Techno-economic analysis of energy efficiency measures in a pulp mill converted to an ethanol production plant

A conceptual ethanol production plant, based on conversion of a kraft pulp mill, has been studied. The process uses softwood as raw material, alkaline pre-treatment combined with delignification, and biochemical conversion of sugars to ethanol (i.e. hydrolysis and fermentation). The plant has been analysed by pinch methods in order to find steam-saving possibilities. It is shown in the study that a large amount of steam surplus can be found if energy efficiency measures are implemented. In order to study the possible effect on the profitability of the plant when introducing steam-saving measures, the process has been analysed from a techno-economic point of view. It is shown that implementing energy efficiency measures could have a substantial effect on profitability if the by-product (in this case lignin biofuel or power) is high-valued. It is also shown that lignin as by-product might be more profitable than power, mainly because the demand for CO2 in lignin extraction might be supplied by CO2 produced in fermentation of sugars to ethanol. If investments are made to convert a pulp mill to ethanol production, energy efficiency measures should be included in the discussion since they might play an important role in minimising ethanol production cost

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

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\uae CTec2, ranging from 62 to 266 FPU\ub7mL−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\ub7L−1\ub7h−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 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

Impacts of future climate on local water supply and demand – A socio-hydrological case study in the Nordic region

Study region Fårö island, part of Region Gotland, Sweden. Study focus Despite its importance for proactive planning and management, understanding of how future climate and socioeconomic trends may interact to influence water supply and demand at sub-regional scale remains limited for the Nordic region. We aim to close this knowledge gap by developing a combined social and hydrological simulation model for Fårö island in the Baltic Sea. We use multivariate Monte Carlo simulations to explore the effects of future climate scenarios (RCP4.5 and RCP8.5) on local groundwater supplies, and subsequent impacts on the housing sector, tourism sector, and municipal water supply system in the period 2020–2050. New hydrological insights for the region Our results suggest that groundwater storage will remain critically low in the coming 30 years, with a 60–70% probability of the groundwater head falling to lower levels than experienced in the past 60 years. Low water availability and widespread saltwater intrusion will constrain housing and tourism development by up to 11% and 30% respectively. To sustain growth, the tourist sector will become increasingly reliant on water from private wells, and supplementary water deliveries from neighboring regions will be required to meet water demand on the municipal grid.publishedVersio

Uncertainty analysis as a tool to consistently evaluate lignocellulosic bioethanol processes at different system scales

Lignocellulosic processes are highly prone to batch-to batch variability, e.g. of raw materials and enzyme activities. Thisvariability can be propagated throughout system scales during process development and optimization, influencing the outputs ofbioreaction models, techno-economic analyses and life cycle assessments. As these outputs are the main decision variablesfor designing and developing lignocellulose-based processes, tools are required to evaluate the influences of process variation atdifferent system scales.Uncertainty analysis quantifies the effects of model input variations on model outputs. It is an effective tool to consistentlypropagate process variation throughout scales and analyse its influence on model outputs. As an example, we use a modeldescribing multi-feed simultaneous saccharification and co-fermentation (SSCF) of wheat straw. During the process enzymeshydrolyse the lignocellulosic material to release glucose which can be converted by microorganisms into ethanol. To investigatethe impact of batch-to-batch variability in enzyme cocktails, we collected literature data on the enzymatic activity of CellicCTec2. Retrieved data were propagated in models at bioreactor, techno-economic analysis and life cycle assessment scale. Weshow how uncertainty analysis can be used to guide process development by comparing different modes of operation. Themethod can identify economically feasible process ranges with low environmental impact while increasing the robustness ofbioprocesses with high variation in raw material inputs. Furthermore, uncertainty analysis could help to identify relevantparameters to choose as response variables in experimental designs

Multi-scale uncertainty analysis – A tool to systematically consider variability in lignocellulosic bioethanol processes

Bioethanol production processes from lignocellulosic raw materials are highly prone to batch-to-batch variations. For example, raw material compositions and enzymatic activities required to release fermentable sugars from lignocellulose vary significantly between batches. To develop lignocellulosic biofuel processes and evaluate their performance regarding economics and sustainability consistently, tools are required to cope with this variability.\ua0In this presentation we will propose a multi-scale uncertainty analysis strategy to propagate input variability throughout system scales. In a first step, we use meta-data obtained from literature to define uncertainties in the process inputs. Utilizing these meta-data, uncertainty analysis is performed on a macro-kinetic model by sampling from the defined uncertain input space. The results of this uncertainty analysis are transferred to process simulations to analyze the impact of input uncertainties on the process mass- and energy balances, and on the economics of building this type of bioprocess. The generated data from process simulations (mass flows, energy integration, and economic data) are in the next step extracted and used as input to an environmental impact assessment of the process. This is done whilst keeping the simulation and systems modeling parameters constant, thus the input variability is propagated throughout the different system scales. The data generated in this integrated approach will then be compared with the variations and uncertainties observed with relevance to the estimated parameters in the process simulation and environmental impact assessment. Based on this consistent strategy, we can analyze the impact of input variability from different system perspectives, identify important bottlenecks for development, and suggest robust and sustainable process designs for different conditions and under given uncertainties. \ua0In a case study we demonstrate how integrated kinetic modeling (in Matlab), process simulation (in SuperPro Designer), and environmental impact assessment together with statistical analysis can be used for assessing how variability in enzymatic activities in bioethanol production can be propagated throughout system scales. A macro-kinetic model is used to describe the enzymatic breakdown of lignocellulose-derived polysaccharides into fermentable sugars (saccharification) and the simultaneous fermentation to bioethanol. We discuss the integration of the simulation results of the macro-kinetic model into the flowsheeting software for mass and energy balance generation, and then further on to assess environmental impacts of the process. We will evaluate different process designs regarding their robustness towards input variability. Finally, we also show how propagated uncertainties at different system scales can be integrated to design experiments at laboratory scale so that these focus on the most important parameters for developing robust kinetic models, and include the parameters that are most important for sustainable design of processes and value chains

Energy efficiency measures in a kraft pulp mill converted to a biorefinery producing ethanol

Large scale, sustainable production of ethanol biofuel will most likely require commercialization of processes using lignocellulosic raw materials. To date no commercial plant exists however, due to the difficulties in reaching production costs that can compete with 1st generation ethanol and fossil fuels.One way of possibly decreasing the production cost is using an unprofitable pulp mill that is converted to ethanol production. The economic benefits of this would be e.g., that existing equipment and infrastructure could be used and that a skilled workforce would be available. These synergetic effects could be important for taking the leap into 2nd generation biofuel production.The objective of the work presented in this thesis has been to analyze a conceptual converted pulp mill ethanol plant with respect to energy efficiency measures and to try and draw some conclusions on the importance of implementation of measures, as well as the profitability of doing so. Furthermore, the ethanol process has been compared in brief with other 2nd generation ethanol processes. Implemented energy efficiency measures have been assessed economically by assuming that steam savings will be turned into increased output of energy in the form of lignin biofuel or electricity.Conclusions that can be drawn from this study are that implementing energy efficiency measures should be considered when converting the pulp mill to ethanol production and that the choice between lignin and electricity as a byproduct is difficult to make. Electricity is a more robust choice with the inputs used in this study but lignin might give higher added value. It is very difficult to assess lignin though, due to the multitude of different uses this product could have in the future

Energy efficiency measures in a kraft pulp mill converted to a biorefinery producing ethanol

Large scale, sustainable production of ethanol biofuel will most likely require commercialization of processes using lignocellulosic raw materials. To date no commercial plant exists however, due to the difficulties in reaching production costs that can compete with 1st generation ethanol and fossil fuels.One way of possibly decreasing the production cost is using an unprofitable pulp mill that is converted to ethanol production. The economic benefits of this would be e.g., that existing equipment and infrastructure could be used and that a skilled workforce would be available. These synergetic effects could be important for taking the leap into 2nd generation biofuel production.The objective of the work presented in this thesis has been to analyze a conceptual converted pulp mill ethanol plant with respect to energy efficiency measures and to try and draw some conclusions on the importance of implementation of measures, as well as the profitability of doing so. Furthermore, the ethanol process has been compared in brief with other 2nd generation ethanol processes. Implemented energy efficiency measures have been assessed economically by assuming that steam savings will be turned into increased output of energy in the form of lignin biofuel or electricity.Conclusions that can be drawn from this study are that implementing energy efficiency measures should be considered when converting the pulp mill to ethanol production and that the choice between lignin and electricity as a byproduct is difficult to make. Electricity is a more robust choice with the inputs used in this study but lignin might give higher added value. It is very difficult to assess lignin though, due to the multitude of different uses this product could have in the future

Process integration studies on Kraft pulp-mill-based biorefineries producing ethanol

Large scale, sustainable production of biofuels will require commercialization ofprocesses using lignocellulosic feedstocks. These processes are still notcompetitive with existing pathways, however. The competitiveness oflignocellulosic biofuel production plants could potentially be improved if theywere integrated with already existing facilities. One such example being exploredcurrently is connected to the fact that the pulping industry is showing a growinginterest in expanding their product portfolio, namely the complete or partialconversion of pulp mills into biorefineries for production of transport fuels.The objective of the work presented in this thesis has been to study differentpotential biorefinery concepts connected to chemical pulping, and morespecifically the Kraft pulping process. Three different process combinations havebeen assessed in the project; a process where a Kraft pulp mill is repurposed toethanol production (no pulp is produced), a process where ethanol and dimethyl-ether is produced in a repurposed Kraft pulp mill, and finally a processwhere an ethanol plant is co-located with a modern Kraft pulp mill.The findings from the studies reveal that an increasing degree of heat integrationleads to a lower production cost of ethanol both if the ethanol plant is based on arepurposed mill and if the plant is co-located with a modern mill. In the ethanolanddi-methyl-ether process, which has much higher conversion efficiency fromfeedstock to biofuel than the other processes, it was shown that the process couldbe competitive with the other combinations in terms of production cost, if thebiofuel price is high and if the biorefinery is perceived as a low risk investment