(326b) Multi-Scale Exploration of the Technical, Economic, and Environmental Dimensions of Bio-Based Chemical Production | AIChE

(326b) Multi-Scale Exploration of the Technical, Economic, and Environmental Dimensions of Bio-Based Chemical Production

Authors 

Zhuang, K. - Presenter, Technical University of Denmark
Herrgård, M. J. - Presenter, Technical University of Denmark

In recent years, bio-based chemicals have gained traction as a sustainable alternative to petrochemicals. However, despite rapid advances in metabolic engineering and synthetic biology, there remain significant economic and environmental challenges. In order to maximize the impact of research investment in a new bio-based chemical industry, there is a need for assessing the technological, economic, and environmental potentials of combinations of biomass feedstocks, biochemical products, bioprocess technologies, and metabolic engineering approaches in the early phase of development of cell factories. 

To address this issue, we have developed a comprehensive Multi-scale framework for modeling Sustainable Industrial Chemicals production (MuSIC), which integrates modeling approaches for cellular metabolism, bioreactor design, upstream/downstream processes, as well as economic and life-cycle impact assessments. We demonstrate the use of the MuSIC framework in a case study where two major polymer precursors (1,3-propanediol and 3-hydroxypropionic acid) are produced from two biomass feedstocks (corn-based glucose and soy-based glycerol) through 66 proposed biosynthetic pathways in two host organisms (E. coli and S. cerevisiae). The MuSIC framework allows exploration of tradeoffs and interactions between economy-scale optimization objectives (e.g. profit maximization, emission minimization), constraints (e.g. land-use constraints) and process- and cell-scale technology choices (e.g. strain design or oxygenation conditions).  We demonstrate that economy-scale assessment can be used to guide specific strain design decisions in metabolic engineering, and that these design decisions can be affected by non-intuitive dependencies across multiple scales.