• Energy Research

Meteorological measurements are conducted in Antwerp, Belgium in July 2013, followed by CFD urban microclimate simulations considering the same city and time period. The simulations are found to be able to reproduce measured air temperatures inside central Antwerp with an average absolute difference of 0.88 °C. The simulation results supplemented with measurements are used to generate location-specific Microclimatic Conditions (MCs) in three locations: (1) a rural location outside Antwerp; (2) an urban location inside Antwerp, away from an urban park; and (3) another urban location, close to the same park. Building Energy Simulations (BES) are performed for 36 cases based on three different MCs, two building use types and six sets of construction characteristics, ranging from pre-1946 buildings to new, low-energy buildings. Monthly Cooling Demands (CDs) are extracted for each case and compared with each other. The results demonstrate that compared to the air temperatures in the rural area, on average, air temperatures at the urban sites away and close to the park are 3.3 °C and 2.4 °C higher, respectively. This leads to an additional monthly CD of up to 90%. CDs of buildings with better thermal insulation and lower infiltration rates can increase by 48% once moved from the rural location to an urban location, which may lead to the reconsideration of design guidelines of low-energy buildings exposed to an urban MC. Although the proximity of an urban park cannot fully compensate the increased CD by an urban MC, residential buildings close to the park are found to have on average 13.9% less CD during July 2013, compared with buildings away from the same park. The influence of the urban park on the CDs of buildings in its vicinity is strongly linked to the meteorological wind direction. Professionals focusing on energy-efficient buildings in cities are advised to conduct energy predictions with location-specific MC data, instead of only using city-averaged meteorological data.

Urban microclimate studies are gaining popularity due to rapid urbanization. Many studies documented that urban microclimate can affect building energy performance, human morbidity and mortality and thermal comfort. Historically, urban microclimate studies were conducted with observational methods such as field measurements. In the last decades, with the advances in computational resources, numerical simulation approaches have become increasingly popular. Nowadays, especially simulations with Computational Fluid Dynamics (CFD) is frequently used to assess urban microclimate. CFD can resolve the transfer of heat and mass and their interaction with individual obstacles such as buildings. Considering the rapid increase in CFD studies of urban microclimate, this paper provides a review of research reported in journal publications on this topic till the end of 2015. The studies are categorized based on the following characteristics: morphology of the urban area (generic versus real) and methodology (with or without validation study). In addition, the studies are categorized by specifying the considered urban settings/locations, simulation equations and models, target parameters and keywords. This review documents the increasing popularity of the research area over the years. Based on the data obtained concerning the urban location, target parameters and keywords, the historical development of the studies is discussed and future perspectives are provided. According to the results, early CFD microclimate studies were conducted for model development and later studies considered CFD approach as a predictive methodology. Later, with the established simulation setups, research efforts shifted to case studies. Recently, an increasing amount of studies focus on urban scale adaptation measures. The review hints a possible change in this trend as the results from CFD simulations can be linked up with different aspects (e.g. economy) and with different scales (e.g. buildings), and thus, CFD can play an important role in transferring urban climate knowledge into engineering and design practice.

Accurate Computational Fluid Dynamics (CFD) simulations of Atmospheric Boundary Layer (ABL) flow are essential for a wide range of applications, including atmospheric heat and pollutant dispersion. An important requirement is that the imposed inlet boundary conditions should yield vertical profiles that maintain horizontal homogeneity (i.e. no streamwise gradients) in the upstream part of the computational domain for all relevant parameters, including temperature. Many previous studies imposed a uniform temperature profile at the inlet, which has often led to horizontal inhomogeneity of the temperature profile. This study presents a new temperature inlet profile that can yield horizontal homogeneity for neutral and near-neutral ABL conditions when used in combination with the Standard Gradient Diffusion Hypothesis (SGDH) and a temperature wall function. The horizontal homogeneity by this profile is verified by 2D Reynolds-Averaged Navier-Stokes (RANS) CFD simulations performed with the standard k-ε turbulence model and the SGDH. The approach in this paper can be extended to other types of wall functions and other RANS closure schemes for Reynolds stresses and turbulent heat fluxes.

The average summer temperatures as well as the frequency and intensity of hot days and heat waves are expected to increase due to climate change. Motivated by this consequence, we propose a methodology to evaluate the monthly heat wave hazard and risk and its spatial distribution within large cities. A simple urban climate model with assimilated satellite-derived land surface temperature images was used to generate a historic database of urban air temperature fields. Heat wave hazard was then estimated from the analysis of these hourly air temperatures distributed at a 1-km grid over Athens, Greece, by identifying the areas that are more likely to suffer higher temperatures in the case of a heat wave event. Innovation lies in the artificial intelligence fuzzy logic model that was used to classify the heat waves from mild to extreme by taking into consideration their duration, intensity and time of occurrence. The monthly hazard was subsequently estimated as the cumulative effect from the individual heat waves that occurred at each grid cell during a month. Finally, monthly heat wave risk maps were produced integrating geospatial information on the population vulnerability to heat waves calculated from socio-economic variables.

A new dynamical downscaling methodology to analyze the impact of global climate change on the local climate of cities worldwide is presented. The urban boundary layer climate model UrbClim is coupled to 11 global climate models contained in the Coupled Model Intercomparison Project 5 archive, conducting 20-year simulations for present (1986–2005) and future (2081–2100) climate conditions, considering the Representative Concentration Pathway 8.5 climate scenario. The evolution of the urban heat island of eight different cities, located on three continents, is quantified and assessed, with an unprecedented horizontal resolution of a few hundred meters. For all cities, urban and rural air temperatures are found to increase strongly, up to 7 °C. However, the urban heat island intensity in most cases increases only slightly, often even below the range of uncertainty. A potential explanation, focusing on the role of increased incoming longwave radiation, is put forth. Finally, an alternative method for generating urban climate projections is proposed, combining the ensemble temperature change statistics and the results of the present-day urban climate.

Urban analysis at different spatial scales (micro- and mesoscale) of local climate conditions is required to test typical artificial urban boundaries and related climate hazards such as high temperatures in built environments. The multitude of finishing materials and sheltering objects within built environments produce distinct patterns of different climate conditions, particularly during the daytime. The combination of high temperatures and intense solar radiation strongly perturb the environment by increasing the thermal heat stress at the pedestrian level. Therefore, it is becoming common practice to use numerical models and tools that enable multiple design and planning alternatives to be quantitatively and qualitatively tested to inform urban planners and decision-makers. These models and tools can be used to compare the relationships between the micro-climatic environment, the subjective thermal assessment, and the social behaviour, which can reveal the attractiveness and effectiveness of new urban spaces and lead to more sustainable and liveable public spaces. This review article presents the applications of selected environmental numerical models and tools to predict human thermal stress at the mesoscale (e.g., satellite thermal images and UrbClim) and the microscale (e.g., mobile measurements, ENVI-met, and UrbClim HR) focusing on case study cities in mid-latitude climate regions framed in two European research projects.