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One important factor which we cannot consider in this study due to a lack of data is residential energy use.
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Heidelberg is residential, barely.
The surrounding area is residential.
The key input data is the empirical residential and tertiary heat demand per square kilometre for 2015, extrapolated to 2030 to account for the potential decrease in the heat demand (energy-efficient buildings).
An advantage of the CHIS for linkage of health and environmental data is knowledge of residential locations at the cross-street (CHIS 2001) and address (CHIS 2003 and 2005) level.
The following data were collected: residential history, smoking, consumption of fluids, and occupational and medical history.
During the sampling process of island mode, the 24-hours and 4-seasons residemandl datand data is used in the demand sampling while the wind speed distributions are fitted for renewable energy output sampling.
One year of monitoring data is collected from a four-storey residential building located in Fort McMurray, Alberta, Canada.
Data is based on excavation of seven residential buildings, combined with mapping and recording of features of all structures at Monte Viudo.
Since there are many types of regional energy statistics, we compiled the dataset from various sources.3 Prefectural residential electricity demand data is from the Energy Consumption Statistics by Prefecture (Agency for Natural Resources and Energy, the Ministry of Economy, Trade and Industry).
Also used in the analysis was residential property data from Western Technologies Group in New Jersey, the Furman Center for Real Estate and Urban Policy at New York University and the New York Office of Real Property Services.
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