Environmental assessment of Dynamic Processes – considering time dependency in Life Cycle Assessment

SCHEME: INTER

CALL: 2013

DOMAIN: SR - Environmental and Earth Sciences

FIRST NAME: Enrico

LAST NAME: Benetto

INDUSTRY PARTNERSHIP / PPP: No

INDUSTRY / PPP PARTNER:

HOST INSTITUTION: LIST

KEYWORDS:

START: 2014-01-06

END: 2017-07-05

WEBSITE: https://www.list.lu/

Submitted Abstract

Since the Brundtlant report in 1987, the assessment of the sustainability of human economic systems has moved from a vague concept to a consistent set of methodologies and modelling tools within the area of Sustainability Science. These methods are nowadays applied in most of the economic sectors, both in industry and in policy making, and are developed in academia worldwide, one of the major outcomes being the eco-design of human activities. This is more particularly the case of Life Cycle Assessment (LCA), ruled by the ISO standards 14040-44 and at the core of the EU policy making and scientific research. After 20 years of steadily development, efforts are currently oriented toward the deepening and broadening of LCA, to support the development of more environmentally sound products for consumers as well as to steer policy making on key societal issues, like e.g. electromobility, building and construction and biotechnologies. Among these developments, the introduction of time dependency in LCA has been dramatically underestimated and underexplored. In conventional LCA, human driven systems are typically considered to run in steady state conditions, including fully elastic activities, neglecting time lags and stocks of goods and products. At best, the current practice considers different scenarios (related to time horizons) where relevant inventory parameters (e.g. related to the production functions like electricity production) are changed according to possible technological, market and regulatory evolutions. Following the same line of reasoning, the lifecycle impact assessment models translating the inventory results into environmental impacts have limited coverage and consideration of dynamic features (related e.g. to pollutant fate, exposure and effect parameters). Conventional LCA models are indeed ideal simplifications of a reality which is, nonetheless, highly dynamic and variable over time. The main objective of DyPLCA is to develop a comprehensive and operational approach (methodology and tools) for the proper consideration of time dependency in LCA, with strong emphasis on the development of an integrated modelling solution for both the life cycle inventory (LCI, at foreground and background levels) and the life cycle impact assessment (LCIA) phases. Results at the end of the project will be a methodology, models and computational tools for true dynamic LCA, well beyond the current practice based on forecasted scenarios, in a form readily usable for LCA practitioners. The modelling framework will be tested and applied to three relevant test bed LCA applications: 1) bio-technologies (complex non steady state, cyclic functioning); 2) buildings (long term non steady state); 3) car tire traffic noise (highly dynamic and stochastic). These systems were selected because of their contribution to the overall environmental impacts generated by human driven economies as well as because of the pertinence of the temporal scale in the assessment. DyPLCA will provide new scientific knowledge, clearly beyond the current state of the art of the science of LCA, focusing in particular on 1) the deepening and broadening the scope and modelling of LCAs in an rather unique way, through the combination of temporal characterization techniques and LCA and the harmonization of micro-process level inventories (i.e. Ecoinvent v3 datasets) with time behaviours of large scale systems; and 2) full implementation of these modelling and investigation approaches on three practical application situations of broad societal interest. Apart from the scientific communication and promotion of scientific and technical culture, higher education will benefit from the project results, thanks to the academic partners involved, and the repercussions on the respective research strategies of the project partners are huge.

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