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Solar irradiance and daylight illuminance are essential for solar energy and daylighting designs. Recently, the International Commission of Illuminance (CIE) adopted 15 Standard Skies to represent the possible sky-diffuse luminance and radiance distributions. Such distributions would improve the solar irradiance and daylight illuminance estimations for the building envelope and photovoltaic panels in any directions. The important issue is whether the sky conditions could be correctly identified by the available variables. Previously, many climatic parameters including sky luminance distributions, vertical diffuse irradiance and illuminance were proposed for identifying sky conditions. However, such data may not always be available from the routine measurements of a weather station. This paper proposes an approach to interpreting the sky conditions using the variables that are readily accessible from meteorological stations for many years. The approach appropriately identified 83.2% of the 3 typical overcast, partly cloudy and clear skies, and further 62.7% of the 15 individual CIE Standard Skies for Hong Kong. The %RMSE of the vertical solar irradiance and daylight illuminance estimated by the approach was found less than 23%. The results show that the proposed approach would be reliable for sky classification.

The energy saving and electricity production schemes for a school building in hot and humid climate were studied by a building energy package eQUEST. High-performance building envelops, energy-efficient air-conditioning systems and lighting fixtures were employed to save energy consumption and building integrated photovoltaic (BIPV) panels were adopted to meet the energy needs. The annual electricity demand was 300 MWh, and 97.5% of it can be supplied by the vertical BIPV facades. Further PV installations on the roof can generate more electricity to balance the energy use. The results show that school block is possible to achieve the zero building energy consumption.

Prediction of the daylight level for any point within an indoor space is important in daylighting analysis. Recently, the International Commission on Illumination (CIE) has adopted a range of 15 standard skies covering the whole probable spectrum of usual skies found in the world. In densely-built urban cities, the exterior obstructions may substantially reduce the amount of daylight entering to the building interior. Through exhaustive investigations, we proposed various daylight computation tools for buildings under different obstructed overcast and non-overcast skies. This paper reviews the daylight factor (DF) based metrics and gives an overview of the latest dynamic daylight metrics, and generalizes the calculation procedures for estimating the internal daylight under the unobstructed and obstructed 15 CIE Standard Skies. The merits and limitations of the calculating procedures on DF-based metrics are discussed. The findings could be globally adopted and useful to students and building professions conducting daylighting studies and designs.

The paper studies the horizontal global, direct-beam and sky-diffuse solar irradiance data measured in Hong Kong from 2008 to 2013. A machine learning algorithm was employed to predict the horizontal sky-diffuse irradiance and conduct sensitivity analysis for the meteorological variables. Apart from the clearness index (horizontal global/extra atmospheric solar irradiance), we found that predictors including solar altitude, air temperature, cloud cover and visibility are also important in predicting the diffuse component. The mean absolute error (MAE) of the logistic regression using the aforementioned predictors was less than 21.5 W/m2 and 30 W/m2 for Hong Kong and Denver, USA, respectively. With the systematic recording of the five variables for more than 35 years, the proposed model would be appropriate to estimate of long-term diffuse solar radiation, study climate change and develope typical meteorological year in Hong Kong and places with similar climates.

The estimation of solar heat gain via vertical fenestration is important in energy-efficient building design and operation especially for subtropical Hong Kong. Being one of the most populated cities in the world, buildings in Hong Kong tend to be densely constructed. In this regard, the shading effect of surrounding buildings could significantly limit solar radiation from the sun and sky to the window while certain amount of solar radiation would be reflected from the opposite facades. This paper presents a calculation approach to compute solar radiation on obstructed fenestration for both overcast and non-overcast skies. Performance of the proposed method is evaluated by comparing with simulated results of a sophisticated lighting program and field measurements. The findings are essential for the assessment of both active and passive building energy saving techniques including shading and building integrated photovoltaic systems in metropolitan environment.

Solar irradiance data particularly on inclined planes are crucial to solar energy applications and energy-efficient building designs. However, the basic solar data for the planes of interest are not always readily available. Recently, the CIE (International Commission on Illumination) adopted a range of 15 standard skies which provide a good overall framework for representing the actual sky conditions. Each sky represents a unique sky-diffuse distribution. Upon the classification of the standard skies, the solar irradiance data at the plane of interest can be computed. This paper presents a method to estimate the solar irradiance on inclined plane based on the CIE Standard Skies. Data recorded in Hong Kong from the end of February to early June in 2015 were used to validate the calculation procedures. The results show that the approach can accurately estimate solar irradiance on inclined planes.

Field investigations and testing on thermal comfort were conducted in Eastern China including 8 representative cities of 4 climate zones of severe cold, cold, hot summer and cold winter, hot summer and warm winter etc. Both subjective questionnaire survey in terms of thermal sensation vote (TSV) and objective on-site measurements were carried out. Clothing levels during summer and winter in 4 climate zones were obtained, and correlations between clothing insulation against operative temperature and outdoor temperature were found, different adaptive models of climate and comfort indoors were developed as well. The energy savings for cooling of indoor design temperature (with and without adaptive model) were calculated in Beijing, Shanghai and Guangzhou, and the total percentage of saving is about 5%, 6.5% and 8%, respectively.

Vertical sky diffuse illuminance data are important for architecture and daylighting designs. In 2003, the International Commission on Illumination (CIE) adopted a range of 15 standard skies representing the actual sky conditions in the world. This paper studies an approach to computing the vertical sky component (VSC) under the 15 CIE Standard Skies. Regression equations for calculating the VSC under various CIE skies based on the scattering angles (χ) were developed to estimate the vertical daylight illuminance on building façades. The performance of the proposed numerical approach and the regression equation are assessed against the results obtained by computer simulations. Our findings show that the VSC data determined by the numerical method and the regression equation are in good agreement with the simulated results. Our research has provided a simple tool for estimating the vertical daylight illuminance under various sky conditions.

In a well day-lit space when the daylight intensity is far more than the required value, photoelectric switching can result an excellent energy saving. However, a problem with the switching control type is the frequent and rapid switching of lights on and off, particularly during the unstable sky conditions when daylight levels are fluctuating around the switching lighting level. This can annoy occupants and lessen lamp life. This paper studies the simple and a few variants of photoelectric switching controls namely standard, differential, switching time delay, daylight time delay and solar reset types which can affect the number of switching operations and the corresponding lighting energy use. For a given time delay, daylight linked time delay performed better than switching linked time delay in terms of the number of switching operations. Several mathematical expressions were established to predict the lighting energy savings at various atrium floors. The findings provide important information and insight into the effects of different switching controls in terms of energy savings and real-time operations.

Summer and winter thermal discomforts in the major climate zones and sub-zones of the Koppen–Geiger world climate classifications during the 21st century were investigated and compared with those in the 20th century. Compared with the 20th century, frequency of distribution of the comfort index for the 21st century shows a distinct decrease in winter thermal discomfort and increase in summer thermal discomfort under the low and medium forcing emissions scenarios. Based on zone-average analysis, decreasing trends of cumulative cold stress and increasing trends of cumulative heat stress have been observed in all the major climate zones and sub-zones. There is an overall increase in energy use for space conditioning for all the sub-zones in equatorial climates, and an overall reduction in all the snow and polar climates sub-zones. In arid and warm temperate climates, the hot sub-zones have an increase in the overall energy requirements whereas the cold/warm sub-zones have a reduction. Locations within the hot summer sub-zones in warm temperate climates will become much more cooling-dominated, and there are significant increases in cumulative heat and proportional stresses in the hot summer sub-zones in snow climates. Implications for energy use and carbon emissions are discussed and mitigation/adaptation measures suggested.

Renewable energy plays a crucial role in replacing major part of fossil fuels to generate sustainable, inexhaustible, clean, and safe energy. In Hong Kong, solar energy has been identified suitable for wide-scale applications. Photovoltaic (PV) and solar water heating (SWH) facilities are the two promising solar-based conversion technologies. Electricity and hot water generations via solar energy means fossil fuel saved together with the likely pollutants and greenhouse gases reductions. However, there are a number of barriers including high initial cost and large installation space required. This paper studies the cost, energy, and environmental issues when PV and SWH systems are widely used in Hong Kong. The energy expenditures in the forms of electricity, gas, and hot water, and the global solar radiation in Hong Kong were analyzed. The total required land areas, the financial implications, and the environmental benefits for such solar energy applications were estimated and reported. Practical application: Solar energy plays an important role in replacing fossil fuels to generate electricity without emitting pollutants and requiring no fuel. This paper analyzes the energy, financial, and environmental aspects for solar thermal and solar electric installations. The findings in this study provide the information when active solar energy systems are widely applied in Hong Kong.

Buildings account for about 40% of the global energy consumption and contribute over 30% of the CO2 emissions. A large proportion of this energy is used for thermal comfort in buildings. This paper reviews thermal comfort research work and discusses the implications for building energy efficiency. Predicted mean vote works well in air-conditioned spaces but not naturally ventilated buildings, whereas adaptive models tend to have a broader comfort temperature ranges. Higher indoor temperatures in summertime conditions would lead to less prevalence of cooling systems as well as less cooling requirements. Raising summer set point temperature has good energy saving potential, in that it can be applied to both new and existing buildings. Further research and development work conducive to a better understanding of thermal comfort and energy conservation in buildings have been identified and discussed. These include (i) social-economic and cultural studies in general and post-occupancy evaluation of the built environment and the corresponding energy use in particular, and (ii) consideration of future climate scenarios in the analysis of co- and tri-generation schemes for HVAC applications, fuel mix and the associated energy planning/distribution systems in response to the expected changes in heating and cooling requirements due to climate change.

Information on solar availability is crucial in the study of both passive building designs and active solar energy systems. There are still many locations within different climate zones worldwide that do not have solar radiation measurements. Correlation between solar radiation and the more commonly measured meteorological variables such as temperature and sunshine hours is useful for locations with no measured solar radiation data. This is also useful for locations with measured solar radiation data, in that any missing data due to equipment breakdown or malfunction can be modelled. Global solar radiation (GSR) was modelled for 96 cities in different climate zones across China using artificial neural networks (ANNs). The novelty of this study is the climate zone approach, by which locations with similar climates were modelled together. Climate classification was based on both the traditional thermal climates and the solar climates. Two sets of models were developed based on measured diurnal temperatures and sunshine hours. Model performance in terms of the predictive power of ANN solar radiation models was evaluated through the Nash-Sutcliffe efficiency coefficient (NSEC). Error analysis of the predicted solar radiation as compared with the measured data was also conducted for each of the 96 cities.

Solar energy is the most popular resource for power generation among the various available renewable energy alternatives. Solar radiation data are important for solar photovoltaic (PV) systems and passive energy-efficient building designs. Due to the unavailability of measurement in rural locations, solar radiation prediction models are required. In recent years, the Artificial Neural Networks (ANN) were successfully used for predicting solar radiation. However, previous works indicated that the ANN techniques were mainly focusing on prediction of monthly average or daily solar radiation, a few of them were modelled for predicting solar irradiance in hourly basis. In this study, prediction models of global solar irradiance on a horizontal surface will be developed based on neural-network techniques. Hourly meteorological variables between 2012 and 2015 acquired from the measurements made by local meteorological station were used for the study. To consider the effectiveness of individual predictors, different combinations of input variables were analysed using the Levenberg-Marquardt (LM) algorithm. Finally, equations were modelled by regression based on the important predictors. The developed models were used to estimate the global irradiance and assessed against measurement results.

In subtropical Hong Kong, a certain amount of electricity is used to create visually comfortable interior spaces through electric lighting, which is the second major electricity-consuming item in commercial buildings, accounting for 20–30% of total electricity use. The burning of fossil fuels for electricity generation has many adverse effects on the environment. Daylighting is an important and useful strategy for enhancing visual comfort and reducing the need for the electricity consumed by light fittings. The rational use of daylight through tools such as photoelectric lighting controls can effectively reduce buildings’ electricity consumption and the related pollutants and greenhouse gas emissions. Daylighting design techniques are often best demonstrated via field measurements that provide reliable operational and energy performance data for establishing design guidelines. An atrium provides an environmentally controlled indoor public space that introduces daylight into the hearts of large buildings. In circulation areas such as corridors, people expect the way ahead to be sufficiently lit and daylight-linked lighting controls can deliver excellent energy savings. This paper presents the daylighting and energy performance of an atrium space using daylight-linked lighting controls. The cost, energy and environmental issues related to various daylight illuminances are estimated and design implications are discussed.

Field studies of the thermal comfort conditions in residential buildings were conducted in high-latitude regions with sub-atmospheric pressure in China. In the summer study, 33 individuals took part in 25 residential units and 43 individuals in 20 residential units in winter. Both subjective questionnaire survey in terms of thermal sensation votes (TSVs) and objective on-site measurements were carried out. In winter about 68% of the occupants felt slightly cool, cool or cold; only one-quarter of the people felt neutral. The summer situation was much better; 96% indicted comfortable. Results from the TSVs indicated that the neutral temperature for winter and summer was 18.9 °C and 23.3 °C, respectively. The winter neutral temperature was 7.6 °C higher than the mean indoor air temperature of 11.3 °C. Reasons for such large difference were suggested. An adaptive comfort model was developed using linear regression, and the indoor temperature limit was 16.4–29.7 °C based on 90% acceptability. These findings were compared with other field studies and the implications for energy use in buildings were discussed.

Buildings account for a significant proportion of the total energy and carbon emissions worldwide, and play an important role in formulating sustainable development strategies. There is a growing interest in ZEBs (zero energy buildings) in recent years. Several countries have adopted or considering establishing ZEBs as their future building energy targets to help alleviate the problems concerning the depletion of energy resources and the deterioration of the environment. Broadly speaking, ZEBs involve two design strategies – minimizing the need for energy use in buildings (especially for heating and cooling) through EEMs (energy-efficient measures) and adopting RETs (renewable energy and other technologies) to meet the remaining energy needs. This paper reviews the works related to these two strategies. EEMs include building envelopes, internal conditions, and building services systems; RETs cover photovoltaic/building-integrated photovoltaic, wind turbines, solar thermal (solar water heaters), heat pumps, and district heating and cooling. Issues pertaining to sustainable development implications and further research work required are also highlighted. These include life-cycle cost and environmental impacts, climate change and social policy issues.

Underlying trends of the long-term summer and winter discomfort in terms of heat and cold stresses in the major climate zones and sub-zones of the Koppen-Geiger world climate classifications during the 20th century were investigated. Decreasing trends of cumulative cold stress and increasing trends of cumulative heat stress were observed in all the major climate types and sub-types. This could have significant implications for building designs and energy use in the built environment. A reduction in cold stress would lead to less heating requirement and an increase in heat stress more cooling. Analysis was also conducted for the world climates in eight regions – North America, South America, Europe, Africa, Asia (Far East), Asia (Southeast), Asia (Middle East), and Australia and Pacific Islands. It was found that South America, Africa and Asia (Southeast) showed an increasing trend in the annual cumulative stress suggesting that the increase in cumulative heat stress outweighed the reduction in cumulative cold stress. Expected increases in the demand for electricity with greater carbon emissions present a challenge to building researchers and energy and environmental policy makers.

In subtropical Hong Kong, buildings consume the most of the electricity use. Computer simulation technique is a useful tool for predicting building thermal and energy performance. Simulation computer programs require weather data input to drive the mathematical models within the simulation tools for comparative studies and annual energy estimation. Typical weather year data representing the long-term climatic conditions are often used. Recently, there has been an increasing interest in incorporating daylight in the architectural and building designs to reduce building energy consumption. However, daylight parameters are not always available. In 2003, the International Commission on Illumination (CIE) adopted a range of 15 standard skies covering probably the whole spectrum of the usual skies in the world. Once the skies have been identified, the basic solar irradiance and daylight illuminance at various inclined planes can be obtained. This paper presents the work on the development and evaluation of two typical weather datasets, namely Typical Meteorological Year (TMY) and Test Reference Year (TRY). Measured hourly weather data for the 30-year period from 1979 to 2008 were analysed. Building energy simulations were conducted to evaluate the two weather datasets. Daylight parameters were derived using luminous efficacy approach and the sky conditions were categorized based on common climatic variables.

Impact of climate change on energy use in office buildings in a city within each of the five major architectural climates across China – Harbin (severe cold), Beijing (cold), Shanghai (hot summer and cold winter), Kunming (mild) and Hong Kong (hot summer and warm winter) – was investigated for two emissions scenarios. For low forcing, the estimated increase in cooling energy use was 18.5% in Harbin, 20.4% in Beijing, 11.4% in Shanghai, 24.2% in Kunming and 14.1% in Hong Kong; and the reduction in heating 22.3% in Harbin, 26.6% in Beijing, 55.7% in Shanghai, 13.8% in Kunming and 23.6% in Hong Kong. Space heating is usually provided by oil- or gas-fired boiler plants, whereas space cooling mainly relies on electricity. There would certainly be a shift towards electrical power demand. More energy use in buildings would lead to larger emissions, which in turn would exacerbate climate change and global warming. Energy conservation measures were considered to mitigate the impact of climate change on building energy use. These included building envelope, indoor condition, lighting load density and chiller coefficient of performance. It was found that raising the summer indoor design condition by 1–2 °C could result in significant energy savings and have great mitigation potential.

Studies on the impact of climate change on energy use in buildings in the different parts of the world were reviewed. Potential mitigation and adaptation measures were discussed and further research work suggested. In severe cold climates reduction in heating requirement would outweigh the modest increase in summer cooling. In the hot summer and cold winter climate zones where both winter heating and summer cooling requirements are important, the magnitude of reduction in heating and the magnitude of increase in cooling could be comparable. The most significant impact on energy use in the built environment would occur in the hot summer and warm winter climates where building energy use is dominated by cooling requirement. Raising the summer set point temperature and reducing the lighting load density would have great energy savings and hence mitigation potential. Space heating is provided largely by oil- or gas-fired boiler plants whereas space cooling mainly relies on electricity. This would result in a shift towards more electrical demand and could have important implications for the nationwide energy and environmental policy for the built environment.

Principal component analysis of 30-year long-term meteorological variables was conducted. Typical principal component years (TPCYs) were determined for Harbin, Beijing, Shanghai, Kunming and Hong Kong representing the five major architectural climates across China: severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. In each climate zone, the TPCY was compared with the 30 individual years and the widely used typical meteorological year (TMY). The monthly principal component and the predicted total building energy consumption based on the TPCY and TMY were very close to the 30-year long-term mean estimation. TPCY for the 21st century in each of the five cities was also identified using predictions from general climate models. The TPCY approach is a good alternative to the TMY method. Firstly, predicted building energy use from TPCY is closer to the long-term estimation than that from the TMY in different climates. Secondly, because only monthly data are considered, the development of TPCY is much simpler and less time-consuming. This would have important applications in the regular updating of typical weather years for building energy studies and in the assessment of the impact of climate change on energy use in the built environment.

Summer and winter discomfort in terms of heat and cold stresses in the nine major architectural climate zones and sub-zones across China in the 21st century were investigated using predictions from general circulation models for the low and medium emissions scenarios. For the six severe cold and cold climate zones in the north, reductions in cumulative cold stress outweighed the increase in cumulative heat stress resulting in an overall decreasing trend in the annual cumulative stress, and vice versa for the other three warmer climate zones in the south. Compared with the 20th century, significant reduction in the cumulative cold stress was observed across the six zones in severe cold and cold climates, ranging from 15.8 in cold-III to 42.3 in severe cold-II. There were modest increases in the cumulative heat stress from 0.3 in cold-II to 12.3 in cold-III. For the warmer climates in the south, reduction in cumulative cold stress ranged from 7.6 in hot summer and warm winter (HSWW) to 10.3 in hot summer and cold winter, while cumulative heat stress increased from 9.9 in the mild zone to 30.6 in HSWW. A reduction in cold stress would result in less winter heating and an increase in heat stress more cooling requirement.

Principal component analysis of dry-bulb temperature, wet-bulb temperature and global solar radiation was considered, and a new climatic index (principal component Z) determined for two emissions scenarios – low and medium forcing. Multi-year building energy simulations were conducted for generic air-conditioned office buildings in Harbin, Beijing, Shanghai, Kunming and Hong Kong, representing the five major architectural climates in China. Regression models were developed to correlate the simulated monthly heating and cooling loads and building energy use with the corresponding Z. The coefficient of determination (R2) was largely within 0.78–0.99, indicating strong correlation. A decreasing trend of heating load and an increasing trend of cooling load due to climate change in future years were observed. For low forcing, the overall impact on the total building energy use would vary from 4.2% reduction in severe cold Harbin (heating-dominated) in the north to 4.3% increase in subtropical Hong Kong (cooling-dominated) in the south. In Beijing and Shanghai where heating and cooling are both important, the average annual building energy use in 2001–2100 would only be about 0.8% and 0.7% higher than that in 1971–2000, respectively.

An attempt was made to develop multiple regression models for office buildings in the five major climates in China – severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. A total of 12 key building design variables were identified through parametric and sensitivity analysis, and considered as inputs in the regression models. The coefficient of determination R2 varies from 0.89 in Harbin to 0.97 in Kunming, indicating that 89–97% of the variations in annual building energy use can be explained by the changes in the 12 parameters. A pseudo-random number generator based on three simple multiplicative congruential generators was employed to generate random designs for evaluation of the regression models. The difference between regression-predicted and DOE-simulated annual building energy use are largely within 10%. It is envisaged that the regression models developed can be used to estimate the likely energy savings/penalty during the initial design stage when different building schemes and design concepts are being considered.

Future trends of cooling load due to heat gain through the building envelopes in the residential sector in subtropical Hong Kong under different emissions scenarios in the 21st century were investigated. Predicted monthly weather data from five general circulation models were gathered and analysed. An increasing trend of building envelope cooling load was observed. The average annual cooling load during the 2009–2100 period would be 6.1% and 9.8% more than that during 1979–2008 for low and medium forcing, respectively. If only the last 30 years (2071–2100) were considered, the percentage increase would be much larger at 12.3% and 21.6%. Four mitigation or energy conservation measures – raising the indoor temperature, thermal insulation, double glazing and tinted glass – were considered. Among them, raising the indoor temperature has the best mitigation potential because there is a growing awareness and recognition of adaptive thermal comfort and it can be readily applied to both existing and new buildings at no extra cost.

Cluster analysis of summer and winter discomfort in terms of heat and cold stresses based on 102-year (1901–2002) weather data in China was conducted. Five bioclimate zones were identified. These were compared with the corresponding thermal and solar zoning classifications. Bio-I and Bio-II tended to locate largely within severe cold and cold climates in the north with excellent solar availability (annual clearness index K t generally exceeding 0.5). Bio-III and Bio-IV covered mostly the hot summer and cold winter and mild climate zones. Despite the relatively low K t in winter, passive solar heating should be able to meet a significant proportion of the heating requirements. Bio-V covered the hot summer and warmer winter region, where heat stress and hence cooling requirement dominated. Decreasing trends in the zone-average annual cumulative cold stress during the 102-year period were observed for all five zones. There was, however, no distinct pattern for the heat stress and the changes tended to be more subtle. These indicate that climate change during the 20 th century affected winter discomfort (especially in colder climates in the north) more than the summer discomfort. This could have significant implications for energy use in buildings if such trends persist.

Past and future trend of electricity use for air conditioning in the entire commercial sector in subtropical climates using 1979–2008 measured meteorological data as well as predictions for 2009–2100 from a general circulation model (MIROC3.2-H) was investigated. Air conditioning consumption showed an increasing trend over the past 30 years from 1979 to 2008. Principal component analysis (PCA) of measured and predicted monthly mean dry-bulb temperature, wet-bulb temperature and global solar radiation was conducted to determine a new climatic index Z for 1979–2008 and future 92 years (2009–2100) based on two emissions scenarios B1 and A1B (low and medium forcing). Through regression analysis, electricity use in air conditioning for the 92-year period was estimated. For low forcing, average consumption in 2009–2038, 2039–2068 and 2069–2100 would be, respectively, 5.7%, 12.8% and 18.4% more than the 1979–2008 average, with a mean 12.5% increase for the entire 92-year period. Medium forcing showed a similar increasing trend, but 1–4% more. Standard deviations of the monthly air conditioning consumption were found to be smaller suggesting possible reduction in seasonal variations in future years.

Underlying trends of long-term summer and winter discomfort in terms of heat and cold stresses in the nine major thermal climate zones and sub-zones across China were investigated using 102-year (1901–2002) weather data. In severe cold climates, winter discomfort dominated (about 66%) and the comfort index (CI) varied from −5 (extremely cold) to +2 (hot). A gradual shift from predominantly negative CI to positive CI was observed as one moved across the climate zones from the north to warmer climates in the south. Temperature rise resulted in less discomfort in the winter and more discomfort in the summer. Though the reduction in cold stress and increase in heat stress were moderate during the 102-year period, the last two decades tended to exhibit the largest changes. It is envisaged that if these trends continue, changes in cold and heat stresses in the 21st century would be much greater than those experienced during the 20th century. This could have significant implications for building designs and energy use in the built environment.

Principal component analysis of prevailing weather conditions in subtropical Hong Kong was conducted, and a new climatic index Z (as a function of the dry-bulb temperature, wet-bulb temperature and global solar radiation) determined for past (1979–2008, measurements made at local meteorological station) and future (2009–2100, predictions from general circulation models) years. Multi-year (1979–2008) building energy simulations were carried out for a generic office building. It was found that Z exhibited monthly and seasonal variations similar to the simulated cooling/heating loads and building energy use. Regression models were developed to correlate the simulated monthly building cooling loads and total energy use with the corresponding Z. Error analysis indicated that annual building energy use from the regression models were very close to the simulated values; the difference was about 1%. Difference in individual monthly cooling load and energy use, however, could be up to 4%. It was also found that both the DOE-simulated results during 1979–2008 and the regression-predicted data during 2009–2100 indicated an increasing trend in annual cooling load and energy use and a gradual reduction in the already insignificant heating requirement in cooling-dominated office buildings in subtropical climates.

Past and future trends of human comfort in terms of heat and cold stresses under the local subtropical climates using measured meteorological data as well as predictions from general climate models were investigated. Summer discomfort showed an increasing trend (and winter discomfort a decreasing trend) over the past 41 years from 1968 to 2008. Monthly mean minimum and maximum temperatures and moisture content predictions from a general climate model (MIROC3.2-H) were used to determine summer and winter discomfort for future years (2009–2100) based on two emissions scenarios B1 and A1B (low and medium forcing). The 92-year (2009–2100) mean cold stress would be reduced from the 41-year (1968–2008) mean value of 8.7 to about three for both emissions scenarios. The 92-year mean heat stress would be 115.9 and 120.6 for B1 and A1B, respectively, representing 31.6% and 36.9% increase over the 1968–2008 long-term average of 88.1. These suggest that the already small winter heating requirement in subtropical Hong Kong would become even more insignificant in future years, whereas the increasing trend of summer discomfort would result in more cooling demand in the built environment.

The objective was to investigate whether energy use in buildings from simulation could be correlated with a new composite climatic index, which would account for the influences of major climatic variables such as temperature, humidity and solar radiation. Principal component analysis of prevailing weather conditions in sub-tropical Hong Kong was conducted, and a new climatic index Z determined. Multi-year (1979–2007) building energy simulations were carried out for a generic office building. It was found that Z exhibited daily and seasonal variations similar to the simulated cooling load and building energy use. Regression models were developed to correlate the simulated daily cooling load and building energy use with the corresponding daily Z. Error analysis indicated that annual building energy use from the regression models were very close to the simulated values; the difference was less than 2%. Difference in individual daily energy use, however, could be up to 6%. It was also found that both the simulated annual building energy use and the new climatic variable Z appeared to show an increasing trend during the 29-year period, indicating a subtle, but gradual change of climatic conditions that might affect energy use in buildings in future years.

Hong Kong is one of the most densely populated cities in the world. Its buildings are largely high-rise blocks constructed close to each other and, hence outdoor obstructions play significant roles in daylighting designs. The light reflected from the ground and surrounding buildings can be important sources of interior lighting and detailed computations are required. We currently propose a calculation procedure in terms of a number of regression equations to determine the daylight illuminance on vertical surfaces. This paper presents the work to assess this approach via full-scale measurements under real sky conditions. The mean surface reflectance for external obstructions was estimated using lighting simulation techniques. It was shown that daylight illuminance obtained by the proposed method were in reasonably good agreement with measured readings. The simple nature of the proposed approach offers building professionals and students a reliable and convenient alternative to predict daylight illuminance particularly when different daylighting schemes and concepts are being considered.

Principal component analysis of dry-bulb temperature, wet-bulb temperature, global solar radiation, clearness index and wind speed was conducted, and a two-component solution obtained which could explain 80% of the variance in the original weather data. Clustering analysis of these two principal components resulted in a total of 18 typical day types being identified. A year long monitoring of the daily chiller plant electricity consumption in a fully air-conditioned office building was conducted. It was found that the typical day types exhibited daily and seasonal variations similar to the daily and monthly electricity consumption recorded. Three regression models were developed to correlate the daily chiller plant electricity consumption and the corresponding day types. The coefficient of determination (R2) was 0.86–0.99 showing strong correlation. It is proposed that the day type approach can be used as a tool for weather normalisation and inter-year comparisons in the analysis of energy savings due to building retrofits. It was also found that the typical day types identified appeared to show a slight increasing trend during the 28-year period (1979–2006) indicating a subtle, but gradual change of climatic conditions that might affect chiller plant electricity consumption in future years.

Daylighting has long been recognized as an important issue in architecture. In Hong Kong many buildings are constructed close to each other and hence the external environment plays a significant role in building designs. Recently, vertical daylight factor (VDF) has been used as a criterion to justify the provision of natural lighting in buildings. This paper studies the calculation approach of VDF in a heavily obstructed environment. The techniques for determining the sky component and the reflected daylight from surrounding buildings and ground surfaces are described. Calculation tools in the form of simple equations and diagrams through computer-simulation analysis were established. The performance of the proposed method was evaluated against the daylight illuminance obtained by other independent computer simulations. It was found that predictions from the proposed approach were in good agreements with those produced by simulated results. The findings provide architects and building designers with a simple method for estimating the daylight illuminance at early design and planning stage.

This short technical note presents an attempt to develop a new climatic variable Z for assessing climate change (global warming) with respect to the built environment. Principal component analysis of long-term (30-year) dry-bulb temperature (DBT), wet-bulb temperature and global solar radiation data was conducted in the 5 major climate zones in China. It was found that while the long-term trend was increasing for the DBT in all 5 major climates, hot summer and warm winter climate zone showed a decreasing trend (though slightly) in the annual and seasonal average Z values. This suggests that climate change might not necessarily result in higher cooling loads in buildings.

Two-parameter regression models were used to predict global solar radiation (GSR) for the nine major thermal zones and sub-zones – severe cold (I, II and III), cold (I, II and III), hot summer and cold winter, mild, and hot summer and warm winter – across China. The impact of using modelled GSR on building energy simulation was investigated. A total of nine cities were selected, one for each thermal zone. Generic office buildings were developed for each of the nine cities according the local design/energy codes. Two sets of energy simulation were conducted for each city, one with the measured GSR and the other the modelled data. The computed results were analysed in four aspects – solar heat through the windows, building heating loads, building cooling loads and the corresponding building energy consumption. It was found that simulated annual heating/cooling loads could differ by 0.1–6.2% and total building energy consumption 0.1–1.2%. These differences were also compared with the mean bias error and root-mean-squared error of the modelled GSR.

Electricity use characteristics of 10 air-conditioned office buildings in subtropical Hong Kong were investigated. Monthly electricity consumption data were gathered and analysed. The annual electricity use per unit gross floor area ranged from 233 to 368 kWh/m 2 , with a mean of 292 kWh/m 2 . The ranges of percentage consumption for the four major electricity end-users – namely heating, ventilation and air-conditioning (HVAC), lighting, electrical equipment, and lifts and escalators – were 40.1–50.7%, 22.1–29%, 16.6–32.9% and 2.2–5.3%, respectively. Ten key design variables were identified in the parametric and sensitivity analysis using building energy simulation technique. Analysis of the resulting influence coefficients suggested that indoor design condition (from 22 to 25.5 °C), electric lighting (a modest 2 W/m 2 reduction in the current lighting code) and chiller COP (from air- to water-cooled) could offer great electricity savings potential, in the order of 14%, 5.2% and 11%, respectively.

Energy performance of office building envelope designs in the five major climate zones – severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter – in China was investigated. A major city within each climate zone was selected. These were Harbin, Beijing, Shanghai, Kunming and Hong Kong. Generic building envelopes were developed based on data gathered from building surveys, local energy codes and the ASHRAE Standard. The overall thermal transfer value (OTTV) method and the heating degree-days technique were adopted in the analysis. Cooling and heating requirements due to heat gain/loss through the building envelopes were determined based on the respective OTTV parameters and building load coefficients. Different shape coefficients were also considered. For a typical floor, chiller load due to heat gain through the building envelope varied from 1.0 kW h/m 2 in Kunming to 23.5 kW h/m 2 in Beijing, and the heating load ranged from 2.7 kW h/m 2 in Hong Kong to 124.3 kW h/m 2 in Harbin.

Energy simulation was conducted for office buildings in the five major climate zones – severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter – in China using DOE-2.1E. The primary aim was to investigate the thermal and energy performance of office buildings with centralised heating, ventilation and air conditioning plants in the major climatic zones in China. The computed results were analysed in three aspects – heating load, cooling load and the corresponding building energy consumption. The building peak monthly heating load varied from 142 MW h (1033 MW h cooling) in Hong Kong to 447 MW h (832 MW h cooling) in Harbin. It was also found that passive solar designs could have large energy savings potential in the severe cold and cold climates. In Harbin, the window solar component helped lower the annual building heating load by 650 MW h. Internal loads (lighting and office equipment) and part load operations of fans and pumps also played a significant role in the overall building energy efficiency. This paper presents the work, its findings and energy efficiency implications.

Correlation between clearness index and sunshine duration is useful to the estimation of the solar radiation for areas where measured solar radiation data are not available. Regression techniques were used to investigate the correlations between daily global solar radiation and sunshine duration for different climates in China. Measurements made during the 30-year period (1971–2000) from 40 measuring stations covering major thermal and solar climatic zones across China have been gathered and analysed. The correlations were developed for each individual station as well as for each of the major climates. It was found that the Angstrom–Prescott equation tended to give a good estimation of global solar radiation based on the corresponding measured sunshine hours. A simple two-parameter linear regression equation was proposed for each of the major thermal and solar climatic zones.

The correlation between the clearness index and sunshine duration is useful in the estimation of the solar radiation for areas where measured solar radiation data are unavailable. Regression techniques and artificial neural networks were used to investigate the correlations between daily global solar radiation (GSR) and sunshine duration for different climates in China. Measurements made during the 30-year period (1971–2000) from 41 measuring stations covering 9 thermal and 7 solar climate zones and sub-zones across China were gathered and analysed. The performance of the regression and the ANN models in the thermal and solar zones was analysed and compared. The coefficient of determination (R2), Nash–Sutcliffe efficiency coefficient (NSEC), mean bias error (MBE) and root-mean-square error (RMSE) were determined. It was found that the regression models in both the thermal and the solar climate zones showed a strong correlation between the clearness index and sunshine duration (R2=0.79–88). There appeared to be an increasing trend of larger MBE and RMSE from colder climates in the north to warmer climates in the south. In terms of the thermal and solar climate zone models, there was very little to choose between the two models.

Artificial neural networks (ANNs) were used to develop prediction models for daily global solar radiation using measured sunshine duration for 40 cities covering nine major thermal climatic zones and sub-zones in China. Coefficients of determination ( R 2 ) for all the 40 cities and nine climatic zones/sub-zones are 0.82 or higher, indicating reasonably strong correlation between daily solar radiation and the corresponding sunshine hours. Mean bias error (MBE) varies from −3.3 MJ/m 2 in Ruoqiang (cold climates) to 2.19 MJ/m 2 in Anyang (cold climates). Root mean square error (RMSE) ranges from 1.4 MJ/m 2 in Altay (severe cold climates) to 4.01 MJ/m 2 in Ruoqiang. The three principal statistics (i.e., R 2 , MBE and RMSE) of the climatic zone/sub-zone ANN models are very close to the corresponding zone/sub-zone averages of the individual city ANN models, suggesting that climatic zone ANN models could be used to estimate global solar radiation for locations within the respective zones/sub-zones where only measured sunshine duration data are available.

We present the energy use situation in Hong Kong from 1979 to 2006. The primary energy requirement (PER) nearly tripled during the 28-year period, rising from 195,405 to 566,685 TJ, about two-third of which was used for electricity generation. The residential and commercial sectors are the two largest electricity end-users with an average annual growth rate of 5.9% and 7.4%, respectively. The monthly consumption in these two sectors shows distinct seasonal variations mainly due to changes in the air-conditioning requirements, which are affected by the prevailing weather conditions. Principal component analysis of five major climatic variables—dry-bulb temperature, wet-bulb temperature, global solar radiation, clearness index and wind speed—was conducted. Measured sector-wide electricity consumption was correlated with the corresponding two principal components determined using multiple regression technique. The regression models could give a very good indication of the annual electricity use (largely within a few percents), but individual monthly estimation could differ by up to 24%. It was also found that the climatic indicators determined appeared to show a slight increasing trend during the 28-year period indicating a subtle, but gradual change of climatic conditions that might affect future air-conditioning requirements.

Detailed hourly energy simulation was conducted for office buildings in the five major climate zones – severe cold, cold, hot summer and cold winter, mild and hot summer and warm winter – in China using multi-year (1971–2000) weather databases as well as typical meteorological years (TMY). The primary aim was to compare the energy simulation results from the TMY with those from individual years and their long term means. A total of 154 simulation runs were performed. Building heating and cooling loads, their components and energy use for heating, ventilation and air-conditioning were analysed. Predicted monthly load and energy consumption profiles from the TMY tended to follow the long term mean quite closely. Mean bias errors ranged from −4.3% in Guangzhou to 0% in Beijing and root-mean-square errors from 3% in Harbin to 5.4% in Guangzhou. These percentages were not always the smallest compared with the 30 individual years, however, they are at the lower end of the percentage error ranges. This paper presents the work and its findings.

China’s climate differs greatly in various regions, ranging from severe cold to hot and arid to humid. This has significant influences on energy efficient building design strategies and energy use. Solar radiation data from 123 measuring stations were used to propose a map indicating the solar radiation climates in China. A cluster analysis was adopted to identify the prevailing solar climates using the monthly average daily clearness index, K t , as climatic variable. Five major solar climates were identified with annual average K t ranging from 0.3 in the Sichuan Basin to 0.65 in the north and northwest regions. The solar climates were compared with the more widely used general (thermal) climates (severe cold, cold, hot summer and cold winter, mild and hot summer and warm winter) and the major topography (basin, plain and plateau), and implications for building designs were briefly discussed.

Typical meteorological years (TMYs) for 60 cities in the five major climatic zones (severe cold, cold, hot summer and cold winter, hot summer and warm winter, mild) in China were investigated. Long term (1971–2000) measured weather data such as dry bulb and dew point temperatures, wind speed and global solar radiation were gathered and analysed. A total of seven climatic indices were used to select the 12 typical meteorological months (TMMs) that made up the TMY for each city. In general, the cumulative distribution functions of the TMMs selected tended to follow their long term counterparts quite well. There was no persistent trend in any particular years being more representative than the others, though 1978 and 1982 tended to be picked most often. This paper presents the work and its findings. Future work on the assessment of TMYs in building energy simulation is also discussed.

Changes in lighting load density affect not only energy use for electric lighting but also energy requirements for space heating and cooling. In general, a reduction in electric energy use would tend to increase space heating during the winter months and lower the cooling requirement in the summer. The implications for total building energy use, however, would vary, depending on the building and building services designs, its operation and the prevailing climates. This paper presents an analysis of the interactions between lighting and space heating/cooling loads in office buildings in the five major climatic zones—severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter—in China through building energy simulation using DOE-2.1E.

This paper presents the work on development of passive design zones for different climates in China. A total of 18 cities representing the five major climatic types, namely severe cold, cold, hot summer and cold winter, mild and hot summer and warm winter were selected for climatic analysis. Measured weather data were gathered and analysed. A bioclimatic approach was adopted in which the comfort zone and 12 monthly climatic lines were determined and plotted on the psychrometric chart for each city. From these bioclimatic charts, the potential use of passive design strategies such as solar heating, natural ventilation, thermal mass with/without night ventilation and evaporative cooling was assessed. A total of nine passive design strategy zones were identified, and appropriate design strategies suggested for both summer and winter consideration.

Daylight illuminance, particularly on vertical surfaces, plays a major role in determining and evaluating the daylighting performance of a building. In many parts of the world, however, the basic daylight illuminance data for various vertical planes are not always readily available. The usual method to obtain diffuse illuminance on tilted planes would be based on inclined surfaces models using data from the horizontal measurements. Alternatively, the diffuse illuminance on a sloping plane can be computed by integrating the luminance distribution of the sky ‘seen’ by the plane. This paper presents an approach to estimate the vertical outdoor illuminance from sky luminance data and solar geometry. Sky luminance data recorded from January 1999 to December 2001 in Hong Kong and generated by two well-known sky luminance models (Kittler and Perez) were used to compute the outdoor illuminance for the four principal vertical planes (N, E, S and W). The performance of this approach was evaluated against data measured in the same period. Statistical analysis indicated that using sky luminance distributions to predict outdoor illuminance can give reasonably good agreement with measured data for all vertical surfaces. The findings provide an accurate alternative to determine the amount of daylight on vertical as well as other inclined surfaces when sky luminance data are available.