Search Results (99)

According to the United Nations Environment Programme reports, buildings are responsible for nearly 40% of energy-related emissions; therefore, energy-optimized building design is crucial to reduce the reliance on non-renewable energy sources as well as greenhouse gas emissions. The OECD reports indicate the use of Building Information Modelling (BIM) as one of the effective strategies for decarbonization of buildings, since a 3D digital representation of both physical and functional characteristics of a building can help to design a more efficient infrastructure. An efficient integration of solar energy in building design can be vital for the enhancement of energy performance in terms of heating, cooling, and lighting demand. This paper presents results of an analysis of how factors related to the use of daylight, such as automatic control of artificial lighting, external shading, or the visual absorptance of internal surfaces, influence the energy efficiency within an example room in two different climatic zones. The simulation was conducted using Design Builder software, with predefined occupancy schedules and internal heat gains, and standard EPW weather files for Warsaw and Genua climate zones. The study indicates that for the examined room, when no automatic sunshades or a lighting control system is utilized, most of the final energy demand is for cooling purposes (45–54%), followed by lighting (42–43%), with only 3–12% for heating purposes. The introduction of sunshades and/or the use of daylight allowed for a reduction of the total demand by up to half. Moreover, it was pointed out that often neglected factors, like the colour of the internal surfaces, can have a significant effect on the final energy consumption. In variants with light interior, the total energy consumption was lower by about 3–4% of the baseline demand, compared to their corresponding ones with dark surfaces. These results are consistent with previous studies on daylighting strategies and highlight the importance of considering both visual and thermal impacts when evaluating energy performance. Similarly, possible side effects of certain actions were highlighted, such as an increase in heat demand resulting from a reduced need for artificial lighting. The results of the analysis highlight the potential of a simulation-based design approach in optimizing daylight use, contributing to the broader goals of building decarbonization. Full article

Thermal simulations of buildings play a critical role in optimizing energy efficiency, thermal comfort, and heating, ventilation and air conditioning (HVAC) systems design. Accurate weather data is essential for reliable simulations, as local weather and climate have a significant impact on energy requirements for space heating and cooling and thermal comfort. This study conducted a literature review regarding the sources, types, and uncertainties of weather data used for thermal simulations of buildings, including typical meteorological years (TMYs) and extreme weather files under current and future climates. Additionally, this paper evaluates methods for weather data processing, including interpolation, downscaling, and synthetic generation, to improve simulation accuracy. Finally, approaches are proposed for constructing weather files for the future and extreme conditions under a changing climate. This review aims to provide a guide for researchers and practitioners to enhance the reliability of thermal modeling through informed construction, selection, and application of weather data. Full article

Projected changes in outdoor environmental conditions are expected to significantly alter building energy demand across the United States. Yet, policymakers and designers lack typology and climate-zone-specific guidance to support long-term planning. We simulated 10 U.S. Department of Energy (DOE) prototype buildings across all 16 ASHRAE climate zones with EnergyPlus. Future weather files generated in Meteonorm from a CMIP6 ensemble reflected two emissions pathways (RCP 4.5 and RCP 8.5) and two planning horizons (2050 and 2080), producing 800 simulations. Envelope parameters and schedules were held at DOE reference values to isolate the pure climate signal. Results show that cooling energy use intensity (EUI) in very hot-humid Zones 1A–2A climbs by 12% for full-service restaurants and 21% for medium offices by 2080 under RCP 8.5, while heating EUI in sub-arctic Zone 8 falls by 14–20%. Hospitals and large hotels change by < 6%, showing resilience linked to high internal gains. A simple linear-regression meta-model (R² > 0.90) links baseline EUI to future percentage change, enabling rapid screening of vulnerable stock without further simulation. These high-resolution maps supply actionable targets for state code updates, retrofit prioritization, and long-term decarbonization planning to support climate adaptation and sustainable development. Full article

The aim of this study was to observe soil erosion by wind, depending on the soil physical properties, climatic conditions, and plant canopy, for three representative soil series in the reclaimed tidal flats. Soil samples were collected from the Ap horizon of three soil series to analyze soil physical properties and particle distribution. Precipitation and wind velocities were measured by the weather station installed at the filed. The particle distribution curves showed that the actual proportions of erodible soil particle were in the order of 74.7%(TH), 66.1%(PS), and 62%(JB). The instantaneous and daily maximum wind speeds exceeded the threshold friction velocity (5.78 m s⁻¹) suggested by Chepil. However, the dynamic velocities, depending on the radius of 0.125 mm and 0.42 mm belonging to erodible particle size, were much lower than the threshold friction velocity suggested by Chepil. The wind profile increases logarithmically with height, just above the plant canopy. The vertical gradients of wind velocity for the winter wheat plot were smaller than that of the bare plot due to the relatively rough canopy, and U(Z)c of the bare plot was slightly higher than that of the winter wheat plot with a plant canopy for the given U(Z)m. Conclusively, the actual proportion of erodible particles was much less than that of the particle size limit. Full article

This paper examines the impact of the urban context on the energy performance of a residential building in Athens. Current and future weather files were modified to consider the urban heat island, the overshadowing of adjacent buildings, and the modification of wind speed due to the effects of urban canyons. Dynamic thermal simulations were carried out using the modified weather files. The results indicate that there was a change in heating and cooling demand in comparison to using typical weather files; heating was reduced, but cooling was increased with a total increase in energy demand. There was variation due to height, while overshadowing impacts energy demand significantly. The modified weather analysis also indicates that there are periods in the year that cooling and heating are negligible. During these periods, passive strategies can be used to maintain good internal air quality if occupants are informed how to use their windows and shading devices according to prevailing weather conditions. A method of achieving this occupant-centric operation of the building is described, and the results of an intervention study are discussed. It shows that internal environmental quality can be improved by occupant actions based on forecast weather conditions to direct them. Full article

Current building energy modeling (BEM) tools lack the capability to inherently simulate the impacts of urban microclimates on building energy performance. While efforts have been made to integrate BEM with Urban Microclimate Modeling (UMM) tools, their ability to capture spatial and seasonal microclimate variations remains limited. This review critically evaluates existing urban microclimate-integrated BEM approaches and their effectiveness in modeling the complex interactions between urban form, microclimate, and building energy performance. Through an analysis of 94 research articles, the review first examines the influence of urban form on microclimates, followed by an assessment of how microclimatic conditions impact building energy use. Additionally, it evaluates conventional modeling frameworks employed in BEM tools and their limitations in representing dynamic microclimatic variations. The findings emphasize the non-linear heat exchange relationships between urban form and microclimate, typically modeled using computationally intensive Computational Fluid Dynamics (CFD)-based UMM tools. This review introduces a classification of heat exchange types: atmospheric heat exchange, involving air temperature, wind, and humidity, and non-atmospheric heat exchange, driven by radiative interactions with surrounding urban surfaces. The study further highlights that modifying standard weather files and heat transfer coefficients alone is insufficient for BEM tools to accurately capture near-surface microclimate variations. By identifying critical insights and research gaps, this review establishes a foundation for advancing next-generation urban microclimate-integrated BEM approaches, emphasizing the need for computationally efficient and dynamically responsive modeling techniques. Full article

The overarching goal of this research is to evaluate the energy demands and performance of multi-storey cross-laminated timber (CLT) buildings. The research examines the various energy demands influencing the performance of multi-storey CLT buildings. The study addresses the following research question: Can different energy demands influence the performance of CLT buildings? The investigation explores building modeling and simulation under two different weather scenarios to assess these issues. The study considers London Islington and St Albans (Test Reference Year—TRY), due to the proximity of the actual case studies to the reference locations of the weather files. The investigation captures energy demands and performance in the warm season (i.e., May–August). The findings show that the Stadt building (STB) temperatures under the two weather scenarios are warmer by 1.2 °C and 1.6 °C than those of Brid building (BDH) under the same weather conditions. Outdoor dry-bulb temperatures have a lesser impact on radiant temperatures than indoor air temperatures and operative temperatures in the buildings. Solar gains for external windows are influenced by design variables (e.g., building shapes, heights, floor areas, orientations, opening sizes, etc.). The indoor environmental conditions of the buildings under different weather conditions are comfortable, except for BDH St Albans TRY. Occupancy is a major driver influencing domestic hot water (DHW) usage profiles, regardless of the energy sources in the buildings. DHW is a significant parameter determining the overall energy usage in buildings. Other energy usage profiles, such as room electricity, computers and equipment, general lighting, and lighting, can also impact energy usage in buildings. The research outcomes can enhance our understanding of energy usage profiles and possible improvements to enhance the overall performance of CLT buildings. Full article

This study evaluates the thermal and energy performance of building envelopes incorporating phase change materials (PCM) compared with traditional resistive thermal insulation, considering future climate scenarios. Using EnergyPlus simulations, the study analyzes a medium office building with varying envelope compositions in two distinct Brazilian climates—Curitiba and Rio de Janeiro—representing bioclimatic zones 1 and 8, respectively. The PCM used, SP24E, aligns with the HVAC system setpoints, and climate projections for 2050 and 2080 are integrated using the Climate Change World Weather File Generator (CCWorldWeatherGen) based on the A2 emissions scenario. Results indicate that in mild climates like Curitiba, PCM significantly improves energy efficiency, reducing annual Energy Use Intensity (EUI) by 8.2% in 2050 and 10% in 2080 compared with resistive insulation. Conversely, in hotter climates like Rio de Janeiro, PCM increases EUI by 12.1% in 2050 and 20.7% in 2080 compared with resistive insulation. This study highlights the varying effectiveness of PCM in different climatic conditions and its implications for future building energy performance. Full article

This paper describes the Weather On-Demand (WOD) forecasting framework which is a software stack used to run operational and on-demand weather forecasts. The WOD framework is a distributed system for the following: (1) running the Weather Research and Forecast (WRF) model for data assimilation and forecasts by triggering either scheduled or on-demand jobs; (2) gathering upstream weather forecasts and observations from a wide variety of sources; (3) reducing output data file sizes for permanent storage; (4) making results available through Application Programming Interfaces (APIs); (5) making data files available to custom post-processors. Much effort is put into starting processing as soon as the required data become available, and in parallel where possible. In addition to being able to create short- to medium-range weather forecasts for any location on the globe, users are granted access to a plethora of both global and regional weather forecasts and observations, as well as seasonal outlooks from the National Oceanic and Atmospheric Administration (NOAA) in the USA through WOD integrated-APIs. All this information can be integrated with third-party software solutions via WOD APIs. The software is maintained in the Git distributed version control system and can be installed on suitable hardware, bringing the full flexibility and power of the WRF modelling system to the user in a matter of hours. Full article

With growing concerns over energy and heat-related mortality/morbidity rates, enhancing building performances is key to improving the health and well-being of building occupants while reducing CO₂ emissions, in line with the UK Government’s Net-Zero targets. This study investigates the impacts of different retrofitting scenarios on overheating risk and energy performance in social housing for current and future climate conditions. Dynamic thermal simulations were carried out using Design Summer Year (DSY) weather files in DesignBuilder software for selected case study buildings. Winter performance was analysed using the Predicted Mean Vote (PMV) index, while summer results were assessed according to the Chartered Institution of Building Services Engineers Technical Memorandum 59 (CIBSE TM59) guidelines. The findings revealed that bedrooms, especially those facing south, were at high risk of overheating. Factors such as building construction, the number of exposed surfaces, and window area influenced the risks. External wall insulation outperformed internal wall insulation in improving summer comfort. In the winter, Passivhaus standards with natural ventilation ensured thermal comfort across all zones, with a 41–53% reduction in heating energy consumption under current weather conditions. The risk of overheating and associated health issues significantly increased for the future weather scenarios. Further investigation into ventilation strategies, occupant behaviour, and passive design is required to mitigate overheating risks while reducing energy consumption in buildings. Full article

LoRa-based sensor nodes may provide a reliable solution for wireless communication in orchard cultivation and smart farming, facilitating real-time environmental monitoring. However, the signal strength and data integrity can be affected by several factors, such as trees, terrain, weather, and nearby electrical devices. The objective of this study is to evaluate the impact of orchard trees on the performance of a LoRa sensor node under orchard conditions. A sensor node, built with a commercial LoRa transceiver and microcontroller unit (MCU), was paired with a single-channel gateway linked to an orchard irrigation system. Performance metrics such as the packet delivery ratio (PDR), received signal strength indicator (RSSI), and signal-to-noise ratio (SNR) were measured over a range of 20 to 120 m under open field conditions and in an orchard with trees averaging 3.12 and 4.36 m in height. Data were sent every 20 s using three spreading factors (SF8, SF10, and SF12) and stored as a CSV file in the MCU via a Python program. The results showed that the PDR remained consistently high (100%) under non-vegetative (open field) conditions. In the orchard under vegetative conditions, the PDR dropped significantly, with SF12 maintaining 100% only up to 120 m. For SF10, the packet delivery rates dropped to 45% at 80 m, while SF8 achieved 100% at 20 m but decreased to 52% at 40 m. SNR values also declined with an increase in distance, becoming largely undetectable beyond 40 m for SF8. These findings indicate that vegetation greatly impacts LoRa sensor node performance, reducing packet delivery and signal quality in orchards. Full article

Although the European residential sector has promoted various heating and cooling passive solar systems in many ways, ongoing climate changes affect these construction elements at an annual level. Using the weather files for three years in the recent past (2018, 2021 and 2023), this paper numerically investigates the energy, environmental and economic performance of two small single-family houses equipped with Trombe walls and fixed horizontal overhangs of different depths (0 m, 0.25 m, 0.5 m, 0.75 m and 1 m) for two characteristic European climate zones: continental (Kielce city, Poland) and moderate continental (Kragujevac city, Serbia). Both houses were created in Google SketchUp 8 software using current Statistical data and Rulebooks of energy efficiency, while adopted heating (gas boiler and radiators) and cooling (individual air-conditioning units) active thermo-technical systems were simulated in EnergyPlus 7.1 software using official specific energy, environmental and economic indicators. Compared to the appropriate reference houses—without mentioning passive solar systems—the main results of this study are as follows: (1) higher outdoor air temperatures can reduce final (thermal) energy consumption for heating by 37.74% (for the Kielce climate zone) and 52.49% (for the Kragujevac climate zone); (2) higher outdoor air temperatures can increase final (electricity) energy consumption for cooling between 5.71 and 11.75 times (for Kielce) and 4.36 and 9.81 times (for Kragujevac); (3) percentage savings of primary energy consumption and monetary savings are highest when houses are equipped with Trombe walls and 1 m deep overhangs; and (4) all considered cases of passive solar systems do not contribute to the reduction of greenhouse gas emissions. Since climate change is a consequence of greenhouse gas emissions, priority should be given to environmental indicators in future investigations. Full article

Buildings exchange heat with different environmental elements: the sun, the outside air, the sky, and outside surfaces (including the walls of environmental buildings and the ground). To correctly account for building energy performance, radiative cooling potential, and other technical considerations, it is essential to evaluate sky temperature. It is an important parameter for the weather files used by energy building simulation software for calculating the longwave radiation heat exchange between exterior surfaces and the sky. In the literature, there are several models to estimate sky temperature. However, these models have not been completely satisfactory for the hot and humid climate in which the sky temperature remains overestimated. The purpose of this paper is to provide a comprehensive analysis of the sky temperature measurement conducted, for the first time, in Djibouti, with a pyrgeometer, a tool designed to measure longwave radiation as a component of thermal radiation, and an artificial neural network (ANN) model for improved sky temperature forecasting. A systematic comparison of known correlations for sky temperature estimation under various climatic conditions revealed their limited accuracy in the region, as indicated by low R² values and root mean square errors (RMSEs). To address these limitations, an ANN model was trained, validated, and tested on the collected data to capture complex patterns and relationships in the data. The ANN model demonstrated superior performance over existing empirical correlations, providing more accurate and reliable sky temperature predictions for Djibouti’s hot and humid climate. This study showcases the effectiveness of an integrated approach using pyrgeometer-based sky temperature measurements and advanced machine learning techniques ANNs for sky temperature forecasting in Djibouti to overcome the limitations of existing correlations and improve the accuracy of sky temperature predictions, particularly in hot and humid climates. Full article

A method for a real-time now- and forecasting hydraulic and quality simulation model for combined sewer networks, based on an enhanced version of the Storm Water Management Model (SWMM) simulator, with added support for storing the hot start file at any time during the simulation, the rotational speed control of the pumps, multiple dry weather flows with unique patterns, and improvements for quality simulations over control devices is presented. The methodology is applied in the combined sewer network of Helsinki, Finland. The model includes all pipes and dry weather flows, including the pollutants, catchment hydrology, infiltration, snowpacks, and other climate aspects. Full article

Climate change significantly affects the operating environment of buildings. These changes impact both energy efficiency and occupants’ comfort and remain crucial even in building restoration, where design decisions typically rely on historical data, yet performance depends on anticipated future scenarios. The present work evaluates the impact of different climate datasets on dynamic energy simulations for an educational building in Central Italy, focusing on estimating heating demands across historical, current, and future climatic scenarios. The assessment considers both the building’s current state and potential energy-efficient retrofits. Initially, various meteorological datasets, including measured and model-generated data, are selected to predict key weather parameters. The analysis reveals the potential and limitations of regional climate models (RCMs) in estimating these variables, with the MM5 dataset emerging as the most reliable. Subsequently, the energy performance of the reference building and its vulnerability to climate change are assessed. Our results show significant differences in energy demand based on construction periods, with the oldest section consuming 29% to 54% more energy monthly than the newer sections. Moreover, using non-representative climatic files can lead to prediction errors of up to 199%. Finally, the building’s energy behaviour is analysed under future climate conditions by generating typical meteorological years (TMYs) for 2030, 2050, and 2070. This analysis evaluates the energy requirements for both existing and retrofitted building configurations. The findings confirm that retrofit interventions with high-performance insulation and upgraded windows significantly enhance the building’s energy efficiency and resilience to future climate conditions, leading to annual energy savings of 50% to 57%. Full article