Fast, transparent, and ex ante: an LCA-based micro–meso tool for prioritizing environmental actions, demonstrated on a soil treatment company and an electronics company.

Main Presenter:    Benedikt Verkic 

Co-Authors:   Annalisa Nolte     Kathrin Greiff      Juliano Araujo                                    

Industrial emissions remain at record highs, and operational decisions at company and industrial-park levels have immediate environmental consequences (IEA, 2025; World Bank, 2021). Yet, many life-cycle-based tools for circular economy (CE) planning are retrospective and do not provide ex-ante, action-level guidance for practitioners (Harris et al., 2021). We present a generally applicable decision support tool that combines life cycle assessment (LCA) with a scoring system to rank operational actions (e.g., mobility concepts, shared infrastructures, process changes) by environmental performance, while evaluating circularity as a complementary perspective. Here, actions are defined as interventions to the status quo intended to improve the environmental performance of companies and industrial parks.
Methodologically, the tool builds on the KREGI approach (Verkic et al., 2025) by adopting its action concepts and best-/worst-case scenario logic. We extend KREGI by (i) pre-quantifying actions via LCA, (ii) translating these results into a transparent scoring system, and (iii) testing the tool in company case studies. Twenty actions (15 generally applicable and 5 case-specific) are pre-quantified against five environmental indicators: global warming potential (GWP), cumulative energy demand (CED), raw material input (RMI), water use, and land use. The tool scales effects with a few company inputs (e.g., electricity demand, employee numbers, transport distances) and applies action-based max normalization, equal weighting, and weighted-sum aggregation to compute indicator-wise and total scores. Scenario bands from best- and worst-case effects express uncertainty. CE aspects are represented via R-strategy mapping and user defined CE indicators.
We demonstrate the methodology with two case studies: a soil‑treatment company and an electronics manufacturer. In the soil‑treatment case, actions that change soil use and logistics strongly reduce RMI, land use, and water use and also moderately reduce GWP and CED. Electrification and renewable‑electricity options reveal trade‑offs between climate/energy and land/water. In the electronics case, employee-scaled workplace and mobility actions (e.g., desk and ride sharing) dominate the portfolio. Together with a renewable-electricity action, they can significantly reduce GWP, CED, and RMI. The case‑specific closed‑loop blending of PA 6.6 regranulate adds further resource savings with negligible land‑ and water‑use changes. Scenario analysis highlights how reliable portfolio results are under varying implementation options. Overall, the tool operationalizes ex-ante, action‑level decision‑making across micro-meso contexts with minimal data burden and explicit trade‑off management and can
be transferred to other sectors and industrial park settings to support the reduction of environmental impacts at company and industrial park levels.

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