34
need a practical and scientifi cally credible implementation of the ideal represented
by the hypothetical CLCA approach.
In our opinion, prospective IE models provide such implementation. The scenario approach makes explicit the underlying exogenous assumptions that necessarily accompany any prospective model of an indeterminate system. Several authors,
including Zamagni et al. ( 2012 ), Plevin et al. ( 2014a ), and Suh and Yang ( 2014 ),
acknowledge the importance of scenario modeling for the scientifi c assessment of
decision-making in general and the questions posed by CLCA in particular. The use
of a comprehensive model of society’s metabolism allows us to study the system
with the high level of detail and biophysical consistency that is a distinctive feature
of industrial ecology methods. The combination of the scenario approach and a
detailed model of society’s metabolism make prospective IE models a powerful and
scientifi cally credible approach to explore the potential consequences of decisions.
4 Prospective Modeling in Industrial Ecology: Future
Development
4.1 Future Applications and Model Development
of Prospective Models within Industrial Ecology
A major goal of prospective modeling is to assess bundles of mitigation and adaptation strategies and investigate whether the different strategies together can transform socioeconomic metabolism to a more sustainable state. Studying strategy
bundles reveals which strategies may yield co-benefi ts and which ones counteract
each other, which is an important information for decision-makers. Bundled assessment leads to “big picture” scenarios for a feasible future, from which environmental, economic, and social performance indicators for individual strategies can be
derived. These indicators can then be monitored during real implementation to
ensure that the impact of the strategies is as intended. Performance indicators may
be material, product, industry sector, or region specifi c.
Strategy bundles affect different materials and energy carriers, which are substitutable to some extent. Flexibility in the choice of materials and energy carriers
allows us to design a more resilient and potentially more sustainable SEM, but it
also represents a challenge for prospective modeling, as models need to provide
insights into the potential consequences of a wide spectrum of material and energy
supply choices.
The cycles of different materials are tightly coupled at several places: Base minerals of different materials often occur together; they are coproduced, often with
fi xed ratios on certain sites. At higher stages of fabrication, materials are mixed
again into compound materials and alloys, products consist of many different materials, and fi nally, waste streams contain material mixes. Assessments of individual
metals on the small scale can neglect this coupling, as it can be assumed that the rest
of the economy is able to supply or absorb ancillary fl ows and a credit or discredit
S. Pauliuk and E.G. Hertwich
need a practical and scientifi cally credible implementation of the ideal represented
by the hypothetical CLCA approach.
In our opinion, prospective IE models provide such implementation. The scenario approach makes explicit the underlying exogenous assumptions that necessarily accompany any prospective model of an indeterminate system. Several authors,
including Zamagni et al. ( 2012 ), Plevin et al. ( 2014a ), and Suh and Yang ( 2014 ),
acknowledge the importance of scenario modeling for the scientifi c assessment of
decision-making in general and the questions posed by CLCA in particular. The use
of a comprehensive model of society’s metabolism allows us to study the system
with the high level of detail and biophysical consistency that is a distinctive feature
of industrial ecology methods. The combination of the scenario approach and a
detailed model of society’s metabolism make prospective IE models a powerful and
scientifi cally credible approach to explore the potential consequences of decisions.
4 Prospective Modeling in Industrial Ecology: Future
Development
4.1 Future Applications and Model Development
of Prospective Models within Industrial Ecology
A major goal of prospective modeling is to assess bundles of mitigation and adaptation strategies and investigate whether the different strategies together can transform socioeconomic metabolism to a more sustainable state. Studying strategy
bundles reveals which strategies may yield co-benefi ts and which ones counteract
each other, which is an important information for decision-makers. Bundled assessment leads to “big picture” scenarios for a feasible future, from which environmental, economic, and social performance indicators for individual strategies can be
derived. These indicators can then be monitored during real implementation to
ensure that the impact of the strategies is as intended. Performance indicators may
be material, product, industry sector, or region specifi c.
Strategy bundles affect different materials and energy carriers, which are substitutable to some extent. Flexibility in the choice of materials and energy carriers
allows us to design a more resilient and potentially more sustainable SEM, but it
also represents a challenge for prospective modeling, as models need to provide
insights into the potential consequences of a wide spectrum of material and energy
supply choices.
The cycles of different materials are tightly coupled at several places: Base minerals of different materials often occur together; they are coproduced, often with
fi xed ratios on certain sites. At higher stages of fabrication, materials are mixed
again into compound materials and alloys, products consist of many different materials, and fi nally, waste streams contain material mixes. Assessments of individual
metals on the small scale can neglect this coupling, as it can be assumed that the rest
of the economy is able to supply or absorb ancillary fl ows and a credit or discredit
S. Pauliuk and E.G. Hertwich