Experimental assessment of low temperature plasma devices for bacterial aerosol inactivation in the air duct of HVAC systems.

In light of growing concerns about indoor air quality and the transmission of pathogens, this study aims to evaluate the effectiveness of low temperature plasma (LTP) devices in inactivating bacterial aerosols in the air duct of HVAC systems, exploring methods to enhance air purification efficiency. This research employed experimental methods to explore the deactivation effects of LTP on common bacteria such as E. coli and Bacillus subtilis, focusing on the role of air parameters such as the airflow rate, relative humidity, and temperature in influencing the device's performance. Notably, the study determined that an operational voltage of 3000 V for the LTP device, combined with conditions of low airflow, low humidity, and high temperature, significantly enhances the inactivation of bacterial aerosols, achieving an 82% inactivation rate at a negative ion concentration of 2.4 × 1011 ions per m3 and a wind speed of 3 m s-1. Despite the generation of ozone and ultraviolet light as by-products, their concentrations were found to be within safe limits for human exposure. In addition, this study identified an effective inactivation range, alongside an optimal arrangement for the airflow direction within ducts, to maximize the sterilization efficiency of the LTP device. Given these promising results, the study advocates for the integration of LTP technology into the air duct of HVAC systems of public buildings to improve air quality and reduce the risk of airborne disease transmission.

Bacterial contamination in the different parts of household air conditioners: a comprehensive evaluation from Chengdu, Southwest China.

Introduction: Air flow driven by air-conditioner has a significant impact on the indoor environment, however, the bacterial contamination conditions in the different parts of air-conditioners have not been fully elucidated. Methods: In this study, we assessed the bacterial pollution in the four parts, including air outlet, filter net, cooling fin and water sink, of ten household air-conditioners quantitatively and qualitatively from Chengdu, southwestern China. Results: The microbial cultivation results showed the large total bacterial counts of 5042.0, 9127.6, 6595.1, and 12296.2 CFU/cm2 in air outlet, filter net, cooling fin, and water sink. Furthermore, the sequencing data showed that these four parts displayed different bacterial characteristics. At the level of genus, Caproiciproducens and Acidipropionibacterium were predominant in air outlet. Bacillus, Acinetobacter, Paracoccus, and Corynebacterium were detected as the characteristic bacteria in filter net. For cooling fin, Rhodococcus, Achromobacter, and Nocardioides were the dominant bacteria. The genera of Methylobacterium-Methylorubrum, Brevibacterium, Stenotrophomonas, and Psychrobacter were identified as the bioindicators in water sink. The bioinformatic analysis on the sequencing data illustrated that the bacteria from air-conditioners were associated with metabolic disturbance. Discussion: This study reveals the distinct bacterial compositions in the different parts of air-conditioner, and provides new clues for the non-negligible bacterial pollution in this common appliance from Chinese households.

Decomposition of air conditioning electricity consumption considering the dependence between the temperature and electricity consumption.

With the continuous increase in air conditioning installations, the proportion of air conditioning electricity consumption to total electricity consumption is growing. Research on the decomposition of air conditioning electricity consumption is of great significance for assessing electricity usage, formulating electricity scheduling plans, and ensuring the stable operation of the power grid. Currently, typical day selection strategies for the decomposition of air conditioning electricity consumption often overlook the corresponding relationship between typical daily electricity consumption and temperature. Therefore, this paper proposes an air conditioning electricity consumption decomposition method based on the dependence between temperature and electricity consumption. This method filters typical days based on Copula-based dependence indicators and equiprobable ellipses, determines the baseline electricity consumption curve through model selection voting, and ultimately calculates the air conditioning electricity consumption. The effectiveness of the proposed method is validated by applying it to electricity consumption data in Fuzhou from 2019 to 2022.

Exploring Synergistic GHG Emissions Mitigation Potential and Costs of Room Air Conditioners.

This study explores the potential of synergistically reducing direct (refrigerant) and indirect (electricity) greenhouse gas (GHG) emissions in the global room air conditioning (RAC) sector, based on 80% of global RAC manufactured in China. Three scenarios are evaluated: Business-as-usual (BAU) based on maintaining refrigerant and energy efficiency levels from 2021 China RAC sales shares, Kigali Amendment compliant with 10% energy efficiency improvement by 2025 (KAE), and accelerated refrigerant transition and energy efficiency improvement (ATE). Each scenario considers the costs of refrigerant and efficiency measures for export market groups based on Kigali Amendment classifications. BAU predicts around 1 Gt CO2-eq average annual global RAC emissions (2022-2060). Cumulative emission reductions in China's RAC manufacturing under KAE and ATE are 12.2 and 17.2 Gt CO2-eq A5II and A5I (except China), presenting cost-effective abatement measures, with average costs of -$51.4 and -$68.8/t CO2-eq in KAE and ATE. Cumulative average abatement costs are around $18 and $4/t CO2-eq globally. KAE and ATE scenarios would avoid surface temperature rises of 0.023 (±0.002) °C and 0.027 (±0.003) °C, respectively, versus BAU. Collaboration between China and importing countries is urged to enhance energy efficiency in RACs traded, ensuring sustainable mitigation aligned with the Kigali Amendment.

Decomposition of air conditioning electricity consumption based on effective duration.

As the share of air conditioning electricity consumption within total grid electricity consumption grows, the decomposition of such consumption becomes increasingly crucial for assessing electricity usage patterns, devising consumption scheduling strategies, and maintaining the stability of the power grid. Although there is a strong correlation between apparent temperature and air conditioning electricity consumption, the literature currently available seldom explores the impact of apparent temperature on this consumption. Moreover, there is a scarcity of effective assessment indices to evaluate the efficacy of air conditioning electricity consumption breakdown. This study introduces a method for decomposing electricity consumption from air conditioning units, utilizing effective duration as a basis to tackle these issues. By employing an apparent temperature model as a constraint, this approach identifies the effective operating time of air conditioning and constructs a constrained convex optimization problem to estimate air conditioning power usage. Additionally, a novel evaluation index for the effectiveness of air conditioning electricity consumption decomposition is proposed, which includes penalties for negative decomposed consumption, alongside the traditional consistency index. Comparative experiments are conducted using real electricity consumption data from Fujian Province. Empirical results indicate that the methodology for air conditioning electricity consumption decomposition presented in this paper aligns more closely with actual conditions. Furthermore, the evaluation metrics introduced for the decomposition of air conditioning electricity consumption are adept at precisely gauging the quality of the air conditioning electricity consumption data.

A CFD study on the effect of portable air cleaner placement on airborne infection control in a classroom.

The utilization of portable air cleaners (PACs) is a recommended supplemental approach to help remove airborne pathogens and mitigate disease transmission in learning environments. To improve PAC effectiveness, science-based information is needed to optimize their implementation strategies such as the deployment location, height, and number of PACs. In this study, we developed a Computational Fluid Dynamics (CFD) model to assess how PACs perform in occupied classrooms equipped with displacement and mixing ventilation systems. The results show that PACs with a flow rate of 2.6 h-1 reduce the mean aerosol intake of all students by up to 66%. A key benefit of using PACs is to facilitate air mixing and movement in indoor environments with inadequate ventilation, thereby effectively reducing high aerosol concentrations near the infector. Furthermore, our results highlight the impact of PAC location on its performance. PACs achieve the best effectiveness when placed closed to the infector (within a distance <3 m). In the absence of knowing who is infected, deploying a PAC at the center of the room is recommended. Moreover, adjusting PAC flow discharge height to the breathing height of occupants (e.g., 0.9-1.2 m for seated people) can enhance their effectiveness in spaces with poor air mixing.

Assessment of monitoring approaches to control Legionella pneumophila within a complex cooling tower system.

Precise and rapid methods are needed to improve monitoring approaches of L. pneumophila (Lp) in cooling towers (CTs) to allow timely operational adjustments and prevent outbreaks. The performance of liquid culture (ASTM D8429-21) and an online qPCR device were first compared to conventional filter plate culture (ISO 11731-2017), qPCR and semi-automated qPCR at three spiked concentrations of Lp (serogroup 1) validated by flow cytometry (total/viable cell count). The most accurate was qPCR, followed by liquid culture, online and semi-automated qPCR, and lastly, by a significant margin, filter plate culture. An industrial CT system was monitored using liquid and direct plate culture by the facility, qPCR and online qPCR. Direct plate and liquid culture results agreed at regulatory sampling point, supporting the use of the faster liquid culture for monitoring culturable Lp. During initial operation, qPCR and online qPCR results were within one log of culture at the primary pump before deviating after first cleaning. Other points revealed high spatial variability of Lp. The secondary pumps and chiller had the most positivity and highest concentrations by both qPCR and liquid culture compared to the basin and infeed tank. Altogether, this suggests that results from monthly compliance sampling at a single location with plate culture are not representative of Lp risks in this CT due to the high temporal and spatial variability. The primary pump, rather than the CT basin, should be designated for sampling, as it is representative of the health risk. An annual multi point survey of the system should be conducted to identify and target Lp hot spots. Generally, a combination of liquid culture for compliance and frequent qPCR for process control provides a more agile and robust monitoring scheme than plate culture alone, enabling early treatment adjustments, due to lower limit of detection (LOD) and turnover time.

Evaluating the effect of passive cooling strategies in school buildings on children's well-being in Barcelona: A quasi-experimental, mixed methods study.

Passive cooling strategies were implemented in 11 school buildings in Barcelona within a pilot project to improve thermal conditions. The present study aimed to evaluate the intervention's impact on students' comfort and well-being at school. A quasi-experimental pre-post study based on mixed methods was conducted. Quantitative data were collected through self-reported questionnaires administrated to sixth-grade students in 21 schools (11 in an intervention group, IG, and 10 in a comparison group, CG). The authors measured changes in satisfaction with indoor temperature and indoor air quality (IAQ), the presence of bothering factors (temperature too high, temperature too low, unpleasant odours, and lighting problems), and students' well-being and performance. Difference-in-difference analysis was conducted to evaluate differences between the IG and CG in pre-post changes. Qualitative data were collected through photovoice-based sessions (59 sixth grade students) and interviews (7 teachers) in the IG. A thematic content analysis identified three main categories: changes in perceptions of indoor environmental conditions, indoor environment-related health and well-being, and indoor environment and their reported impact on learning. Quantitative findings show positive changes among the IG in perceived indoor temperature, air quality, and well-being at school, while suggest no significant changes in perceptions of temperature too low, lighting problems, and students' performance, in relation to the CG. Compared to the CG, students in the IG perceiving temperature too high significantly decreased among girls, while unpleasant odours decreased only among boys. In the qualitative assessment, participants reported that school transformations improved their indoor thermal and visual comfort, IAQ, and unpleasant odours. Participants also reported a reduction of fatigue, stress, irritability, and stifling sensation, as well as enhanced concentration. This study highlights the benefits of school passive design for student's comfort and well-being in Mediterranean climates and suggests the need to extend these interventions to other school buildings in similar contexts.

Moderating AC Usage Can Reduce Thermal Disparity between Indoor and Outdoor Environments.

In the context of escalating urban heat events due to climate change, air conditioning (AC) has become a critical factor in maintaining indoor thermal comfort. Yet the usage of AC can also exacerbate outdoor heat stress and burden the electricity system, and there is little scientific knowledge regarding how to balance these conflicting goals. To address this issue, we established a coupled modeling approach, integrating the Weather Research and Forecasting model with the building energy model (WRF_BEP + BEM), and designed multiple AC usage scenarios. We selected Chongqing, China's fourth-largest megacity, as our study area due to its significant socioeconomic importance, the severity of extreme heat events, and the uniqueness of its energy infrastructure. Our analysis reveals that AC systems can substantially reduce indoor temperatures by up to 18 °C; however, it also identifies substantial nighttime warming (2-2.5 °C) and a decline in thermal comfort. Particularly for high-density neighborhoods, when we increase 2 °C indoors, the outdoor temperature can be alleviated by up to 1 °C. Besides, despite the limited capacity to regulate peak electricity demand, we identified that reducing the spatial cooled fraction, increasing targeted indoor temperature by 2 °C, and implementing temporal AC schedules can effectively lower energy consumption in high-density neighborhoods, especially the reduction of spatial cooled fraction (up to 50%). Considering the substantial demand for cooling energy, it is imperative to carefully assess the adequacy and continuity of backup energy sources. The study underscores the urgency of reassessing energy resilience and advocates for addressing the thermal equity between indoor and outdoor environments, contributing to the development of a sustainable and just urban climate strategy in an era of intensifying heat events.

Automated cooling tower detection through deep learning for Legionnaires' disease outbreak investigations: a model development and validation study.

BACKGROUND: Cooling towers containing Legionella spp are a high-risk source of Legionnaires' disease outbreaks. Manually locating cooling towers from aerial imagery during outbreak investigations requires expertise, is labour intensive, and can be prone to errors. We aimed to train a deep learning computer vision model to automatically detect cooling towers that are aerially visible. METHODS: Between Jan 1 and 31, 2021, we extracted satellite view images of Philadelphia (PN, USA) and New York state (NY, USA) from Google Maps and annotated cooling towers to create training datasets. We augmented training data with synthetic data and model-assisted labelling of additional cities. Using 2051 images containing 7292 cooling towers, we trained a two-stage model using YOLOv5, a model that detects objects in images, and EfficientNet-b5, a model that classifies images. We assessed the primary outcomes of sensitivity and positive predictive value (PPV) of the model against manual labelling on test datasets of 548 images, including from two cities not seen in training (Boston [MA, USA] and Athens [GA, USA]). We compared the search speed of the model with that of manual searching by four epidemiologists. FINDINGS: The model identified visible cooling towers with 95·1% sensitivity (95% CI 94·0-96·1) and a PPV of 90·1% (95% CI 90·0-90·2) in New York City and Philadelphia. In Boston, sensitivity was 91·6% (89·2-93·7) and PPV was 80·8% (80·5-81·2). In Athens, sensitivity was 86·9% (75·8-94·2) and PPV was 85·5% (84·2-86·7). For an area of New York City encompassing 45 blocks (0·26 square miles), the model searched more than 600 times faster (7·6 s; 351 potential cooling towers identified) than did human investigators (mean 83·75 min [SD 29·5]; mean 310·8 cooling towers [42·2]). INTERPRETATION: The model could be used to accelerate investigation and source control during outbreaks of Legionnaires' disease through the identification of cooling towers from aerial imagery, potentially preventing additional disease spread. The model has already been used by public health teams for outbreak investigations and to initialise cooling tower registries, which are considered best practice for preventing and responding to outbreaks of Legionnaires' disease. FUNDING: None.

Clearing the Air: Acute Invasive Fungal Rhinosinusitis in Hematologic Cancer Patients.

OBJECTIVES: Air quality has been shown to impact the rates of fungal infection of the airway, causing diseases such as acute invasive fungal rhinosinusitis (AIFRS), particularly in immunocompromised patients. We theorize that patients with hematologic malignancies in units with aging air handling units (AHUs) have a higher attack rate of AIFRS. METHODS: Retrospective chart review identified patients with hematologic malignancy and AIFRS in two distinct and equal time periods between 2013 and 2022, representing the presence of aging AHUs and new AHUs, respectively. Cubic feet per minute (CFM) air flows, AIFRS attack rates, and clinical data were compared between the two groups and statistical analyses performed. RESULTS: The older AHUs produce air flow of 27,610 CFM and the newer AHUs produce air flow of 80,000 CFM. There were 18 patients with air supplied by older AHUs and 7 patients with air supplied by new AHUs who developed AIFRS. There was a significantly higher AIFRS attack rate for patients supplied by the older AHUs compared with patients supplied by newer AHUs (p = 0.033). The patients supplied by the older AHUs tended to be younger. The white blood cell counts, absolute neutrophil counts, and the mean time to diagnosis did not differ between the two groups. CONCLUSIONS: To our knowledge, this is the first study to examine AIFRS in immunocompromised patients' inpatient environment. Further research should explore whether higher CFM AHUs can decrease this disease among our most vulnerable patients. LEVEL OF EVIDENCE: 3 Laryngoscope, 134:4466-4470, 2024.

The abundance and pathogenicity of microbes in automobile air conditioning filters across the typical cities of China and Europe.

Bioaerosols are widely distributed in urban air and can be transmitted across the atmosphere, biosphere, and anthroposphere, resulting in infectious diseases. Automobile air conditioning (AAC) filters can trap airborne microbes. In this study, AAC filters were used to investigate the abundance and pathogenicity of airborne microorganisms in typical Chinese and European cities. Culturable bacteria and fungi concentrations were determined using microbial culturing. High-throughput sequencing was employed to analyze microbial community structures. The levels of culturable bioaerosols in Chinese and European cities exhibited disparities (Analysis of Variance, P < 0.01). The most dominant pathogenic bacteria and fungi were similar in Chinese (Mycobacterium: 18.2-18.9 %; Cladosporium: 23.0-30.2 %) and European cities (Mycobacterium: 15.4-37.7 %; Cladosporium: 18.1-29.3 %). Bartonella, Bordetella, Alternaria, and Aspergillus were also widely identified. BugBase analysis showed that microbiomes in China exhibited higher abundances of mobile genetic elements (MGEs) and biofilm formation capacity than those in Europe, indicating higher health risks. Through co-occurrence network analysis, heavy metals such as zinc were found to correlate with microorganism abundance; most bacteria were inversely associated, while fungi exhibited greater tolerance, indicating that heavy metals affect the growth and reproduction of bioaerosol microorganisms. This study elucidates the influence of social and environmental factors on shaping microbial community structures, offering practical insights for preventing and controlling regional bioaerosol pollution.

Enterovirga aerilata sp. nov. and Knoellia koreensis sp. nov., isolated from an automobile air conditioning system.

Two strictly aerobic and rod-shaped bacteria, labelled as DB1703T and DB2414ST, were obtained from an automobile air conditioning system. Strain DB1703T was Gram-stain-negative, while strain DB2414ST was Gram-stain-positive. Both strains were catalase-positive and oxidase-negative. Strains DB1703T and DB2414ST were able to grow at 18-42 °C. Strain DB1703T grew within a NaCl range of 0-3 % and a pH range of 6.0-8.0; while strain DB2414ST grew at 0-1 % and pH 6.5-8.5. The phylogenetic and 16S rRNA gene sequence analysis indicated that strains DB1703T and DB2414ST belonged to the genera Enterovirga and Knoellia, respectively. Strain DB1703T showed the closest phylogenetic similarity to Enterovirga rhinocerotis YIM 100770T (94.8 %), whereas strain DB2414ST was most closely related to Knoellia remsis ATCC BAA-1496T (97.7 %). The genome sizes of strains DB1703T and DB2414ST were 4 652 148 and 4 282 418 bp, respectively, with DNA G+C contents of 68.8 and 70.5 mol%, respectively. Chemotaxonomic data showed Q-10 as the sole ubiquinone in DB1703T and ML-8 (H4) in DB2414ST. The predominant cellular fatty acid in DB1703T was summed feature 8 (C18 : 1 ω7c and/or C18 : 1 ω6c), whereas iso-C16 : 0, C17 : 1 ω8c, and iso-C15 : 0 were dominant in DB2414ST. Overall, the polyphasic taxonomic comparisons showed that strains DB1703T and DB2414ST were distinct from their closest taxa and represent novel species within the genera Enterovirga and Knoellia, respectively. Accordingly, we propose the names Enterovirga aerilata sp. nov., with the type strain DB1703T (=KCTC 72724T=NBRC 114759T), and Knoellia koreensis sp. nov., with the type strain DB2414ST (=KCTC 49355T=NBRC 114620T).

Passive and low-energy strategies to improve sleep thermal comfort and energy resilience during heat waves and cold snaps.

Sleep is a pillar of human health and wellbeing. In high- and middle-income countries, there is a great reliance on heating, ventilation, and air conditioning systems (HVAC) to control the interior thermal environment in the bedroom. However, these systems are expensive to buy, maintain, and operate while being energy and environmentally intensive-problems that may increase due to climate change. Easily-accessible passive and low-energy strategies, such as fans and electrical heated blankets, address these challenges but their comparative effectiveness for providing comfort in sleep environments has not been studied. We used a thermal manikin to experimentally show that many passive and low-energy strategies are highly effective in supplementing or replacing HVAC systems during sleep. Using passive strategies in combination with low-energy strategies that elevate air movement like ceiling or pedestal fans enhances the cooling effect by three times compared to using fans alone. We extrapolated our experimental findings to estimate heating and cooling effects in two historical case studies: the 2015 Pakistan heat wave and the 2021 Texas power crisis. Passive and low-energy strategies reduced sleep-time heat or cold exposure by 69-91%. The low-energy strategies we tested require one to two orders of magnitude less energy than HVAC systems, and the passive strategies require no energy input. These strategies can also help reduce peak load surges and total energy demand in extreme temperature events. This reduces the need for utility load shedding, which can put individuals at risk of hazardous heat or cold exposure. Our results may serve as a starting point for evidence-based public health guidelines on how individuals can sleep better during heat waves and cold snaps without relying on HVAC.

Effects of decongestion on nasal cavity air conditioning efficiency: a CFD cohort study.

Decongestion reduces blood flow in the nasal turbinates, enlarging the airway lumen. Although the enlarged airspace reduces the trans-nasal inspiratory pressure drop, symptoms of nasal obstruction may relate to nasal cavity air-conditioning. Thus, it is necessary to quantify the efficiency of nasal cavity conditioning of the inhaled air. This study quantifies both overall and regional nasal air-conditioning in a cohort of 10 healthy subjects using computational fluid dynamics simulations before and after nasal decongestion. The 3D virtual geometry model was segmented from magnetic resonance images (MRI). Each subject was under two MRI acquisitions before and after the decongestion condition. The effects of decongestion on nasal cavity air conditioning efficiency were modelled at two inspiratory flowrates: 15 and 30 L min-1 to represent restful and light exercise conditions. Results show inhaled air was both heated and humidified up to 90% of alveolar conditions at the posterior septum. The air-conditioning efficiency of the nasal cavity remained nearly constant between nostril and posterior septum but dropped significantly after posterior septum. In summary, nasal cavity decongestion not only reduces inhaled air added heat by 23% and added moisture content by 19%, but also reduces the air-conditioning efficiency by 35% on average.

Comparison of thermal comfort between different heating systems and adaptation to different indoor climates in winter.

Individual heating systems, such as the air-source heat pump (ASHP) air-conditioner or floor heating (FH), are usually used by people living in the hot summer and cold winter (HSCW) zone of China to heat indoor climates in the winter. However, little research has been conducted in the HSCW zone on the thermal comfort difference between indoor climates heated by ASHP air-conditioners and those heated by floor heating, as well as how occupants adapt to different indoor climates. We conducted a comparative field experiment in ASHP-heated and FH-heated apartments in Nanjing to investigate how different types of heating systems influence the thermal sensation of occupants, and we conducted a comparative field experiment in ASHP-heated office buildings and naturally ventilated teaching buildings in Shanghai to investigate how occupants adapt to different indoor thermal environments. Indoor environmental parameters and body surface temperatures were measured using instruments, and occupants' thermal sensation, activity level, and clothing were evaluated using the questionnaire. The results show that floor heating improves thermal comfort by raising foot temperature compared to the ASHP air-conditioner, and that occupants become acclimatized to different indoor climates by adjusting neutral operative temperature. According to the findings, there is no need to overheat the indoor environment in the HSCW zone because occupants can adapt to their experienced thermal environment and it is critical to maintain warm foot temperature in the cool/cold indoor environment.

Enhancing thermal comfort prediction in high-speed trains through machine learning and physiological signals integration.

Heating, Ventilation, and Air Conditioning (HVAC) systems in high-speed trains (HST) are responsible for consuming approximately 70% of non-operational energy sources, yet they frequently fail to ensure provide adequate thermal comfort for the majority of passengers. Recent advancements in portable wearable sensors have opened up new possibilities for real-time detection of occupant thermal comfort status and timely feedback to the HVAC system. However, since occupant thermal comfort is subjective and cannot be directly measured, it is generally inferred from thermal environment parameters or physiological signals of occupants within the HST compartment. This paper presents a field test conducted to assess the thermal comfort of occupants within HST compartments. Leveraging physiological signals, including skin temperature, galvanic skin reaction, heart rate, and ambient temperature, we propose a Predicted Thermal Comfort (PTC) model for HST cabin occupants and establish an intelligent regulation model for the HVAC system. Nine input factors, comprising physiological signals, individual physiological characteristics, compartment seating, and ambient temperature, were formulated for the PTS model. In order to obtain an efficient and accurate PTC prediction model for HST cabin occupants, we compared the accuracy of different subsets of features trained by Machine Learning (ML) models of Random Forest, Decision Tree, Vector Machine and K-neighbourhood. We divided all the predicted feature values into four subsets, and did hyperparameter optimisation for each ML model. The HST compartment occupant PTC prediction model trained by Random Forest model obtained 90.4% Accuracy (F1 macro = 0.889). Subsequent sensitivity analyses of the best predictive models were then performed using SHapley Additive explanation (SHAP) and data-based sensitivity analysis (DSA) methods. The development of a more accurate and operationally efficient thermal comfort prediction model for HST occupants allows for precise and detailed feedback to the HVAC system. Consequently, the HVAC system can make the most appropriate and effective air supply adjustments, leading to improved satisfaction rates for HST occupant thermal comfort and the avoidance of energy wastage caused by inaccurate and untimely predictive feedback.

Characteristics, sources, and improvement measures regarding fine particulate matter in subway station office and the VAC system.

In order to study the characteristics and transport path of PM2.5 in the subway station office, three different types of typical subway station were selected for sampling and analysis. The PM2.5 of mechanical air duct and VAC (ventilation and air conditioning system) were tested simultaneously. Both the particulate matter in the station office and VAC exhibit highly enriched characteristics of metal elements. The mass balance equation with elemental Fe as the tracer element is established firstly in subway station, and the transport path of PM2.5 in the work area is revealed: if the work area is obviously under positive pressure compared to the station hall, metal-enriched fine particles come from the VAC system; otherwise, the particles come both from the VAC system and air infiltration from the station hall. The contribution of air infiltration to metal-enriched fine particles can reach 50%. Finally, following an investigation into the source of fine particles in the office, the measures to improve air quality are proposed and validated.

The air conditioning in the nose of mammals depends on their mass and on their maximal running speed.

The nose of the mammals is responsible for filtering, humidifying, and heating the air before entering the lower respiratory tract. This conditioning avoids, notably, dehydration of the bronchial and alveolar mucosa. However, since this conditioning is not perfect, exercising in cold air can induce lung inflammation, both for human and non-human mammals. This work aims to compare the air conditioning in the noses of various mammals during inspiration. We build our study on computational fluid dynamics simulations of the heat exchanges in the lumen of the upper respiratory tract of these mammals. These simulations show that the efficiency of the air conditioning in the nose during inspiration does not relate only to the mass m of the mammal but also to its maximal running speed v. More precisely, the results allow establishing a scaling law relating the efficiency of air conditioning in the nose of mammals to the ratio v / log 10 ( m ) . The simulations also correlate the resistance to the flow in the nose to the efficiency of this air conditioning. The obtained scaling law allows predicting the air temperature at the top of the trachea during inspiration for nasal-breathing mammals, and thus notably for humans of various ages.

Optimization of air quality and energy consumption in the cabin of electric vehicles using system simulation.

In electric vehicles, the Heating, Ventilation and Air-Conditioning (HVAC) function is often performed by a heat pump. Heating and cooling the cabin air drains energy directly from the vehicle's battery. In addition, these vehicles may operate in environments with high level of air pollution. In the cabin, passengers are confined to a small space where particles and harmful gases can accumulate. In addition, the ventilation system must also handle the air which does not enter the cabin through blower operation. This "infiltration" is a function of the vehicle speed and allows pollution to enter the cabin without being filtered or thermally treated. The objective of the study is to optimize the competing goals of the HVAC system: achieving the best air quality while maintaining good thermal comfort, at minimum energy costs. A system simulation tool is calibrated to represent the heating and cooling of an electric car. With this model, the influence of key factors is evaluated. Depending on ambient conditions and other parameters (number of occupants, vehicle speed, etc.), the blower flow rate and recirculation ratio can be adjusted to reach the objectives. The management of the proportion of fresh and recirculated air allows to regulate the humidity and carbon dioxide levels. Optimum controls are proposed as good trade-offs to reduce the power consumption, while maintaining a safe and comfortable environment for occupants. Compared to the full fresh air mode, the driving range gains are estimated in cold (-15 °C) and hot (30 °C) scenarios at 9 and 26 km respectively.