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).

Digital Twin Technology Challenges and Applications: A Comprehensive Review

“…With the large amount of data generated and analyzed in DT systems, big data algorithms and the IoT technology are powerful allies that can provide support to a great extent to successful DT implementations [75]. Furthermore, information flowing from various levels of indicator systems presents a challenge for developing common policies and standards [82]. Effectively targeting levels 4 and 5 of the maturity spectrum, this challenge could enable bidirectional flow of information, control of the physical world from the digital model and even autonomous operations and asset maintenance.…”

Combined Greening Strategies for Improved Results on Carbon-Neutral Urban Policies

“…The proposed neighbourhood scenario corresponds to the Benicalap district in the city of Valencia. The model, or digital twin, of the physical neighbourhood starts with the cadastral digital information which is developed into a digital entity using the ArcGIS Pro 2.9 software from ESRI (Redlands, CA, USA) and following the process developed by the authors of [18]. This model has been adapted to include all building-related parameters (according to their heritage status) for a simplified LCA analysis [19,20], which is required for predicting building energy performance from environmental conditions.…”

“…Zürich, Switzerland) [23]. The digital twin facilitates an automated virtual testbed, handling all steps from monitoring to virtual modelling of real interactions using metadata and software routines, and the actual neighbourhood digital twin is built using the procedure described in [18].…”

“…The Valencia Open Data platform [18] follows the ISO standard specification ISO/IEC 20802-2:2016 [27] under a simple architecture (Figure 3) running under Oracle (platformneutral), supporting all city datasets including the research data output from city projects, while fulfilling the EU data policies and joint repositories [28]. •…”

“…The Valencia Open Data platform [18] follows the ISO standard specification ISO/IEC 20802-2:2016 [27] under a simple architecture (Figure 3) running under Oracle (platformneutral), supporting all city datasets including the research data output from city projects, while fulfilling the EU data policies and joint repositories [28]. Figure 2 presents the reference infrastructure model and high-level technical specification for all data referenced in this paper, including its main components and connection points to other tools and systems.…”