30 C O N T E X T 1 4 5 : J U LY 2 0 1 6 of the specific historic district that is being studied. In order to build this priority list, the DSS additionally translates the preferences of the user regarding five criteria (thermal comfort, energy savings, indoor air quality, cost and low-impact solutions) into weighted criteria using the analytic hierarchy process.The process transforms the comparison of criteria by pairs into the different weightings that are chosen by the user.This then synthesises the decision-maker’s judgments, and allows priority rankings of the alternatives to be obtained for each criterion, with an overall priority ranking. The accuracy of decision-making and consequently the DSS outputs depend on the availability, completeness and quality of the building stock data for the historic district in question.These vary significantly across Europe. To make the DSS as widely useable as possible, it allows for two different forms of assessment: the transferable model approach and the simulation approach. In situations where only very limited data is available, the DSS bases its assessment on urban typologies: the transferable model approach. To input the locationspecific data, the software user is guided through a process of questions and predefined answers to assign to the city district a type which describes it sufficiently to identify suitable retrofit measures. In cities where good quality data is available, the DSS assessment will use the simulation approach to iteratively model the impacts of the different retrofit measures listed in the repository.The district data, which can come from existing sources or field assessments, need to include a heritage significance assessment, which is likely to be the result of fieldwork by heritage specialists.The available district data is collated into a spatial data model which the DSS can interrogate. Ideally, data would be available for every building in a district. In practice this is rarely the case. Accordingly the DSS offers the option to reduce the size of the data model through a building stock categorisation tool. For this, a number of sample buildings, taken from the total building stock in the district, will be selected which describe the district sufficiently well to allow the identification of retrofit measures suitable for the majority of the district’s buildings. Criteria used in this categorisation include building age, floor area and three-dimensional form, use, construction type, and the differing levels of heritage significance that are ascribed to its diverse building elements (including roof and wall constructions and their external and internal finishes, windows and doors). The DSS has been validated using three of the seven real-world case studies in the EFFESUS project. (The other four case studies were used to test the building fabric retrofit measures developed by EFFESUS.) To reflect the priority that is attached in the project to heritage significance, these three urban districts are all world heritage sites. The first site is the historic district of Via Garibaldi in the town centre of Genoa (Italy), one of the most impressive examples of urban residential planning in Europe, and symbol of the city’s economic and financial power in the 16th and 17th centuries. Here the study of the city’s existing data showed a low level of available information. For this reason, the urban district was selected for the validation of the DSS using the transferable model approach. The second site is the medieval old town of Santiago de Compostela (Spain), composed of many narrow winding streets lined by historic buildings in the surroundings of the cathedral. Santiago already had a rich database of the buildings in this historic district, stored in a geographic information system. Hence it was possible to develop a multiscale data model without extensive fieldwork, and the district was selected for the validation of the categorisation tool and the DSS using the simulation approach. The results for Santiago demonstrated: •• The current energy demand and associated carbon emissions for the whole district. •• A priority list of packages of retrofit measures which should be suitable and effective for the different building types identified as representative by the categorisation tool. •• The reduction of the energy demand and carbon emissions achieved by the selected retrofit measures. The third site,Visby, located on the island of Gotland (Sweden), is an example of a north European medieval walled trading town. It preserves a townscape and assemblage of high-quality historic buildings that Visby, Gotland, Sweden: the medieval Hanseatic walled city
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