal environment. The hotness in summer increased “boring” feelings, and the coldness in winter reduced people’s pleasantness. T_dif was proposed as a reflection of human thermoregulation. An optimal T_dif range between 6.0°C and 12.0°C was proposed, in which optimal thermal and emotional conditions were achieved. The study provides a theoretical basis for the seasonal study of human thermal response and the dynamic control of the indoor environment in the future.

Researchers and transnational public health organizations have recognized aerosol transmission as an essential route of COVID-19 transmission. Therefore, improving ventilation systems is now adopted as a core preventive measure. As young children aged 2–6 in kindergartens generally lack vaccine protection and multiple infection clusters have been identified during the pandemic, we aimed to quantify the risk of aerosol transmission in kindergartens in Taipei, Taiwan. From August to November 2021, we conducted on-site visits and continuously monitored indoor air quality indicators including carbon dioxide (CO₂) in a kindergarten located in northern Taiwan. We utilized the Wells–Riley model to estimate the basic reproduction number (R₀) of each classroom and staff office, with input parameters including the number of occupants, duration of their stay, and indoor/outdoor CO₂ concentration. Contagious settings were defined as those where the R₀ estimate exceeded 1. We conducted a scenario/sensitivity analysis to assess the effect of simulated improvement measures. During school hours, the average concentration of CO₂ in each classroom and the staff office was often more than 400 ppm higher than the outdoor levels. The R₀ estimates gradually increased from Monday to Friday and throughout school hours, corresponding to the hourly and daily distribution of the CO₂ concentration, which could not dissipate completely during off-duty time. The R₀ estimates during school hours ranged from 3.01 to 3.12 in classrooms with a maximum of 30 occupants. To lower the R₀ estimate, it is imperative to substantially reduce the number of occupants, the duration of their stay, and indoor CO₂ concentration. The risk of outbreaks of cluster infections in kindergartens should not be underestimated. Feasible strategies to mitigate this risk should include improving ventilation systems through engineering control and limiting the number of indoor occupants and their time staying indoor through administrative control.

The COVID-19 pandemic has prompted renewed interest in indoor air quality (IAQ). Poor ventilation habits, energy obsolescence, and the lack of cooling equipment in schools, combined with increasing temperatures due to climate change, are leading to situations of thermal stress in classrooms. Changes in school operation, following the COVID pandemic, have made it necessary to establish an accurate understanding of the current situation. This research work presents an assessment of winter and summer IAQ and thermal comfort (TC) for a sample of 7 archetypal secondary schools in 5 Mediterranean climate variants in southern Spain in a postpandemic situation. IAQ was assessed through CO₂, PM2.5, PM10, and CH₂O, while static and adaptive models were used in the case of TC. Surveys were also used to assess both of these. The main novelty is the use of IAPI (indoor air pollution index) and IDI (indoor dissatisfaction index) objective global dimensionless indices to optimize the joint assessment of both variables. Poor objective IAQ results, especially for CO₂ and PM2.5, were obtained for both seasons and all climate variants. Global IAPI is between 6.2 and 8.1, with an index of 10 considered unacceptable, while time percentages exceeding established limits are more variable in winter, ranging from 7% to 31.9%, than in summer, ranging from 14.3% to 20.9%. TC objective results varied, and the summer percentage of hours outside the comfort bands reached 40%–47% due to excess heat in the hottest regions. This discomfort was reported by 58.3% of users.

We introduce the holographic air-quality monitor (HAM) system, uniquely tailored for monitoring large particulate matter (PM) over 10 μm in diameter—particles critical for disease transmission and public health but overlooked by most commercial PM sensors. The HAM system utilizes a lensless digital inline holography (DIH) sensor combined with a deep learning model, enabling real-time detection of PMs with greater than 97% true positive rate at less than 0.6% false positive rate and analysis of PMs by size and morphology at a sampling rate of 26 L/min for a wide range of particle concentrations up to 4000 particles/L. Such throughput not only significantly outperforms traditional imaging-based sensors but also rivals some lower-fidelity, nonimaging sensors. Additionally, the HAM system is equipped with additional sensors for smaller PMs and various air quality conditions, ensuring a comprehensive assessment of indoor air quality. The performance of the DIH sensor within the HAM system was evaluated through comparison with brightfield microscopy, showing high concordance in size and morphology measurements. The efficacy of the DIH sensor was also demonstrated in two 2-h experiments under different environments simulating practical conditions, with one involving distinct PM-generating events. These tests highlighted the HAM system’s advanced capability to differentiate PM events from background noise and its exceptional sensitivity to irregular, large-sized PMs of low concentration.

This study investigates the adoption of indoor air quality (IAQ) management technologies in Germany and Portugal, focusing on the common and differentiating factors influencing individuals’ motivations and the perceived health impacts of these technologies. Utilizing a model based on the protection motivation theory, we surveyed 800 participants (400 from each country) to understand how their perceptions of the risks associated with poor IAQ and their evaluations of the effectiveness and costs of technologies like air purifiers and sensors drive the adoption intention of these technologies and well-being of individuals. To estimate the complex relationships in our model, we employed partial least squares structural equation modeling (PLS-SEM). Our model explains nearly 50% of the variance in well-being for both countries. The results revealed significant differences in the factors driving technology adoption: Germans are primarily motivated by individual efficacy and personal responsibility with the people close to them. Regarding the similarities, participants from both countries value the technology’s effectiveness in improving IAQ and do not see being vulnerable to health issues derived from poor IAQ as a motivator. These insights highlight the need for strategies that are tailored to specific cultural and national contexts to promote the adoption of IAQ management technologies, aiming to enhance IAQ and public health outcomes.

Air exchange rate is a key determinant of indoor air quality which is highly variable within the rooms of a naturally ventilated terraced house (townhouse). Window opening can increase the air exchange rate, but internal door opening between rooms inside decreases the rate. Inert perfluorocarbon gas-phase tracers demonstrated flow within the house, and the penetration of tracers released outside into the house showed a strong dependence on wind speed and wind direction. Between experiments, it was found that the tracer could be detected within certain parts of the house weeks after the initial release, with implications for pollutants and their impact on the indoor environment. A limited number of reactive tracer experiments suggested an upper limit for indoor [OH]~1 × 10⁵ molecule cm^-3 with up to 0.5 ppt of [NO₃] estimated, leading to an estimated indoor lifetime for d5 isoprene of many hours. Ultrafine particulate matter generated in the kitchen travels throughout the house, and the persistence of elevated aerosol concentrations is seen even in well-ventilated rooms, with implications for particle exposure in the evening and during the night.

Detailed investigation of pathogen transmission by respiratory droplets requires extensive experimental datasets with high spatial–temporal resolution in a wide range of ambient conditions. Respiratory simulators are attractive tools for those measurements, because they improve repeatability, endurance, and control of experimental conditions with respect to studies on human subjects. They also enable the use of powerful experimental techniques, which may raise health concerns if employed on humans. In this paper, we design and present a respiratory simulator, which is capable of accurately reproducing physiological flow rate profiles and allows the investigation of the spatial and temporal features of the exhaust flow by background-oriented schlieren (BOS) and particle image velocimetry (PIV). We use laser interferometry and high-magnification shadowgraphy to verify the size distributions of the emitted droplets, and we quantify the evolution of the droplet concentration during cough events by Mie scattering analysis. The experiments demonstrate the ability of the respiratory simulator to generate highly reproducible cough events with precise and controllable droplet size distributions over a wide range of flow rates.

Background: The COVID-19 pandemic has triggered a renewed interest in indoor air sampling for infectious disease surveillance. However, scalability is currently limited, as samples are usually collected in a single indoor space. An alternative is to place the device within a heating, ventilation, and air conditioning system (HVAC), but this approach has not been tested against room air sampling.

Methods: In this observational study, we sampled the air in an indoor fitness centre for 2 or 6 h, simultaneously in three locations of the main exercise hall and in the return plenum of the HVAC system. Samples were collected twice weekly for 11 weeks. All samples were tested for 29 respiratory pathogens using PCR. We compared the ventilation system and exercise hall air with regard to the presence and quantity of pathogens.

Findings: Samples collected in two locations in the exercise hall had a similar overall sensitivity to the HVAC sampler for detecting pathogens, while a third sampling location was associated with significantly lower sensitivity. Overall, the pathogen concentration was similar in the ventilation system and the exercise hall air (ratio: 1.0; 95% CI: 0.8–1.3).

Interpretation: Our results show that air sampling within a ventilation system can have equal sensitivity for detecting respiratory pathogens, compared to room-based sampling. Thus, placing samplers within central ventilation systems could increase the scalability of air sampling for infectious disease surveillance.