Different functional areas within general hospitals have varying environmental requirements, with relatively high energy consumption. A comprehensive evaluation of the operational performance’s rationality is of great significance in hospitals’ energy conservation efforts. This study conducted an annual post-occupancy evaluation of a general hospital located in a hot summer and cold winter area in east of China. Two hundred and seventy-eight valid online satisfaction questionnaires, sixty valid point-to-point questionnaires, indoor environment data of each typical season, and energy consumption data were obtained. The overall indoor environment of the selected hospital met the standard requirements. The results showed that occupant satisfaction was influenced by gender, working hours, and length of stay. The annual energy consumption level of this building was 84.7 kWh/m², which is significantly lower than that of other public general hospitals in China and general hospitals in developed countries. The energy consumption of the inpatient department was directly related to the hospital days, with an increase of 12.2 kWh/m² for every 1000 additional hospital days. A new indoor environment quality (IEQ) model and a new comprehensive evaluation model for energy efficiency were established. Overall, the outpatient department exhibited superior performance compared to the inpatient department. These evaluation models can help owners and decision-makers in the identification of environmental performance in hospitals.

The physical environment of classrooms has a strong relationship with student learning performance and health. Since the outbreak of COVID-19 in 2019, almost all universities have begun implementing closed instructional management, which has forced students to spend a much longer amount of time inside the classroom. This has also led to an increasing problem of thermal comfort in classroom indoor environments. In this paper, classrooms evolved from three dominant teaching modes at Zhejiang Sci-Tech University (ZSTU), located in the Hot Summer and Cold Winter (HSCW) zone of China, were selected as experimental spaces. Meanwhile, 12 learning groups with 60 students (30 of each sex) were selected as the tested samples. The relationship between thermal comfort and learning efficiency of the tested students was established through thermal comfort questionnaires and learning efficiency tests under the typical natural conditions in transition seasons. Based on this, improvement strategies were proposed for the current state of the classroom environment, providing a database for optimizing the environmental conditions of university classrooms in HSCW zone on the basis of improving students’ learning efficiency.

Along with the rapid urbanization and economic growth of China over the past decades, the thermal comfort needs of the people in this region have risen dramatically, and at the same time, promoting building energy efficiency is cited as part of the major projects in the 14th five-year plan for energy efficiency improvement. In addition, the outbreak of the COVID-19 epidemic has plunged people into long-term panic, and promoted the entire construction industry to think about a healthier and more sustainable living environment. To respond to the imbalance between energy supply and demand, an optimization analysis based on energy use is developed, assessing the energy efficiency of the window-to-wall ratio (WWR) design and calculating the energy consumption of three different types of residential buildings for both cooling and heating loads as well as for year-round loads. Owing to its harsh climate and huge energy consumption, in this study, the Hot-summer and Cold-winter (HSCW) zone of China was chosen as the experimental setting for the optimization analysis of WWR. Then, in the three main types of residential buildings, including detached houses, multi-story dwellings and high-rise dwellings, a correlation between WWR_S and energy consumption in the cooling season, heating season and year-round was built. The comparisons between the WWR_S and energy consumption for different types of residential buildings are presented. The design optimization recommendation for WWR_S are proposed. It has significant positive meanings for the development of green and sustainably designed residential buildings that offer high levels of thermal comfort and energy efficiency.

This study pioneers the comprehensive evaluation of the spatiotemporal evolution of land use/land cover (LULC) in Hangzhou city, introducing the novel water body shape index (WBSI) to analyze its seasonal impacts on the urban thermal environment and urban cool island (UCI) effects, uncovering distinct patterns of thermal regulation. It particularly investigates how distance gradients and the water body shape index (WBSI) influence land surface temperature (LST) in the urban core. The region’s climate, featuring hot summers and cold winters, highlights significant seasonal LST variations. Addressing a gap in existing UCI research, the analysis extends beyond the typical large-scale planning focus to include small-scale, high-resolution aspects. Employing remote sensing and geographic information system (GIS) analysis techniques, this study analyzes the seasonal dynamics in Hangzhou’s central urban area. High-resolution LST data, obtained through single-channel inversion and resolution enhancement algorithms, are crucial to this analysis. This study employs the maximum likelihood classification method to analyze land use and land cover changes from 1990 to 2020. This analysis reveals potential drivers of urban thermal environment changes, such as the expansion of residential and commercial areas and the reduction in green spaces. Different regions in LST data are delineated to assess the cool island effect, and the complexity of water body boundaries is quantified using the water body shape index. Spatial and temporal patterns of LST changes are investigated using multivariate regression and time-series analysis models. We identified significant changes in LULC over the past 30 years in Hangzhou, closely correlating with a continuous rise in LST. This observation underscores a clear finding: the strategic importance of blue–green infrastructure in mitigating urban heat, a novel insight that extends the current understanding of urban thermal dynamics. A clear and novel finding of this study is that the intensity of the cool island effect from large water bodies not only diminishes with distance but is intricately influenced by the complexity of their shapes, as quantified by the WBSI, whereas the complexity of their boundaries enhances this effect. Additionally, the regulatory role of the cool island effect is observed to vary seasonally, being most pronounced in summer and less so in autumn and winter, thereby demonstrating a positive impact. In conclusion, our findings innovatively highlight how the specific shapes of water bodies, quantified through the water body shape index (WBSI), emerge as critical, yet previously underappreciated, drivers in modulating the urban thermal environment. This underscores a new avenue for urban planning, advocating for the strategic design of water bodies within urban landscapes. It also finds that spatial factors and seasonal variations significantly affect the intensity of the cool island effect. These findings offer valuable evidence for urban planning and climate change adaptation, emphasizing balancing natural elements with the built environment in urban design.

This study aims to optimize indoor thermal environment assessment methods for primary school classrooms in regions with hot summers and cold winters, enhancing air-conditioning management efficiency and accuracy. Given the complexity of Predicted Mean Vote (PMV) calculations and its reduced accuracy under high temperature and humidity, this research explores the use of Thermal Sensation Vote (TSV) as a simpler alternative. Field measurements and subjective assessments were conducted to analyze the relationship between TSV and PMV, leading to a regression model linking predicted TSV (TSV_p) with temperature and humidity. Results indicate that temperature and humidity significantly impact TSV, with regression coefficients of 0.499 and 0.055, respectively. Furthermore, when TSV is ≥1, the proportion of PMV of ≥0.5 remains stable, validating TSV_p as a reliable indicator. Based on these findings, energy-efficient air-conditioning management strategies are proposed, recommending a temperature setting of 28 °C for thermal comfort. This study provides insights into climate control strategies in educational buildings, promoting sustainable development.

In built environment, there is renewed interest towards the local building material, which is cost-effective, environmental-friendly, and best suited to the local climate. In this framework, the study will be emphasized the impact of local roofing materials on indoor thermal comfort of Bamboo house in a warm and humid region of Myanmar. In practice, Bamboo houses with different roofing materials were monitored with seven sensor points at outdoor and indoor to observe its thermal performance. By regarding microclimate conditions, the performance of different roofing materials on the indoor environment will be analyzed by statistical analysis based on the thermal comfort index. The result shows indigenous roofing material has less thermal conductivity impact on indoor thermal comfort than the other roofing materials. Moreover, the double roof, which is made of a combined layer of Dani and GI sheet, keeps the room with moderate thermal comfort for almost the whole day. The result of this study will propose suitable roofing material of Bamboo House and the required period to operate an air-conditioner with an extensive explanation to lead the reduction of Energy Consumption in further.