Multi-scale exploration of the technical, economic, and environmental dimensions of bio-based chemical production

Zhuang, Kai; Herrgård, Markus J.

doi:10.1016/j.ymben.2015.05.007

Cited by 31 publications

(14 citation statements)

References 51 publications

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“…This is a process that is considered in detail in the private sector, but is often neglected in the academic P E R S P E C T I V E npg milieu. Once the bioproduct to be produced has been chosen, a preliminary techno-economic analysis should be performed using several candidate host strains under the most plausible scenarios (e.g., cost-effective carbon sources, aerobic versus anaerobic fermentation, batch, fed-batch or continuous culture, fermenters and downstream processing equipment to be employed) 27 . Depending on the natural or synthetic nature of the product, different strategies can be employed for strain design 4 .…”

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confidence: 99%

Systems strategies for developing industrial microbial strains

Lee¹,

2015

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Industrial strain development requires system-wide engineering and optimization of cellular metabolism while considering industrially relevant fermentation and recovery processes. It can be conceptualized as several strategies, which may be implemented in an iterative fashion and in different orders. The key challenges have been the time-, cost- and labor-intensive processes of strain development owing to the difficulties in understanding complex interactions among the metabolic, gene regulatory and signaling networks at the cell level, which are collectively represented as overall system performance under industrial fermentation conditions. These challenges can be overcome by taking systems approaches through the use of state-of-the-art tools of systems biology, synthetic biology and evolutionary engineering in the context of industrial bioprocess. Major systems metabolic engineering achievements in recent years include microbial production of amino acids (L-valine, L-threonine, L-lysine and L-arginine), bulk chemicals (1,4-butanediol, 1,4-diaminobutane, 1,5-diaminopentane, 1,3-propanediol, butanol, isobutanol and succinic acid) and drugs (artemisinin).

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confidence: 99%

Systems strategies for developing industrial microbial strains

Lee¹,

2015

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“…The basic economic analysis of autotrophic succinic acid production conducted here was based on minimal input of experimental data and excluded downstream processing and investment costs. Further, more detailed economic evaluations are necessary to evaluate sustainability and competitiveness similar to Zhuang and Herrgard (2015) who included land use, and agricultural features of the feedstock, impact of the energy and market sector, metabolic details of the applied strain and process designs. If similarly adapted for autotrophic succinic acid production, it is possible to more precisely identify optimal environmental and regulatory application niches.…”

Section: Discussionmentioning

confidence: 99%

CO2 to succinic acid – Estimating the potential of biocatalytic routes

Liebal

Blank

Ebert

2018

Metabolic Engineering Communications

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Microbial carbon dioxide assimilation and conversion to chemical platform molecules has the potential to be developed as economic, sustainable processes. The carbon dioxide assimilation can proceed by a variety of natural pathways and recently even synthetic CO2 fixation routes have been designed. Early assessment of the performance of the different carbon fixation alternatives within biotechnological processes is desirable to evaluate their potential. Here we applied stoichiometric metabolic modeling based on physiological and process data to evaluate different process variants for the conversion of C1 carbon compounds to the industrial relevant platform chemical succinic acid. We computationally analyzed the performance of cyanobacteria, acetogens, methylotrophs, and synthetic CO2 fixation pathways in Saccharomyces cerevisiae in terms of production rates, product yields, and the optimization potential. This analysis provided insight into the economic feasibility and allowed to estimate the future industrial applicability by estimating overall production costs. With reported, or estimated data of engineered or wild type strains, none of the simulated microbial succinate production processes showed a performance allowing competitive production. The main limiting factors were identified as gas and photon transfer and metabolic activities whereas metabolic network structure was not restricting. In simulations with optimized parameters most process alternatives reached economically interesting values, hence, represent promising alternatives to sugar-based fermentations.

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“…Multiscale models have been established in various disciplines, e.g., in fluid phase and wastewater treatment research (Deen et al, 2004;Xavier et al, 2007;Ofiteru et al, 2014), metabolic engineering (Dada and Mendes, 2011;Bogart and Myers, 2016), and biomass pretreatment (Hosseini and Shah, 2009). Zhuang and Herrgård (2015) proposed a biorefinery multi-scale model to describe the impacts different microbial strains, products and raw materials have on process economics and environmental impacts by connecting dynamic flux balance analysis to TEA and LCA. The authors used the model to guide strain development from an economic and environmental perspective in early process development stages.…”

Section: Introductionmentioning

confidence: 99%

Multi-Scale Variability Analysis of Wheat Straw-Based Ethanol Biorefineries Identifies Bioprocess Designs Robust Against Process Input Variations

et al. 2020

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Bioprocesses based on (ligno-)cellulosic biomass are highly prone to batch-to-batch variations. Varying raw material compositions and enzyme activities hamper the prediction of process yields, economic feasibility and environmental impacts. Commonly, these performance indicators are averaged over several experiments to select suitable process designs. The variabilities in performance indicators resulting from variable process inputs are often neglected, causing a risk for faulty performance predictions and poor process design choices during scale-up. In this paper, a multi-scale variability analysis framework is presented that quantifies the effects of process input variations on performance indicators. Using the framework, a kinetic model describing simultaneous saccharification and ethanol fermentation was integrated with a flowsheet process model, techno-economic analysis and life cycle assessment in order to evaluate a wheat straw-based ethanol biorefinery. Hydrolytic activities reported in the literature for the enzyme cocktail Cellic ® CTec2, ranging from 62 to 266 FPU·mL −1 , were used as inputs to the multi-scale model to compare the variability in performance indicators under batch and multi-feed operation for simultaneous saccharification and fermentation. Bioprocess simulations were stopped at ethanol productivities ≤0.1 g·L −1 ·h −1 . The resulting spreads in process times, hydrolysis yields, and fermentation yields were incorporated into flowsheet, techno-economic and life cycle scales. At median enzymatic activities the payback time was 7%, equal to 0.6 years, shorter under multi-feed conditions. All other performance indicators showed insignificant differences. However, batch operation is simpler to control and well-established in industry. Thus, an analysis at median conditions might favor batch conditions despite the disadvantage in payback time. Contrary to median conditions, analyzing the input variability favored multi-feed operation due to a lower variability in all performance indicators. Variabilities in performance indicators were at least 50% lower under multi-feed operation. Counteracting the variability in enzymatic activities by adjusting the amount of added enzyme instead resulted in Nickel et al.Multi-Scale Variability Analysis of Biorefineries higher uncertainties in environmental impacts. The results show that the robustness of performance indicators against input variations must be considered during process development. Based on the multi-scale variability analysis process designs can be selected which deliver more precise performance indicators at multiple system levels.

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Multi-scale exploration of the technical, economic, and environmental dimensions of bio-based chemical production

Cited by 31 publications

References 51 publications

Systems strategies for developing industrial microbial strains

Systems strategies for developing industrial microbial strains

CO2 to succinic acid – Estimating the potential of biocatalytic routes

Multi-Scale Variability Analysis of Wheat Straw-Based Ethanol Biorefineries Identifies Bioprocess Designs Robust Against Process Input Variations

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