Influence of Street Canyon's Microclimate on the Energy Demand for Space Cooling and Heating of Buildings

Analysis of urban streets and surface thermal characteristics using thermal imaging camera in residential streets of Gurugram City, India

The thermal properties of the urban landscape are significantly affected by various human activities such as changing land use patterns, the construction of buildings and other impervious surfaces, and the development of transport systems. Urbanization often leads to the replacement of natural landscapes with impervious surfaces such as concrete and asphalt, which have a higher heat absorption capacity and lower emissivity. The continuous displacement of urban landscapes by impermeable surfaces therefore leads to an increase in urban temperatures, ultimately causing the development of the urban heat island (UHI) phenomenon. The study aims to analyze the thermal properties of physical elements in residential streets of Gurugram City using a thermal imaging camera to investigate the relationship between ambient air temperature and thermal behavior of surface materials. The study shows that the compact streets are 2-4 °C cooler than the open streets due to mutual shading of the buildings. Similarly, the temperature in the light-colored buildings is 1.5-4 °C lower than the dark buildings in the streets. In addition, a simple coat of paint over a plastered wall is much cooler than granite stone wall cladding. The study also showed how shading, whether by mutual shading or vegetative shading, can lower the surface temperature of urban materials. Building codes and design guidelines can therefore use such studies to make urban exteriors more pleasant by recommending lighter colors, plants, and local materials.

Revealing Microclimate around Buildings with Long-Term Monitoring through the Neural Network Algorithms

The profile of urban microclimates is important in many engineering fields, such as occupant’s thermal comfort and health, and other building engineering. To predict the profile of urban microclimate, this study applies the artificial neural network and long short-term memory network predictive models, and an urban microclimate dataset was obtained with a long-term monitoring from year 2017 to 2019 with 5-min resolution including temperature, relative humidity, and solar radiation. Two predictive models were applied, and the first (Model 1) is to apply the predictive techniques to predict the urban microclimate in the real-time sequence, and then extract the characteristics of urban microclimate, while the second (Model 2) is to directly extract the characteristics of the microclimate, and then predict the characteristics of the microclimate. Backpropagation artificial neural network (BP-ANN) and long-short term memory (LSTM) techniques were applied in both models. The results show Model 1 with as the time-series prediction can reach the best (99.92%) of correlation coefficient and 98% of the mean average percentage error (MAPE), for temperature, while 99.66% and 98.18% for relative humidity, respectively, while accuracies in Model 2 decreased to 79% and 88.6% of MAPE for temperature and relative humidity, respectively. The prediction of solar radiation using ANN and LSTM are 51.1% and 57.8% of the correlation coefficient, respectively.

On the Optimisation of Urban form Design, Energy Consumption and Outdoor Thermal Comfort Using a Parametric Workflow in a Hot Arid Zone

The recent reports from the Intergovernmental Panel on Climate Change (IPCC) urge for the reconceptualization of our design of the urban built environments. However, current efforts to integrate urban environmental assessment into practice in Egypt are proving insufficient. This paper utilises the Ladybug tools simulation plugins to investigate the impact of changing the morphological characteristics of three-block typologies (scattered, linear and courtyard) and their associated parameters to understand their multidimensional relationship with environmental conditions, outdoor thermal comfort and energy use intensity. This study based in Cairo, Egypt, considers 3430 hypothetical geometrical configurations comprising of a variety of design parameters and indicators. The results show a strong correlation between the design parameters and the combined performance of thermal comfort and energy consumption (R2 = 0.84), with urban density having the strongest impact on both thermal comfort and energy use (R2 = 0.7 and 0.95, respectively). The design parameters exhibited a consistent impact on the different typologies, albeit with varying magnitude. Compact and medium-density urban forms are shown to elicit the best overall performance, especially for ordinal orientations (e.g., ~45°) across all typologies. Compact high-density scattered forms are favoured when considering thermal comfort, while courtyards outperform other typologies when considering energy efficiency and overall performance.

Study on Passive Ventilation and Cooling Strategies for Cold Lanes and Courtyard Houses—A Case Study of Rural Traditional Village in Shaanxi, China

China’s research on and specific implementation of energy saving for buildings are mainly concentrated in urban areas, but according to 2016 statistics, the rural population accounts for 42.65% of the total population, so rural housing has considerable energy-saving potential. However, the degree of attention to the energy consumption of rural houses needs to be improved. Regarding the research on and implementation of passive energy-saving strategies for residences, compared with centralized urban high-rise residences, rural residences mainly have independent courtyards, with a flexible layout and easier transformation. In this study, a system that uses the common cold lanes in traditional villages and buildings’ exterior walls was constructed, and the indoor spaces of courtyard buildings in southern Shaanxi were completely passively cooled in summer. This system can be completely separated from the supply of artificial energy by relying on the accumulation and buoyancy effects of air in patios and cold lanes and the hot-pressure ventilation in buildings to cool the buildings and greatly improve indoor ventilation efficiency. As the building is ventilated and cooled, the air wall formed in the system can effectively prevent direct contact between the outdoor and indoor temperatures and reduce the impact of thermal wall radiation on the interior. In previous studies on the passive design of courtyard houses, scholars considered the effect of thermal wall radiation on indoor temperature in simulations. Therefore, in this study, we also separately calculated whether to consider the difference between the situation with and without wall heat radiation (WHR) when simulating thermal conversion. The final results show that when the cooling system was adopted, the annual cooling load of the whole building was 4786.494 kW·h without WHR. However, with WHR, the cooling load reduction was 2989.128 kW·h, a difference of 1797.336 kW·h.

Energy Consumption Models at Urban Scale to Measure Energy Resilience

Energy resilience can be reached with a secure, sustainable, competitive, and affordable system. In order to achieve energy resilience in the urban environment, urban-scale energy models play a key role in supporting the promotion and identification of effective energy-efficient and low-carbon policies pertaining to buildings. In this work, a dynamic urban-scale energy model, based on an energy balance, has been designed to take into account the local climate conditions and morphological urban-scale parameters. The aim is to present an engineering methodology, applied to clusters of buildings, using the available urban databases. This methodology has been calibrated and optimized through an iterative procedure on 102 residential buildings in a district of the city of Turin (Italy). The results of this work show how a place-based dynamic energy balance methodology can also be sufficiently accurate at an urban scale with an average seasonal relative error of 14%. In particular, to achieve this accuracy, the model has been optimized by correcting the typological and geometrical characteristics of the buildings and the typologies of ventilation and heating system; in addition, the indoor temperatures of the buildings—that were initially estimated as constant—have been correlated to the climatic variables. The proposed model can be applied to other cities utilizing the existing databases or, being an engineering model, can be used to assess the impact of climate change or other scenarios.