Globally, urbanization has altered the surface heat flux and the emission flux which has significantly affected the micro and macro climatic trends. Urban Heat Island (UHI) phenomenon, altered precipitation cycles and the extended green house gas effect are one of the few artificially induced global environmental hazards. UHIs significantly affect the health of the people, the energy consumption and the overall environment. Delhi, the capital of India, has witnessed rampant urbanization in the past few decades. This change in the land use / land cover has resulted in the formation of many micro-urban heat islands which have altered the macro and micro climate of Delhi. The present study attempts to put light on the growth of the UHIs across Delhi and translates the UHI effect into power consumption for space-cooling. Remotely sensed annual land surface temperature for the duration 2001-2011 and the field campaign done for collecting ambient temperature and relative humidity across 30 locations during 27-28 May, 2008 were used for micromapping the UHIs of Delhi while multiple micro-climatic data was used for simulating the impact of UHI on power consumption for space-cooling using a building energy model. The mapping of the land surface temperature was done using Geographic Information System (Arc GIS 9.3) while building energy model ‘eQUEST’ was used for energy simulation. The UHI maps were further interfaced with the land use / land cover maps and the population maps.

The results reveal that the UHI intensity across Delhi was as high as 8.3°C. Moreover, the high UHI intensity zones almost remain unchanged but new zones of moderate UHI intensity appeared. The building energy simulations done using the multiple micro-climatic data representing various land use / land covers like built-up canopies which includes dense, medium dense and less dense, forest canopy, water body and rural canopy reveal that the UHI effect has significantly increased the power consumption. In the background of the urbanizing process, the paper thus discusses the changing micro-urban climate viz.-a-viz. the UHI effect across Delhi and its impact of the power consumption for space cooling.

The urban heat island (UHI) phenomenon has been more accelerated and the outdoor air temperature (OT) has become higher. Such OT rise is posing an increase in electricity consumption (EC) for air conditioning. Nowadays, many UHI countermeasures which are reflective paint, water-retentive pavement, sidewall greening, and so on are developed and installed in order to mitigate OT and reduce energy consumption for air conditioning. However, these countermeasures can bring adverse effects on the society. For example, water-retentive pavement increases outdoor air humidity. It can increase EC for air conditioning through lowered efficiency of air conditioners due to dew condensation. Sidewall greening cuts penetration of solar radiation (SR) into the room through the windows. It can increase EC for lighting. Needless to say, reflective paint can increase EC for heating because it decreases OT in winter.

Therefore, we need to understand a quantitative relationship between the energy consumption and the meteorological elements such as OT, air humidity, and SR throughout the year for reasonable installation of the UHI countermeasures. Thus, we aimed at quantifying sensitivities of EC to meteorological elements in city-block scale. The reason that we chose finer scale is that the countermeasures are installed in small areas.

We installed meteorological instruments to the rooftops of fifteen primary schools in both of business and residential districts of Osaka city, which is the second largest city of Japan. The meteorological data which are OT, relative humidity, and SR were measured from March 2013 to March 2014. Then, we calculated the sensitivities of EC to meteorological elements using the multiple regression analysis. The concept of our methodology is similar to cooling and heating degree days. It is explained as follows by taking air temperature as an example. EC increases by heating in winter when OT becomes lower than a certain temperature. We define this certain temperature as a branch point of winter OT. We also define the increment of EC by OT decrease as a sensitivity of EC to winter OT. EC increases by air conditioning in summer when OT becomes higher than a certain temperature at the same time. A branch point of summer OT and a sensitivity of EC to winter OT are also defined. Thus, hourly EC is separated to base load and air-temperature related parts.

Our analysis showed that the branch points of summer OT in the business districts were lower than that in the residential districts. It is suggested that office automation equipment leads to the air conditioning demand. The branch points of summer OT in the residential districts were around 28 degree in the early afternoon (from 13:00 to 15:00). These values were higher than we thought and suggested that the residents in Osaka city are saving electricity because all of the nuclear power plants of Japan are still shut down.

The branch points of winter OT in the business district were similar to that in the residential districts. The sensitivities of EC to winter OT in the business districts were larger than that in the residential districts. However, ratios of the sensitivities to the base loads in the business districts were smaller. These results show that the air conditioners in the residential districts had a more significant impact on EC.

Specific humidity (SH) is considered to be related to EC because dehumidification on the fan coils in the air conditioner occurs and leads to EC. We analyzed branch points and sensitivities of summer OT and SH during only summer. The branch points and sensitivities of summer SH were the similar tendency of those of summer OT.

SR affects room temperature and illumination. SR enters through windows and becomes heat the air in rooms while the entered SR illuminates the rooms. We found the existence of branch points of SR during no air conditioning period. The residents were considered to begin to turn the lighting on at this point.

The outline of the authors’ ongoing research project concerning the interaction between energy demand and urban climate will be presented with the latest results. The goal of the project is to substantiate the performance of the authors’ numerical simulation system for simultaneous prediction of urban climate and building energy demand with the spatial resolution of 1km and the temporal resolution of 1 hour throughout a city and a year. The system has been originally developed and consists of the mesoscale Weather Research and Forecasting (WRF) model and a coupled multilayer urban Canopy Model and Building Energy Model (CM-BEM). The latter CM-BEM is original one and was developed as the first coupled system of Urban Canopy Parameterization and Building Energy Model (UCP-BEM) about 10 years ago. CM-BEM can simulate the feedback process of the sensible and latent anthropogenic heat from HVAC systems of the urban buildings to the atmospheric heat balance in the urban canopy layer. The project is being carried out based on field observations in the third largest Japanese city Osaka.

In order to obtain actual measurements used for validation of the simulation system WRF-CM-BEM, the project team carried out a yearlong field campaign in Osaka in fiscal year 2013. The meteorological measurements were conducted in the 15 urban areas (3 downtown commercial areas, 9 residential areas, and 3 mixed-use areas) at a couple of rooftop and ground sites in each area. Those sites composed an original high-spatial-resolution network for urban climate observation with mean distance between the sites less than 4km. Additionally thanks to cooperation from an electric power company, the project team obtained areal and hourly electricity demand data monitored at 13 distribution substations each located in 13 observed urban areas with horizontal dimensions of 500 m to 2 km square each. Those yearlong meteorological measurements and electricity demand data was used for the validation. Furthermore to check the potential of WRF-CM-BEM as an urban energy management tool especially in the prediction of photovoltaic power generation, the solar radiation was also monitored at all rooftop sites, and its intraurban spatial inhomogeneity was analyzed. Then the derived statistical characteristics of the observed insolation inhomogeneity were also used for the validation.

As a result of analyses of the yearlong observed insolation, it was found that Mean Absolute Percentage Deviations (MAPD) of the observed 5-minutes-averaged insolation at each site from that at the downtown reference site reached up to 40% indicating relatively large intraurban insolation inhomogeneity. Those MAPDs especially became larger on lightly and partly cloudy days than those on sunny and overcast days due to partly cloud cover in the sky. Those statistical characteristics of insolation inhomogeneity were able to be roughly reproduced by WRF-CM-BEM suggesting its potential application to evaluation of photovoltaic power generation. Additionally WRF-CM-BEM showed a good performance in terms of reproducibility of the near-surface urban climatology over Osaka especially in the surface air temperature. As a result of WRF-CM-BEM simulations, the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) between the observed and calculated summer 2m-height air temperatures over Osaka indicated less values compared to those in the latest relevant study which adopted an official UCP-BEM option named “BEP +BEM” in the WRF simulations for Phoenix USA. Lastly the reproducibility of the areal building electricity demand was validated. WRF-CM-BEM was found to be able to reproduce the observed contrast in the building electricity demand between downtown commercial areas and uptown residential areas quantitatively.

Thus the promising performances of WRF-CM-BEM for simultaneous prediction of urban climate and building energy demand were finally confirmed with its suggested potential application to the prediction of photovoltaic power generation toward the contribution to “smart grid” technology.

Building and urban form are recognised to modify the background climate by changing the solar and wind paths and by trapping both heat and pollution. These modifications are site specific and often results in uncomfortable urban environments, which in turn increases building energy demand. However with careful consideration these interdependent energy relationships (between form and climate) can be optimised to improve the urban environment, which in turn not only lowers energy demand, but improves the efficiencies of so-called ‘generic’ low energy technologies (for example, façade design and renewable/passive systems), alongside improving the health and wellbeing of urban residence.

Whilst the significance of these urban climate effects on both internal and external environments is acknowledged, for the most part they fall outside the broader discussion on sustainable urban development. This is evident by the lack of suitable tools, methodologies and guidelines to measure and incorporate these effects into the design of urban places, limited to a consideration of aesthetic values e.g. views, and impact assessments e.g. rights to light.

The energy and environmental management of our urban environments is more complex than dealing with the particulars of an individual building or relying exclusively on renewables to reduce the impact of climate change and the growing energy crisis. There is a growing need for methodologies that are capable of dealing with the many variables that exist in our urban systems.

London is experiencing a radical changes to the city’s urban morphology and infrastructure. The city, already populated with many tall buildings, is expected to experience a rapid change in response to modern concerns that include a desire for taller buildings, higher density and sustainable urban design (including energy efficient buildings and high-quality outdoor spaces). However architectural decisions (individually and in aggregate) are key to achieving both local and global objectives of sustainable urban development; nonetheless, to achieve this, it is critical to recognise the interdependent energy relationships that form between buildings at the neighbourhood scale.

This work reports on the impact of London’s changing skyline on both the urban climate and building energy needs, and investigates through a series of studies that are concerned with the difference in regulated loads of modern building types in their standalone setting (as is current practice) against identical buildings in various urban settings. The work will establish direct links between ‘form’ driven microclimate generation and building energy management at neighbourhood scale. In doing so the work will lay the foundation for the improved efficiency of ‘generic’ methodologies, further increasing London’s sustainable credentials.

The overall aim of the work is to outline a broad planning framework to guide future urban development in a climate sensitive manner.

To date, the urban sprawl has accompanied the 20th century rapid urbanization. It results in particular in the artificialization of vast natural surfaces and fragmentation of the landscape. The latter is regularly pointed out in the ecological studies as it dramatically alters the ecological diversity. Indeed the postulate is that large ecological reserves, the area provided to the species for their usual activities, home higher species diversity. With the Grenelle 1, the biodiversity preservation and the control of the urban development especially to save energy and protect environmental resources become the local authority policies’ priorities. Both could be achieved by promoting the urban densities, the urban renewals or by preserving species reserves that are necessary to maintain the connectivity of the ecological network.In parallel the changing of moist surfaces by impervious construction materials characterized by a high roughness and heat capacities alters the surface-atmosphere energy, momentum, and radiations exchanges. The urban heat island is originating by such land changes and depicts the formation of a buoyant efficient turbulent convective and extended boundary layer downstream built-up area. Several numerical studies highlighted its influence on seasonal building energy requirement patterns for space heating and cooling over megacities using physically based numerical urban climate modelling systems and finest grid resolutions ranging from 1km up to 250m.

The first research objective of our study is to test the ability of the numerical urban climate modelling system to consider high resolved and small land cover changes using the WRF-BEP+BEM urban modelling system. The second objective is to quantify the energy performance of six contrasted urban developments scenarios.

The urban development control and species reserves preservations policies have been translated into non-developable lands maps using the Graphab and Morpholim softwares developed at ThéMa (Besançon, France) while the SLEUTH* model of Doukhari et al. (2011) is used for simulating the six scenarios urban development that in turns serve providing the surface boundary conditions to the climate modelling system. The study has been performed over the intermediate populated urban region of Strasbourg-Kehl (France) taking into benefits the existence of up-to-date and high resolved building and land use land cover data. The urban development by 2030 is considered. The results show that urban climate modelling system in our study achieves reproducing global built-up patterns features but has difficulties to consider high resolved land cover changes that are of the urban planners resolution. The methodology and the results will be both presented and discussed.

This paper reports on preliminary results of the ongoing KLISGEE project which addresses the issue of quantifying the consequences of the urban climate and mid-term climate change on the energy demand of buildings for the case of Stuttgart, Germany. The method applied combines 1) numerical modelling using TEB and TRNSYS, 2) statistical analysis for pre- and post-processing of the data and 3) GIS-methods.

Information about the city is required, including weather data from atmospheric model for the period 1971-2000 and 2021-2050 with hourly temporal and 2.8 km spatial resolution, interpolated observed weather data from the hydrological LARSIM-model for the period 2003-2012 with hourly temporal and 1 km spatial resolution, 2D and 3D city maps in high resolution, data about use and age of buildings, statistical data of traffic and residents etc.

The high spatial resolution of the weather data enables a better description of spatially differentiated local climate due to the distinctive topography of Stuttgart.

First, the weather data are further corrected by means of the urban canyon model TEB in order to take into account the microclimatic effects of the various urban structures (urban density, land use, land cover, residential density and traffic density etc.).

Second, the dynamic building energy simulations using TRNSYS are undertaken for representative urban structures and building typologies identified in the city of Stuttgart. To keep the simulation times reasonable for the huge extent of the object of study (whole city), it is necessary to proceed to a generic depiction of the urban and building typologies based on an abstraction of their thermal properties instead of their real physical description. These include decisive parameters like street aspect ratio, residential density, density of traffic, building compactness, thermal insulation, building use, window ratio, etc. The simulation series are based on a DOE design of experiment plan.

Finally, the results are post-processed statistically. The single and double interactions of the investigated parameters as well as their hierarchical importance are quantified, so that mathematical models can be derived, which are then used for the representation of the spatial distribution of the energy demand results for the whole city at urban block level by means of GIS-techniques. The key metrics are mainly heating, cooling and lighting net energy demands.

The results confirm the importance of urban climate and climate change prognosis, as well as all investigated physical parameters characterising the city. This advocates for 1) the necessity of taking climate boundary conditions into account when dealing with building modelling and 2) on the importance of a proper building design to avoid negative cumulative urban climate effects.

The KLISGEE project is being carried out in the framework of the Program KLIMOPASS-Teil 1 funded by the land Baden-Württemberg, Germany.