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Implementing Smart Urban Metabolism in the Stockholm Royal Seaport: Smart City SRS
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.ORCID iD: 0000-0003-2621-4253
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.ORCID iD: 0000-0002-2955-060X
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.ORCID iD: 0000-0002-9869-9707
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.ORCID iD: 0000-0003-4938-8862
Show others and affiliations
2015 (English)In: Journal of Industrial Ecology, ISSN 1088-1980, E-ISSN 1530-9290, Vol. 19, no 5, 917-929 p.Article in journal (Refereed) Published
Abstract [en]

For half a century, system scientists have relied on urban metabolism (UM) as a pragmatic framework to support the needed transition toward sustainable urban development. It has been suggested that information and communication technology (ICT) and, more specifically, smart cities can be leveraged in this transition. Given the recent advances in smart cities, smart urban metabolism (SUM) is considered a technology-enabled evolution of the UM framework, overcoming some of its current limitations. Most significantly, the SUM framework works at high temporal (up to real-time) and spatial (down to household/individual) resolutions. This article presents the first implementation of SUM in the Smart City Stockholm Royal Seaport R&D project; it further analyzes barriers and discusses the potential long-term implications of the findings. Four key performance indicators (KPIs) are generated in real time based on the integration of heterogeneous, real-time data sources. These are kilowatt-hours per square meter, carbon dioxide equivalents per capita, kilowatt-hours of primary energy per capita, and share of renewables percentage. These KPIs are fed back on three levels (household, building, and district) on four interfaces, developed for different audiences. The most challenging barrier identified was accessing and integrating siloed data from the different data owners (utilities, building owners, and so forth). It is hard to overcome unless a significant value is perceived. A number of long-term opportunities were described in the SUM context; among those, it is envisioned that SUM could enable a new understanding of the causalities that govern urbanism and allow citizens and city officials to receive feedback on the system consequences of their choices.

Place, publisher, year, edition, pages
John Wiley & Sons, 2015. Vol. 19, no 5, 917-929 p.
Keyword [en]
augmented reality, big data, industrial ecology, smart cities, sustainable city, urban metabolism
National Category
Environmental Engineering
Identifiers
URN: urn:nbn:se:kth:diva-172653DOI: 10.1111/jiec.12308ISI: 000363267800020Scopus ID: 2-s2.0-84949537790OAI: oai:DiVA.org:kth-172653DiVA: diva2:849066
Note

QC 20151113

Available from: 2015-08-27 Created: 2015-08-27 Last updated: 2017-12-04Bibliographically approved
In thesis
1. Smart Urban Metabolism: Toward a New Understanding of Causalities in Cities
Open this publication in new window or tab >>Smart Urban Metabolism: Toward a New Understanding of Causalities in Cities
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

For half a century, urban metabolism has been used to provide insights to support transitions to sustainable urban development (SUD). Internet and Communication Technology (ICT) has recently been recognized as a potential technology enabler to advance this transition. This thesis explored the potential for an ICT-enabled urban metabolism framework aimed at improving resource efficiency in urban areas by supporting decision-making processes. Three research objectives were identified: i) investigation of how the urban metabolism framework, aided by ICT, could be utilized to support decision-making processes; ii) development of an ICT platform that manages real-time, high spatial and temporal resolution urban metabolism data and evaluation of its implementation; and iii) identification of the potential for efficiency improvements through the use of resulting high spatial and temporal resolution urban metabolism data. The work to achieve these objectives was based on literature reviews, single-case study research in Stockholm, software engineering research, and big data analytics of resulting data. The evolved framework, Smart Urban Metabolism (SUM), enabled by the emerging context of smart cities, operates at higher temporal (up to real-time), and spatial (up to household/individual) data resolution. A key finding was that the new framework overcomes some of the barriers identified for the conventional urban metabolism framework. The results confirm that there are hidden urban patterns that may be uncovered by analyzing structured big urban data. Some of those patterns may lead to the identification of appropriate intervention measures for SUD.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. xiii, 73 p.
Series
TRITA-IM, ISSN 1402-7615 ; 2015:01
Keyword
industrial ecology, urban metabolism, smart cities, big data, data science
National Category
Other Environmental Engineering Environmental Analysis and Construction Information Technology
Research subject
Industrial Ecology
Identifiers
urn:nbn:se:kth:diva-176892 (URN)978-91-7595-737-1 (ISBN)
Public defence
2015-12-16, F3, Lindstedtsvägen 26, KTH, Stockholm, 14:00 (English)
Opponent
Supervisors
Projects
Smart City SRS
Funder
VINNOVA, 2012-01148
Note

QC 20151120

Available from: 2015-11-20 Created: 2015-11-11 Last updated: 2015-11-20Bibliographically approved

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Shahrokni‎, HosseinÅrman, LouiseLazarevic, DavidNilsson, Anders

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