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• Globally, population weighting substantially changes degree-days rate of change. • Choice of base temperature strongly influences degree-day calculation. • For typical base temperatures, heating degree-days are falling at twice the rate that cooling degree days are increasing. • Within countries, heterogeneity in population changes determines relative changes in heating and cooling degree-days. Anthropogenic greenhouse gas emissions are driving global increases in temperature. This rise will likely lead to an increase in demand for cooling in the coming years. However, increasing temperatures are not the main explanatory factor for why the world is moving towards more cooling. This paper compares population and area-weighted cooling and heating degree-days derived using ERA5-Land reanalysis temperature, to show that population growth in warmer parts of the world drives cooling demand globally. The analysis shows that mean global area-weighted heating degree-days have fallen 8.46 °C days/year, whereas population-weighted heating degree-days have fallen by 12.5 °C days/year. At the same time, mean global area-weighted cooling degree-days have risen by 3.0 °C days/year, while population-weighted cooling degree-days have risen at 6.0 °C days/year. By using sub-country analysis, this paper shows that population-weighted degree-days can substantially differ from area-weighted degree-days. Finally, the findings highlight that the choice of heating and cooling degree-day base temperature is the most important parameter in the variability of degree-days and will need to be understood better in order to accurately account for future heating and cooling energy demand. [ABSTRACT FROM AUTHOR]

Global warming has drawn great attention in recent years because of its large impact on many aspects of the environment and human activities in buildings. One area directly affected by climate change is the energy consumption for heating and cooling. To quantify the impact, this study used the HadCM3 Global Circulation Model (GCM) to generate weather data for future typical meteorological years, such as 2020, 2050, and 2080, for 15 cities in the U.S. based on three CO 2 emission scenarios. The method was validated by comparing the projected TMY3 data using HadCM3 with the actual TMY3 data. By morphing method, the weather data was downscaled to hourly data for use in building energy simulations by EnergyPlus. Two types of residential buildings and seven types of commercial buildings were simulated for each of the 15 cities. This paper is the first to systematically study the climate change impact on various types of residential and commercial buildings in all seven climate zones in the U.S. through EnergyPlus simulations and provide weighted averaged results for national-wide building stock. We also identified geographical dependency of the impact of climate change on future energy uses. There would be a net increase in source energy consumption by the 2080s for climate zones 1–4 and net decrease in climate zones 6–7 based on the HadCM3 weather projection. Furthermore, this paper investigated natural ventilation performance in San Francisco, San Diego, and Seattle with improved natural ventilation model. We found that by the 2080s passive cooling would not be suitable for San Diego because of global warming, but it would still be acceptable for San Francisco and Seattle. [ABSTRACT FROM AUTHOR]

Buildings account for 40% of total energy consumption in the UK and more than 55% of this energy is used by heating, ventilation, air-conditioning and refrigeration (HVAC&R) systems. This significant energy demand and the ascending trend in utilising HVAC&R systems together with the global need to impose energy-efficiency measures underline the importance of selecting the most appropriate HVAC&R system during the design process. This paper reviewed and classified a broad range of principal multiple attribute decision making methods. Among them, the fuzzy multiple attribute decision making approach was adopted to develop a decision making tool for HVAC&R systems selection. This was mainly due to the ability of this method to deal with the uncertainties and imprecisions of the linguistic terms involved in the decision making process. In order to make a decision on HVAC&R systems selection, 58 alternative systems, including both primary and secondary parts, were examined. The scope of this study enabled the consideration of all 18 climate regions in the UK and included the effects of climate change. In addition, the Government’s electricity decarbonisation plans were integrated within the developed decision making model for HVAC&R systems selection in office buildings in the UK. Finally, the model was transferred into a computational tool with a user-friendly interface. [ABSTRACT FROM AUTHOR]

• Genetic Algorithm (GA) based on Non-dominated Sorting Genetic Algorithm 2 (NSGA2) method is used for optimization. • Building optimization using passive design strategies can reduce final HVAC energy use 32% • Building optimization using passive design strategies can reduce time-integrated discomfort 46% • Overheating in nearly Zero Energy Buildings will be aggravated with continuation of global warming. • Building thermal comfort optimization does not ensure overheating mitigation during unprecedented events. It is expected that heatwaves will strike more frequently and with higher temperatures with the continuation of global warming. More extreme heatwaves concurrent with disruptions in the cooling system can lead to significant overheating problems in buildings affecting occupants' health, productivity, and comfort. This paper projects current and future heatwaves on an optimized nearly Zero-Energy terraced dwelling in Brussels, assuming the outage of the cooling system. Initially, a multi-objective optimization is performed considering 13 passive design strategies using the Genetic Algorithm (GA) based on the Non-dominated Sorting Genetic Algorithm 2 (NSGA-II) method. It is found that high ventilation rate, low infiltration rate, high insulation, high thermal mass, integration of green roof, and application of operable roller blinds are beneficial in reducing the final HVAC energy use up to 32% and enhancing thermal comfort up to 46%. Subsequently, three optimal solutions are selected and analyzed under the highest maximal temperature heatwaves detected during the 2001–2020, 2041–2060, and 2081–2100 periods. It is found that non of the optimal solutions are able to fully suppress overheating during heatwaves and the cooling system outage. The indoor operative temperatures reach more than 29 ° C , which can cause serious health issues for the occupants. The situation will be exacerbated in the future since an increase in maximum Heat Index (HI) between 0.28 °C and 0.49 °C, an increase in the maximum operative temperature between 1.34 ° C and 2.33 ° C , and a decrease in Thermal Autonomy (TA) between 17% and 28% are estimated. Finally, some recommendations are provided for practice and future research. [ABSTRACT FROM AUTHOR]

• Developed a general methodology to define and characterise overheating events and evaluate the risk to reduced comfort and undesirable health effects of building occupants exposed to extreme heat events. • Developed criteria to declare overheating based on heat-related health outcomes related to limits for body dehydration and core temperature of healthy average-age and older people. • Applied the methodology to a case study of a residential building with typical local construction in cold climates and compared the results with those from other existing methods. • The proposed methodology sets the groundwork for establishing a benchmark model from which different overheating metrics can be compared. Overheating in built environments during climate extreme heat events is a major concern to human health, particularly for people vulnerable to prolonged exposure to heat and humidity. However, currently available methods for assessing the risk of overheating lack robust procedures to evaluate the effects of overheating on the comfort and health of vulnerable occupants residing in the various different dwellings. This paper developed a general methodology to define and characterise overheating events and evaluate the risk to reduced comfort and undesirable health effects of building occupants exposed to extreme heat events. Criteria to declare overheating were developed based on heat-related health outcomes related to limits for body dehydration and core temperature of healthy average-age and older adults. The methodology was then applied to a case study of a residential building with typical local construction practice for cold climates and compared with existing methods for assessing risk from exposure to extreme heat events. The results showed that all the methods predicted that highly insulated and airtight buildings are more prone to overheating than older buildings that are less well insulated and airtight. However, only the proposed methodology described in this paper predicted that natural ventilation through opening windows significantly reduced the overheating risk to below the threshold value. Furthermore, multi criteria methods might be difficult to apply in practice in that it is not guaranteed to violate all the criteria to declare a building space is not overheated. The proposed methodology sets the groundwork for establishing a benchmark model from which different overheating metrics can be compared. [ABSTRACT FROM AUTHOR]

Urban heat island (UHI) and global warming effects will raise the ambient temperature of cities and increase building energy consumption. This paper discusses the residential cooling energy variations imposed by urban warming in the present and future. Data from a dynamically downscaled hourly meteorological model with a grid resolution of 5 km and for time slices 1979–2003, 2015–2039, and 2075–2099 were used for dynamic building energy simulation against a typical residential apartment in the central Taiwan region. The meteorological grids were classified as 4 city grids, 25 town grids, and 31 countryside grids based on their urban morphology attributes. The values from 20 countryside grids with lower average ambient temperatures during cooling seasons were selected as reference. The spatial and temporal distributions of the impact of indoor overheating risk and annual cooling energy consumption by UHI and global warming effects were quantified against the reference value. Furthermore, because the energy penalty can be used to rapidly estimate the urban warming impact on total cooling energy consumption of a given city, the linear correlation of the energy penalty and the magnitude of the UHI effect was also established and discussed. [ABSTRACT FROM AUTHOR]

Urban heat island and global warming increase ambient temperature and modify the energy budget of buildings. The magnitude of the modification has been evaluated in a large number of articles, under different climatic and building boundary conditions. This paper collects, analyzes and classifies existing knowledge regarding the energy impact of urban heating to buildings and calculates preliminary indicators and impact figures. Based on the analysis of the impact studies, it is found that in average the cooling load of typical urban buildings is by 13% higher compared to similar buildings in rural areas. Four specific energy impact indicators, the global energy penalty per m 2 , the global energy penalty per m 2 and degree of UHI, the global energy penalty per person and the global energy penalty per person and per degree of the UHI are defined and calculated. The variability of the heating and cooling loads of typical buildings is evaluated for the period 1970–2010. The average increase of the cooling demand is 23% while the corresponding average reduction of the heating is 19%. In total, the average energy consumption of typical buildings for heating and cooling purposes increased by 11% for the same period. [ABSTRACT FROM AUTHOR]

[Display omitted] Dynamic modeling of building performance is essential for understanding how current buildings will respond to projected changes in environmental conditions, and how these responses will in turn affect building occupants. Additionally, expected shifts in background energy systems will change the carbon intensity of energy delivered to buildings, while shifts in atmospheric composition will alter the global warming potential of each greenhouse gas. This paper models these three dynamic systems simultaneously to determine which projected shifts will have the largest influence on global warming impacts and occupant satisfaction metrics throughout the use phase of an office building prototype model in different climate zones of the United States. The median of RCP8.5 and RCP4.5 climate scenarios were used to morph local weather files to simulate the electricity and natural gas needed to meet heating and cooling loads in each location, as well as thermal comfort and daylighting metrics. These RCPs were also used to estimate shifts in the global warming potential factors for CO 2 , CH 4 , and N 2 O. Projected shifts in the electricity generation mix and upgrades to transmissions and distribution infrastructure in each region were used to estimate future carbon intensity factors for building site energy use. Compared to the baseline results, decarbonization of the electricity grid results in the largest shift in building operational GHG emissions, far outweighing emissions increases due to higher cooling loads. Shifts in ambient temperatures and direct and diffuse radiation had heterogeneous effects on occupant comfort, particularly in Boston across different seasons and orientations. Understanding how building performance is expected to respond to complex future trends will assist in designing adaptive buildings that take advantage of projected changes. [ABSTRACT FROM AUTHOR]

Through tests conducted at the Toronto and Region Conservation Authority's (TRCA) Archetype Sustainable Houses, a hybrid residential space heating system with a supervisory controller was monitored and studied to evaluate its performance and effectiveness for the heating season. A high efficiency natural gas furnace (NGF) and an electric air source heat pump (ASHP) were coupled together to meet the space heating demand of the house. This integrated system is called the cloud based Smart Dual Fuel Switching System (SDFSS) that considers time-of-use (TOU) pricing, fuel cost, short-term weather forecast, and equipment efficiencies and capacities. This multi-variable decision-making process defines an optimal schedule for the hybrid system to run more cost effectively. This paper analyses two separate SDFSSs. According to these analyses, the SDFSS systems showed lower operating cost with respect to the furnace or the ASHP system alone with various carbon tax (CT) levels from $0 to $250/tonne of CT with an increment of $10/tonne of CT that were simulated, along with a significant GHG emission reduction relative to the conventional heating systems. Furthermore, with these technologies, Canada's residential sector could potentially meet Canada's Paris Agreement goals. The SDFSS technology is a is flexible, user friendly, ubiquitous technology for the smooth transition from today's natural gas dominated space heating system to the future's low carbon infrastructure powered by a heat pump and renewable energy. [ABSTRACT FROM AUTHOR]