Abstract Portable air cleaners (PACs) are commonly used to remove airborne particulate matter (PM) from indoor environments. This study evaluated the impact of a PAC on cognitive performance among 62 participants in an office environment by using a computer-based cognitive test battery of six tasks. Participants were exposed to PM from an essential oil diffuser with unscented oil and tap water during both air cleaner and placebo conditions in a balanced design. PM concentrations were 2.4 to 4 times lower when using the PAC compared to the placebo condition. Despite the significant reduction in PM levels, no significant improvement in cognitive scores was observed during PAC operation. However, using a mixed-effects model with outliers removed, a significant improvement in the feature match task was observed. When the PAC achieved a higher reduction in PM2.5 concentration, cognitive scores improved for three out of six tasks when compared to a smaller reduction in PM2.5, although the effect was not statistically significant. There was also no ordering effect between initial and subsequent placements of participants in either condition. Overall, these results indicate that although PACs effectively reduce PM, their impact on cognitive performance remains uncertain and may vary with PM source type, concentration, exposure duration, task demands, and other contextual factors.

Mechanical ventilation (MV) in public buildings is typically designed for minimum ventilation rates, which challenges the global carbon-reduction goals. While portable air cleaners (PACs) are widely used as supplementary devices, their potential as partial substitutes for ventilation—maintaining acceptable indoor air quality (IAQ) with reduced energy demand—remains underexplored. This study integrated controlled twin-chamber experiments with multi-city modelling to quantify energy-IAQ trade-offs of MV and PAC systems at different air change rates (ACHs) and explore integrated MV–PAC strategies. The experiments aimed to: (1) quantify the cleaning performance and energy burden of MV-only and PAC-only systems across representative pollutants (ultrafine particles, PM0.3–10, ozone, TVOC, and benzene series) using the Levenberg–Marquardt optimization; (2) assess the effects of air distribution, ACH, and emission sources; and (3) validate a theoretical MV–PAC coupling model. Five scenarios were developed based on CO₂-derived clean air demand, each representing a different PAC-to-MV substitution ratio. Two key decision factors—the dominant pollutant type and the indoor–outdoor enthalpy difference—were applied to analyze system performance across 15 cities spanning various climate zones and seasons. Results indicated that both MV and PAC systems removed particles more effectively than ozone, with PAC performance sensitive to ACH and more effective when indoor emissions dominated. Integrated MV-PAC system achieved up to 50% energy savings in summer while maintaining pollutant removal above 80%, with optimal configurations varying by climate and pollutant profiles. These findings support informed decision-making for integrating PACs with MV systems, promoting more flexible and energy-efficient ventilation strategies.

Indoor environmental quality (IEQ) is a central determinant of occupant health, comfort, and well-being, and is closely intertwined with building energy use and operational performance. Yet, prevailing IEQ evaluation methods rely primarily on threshold-based criteria that inadequately capture the multidimensional and interdependent nature of IEQ and the variability in occupant perceptions. This study presents the ATLAS Index (Air quality, Thermal comfort, Lighting, and Acoustics Scale), a novel performance-based framework for integrated and continuous IEQ evaluation, developed for residential environments but readily adaptable to other indoor spaces. ATLAS integrates multiple parameters across four IEQ domains using a logarithmic aggregation method that prioritizes the lowest-performing domain, minimizes artifacts associated with rigid threshold cut-offs, and enables flexible domain weighting. Parameter selection and scoring criteria are grounded in internationally recognized guidelines and standards including WHO guidelines, ASHRAE standards, and EN standards, adapted to residential environments where relevant. Occupant perceptions were integrated by dynamically reweighting IEQ domains using Bayesian updating based on periodic surveys. The ATLAS index was demonstrated with 1.5 years of continuous IEQ measurements from 10 occupied apartments in Valencia, Spain. Results show that acoustic conditions frequently constrained overall IEQ scores, and that correlations between objective IEQ scores and self-reported satisfaction were weak, underscoring the complexity of interpreting residential IEQ based solely on physical measurements. An open-source web-based visualization tool is provided to facilitate practical deployment and benchmarking. The ATLAS index provides a flexible and scalable framework for next-generation IEQ assessment, adaptable to evolving emerging sensing technologies and diverse building contexts.

Indoor air quality (IAQ) in classrooms significantly impacts the comfort, health, and cognitive performance of students and teachers. The COVID-19 pandemic heightened awareness of IAQ, leading to increasing adoption of mechanical ventilation systems in schools. This study investigates IAQ across 24 primary schools (11 equipped with mechanical ventilation) in the French-speaking region of Switzerland. Concentrations of carbon dioxide (CO2), particulate matter (PM), and volatile organic compounds (VOCs) were monitored during four week-long campaigns spanning from autumn 2021 to winter 2023, partially encompassing the COVID-19 pandemic until February 2022 and heating energy shortages in winter 2023. Supplementary measurements of radon and nanoparticles were performed at selected locations. During school hours, the median concentrations of CO2 and PM2.5 were 560 ppm and 4 mu g/m3, respectively (interquartile ranges: 450-780 ppm and 2-6 mu g/m3, respectively). Total VOCs (TVOCs) concentrations averaged 41 +/- 66 ppb (mean +/- standard deviation; integrated measurement including nighttime and weekends). In autumn and winter, classrooms with mechanical ventilation had 20-30 % lower CO2 and TVOC levels compared to naturally ventilated ones. Notably, naturally ventilated classrooms had significantly higher TVOC but lower CO2 levels in winter 2022 than in winter 2023, presumably due to more frequent window opening and cleaning practices tied to COVID-19 regulations. Commonly identified VOCs included acetaldehyde, formaldehyde, acetone, and ethanol. The findings underscore the effectiveness of mechanical ventilation in improving IAQ in schools, while highlighting the influence of seasonal and contextual factors on pollutant levels.

With a growing emphasis on indoor air quality (IAQ) in educational environments, CO2 monitoring in classrooms has become commonplace. CO2 data can be used to estimate outdoor air change rate (ACH) based on the mass balance principle, which can be further linked to human health, performance, and building energy consumption. This study used a novel machine learning method to automatically segment CO2 concentration time series data into build-up, equilibrium, and decay periods, and then estimated classroom ACH using the corresponding CO2 mass balance equations. This method, applied to 40 classrooms in two mechanically ventilated K-6 schools, generated up to ten ACH estimates per day per classroom. A comparison with ACH calculated using the mechanical ventilation rates with 100% outdoor air reported by the building automation system during the study period reveals a slight underestimation by the decay and build-up methods, while the equilibrium method produced closer estimates. These differences may be attributed to uncertainties in occupancy, activity, CO2 emission rates, and air mixing. This research underscores the potential of leveraging CO2 data for more comprehensive IAQ assessments and highlights the challenges associated with accurately estimating ACH in real-world settings.

Mould growth is a common problem in building envelopes. This issue is usually caused by poor design and construction of walls and results from the difference between indoor and outdoor climatic conditions. Mould spores produced by mouldy walls may diffuse into the air, thereby affecting indoor air quality and threatening occupant health. Therefore, it is important to predict the risk of mould growth in building envelopes under various conditions. This study selected three buildings from a traditional community in Shanghai, China. First, the mould species in these building envelopes were identified. Based on the identification results, the growth rate of the corresponding genera was extracted from the literature to establish an isoline model that describes mould growth on the agar surface. In addition, the mould growth rate between and outside the isoline areas was predicted by modifying the Sautour model to relevant air temperature and humidity conditions. According to the results of the proposed model, the critical temperature and humidity that allow the growth of representative moulds from the buildings selected for this study can be expressed as φ=0.002633·cosh[0.10083·( θ-30)]+0.7153. The accuracy of the above model was verified experimentally, and the maximum relative error of the growth rate was within 25%.

Low-cost air quality monitors are increasingly being deployed in various indoor environments. However, data of high temporal resolution from those sensors are often summarized into a single mean value, with information about pollutant dynamics discarded. Further, low-cost sensors often suffer from limitations such as a lack of absolute accuracy and drift over time. There is a growing interest in utilizing data science and machine learning techniques to overcome those limitations and take full advantage of low-cost sensors. In this study, we developed an unsupervised machine learning model for automatically recognizing decay periods from concentration time series data and estimating pollutant loss rates. The model uses k-means and DBSCAN clustering to extract decays and then mass balance equations to estimate loss rates. Applications on data collected from various environments suggest that the CO2 loss rate was consistently lower than the PM2.5 loss rate in the same environment, while both varied spatially and temporally. Further, detailed protocols were established to select optimal model hyperparameters and filter out results with high uncertainty. Overall, this model provides a novel solution to monitoring pollutant removal rates with potentially wide applications such as evaluating filtration and ventilation and characterizing indoor emission sources.

Central flues are now commonly adopted in high-rise residential buildings in China for cooking oil fumes (COF) exhaust. Range hoods of all floors are connected to the central shaft, where oil fumes were gathered and exhausted through the outlet at the building roof. As households may cook and use their range hood at random periods, there is great uncertainty of the amount of COF being exhausted. In addition, users can often adjust the exhaust rate of the range hood according to their needs. As a result, thousands of possible operating conditions consisting of distinct combinations of on/off conditions and fan speed occur randomly in the central COF exhaust system, causing the exhaust performance to vary considerably from condition to condition. This work developed a mathematical model for characterizing the operation of the central COF exhaust system in a high-rise residential building as well as its iterative solving method. Full-scale tests coupled with CFD simulation referring to a real 30-floor building were conducted to validate the proposed model. The results show that the model agreed well with the CFD and experimental data under various system operating conditions. Moreover, the Monte-Carlo method was introduced to simulate the random operating characteristics of the system, and a hundred thousand cases corresponding to distinct system operating conditions were sampled and statistically analyzed.

In the scenarios of cooking oil fume exhaust in high-rise residential buildings and pollutants removal in industrial workshops, how to realize the exhaust uniformity is a problem. We discovered through our previous work that installing flow-guide devices at terminals within the exhaust system can greatly improve the exhaust uniformity of the system, but in-depth experimental studies on the flow balance characteristics of such devices under different influential factors are required. Therefore, this study aims to verify the effect of the proposed flow-guide devices on improving the exhaust performance of the system through a full-scale experiment considering multiple factors. First, the key parameter of the flow-guide device was identified. Then, the exhaust air volume and pressure of the terminals were tested under various opening modes and coincidence factors. Finally, error, significance and variance analyses were performed to process the experimental data comprehensively. Results show that the system with flow-guide devices exhibited a considerably improved exhaust uniformity compared with the system without such devices. Meanwhile, the use of flow-guide devices alters the function of the coincidence factors and the opening modes of the terminals in the exhaust uniformity and energy consumption of the system. Furthermore, the proposed devices are suitable for scenarios with a high coincidence factor. The novelty of this work is to comprehensively test the effect of flow-guide devices on the exhaust uniformity and energy consumption of the centralized exhaust system, accumulating experimental data for future engineering applications.

Ultrasonic essential oil diffusers (EODs) are a popular type of indoor scenting source. We performed a chamber study in which we measured the emissions from EODs used with lemon, lavender, eucalyptus, and grapeseed oils. Over the course of 15 min, the most abundant VOCs released from lemon, lavender, eucalyptus, and grapeseed oils were 2.6 ± 0.7 mg of d-limonene, 3.5 ± 0.4 mg of eucalyptol, 1.0 ± 0.1 mg of linalyl acetate, and 0.2 ± 0.02 mg of linalyl acetate, respectively. Each oil had a unique particulate matter (PM) emission profile in terms of size, number density, and rate. The dominant size ranges of the PM were 10-100 nm for lemon oil, 50-100 nm for lavender oil, 10-50 nm for lemon oil, and above 200 nm for grapeseed oil. PM1 emission rates of approximately 2 mg/h, 0.1 mg/h, and 3 mg/h, were observed for lemon, lavender/eucalyptus, and grapeseed oils, respectively. A fivefold increase in PM1 emission was measured when the EOD with eucalyptus oil was filled with tap water as opposed to deionized water. Modeling suggests that reasonable use cases of EODs can contribute substantially to primary and secondary PM in indoor environments, but this potential varies depending on the oil and water types used.

Essential oil products are increasingly used in indoor environments and have been found to negatively contribute to indoor air quality. Moreover, the chemicals and fragrances emitted by those products may affect the central nervous system and cognitive function. This study uses a double-blind between-subject design to investigate the cognitive impact of exposure to the emissions from essential oil used in an ultrasonic diffuser. In a simulated office environment where other environmental parameters were maintained constant, 34 female and 25 male university students were randomly allocated into four essential oil exposure scenarios. The first two scenarios contrast lemon oil to pure deionized water, while the latter two focus on different levels of particulate matter differentiated by HEPA filters with non-scented grapeseed oil as the source. Cognitive function was assessed using a computer-based battery consisting of five objective tests that involve reasoning, response inhabitation, memory, risk-taking, and decision-making. Results show that exposure to essential oil emissions caused shortened reaction time at the cost of significantly worse response inhabitation control and memory sensitivity, indicating potentially more impulsive decision-making. The cognitive responses caused by scented lemon oil and non-scented grapeseed oil were similar, as was the perception of odor pleasantness and intensity.

Poor indoor air quality indicated by elevated indoor CO2 concentrations has been linked with impaired cognitive function, yet current findings of the cognitive impact of CO2 are inconsistent. This review summarizes the results from 37 experimental studies that conducted objective cognitive tests with manipulated CO2 concentrations, either through adding pure CO2 or adjusting ventilation rates (the latter also affects other indoor pollutants). Studies with varied designs suggested that both approaches can affect multiple cognitive functions. In a subset of studies that meet objective criteria for strength and consistency, pure CO2 at a concentration common in indoor environments was only found to affect high-level decision-making measured by the Strategic Management Simulation battery in non-specialized populations, while lower ventilation and accumulation of indoor pollutants, including CO2, could reduce the speed of various functions but leave accuracy unaffected. Major confounding factors include variations in cognitive assessment methods, study designs, individual and populational differences in subjects, and uncertainties in exposure doses. Accordingly, future research is suggested to adopt direct air delivery for precise control of CO2 inhalation, include brain imaging techniques to better understand the underlying mechanisms that link CO2 and cognitive function, and explore the potential interaction between CO2 and other environmental stimuli.

Editor—Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is thought to be through fomites, droplets, and droplet nuclei (aerosols).1van Doremalen N. Bushmaker T. Morris D.H. et al.Aerosol and surface stability of SARS-CoV-2 as compared with SARS-CoV-1.N Engl J Med. 2020; 382: 1564-1567Crossref PubMed Scopus (6034) Google Scholar Aerosol-generating medical procedures are commonly performed and are associated with increased risk of infection of healthcare workers.2Tran K. Cimon K. Severn M. Pessoa-Silva C.L. Conly J. Aerosol generating procedures and risk of transmission of acute respiratory infections to healthcare workers: a systematic review.PLoS One. 2012; 7e35797Crossref PubMed Scopus (1223) Google Scholar Some clinicians are using barriers such as transparent plastics and Plexiglas boxes to reduce aerosol spread.3Matava C.T. Yu J. Denning S. Clear plastic drapes may be effective at limiting aerosolization and droplet spray during extubation: implications for COVID-19.Can J Anaesth. 2020; 67: 902-904Crossref PubMed Scopus (122) Google Scholar, 4Cubillos J. Querney J. Rankin A. Moore J. Armstrong K. A multipurpose portable negative air flow isolation chamber for aerosol-generating procedures during the COVID-19 pandemic.Br J Anaesth. 2020; 125: e179-e181Abstract Full Text Full Text PDF PubMed Scopus (46) Google Scholar, 5Lang A.L. Shaw K.M. Lozano R. Wang J. Effectiveness of a negative-pressure patient isolation hood shown using particle count.Br J Anaesth. 2020; (Advance Access published on May 15)https://doi.org/10.1016/j.bja.2020.05.002Abstract Full Text Full Text PDF PubMed Scopus (13) Google Scholar, 6Begley J.L. Lavery K.E. Nickson C.P. Brewster D.J. The aerosol box for intubation in COVID-19 patients: an in-situ simulation crossover study.Anaesthesia. 2020; 75: 1014-1021Crossref PubMed Scopus (166) Google Scholar, 7Yang S.S. Zhang M. Chong J.J.R. Comparison of three tracheal intubation methods for reducing droplet spread for use in COVID-19 patients.Br J Anaesth. 2020; 125: e190-e191Abstract Full Text Full Text PDF PubMed Scopus (13) Google Scholar However, these barriers may limit access to the patient and mobility of the clinician.8Kovatsis P.G. Matava C.T. Peyton J.M. More on barrier enclosure during endotracheal intubation.N Engl J Med. 2020; 382: e69Crossref PubMed Scopus (23) Google Scholar An alternative to barriers that may reduce aerosol spread is directed high flow air extraction. A high flow air extractor combines high flow suction and a high-efficiency particulate (HEPA) filter. We conducted a study to determine if high flow air extraction reduces aerosol exposure of clinicians. We designed an experimental model that determined the efficacy of removal of particles similar in size to human aerosols. We used two particles to simulate aerosols, essential oil particles ranging in size from 1 nm to 1 μm, and ISO 12103-1 A1 Ultrafine test dust (Powder Technologies Inc., Arden Hills, MN, USA) ranging in size from 1 to 20 μm. We simulated human breathing using an essential oil diffuser as a continuous aerosol source. Human cough aerosols range in size from 0.58 to 5.42 μm with 80% in the 0.74–2.12 μm range.9Yang S. Lee G.W. Chen C.M. Wu C.C. Yu K.P. The size and concentration of droplets generated by coughing in human subjects.J Aerosol Med. 2007; 20: 484-494Crossref PubMed Scopus (321) Google Scholar For coughing experiments, a manikin (Electripod ET/J10 Tracheal Intubation model; TUQI, Shanghai, China) was used (Supplementary 1a, b). We applied 500 mg of A1 Ultrafine test dust to the oropharynx and distal trachea of the manikin and simulated a cough using a medical air gun connected to the distal trachea and fired for 0.4 s. The researchers placed their hand 2–3 cm from the mouth of the manikin to simulate a covered cough. The high-flow air extractor Epurair HA-500 (Industrie Orkan Inc., Montreal, Quebec, Canada) was placed 25–30 cm above the manikin's head. We quantified aerosols with the following sensors (Supplementary 1a, b). Two dust aerosol calibrated DustTrak DRX (TSI, Shoreview, MN, USA) units using four chambers placed near the source and the clinician's head. Two wide-range aerosol spectrometers, miniWRAS 1371 (Grimm Aerosol Technik, Ainring, Germany) each with 41 bins and calibrated to an oil aerosol were similarly placed. To determine the vertical and horizontal variation in concentrations, 10 DC1700 optical particle monitors (Dylos, Riverside, CA, USA) were placed at predetermined positions (Supplementary 1a, b). To eliminate inter-monitor variation, monitors were co-located for 10 min after the experiments and reported concentrations corrected by the deviation from the mean concentration of each monitor. The high-flow air extractor is a portable high efficiency filtration unit allowing up to 235 L s−1 (500 ft3 min−1) that can be used to transform a regular room into a negative pressure room. It contains a HEPA filter that removes 99.97% of all airborne pathogens of 0.3 μm or greater. The filtered air can be adapted to an existing exhaust system or vented outside. We operated the device with a calibrated booster fan to maintain a continuously measured flow of 142 L min−1 for the experiments (Supplementary 2). Each experiment was completed in triplicate, and mean concentration values were used for analysis. Our primary outcome was to determine the reduction of aerosols at the source. A 99% reduction in the aerosol concentration near the source would be consistent with the Centre for Disease Prevention and Control's (CDC) requirements for air exchanges between patient encounters.10Jensen P.A. Lambert L.A. Iademarco M.F. Ridzon R. Guidelines for preventing the transmission of Mycobacterium tuberculosis in health-care settings.MMWR Recomm Rep. 2005; 54 (2005): 1-141PubMed Google Scholar Secondary outcomes included reduction of aerosol concentrations at the level of the clinician's head with the high-flow air extractor 'on' during a cough and an obstructed cough. The effectiveness, H, was calculated by subtracting the ratio of 'high-flow air extractor on' to 'high-flow air extractor off' mean particle concentration measured by each aerosol quantification device from unity. The high-flow extractor device was 99% effective at removing aerosols near the source, resulting in no levels detected at the clinician's head (Fig. 1a and Supplementary 3 online video). During an uncovered cough, the high-flow extractor had a 97% effectiveness in reducing the aerosols detected near the clinician's head (Fig. 1b). In these first two scenarios, aerosols were effectively removed at source and did not contaminate the room or reach the clinician's head. However, when the cough was covered by the provider's hand there was only a 52% reduction in aerosols detected at the clinician's head; the absolute concentration was very low because of less aerosols reaching the clinician's head as a result of covering the cough (Fig. 1c). The covered cough resulted in a higher concentration of aerosols at sensors placed lateral to the patient (Supplementary 4). This was likely because aerosols were diverted away from the device's intake but subsequently reached the clinician's head. The effectiveness of the high-flow air extractor was high for larger particles (>1 μm) emitted from the simulated cough, and generally low for small particles (<1 μm) (Supplementary 5a, b). The following is the supplementary data related to this article:eyJraWQiOiI4ZjUxYWNhY2IzYjhiNjNlNzFlYmIzYWFmYTU5NmZmYyIsImFsZyI6IlJTMjU2In0.eyJzdWIiOiI5NjM3NTIyMDVkYTllYzk0ODNlMTJiNjM4YmNhMGNiYiIsImtpZCI6IjhmNTFhY2FjYjNiOGI2M2U3MWViYjNhYWZhNTk2ZmZjIiwiZXhwIjoxNjg4MzY0Njk5fQ.khN1bVz7GnwLDGDL6k63nf7VI5RON9zuyc6-Wp_FIrCF9HgjkfIPJiZFX7UaHyFrDBLR2p190QHEyRrhHZPb74UqfWuGYh9neTl1bykIoYi_FBTMzGCG_b9A3xXZFovNXQGcBWOUOjvqxJrwToizfL5Ea7pbk0F9Or0BwunarqPsF1K5InfKxE87fQTuJCvMc8vRRwuSF0PvY8OV-lPr27Sg8HUFO0f8-PS6SRSiNlROyW5sAUr_g1JNxs6LaFARl8DQz_NUMvckIyIJmSvZAugKnYQrgIomGDoT2VYSJFQp4EPAJM3kpZWg2qjBSlnFsC5JsOYjqVKZNchRObSrTg(mp4, (17.14 MB) Download video eyJraWQiOiI4ZjUxYWNhY2IzYjhiNjNlNzFlYmIzYWFmYTU5NmZmYyIsImFsZyI6IlJTMjU2In0.eyJzdWIiOiI5NjM3NTIyMDVkYTllYzk0ODNlMTJiNjM4YmNhMGNiYiIsImtpZCI6IjhmNTFhY2FjYjNiOGI2M2U3MWViYjNhYWZhNTk2ZmZjIiwiZXhwIjoxNjg4MzY0Njk5fQ.khN1bVz7GnwLDGDL6k63nf7VI5RON9zuyc6-Wp_FIrCF9HgjkfIPJiZFX7UaHyFrDBLR2p190QHEyRrhHZPb74UqfWuGYh9neTl1bykIoYi_FBTMzGCG_b9A3xXZFovNXQGcBWOUOjvqxJrwToizfL5Ea7pbk0F9Or0BwunarqPsF1K5InfKxE87fQTuJCvMc8vRRwuSF0PvY8OV-lPr27Sg8HUFO0f8-PS6SRSiNlROyW5sAUr_g1JNxs6LaFARl8DQz_NUMvckIyIJmSvZAugKnYQrgIomGDoT2VYSJFQp4EPAJM3kpZWg2qjBSlnFsC5JsOYjqVKZNchRObSrTg(mp4, (17.14 MB) Download video Our study shows that a high-air flow extractor is effective in removing aerosols during simulated continuous breathing and a simulated cough. However, simply covering a cough with a gloved hand resulted in the escape of aerosols and subsequent detection at the clinician's head. Removal of aerosols may enhance the safety of healthcare workers and improve operational efficiencies. Currently, a minimal air exchange rate of 15–20 h−1 is recommended for operating room air decontamination. At this rate 18–28 min is required to reduce airborne contaminants by 99%.10Jensen P.A. Lambert L.A. Iademarco M.F. Ridzon R. Guidelines for preventing the transmission of Mycobacterium tuberculosis in health-care settings.MMWR Recomm Rep. 2005; 54 (2005): 1-141PubMed Google Scholar This delay causes workflow inefficiencies and the extractor can be used to accelerate air decontamination. A limitation of this study is the difference between airflows in the test environment and actual operating rooms. Compared with the test environment, operating rooms have higher air exchange rates (15–20 vs 0.75 h−1), which may cause turbulence, interfere with the extractor exhaust plume, and decrease capture efficiency. We have shown that the high-flow air extractor is highly effective at reducing aerosol concentrations at the source. This has potentially large-scale implications for clinical practice and warrants translation into high-risk clinical areas in order to minimise clinician exposure. Furthermore, this technique is consistent with current recommendations from the CDC to augment room air exchanges. Conceptualisation: CM, TE, VC, PF, JF Methodology: CM, TE, VC, PF, JS, SD Visualisation: CM, TE, VC, PF, JS, TL, BD Software: PF, JS, TL, BD Analysis: PF, JS, TL, BD Original draft preparation: CM, TE, VC, PF, JS, SD, TL, BD Review and editing of the manuscript: CM, TE, VC, PF, JS, SD, TL, BD, JF We acknowledge the contributions of Theo Tackey, Rachelle and Jesse Matava. The authors declare no that they have no conflicts of interest. National Sciences and Engineering Research Council of Canada (Grant RGPIN-2014-06698) and the Canada Foundation for Innovation (Grant 32319) to JS.

Poor indoor air quality indicated by elevated indoor CO2 concentrations has been linked with impaired cognitive function, yet current findings of the cognitive impact of CO2 are inconsistent. This review summarizes the results from 37 experimental studies that conducted objective cognitive tests with manipulated CO2 concentrations, either through adding pure CO2 or adjusting ventilation rates (the latter also affects other indoor pollutants). Studies with varied designs suggested that both approaches can affect multiple cognitive functions. In a subset of studies that meet objective criteria for strength and consistency, pure CO2 at a concentration common in indoor environments was only found to affect high-level decision-making measured by the Strategic Management Simulation battery in non-specialized populations, while lower ventilation and accumulation of indoor pollutants, including CO2, could reduce the speed of various functions but leave accuracy unaffected. Major confounding factors include variations in cognitive assessment methods, study designs, individual and populational differences in subjects, and uncertainties in exposure doses. Accordingly, future research is suggested to adopt direct air delivery for precise control of CO2 inhalation, include brain imaging techniques to better understand the underlying mechanisms that link CO2 and cognitive function, and explore the potential interaction between CO2 and other environmental stimuli.

This paper illustrated an optimization method of sensor layout in air duct system, aiming at detecting toxicant before any catastrophic consequence in a bio-terrorist attack. The method was based on genetic algorithm ( GA) with minimal emissions as objective function of the optimization procedure. In this paper, we discussed the impact of the number of sensors, the distance between nodes and the accuracy of sensors on the optimizing objective function. Results of a case study showed that the minimal emission of contaminants decreased significantly as more sensors were set in the ventilation system. However, the decrement provided by every sensor was only about 2％when the number of sensors exceeded three. Thus, the optimized number of sensors in this case was supposed to be three, considering the high cost of each sensor. Moreover, the value of the objective function was reduced by 59.3％with sensor layout optimization applied with three sensors while the effects of the accuracy of sensors and the distance between nodes were not significant. In conclusion, adopting the sensor layout optimized with GA ensured the detection of contaminants with the minimal distribution into rooms, which enabled a security control center to learn the concentration and location of the contaminants and respond quickly.

Once a biochemical pollutant is deliberately released into a ventilation system, the source information including the releasing time and location need to be determined promptly and accurately. Successful inversion algorithms to identify airborne contaminant source within enclosed spaces were deeply developed by previous studies. Such mathematical algorithms inversely simulate airflow and concentration field with numerous intricate inverse matrixes and spend plenty of time in the simulation process. However, tracking airborne pollutant sources within a ventilation system has a higher requirement on computation time due to the rapid spread of contaminants in high-speed airflow, which imposes a great challenge on model abstraction and method selection. This paper mainly focuses on a specific source identification scenario: characterizing an instantaneous pollutant source within a ventilation system by employing a probability-based inverse model. The mathematical model and the solving process of both forward propagation and backward identification of the source are investigated and proposed. To verify the feasibility of the forward model and to validate the applicability of the proposed inverse modeling, a concentration-measured experiment was conducted in a real-built ventilation system. The measured concentrations are used as model inputs to calculate the unconditional and the conditional backward time probability density function (PDF). Then, the impact of sensor errors, sensor number and the change of the operating status of the ventilation system on the results of source identification are discussed. Finally, the basis and limitations of this work are extensively commented.

Adsorption desalination is an emerging method to address the shortage of fresh water. To achieve its energy saving potentials, a renewable low-temperature heat source is the key. This paper focuses on the area optimization of solar collectors in combined solar heating systems that supply heat for adsorption desalination, aiming at achieving the maximum economic benefits during the lifespan of a project. The optimum tilt angle was discussed and the corresponding daily radiation data were calculated with HDKR (Hay, Davies, Klucher, Reindl) model. The area optimization function was proposed with the unit costs of fresh water as the optimization objective. A reference area calculated according to annual solar radiation was employed to describe the optimization results. Then the influences of the price of auxiliary energy sources, the performance ratio of adsorption desalination, and the heat loss of solar heating on the optimization results were studied with an actual adsorption desalination project in Tianjin. It has been found that the optimal area is positively associated with the auxiliary energy price, however approximately inversely proportional to the performance ratio of desalination and the energy efficiency of solar heating. The unit costs of producing fresh water can be reduced up to 20% after collector area optimization when the auxiliary energy is expensive.. Besides, the overall costs of utilizing solar heating to supply heat for adsorption desalination is around 0.03-0.04 CNY/MJ which is lower than conventional energy sources. We also tested the optimization results with an altered precision of radiation data and different meteorological conditions. Findings in this paper proved the advantages of incorporating solar heating in adsorption desalination and provided instructions for designing solar adsorption desalination projects.

Cooking oil fumes contain massive aerial pollutants and may cause unpleasant indoor environments. Exposure to oil fumes often induces uncomfortable feelings and general symptoms. Among them, cough is a common symptom that is associated with diverse respiratory diseases. In this paper, we conducted controlled experiments in a kitchen chamber to evaluate the possibility of using cough as a non-invasive biomarker for oil fumes exposure. The participants were invited to cook typical Chinese dishes under different ventilation conditions. The particulate concentration and participants’ cough frequency were measured during cooking. Results showed that the cough frequency was significantly correlated with the PM2.5 mass concentration in the breathing zone. Besides, the automatic recognition achieved an overall accuracy of 88.4%. Therefore, cough was regarded as a promising biomarker for assessing the COF exposure, which might contribute to better understanding the mechanisms of health risks related to aerial pollutants.

Cooking oil fumes (COF) contain massive particulate matter. Chronic exposure to cooking oil fumes constitutes a health hazard. This study aims to measure the COF exposure level during a typical Chinese domestic cooking process and evaluate whether a short-term exposure at this level entails deleterious cardiopulmonary, inflammatory health effects and oxidative stress.6 young healthy students were recruited to conduct a contrast experiment in a kitchen chamber. Every participant cooked successively three typical Chinese dishes twice a day for two consecutive days, during which the particle mass and number concentration in the breathing zone were monitored. A slot around the pan supplied air at varied rates during cooking, resulting in altered exposure dose. Before the experiment and after their cooking, the levels of biomarkers were measured including 8 biomarkers for lung function, fractional exhaled nitric oxide for respiratory inflammation, blood pressure for cardiovascular risks and three biomarkers in urine for oxidative stress.PM2.5 concentration and particle number concentration in 0.02-6.25 mu m were 10.97 +/- 9.53 mg/m(3) and 23.12 +/- 18.27 10(3)/cm(3) in the breathing zone under normal ventilation condition and might triple under poor ventilation. Health measurements showed that forced vital capacity and vital capacity declined significantly after the fourth cooking process. Peak expiratory flow rose significantly after the third cooking. Meanwhile, forced expiratory flows at 25% of the vital capacity also increased significantly after both the third and fourth cooking. However, a single short-term exposure to COF of around 20 min does not explicitly entail significant health risks. (C) 2017 Elsevier Ltd. All rights reserved.