scholarly journals Influence of Air-Conditioning Waste Heat on Air Temperature in Tokyo during Summer: Numerical Experiments Using an Urban Canopy Model Coupled with a Building Energy Model

2007 ◽  
Vol 46 (1) ◽  
pp. 66-81 ◽  
Author(s):  
Yukitaka Ohashi ◽  
Yutaka Genchi ◽  
Hiroaki Kondo ◽  
Yukihiro Kikegawa ◽  
Hiroshi Yoshikado ◽  
...  

Abstract A coupled model consisting of a multilayer urban canopy model and a building energy analysis model has been developed to investigate the diurnal variations of outdoor air temperature in the office areas of Tokyo, Japan. Observations and numerical experiments have been performed for the two office areas in Tokyo. The main results obtained in this study are as follows. The coupled model has accurately simulated the air temperature for a weekday case in which released waste heat has been calculated from the energy consumption and cooling load in the buildings. The model has also simulated the air temperature for a holiday case. However, the waste heat from the buildings has little influence on the outdoor temperatures and can be neglected because of the low working activity in the buildings. The waste heat from the air conditioners has caused a temperature rise of 1°–2°C or more on weekdays in the Tokyo office areas. This heating promotes the heat-island phenomenon in Tokyo on weekdays. Thus, it is shown that the energy consumption process (mainly with air conditioning) in buildings should be included in the modeling of summertime air temperature on weekdays in urban areas.

2005 ◽  
Vol 116 (3) ◽  
pp. 395-421 ◽  
Author(s):  
Hiroaki Kondo ◽  
Yutaka Genchi ◽  
Yukihiro Kikegawa ◽  
Yukitaka Ohashi ◽  
Hiroshi Yoshikado ◽  
...  

Author(s):  
Luxi Jin ◽  
Sebastian Schubert ◽  
Mohamed Hefny Salim ◽  
Christoph Schneider

This study investigates the effect of anthropogenic heat emissions from air conditioning systems (AC) on air temperature and AC energy consumption in Berlin, Germany. We conduct simulations applying the model system CCLM/DCEP-BEM, a coupled system of the mesoscale climate model COSMO-CLM (CCLM) and the urban Double Canyon Effect Parameterization scheme with a building energy model (DCEP-BEM), for a summer period of 2018. The DCEP-BEM model is designed to explicitly compute the anthropogenic heat emissions from urban buildings and the heat flux transfer between buildings and the atmosphere. We investigate two locations where the AC outdoor units are installed: either on the wall of a building (VerAC) or on the rooftop of a building (HorAC). AC waste heat emissions considerably increase the near-surface air temperature. Compared to a reference scenario without AC systems, the VerAC scenario with a target indoor temperature of 22 ∘ C results in a temperature increase of up to 0.6 K . The increase is more pronounced during the night and for urban areas. The effect of HorAC on air temperature is overall smaller than in VerAC. With the target indoor temperature of 22 ∘ C , an urban site’s daily average AC energy consumption per floor area of a room is 9.1 W   m 2 , which is 35% more than that of a suburban site. This energy-saving results from the urban heat island effect and different building parameters between both sits. The maximum AC energy consumption occurs in the afternoon. When the target indoor temperature rises, the AC energy consumption decreases at a rate of about 16% per 2 K change in indoor temperature. The nighttime near-surface temperature in VerAC scenarios shows a declining trend ( 0.06 K per 2 K change) with increasing target indoor temperature. This feature is not obvious in HorAC scenarios which further confirms that HorAC has a smaller impact on near-surface air temperature.


2011 ◽  
Vol 140 (3) ◽  
pp. 471-489 ◽  
Author(s):  
Bruno Bueno ◽  
Leslie Norford ◽  
Grégoire Pigeon ◽  
Rex Britter

2011 ◽  
Vol 50 (5) ◽  
pp. 1107-1128 ◽  
Author(s):  
Francisco Salamanca ◽  
Alberto Martilli ◽  
Mukul Tewari ◽  
Fei Chen

AbstractIn the last two decades, mesoscale models (MMs) with urban canopy parameterizations have been widely used to study urban boundary layer processes. Different studies show that such parameterizations are sensitive to the urban canopy parameters (UCPs) that define the urban morphology. At the same time, high-resolution UCP databases are becoming available for several cities. Studies are then needed to determine, for a specific application of an MM, the optimum degree of complexity of the urban canopy parameterizations and the resolution and details necessary in the UCP datasets. In this work, and in an attempt to answer the previous issues, four urban canopy schemes, with different degrees of complexity, have been used with the Weather Research and Forecasting (WRF) model to simulate the planetary boundary layer over the city of Houston, Texas, for two days in August 2000. For the UCP two approaches have been considered: one based on three urban classes derived from the National Land Cover Data of the U.S. Geological Survey and one based on the highly detailed National Urban Database and Access Portal Tool (NUDAPT) dataset with a spatial resolution of 1 km2. Two-meter air temperature and surface wind speed have been used in the evaluation. The statistical analysis shows a tendency to overestimate the air temperatures by the simple bulk scheme and underestimate the air temperatures by the more detailed urban canopy parameterizations. Similarly, the bulk and single-layer schemes tend to overestimate the wind speed while the multilayer schemes underestimate it. The three-dimensional analysis of the meteorological fields revealed a possible impact (to be verified against measurements) of both the urban schemes and the UCP on cloud prediction. Moreover, the impact of air conditioning systems on the air temperature and their energy consumption has been evaluated with the most developed urban scheme for the two simulated days. During the night, this anthropogenic heat was responsible for an increase in the air temperature of up to 2°C in the densest urban areas, and the estimated energy consumption was of the same magnitude as energy consumption obtained with different methods when the most detailed UCP database was used. On the basis of the results for the present case study, one can conclude that if the purpose of the simulation requires only an estimate of the 2-m temperature a simple bulk scheme is sufficient but if the purpose of the simulation is an evaluation of an urban heat island mitigation strategy or the evaluation of the energy consumption due to air conditioning at city scale, it is necessary to use a complex urban canopy scheme and a detailed UCP.


2019 ◽  
pp. 53-65
Author(s):  
Renata Domingos ◽  
Emeli Guarda ◽  
Elaise Gabriel ◽  
João Sanches

In the last decades, many studies have shown ample evidence that the existence of trees and vegetation around buildings can contribute to reduce the demand for energy by cooling and heating. The use of green areas in the urban environment as an effective strategy in reducing the cooling load of buildings has attracted much attention, though there is a lack of quantitative actions to apply the general idea to a specific building or location. Due to the large-scale construction of high buildings, large amounts of solar radiation are reflected and stored in the canyons of the streets. This causes higher air temperature and surface temperature in city areas compared to the rural environment and, consequently, deteriorates the urban heat island effect. The constant high temperatures lead to more air conditioning demand time, which results in a significant increase in building energy consumption. In general, the shade of the trees reduces the building energy demand for air conditioning, reducing solar radiation on the walls and roofs. The increase of urban green spaces has been extensively accepted as effective in mitigating the effects of heat island and reducing energy use in buildings. However, by influencing temperatures, especially extreme, it is likely that trees also affect human health, an important economic variable of interest. Since human behavior has a major influence on maintaining environmental quality, today's urban problems such as air and water pollution, floods, excessive noise, cause serious damage to the physical and mental health of the population. By minimizing these problems, vegetation (especially trees) is generally known to provide a range of ecosystem services such as rainwater reduction, air pollution mitigation, noise reduction, etc. This study focuses on the functions of temperature regulation, improvement of external thermal comfort and cooling energy reduction, so it aims to evaluate the influence of trees on the energy consumption of a house in the mid-western Brazil, located at latitude 15 ° S, in the center of South America. The methodology adopted was computer simulation, analyzing two scenarios that deal with issues such as the influence of vegetation and tree shade on the energy consumption of a building. In this way, the methodological procedures were divided into three stages: climatic contextualization of the study region; definition of a basic dwelling, of the thermophysical properties; computational simulation for quantification of energy consumption for the four facade orientations. The results show that the façades orientated to north, east and south, without the insertion of arboreal shading, obtained higher values of annual energy consumption. With the adoption of shading, the facades obtained a consumption reduction of around 7,4%. It is concluded that shading vegetation can bring significant climatic contribution to the interior of built environments and, consequently, reduction in energy consumption, promoting improvements in the thermal comfort conditions of users.


2017 ◽  
Vol 56 (8) ◽  
pp. 2173-2187 ◽  
Author(s):  
James Brownlee ◽  
Pallav Ray ◽  
Mukul Tewari ◽  
Haochen Tan

AbstractNumerical simulations without hydrological processes tend to overestimate the near-surface temperatures over urban areas. This is presumably due to underestimation of surface latent heat flux. To test this hypothesis, the existing single-layer urban canopy model (SLUCM) within the Weather Research and Forecasting Model is evaluated over Houston, Texas. Three simulations were conducted during 24–26 August 2000. The simulations include the use of the default “BULK” urban scheme, the SLUCM without hydrological processes, and the SLUCM with hydrological processes. The results show that the BULK scheme was least accurate, and it overestimated the near-surface temperatures and winds over the urban regions. In the presence of urban hydrological processes, the SLUCM underestimates these parameters. An analysis of the surface heat fluxes suggests that the error in the BULK scheme is due to a lack of moisture at the urban surface, whereas the error in the SLUCM with hydrological processes is due to increases in moisture at the urban surface. These results confirm earlier studies in which changes in near-surface temperature were primarily due to the changes in the turbulent (latent and sensible heat) fluxes in the presence of hydrological processes. The contribution from radiative flux was about one-third of that from turbulent flux. In the absence of hydrological processes, however, the results indicate that the changes in radiative flux contribute more to the near-surface temperature changes than the turbulent heat flux. The implications of these results are discussed.


2016 ◽  
Author(s):  
M. García-Díez ◽  
D. Lauwaet ◽  
H. Hooyberghs ◽  
J. Ballester ◽  
K. De Ridder ◽  
...  

Abstract. As most of the population lives in urban environments, the simulation of the urban climate has become a key problem in the framework of the climate change impact assessment. However, the high computational power required by these simulations is a severe limitation. Here we present a study on the performance of a Urban Climate Model (UrbClim), designed to be several orders of magnitude faster than a full-fledge mesoscale model. The simulations are validated with station data and with land surface temperature observations retrieved by satellites. To explore the advantages of using a simple model like UrbClim, the results are compared with a simulation carried out with a state-of-the-art mesoscale model, the Weather Research and Forecasting model, using an Urban Canopy model. The effect of using different driving data is explored too, by using both relatively low resolution reanalysis data (70 km) and a higher resolution forecast model (15 km). The results show that, generally, the performance of the simple model is comparable to or better than the mesoscale model. The exception are the winds and the day-to-day correlation in the reanalysis driven run, but these problems disappear when taking the boundary conditions from the higher resolution forecast model.


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