Analysis of the urban heat island effects on building energy consumption

Urban areas usually experience higher temperatures when compared to their rural surroundings. Several studies underlined that specific urban conditions are strictly connected with the Urban heat island (UHI) phenomenon, which consists in the environmental overheating related to anthropic activities. As a matter of fact, urban areas, characterized by massive constructions that reduce local vegetation coverage, are subject to the absorption of a great amount of solar radiation (short wave) which is only partially released into the atmosphere by radiation in the thermal infrared (long wave). On the contrary, green areas and rural environments in general show a reduced UHI effect, that is lower air temperatures, due to evapo-transpiration fluxes. Several studies demonstrate that urban microclimate affects buildings’ energy consumption and calculations based on typical meteorological year could misestimate their actual energy consumption. In this study, two different sets of meteorological data are used for the calculation of the heating and cooling energy needs of an existing university building. The building is modeled using TRNSYS v.17 software. The first set of data was collected by a weather station located in the city center of Modena, while the second set of data was collected by another station, located in the surrounding area of the city, near to the studied building. The influence of the different meteorological situations described by the two weather stations are analyzed and assumed to be representative of the UHI effect. Furthermore, the effects of UHI mitigation strategies on the building energy needs are evaluated and discussed

The International Urban Energy Balance Models Comparison Project: First Results from Phase 1

A large number of urban surface energy balance models now exist with different assumptions about the important features of the surface and exchange processes that need to be incorporated. To date, no com- parison of these models has been conducted; in contrast, models for natural surfaces have been compared extensively as part of the Project for Intercomparison of Land-surface Parameterization Schemes. Here, the methods and first results from an extensive international comparison of 33 models are presented. The aim of the comparison overall is to understand the complexity required to model energy and water exchanges in urban areas. The degree of complexity included in the models is outlined and impacts on model performance are discussed. During the comparison there have been significant developments in the models with resulting improvements in performance (root-mean-square error falling by up to two-thirds). Evaluation is based on a dataset containing net all-wave radiation, sensible heat, and latent heat flux observations for an industrial area in Vancouver, British Columbia, Canada. The aim of the comparison is twofold: to identify those modeling ap- proaches that minimize the errors in the simulated fluxes of the urban energy balance and to determine the degree of model complexity required for accurate simulations. There is evidence that some classes of models perform better for individual fluxes but no model performs best or worst for all fluxes. In general, the simpler models perform as well as the more complex models based on all statistical measures. Generally the schemes have best overall capability to model net all-wave radiation and least capability to model latent heat flux

Anthropogenic heat flux: advisable spatial resolutions when input data are scarce

Anthropogenic heat flux (QF) may be significant in cities, especially under low solar irradiance and at night. It is of interest to many practitioners including meteorologists, city planners and climatologists. QF estimates at fine temporal and spatial resolution can be derived from models that use varying amounts of empirical data. This study compares simple and detailed models in a European megacity (London) at 500 m spatial resolution. The simple model (LQF) uses spatially resolved population data and national energy statistics. The detailed model (GQF) additionally uses local energy, road network and workday population data. The Fractions Skill Score (FSS) and bias are used to rate the skill with which the simple model reproduces the spatial patterns and magnitudes of QF, and its sub-components, from the detailed model. LQF skill was consistently good across 90% of the city, away from the centre and major roads. The remaining 10% contained elevated emissions and B hot spots ^ representing 30 – 40% of the total city-wide energy. This structure was lost because it requires workday population, spatially resolved building energy consumption and/or road network data. Daily total building and traffic energy consumption estimates from national data were within ± 40% of local values. Progressively coarser spatial resolutions to 5 km improved skill for total Q F , but important features (hot spots, transport network) were lost at all resolutions when residential population controlled spatial variations. The results demonstrate that simple QF models should be applied with conservative spatial resolution in cities that, like London, exhibit time-varying energy use patterns

Local-scale urban meteorological parameterization scheme (LUMPS): longwave radiation parameterization and seasonality-related developments

Recent developments to the Local-scale Urban Meteorological Parameterization Scheme (LUMPS), a simple model able to simulate the urban energy balance, are presented. The major development is the coupling of LUMPS to the Net All-Wave Radiation Parameterization (NARP). Other enhancements include that the model now accounts for the changing availability of water at the surface, seasonal variations of active vegetation, and the anthropogenic heat flux, while maintaining the need for only commonly available meteorological observations and basic surface characteristics. The incoming component of the longwave radiation (L↓) in NARP is improved through a simple relation derived using cloud cover observations from a ceilometer collected in central London, England. The new L↓ formulation is evaluated with two independent multiyear datasets (Łódź, Poland, and Baltimore, Maryland) and compared with alternatives that include the original NARP and a simpler one using the National Climatic Data Center cloud observation database as input. The performance for the surface energy balance fluxes is assessed using a 2-yr dataset (Łódź). Results have an overall RMSE < 34 W m−2 for all surface energy balance fluxes over the 2-yr period whe