Modeling the circular economy in environmentally extended input-output tables: Methods, software and case study

•Pycirk, a python package to create complex scenarios using the mrEEIOA database EXIOBASE (https://pypi.org/project/pycirk/).•Methods and blueprints to increase transparency of modeling assumptions for the Circular Economy.•A case study on two circular economy strategies - Product Life Extension and...

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Published in:Resources, conservation and recycling Vol. 152; p. 104508
Main Authors: Donati, Franco, Aguilar-Hernandez, Glenn A., Sigüenza-Sánchez, Carlos Pablo, de Koning, Arjan, Rodrigues, João F.D., Tukker, Arnold
Format: Journal Article
Language:English
Published: Elsevier B.V 01.01.2020
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ISSN:0921-3449, 1879-0658
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Abstract •Pycirk, a python package to create complex scenarios using the mrEEIOA database EXIOBASE (https://pypi.org/project/pycirk/).•Methods and blueprints to increase transparency of modeling assumptions for the Circular Economy.•A case study on two circular economy strategies - Product Life Extension and Resource Efficiency. A circular economy is an industrial system that is restorative or regenerative by intention or design. During the last decade, the circular economy became an attractive paradigm to increase global welfare while minimizing the environmental impacts of economic activities. Although several studies concerning the potential benefits and drawbacks of policies that implement the new paradigm have been performed, there is currently no standardized theoretical model or software to execute such assessment. In order to fill this gap, in the present paper we show how to perform these analyses using Environmentally Extended Input-Output Analysis. We also describe a python package (pycirk) for modeling Circular Economy scenarios in the context of the Environmentally Extended Multi-Regional Input-Output database EXIOBASE V3.3, for the year 2011. We exemplify the methods and software through a what-if zero-cost case study on two circular economy strategies (Resource Efficiency and Product Lifetime Extension), four environmental pressures and two socio-economic factors.
AbstractList A circular economy is an industrial system that is restorative or regenerative by intention or design. During the last decade, the circular economy became an attractive paradigm to increase global welfare while minimizing the environmental impacts of economic activities. Although several studies concerning the potential benefits and drawbacks of policies that implement the new paradigm have been performed, there is currently no standardized theoretical model or software to execute such assessment. In order to fill this gap, in the present paper we show how to perform these analyses using Environmentally Extended Input-Output Analysis. We also describe a python package (pycirk) for modelling Circular Economy scenarios in the context of the Environmentally Extended Multi-Regional Input-Output database EXIOBASE V3.3, for the year 2011. We exemplify the methods and software through a what-if zero-cost case study on two circular economy strategies (Resource Efficiency and Product Lifetime Extension), four environmental pressures and two socio-economic factors.
•Pycirk, a python package to create complex scenarios using the mrEEIOA database EXIOBASE (https://pypi.org/project/pycirk/).•Methods and blueprints to increase transparency of modeling assumptions for the Circular Economy.•A case study on two circular economy strategies - Product Life Extension and Resource Efficiency. A circular economy is an industrial system that is restorative or regenerative by intention or design. During the last decade, the circular economy became an attractive paradigm to increase global welfare while minimizing the environmental impacts of economic activities. Although several studies concerning the potential benefits and drawbacks of policies that implement the new paradigm have been performed, there is currently no standardized theoretical model or software to execute such assessment. In order to fill this gap, in the present paper we show how to perform these analyses using Environmentally Extended Input-Output Analysis. We also describe a python package (pycirk) for modeling Circular Economy scenarios in the context of the Environmentally Extended Multi-Regional Input-Output database EXIOBASE V3.3, for the year 2011. We exemplify the methods and software through a what-if zero-cost case study on two circular economy strategies (Resource Efficiency and Product Lifetime Extension), four environmental pressures and two socio-economic factors.
ArticleNumber 104508
Author Rodrigues, João F.D.
Sigüenza-Sánchez, Carlos Pablo
de Koning, Arjan
Aguilar-Hernandez, Glenn A.
Donati, Franco
Tukker, Arnold
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  fullname: Donati, Franco
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  organization: Institute of Environmental Sciences (CML), Department of Industrial Ecology, Leiden University, Einsteinweg 2, 2333 CC Leiden, The Netherlands
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  givenname: Glenn A.
  surname: Aguilar-Hernandez
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  givenname: Carlos Pablo
  surname: Sigüenza-Sánchez
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  givenname: Arjan
  orcidid: 0000-0001-9765-3179
  surname: de Koning
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  orcidid: 0000-0002-1437-0059
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  givenname: Arnold
  surname: Tukker
  fullname: Tukker, Arnold
  organization: Institute of Environmental Sciences (CML), Department of Industrial Ecology, Leiden University, Einsteinweg 2, 2333 CC Leiden, The Netherlands
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Keywords Policy
Scenarios
Software
Circular economy
Interventions
EEIOA
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Snippet •Pycirk, a python package to create complex scenarios using the mrEEIOA database EXIOBASE (https://pypi.org/project/pycirk/).•Methods and blueprints to...
A circular economy is an industrial system that is restorative or regenerative by intention or design. During the last decade, the circular economy became an...
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StartPage 104508
SubjectTerms case studies
Circular economy
computer software
EEIOA
environmental impact
input output analysis
Interventions
issues and policy
Policy
Scenarios
socioeconomic factors
Software
theoretical models
Title Modeling the circular economy in environmentally extended input-output tables: Methods, software and case study
URI https://dx.doi.org/10.1016/j.resconrec.2019.104508
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