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• A simple, large-scale fabrication of cooling paper via pulping and papermaking technology. • The cooling paper is facilely deconstructed and regenerated to architect the secondary cooler. • The cooling paper features a high solar reflectance of 94% and emissivity of 0.95. • The cooling paper shows the sub-ambient temperature drop of 6 ∼ 8.8 °C under directly solar radiation at daytime. Passive radiative cooling materials provide coldness without energy consumption for all-day thermal comfort by reflecting solar irradiation and emitting heat into the 3 K universe. However, the conventional radiative cooling materials involve complex multilayer structures and unsustainable polymers, showing the non-recyclable disadvantage, which induces resource waste and environmental issues. Herein, we reported a low-cost, scalable, and eco-friendly radiative cooling material (namely cooling paper), consisting of the delignified, fibrillated cellulose fibers and nano-sized hydroxyapatite (HA) via the mature pulping and papermaking process. The resulting cooled paper can be recycled, and it can be easily deconstructed to harvest cellulose fibers and HA, individually. The recovered source materials can be reused to prepare secondary products that show comparable performance to the original cooling paper, including a high solar reflectance of ∼94% and an infrared emissivity of ∼0.95 in the atmospheric transparency window. Such cooling paper enables superior cooling performance with the temperature drop of 6 ∼ 8.8 °C under directly solar radiation. Based on the EnergyPlus simulation, our cooling paper shows a average cooling energy saving of ∼29 % in buildings across China. The recyclable cooling paper with high cooling capability and scalability, as well as environmental friendliness, shows promising potential for sustainable energy-efficient buildings. [ABSTRACT FROM AUTHOR]

The rapid development of urbanization in China inevitably leads to a sharp increase in building energy consumption, and Passive House (PH) have received much attention in China in recent years. In this paper, the annual energy demand (AED) and summer discomfort hours (SUH) of PH are used as optimization objectives to establish a set of design solutions for multi-objective optimization (MTO) and economic analysis of a PH in Shandong Province, China. It is found that (1) the algorithm based on nearest neighbor component analysis (NCA) feature extraction applies to the sensitivity analysis of multivariate nonlinear high-dimensional data, and the NCA-GA-RBF neural network technique is proposed, which has significantly improved the goodness of fit and generalization ability for AED and SUH. (2) The NSGA-II genetic algorithm is used for the optimization search, and the results show that the overall improvement rates of AED and SUH are 25.5% and 21.6%, respectively, among the nine solutions after comprehensive evaluation; (3) Finally, the optimal scheme of energy saving and the optimal scheme of the economy are selected for economic evaluation. By comparing the economics of the two options and the improvement rates of AEDs and SUHs, the guidelines for design decision-makers are provided. In summary, the design scheme of this paper is forward-looking and reference-oriented and provides some reference suggestions for the development of PH in China. • The NCA algorithm is suitable for multivariate nonlinear sensitivity analysis. • NCA-GA-RBF has stronger and more stable generalization ability and accuracy. • In this paper, climate is the main factor affecting thermal parameters. • Global costs have a stronger economic interpretation. [ABSTRACT FROM AUTHOR]

The effective resistance and rapid recovery from external environmental risks has risen to be a social challenge in the accelerated urbanization process of China. However, the current measures for urban high-rise and high-density core area with high-volume pedestrians and high pollution are often focused on one-dimensional means, which cannot meet the multi-objective demands simultaneously. Therefore, this paper is aimed to explore a prevention-oriented route - a vertical pedestrian system for high-rise buildings based on scheme phase, with multiple objectives optimization of strengthening the ability of ecological order restoration and assisting occupants in recovering psychological and physiological injury from high-density environment in a relative fast speed. The feasibility and effectiveness have been verified by a complete technology route of scheme selection, numerical simulation and field measurements. The results show that, first, after the integration of secondary ground pedestrian system (SGPS) basic unit, the average predicted mean vote (PMV) improves 75.45%, the average air temperature declines 2.75 °C, and the average spatial integration increases 35.35%. Second, the optimal range of unit height difference in SGPS under hot-humid climate condition is suggested to be 6–9 storeys. Third, compared with single-sided "E-type" connection, the thermal comfort improves 70.49% and the indoor average PMV is optimized by 2.56%, with a more stable wind speed by using bilateral alternating "S-type" connection. Finally, compared with connections among low-integrated secondary ground units, the average integration is up to 6.98% with visual and path links of high-integrated-orientation. This paper objectively answers the question of whether and to what extent the combination of vertical greening and walking system contributes to ecological order restoration, which provides a new orientation for exploring the routes of maintaining urban ecological stability and optimizing environmental structure. • It evaluates the effect of SGPS on the high-rise and high-density environment. • It analyzes SGPS's effects from a multi-objective perspective. • The SPGS plays a positive role in environmental regulation and health promotion. • The union of walking system and ventilating shaft effectively integrate resources. [ABSTRACT FROM AUTHOR]

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]

By measuring practical temperature and performing questionnaire surveys, this paper investigates the energy consumption and existing indoor thermal condition in rural residential buildings during heating season in severe cold areas in northeast of China. Research is conducted on the characteristics of heating and energy consumption in rural residential buildings in severe cold areas from heating system such as Chinese “kangs”, rustic heaters, stoves and heated walls. The main results in the paper can be summarized as follows: (1) The remarkable characteristic of thermal environment in rural residential buildings is the uneven distribution of temperature both in one room and in different rooms; (2) Installation of insulation layers can effectively improve indoor thermal environment; (3) Income level of rural residents is the main factor that influences indoor thermal environment; (4) The main ways of heating are Chinese “kangs”, rustic heaters, stoves and heated walls in rural residential buildings in severe cold areas. These factors and laws obtained can influence the energy consumption in rural residential buildings in heating season in severe cold areas in northeast of China. [ABSTRACT FROM AUTHOR]

Aiming at the current situation in China with vast territory, diverse climate, and a big difference on thermal adaptation of the indoor thermal environment among the people in different regions, the paper analyzes the typical model research of thermal adaptation, and points out the features of three representative models and the ignored reason of physiological thermal adaptation, summarizes some results on field studies of thermal adaptation in China, induces three research directions about physiological indexes selection research, physiological thermal adaptation research and multivariate evaluation model research of thermal comfort based on the physical, psychological and behavioral adjustments. The paper proposes to explain the differences of physiological thermal adaptation in these different climatic regions and to further finds out the relations between all these differences and the physiological indexes. The goal is to establish physiological index to evaluate thermal comfort and to perfect the climate adaptation model which can give some advises to the architecture designers on how to realize the comfortable and energy-saving thermal environment. [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]

• BIM-DB can effectively simulate building performance parameters. • The PSO-RF-NSGA-III hybrid method can be used to predict and optimize building performance. • NSGA can simultaneously optimize energy consumption, carbon emissions and thermal comfort. • The optimal building parameters are different in different regions. Near-zero-energy-consumption buildings (NZEBs) are of great significance for sustainable development, and their design and research have attracted increasing academic attention. To drive and realize the energy saving design and achieve carbon emission and thermal comfort optimization of NZEBs, in this paper, an intelligent optimization method integrating the BIM-DB and PSO-RF-NSGA-III method is established. Multiobjective optimization problems involving NZEBs in four typical climate regions in China are explored. With a typical office building as an example, first, simulation calculations regarding the energy consumption, carbon emissions and indoor thermal comfort in the four climatic regions are performed based on orthogonal tests and BIM-DB. Second, the nonlinear mapping relationships between building design parameters and prediction targets are constructed with the PSO-RF model, which is trained with sample data. The obtained nonlinear mapping relations are used to establish the objective function of NSGA-III, and the multiobjective Pareto-optimal solution set is obtained with the developed PSO-RF-NSGA-III algorithm. Finally, the only optimal solution is determined by using the ideal point method, and reference near-zero-energy-consumption office building parameters are calculated for different climate regions. The conclusions are as follows. (1) The PSO-RF algorithm can efficiently predict building energy consumption, carbon emissions and thermal comfort. In the four regions, the goodness of fit of the three targets is greater than 0.94. (2) Multiobjective optimization can be performed with the proposed RF-NSGA-III intelligent optimization method. After optimizing multiple groups of optimization schemes and adopting energy saving measures, the energy consumption levels in the four climate regions are reduced by 39.72 %, 32.22 %, 26.94 % and 35.37 %, and the other goals are optimized. (3) Index calculations indicate that the optimized building design parameters meet the specified standards for NZEBs, and the main influencing factors and corresponding measures vary from region to region. [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]

• Indoor thermal environment and AC usage behavior was investigated for low-quality centrally heated dwellings. • 90% of AC trigger temperature is 15 ℃ for the living room and 14 ℃ for the bedroom. • The heating demand drivers of cool housing are identified by heteroskedasticity-robust Ordinary Least Square. • The study presents new knowledge for appropriate way to meet actual heating demand while reducing energy use. • Relationships between indoor temperature, heath and energy use are discussed. In northern China, district heating systems without terminal control typically serve thousands of end-users, thus inevitably some users suffer from insufficient warmth and others are overheated indoors due to hydraulic imbalances. This paper aimed to understand the indoor thermal conditions and the actual heating demand in low-quality centrally heated dwellings. The driving force of heating demand was analyzed based on a smartphone survey of 233 households in cold climates, and field measurements of winter indoor thermal environment and AC supplemental heating behavior were conducted in a sample of 13 cool dwellings. Logistic regression and heteroskedasticity-robust Ordinary Least Squares were adopted to assess AC usage patterns and driving forces of heating demand, respectively. New knowledge has been gathered regarding average temperatures of 17.4 ℃ and 16.8 °C in cool housing living rooms and bedrooms, respectively, outside the human thermal comfort zone. Simultaneously, intermittent and partial AC usage patterns induced by time and air temperature were observed in these cool end-users for the comfort. The average daily running time of AC devices was 2.0 h for the living room and 1.8 h for the bedroom. There were statistically significant base linking occupants' heating demands to education level, household income, tenure type, presence of children, thermal experience and heating system. However, it was not a significant factor for household size. In addition, a rebound effect of building energy efficiency improvements on the interior temperature was also noticed. The results of this study shed light on better and target-oriented residential internal temperature or heating system design for both thermal comfort requirements and energy-savings. [ABSTRACT FROM AUTHOR]

This paper aims to develop a green building meta-model for a representative passively designed high-rise residential building in Hong Kong. Modelling experiments are conducted with EnergyPlus to explore a Monte Carlo regression approach, which intends to interpret the relationship between input parameters and output indices of a generic building model and provide reliable building performance predictions. Input parameters are selected from different passive design strategies including the building layout, envelop thermophysics, building geometry and infiltration & air-tightness, while output indices are corresponding indoor environmental indices of the daylight, natural ventilation and thermal comfort to fulfil current green building requirements. The variation of sampling size, application of response transformation and bootstrap method, as well as different statistical regression models are tested and validated through separate modelling datasets. A sampling size of 100 per regression coefficient is determined from the variation of sensitivity coefficients, coefficients of determination and prediction uncertainties. The rank transformation of responses can calibrate sensitivity coefficients of a non-linear model, by considering their variation obtained from sufficient bootstrapping replications. Furthermore, the acquired meta-model with MARS (Multivariate Adaptive Regression Splines) is proved to have better model fitting and predicting performances. This research can accurately identify important architectural design factors and make robust building performance predictions associated with the green building assessment. Sensitivity analysis results and obtained meta-models can improve the efficiency of future optimization studies by pruning the problem space and shorten the computation time. [ABSTRACT FROM AUTHOR]

Thermoregulation models of the human body have been widely used in thermal comfort studies. The existing models are complicated and not fully verified for application in China. This paper presents a simplified thermoregulation model which has been statistically validated by the predicted and measured mean skin temperature in warm environments, including 21 typical conditions with 400 Chinese subjects. This model comprises three parts: i) the physical model; ii) the controlled system; and iii) the controlling system, and considers three key questions formerly ignored by the existing models including: a) the evaporation efficiency of regulatory sweat; b) the proportional relation of total skin blood flow and total heat loss by regulatory sweating against body surface area; and c) discrepancies in the mean skin temperatures by gender. The developed model has been validated to be within the 95% confidence interval of the population mean skin temperature in three cases. [ABSTRACT FROM AUTHOR]

Traditional residence is an important part of our culture and heritage of ancient architecture, which contains rich experience in the construction of ecological. But limited at the construction technology and economic level, traditional residence also has shortcomings. Therefore, in addition to heritage of its ecological wisdom, syndrome differentiation treatment should be used. In this paper, on the basis of the energy-saving reconstruction project located in Anju town of Chongqing, its energy-saving advantages and disadvantages were analyzed. Then methods of traditional residence in energy-saving were proposed, which not only met the energy requirements and economics, but also improved the thermal comfort significantly. Analyzing the annual energy consumption of its before-after renovation by Design Builder. The building energy saving rate was 54.36% after renovation. [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]

The buildings in the hot summer and cold winter region in China do not install space heating systems traditionally. However, with the development of the economics, the thermal comfort is getting in demand. Although heating technology has a long history and becomes quite mature in the severe cold area and the cold region in China, it is not fit for the hot summer and cold winter region. In the paper, based on the analysis of the local climate features and the properties of the local buildings, several heating systems are introduced and compared. The results show that the central heating system which is commonly applied in North China is not suitable for the buildings in the hot summer and cold winter region in China; the warm air heating system and the floor heating system are the suitable space heating forms; the heat pump systems including the air source heat pump system and the surface water heat pump and the ground source heat pump system are the appropriate choices as the heat source for the hot summer and cold winter region. [ABSTRACT FROM AUTHOR]

This study aims to investigate thermal environment and occupant local thermal sensation in offices with cooling ceiling. A field survey combining environment measurements and questionnaires was conducted in offices in Zhuhai, China. The obtained results indicated that compared with experimental conditions, occupants in real crowded offices experienced warmer environment because the mean radiant temperature (MRT) was higher than the air temperature due to the shelter effect of indoor furniture etc. MRT also showed higher correlations with both overall thermal sensation (OTS) and overall thermal comfort (OTC) than air temperature because a great part of heat transferred through radiation. Air temperature showed linear correlation with the ceiling temperature when cooling ceiling could fully handle the cooling load, but supplementary air cooling was also necessary for radiant cooling systems in real offices. Moreover, local thermal sensation (LTS) of different body parts showed great differences due to many factors such as clothes and adaptive behaviors, and it significantly influenced both OTS and OTC. Particularly, head, hand, leg and foot had considerable effects on OTS while head and leg showed influences on OTC. In addition, this paper also validated against some important results of previous studies and provided references for future work. [ABSTRACT FROM AUTHOR]

Residential sector is one of the greatest contributors to national CO 2 emissions in China, contributing towards 10.3% in 2012. With rapid urbanization and development in the future, it will inevitably keep increasing, thus it is of great importance to study the characteristics of residential carbon emissions. This paper investigates the carbon emission evolutions during 1996–2012 in urban and rural residential sector, from an end-use perspective. Especially, comprehensive emission factors of electricity and heat in terms of time-series are taken into consideration, and five end-use activities are analyzed. The key findings are: in urban areas, carbon emissions from private transportations grew the fastest and it still has great growth potential in the medium and short term; carbon emissions from space heating and cooling; and cooking and water heating accounted for the largest, with about 40% and 30%, respectively. The growth rates of these are also fast, therefore controls to maintain high standards for degree of comfort are needed. In rural areas, carbon emissions from private transportations also grew fast, even higher than that of urban residents, so it should develop rural public transportation; the rapid growth of carbon emissions from home appliances and lighting reflected the improvement of living conditions and modernization; carbon emissions from space heating and cooling accounted for the largest proportion and has great potential in the future. [ABSTRACT FROM AUTHOR]

• The temporal and spatial distribution of thermal comfort of four typical block models of a cold-region city was indicated by using PET simulation. • The important microclimate factors affecting the thermal comfort of the blocks were verified through ENVI-met simulation and Pearson correlation analysis. • The improvement strategies of block thermal comfort are proposed based on the visual models. A block is an urban construction of land surrounded by roads and its internal buildings and environment. It is an essential element of modern cities and the most direct way to perceive the urban living environment. The thermal comfort of a block is a crucial indicator for building a healthy and comfortable urban life. This study examined Dalian, a cold-region city in China, to put forward research on thermal comfort improvement strategies. In this paper, four typical blocks were selected to simulate the microclimate by ENVI-met, and the physiological equivalent temperature (PET) was calculated. Through the simplified model, the thermal comfort building strategy suitable for Dalian was explored, and the effectiveness was verified. The results show that direct solar radiation and wind speed are the critical factors for the thermal comfort of the settlements residents. The building orientation, sunshine spacing coefficient, and building layout will affect the thermal environment of the block through these two factors. The outdoor thermal environment in Dalian can be improved by adjusting the orientation of buildings away from the traditional south direction, increasing the sunshine spacing coefficient, dislocating buildings, or adopting a peripheral-type building layout. This study can provide a scientific basis for building healthy and comfortable urban living environments and block development and renovation decisions. [ABSTRACT FROM AUTHOR]

A large part of energy consumption in homes, offices and commercial spaces is related to Heating, Ventilation and Air-conditioning (HVAC) devices. The effective parameter on the consumption of HVAC systems is internal heat gains that arise from occupants, electric equipment and lighting. In order to reduce the energy consumption of these systems, internal heat gains should be predicted accurately. Since there are few investigations performed on the prediction of internal heat gains, in this paper, three predictive models, namely multiple regression model, Levenberg–Marquardt back-propagation (LM-BP) model and similar days method based on combined weights, have been deployed. By assessing the influential factors on internal heat gains, fundamental theories, structures, equations and parameters of these models are thoroughly proposed. To examine the prediction techniques, an office building in China was considered. It was found that all the proposed models have high accuracy; however, the LM-BP neural network showed the most precision among other models with RMSE = 15.59, MAE = 10.16 and MAPE = 6.35. This model had a higher agreement with the actual internal heat gains compared to the predetermined working programs in the ASHRAE standard 90.1. The proposed models used in this study can lead to providing a theoretical base for scholars and engineers to improve the predictive control of HVAC systems, which plays an important role in enhancing thermal comfort, saving energy of residential buildings. [ABSTRACT FROM AUTHOR]

• A new interlayer ventilated PCM component was proposed and developed. • A new PCM component model was established in TRNSYS. • The interlayer ventilated PCM component can increase the minimum temperature of the room by more than 2℃ at night. The application of solar energy for heating in buildings has the problem of heat supply and demand time mismatch. In this paper, an interlayer ventilated phase change material (PCM) component (IVPC) that can be coupled with solar air collector was proposed. The thermal performance of IVPC was tested through experiments. The results show that if IVPC completes latent heat storage, the optimal air supply temperature of solar hot air is 35 ∼ 45℃ and the air supply speed is 3 ∼ 4 m/s. The latent heat release time can be maintained for 5 h. To build an IVPC coupled with solar air collector system (IVPSS) in TRNSYS, to simulate the improvement effect of IVPC on heating temperature fluctuations, a rural building in cold regions of China was selected. IVPSS can maintain the indoor temperature of the building in the range of 8 ∼ 16℃. Compared with buildings without IVPSS, the room temperature throughout the day can be increased by 5 ∼ 8℃. IVPC can effectively use solar energy to peak load shifting, reduce room temperature fluctuations, improve indoor thermal comfort, and provide solutions for farmhouses in cold regions to use clean energy for heating. [ABSTRACT FROM AUTHOR]

Abstract: In sub-tropical city of Hong Kong where summer is hot and humid, the usage of outdoor spaces is often hindered due to thermal discomfort. In order to improve the thermal comfort of the outdoor environment and to make urban outdoor spaces delightful places for people to use and enjoy, better understanding of the thermal perception of people is needed. This paper presents the results of an outdoor thermal comfort study conducted in Hong Kong. The findings of the study reveal that air temperature, wind speed and solar radiation intensity are influential factors in determining the thermal sensation of people outdoor. Based on our analysis, the neutral physiological equivalent temperature (PET) in summer in Hong Kong is around 28°C. Under shaded condition, a wind speed of 0.9–1.3m/s is needed for a person in light clothing to achieve neutral thermal sensation in an urban environment. This understanding can contribute towards establishing wind performance standards for thermal comfort in hot and humid tropical and sub-tropical cities. [Copyright &y& Elsevier]

Abstract: A number of radiant heating/cooling systems have been applied in Mainland China in recent years for its improved thermal comfort and inherent energy saving potential. Because the systems require relatively higher temperatures for cooling and lower temperatures for heating, many natural low-grade energy sources can be directly or indirectly used. However, because of a lack of information about prior practical projects, a number of difficulties in design, construction and management of the systems have been encountered, and energy efficiency is not necessarily achieved in all situations. This paper reviews the practical applications in four major projects involving different building types located in different climatic cities and presents the associated considerations in system design. Other factors affecting the energy efficiency of the systems are identified, such as the spatial convection and radiation heat transfer processes in indoor environments and the envelope thermal properties. Further studies are needed to achieve system optimization and to realize the full energy saving potentials of radiant systems by developing analytical design methods and monitoring the actual energy use of such systems in completed projects. [Copyright &y& Elsevier]

Abstract: In Hong Kong, conventional air-conditioning (AC) systems cause a high energy consumption and poor indoor thermal comfort. This paper investigated the AC load profiles of three typical local commercial buildings, i.e. office, hotel and retail, and examined the energy consumption of liquid desiccant cooling system (LDCS) for these buildings. Simulation results showed that the cooling load contributed to more than 98% of total annual load, with high latent load proportion from March to September. The high reheating ratio, i.e. from 60% to 90%, is found to be the main reason for the poor thermal comfort. Therefore, the LDCS which could handle sensible and latent loads separately was proposed. However, the electricity-driven LDCS was found not suitable for local commercial buildings. significant energy saving could be achieved by the solar-assisted LDCS system with thermal storage, when the installation area for solar collectors is larger than the minimum required one, i.e. 9.7m2/(kWm−2) for office and 12.7m2/(kWm−2) for hotel buildings. Energy saving of different system types with different installation areas was also studied. The solar-assisted LDCS shows more energy saving in winter but less in summer. Results and conclusions can be useful for researchers and local engineers. [Copyright &y& Elsevier]

Abstract: According to the climatic characteristics in Tianjin where lies in the cold climate regions of China, the passage describes a technique called adjustable external blinds which is to enhance the architectural thermal comfort degree. This technique based on a series of experiments of architectures with different orientations in local climatic condition and numerical analysis of thermal environment with finite element method afterwards. This paper shows that alumina shutter has great advantages which can isolate indoor heat greatly in summer of Tianjin, and some optimization measures has also been adopted in order to improve indoor thermal comfort. [Copyright &y& Elsevier]

Abstract: A traditional Chinese heating system, the Chinese Kang, is used by 175 million people in detached houses in the rural regions of China, especially in Northeast China. This system utilizes biomass such as corn stalks, straw, corncob and energy plants as the heat sources. The objective of this paper is to establish a set of models to simulate the energy performance of the Kang heating system in one Chinese detached house. An experimental field study was carried out to collect practical parameters in a newly constructed Chinese detached house. The dynamic performance of the Kang heating system was simulated by using IDA-ICE 4.0 embedded with an empirical model built in the field study. The results show that the simulation can obtain good overall agreement with the field measurement results. It was confirmed that the Kang model created by IDA-ICE 4.0 is capable of simulating the performance of the Kang system and of calculating energy consumption in the detached house. Moreover, the result reveals that the thermal environment in the present Chinese detached house is still poor during the severe cold season if only the Kang system is used to heat the whole house. [ABSTRACT FROM AUTHOR]

Abstract: A year-long field study of the thermal environment in university classrooms was conducted from March 2005 to May 2006 in Chongqing, China. This paper presents the occupants’ thermal sensation votes and discusses the occupants’ adaptive response and perception of the thermal environment in a naturally conditioned space. Comparisons between the Actual Mean Vote (AMV) and Predicted Mean Vote (PMV) have been made as well as between the Actual Percentage of Dissatisfied (APD) and Predicted Percentage of Dissatisfied (PPD). The adaptive thermal comfort zone for the naturally conditioned space for Chongqing, which has hot summer and cold winter climatic characteristics, has been proposed based on the field study results. The Chongqing adaptive comfort range is broader than that of the ASHRAE Standard 55-2004 in general, but in the extreme cold and hot months, it is narrower. The thermal conditions in classrooms in Chongqing in summer and winter are severe. Behavioural adaptation such as changing clothing, adjusting indoor air velocity, taking hot/cold drinks, etc., as well as psychological adaptation, has played a role in adapting to the thermal environment. [Copyright &y& Elsevier]

Abstract: The purposes of this paper are to analyse energy consumption characteristics and to find out influence factors of residential energy consumption in summer in typical cities of China. The investigated residences were located in seven cities of five architecture thermotechnical design zones. Questionnaire surveys revealed housing unit characteristics, household characteristics, the possession and utilization of domestic energy consuming appliances and indoor thermal environment in summer. Energy consumption analyses show that summer energy consumption amounts in different cities bear distinct regional characteristics: the household amounts of electricity use are largest in Hongkong, and the values are smaller but still at a high level in Beijing, Shanghai and Changsha, and at the smallest level in Kunming, Harbin and Urumqi, while the difference in gas use is small among these cities. Influence factor analyses show that city locations, housing unit characteristics, the utilization of space coolers and water heaters, household characteristics, and subjective evaluation of indoor thermal environment all contribute to the residential energy consumption in summer when taking all the families in the seven cities as the sample collectivity, while detail analyses for separate cities shows each city has its own characteristics. In Shanghai, the satisfaction rate of thermal environment, the possession and operation of air conditioners and housing unit characteristics greatly affect the summer energy consumption, but the electrical fan is judged as the non-influence factor, while in Urumqi, the possession and operation of electrical fans and the categories of water heaters have remarkable effect, and the influence of housing unit characteristics is also distinct, but the number of air conditioners and their usage contribute little to energy use due to the cool climate. [Copyright &y& Elsevier]

Abstract: The paper presents a field study of occupants’ thermal comfort and residential thermal environment conducted in an urban and a rural area in Hunan province, which is located in central southern China. The study was performed during the cold winter 2006. Twenty-eight naturally ventilated urban residences and 30 also naturally ventilated rural residences were investigated. A comparative analysis was performed on results from urban and rural residences. The mean thermal sensation vote of rural residences is approximately 0.4 higher than that of urban residences at the same operative temperature. Thermal sensation votes calculated by Fanger’s PMV model did not agree with these obtained directly from the questionnaire data. The neutral operative temperature of urban and rural residences is 14.0 and 11.5°C, respectively. Percentage of acceptable votes of rural occupants is higher than that of urban occupants at the same operative temperature. It suggests that rural occupants may have higher cold tolerance than urban occupants for their physiological acclimatization, or have relative lower thermal expectation than urban occupants because of few air-conditioners used in the rural area. The research will be instrumental to researchers to formulate thermal standards for naturally ventilated buildings in rural areas. [Copyright &y& Elsevier]

[Display omitted] • Coal combustion, ASHP, solar heating, gas furnace and electric heating are compared. • Thermal comfort, economic, energy consumption and environmental benefit are evaluated. • Different PMV-PPD are set, and the design thermal index is amended. • The optimal heating mode of rural buildings in cold areas is found. In recent years, space heating modes are diversified. In the early stage of space heating design, we should reasonably evaluate and optimize the heating mode in order to get a better heating effect. In the past, the evaluation of different heating modes was mostly single evaluation. In this paper, the thermal comfort, economic, energy consumption and environmental benefit are comprehensively evaluated. Four heating modes in the "Coal to electricity" project of China are compared with coal combustion. The modes are ASHP (Air Source Heat Pump), solar heating, gas furnace and electric heating. Based on PMV-PPD, a more reasonable design thermal index of 35.18 W/m2 is obtained. The matched capacity and operation of heating system are optimized. The results show that ASHP combined with floor radiation heating is the best space heating mode in cold areas of China. The comprehensive rate of the four evaluations is 89.64%, and its thermal comfort is the best. For a 120 m2 house in Lanzhou, after the transformation of traditional coal burning heating mode, the static payback period is 6.9 years. The actual energy consumption reduction of society is 2,769 kg/year. The reduction of CO 2 emissions is 4,014 kg/year. [ABSTRACT FROM AUTHOR]

Indoor thermal environment design parameters have a significant impact on human thermal comfort, health and building energy consumption. The methods of determining indoor thermal environment design parameters in China and around the world are mainly based on the PMV model. This method often results in certain errors deviations from the actual situation and has difficulty reflecting the differences in the thermal environmental requirements in different climate regions, seasons, building types, etc. This paper proposes a data-driven method based on Chinese Thermal Comfort Database and uses a logistic regression to obtain the indoor air temperature range that 80% of occupants find thermally acceptable under different conditions. The results indicate that the prediction of this model are in good agreement with the actual data and have as higher accuracy in predicting the percentage of thermal acceptability than a linear regression method. This model shows that different regions, seasons, and building types have different acceptable temperature ranges and that the acceptable air temperature ranges are on average 2.0 °C wider than the ISO 7730 and 0.7 °C wider than the GB50736-2012. This method is conducive to the determination of air temperature thresholds and better reflects people's equirements for thermal environment under different conditions. [ABSTRACT FROM AUTHOR]

The building envelope performance significantly influences the building energy consumption, and the major influencing factors of the building envelope include the external wall U-value, external wall solar absorptance, roof U-value, roof solar absorptance, external window U-value, and window-to-wall ratio. This paper proposed a framework that integrates Building Information Modeling (BIM) with LSSVM (least square support vector machine (LSSVM) and non-dominated sorting genetic algorithm-II (NSGA-II) to study the influence of building envelope parameters on building energy consumption and discover the best design. The DesignBuilder (DB) is used to perform energy consumption simulation and orthogonal experiment to obtain the sample data set. The LSSVM is utilized to learn the data set to establish a prediction model between the building envelope and energy consumption, which is used as the fitness function of the building energy consumption in NSGA-II. With the objective of minimizing building energy consumption and maximizing the indoor thermal comfort (measured by predicted mean vote or PMV), an NSGA-II multi-objective optimization model is established. The Pareto front is obtained through calculation, and the optimal combination of building envelope parameters is discovered using the ideal point method. A case of a proposed school building in China is used to demonstrate the feasibility and effectiveness of the developed framework, the results show that: (1) The LSSVM has great ability to predict building energy consumption, achieving an accurate prediction with a goodness-of-fit of 0.9549 and an RMSE of 0.0273; (2) The optimized envelope design parameters of the proposed building are presented, including the External wall U-value is 0.2, the External wall solar absorptance is 0.55, the Roof U-value is 0.2, the External window U-value is 0.4166, the External window U-value is 1, the Window-wall ratio is 0.215. (3) The developed LSSVM-NSGA II hybrid approach can effectively improve the building's energy consumption and thermal comfort with the building energy consumption reduced by 10.6% and the thermal comfort increased by 32.2% than the initial values, respectively. The proposed LSSVM-NSGA II framework is able to optimize building envelope design parameters than its precedent, which can provide effective thinking for similar problems. • LSSVM-NSGA-II hybrid method can predict and optimize the building energy consumption. • The energy consumption prediction surrogate model trained by LSSVM is an efficient NSGA-II fitness function. • NSGA can effectively reduce building energy consumption and improve thermal comfort at the same time. [ABSTRACT FROM AUTHOR]

• Detailed analysis on the application of radiant cooling systems in China with regard to policies, standards, and engineering. • Mechanism analysis of a radiant cooling system based on occupant comfort and energy savings. • Discussion of the research methods of the radiant heat transfer process for radiant cooling. • The applied potential and the existing issues of radiant cooling systems in China. Radiant cooling (RC) systems have attracted more attention due to their advantages of better thermal comfort and higher energy saving potential compared with the conventional cooling systems in China. This paper comprehensively reviews the current status of RC systems in terms of their application and mechanism research. First, current policies and standards of RC technology applications are sorted out. Then, the current application cases and existing engineering difficulties for RC technologies are discussed in China. This shows the degree of the adaption problem of RC technology in China due to the issues of condensation, fewer natural cooling sources, etc. Furthermore, the energy-saving potential of RC technology indeed does not achieve the expected objectives in China, according to most of the conclusions of previous research studies. The key reason for this lies in the change of heat exchange method to RC technology. Current methods are often limited in analyzing the impact of this change. Then, the special characters are reviewed and discussed in relation to topic of comfort and energy saving. Additionally, a novel analyzing method is proposed for solving the problems comprehensively. Finally, this review suggests future areas of research directions and methods. It will be conducive to a deeper understanding of design and application of RC systems for researchers and policymakers. [ABSTRACT FROM AUTHOR]

• Traditional Chinese kang systems are reviewed and compared. • Improved kang systems are summarized and compared. • Possible directions for further study of Chinese kang are suggested. Chinese kang, which serves as the main space heating equipment in rural residences of cold regions of China, has received increasing attention due to people's increasing requirements of thermal comfort and concerns about indoor air environment in recent years. Most of the existing studies focused on one specific type of Chinese kang by using experimental or numerical methods to investigate the system's energy performance and its effect on the indoor environment. Therefore, there is a lack of comprehensive review of all the existing types of Chinese kangs. This paper firstly classifies the traditional Chinese kangs into three categories according to their culture and ethnic background. Secondly, the detailed construction, flue modality and thermal performance of the three kang systems are reviewed and compared. Thirdly, some recently proposed improved kang systems are introduced and analyzed. Finally, based on the review results, several possible research opportunities are suggested to guide future research on Chinese kangs. [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]

• 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]

• PMV overestimated the thermal sensation of students. • Students preferred cooler thermal environment. • A higher percentage of students felt local thermal discomfort. • The lower limit for 80% acceptability determined by TAV could be 19 ℃. • If indoor design temperature is 19 ℃, 3.46% of annual heating load can be saved. A classroom thermal environment directly not only influences students' thermal comfort but also energy-saving. Numerous studies indicate that students' actual thermal comfort is different from the PMV and adaptive model predictions, and the current thermal comfort standards could not be applicable for the classroom thermal environment design and evaluation. This paper aims to study the university students' general and local thermal comfort by a field survey conducted in a classroom during the heating season in Taiyuan, China. The results indicated that PMV overestimated the thermal sensation of students. Thermal acceptance vote (TAV) defined the widest acceptable temperature range, and the lower limit for 80% acceptability could be 19 ℃ in Taiyuan. Students preferred a cooler than a neutral environment. The indoor design temperature determined by the heating load duration curve (LDC) was about 21.85 ℃. If the indoor design temperature could decrease from 21.85 ℃ to 19 ℃, 3.46% of the annual heating load could be saved. Moreover, although a majority of students found the environment general thermal acceptable, a higher percentage of students felt local thermal discomfort. Local thermal comfort should be a critical issue for the classrooms' thermal environment improvement. [ABSTRACT FROM AUTHOR]