A main challenge in building carbon-neutral built environments is the ability to scale and replicate solutions. We examine how to develop low-carbon neighbourhoods and districts, while aiming at climate-friendly and sustainable livable urban environments. We take a view that not only scales up individual building solutions, but embraces the added complexities arising from the scale change and utilizes them for a novel approach. It includes a strong focus on co-creation and open innovation to develop sustainable solutions.
In this contribution, we present the approach of the +CityxChange project in implementing Positive Energy Blocks (PEB) through a European H2020 project from the topic of Smart Cities and Communities. A PEB comprises several connected buildings that have a averaged yearly positive energy balance between them. This definition excludes embodied emissions, but allows to focus on the infrastructure and systems between buildings as part of the built environment, and ways to implement and incorporate them within existing cities. The +CityxChange approach relies on co-creating Europe-wide deployment of Positive Energy Districts, with Integrated Planning and Design, Creation of a Common Energy Market, and CommunityxChange with all stakeholders of the city.
Smart Cities denote a stronger integration of information technology into the organisation of a city and the interaction and participation of its citizens. In developing the concept further, we propose to understand Smart Cities through the lens of Social Machines and thus stronger focus on the city as a socio-technical construct. We draw from an interdisciplinary background of computer science and urban planning to reexamine and combine existing theories and find a common understanding. We substantiate our claim to the validity of the concept of Smart-City-as-a-Social-Machine with a thorough literature study and comparison. We discuss the resulting system complexity issues and ways to address them. We further propose areas where this understanding can be useful in furthering research on both the Smart City and the Social Machine topics.
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