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The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay’s theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice. [ABSTRACT FROM AUTHOR]

The acceleration of urbanization and the growth of population are considered to be the reasons of increasing demands for construction, life quality and energy consumption. This leads to more research in climate adaptive strategies such as traditional design methods, construction techniques and building materials. Traditional dwelling has been successful in achieving harmony between dwelling and climatic environment, which is one of the most important conditions for sustainability. Firstly, this paper focused on analyzing the characteristics of traditional dwellings in Qinba mountainous areas to adapt to the climatic environment. Secondly, two typical dwellings constructed respectively with brick and earth materials were selected for monitoring and simulating of its indoor thermal, luminous and ventilation environment in summer and winter. In addition, the research summarized the advantages and disadvantages of the dwelling's physical environment in response to climatic characteristics. It revealed that the traditional earth dwelling is well adapted to the local climate during summer, although the indoor thermal comfort is not fully satisfactory during winter. Finally, we prompted effective climate adaptive strategies of traditional earth dwelling, such as natural ventilation, thermal insulation and thermal buffer space. We want to provide guidance and reference for the development of traditional dwellings in the mountainous areas. [ABSTRACT FROM AUTHOR]

In this paper, an intelligent ensemble machine learning (EML) method - Bagging was developed for thermal perception prediction. Field data was collected in naturally ventilated (NV) and split air-conditioning (SAC) dormitory buildings in hot summer and cold winter (HSCW) area of China during the summer of 2016. The indoor physical measurement and subjective survey were conducted simultaneously during the field study. To determine the merit of the proposed Bagging approach, the performances of Bagging approach were compared against the artificial neural network (ANN) and support vector machine (SVM) regarding conventional statistical indicators, i.e., mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R 2 ) and Pearson correlation coefficient (r). Several thermal indices, i.e., thermal sensation (TS), effective temperature (ET*), standard effective temperature (SET*) and predicted mean vote (PMV), were adopted to access the occupants’ thermal comfort and evaluate the model prediction. In our case study, the Bagging model's R 2 for TS, PMV, ET* and SET* were 0.4986, 0.9892, 0.9920 and 0.9900, respectively. It shows higher accuracy than SVM and ANN models in thermal perception prediction and outperforms the classical PMV index in TS prediction. Results indicate the proposed Bagging model's prediction performance is reliable and is highly accurate to predict the thermal perception. [ABSTRACT FROM AUTHOR]

• Analyzed residents' thermal demand characteristics under the global climate change. • A new thermal comfort evaluation model of traditional dwellings was established. • The new thermal neutral temperature and comfort range of residents were proposed. • Different measures to improve the old and new types of dwellings were put forward. Global climate change has led to increased differences in the indoor thermal environment of traditional dwellings and residents' thermal adaptability, but quantitative research in this area needs to be updated and improved. In this paper, taking the old and new types of traditional dwellings of Guangfu Ancient City in Hebei province, China as the example, we first investigated the current situation of indoor thermal environment and thermal comfort characteristics of residents by means of subjective questionnaire survey and objective data measurement. The measured data showed that the average indoor temperature of old-type traditional dwellings in winter was far lower than the thermal comfort range of human body, and it was also higher than the relevant standard in summer. Secondly, we established a new thermal comfort evaluation model of traditional dwellings and proposed a new thermal neutral temperature of residents: old-type traditional dwellings (18.1 °C in winter and 27.1 °C in summer), new-type traditional dwellings (19.8 °C in winter and 25.7 °C in summer). Although the measured data showed that the thermal environment quality of the old-type traditional dwellings was poor, the residents had strong thermal adaptability. Finally, we put forward the different living performance improvement strategies of old and new types of traditional dwellings: The old-type traditional dwellings should focus on strengthening the thermal performance of the envelope structure, while the new-type traditional dwellings should solve the problem of low indoor humidity in winter. This research improves the evaluation system of human thermal comfort of dwellings in cold region of China, and provides a good case reference. [ABSTRACT FROM AUTHOR]

Seasonal variation of thermal comfort demands directly affects the energy needs for heating or cooling purpose. In previous studies, the differences of neutral temperatures between summer and winter were revealed, but the studies on the difference of human thermal adaption in transitional seasons are insufficient. To clarify this, this paper presents a year-long survey which was carried out in 505 residential buildings in six cities located in the Hot Summer and Cold Winter (HSCW) zone of China involving 11,524 subjects. Results show a significant difference of adaptive responses in different seasons, and a lag of behavioral responses behind climate change in transitional seasons is observed. Occupants not only adjust clothing insulation according to air temperature in different seasons, but also actively control indoor air movement, including closing/opening windows and using fans. The seasonal, monthly and daily neutral temperatures are studied, implying that occupants’ thermal experience has significant effect on their thermal comfort by behavioral, physiological and psychological paths. According to the comparative study, the running mean air temperature method and aPMV model are recommended in free-running space. The findings provide scientific evidence to the concept that dynamic thermal comfort temperature range should be considered in evaluation of indoor thermal environment. [ABSTRACT FROM AUTHOR]

In light of growing concerns about climate change and energy conservation, the adaptive thermal comfort theory has become a research focus. However, to date, few about the dynamic process of human thermal adaptation has been explored. In this paper, we ask the question as to whether people accustomed to one indoor climate can readapt to another one? And what about the timescale and difficulty of thermal re-adaptation? A comparative study was conducted in China where wintertime indoor thermal environments remarkably varied between the northern region (with pervasive district heating) and southern region (without district heating). Four college student groups were surveyed in teaching buildings and over 2000 valid responses were collected. The results show that occupants’ subjective thermal comfort perception is strongly influenced by their previous thermal experience. People accustomed to indoor climate excellence are able to readapt themselves to environments with lesser quality, however, the adapting process may take some time. The effort of this study shed some light on the dynamic process of human thermal adaptation, which is helpful to shape the future indoor climate. [ABSTRACT FROM AUTHOR]

Numerous questionnaire-based studies were conducted to investigate associations of home environment with childhood health, whereas few studies confirmed validity of parents-reported questionnaire regarding dwelling characteristics and dampness-related indicators. According to data obtained by standard questions regarding these items via on-site inspection in 454 residences with young children during 2013–2014, and data collected for these items from their parents-reported questionnaires in cross-sectional survey during 2011–2012 in Shanghai, China, this paper validated consistencies of information for these items between the two phases, thus to confirm validity of parents-reported questionnaire regarding these items. According to Kappa ( k ) values, parents and inspectors had moderate/substantial consistencies regarding dwelling characteristics ( k = 0.212–0.894), but had slight consistencies regarding dampness-related indicators and indoor odors (absolute k = 0.019–0.144). However, according to the observed, positive, and negative proportional agreement (P o , P pos , and P neg ), parents and inspectors had substantial/prefect consistencies in most of the studied items (P o = 0.45–0.96). These trends of consistencies for different items had no notable differences, regardless of father or mother as the questionnaire-reporter, and among the residences inspected in different seasons. This study suggests parents-reported questionnaire could be a reliable and valid method to indicate the overall status of dwelling characteristics and home dampness-related exposures. [ABSTRACT FROM AUTHOR]

In order to solve the practical problems on the utilization of a burning cave, such as overheated floor, uneven heat distribution, and serious heat lose, a hot water heating system integrated with a burning cave has been designed based on the principle of energy cascade utilization. However, there is no prediction and calculation method for designing this combined heating system. In this paper, through theoretical calculation, the response formula of time–temperature on the hot water heating system changed with the radiation intensity on biomass fuel combustion layer has been deduced and verified by experimental data. Besides, the impacts of the radiation temperature on fuel combustion layer, the height of fuel layer, pipe diameter, pipe spacing and water flow velocity on the heat transfer performance of this heating system have been respectively discussed. The thermal efficiency can be up to 39.3%. [ABSTRACT FROM AUTHOR]

The building envelopes are exposed to the hot-humid climate with high humidity in hot summer and cold winter zone (HSCW) of China. The moisture transfer may severely influence the conduction loads through exterior walls. In this paper, a coupled heat and moisture transfer model is developed and validated to investigate the thermal performance of exterior walls. The conduction loads through a typical exterior wall are used to evaluate the effect of moisture transfer on the thermal performance of exterior walls in HSCW zone of China. The results show that the peak cooling and heating loads are overestimated by 2.1–3.9% and 4.2–10.1%, respectively, when ignoring moisture transfer. In cooling season, the sum of the latent load accounts for 14.3–52.2% of the sum of the total load and the yearly latent load accounts for 4.9–6.1% of the yearly total load when considering moisture transfer. The total cooling, heating and the yearly load are underestimated by 9.9–34.4%, 1.7–4.0%, and 5.2–6.8%, respectively, when ignoring moisture transfer. The results indicate that ignoring moisture transfer causes significant discrepancy in predicting the conduction loads. A detailed model considering moisture transfer in building envelope is essential to accurately evaluate the building energy performance in HSCW zone of China. [ABSTRACT FROM AUTHOR]

SI (Skeleton and Infill) housing system can significantly improve residential adaptability and flexibility, and provides easier access to housing maintenance compared to traditional building structures. However the promotion of this system in China's building industry remains sluggish. By conducting an investigation and applying Factor Analysis method, this paper explored the factors that inhibit the promotion of SI housing system. Findings revealed that costs and benefits, technology and management, industrial chain and enterprise capacity, as well as policies and regulations are the four major factors that confine the application and widespread of SI housing system in China. In addition, Mean Score method was conducted to explore other critical factors for different stakeholders. The results indicate that the government sectors consider enterprise capacity and industry development as the main barriers while other stakeholders lay emphasis on government support and cost. These findings provide a valuable reference for different stakeholders to identify the major barriers, and make appropriate strategies to participate in promoting CSI housing system. [ABSTRACT FROM AUTHOR]

Abstracts China's building energy efficiency design standards have been always treated as the base of national energy conservation planning and industrial investment. However, they cannot fully achieve the expected benefits due to the energy rebound effect. This paper verifies the energy rebound effect in China's urban and rural residential buildings based on the LA-AIDS theory, and further estimates the building energy conservation by counterfactual analysis, catching the specific influences of rebound effect on building energy conservation and the corresponding residential building energy conservation potentials of China. The empirical results reveal that: (i) The rebound effect in the rural residential buildings is much larger than that in the urban residential buildings, where presenting the “back-fire” effect. (ii) The rebound effect in the rural residential buildings is weakening while it is enhancing in the urban residential buildings. (iii) Nationally, if energy policies including price polices, technological improvements as well as some other measures were implemented to avoid the rebound effect, we could have conserved about 20% electricity consumption in China's residential buildings each year. The magnitude increased by time to the highest level (107.66 GWh) in 2011, equivalent to the CO 2 emission reduction of 0.1 billion tons. [ABSTRACT FROM AUTHOR]

Thermal comfort evaluations in the built environment are essential to occupant's satisfaction and also building energy consumption. Traditionally, thermal comfort has been assessed by Fanger's PMV model that was developed based on extensive laboratory tests. However, it's been found that PMV predictions are not good in field studies, especially in buildings with natural ventilation. In this paper, machine learning (ML) algorithms were used to predicted occupants' thermal comfort votes (TCV) and thermal sensation votes (TSV), using 5512 sets of thermal comfort data collected in naturally ventilated residential buildings in fourteen cities in China. Environmental parameters, personal parameters, climatic types, and adaptive control measures were considered and used as input parameters for the ML model. It was found that environmental parameters (both outdoors and indoors), personal parameters (metabolic rate and clothing insulation), and climatic types all significant affect both TCV and TSV, while adaptive control measures only affect TSV but not TCV. Comparing with established models (PMV, ePMV and aPMV), the ML models had smaller errors in predicting TSV and TCV. Based on these results, we suggest that the ML, especially ANNs model was reliable in predicting occupants' TCV and TSV in naturally ventilated residential buildings, and performed better than traditional thermal balance based models. Moreover, using the new model, we found that acceptable temperature ranges in naturally ventilated buildings were far wider than the ASHRAE adaptive comfort zone, suggesting that appropriate models should be established based on local data. [ABSTRACT FROM AUTHOR]

• A series of typical residential building models were defined through statistic method. • The envelope's size, shape, thermal properties and opaque feature were determined. • The indoor space partition and function area distribution were also identified. • The models could serve as a standard platform for building energy simulation research. • The method can be applied to other regions and building types with sufficient data. With the rapid growth of urban population in the Pearl River Delta (PRD) region, the research on residential energy saving has attracted increasing attention. Typical buildings are useful tools for building performance simulation of residential district, which is of great significance for local green building-related research, policy formulation as well as market orientation. In this paper, the spatial information (building size, shape, area and amount of dwelling unit area) and the thermal properties of the envelope (such as window-to-wall ratios, shading coefficient, and the heat transfer coefficient) of about 120 residential districts were collected and statistically analyzed. Meanwhile, 120 residential districts are the actual data in the PRD region since 2010. The analysis method involved K-means, histogram and bubble diagram, box plot - bin mean method and slope method, which aims to remove outlier points and find representative value for each parameter, and define a series of typical residential building models. From the analysis result of 120 residential districts, which involved around 350 types of 1300 residential buildings and over 900 types of dwelling units, 7 typical residential building models were determined to be used in other research. [ABSTRACT FROM AUTHOR]

• Two thermal comfort investigations were conducted in severe cold area. • The thermal neutral temperatures derived from the linear regression model and logistic model were compared. • The relationship between probability of opening windows and temperature difference was developed. In recent years, the indoor air temperature in residential buildings for space heating rose gradually in the severe cold area of China. Would people feel comfortable in a warmer environment? This paper focuses on the appropriate indoor air temperature in winter. Two field investigations were conducted on the indoor thermal environment and human adaptation in residential buildings with district heating in Harbin during two winter seasons from 2011 to 2014. Ten apartments and their residents were chosen as samples in each investigation. The investigations included measurements of physical environmental parameters as well as subjective questionnaires. The results show that when the indoor air temperature was higher than 24 °C, people would have a sensitive response and preferred a lower temperature. An ordinal logistic regression model was used to examine the result of the linear regression model. The neutral temperature derived from the logistic model is 0.5 °C higher than that from the linear model and the adjusted neutral temperature is 0.8 °C higher than the linear model. Detecting whether people felt "cool" or not and "warm" or not is relatively accurate with the logistic model. It is not sensitive to judge whether people felt "neutral" in low air temperatures. Thermal neutral temperature is not a suitable set-point of indoor air temperature. In the severe cold area of China, the indoor air temperature of 20 °C is suggested as the standard for space heating in residential buildings in terms of comfort and energy saving. [ABSTRACT FROM AUTHOR]