Mapping temperature variation and degree-days in metropolitan areas with publicly available sensors

Buildings are nowadays responsible for as much as 32% of the total final energy consumption, constituting one of the biggest energy consumers. Usually the estimation of the energy needs for covering the heating and cooling demands of buildings are based on a low resolution average climatic dataset, which is considered as representative of a greater geographic area. Nevertheless, this practice does not account for the differences of climatic parameters frequently detected among core urban, sub-urban and rural areas which coexist in the same region and in some cases might be significant. In the current work, publicly available data collected from 15 meteorological stations scattered as evenly as possibly in the Greater Metropolitan Area of London are utilized in order to estimate energy demand differences between urban and suburban areas. The result was consistent with previous attempts found in the literature, thus proving that the existing publicly available meteorological stations can be carefully utilized for the production of fine resolution climatic datasets in order to be used for estimation of energy demands for heating and cooling through metropolitan areas. Results are more accurate than with the use of typical average climate datasets, for estimating of location specific energy consumption demand.