| 1. |
- Janssen, Mathias, 1973, et al.
(author)
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Environmental assessment of a biorefinery concept for production of bulk and fine chemicals
- 2019
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Conference paper (other academic/artistic)abstract
- Moving from a fossil-based to a bio-based economy requires the development of new technologies and process concepts for the production of bio-based energy, chemicals and materials. Biorefinery concepts can be designed by integrating such technologies in order to provide environmentally and economically attractive alternatives to produce bulk and fine chemicals. This paper presents life cycle and techno-economic assessments of a novel biorefinery concept, in its early stages of development, for the combined production of adipic acid from forest residues and of lutein from micro-algae. Adipic acid is a bulk chemical with a yearly production of approximately 2.3 million tonnes, and is primarily used for the production of nylon-6,6. Conventional adipic acid production from fossil resources causes significant emissions of N2O due to the use of nitric acid as an oxidizing agent. This conventional production can thus lead to a significant climate impact if these emissions are not sufficiently mitigated. Lutein is a high added-value chemical used in the food and pharmaceutical industries, and is conventionally produced from marigold flowers. The biorefinery concept in this work consists of the pretreatment of forest residues, the separation of lignin (which is an important by-product), and the hydrolysis and fermentation of the pretreated forest residues to adipic acid which is then separated and purified. Water, nutrients and CO2 flows from the adipic acid production can be connected to the algae production. The lutein is extracted from the micro-algae using methanol. Anaerobic digestion is used in this concept to produce biogas (another important by-product) from waste streams. The biorefinery concept thus comprises technologies that are at different technology readiness levels (TRLs), from as low as a TRL of 2 for the fermentation process, to a TRL of 9 for the anaerobic digestion process. Twelve design variants of the biorefinery concept were modelled and simulated based on experimental and literature data. These variants aimed at narrowing down uncertainties about, for instance, the performance of the fermentation process. The data and information resulting from the simulations of the design variants were used 1) to compile the life cycle inventories for the LCA of each of these variants, and to do the subsequent life cycle impact assessment, and 2) to determine the capital and operating costs in order to calculate the economic feasibility of the biorefinery design variants. The assessment of all variants provides a range for the environmental and economic performance of the biorefinery concept based on design choices and process conditions. Furthermore, scenarios for future energy systems were considered in order to assess the influence of the background system on the performance of the biorefinery concept. The results show that there is a large variation in the performance among the different design variants, where some designs can significantly improve the prospects for the bio-based adipic acid production. However, the results are strongly dependent on the foreground and background energy systems. The results provide valuable insights to industry and policy decision makers in order to guarantee an environmentally benign and economically feasible production of bulk and fine chemicals in a biorefinery.
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| 2. |
- Karka, P., et al.
(author)
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Environmental impact assessment of biomass process chains at early design stages using decision trees
- 2019
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In: International Journal of Life Cycle Assessment. - : Springer Science and Business Media LLC. - 1614-7502 .- 0948-3349. ; 24:9, s. 1675-1700
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Journal article (peer-reviewed)abstract
- Purpose: Life cycle assessment (LCA) is generally considered as a suitable methodology for the evaluation of environmental impacts of processes. However, it requires large amount and often inaccessible process data at early design stages. The present study provides an approach to streamline LCA for a broad set of biomass process chains. The proposed method breaks away from conventional LCA work in that the purpose is to support decision at early stages assuming minimal use of data available and points to most dominant LCA impacts, providing useful feedback to process design. Methods: The prediction mechanism employs decision trees, which form “if-then rules” using a set of critical parameters of the process chain with respect to various environmental impacts. The models classify products into three classes, namely having low, medium, and high environmental impact. Data for model development were obtained from early design stages and include descriptors of the molecular structure of the product and process chain-related variables corresponding to chemistry, complexity, and generic process conditions. Twenty-three LCA metrics were selected as target attributes, according to the ReCiPe and the cumulative energy demand (CED) methods. A broad set of process chains is derived from the work of Karka et al. (Int J Life Cycle Assess 22(9):1418–1440, 2017). Results and discussion: Results demonstrate that the average classification error for the decision trees ranges between 13.4 and 43.8% for the various LCA metrics and multifunctionality approaches. Allocation approaches present a better classification performance (up to 25% error) compared with the substitution approach for LCA metrics, such as climate change, CED, and human health. For the majority of models, low- and high-output classes are characterized by better predictive performance compared with the medium class. The interpretability of selected decision trees is analyzed in terms of pruning levels and “irrational” branches. The results of the application of the decision tress for recently published case studies show for instance that 8 out of 13 cases were correctly classified for CED. Conclusions: The proposed approach provides a first generation of models in the form of computationally inexpensive and easily interpretable decision trees that can be used as pre-screening tools for the environmental assessment of bio-based production ahead of detailed design and conventional LCA approaches. The transparent structure of the decision trees facilitates the identification of critical decision variables providing insights for improvement in terms of process parameters, biomass feedstock, or even targeted product.
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| 3. |
- Karka, P., et al.
(author)
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Predictive LCA - a systems approach to integrate LCA decisions ahead of design
- 2019
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In: Computer Aided Chemical Engineering. - 1570-7946. ; 46, s. 97-102
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Book chapter (other academic/artistic)abstract
- Bio-refineries are promising production options of chemicals production, capable to produce a wide range of fuels and chemicals equivalent to the conventional fossil-based products. To establish bio-refineries as mature choices and achieve the commercialization of their technologies, the application of sustainable solutions during the design and development stages are crucial. The innovative character of bio-based production and therefore data availability and access on process modelling details, is a challenging point for decision makers to move towards this direction. Considering the environmental dimension out of the three aspects of sustainability, Life Cycle Assessment (LCA) is a suitable methodology for the evaluation of environmental impacts of bio-based processes because it highlights the stages with the greatest impact along a production chain. LCA studies require large amount of information, usually extracted from detailed flowsheets or from already completed pilot plants, making this procedure, costly, time consuming and not practical to act as a decision- support tool for the development of a bio-refinery. The aim of this study is to develop predictive models for the assessment of LCA metrics and use them to highlight sustainable design options for bio-refineries. Models require the least possible information, which can be obtained from chemistry - level data or early (conceptual) design stages. The modelling techniques used in this study are decision trees and Artificial Neural Networks (ANN), due to their easily interpretable structure and high computational capabilities, respectively. Models are based on the extraction of knowledge from a wide dataset for bio-refineries (it refers to 32 products that is, platform chemicals (e.g., syngas, sugars and lignin) and biofuels (e.g., biodiesel, biogas, and alcohols), starting from diverse biomass sources (e.g., wood chips, wheat straw, vegetable oil)). Input parameters include descriptors of the molecular structure and process related data which describe the production path of a study product. Models are able to predict LCA metrics which cover the most critical aspects of environmental sustainability such as cumulative energy demand (CED) and Climate Change (CC). The average classification errors for decision- tree models range between 17% (± 10%) to 38% (± 11%) whereas for ANN models the average R2cv values (coefficient of determination) range between 0.55 (± 0.42%) to 0.87 (± 0.07%). Demonstration of models is provided using case studies found in literature. Models are used to rank options in various design problems and support decisions on the selection of the most profitable option. Examples of such cases are the selection of the appropriate technology or feedstock to produce a desired product or the preliminary design of a bio-refinery configuration. The proposed approach provides a first generation of models that correlate available and easily accessed information to desirable output process parameters and assessment metrics and can be used as pre-screening tools in the development of innovative processes, ahead of detailed design, thus saving time and money.
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| 4. |
- Papadopoulos, A. I., et al.
(author)
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A Framework for the Integration of Holistic Sustainability Assessment in Computer-Aided Molecular Design
- 2019
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In: Computer Aided Chemical Engineering. - 1570-7946. ; 46, s. 13-18
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Book chapter (other academic/artistic)abstract
- We propose the integration of a holistic sustainability assessment framework in computer-aided molecular design (CAMD). The framework enables the assessment of life cycle (LCA) and safety, hazard and environmental (SHE) impacts from cradle-to-gate of chemicals designed through CAMD. It enables the calculation of an overall of 14 sustainability-related indices, with some of them aggregating several impact categories. Lack of models and data gaps in property prediction are addressed systematically through a data mining approach which exploits on-line similarity assessment with existing molecules for which data exist or can be predicted. The framework is implemented both simultaneously with CAMD or after CAMD to assess the designed solvents. A case study is presented on the design of phase-change solvents for chemisorption-based post-combustion CO2 capture. Results indicate that the proposed approach enables the identification of verifiably useful phase-change solvents which exhibit favourable performance trade-offs compared to a reference CO2 capture solvent.
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| 5. |
- Shavalieva, Gulnara, 1987, et al.
(author)
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Sustainability analysis of phase-change solvents for post-combustion CO2 capture
- 2019
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In: Chemical Engineering Transactions. - 2283-9216. ; 76, s. 1045-1050
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Journal article (peer-reviewed)abstract
- Phase-change solvents is a solution to the energy penalty problem of post-combustion CO2 capture. While the improved thermodynamic performance of processes using phase-change solvents is previously demonstrated, there is no research done on the environmental and health aspects of such processes. The purpose of this study is to bridge this gap with the help of combined life cycle and safety, health and environment hazard assessment. In terms of life cycle analysis, steam for the reboiler, CO2 compression for transport and electricity consumption by the flue gas blower are the main contributors to the impact, however, in comparison with the conventional solvents, phase-change solvents will require additional electricity and reclaimer steam input due to phase-separation and potential increase of degradation compounds, the overall energy requirement is, however, smaller. The assessment indicated that phase-change solvent systems may experience additional problems of accumulation of harmful solvent degradation products due to the design of the process. The study highlights that in comparison with the conventional systems, phase-change solvent process might require additional safety equipment, but the overall environmental and health impact of the system is expected to be lower.
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