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Original article (peer-reviewed)

Journal International Journal of Life Cycle Assessment
Volume (Issue) 21(4)
Page(s) 510 - 522
Title of proceedings International Journal of Life Cycle Assessment
DOI 10.1007/s11367-015-1015-3

Open Access

Type of Open Access Publisher (Gold Open Access)


Purpose Over the life cycle of products or services there are often several key decisions – e.g. the choice of technologies – that affect environmental performance. This paper introduces a modular LCA approach that is capable of reducing the effort involved in performing scenario analyses and optimization when several key choices along a product’s value chain lead to many alternative life cycles. Methods The main idea is that the value chain of a product can be divided into interconnected, but exchangea-ble modules, which together represent a full life cycle. The modules are comprised of unit processes from the practitioner’s LCI database. The inputs, outputs, and system boundaries of each module can be tailored to the context of the studied system. Alternatives arise whenever multiple modules produce substitutable products. Unlike in conventional LCI databases, no copies are necessary to represent the same process with different inputs. A module-product matrix is used to store this information. It can be used as a basis for an automated scenario analysis of all alternatives or as an input to an optimization model. Results Our framework is applied in two case studies: 1) Passenger car fuel choices are modeled by 15 mod-ules representing 33 alternative value chains for diesel, petrol, natural gas, and electric cars. The au-tomated comparison of LCA results indicates that electric mobility is often the preferable option from a climate perspective, but impacts depend strongly on the electricity source. 2) A dynamic optimization model including stocks is built from 8 modules to analyze the optimal use of wood for material and energy applications. Results indicate that although direct substitution benefits are higher for energy applications, cascading use of wood can maximize environmental performance over the entire life cycle. Conclusions The modular LCA approach permits an efficient modeling and comparison of alternative product life cycles, enabling practitioners to focus on key decisions. It can be applied to exploit a potential that is hidden in LCI databases, which is that they contain many specific inventories, but not all useful combinations in the context of scenario analyses. The user-defined level of abstraction that is introduced through modules can be helpful in the communication of LCA results. The modular approach also facilitates the integration of LCA and optimization as well as other industrial ecology methods. An open source software is provided to enable others to apply, further develop, or ‘steel’ our implementation of a modular LCA approach.