Different Climate Zones In China Research Articles

Machine learning models for daily net radiation prediction across different climatic zones of China

Net radiation (Rn), a critical component in land surface energy cycling, is calculated as the difference between net shortwave radiation and longwave radiation at the Earth’s surface and holds significant importance in crop models for precision agriculture management. In this study, we examined the performance of four machine learning models, including extreme learning machine (ELM), hybrid artificial neural networks with genetic algorithm models (GANN), generalized regression neural networks (GRNN), and random forests (RF), in estimating daily Rn at four representative sites across different climatic zones of China. The input variables included common meteorological factors such as minimum and maximum temperature, relative humidity, sunshine duration, and shortwave solar radiation. Model performance was assessed and compared using statistical parameters such as the correlation coefficient (R2), root mean square errors (RMSE), mean absolute errors (MAE), and Nash–Sutcliffe coefficient (NS). The results indicated that all models slightly underestimated actual Rn, with linear regression slopes ranging from 0.810 to 0.870 across different zones. The estimated Rn was found to be comparable to observed values in terms of data distribution characteristics. Among the models, the ELM and GANN demonstrated higher consistency with observed values, exhibiting R2 values ranging from 0.838 to 0.963 and 0.836 to 0.963, respectively, across varying climatic zones. These values surpassed those of the RF (0.809–0.959) and GRNN (0.812–0.949) models. Additionally, the ELM and GANN models showed smaller simulation errors in terms of RMSE, MAE, and NS across the four climatic zones compared to the RF and GRNN models. Overall, the ELM and GANN models outperformed the RF and GRNN models. Notably, the ELM model's faster computational speed makes it a strong recommendation for Rn estimates across different climatic zones of China.

Research on the Contribution Rate of Photovoltaic Power in Indoor Ice Arenas across Different Climatic Zones: A Case Study in China

With the increasing construction of ice arena facilities, addressing their energy consumption issues has become crucial, emphasizing the need for renewable energy utilization. This study aims to determine the contribution rate of photovoltaic (PV) power generation in indoor ice arenas across different climate zones in China and proposes corresponding PV application strategies. By modeling the vertical zoning above the ice arena, energy consumption in indoor ice arenas across six typical cities was simulated, calculating annual and monthly renewable energy contribution rates and proposing utilization strategies. The research reveals a growing proportion of cooling energy consumption due to climate warming, exceeding half of the total energy even in cold cities. Differences in energy consumption and renewable energy contribution rates among cities highlight the impact of local climate conditions. Favorable climates and abundant solar resources in some cities enable more energy-efficient ice arena construction, while high energy consumption and limited solar resources pose challenges in others. The study identifies seasonal variations in renewable energy contribution rates, emphasizing the need to optimize power generation seasonally. In colder cities, summer power generation is essential, while in hotter climates, winter power generation is more advantageous. This study provides insights for designing energy-efficient and sustainable ice arenas.

Multi-objective optimization of daylighting performance and energy consumption of educational buildings in different climatic zones of China

With the implementation of China's “Healthy Building” and “Dual Carbon” strategies, daylight health and energy-saving carbon reduction in buildings have become key research areas. In educational buildings, early design decisions significantly impact students' eye health and energy consumption reduction, making it crucial to balance these concerns. Studies indicate that sufficient and continuous daylight can significantly improve students' eye health, mood and sleep. To maximize the UDI level at the eye level (seated) and minimize EUI and DGP, this study used the multi-objective optimization tool Wallacei based on NSGA-II (Non-dominated Sorting Genetic Algorithm II) for genetic optimization. This study uses the Shiji Building of Central South University in Changsha, Hunan, as a reference model to provide optimal classroom designs for China's five major thermal design zones: severe cold, cold, hot summer and warm winter, hot summer and cold winter, and mild. The results indicate that optimizing the classroom's deflection angle, length, width, height, and WWR significantly improves energy efficiency and daylighting performance. Specific data shows that an orientation 5° east or 5° west of south helps balance energy consumption and daylighting performance in both large and small classrooms. The length and width of the classrooms vary greatly, but the height generally converges to 3.2 m. Increasing the WWR to 0.5–0.7 demonstrates good energy efficiency and daylighting performance in both large and small classrooms in hot climate zones. In all climate zones, compared to the initial scheme, the Knee solutions reduced the EUI of both types of classrooms by up to 19.0 %, reduced DGP by up to 56.4 %, and increased UDI by up to 19.0 %.

Optimal HVAC setpoints for energy efficiency and thermal comfort in Chinese residential buildings

The easiest way to improve energy efficiency and thermal comfort in existing buildings is to adjust setpoints. However, although Chinese standards regulated the heating and cooling setpoints for different climate zones in China, they lacked consideration for occupants’ thermal comfort and ignored the ventilation setpoints. Therefore, this study aimed to identify optimal heating, cooling, and ventilation setpoints at the design stage to enhance building energy performance and indoor thermal comfort in Chinese residential buildings. This study used DesignBuilder to simulate the energy usage and thermal comfort with different setpoints and judged which combination was the best. To conduct this study across the whole of China, the typical cities in different climate zones were selected by using machine learning. Results indicated that adjusting setpoints in Harbin, Beijing, and Shanghai could increase comfortable days by 43.95 %, 54.23 %, and 23.36 % respectively, with minimal impact on energy usage. In Guangzhou, energy usage could be reduced by 7.56 % with a 5.91 % decrease in comfortable days, while Kunming could see an 11.11 % increase in comfortable days with a 5.92 % rise in energy consumption. Additionally, sensitivity analysis revealed that activity template variation was most critical for energy usage in Harbin, Beijing and equipment power density variation was most important for thermal comfort in Shanghai, Guangzhou, and Kunming. Furthermore, proposed setpoint combinations demonstrated resilience to future weather conditions in most typical cities, except for Guangzhou. These findings provide valuable insights for designers and researchers aiming to retrofit residential buildings, emphasizing the importance of considering both energy efficiency and occupant comfort. This study introduces innovative approaches like comprehensive setpoint optimization and machine learning for typical city selection, providing practical solutions to improve energy efficiency and thermal comfort in residential buildings.

Thermophysical properties and energy-saving efficiency of phase change microcapsule foamed cement composite insulation materials

The addition of phase change materials (PCMs) to building envelopes can improve building thermal stability and reduce energy consumption. In this study, phase change paraffin microcapsules are combined with foamed cement to create composite thermal insulation materials with varying mass ratios of microcapsules. A heat transfer characterization experimental platform was established to investigate the heat transfer laws. The incorporation of phase change microcapsules (MPCMs) into foamed cement resulted in a reduction in thermal conductivity. The thermal conductivity of the test blocks exhibited a linear relationship with the mass ratio of MPCMs, with an average thermal conductivity of 0.053 W/(m-K) observed for 20 % MPCMs. The impact of foamed cement containing MPCMs on building energy consumption was analyzed in five different climate zones in China using EnergyPlus. The results show that energy savings are more significant in cities with higher heating demand. In non-cold regions, energy savings are highest when the phase change temperature is close to the local annual average temperature. The optimal energy saving program is evaluated by energy consumption simulation. The results show that it achieves the highest energy savings in Harbin, which saves a total of 1074,007 kWh. Additionally, it has the highest energy saving rate in Beijing, with a rate of 14.66 %.

Impact of urban form on building energy consumption in different climate zones of China

Despite numerous studies on the relationship between urban form and building energy demand, understanding the impact mechanisms of urban form is still insufficient. Here, we identified the direct and indirect influences of urban form on building energy demand. The direct influence includes the blocking of solar radiation. The indirect influence is exerted through the urban heat island (UHI) effect as different urban forms produce different UHI intensities. The UHI effect was calculated using the urban weather generator (UWG) tool. Then, the analysis of the direct and indirect influences on the building energy demand was carried out using building energy modeling (BEM) based on the output of UWG. Five cities in different building climate zones in China were investigated, and the corresponding direct and indirect influences were quantified based on the proposed UWG + BEM framework. Results show that warmer temperatures lead to an average increase in space cooling of 16 %–46 % while reduced space heating of 8 %–17 %. The shading of surrounding buildings allows an increase of 7 %–36 % in space heating and a decrease of 14 %–48 % in space cooling compared to that of an isolated building. In addition, direct influence due to shading is prominent in Shuangyashan, Xuzhou, and Fuzhou, accounting for 50 %, 80 %, and 57 % of variations in building energy consumption.

Numerical study of the impact of make-up air in a residential kitchen on the heating and cooling demands of ULEBs

Ventilation significantly impacts energy consumption in ultra-low-energy buildings (ULEBs). However, in Chinese residential kitchens, the influence of mechanical ventilation formed by range hoods and make-up air systems on energy consumption has received limited attention. This study assesses the heating and cooling demands in ULEBs resulting from kitchen make-up air across different climate zones in China. The results reveal that in natural make-up air mode, there is a substantial rise in annual heating demand in cold and severe cold zones and a notable increase in annual cooling demand in hot summer and warm winter as well as hot summer and cold winter zones. Additionally, the natural make-up air mode often poses challenges in maintaining a satisfactory thermal environment in kitchens during both heating and cooling seasons. Conversely, the mechanical make-up air mode, especially with pretreatment of outdoor air to ensure thermal comfort in kitchens, significantly elevates both annual heating and cooling demands, making it hard for the building to meet the ULEB specifications, particularly in cold and severe cold zones. Furthermore, despite a generally small increase in annual cooling demand, the percentage rise in heating demand often exceeds the ULEB limits, ranging from 12.0% to 36.0%, depending on the climate zone.

A Study on the Daylighting, Energy Consumption, and Climate Adaptability of Curved Mesh Shading Based on the Parametric Performance Design Method

Building shading forms are becoming increasingly diversified, driven by both building performance requirements and architectural aesthetics. The application of computer technology in shading design and performance evaluation is becoming increasingly popular. This study adopted a parametric performance design method and created a one-click workflow for parametric curved mesh shading design and performance evaluation based on the Grasshopper platform and Ladybugtools. Applying this workflow, this paper takes five typical cities in different climate zones in China as examples to analyze the impact rules of curved mesh shading parameters (blade width, number of horizontal grids, and number of vertical grids) on building daylighting and energy consumption and explore the application potential of curved mesh shading. This study found that curved mesh shading has the best potential to improve daylighting in Harbin and can increase the annual average UDIa (300~3000 lux) by 7.42%. In Guangzhou, curved mesh shading has the highest potential for energy saving, which can reduce annual energy consumption by 14.8%. This study can provide theoretical, methodological, and data support for the optimal design of curved mesh shading.

The Relationship between Trait-Based Functional Niche Hypervolume and Community Phylogenetic Structures of Typical Forests across Different Climatic Zones in China

Functional traits are pivotal for understanding the functional niche within plant communities. Yet, the relationship between the functional niches of typical forest plant communities across different climatic zones, as defined by functional traits, and their association with community and phylogenetic structures remains elusive. In this study, we examined 215 woody species, incorporating 11 functional traits spanning leaf economy, mechanical support, and reproductive phenology, gathered from forests in four climatic zones from tropical, subtropical, warm-temperate to cold-temperate zones in China and supplemented by the literature. We quantified the functional niche hypervolume (FNH), reflecting the multidimensional functional niche variability. We then probed into the correlation between the FNH and community and phylogenetic structures of forests. Our findings reveal that species richness significantly influences the geographic variance of functional niche space in forest vegetation across different climatic zones. Specifically, a community’s species richness correlates positively with the functional niche breadth occupied by the community species. The FNH of woody plants across diverse forest types shows significant associations with both the mean phylogenetic distance (MPD) and the mean nearest phylogenetic taxon distance (MNTD) of the communities. There is a progressive increase in tropical rainforest (TF), subtropical evergreen deciduous broad-leaved mixed forest (SF), and warm-temperate coniferous broad-leaved mixed forest (WF), followed by a decline in the cold-temperate coniferous forest (CF). This pattern suggests potential environmental filtering in CF, which may constrain the spatial extent of plant functional niches. Our research underscores the substantial variability in the FNH across China’s typical forest vegetation, highlighting the complex interplay between functional traits, community richness, and phylogenetic distance.

A thermal comfort assessment on semi-outdoor sports stadiums located in 3 different climate zones in China

The thermal environment of sports stadiums, one of the biggest public facilities in the city, can easily impact the health of tens of thousands of people. Semi-outdoor stadiums are susceptible to summer heat waves due to global warming. Overall, this paper provides insights into the thermal comfort conditions in semi-outdoor sports stadiums in three different climate zones in China. Through field research, a method is provided to monitor the thermal environment in the stands of a big stadium using eight sensors. Stadium occupants' thermal comfort is assessed using the Universal Thermal Climate Index (UTCI), and the effects of various climatic conditions are examined. The results of the study show that the north side of the stadium stands is the point with the highest thermal risk, even if the climatic zones are different. The distribution of thermal comfort in the stands will be directly impacted by the stadium's roof prototype. The UTCI has modest sensitivity to wind speed and great sensitivity to the three climatic parameters of air temperature, mean radiant temperature, and relative humidity. This implies that in the stadium grandstand, the shading strategies will enhance the thermal environment more effectively than the natural ventilation strategies. The findings suggest that a combination of passive and active strategies can be used to improve thermal comfort, such as asymmetrical seating design, full wrap-around roofs, and scheduling events to avoid peak heat stress.

Diversity of Cellular Slime Molds (Dictyostelids) in the Fanjing Mountain Nature Reserve and Geographical Distribution Comparisons with Other Representative Nature Reserves in Different Climate Zones of China.

Protected areas are widely considered an essential strategy for biodiversity conservation. Dictyostelids are unique protists known to have important ecological functions in promoting soil and plant health through their top-down regulation of ecosystem processes, such as decomposition, that involve bacterial populations. But the relationship between dictyostelid diversity within protected areas remains poorly understood, especially on a large scale. Herein, we report data on the distribution of dictyostelids, identified with ITS + SSU rRNA molecular and morphology-based taxonomy, from soil samples collected in the Fanjing Mountain protected area of Guizhou Province, Southwest China. We compared the biodiversity data of dictyostelids in Fanjing Mountain with similar data from previously sampled sites in four other protected areas, including Changbai Mountain (CB), Gushan Mountain (GS), Baiyun Mountain (BY), and Qinghai-Tibet Plateau (QT) in China. We identified four species of dictyostelids belonging to three genera (Dictyostelium, Heterostelium, and Polysphondylium) and herein provide information on the taxonomy of these species. Two species (Heterostelium pallidum and Dictyostelium purpureum) are common and widely distributed throughout the world, but one species (Polysphondylium fuscans) was new to China. Our data indicate that there is no distinguishable significant correlation between the dictyostelid species studied and environmental factors. Overall, the similarity index between Baiyun Mountain in Henan Province and Fanjing Mountain in Guizhou Province, located at approximately the same longitude, is the highest, and the Jaccard similarity coefficients (Jaccard index) of family, genus, and species are 100%, 100%, and 12.5%, respectively. From a species perspective, species in the same climate zone are not closely related, but obvious geographical distributions are evident in different climate zones. This preliminary study provided evidence of the ecological adaptation of dictyostelids to different biological niches.

Source tracing the bedroom bacteria across different climate zones in China during the heating season

Approximately 1/3 of people's time is spent in bedrooms. Regulating the health implications arising from the bedroom bacterial community demands an in-depth understanding of both the bacterial composition and the influential factors. This study employed high-throughput 16 S rRNA amplicon sequencing to characterize the bacterial community in 23 residential bedrooms across five climate zones in China. Our findings reveal that the bacterial richness and diversity were highest in the Hot-Summer-Cold-Winter (HSCW) zone, possibly due to its lowest indoor temperature during the heating season. Employing an advanced source tracing algorithm, we identified ventilation rate as the dominant factor affecting outdoor bacterial presence, with each additional air change per hour (ACH) increasing the outdoor bacterial abundance by 13.7 %. The integumentary system was the largest contributor to the occupant-associated bacteria, particularly in the residences located in the Severe Cold and Cold zones. Our study provides valuable insights into the diverse bacterial communities in residential bedrooms across various climate zones in China, elucidating the key factors and sources that contribute to shaping these complex microbial ecosystems.

Spatial-temporal variation of water vapor scale height and its impact factors in different climate zones of China

Water vapor scale height reflects the vertical distribution of water vapor in the atmosphere, which is a vital parameter in tropospheric zenith wet delay (ZWD) modeling and GNSS meteorology. This study accurately calculated the long-term water vapor scale height using 89 radiosonde stations in China, analyzed the characteristics in temporal and spatial variations and explored the impact factors of the water vapor scale height from the perspective of the climate zones. The numerical results indicate that the water vapor scale height in China exhibits annual and semiannual variations with a rising-then-decreasing trend across the four seasons. A relatively larger value for the water vapor scale height were observed in the subtropical monsoon climate and the temperate continental climate zone, in which the values are greater than 2.35 km, while the values in temperate monsoon climate and the alpine plateau climate zone are relatively small. In addition, the water vapor scale height in different climate zones shows different trends, with a downward trend appeared in the subtropical monsoon climate and the alpine plateau climate zone, while an upward trend was observed in the temperate monsoon climate and the temperate continental climate zone. Furthermore, a positive correlation between water vapor scale height and temperature, pressure, and atmospheric precipitable water was found in China, with a varied degree of correlation in different climate zones.

The influence patterns of carbon flux in different climatic zones in China —Based on the complex network approach

Research on ecosystem carbon flux can provide important methodological and strategic support for climate change mitigation. The existing studies focus on the calculation of carbon flux, ignoring the intertwined effects between regions. The quantification and analysis of the interaction patterns of carbon flux is crucial for understanding the global carbon cycle process, forecasting and coping with climate change. In this study, carbon flux network model sequences are established based on complex network theory using carbon flux data spanning from December 1, 2005, to November 30, 2020. The time delay effect is introduced to accurately quantify the influence patterns of carbon flux within climate zones across China. The findings indicate that the probability distribution function of the link weights during the various seasons of each year exhibits a bimodal distribution with distinct positive and negative components. The delay probability distribution function reveals the significant impact of delay effects, which are especially pronounced and mostly significant long-term lag effects in nodes with negative weights. Further, the results of the interactions of carbon flux among climate zones demonstrate that changes in carbon flux in the plateau and southern temperate regions have either positive or negative impacts on other climate zones. Therefore, controlling carbon flux changes in these climatic zones can effectively optimize the distribution of carbon flux. The modeling framework and results presented in this paper provide useful insights for the regulation and distribution optimization of carbon flux in China.

An interpretable framework for modeling global solar radiation using tree-based ensemble machine learning and Shapley additive explanations methods

Machine learning techniques provide an effective and cost-efficient solution for estimating solar radiation for solar energy utilization. However, the reported machine learning-based solar radiation models fail to offer comprehensive explanations for their outputs. Therefore, this study aims to tackle this issue by developing machine learning models that are both accurate and interpretable. To achieve the objective, this study evaluated the performance of tree-based ensemble algorithms, using optimized combinations of model input parameters for different climate zones in China. The results showed that the extreme gradient boosting (XGBoost) models demonstrated the highest overall accuracy, model stability, and generalization ability. At the national scale, the developed XGBoost models yielded an average R2, MAE, and RMSE of 0.939, 1.226 MJ/m2, and 1.663 MJ/m2, respectively, showing significant improvements of 2.13–27.78% in RMSE compared to recently reported models. Most importantly, the state-of-the-art SHapley Additive exPlanations (SHAP) technique was integrated with the developed XGBoost models to enhance model interpretability in terms of global and local feature importance, as well as the interaction effects between model features. The results of the SHAP value analysis demonstrated the robustness of sunshine duration in modeling global solar radiation, revealing thresholds where its values undergo a shift from negative to positive effects on model output. SHAP interaction values illustrated the interaction effects among features in the developed solar radiation model, uncovering the model's complex non-linear relationships. Additionally, this study provided explanations for individual instances based on the SHAP method. Overall, this study provided an accurate, reliable, and transparent machine learning model and an enlightening framework for modeling global solar radiation at sites without observations.

Effectiveness of enhanced roof ventilation unit (ERU) based on venturi cap in different wind environments and new evaluation models: A numerical study

Reasonable building ventilation design can effectively improve indoor thermal comfort and reduce energy consumption. Therefore, an enhanced roof ventilation unit (ERU) was developed for this study, and its performance and influence law under various wind speeds and directions were explored through numerical simulation. Additionally, a new evaluation method for ERU was proposed through data fitting, and applicability was verified for different climate zones in China. The results showed that: (1) With a maximum difference of 3.11 °C, the ERU performed best in the N direction and poorest in the SW direction for indoor temperature. Furthermore, the impact of wind directions was more evident than wind speeds. (2) The wind speed affected the volume flow rate significantly in the NE direction (7.77 m3/s) and insignificantly not in the SE direction (0.32 m3/s). Nevertheless, the performance was the opposite in the NE and SE directions when the wind speed increased from 0.5 m/s (3) The air age performed best in the NE and worst in the SE directions. As wind speeds surpassed 2.0 m/s, the air age variation steadily stabilized in various wind directions. (4) The fitted equation for indoor temperature has applicability in typical cities in five climate zones, and the fitted equation for volume flow rate is applicable in four climate zones except the hot summer and warm winter zone. The study results can provide references for the ERU to improve indoor thermal ventilation, contributing to sustainable building energy efficiency.

Study on the Influence of the Application of Phase Change Material on Residential Energy Consumption in Cold Regions of China

As the impact of climate change intensifies, meeting the energy demand of buildings in China’s cold regions is becoming increasingly challenging, particularly in terms of cooling energy consumption. The effectiveness of integrating phase change material (PCM) into building envelopes for energy saving in China’s cold regions is unclear. The aim of this study is to assess the effectiveness of PCM integration in building enclosures for energy efficiency in these regions. The research monitored and recorded indoor temperature data from typical residential cases from May to September. This measured data was then used to validate the accuracy of EnergyPlus22-1 software simulation models. Subsequently, the calibrated model was utilized to conduct a comparative analysis on the effects of PCM on indoor temperatures and cooling energy consumption across these regions. The results of these comparative analyses indicated that PCM can alleviate indoor overheating to varying degrees in severe cold regions of China. Focusing on north-facing bedrooms, applying PCMs reduced the duration of overheating in non-air-conditioned buildings in severe cold regions of China by 136 h (Yichun), 340 h (Harbin), 356 h (Shenyang), and 153 h (Dalian). In terms of cooling energy consumption, the energy saved by applying PCMs ranged from 1.48 to 13.83 kWh/m2. These results emphasize that the performance of PCM varies with climate change, with the most significant energy-saving effects observed in severe cold regions. In north-facing bedrooms in Harbin, the energy-saving rate was as high as 60.30%. Based on these results, the study offers guidance and recommendations for feasible passive energy-saving strategies for buildings in severe cold and cold regions of China in the face of climate change. Additionally, it provides practical guidance for applying PCMs in different climatic zones in China.

Applicability and improvement of different potential evapotranspiration models in different climate zones of China

BackgroundAccurate estimation of potential evapotranspiration (PET) is the key for studying land-air interaction hydrological processes. Several models are used to estimate the PET based on standardized meteorological data. Although combination-based models have the highest level performance estimation of PET, they require more meteorological data and may therefore be difficult to apply in areas lacking meteorological observation data.ResultsThe results showed significant differences in the spatial trends of PET calculated by different models in China, the Doorenbots–Pruitts model revealed the highest PET (1902.6 mm), and the Kuzmin model revealed the lowest PET (349.6 mm), with the largest difference being 5.5 times. The Romanenko and the Rohwer models were the recommended temperature-based and aerodynamic-based models. On the other hand, the Abtew model was more suitable for arid and semi-arid regions, while the Priestley–Taylor model was more suitable for humid regions. Combination-based models revealed ideal calculation accuracies, among which the Penman–Monteith model was the best option for PET calculation.ConclusionsThe accuracy range of Romanenko, Rohwer, Abten, Priestley Taylor, and Penman Monteith models improved in MPZ and TCZ is higher than that improved in TMZ and SMZ. This does not mean that the improved models have higher accuracy in MPZ and TCZ than in TMZ and SMZ. On the contrary, the original model performed poorly in MPZ and TCZ, so the improved accuracy was relatively large. The unimproved model was already more suitable in TMZ and SMZ, so the improved accuracy was relatively small. Therefore, regional calibration of the PET models can improve the accuracy and applicability of PET calculation, providing a reference for studying hydrological processes in different climatic zones.

A Systematic Review on the Studies of Thermal Comfort in Urban Residential Buildings in China

There have been fruitful publications on thermal comfort of urban residential buildings in China. However, there is a lack of reviews on this topic to perform a comprehensive analysis and find opportunities to meet occupants’ thermal comfort needs while improving building energy efficiencies. This paper addresses this issue by presenting a systematic review on the advancements in research on thermal comfort in urban residential buildings in China. Firstly, two common thermal comfort research approaches, i.e., field studies and laboratory studies, are discussed. Secondly, eleven main thermal comfort evaluation indicators are summarized. Finally, this paper analyzes the thermal comfort survey data from different researchers, discusses the impacts of adaptive behaviors on human thermal comfort, and provides recommendations for future research on urban residential thermal comfort. It was found that people have higher and higher requirements for their indoor thermal environment as time goes by, especially in the winter; the thermoneutral temperature is higher in warmer climate regions in the summer but lower in the winter than in colder climate regions; the thermoneutral temperature tends to increase with the indoor air temperature due to an adaptation to the indoor thermal environment. The outcomes of this paper provide valuable information on thermal comfort behaviors of urban residents in different climate zones in China, which can serve as a resource for the academic community conducting future research on thermal comfort and assist policymakers in enhancing building energy efficiencies without compromising the occupants’ comfort.

Influence of Different Forms on BIPV Gymnasium Carbon-Saving Potential Based on Energy Consumption and Solar Energy in Multi-Climate Zones

In this study, the influence of the gymnasium building form on energy consumption and photovoltaic (PV) potential was investigated to address its high energy consumption and carbon emissions issues. Five cities in different climate zones in China (Harbin, Beijing, Shanghai, Guangzhou, and Kunming) were selected as case study environments to simulate and calculate the energy use intensity (EUI), photovoltaic power generation potential (PVPG), and CO2 emission (CE) indicators for 10 typical gymnasium building forms, while also assessing the impact of building orientation. This study found that changes in gymnasium building orientation can cause a 0.5–2.5% difference in EUI under the five climatic conditions, whereas changes in building form can cause a 1.9–6.4% difference in EUI. After integrating a building-integrated photovoltaic (BIPV) system on the roof, changes in building orientation and form can lead to a 0–14.4% and 7.6–11.1% difference in PVPG and a 7.8–68.1% and 8.7–72.0% difference in CE. The results demonstrate that both the choice of form and orientation contribute to a reduction in carbon emissions from BIPV gymnasiums, with the rational choice of form having a higher potential for carbon savings than orientation. These research findings can guide the initial selection of gymnasium designs to pursue low-carbon goals.