Solving LCI data gaps for fine chemicals by retrosynthesis for industrially relevant reactions

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Poster Number:  29 

Main Presenter:    Jonas Goßen 

Co-Authors:   Raoul Meys                                               

Life Cycle Assessment (LCA) is a widely recognized methodology that plays a crucial role in promoting environmentally responsible behaviors and sustainable practices.(1,2) It involves a comprehensive analysis of the material and energy flows that occur within the supply and value chains of a product, process, or service. The ultimate objective of LCA is to calculate and improve the overall environmental impact of a particular product, making it a powerful tool for evaluating cumulative environmental consequences.(3,4) However, creating LCAs for chemical reactions can be challenging due to data scarcity. Particularly, the fine chemical industry faces the challenges of confidentiality concerns and choosing sustainable and environmentally friendly reaction routes. These challenges occur, particularly due to the absence of crucial environmental emission factors for most fine chemicals. This data scarcity increases the difficulty of making informed decisions about the environmental impact
of different reaction routes.(5) Furthermore, even when laboratory data is available, it is often not representative of larger-scale production processes, and direct upscaling without further consideration can lead to inaccurate assessments of environmental impact. To close this gap, we propose an automatized generation of LCA entries to speed up slower modeling approaches by automatizing the retrosynthesis of relevant fine chemicals.

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