With increasing demands for professional protection and pharmaceutical quality during drug compounding, pharmacy intravenous admixture services (PIVAS) have rapidly become widespread in Chinese hospitals. However, the diffusion mechanisms of particulate contaminants within these high-ventilation cleanrooms used for large-scale compounding of antineoplastic drugs (ADs) remain insufficiently characterized, raising concerns about potential occupational exposure risks. This study analyzed the effects of static occupant disturbances, the exhaust slot structure and operating modes of the biological safety cabinet (BSC) on indoor airflow characteristics and particle diffusion pathways in scenarios involving multiple pollution sources. A numerical model based on a compounding room in a Chinese hospital was constructed and experimentally validated. The fully transient Euler-Lagrange approach was employed to analyze flow field structures and particle distributions under different scenarios. Quantitative evaluations were conducted using air age, air change efficiency, concentration distribution index, and contamination removal index. The results showed that: (1) Occupants are the primary disturbance source disrupting indoor air distribution and inducing lateral airflow migration, making regular dynamic inspections necessary; (2) Inwardly inclined BSC exhaust slots can significantly reduce contaminant concentrations in the breathing zone; (3) Increasing BSC exhaust airflow enhances contaminant removal while accelerating particle diffusion within the room; (4) Room entrances/exits and areas under BSCs represent high-risk zones for particle retention and accumulation. These findings will provide valuable reference for inspecting, designing, operating, and disinfecting similar medication compounding rooms.

Controlling operation-stage carbon emissions (CE) from transport buildings is crucial for China's dual-carbon goals and the ecological security of the Qinghai-Tibet Plateau (QTP), and the sustainable development of plateau transport infrastructure. For plateau railway passenger stations (RPS), limited monitoring and distinctive high-altitude, cold-climate operations make daily CE prediction difficult with conventional measurement- or simulation-based methods. This study develops a machine-learning approach based on a Monte Carlo synthetic database and derives engineering-standard formulas for direct use. Building scale, meteorology and passenger flow volume (PFV) were compiled for 12 representative RPS, and a large synthetic database of daily carbon emission was generated under multiple distribution constraints. With daily mean temperature, heating degree days, altitude, station floor area and PFV as inputs, four models were trained and assessed using mean absolute error, root mean square error, mean absolute percentage error (MAPE) and R-2. The results show that random forest (RF) performed best, achieving similar to 6% MAPE and R-2 > 0.99 on the test set, and markedly lower errors than multivariable linear regression. Interpretation of RF via feature importance and partial dependence shows that floor area, altitude and PFV dominate emissions and exhibit nonlinear response patterns. To improve transparency and transferability, ridge regression was used to fit a linear surrogate to RF predictions, producing engineering-standard formulas for daily and annual operation-stage CE. The formulas retain most predictive accuracy while requiring only readily obtainable variables, enabling rapid estimation and scenario analysis for cold, high-altitude RPS. The proposed workflow provides a replicable pathway for operational CE assessment in data-scarce regions and supports low-carbon planning, design and operation of RPS on the QTP, thereby contributing to more sustainable infrastructure development in high-altitude regions.

While extensive thermal comfort research exists for severe cold and hot-humid climates, studies focusing on moderate climate zones remain scarce and fragmented. To address this gap, this study synthesizes one of the most temporally extensive and typologically comprehensive field investigations (2006–2022) in such zones, with a primary focus on Kunming. By analyzing 7 289 subjective questionnaires across diverse building types (residential, office, educational, healthcare), this study quantifies the seasonal thermal neutral temperatures, revealing a mean of 23.3 ℃ in summer (range: 21.6–25.0 ℃) and 18.1 ℃ in winter (range: 15.6–21.4 ℃). A key finding is the significant disparity between the winter neutral temperature and the measured average indoor temperature (14.5 ℃), highlighting a critical comfort deficit during colder months. Furthermore, this study pioneers the explicit inclusion of vulnerable groups and explores synergies between comfort attainment and energy efficiency. Based on these findings, we propose actionable indoor temperature setpoints of 23.0–25.0 ℃ for summer and 17.0–19.0 ℃ for winter, alongside tailored architectural design strategies. This study provides a robust, data-driven foundation for refining building standards and optimizing energy-efficient design in understudied moderate climate zones.

Operational carbon emissions of buildings account for more than 25% of global carbon emissions and, generally, over 50% of the total carbon emissions across the whole life cycle of a building. The evaluation and management of carbon emission levels during the operational phase of buildings are at present important tasks for China’s construction industry administration departments. This paper analyzes the indicators for evaluating the operational carbon emission levels of buildings and the content of carbon emission calculations, and introduces a specific operation mode for characterizing building energy consumption by the equivalent electricity method from the perspective of building energy consumption statistics. A calculation method for the carbon emission intensity per unit energy consumption of buildings based on the equivalent electricity method is constructed, and its validity is verified through calculations on 15 actual projects. The results show that the variances in carbon emission intensity per unit energy consumption index based on the equivalent electricity method are 0.03, 0.04 and 0.03 for residential, office and venue buildings, respectively, which are far lower than those of the carbon emission intensity per unit building area index (72.79, 123.33 and 153.35) and close to those of the building energy saving rate index (0.02, 0.01 and 0.02). Compared with the building energy saving rate and carbon emission intensity per unit building area, this index can better characterize the degree of building decarbonization and exhibits good evaluation stability across buildings of different functional types. Combined with the building energy consumption quota index, it is conducive to promoting the transformation of the construction sector from dual control of energy consumption to dual control of carbon emissions.

In response to the continuous refinement of distributed renewable energy policies, the optimal energy system configuration for small-scale nearly zero-energy office buildings remains uncertain. This study investigates a representative building in Qingdao, China, and evaluates the applicability of photovoltaic (PV) and their coupling with energy storage technologies, including electrochemical and hydrogen energy storage, from the perspective of building owners under varying revenue-cost scenarios. To this end, a total of 20 representative scenarios were constructed and a coupled TRNSYS–NSGA-II framework was employed to perform multi-objective optimization. The optimal system configurations were subsequently identified through economic feasibility screening and the ideal point method. The findings indicate that policy-induced fluctuations in revenue exert variable impacts on the optimal solutions. Under conditions of low or high cost, the influence is relatively limited. However, as system costs approach the local baseline level, revenue variations significantly reshape the boundaries of system decisions. Moreover, PV coupled with electrochemical storage dominates in most scenarios, and hydrogen energy system has yet to demonstrate realistically competitive application potential, which is dependent on cost reductions of both PV and hydrogen-related equipment.

Rural street spaces serve as primary venues for communal activities, yet emotion-based design in these spaces remains underexplored. This study delineates three typical scales of rural street spaces in China northern plains region, utilizing eye-tracking technology, investigates the constituent elements and materials of various optimized design schemes, analyzing people's emotional perceptions of different elements and materials. The results indicate that: (1) narrower streets evoke a greater sense of security among individuals; (2) an increased variety and quantity of paving materials, landscape flower beds, seating areas, and public facilities heighten people's visual interest, enhancing the spatial publicness and safety; (3) higher coverage of green landscape relaxes visual perceptions, leading individuals to linger and dwell in the space. Consequently, through judicious design of scale, constituent elements, and materials, rural street spaces can be effectively imbued with emotional expressions, thereby elevating the spatial quality of rural street spaces to meet people's emotional needs.

Based on the investigation of residential buildings in the moderate climate zone of China, the thermal comfort demand and building energy consumption were analyzed. The results show that about 50.48% of people found it comfortable in summer, and approximately 13.33% felt it was uncomfortable. An open window for ventilation was the main way to adjust room temperature, which was also the reason that the electricity cost was low in summer. Most people thought it was cold in winter, and about 21.9% felt the room temperature was comfortable. For the regulation of room temperature, mainly electric heating equipment is used as auxiliary heating, including electric oil heater, small sun heater, and fan heater. However, using the air conditioning and floor heating to adjust room temperature was less. In terms of energy consumption, domestic hot water throughout the year was mainly provided by electric water heaters and gas water heaters, and the usage proportion of solar water heaters was only 26.67%. According to actual research data, energy consumption in winter was significantly higher than that of in summer, especially for heating and hot water supply. In terms of economic analysis, electricity consumption in summer was mostly in the range of 92 degrees-445 degrees and gas consumption was mostly between 0 and 34 m(3). However, the electricity consumption and gas consumption in winter were higher than in summer. It is hoped that the results of the research can provide some reference for the energy-saving renovation of residential buildings in the moderate zone.

Working in hyperthermal environments can lead to heat-related illnesses. Evaluating and predicting high-temperature environments can effectively reduce heat risks and hazards. However, there is still a lack of corresponding high-temperature environment assessment methods and indicators in existing research. Moreover, traditional evaluation indicators and prediction methods have shortcomings in objectivity, accuracy, and practicality. To fill these gaps, a climate chamber was constructed to simulate different environmental conditions, and human labor experiments with 98 subjects were conducted. The ambient temperatures were set to 34 °C, 36 °C, 38 °C, and 40 °C, and the relative humidity was set to 60%, 70%, 80%, and 90%, respectively. During the experiments, the subjects’ oral temperatures, heart rates, skin temperatures, and subjective perceptions were recorded. Based on the obtained parameters of the subjects, two principal components with an explained variance of 92.131% were extracted by principal component analysis, and with the determination of weightings, a comprehensive evaluation index (F) was established and the F-score was calculated. According to the F-score, 16 different hyperthermal environments were classified into three categories through hierarchical clustering analysis and discriminant analysis, with the corresponding F-score ranges of 28.14–39.76, 39.17–45.21, and 44.13–52.39. An analysis was conducted on the value of physiological and subjective indicators to test the nature of classification.

In recent years, ultraviolet (UV) germicidal irradiation (UVGI) has garnered increasing interest for use in public settings owing to its effectiveness and economic viability. In particular, the ultraviolet C (UVC) band exhibits strong microbicidal effects. Accurate modelling of UV fluence rate fields is essential for evaluating the disinfection performance of UVGI systems in complex indoor environments. In this study, we developed a ray-tracing-based simulation method capable of resolving fluence rate distributions under complex geometries and multiple occlusion conditions. The simulated fluence rate field was coupled with a computational fluid dynamics model to construct a predictive framework for airborne bioaerosol transport and ultraviolet disinfection. The model was validated through field measurements within a biosafety laboratory characterized by complex geometries, then used to assess the disinfection efficacy of three 0.34W, 222nm far-UVC lamps under 30 air changes per hour ventilation. Results indicated that far-UVC irradiation reduced bioaerosol concentrations by 18.6% in the near-field breathing zone and by 60.0% in the far-field zone, with a 31.0% concentration reduction across the occupied zone. The disinfection performance was found to be influenced by pathogen-specific characteristics, source-side design parameters and environmental conditions. This method provides a robust tool for evaluating far-UVC disinfection systems in realistic indoor environments,.

Efforts to further lower China's heating consumption are highly desirable to achieve the goals of peak carbon by 2030 and carbon neutrality by 2060. A two-tier zoning method for heat source retrofit based on coldness and resource abundance has been proposed in the cold regions of China and the relations between climate and resources have been explored. Besides, the heat index and heat consumption under different retrofitting zones of urban settlements have been assessed to reveal the impact of building energy efficiency on heat consumption. Results obtained are as follows: (1) Cold regions are divided into I-R0, I-R1, I-R2, I-R3, II-R1, II-R2, II-R3, III-R1, and III-R2 zones. Climate and resources show an overall negative correlation. (2) The I-R2 zone has the highest heat index and heat consumption, which are 56.21 W/m(2) and 0.38 GJ/m(2)a, respectively, while the III-R1 zone has the lowest heat index and the III-R2 zone has the lowest heat consumption, which is 33.57 W/m(2) and 0.18 GJ/m(2)a, respectively. (3) Heat indexes are reduced less than heat consumption as the rate of energy efficiency in buildings increases. (4) The new zoning and heat consumption modeling provides a computational basis for retrofitting heating systems in existing urban settlements.

Hyperthermal environments are encountered in many situations, and significant heat stress can exacerbate the fatigue perception of individuals and potentially threaten their safety. Heat acclimation (HA) interventions have many benefits in preventing the risk of incidents. However, whether HA interventions in specific environments can cope with other different hyperthermal environments remains uncertain. In this study, forty-three young male participants were heat-acclimated over 10 days of training on a motorized treadmill in a fixed hyperthermal environment, and they were tested in different hyperthermal environments. Physiological indices (rectal temperature (Tr), heart rate (HR), skin temperature (Tsk), and total sweat loss (Msl)) and subjective perception (rating of perceived exertion (RPE) and thermal sensation votes (TSVs)) were measured during both the heat stress test (HST) sessions and HA training sessions. The results show that HR and Tsk significantly differed between pre- and post-heat acclimation (p < 0.05 for all) following the acclimation program. However, after heat acclimation training, the reduction in Tr (ΔTr) was more notable in lower-ET* environments, and Msl showed distinct changes in different ET* environments. The RPE and TSV decreased after HA interventions, although the difference was not significant. The results indicate that HA can effectively reduce the peak of physiological parameters. However, when subjected to stronger heat stress, the improvement effects of heat acclimation on human responses will be affected. In addition, HA can alleviate physiological thermal strain, thereby reducing the adverse effects on mobility, but it has no effect on the supervisor’s ability to perceive the environment. This study suggests that additional HA training can reduce the risk of activities in high-temperature environments but exhibits different effects under different environmental conditions, indicating that hot acclimation suits have selective effects on the environment. This study provides recommendations for additional HA training before high-temperature activities.

To promote green and low-carbon transformation in the transportation sector and achieve the national "dual-carbon" targets, this study examines rooftop photovoltaic (PV) deployment at 12 representative railway stations located on the Qinghai-Tibet Plateau. Using high-resolution solar radiation data, building spatial information, and regional electricity pricing, we develop an integrated analysis framework that combines a PV power-generation simulation, life-cycle cost assessment, and carbon emission reduction evaluation. The model systematically evaluates the power output, economic performance, and emission reduction potential of rooftop PV systems installed on railway station buildings. Two PV array configurations-horizontal angle and optimum tilt angle-together with three business models (T1: all-consumption; T2: all-feed-into-grid; T3: self-consumption with surplus feed-in) are compared. The results indicate that the Qinghai-Tibet Plateau possesses substantial solar energy advantages. Rooftop arrays installed at a horizontal angle significantly increase both installed capacity and lifetime electricity generation, with stations XN and LS producing 523.12 GWh and 300.87 GWh, respectively, values that exceed the corresponding optimum tilt scenarios. In terms of economic performance, the T1 model yields the highest returns, with several stations achieving a lifetime return on investment exceeding 300% over a 25-year period. The T3 model demonstrates strong profit potential at stations such as RKZ and ZN, whereas the T2 model shows the weakest economic viability due to feed-in tariff constraints. Regarding carbon reduction, horizontal systems perform the best, with cumulative CO2 emission reductions at station XN exceeding 300,000 tonnes of CO2-equivalent. Overall, the findings highlight the substantial PV development potential of railway station rooftops on the Qinghai-Tibet Plateau. By selecting appropriate installation angles and business models, significant economic benefits and carbon emission reduction outcomes can be achieved, providing practical guidance for renewable-energy utilization in high-altitude transportation infrastructure.

As an important carrier of urban economic activities, the air-conditioning system of an office building has a high operational energy consumption while satisfying thermal comfort needs. Under constant flow rate operation, the traditional fixed chilled water temperature (7 degrees C) operation condition often leads to overcooling, especially under part-load conditions with low energy efficiency. This investigation focused on an office building to targete the office with the highest cooling load demand. The air parameter and operational data collection were conducted with subjective thermal comfort surveys, and model simulation of air conditioning systems. The research investigates the impact of variable chilled water temperature on indoor comfort under different load rates. It performs an energy-saving analysis by evaluating the effects on the performance of the chiller unit. The results showedthat air temperature and humidity were a good fit for chilled water supply temperature (R2 were 0.861 and 0.841). When the chilled water temperature changed, the indoor temperature and humidity would vary, further affecting indoor personnel's thermal comfort. Thermal comfort measurements and the predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) model calculations were highly consistent (upper and lower errors of 1.84% and 0.42%). It is recommended that the office building's chilled water temperature be controlled according to the load rate grading control: load rate of less than 70% to 12 degrees C, 70-90% to maintain 9 degrees C, greater than 90% adjusted to 7 degrees C.

As kitchen oil fume pollution becomes an increasing health risk, vertical centralized exhaust systems are widely used in Chinese residential buildings. However, these systems face issues such as backdraft and odor crossover, which compromise exhaust efficiency. To address these challenges, this study developed a six-story experimental system and used the control variable method to assess exhaust performance at varying range hood operation rates. Dynamic monitoring techniques were applied to analyze the dispersion of pollutants (PM2.5) during cooking. The results showed that higher operation rates led to increased exhaust resistance: as the rate rose from 16.67 % to 100 %, the average backpressure on floors 1, 3, 4, and 5 increased by 70.25Pa. At higher operation rates, the dispersion concentrations and rates of PM2.5 also increased, leading to poorer exhaust performance. On the 4th floor, the average PM2.5 dispersion concentrations (and rates) at 16.67 %, 50 %, and 100 % operation were 0.049 mg/m3 (5.4 %), 0.053 mg/m3 (5.8 %), and 0.071 mg/m3 (7.8 %), respectively. This study provides valuable insights for optimizing kitchen exhaust performance, refining range hood operation strategies, and reducing oil fume retention and backdraft.

Frost accumulation on surfaces of finned-tube exchanger is an important topic, and different prediction models have been developed. However, there are some shortcomings of existing models in practice. In this study, the ANFIS method with high accuracy is proposed to estimate the frost accumulation on surfaces of finned-tube exchanger. In the ANFIS model, six input parameters including j/f1/3, relative humidity, air temperature, air velocity, wall temperature of heat exchanger and time, were proposed over an extensive range. The output parameter is frost accumulation mass per meter tube mfr. The study compiled 5,005 experimental data points from both original experiments and published literature. Through stratified random sampling, 4,005 samples (80 %) were allocated for model training, while the remaining 1,000 samples (20 %) served as an independent test set to evaluate model robustness and generalization capability. R2 and RMSE for training gave values of 0.9985 and 0.6945, while R2 and RMSE for testing were 0.9984 and 0.7018, respectively. The result shows that when j/ f1/3 is introduced into the ANFIS model, the influence of finned-tube exchanger geometry on frost accumulation can be quantified and the frost mass of finned-tube exchanger with different geometries can be accurately estimated. In the primary stage of frost accumulation, ANFIS model estimates with large error of about 40 %. Subsequently, the error reduces to 5 % after 15mins which demonstrates a relatively high accuracy. Compared with existing theoretical model, ANFIS model in this study shows advantages of high accuracy, convenience, wide application etc.

Titanium dioxide (TiO₂)-based photocatalytic materials have demonstrated significant potential in enhancing indoor environments. This review systematically examines TiO₂’s fundamental mechanisms, applications in building environments, and performance enhancement strategies. The integration of TiO₂ with traditional building materials is explored, emphasizing its impact on air purification, antibacterial properties, and self-cleaning. Additionally, the review highlights key challenges, including environmental sensitivity and material compatibility, while providing insights into future research directions to promote healthier and more sustainable buildings.

Urban carbon emissions account for 75% of the total social emissions and are a key area for achieving the country’s “dual carbon” goals. This study takes the Sino-Singapore Tianjin Eco-City as a case, constructs a multi-dimensional carbon emission accounting model, integrates six systems, including buildings, transportation, water systems, solid waste, renewable energy, and carbon sinks, and proposes a comprehensive research method that takes into account both long-term prediction and a short-term dynamic analysis. The long-term emission trends under different scenarios are simulated through the KAYA model. It is found that under the enhanced low-carbon scenario, the Eco-City will reach its peak in 2043 (2.253 million tons of CO2) and drop to 2.182 million tons of CO2 in 2050. At the same time, after comparing models, such as random forest and support vector machine, the XGBoost algorithm is adopted for short-term prediction (R2 = 0.984, MAE = 0.195). The results show that it is significantly superior to traditional methods and can effectively capture the dynamic changes in fields, such as buildings and transportation. Based on the prediction results, the study proposes six types of collaborative emission-reduction paths: improving building energy efficiency (annual emission reduction of 93800 tons), promoting green travel (58,900 tons), increasing the utilization rate of non-conventional water resources (3700 tons), reducing per capita solid waste generation (14,400 tons), expanding the application of renewable energy (288,200 tons), and increasing green space carbon sinks (135,000 tons). The total annual emission-reduction potential amounts to 594,000 tons. This study provides a valuable reference for developing carbon reduction strategies in urban areas.