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.

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.

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.

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).

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.

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.

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.

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.

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.

Reducing heat exposure from personal cooling strategies to green city construction in China's tropical city.

With rapid industrialization and urbanization, the risk of summer heat exposure for urban dwellers has increased. The use of air conditioners (ACs) has become the most common personal cooling strategy, but further increasing fossil fuel consumption. As sustainable and affordable cooling strategies, urban parks can reduce heat exposure and substitute a part of air conditioners use. This study evaluates the heat exposure reduction from personal cooling to urban parks based on satellite images, questionnaire surveys, and network analysis in Liuzhou, one tropical city in China. We found that residents with lower income had a higher risk of heat exposure. Among the respondents, 85 % of residents chose to use ACs to alleviate high temperatures in summer, and 81.8 % among them were willing to access park cooling area (PCA) to cool off instead of using ACs. About one third parks could serve as potential alternatives (with temperatures <28 °C) to air conditioning, reducing carbon emissions by 175.93 tons per day during the hot summer and offsetting 2.5 % of urban fossil fuel carbon emissions. The design of parks should give more consideration to elder people and provide a good cooling platform for various social income groups. Future planning should also focus on accessibility to enable residents to fully utilize the parks. Building parks within 34.10 ha would provide a more efficient use of land. This research guides sustainable, high-quality growth in industrial cities and might contribute to promotion of low-carbon cities and social equity.

Resilient performance in building maintenance: A macro-cognition perspective during sudden breakdowns.

Building maintenance encompasses multiple tightly inter-connected agents (e.g., technicians, occupants, supervisors, and equipment). Variable working conditions and limited resources may affect the safety and sustainability of the activities. Although recent studies have explored how complex systems can perform resilient behavior in facing the complexity of everyday activities, the factors that effectively contribute to resilient performance are still paired with limited empirical evidence. We studied the performance of the maintenance team during sudden breakdowns of air-conditioning devices in a large university campus, using the Functional Resonance Analysis Method (FRAM). A FRAM diagram containing 30 functions was organized including six macro-cognitive functions (expertise, sensemaking, communication, coordination, collaboration, and adaptation/improvisation), examining their role in anticipating, and responding to emergencies, and eight functional units that are directly impacted by disturbances were analyzed in more detail. Results indicate that macro-cognitive functions can greatly impact the functionality of the maintenance team in pursuit of their goals. Moreover, we noted those macro-cognitive functions here analyzed depend on each other to produce resilient performance.

Effect of unidirectional airflow ventilation on surgical site infection in cardiac surgery: environmental impact as a factor in the choice for turbulent mixed air flow.

BACKGROUND: Surgical site infection (SSI) in the form of postoperative deep sternal wound infection (DSWI) after cardiac surgery is a rare, but potentially fatal, complication. In addressing this, the focus is on preventive measures, as most risk factors for SSI are not controllable. Therefore, operating rooms are equipped with heating, ventilation and air conditioning (HVAC) systems to prevent airborne contamination of the wound, either through turbulent mixed air flow (TMA) or unidirectional air flow (UDAF). AIM: To investigate if the risk for SSI after cardiac surgery was decreased after changing from TMA to UDAF. METHODS: This observational retrospective single-centre cohort study collected data from 1288 patients who underwent open heart surgery over 2 years. During the two study periods, institutional SSI preventive measures remained the same, with the exception of the type of HVAC system that was used. FINDINGS: Using multi-variable logistic regression analysis that considered confounding factors (diabetes, obesity, duration of surgery, and re-operation), the hypothesis that TMA is an independent risk factor for SSI was rejected (odds ratio 0.9, 95% confidence interval 0.4-1.8; P>0.05). It was not possible to demonstrate the preventive effect of UDAF on the incidence of SSI in patients undergoing open heart surgery when compared with TMA. CONCLUSION: Based on these results, the use of UDAF in open heart surgery should be weighed against its low cost-effectiveness and negative environmental impact due to high electricity consumption. Reducing energy overuse by utilizing TMA for cardiac surgery can diminish the carbon footprint of operating rooms, and their contribution to climate-related health hazards.

Performance investigation of solar energy-aided compression-based building air conditioning strategies for variable climatic regions.

Decoupling cooling and ventilation tasks with an existing air conditioning methodology are a promising performance-enhancement technology. In this direction, different configurations of a desiccant-integrated independent ventilation element attached to a conventional cooling system are proposed in this study. This work establishes a quantitative comparative performance analysis among the different process air cooling (obtained through desiccant dehumidification) techniques for three different climates, namely, hot-dry, tropical, and Mediterranean. EnergyPlus simulations have been executed on a small-scale office building of 400-m2 area. The building constructional details and other required simulation input parameters follow benchmark standards. As the chemical dehumidification increases, the process air, i.e., supply air temperature that cannot be sent directly to the room, needs to be cooled. Three approaches for process air cooling have been considered: direct expansion (DX) cooling coil, indirect evaporative cooling (IEC), and sensible heat recovery wheel (SHRW). A solar collector assembly with a supporting heating arrangement is coupled with desiccant unit for regeneration. Outdoor air is used for regeneration in the case of the DX cooling coil and IEC, whereas return air is used in the heat recovery wheel case. Annual simulation results reveal that the SHRW-aided case performs superior than DX coil case for the pertinent climatic conditions, with 9.6 to 45.01% of annual energy savings. For the IEC, energy consumption was 1.8 to 18.38% less than that of DX coil. Also, using return air in this best-suited case reduces the net thermal energy requirement for regeneration by 14.63 to 71.65% with respect to DX coil.

Zonal demand-controlled ventilation strategy to minimize infection probability and energy consumption: A coordinated control based on occupant detection.

Due to the outbreak of COVID-19, an increased risk of airborne transmission has been experienced in buildings, particularly in confined public places. The need for ventilation as a means of infection prevention has become more pronounced given that some basic precautions (like wearing masks) are no longer mandatory. However, ventilating the space as a whole (e.g., using a unified ventilation rate) may lead to situations where there is either insufficient or excessive ventilation in localized areas, potentially resulting in localized virus accumulation or large energy consumption. It is of urgent need to investigate real-time control of ventilation systems based on local demands of the occupants to strike a balance between infection risk and energy saving. In this work, a zonal demand-controlled ventilation (ZDCV) strategy was proposed to optimize the ventilation rates in sub-zones. A camera-based occupant detection method was developed to detect occupants (with eight possible locations in sub-zones denoted as 'A' to 'H'). Linear ventilation model (LVM), dimension reduction, and artificial neural network (ANN) were integrated for rapid prediction of pollutant concentrations in sub-zones with the identified occupants and ventilation rates as inputs. Coordinated ventilation effects between sub-zones were optimized to improve infection prevention and energy savings. Results showed that rapid prediction models achieved an average prediction error of 6 ppm for CO2 concentration fields compared with the simulation under different occupant scenarios (i.e., occupant locations at ABH, ABCFH, and ABCDEFH). ZDCV largely reduced the infection risk to 2.8% while improved energy-saving efficiency by 34% compared with the system using constant ventilation rate. This work can contribute to the development of building environmental control systems in terms of pollutant removal, infection prevention, and energy sustainability.

What is the effect of reducing the air change rate on the ventilation effectiveness in ultra-clean operating rooms?

BACKGROUND: The operating room (OR) department is one of the most energy-intensive departments of a hospital. The majority of ORs in the Netherlands have an air-handling installation with an ultra-clean ventilation system. However, not all surgeries require an ultra-clean OR. AIM: To determine the effect of reducing the air change rate on the ventilation effectiveness in ultra-clean ORs. METHODS: Lower air volume ventilation effectiveness (VELv) of conventional ventilation (CV), controlled dilution ventilation (cDV), temperature-controlled airflow (TcAF) and unidirectional airflow (UDAF) systems were evaluated within a 4 × 4 m measuring grid of 1 × 1 m. The VELv was defined as the recovery degree (RD), cleanliness recovery rate (CRR) and air change effectiveness (ACE). FINDINGS: The CV, cDVLv and TcAFLv ventilation systems showed a comparable mixing character in all areas (A, B and AB) when reducing the air change rate to 20/h. Ventilation effectiveness decreased when the air change rate was reduced, with the exception of the ACE. At all points for the UDAF-2Lv and at the centre point (C3) of the TcAFLv, higher RD10Lv and CRRLv were measured when compared with the other examined ventilation systems. CONCLUSIONS: The ventilation effectiveness decreased when an ultra-clean OR with an ultra-clean ventilation air-supply system was switched to an air change rate of 20/h. Reducing the air change rate in the OR from an ultra-clean OR to a generic OR will reduce the recovery degree (RD10) by a factor of 10-100 and the local air change rate (CRR) by between 42% and 81%.

Up in the air: Presence and collection of DNA from air and air conditioner units.

Biological material is routinely collected at crime scenes and from exhibits and is a key type of evidence during criminal investigations. Touch or trace DNA samples from surfaces and objects deemed to have been contacted are frequently collected. However, a person of interest may not leave any traces on contacted surfaces, for example, if wearing gloves. A novel means of sampling human DNA from air offers additional avenues for DNA collection. In the present study, we report on the results of a pilot study into the prevalence and persistence of human DNA in the air. The first aspect of the pilot study investigates air conditioner units that circulate air around a room, by sampling units located in four offices and four houses at different time frames post-cleaning. The second aspect investigates the ability to collect human DNA from the air in rooms, with and without people, for different periods of time and with different types of collection filters. Results of this pilot study show that human DNA can be collected on air conditioner unit surfaces and from the air, with air samples representing the more recent occupation while air conditioner units showing historic use of the room.

Study on infection risk in a negative pressure ward under different fresh airflow patterns based on a radiation air conditioning system.

COVID-19 and other respiratory infectious viruses are highly contagious, and patients need to be treated in negative pressure wards. At present, many negative pressure wards use independent air conditioning equipment, but independent air conditioning equipment has problems such as indoor air circulation flow, condensate water accumulation, and improper filter maintenance, which increase the risk of infection for healthcare workers and patients. The radiation air conditioning system relies on the radiation ceiling to control the indoor temperature and uses new air to control the indoor humidity and air quality. The problems caused by the use of independent air conditioning equipment should be avoided. This paper studies the thermal comfort, contaminant distribution characteristics, contaminant removal efficiency, and accessibility of supply air in a negative pressure ward with a radiation air conditioning system under three airflow patterns. In addition, the negative pressure ward was divided into 12 areas, and the infection probability of healthcare workers in different areas was analyzed. The results show that the application of radiation air conditioning systems in negative pressure wards can ensure the thermal comfort of patients. Stratum ventilation and ceiling-attached jets have similar effects in protecting healthcare workers; both can effectively reduce the contaminant concentrations and the risk of infection of healthcare workers. Ceiling-attached jets decreases the contaminant concentrations by 10.73%, increases the contaminant removal efficiency by 12.50%, and decreases the infection probability of healthcare workers staying indoors for 10 min by 23.18%, compared with downward ventilation.

Thermal sensation prediction model for high-speed train occupants based on skin temperatures and skin wettedness.

Passenger thermal comfort in high-speed train (HST) carriages presents unique challenges due to factors such as extensive operational areas, longer travel durations, larger spaces, and higher passenger capacities. This study aims to propose a new prediction model to better understand and address thermal comfort in HST carriages. The proposed prediction model incorporates skin wettedness, vertical skin temperature difference (ΔTd), and skin temperature as parameters to predict the thermal sensation vote (TSV) of HST passengers. The experiments were conducted with 65 subjects, evenly distributed throughout the HST compartment. Thermal environmental conditions and physiological signals were measured to capture the subjects' thermal responses. The study also investigated regional and overall thermal sensations experienced by the subjects. Results revealed significant regional differences in skin temperature between upper and lower body parts. By analyzing data from 45 subjects, We analyzed the effect of 25 variables on TSV by partial least squares (PLS), from which we singled out 3 key factors. And the optimal multiple regression equation was derived to predict the TSV of HST occupants. Validation with an additional 20 subjects demonstrated a strong linear correlation (0.965) between the actual TSV and the predicted values, confirming the feasibility and accuracy of the developed prediction model. By integrating skin wettedness and ΔTd with skin temperature, the model provides a comprehensive approach to predicting thermal comfort in HST environments. This research contributes to advancing thermal comfort analysis in HST and offers valuable insights for optimizing HST system design and operation to meet passengers' comfort requirements.

Reduction of airborne and surface-borne bacteria in a medical center burn intensive care unit using active, upper-room, germicidal ultraviolet (GUV) disinfection.

OBJECTIVE: To determine the effectiveness of active, upper-room, germicidal ultraviolet (GUV) devices in reducing bacterial contamination in patient rooms in air and on surfaces as a supplement to the central heating, ventilation, and air conditioning (HVAC) air handling unit (AHU) with MERV 14 filters and UV-C disinfection. METHODS: This study was conducted in an academic medical center, burn intensive care unit (BICU), for 4 months in 2022. Room occupancy was monitored and recorded. In total, 402 preinstallation and postinstallation bacterial air and non-high-touch surface samples were obtained from 10 BICU patient rooms. Airborne particle counts were measured in the rooms, and bacterial air samples were obtained from the patient-room supply air vents and outdoor air, before and after the intervention. After preintervention samples were obtained, an active, upper-room, GUV air disinfection system was deployed in each of the patient rooms in the BICU. RESULTS: The average levels of airborne bacteria of 395 CFU/m3 before GUV device installation and 37 CFU/m3 after installation indicated an 89% overall decrease (P < .0001). Levels of surface-borne bacteria were associated with a 69% decrease (P < .0001) after GUV device installation. Outdoor levels of airborne bacteria averaged 341 CFU/m3 in March before installation and 676 CFU/m3 in June after installation, but this increase was not significant (P = .517). CONCLUSIONS: Significant reductions in air and surface contamination occurred in all rooms and areas and were not associated with variations in outdoor air concentrations of bacteria. The significant decrease of surface bacteria is an unexpected benefit associated with in-room GUV air disinfection, which can potentially reduce overall bioburden.