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Article

English

ID: <

oai:doaj.org/article:bfa49e99f47346ddbb0576dae0fd6f69

>

·

DOI: <

10.3390/su13094654

>

Where these data come from
Neighbourhood Modelling for Urban Sustainability Assessment

Abstract

Climate change is becoming a dominant concern for advanced countries. The Paris Agreement sets out a global framework whose implementation relates to all human activities and is commonly guided by the United Nations Sustainable Development Goals (UN SDGs), which set the scene for sustainable development performance configuring all climate action related policies. Fast control of CO2 emissions necessarily involves cities since they are responsible for 70 percent of greenhouse gas emissions. SDG 11 (Sustainable cities and communities) is clearly involved in the deployment of SDG 13 (Climate Action). European Sustainability policies are financially guided by the European Green Deal for a climate neutral urban environment. In turn, a common framework for urban policy impact assessment must be based on architectural design tools, such as building certification, and common data repositories for standard digital building models. Many Neighbourhood Sustainability Assessment (NSA) tools have been developed but the growing availability of open data repositories for cities, together with big-data sources (provided through Internet of Things repositories), allow accurate neighbourhood simulations, or in other words, digital twins of neighbourhoods. These digital twins are excellent tools for policy impact assessment. After a careful analysis of current scientific literature, this paper provides a generic approach for a simple neighbourhood model developed from building physical parameters which meets relevant assessment requirements, while simultaneously being updated (and tested) against real open data repositories, and how this assessment is related to building certification tools. The proposal is validated by real data on energy consumption and on its application to the Benicalap neighbourhood in Valencia (Spain).

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