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The paper presents an energy simulation-based study to investigate the impacts of climate change on energy consumptions of an office building located in five different cities, United States. Annual energy consumption of a medium-size office building was predicted by building energy simulation software—EnergyPlus using TMY3 weather data and future climate data. In this study, we have used two sets of further climate data with different climate models including (1) Hadley Centre Coupled Model, version 3 (HadCM3), and (2) NCAR Community Earth System Model version 1 (CESM1) with the Community Atmosphere Model version 5 (CAM5). A morphing method was applied to downscale the monthly weather forecast to hourly forecast for use in building energy simulation for the two General Circulation Models (GCMs): HadCM3 and CESM1. Using the generated future weather files, HVAC operation related mitigation measures including adjustment of thermostat setpoints, reduced HVAC operation hours, reduced VAV box minimum flow setting, and mixed-mode ventilation were simulated to compare with ASHRAE Standard 90.1 baseline simulated using TMY3 weather data. Simulation results on predicted whole building, heating and cooling energy consumptions were examined. The paper highlighted the importance of efficiently operating mechanical systems in buildings to ensure a more sustainable future. [ABSTRACT FROM AUTHOR]

This study assesses the impacts of sustainable urban development adapted to climate change in the city of Stuttgart, Germany. We use the state-of-the-art meteorological modelling system PALM-4U to simulate the microclimate and outdoor thermal comfort of the development site Neckarpark during a heatwave. We compare the atmospheric conditions of the current urban structure before the development project (2018) and the future state, representing the new district after completion (2025). Our results indicate that the restructuring barely affects surrounding neighbourhoods, but leads to mean near-surface air temperature increases in the centre of development between ▪ and ▪. Differences in Physiologically Equivalent Temperature (PET) show a heterogeneous pattern at daytime, with a large amplitude and temporal variability in the diurnal cycle (▪). At night, the planned buildings increase the mean PET by ▪. The new buildings reduce the effect of adaptation measures designed to increase the cooling effects, i.e. urban trees and vegetation, amplifying the thermal stress during heatwaves. Our study confirms the complex composite impacts of urban restructuring due to the thermal and dynamic flow processes. The paper may serve as a guide for the use of meteorological models to assess microclimatic impacts of planned development projects, contributing to urban planning and adaptation strategies. [ABSTRACT FROM AUTHOR]

• Investigated climate change impacts on office building performance in Brussels. • Applied a long-term climate change sensitive system sizing and design approach. • Time-integrated discomfort analysis showed a major surge in overheating by 2100. • Long-term climate change resistivity is ensured in reference building until 2100. • Primary energy use and GHG emission findings are useful in mixed humid climates. As climate change continues, it is expected that the risk of overheating will rise in both new and existing buildings in mixed humid climate zones in Europe. This study introduced a novel climate change sensitive sizing and design approach for cooling and heating systems in nearly zero-energy office buildings in Brussels, Belgium, for different weather scenarios. This approach considered the long-term effects of climate change on building performance. The climate change effects were assessed using current and future climate data from the regional atmospheric model, MAR. To demonstrate the approach, a case study of a nearly zero-energy office building in Brussels was conducted. The reference building model was first calibrated using monthly energy use data from the year 2019 using ASHRAE Guideline 14. Then, the building was evaluated with different HVAC strategies and their performances were quantified. The results indicated an increase in overheating as high as 1.2 °C and cooling energy use as high as 13.5 kWh/m2 and a decrease in overcooling as low as 0.3 °C and heating energy use as low as 10.9 kWh/m2 in the reference building by the end of the century. In addition, due to climate change sensitive sizing and design approach coupled with optimal sizing, the reference building was climate change resistant towards the worst-case scenario by end of the century with up to 3.7 for climate change overheating resistivity and 20.2 for climate change overcooling resistivity. Finally, the paper provided recommendations for future practice and research based on the study findings. [ABSTRACT FROM AUTHOR]

In building energy simulation, researchers commonly use weather data obtained from the software database or (meteorological) MET station. However, this method leads to disparity of urban-rural temperature condition, hence the input weather data do not characterize the on-site condition. This paper highlights the importance of generating and implementing the urbanized weather data, primarily on the ambient temperature. A parametric approach was used to create hundreds urban layouts of the hypothetical office block plan. An annual temperature profile was generated for each scenario using the Screening Tool for Estate Environment Evaluation (STEVE) tool. It was found that the local average temperature ( T avg ) and peak afternoon period ( T max ) from these scenarios could differ 1–2 °C and 1.2–3.5 °C respectively as compared to the MET station data. Using Integrated Environmental Solutions (IES) to simulate the thermal load performance, this temperature difference can lead to an approximately 8% difference in the predicted cooling load, 20% in external conduction gain, and 17% in fresh air intake gain. These numbers can be deemed substantial in simulating building performance, especially cooling load due to changes in the external condition. Furthermore, the comparison proves to be significant in term of enhancing the simulation result and representing the studied area. [ABSTRACT FROM AUTHOR]

• Climate change and building load variations may impact optimised building designs. • A method using climate models and optimisation is used to optimise future buildings. • A case study is conducted on two cities in Australia: Canberra and Brisbane. • Results show that optimising for future climates can save energy for Canberra. • For Brisbane, savings are small and the present-optimised design seems acceptable. Building energy optimisation is generally performed under present climate conditions with fixed simulation parameters (e.g. internal loads). However, climate change and variations in simulation parameters over the building's life span may impact the optimised design. A key question is whether a particular energy-optimised design under present climate conditions would remain energy-optimised in the future. Accordingly, in this paper, a new simulation-based optimisation method is developed, which uses climate models and Ant Colony Optimisation to compare the energy-optimised designs under present and future climates. To demonstrate its potential, this method is applied to a typical office building in two Australian cities, Brisbane and Canberra. The results show that optimising under future climate conditions can lead to different optimal building designs. For Brisbane, the energy difference between optimising under present and future climate conditions is small, but in Canberra the cooling load is increased by up to 6%. This suggests that optimising the studied office building under present climate conditions is acceptable for Brisbane, while considering future climate may yield some savings in Canberra. Results also show that the energy-optimised building configuration for both future and present climates in Brisbane is less sensitive to changes in the load scenario than in Canberra. [ABSTRACT FROM AUTHOR]

The paper analyses effects of changes in temperatures on heating and cooling demands in Europe until 2050. Specifically, the study addresses changes in trends (10-year mean) and extremes (10-year min/max). The analysis is based on two GHG emission climate scenarios (RCP2.6 and RCP4.5) and eight high-resolution regional climate models and results are provided as relative and absolute changes on grid and country scales. Population density is used as proxy for spatial distribution of demands. Projected future temperatures are proportional with RCP scenario and distance into the future and the highest relative changes occur towards north-eastern Europe and for high-altitude areas. The temperature changes lead to general decreased heating demands and corresponding increased cooling demands. In general, higher spreads are seen between demand change ratios for individual models when addressing extremes as opposed to trends: The general 2010–2050 change ratios for heating between countries are 0.85–95 for model means and average 0.69 for the extreme analysis. For cooling, corresponding ratios are 1.25–1.5 for model means and average 2.76 for model maxima. For absolute demand changes, some countries are projected to experience significant changes e.g. exceeding a doubling in cooling demands. The results are suggested as a basis for energy system analyses. [ABSTRACT FROM AUTHOR]

• Future-TMY (F-TMY) and Morphing methodologies are compared in 14 Iberian cities. • Morphing sensitive analysis using 3 different files is performed. • High-quality Morphing and F-TMY have similar climate and BES performances (7%−8%). • F-TMY is representative of the multi-year simulation for BES applications. • Low-quality Morphing leads to average errors between 16% to 20%. In the last decade, building energy simulation (BES) became a central component in building energy systems' design and optimization. For each building location, BES requires one year of hourly weather data. Most buildings are designed to last 50+ years, consequently, the building design phase should include BES with future weather files considering climate change. This paper presents a comparative study of two methods to produce future climate hourly data files for BES: Morphing and typical meteorological year of future climate (F-TMY). The study uses data from a high-resolution (9 km) regional climate atmospheric model simulation of Iberia, spanning 10 years of historical and future hourly data. This study compares both methods by analyzing anomalies in air temperature, and the impact in BES predictions of annual and peak energy consumption for space heating, cooling and ventilation in 4 buildings. Additionally, this study performs a sensitivity analysis of morphing method. The analysis shows that F-TMY is representative of the multi-year simulation for BES applications. A high-quality Morphed TMY weather file has a similar performance compared to F-TMY (average difference: 8% versus 7%). Morphing based on different baseline climates, low-grid resolution and/or outdated climate projections leads to BES average differences of 16%-20%. [ABSTRACT FROM AUTHOR]

A warming climate, increasing frequency and severity of extreme heat events, and the heat island effect are cumulatively expected to exacerbate climate thermal loading on urban buildings. This in turn could lead to increased summertime overheating risk, with any active means for addressing this likely to influence future energy consumption and CO 2 emission patterns. This paper examines how the microclimatic loading presented by the heat island (UHI) effect influences summertime adaptive comfort in traditional urban residential buildings. The method for addressing this utilises the novel approach of coupling a computationally efficient urban climate model with an established building energy model to simulate a residential street canyon within the London heat island. Key findings highlighted adaptive capabilities to achieve summertime 'comfort' in most rooms without the need for energy intensive mechanical cooling. The alternative of using indiscriminate and widespread mechanical cooling within the canyon length is estimated to result in a 0.4 K increase in nocturnal canyon temperatures, and an additional 4.4% of CO 2 released to the climate. In contrast, a targeted approach of cooling rooms where adaptive capacity is insufficient more than halves the canyon CO 2 emission estimate; which in turn highlights the necessity for detailed overheating assessments in managing energy use in such traditional residential neighbourhoods within UHIs. [ABSTRACT FROM AUTHOR]