Mass and heat integration in ethanol production mills for enhanced process efficiency and exergy-based renewability performance

This paper presents the process design and assessment of a sugarcane-based ethanol production system that combines the usage of both mass and heat integration (pinch analysis) strategies to enhance the process efficiency and renewability performance. Three configurations were analyzed: (i) Base case: traditional ethanol production (1G); (ii) mass-integrated (1G2G); and (iii) mass and heat-integrated system (1G2G-HI). The overall assessment of these systems was based on complementary approaches such as mass and mass-heat integration, energy and exergy analysis, exergy-based greenhouse gas (GHG) emissions, and renewability exergy criteria. The performances of the three cases were assessed through five key performance indicators (KIPs) divided into two groups: one is related to process performance, namely, energy efficiency, exergy efficiency, and average unitary exergy cost (AUEC), and the other one is associated to environmental performance i.e., exergy-based CO2-equation emissions and renewability exergy index. Results showed a higher exergy efficiency of 50% and the lowest AUEC of all the systems (1.61 kJ/kJ) for 1G2G-HI. Furthermore, the destroyed exergy in 1G2G-HI was lower by 7% and 9% in comparison to the 1G and 1G2G cases, respectively. Regarding the exergy-based GHG emissions and renewability performance (λindex), the 1G2G-HI case presented the lowest impacts in terms of the CO2-equivalent emissions (94.10 gCO2-eq/MJ products), while λindex was found to be environmentally unfavorable (λ = 0.77). However, λindex became favorable (λ > 1) when the useful exergy of the byproducts was considered.BT/Biotechnology and Societ

Decarbonizing ethanol production via gas fermentation: Impact of the CO/H₂/CO₂ mix source on greenhouse gas emissions and production costs

This study explores key success factors for ethanol production via fermentation of gas streams, by assessing the effects of eight process variables driving the fermentation performance on the production costs and greenhouse gas emissions. Three fermentation feedstocks are assessed: off-gases from the steel industry, lignocellulosic biomass-derived syngas and a mixture of H2 and CO2. The analysis is done through a sequence of (i) sensitivity analyses based on stochastic simulations and (ii) multi-objective optimizations. In economic terms, the use of steel off-gas leads to the best performance and the highest robustness to low mass transfer coefficients, low microbial tolerance to ethanol, acetic-acid co-production and to dilution of the gas feed with CO2, due to the relatively high temperature at which the gas feedstock is available. The ethanol produced from the three feedstocks lead to lower greenhouse gas emissions than fossil-based gasoline and compete with first and second generation ethanol.BT/Biotechnology and SocietyBT/Bioprocess Engineerin

A systematic approach for the processing of experimental data from anaerobic syngas fermentations

This study describes a methodological framework designed for the systematic processing of experimental syngas fermentation data for its use by metabolic models at pseudo-steady state and at transient state. The developed approach allows the use of not only own experimental data but also from experiments reported in literature which employ a wide range of gas feed compositions (from pure CO to a mixture between H2 and CO2), different pH values, two different bacterial strains and bioreactor configurations (stirred tanks and bubble columns). The developed data processing framework includes i) the smoothing of time-dependent concentrations data (using moving averages and statistical methods that reduce the relevance of outliers), ii) the reconciliation of net conversion rates such that mass balances are satisfied from a black-box perspective (using minimizations), and iii) the estimation of dissolved concentrations of the syngas components (CO, H2 and CO2) in the fermentation broth (using mass transfer models). Special care has been given such that the framework allows the estimation of missing or unreported net conversion data and metabolite concentrations at the intra or extracellular spaces (considering that there is availability of at least two replicate experiments) through the use of approximative kinetic equations.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.BT/Bioprocess EngineeringBT/Biotechnology and Societ

Modeling ethanol production through gas fermentation: A biothermodynamics and mass transfer-based hybrid model for microbial growth in a large-scale bubble column bioreactor

Background: Ethanol production through fermentation of gas mixtures containing CO, CO2 and H2 has just started operating at commercial scale. However, quantitative schemes for understanding and predicting productivities, yields, mass transfer rates, gas flow profiles and detailed energy requirements have been lacking in literature; such are invaluable tools for process improvements and better systems design. The present study describes the construction of a hybrid model for simulating ethanol production inside a 700 m3 bubble column bioreactor fed with gas of two possible compositions, i.e., pure CO and a 3:1 mixture of H2 and CO2. Results: Estimations made using the thermodynamics-based black-box model of microbial reactions on substrate threshold concentrations, biomass yields, as well as CO and H2 maximum specific uptake rates agreed reasonably well with data and observations reported in literature. According to the bioreactor simulation, there is a strong dependency of process performance on mass transfer rates. When mass transfer coefficients were estimated using a model developed from oxygen transfer to water, ethanol productivity reached 5.1 g L-1 h-1; when the H2/CO2 mixture is fed to the bioreactor, productivity of CO fermentation was 19% lower. Gas utilization reached 23 and 17% for H2/CO2 and CO fermentations, respectively. If mass transfer coefficients were 100% higher than those estimated, ethanol productivity and gas utilization may reach 9.4 g L-1 h-1 and 38% when feeding the H2/CO2 mixture at the same process conditions. The largest energetic requirements for a complete manufacturing plant were identified for gas compression and ethanol distillation, being higher for CO fermentation due to the production of CO2. Conclusions: The thermodynamics-based black-box model of microbial reactions may be used to quantitatively assess and consolidate the diversity of reported data on CO, CO2 and H2 threshold concentrations, biomass yields, maximum substrate uptake rates, and half-saturation constants for CO and H2 for syngas fermentations by acetogenic bacteria. The maximization of ethanol productivity in the bioreactor may come with a cost: low gas utilization. Exploiting the model flexibility, multi-objective optimizations of bioreactor performance might reveal how process conditions and configurations could be adjusted to guide further process development.BT/Biotechnology and SocietyBT/Bioprocess Engineerin

Dynamic modeling of syngas fermentation in a continuous stirred-tank reactor: Multi-response parameter estimation and process optimization

Syngas fermentation is one of the bets for the future sustainable biobased economies due to its potential as an intermediate step in the conversion of waste carbon to ethanol fuel and other chemicals. Integrated with gasification and suitable downstream processing, it may constitute an efficient and competitive route for the valorization of various waste materials, especially if systems engineering principles are employed targeting process optimization. In this study, a dynamic multi-response model is presented for syngas fermentation with acetogenic bacteria in a continuous stirred-tank reactor, accounting for gas–liquid mass transfer, substrate (CO, H2) uptake, biomass growth and death, acetic acid reassimilation, and product selectivity. The unknown parameters were estimated from literature data using the maximum likelihood principle with a multi-response nonlinear modeling framework and metaheuristic optimization, and model adequacy was verified with statistical analysis via generation of confidence intervals as well as parameter significance tests. The model was then used to study the effects of process conditions (gas composition, dilution rate, gas flow rates, and cell recycle) as well as the sensitivity of kinetic parameters, and multiobjective genetic algorithm was used to maximize ethanol productivity and CO conversion. It was observed that these two objectives were clearly conflicting when CO-rich gas was used, but increasing the content of H2 favored higher productivities while maintaining 100% CO conversion. The maximum productivity predicted with full conversion was 2 g·L−1·hr−1 with a feed gas composition of 54% CO and 46% H2 and a dilution rate of 0.06 hr−1 with roughly 90% of cell recycle.BT/Bioprocess EngineeringBT/Biotechnology and Societ

Production of ethanol fuel via syngas fermentation: Optimization of economic performance and energy efficiency

In this work, a model was developed to predict the performance of a bubble column reactor for syngas fermentation and the subsequent recovery of anhydrous ethanol. The model was embedded in an optimization framework which employs surrogate models (artificial neural networks) and multi-objective genetic algorithm to optimize different process conditions and design variables with objectives related to investment, minimum selling price, energy efficiency and bioreactor productivity. The results indicate the optimal trade-offs between these objectives while providing a range of solutions such that, if desired, a single solution can be picked, depending on the priority conferred to different process targets. The Pareto-optimal values of the decision variables were discussed for different case studies with and without the recovery unit. It was shown that enhancing the gas-liquid mass transfer coefficient is a key strategy toward sustainability improvement.BT/Bioprocess EngineeringBT/Biotechnology and Societ

Multi-Objective Sustainability Optimization of Biomass Residues to Ethanol via Gasification and Syngas Fermentation: Trade-Offs between Profitability, Energy Efficiency, and Carbon Emissions

This work presents a strategy for optimizing the production process of ethanol via integrated gasification and syngas fermentation, a conversion platform of growing interest for its contribution to carbon recycling. The objective functions (minimum ethanol selling price (MESP), energy efficiency, and carbon footprint) were evaluated for the combinations of different input variables in models of biomass gasification, energy production from syngas, fermentation, and ethanol distillation, and a multi-objective genetic algorithm was employed for the optimization of the integrated process. Two types of waste feedstocks were considered, wood residues and sugarcane bagasse, with the former leading to lower MESP and a carbon footprint of 0.93 USD/L and 3 g CO2eq/MJ comparedto 1.00 USD/L and 10 g CO2eq/MJ for sugarcane bagasse. The energy efficiency was found to be 32% in both cases. An uncertainty analysis was conducted to determine critical decision variables, which were found to be the gasification zone temperature, the split fraction of the unreformed syngas sent to the combustion chamber, the dilution rate, and the gas residence time in the bioreactor. Apart from the abovementioned objectives, other aspects such as water footprint, ethanol yield, and energyself-sufficiency were also discussed.BT/Bioprocess EngineeringBT/Biotechnology and Societ

Unit exergy cost and specific CO₂ emissions of the electricity generation in the Netherlands

Exergy and environmental analyses have been developed to determine the performance of the electricity generation in the Dutch mix. A comparative assessment of diverse technological routes, including fossil and renewable energy resources consumption, is carried out in terms of the exergy costs and specific CO2 emissions. Hence, an exergoeconomy methodology is used to properly allocate the renewable and non-renewable exergy costs and specific CO2 emissions among the various products of the polygeneration energy systems. By using a suitable methodology, the distribution of irreversibility throughout the different steps of the energy conversion processes of the Dutch electricity mix is characterized in the light of the Second Law of Thermodynamics. The results may help to propose performance indicators that support the Dutch government and research institutions. To identify sustainable energy planning strategies and fairly comparing electricity generation and end-use processing stages with other types of energy resources, such as fuels used in transportation, residential and industrial sectors. In brief, the weighted average of the renewable and non-renewable unit exergy costs and the specific CO2 emissions of the electricity generated in each route of the Dutch mix is calculated and compared to another electricity mix with a higher share of renewable energy resources. The weighted average renewable and non-renewable unit exergy costs of the electricity generated in the Netherlands are calculated as cR = 0.8375 kJ/kJE/W and cNR = 1.7180 kJ/kJE/W, respectively (cR/cNR= 0.49). Furthermore, the specific CO2 emissions in the Dutch electricity generation achieve 373.21 gCO2/kWhE/W.BT/Biotechnology and Societ