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1. Comparative Analysis of Urban Heat Island Effects on Building Energy Consumption in the U.S. Midwest: A combined workflow using Urban Weather Generator and Future Typical Meteorological Year Climate Scenarios

   HASHEMI, FARZAD; SALAHI, NEGAR; GHIASI, SEDIGHEH; PASSE, ULRIKE (October 2024, Wrocław University of Science and Technology Publishing House)

   Widera, Barbara; Rudnicka-Bogusz, Marta; Onyszkiewicz, Jakub; Woźniczka, Agata (Ed.)

   Urban areas often experience higher air temperatures than their surrounding rural counterparts, a phenomenon known as the urban heat island (UHI) effect. This significant human-induced alteration of urban microclimates has notable consequences, especially on urban energy consumption and resulting economic implications. This study presents an in-depth analysis of the UHI effect on urban building energy consumption in a US Midwest neighbourhood. Utilizing a three-phase methodology, the research first simulated UHI intensities with current and future Typical Meteorological Year (TMY) data, integrated with the Local Climate Zone (LCZ) classification system and the Urban Weather Generator (UWG) model. The second phase employed the urban modelling interface (umi) for building energy simulation, capturing the UHI impact on both residential and commercial buildings. The third phase demonstrates that UHI effects lead to reduced heating demand but increased cooling requirements in the future, with residential areas being more affected. The study's findings reveal critical challenges for urban planners and policymakers, emphasizing the need for sustainable designs to address fluctuating heating and cooling demands in changing climates. 

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2. Application of Machine Learning for Predicting Building Energy Use at Different Temporal and Spatial Resolution under Climate Change in USA

   https://doi.org/10.3390/buildings10080139  

   Mohammadiziazi, Rezvan; Bilec, Melissa M. (August 2020, Buildings)

   Given the urgency of climate change, development of fast and reliable methods is essential to understand urban building energy use in the sector that accounts for 40% of total energy use in USA. Although machine learning (ML) methods may offer promise and are less difficult to develop, discrepancy in methods, results, and recommendations have emerged that requires attention. Existing research also shows inconsistencies related to integrating climate change models into energy modeling. To address these challenges, four models: random forest (RF), extreme gradient boosting (XGBoost), single regression tree, and multiple linear regression (MLR), were developed using the Commercial Building Energy Consumption Survey dataset to predict energy use intensity (EUI) under projected heating and cooling degree days by the Intergovernmental Panel on Climate Change (IPCC) across the USA during the 21st century. The RF model provided better performance and reduced the mean absolute error by 4%, 11%, and 12% compared to XGBoost, single regression tree, and MLR, respectively. Moreover, using the RF model for climate change analysis showed that office buildings’ EUI will increase between 8.9% to 63.1% compared to 2012 baseline for different geographic regions between 2030 and 2080. One region is projected to experience an EUI reduction of almost 1.5%. Finally, good data enhance the predicting ability of ML therefore, comprehensive regional building datasets are crucial to assess counteraction of building energy use in the face of climate change at finer spatial scale. 

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3. Mitigation Options to Reduce Peak Air Temperature and Air-Conditioning Demand in the Context of a Warming Climate for a Tropical Coastal City

   https://doi.org/10.1115/1.4051160  

   Pokhrel, Rabindra; González-Cruz, Jorge E. (May 2021, ASME Journal of Engineering for Sustainable Buildings and Cities)

   null (Ed.)

   Abstract Air conditioning (AC) demand has recently grown to about 10% of total electricity globally, and the International Energy Agency (IEA) predicts that the cooling requirement for buildings globally increases by three-fold by 2050 without additional policy interventions. The impacts of these increases for energy demand for human comfort are more pronounced in tropical coastal areas due to the high temperatures and humidity and their limited energy resources. One of those regions is the Caribbean, where building energy demands often exceed 50% of the total electricity, and this demand is projected to increase due to a warming climate. The interconnection between the built environment and the local environment introduces the challenge to find new approaches to explore future energy demand changes and the role of mitigation measures to curb the increasing demands for vulnerable tropical coastal cities due to climate change. This study presents mid-of-century and end-of-century cooling demand projections along with demand alleviation measures for the San Juan Metropolitan Area in the Caribbean Island of Puerto Rico using a high-resolution configuration of the Weather Research and Forecasting (WRF) model coupled with Building Energy Model (BEM) forced by bias-corrected Community Earth Systems Model (CESM1) global simulations. The World Urban Database Access Portal Tool (WUDAPT) Land Class Zones (LCZs) bridge the gap required by BEM for their morphology and urban parameters. MODIS land covers land use is depicted for all-natural classes. The baseline historical period of 2008–2012 is compared with climate and energy projections in addition to energy mitigation options. Energy mitigation options explored include the integration of solar power in buildings, the use of white roofs, and high-efficiency heating, ventilation, and air conditioning (HVAC) systems. The impact of climate change is simulated to increase minimum temperatures at the same rate as maximum temperatures. However, the maximum temperatures are projected to rise by 1–1.5 °C and 2 °C for mid- and end-of-century, respectively, increasing peak AC demand by 12.5% and 25%, correspondingly. However, the explored mitigation options surpass both increases in temperature and AC demand. The AC demand reduction potential with energy mitigation options for 2050 and 2100 decreases the need by 13% and 1.5% with the historical periods. Overall, the demand reduction potential varies with LCZs showing a high reduction potential for sparsely built (32%), and low for compact low rise (21%) for the mid-of-century period compared with the same period without mitigation options. 

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4. Quantifying the Urban Heat Island Effects and Energy Performance of Solar-Reflective Facades: A Simulation Study in a Dense Urban Context

   Chen, C.; Duan, Q.; Zhang, E.; Wang, J. (October 2023, The 18th Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES))

   Many researchers have studied the roles of building envelope materials on UHI, such as roofs, and walls, but few of them have explored the impacts of the emergence of the solar-reflective coatings, films, and panels but well-visible transmittance that is increasingly applied to glazed building facades, especially in hot climates, for outdoor thermal environments. The question then arises: Despite the positive effects of these strong solar-reflective facades on building heating and cooling energy savings, do they have the same positive effects on the adjacent outdoor area, especially in a dense urban context? This research aims to quantify the potential UHI effects of the solar-reflective facades relative to the non-reflective ones in a dense urban context, along with the heating and cooling energy performance analysis. As such, a simulation method in terms of a series of tools including LBNL Radiance, EnergyPlus, and WINDOW software was adopted in this work to analyze the solar radiation interactions between the façade surface and the surrounding urban structures and potential temperature rise under solar-reflective and non-reflective facades. The result shows that the annual cooling energy savings by using the solar-reflective facades are about 33.8% relative to the typical double-pane clear glazed façade because of the substantial reduction of U-factor and solar heat gains; But, this preliminary work also unveils the potential adverse effects of using such materials at the urban scale, leading nearly 2 times greater solar irradiation and UHI effects than the ones by the solar-non-reflective building surfaces in an urban area. Future optimization studies on the trade-off between the building cooling energy savings and UHI effects by the solar-reflective façades need to be conducted. 

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5. Enhancing Urban Thermal Environment and Energy Sustainability With Temperature‐Adaptive Radiative Roofs

   https://doi.org/10.1029/2024EF005246  

   Zhang, Keer; Zhao, Lei; Oleson, Keith; Li, Xinchang “Cathy”; Lee, Xuhui (January 2025, Earth's Future)

   Abstract Urban overheating presents significant challenges to public health and energy sustainability. Conventional radiative cooling strategies, such as cool roofs with high albedo, lead to undesired winter cooling and increased space heating demand for cities with cold winters, a phenomenon known as heating energy penalty. A novel roof coating with high albedo and temperature‐adaptive emissivity (TAE)—low emissivity during cold conditions and high emissivity during hot conditions—has the potential to mitigate winter heating energy penalty. In this study, we implement this roof coating in a global climate model to evaluate its impact on air temperature and building energy demand for space heating and cooling in global cities. Adopting roofs with TAE increases global urban air temperature by up to +0.54°C in the winter (99th percentile; mean change +0.16°C) but has negligible effects on summer urban air temperature (mean change +0.05°C). Combining TAE with high albedo effectively provides summer cooling and does not increase building energy demand in the winter, particularly for mid‐latitude cities. Sensitivities of air temperature to changes in emissivity and albedo are associated with local “apparent” net longwave radiation and incoming solar radiation, respectively. We propose a simple parameterization of air temperature responses to emissivity and albedo to facilitate the development of city‐specific radiative mitigation strategies. This study emphasizes the necessity of developing mitigation approaches specific to local cloudiness. 

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