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Implementation of Cross‐Industrial Networks Targeting CO2 Reduction from a Systemic Approach
Abstract
Within the Carbon2Chem® project, unavoidable CO2 emissions are used creating a new type of production network comprising a steelworks and chemical production. In the second project phase (2020–2024), the focus lies on additional expansion of already developed cross‐industrial networks as well as the implementation of additional ones (i.e., based on alternative CO2 sources) from an integral perspective that includes process simulation, process design, ecological and economic evaluation, and finally scale up. Moreover, the most promising process concepts will be further developed to a higher degree of detail aiming industrial implementation. The focus of the current second project phase of Carbon2Chem® lies on additional expansion of already developed cross‐industrial networks as well as the implementation of additional ones from an integral perspective that includes process simulation and design, ecological and economic evaluation, as well as scale up.
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Recycling of waste CO2 to bulk chemicals has a tremendous potential for the decarbonization of the chemical industry. Quantitative analysis of the prospects of this technology is hindered by the lack of flexible techno-economic assessment (TEA) models that enable evaluation of the processing costs under different deployment scenarios. In this protocol, we explain how to convert literature data into metrics useful for evaluation of the emerging electrolysis technologies, derive TEA models, and illustrate their use with a CO2-to-ethylene example.
For complete details on the use and execution of this protocol, please refer to Barecka et al. (2021a).
The utilization of industrial off‐gases as raw material requires a detailed knowledge on their time‐depending composition, especially with regard to trace components. Within the framework of the HüGaProp project (Hüttengas Properties) a measuring container and the analytical methods for the characterization of trace components in the three raw metallurgical gases was developed. The mobile container is deployed in the project Carbon2Chem® to characterize the available off‐gases at a steel mill and provide fundamental data to determine the required gas cleaning as well as the background for the further process design.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Methanol production is one promising way to minimize the ecological impact of the conventional steelmaking process. This synthesis needs additional hydrogen, preferably produced from a green power source. In this paper, the influence of different power supply scenarios, gas storage volumes, and hydrogen production capacities on the overall carbon saving potential-defined as carbon binding ratio-from a flexible methanol production case will be investigated. A mixed-integer linear programming model with rolling horizon is used to calculate the optimal production plan.
Deutschland hat sich zum Ziel gesetzt, die Treibhausgasemissionen bis zum Jahr 2050 um 80 bis 95 % gegenüber dem Emissionsniveau von 1990 zu reduzieren. Die hierfür festgelegten Treibhausgasreduktionspfade werden durch eine Vielzahl von weiteren zum Teil sehr detaillierten Zielsetzungen (z. B. Anteil erneuerbarer Energien an der Stromerzeugung) flankiert, die von der Bundesregierung als notwendig gesehen werden, um die übergeordneten Treibhausgasreduktionsziele zu erreichen. Dieser Zielekanon wurde im Laufe der letzten Dekade sukzessive entwickelt und erweitert. Viele vorliegende Studien, in denen Transformationspfade vorgeschlagen werden, integrieren diesen Zielkanon durch exogene Annahmen und schränken damit das Technikportfolio ein. Dies widerspricht einem Lösungsansatz, der sich vor allem durch Technologieoffenheit auszeichnen sollte. Die Frage, ob es sich bei den vorgeschlagenen Transformationspfaden um kostenoptimale Strategien handelt, bleibt in aller Regel unbeantwortet.
Ziel der vorliegenden Studie ist es daher, die kosteneffizientesten CO2 Minderungsstrategien zur Erreichung der Klimaschutzziele Deutschlands bis zum Jahr 2050 zu identifizieren. Hierzu werden zwei CO2-Reduktionsszenarien analysiert, die sich ausschließlich an den Minderungszielen für das Jahr 2050 von -80 % (Szenario 80) und -95 % (Szenario 95) orientieren. Für die Analyse wird eine neuartige Modellfamilie eingesetzt, die am Forschungszentrum Jülich entwickelt wurde. Diese ermöglicht es, die nationale Energieversorgung in all ihren Wechselwirkungen und Pfaden abzubilden. Unter der Randbedingung der Einhaltung der Reduktionsziele lassen sich die kosteneffizientesten Maßnahmen bzw. Treibhausgasminderungsstrategien ermitteln. Die Kombination der verschiedenen eingesetzten Modelle, die sich durch unterschiedliche methodische Vorgehensweisen auszeichnen, erlaubt eine fundierte und tiefgehende Analyse von Treibhausgasminderungsstrategien. Die hohe zeitliche und räumliche Auflösung ermöglicht Aussagen zur Konzeption von zukünftigen Energieinfrastrukturen (Strom, Erdgas und Wasserstoff) sowie detaillierte Regionalanalysen eines möglichen Windkraft- sowie PV-Ausbaus. Darüber hinaus können zukünftige globale Energiemärkte (z. B. synthetische Kraftstoffe, synthetisches Methan, Wasserstoff) simuliert und mögliche Energieimporte und -exporte im Kontext der Energiewende abgeschätzt werden.
Besides water, raw methanol produced from steel mill gases within the Carbon2Chem® project contains dissolved carbon dioxide. Refractometry and densimetry were investigated as analysis methods to analyze raw methanol samples quickly and reliably. To verify existing calibration curves, a set of standard solutions from pure chemicals was produced. Experimental results differed significantly from published refractive index data, especially in the range of high methanol weight fractions, which are of particular interest for the Carbon2Chem® project.
The time‐dependent operation of methanol, ammonia, and urea production units embedded in a steel mill environment is analyzed with dynamic simulation models. From different process concepts and gas availability scenarios, a set of simulation cases is defined with blast furnace gas as carbon and coke oven gas as hydrogen source. Dynamic simulations indicate that significant CO2 reductions require large amounts of additional H2 from sustainable sources. From the results, global data such as carbon footprint or energy demands and details about process unit operation are obtained and processed. Time‐dependent operation of methanol and urea plants embedded in a steelworks environment is analyzed with dynamic simulation models. Different process concepts and gas availability scenarios are considered to study the chemical production from blast furnace gas, coke oven gas, and external hydrogen.
Emerging technologies are expected to contribute to environmental sustainable development. However, throughout the development of novel technologies, it is unknown whether emerging technologies can lead to reduced environmental impacts compared to a potentially displaced mature technology. Additionally, process steps suspected to be environmental hotspots can be improved by process engineers early in the development of the emerging technology. In order to determine the environmental impacts of emerging technologies at an early stage of development, prospective life cycle assessment (LCA) should be performed. However, consistency in prospective LCA methodology is lacking. Therefore, this article develops a framework for a prospective LCA in order to overcome the methodological inconsistencies regarding prospective LCAs. The methodological framework was developed using literature on prospective LCAs of emerging technologies, and therefore, a literature review on prospective LCAs was conducted. We found 44 case studies, four review papers, and 17 papers on methodological guidance. Three main challenges for conducting prospective LCAs are identified: Comparability, data, and uncertainty challenges. The issues in defining the aim, functionality, and system boundaries of the prospective LCAs, as well as problems with specifying LCIA methodologies, comprise the comparability challenge. Data availability, quality, and scaling are issues within the data challenge. Finally, uncertainty exists as an overarching challenge when applying a prospective LCA. These three challenges are especially crucial for the prospective assessment of emerging technologies. However, this review also shows that within the methodological papers and case studies, several approaches exist to tackle these challenges. These approaches were systematically summarized within a framework to give guidance on how to overcome the issues when conducting prospective LCAs of emerging technologies. Accordingly, this framework is useful for LCA practitioners who are analyzing early-stage technologies. Nevertheless, further research is needed to develop appropriate scale-up schemes and to include uncertainty analyses for a more in-depth interpretation of results.
In recent literature, prospective application of life cycle assessment (LCA) at low technology readiness levels (TRL) has gained immense interest for its potential to enable development of emerging technologies with improved environmental performances. However, limited data, uncertain functionality, scale up issues and uncertainties make it very challenging for the standard LCA guidelines to evaluate emerging technologies and requires methodological advances in the current LCA framework. In this paper, we review published literature to identify major methodological challenges and key research efforts to resolve these issues with a focus on recent developments in five major areas: cross‐study comparability, data availability and quality, scale‐up issues, uncertainty and uncertainty communication, and assessment time. We also provide a number of recommendations for future research to support the evaluation of emerging technologies at low technology readiness levels: (a) the development of a consistent framework and reporting methods for LCA of emerging technologies; (b) the integration of other tools with LCA, such as multicriteria decision analysis, risk analysis, technoeconomic analysis; and (c) the development of a data repository for emerging materials, processes, and technologies.
We present an effective procedure to differentiate instrumental artefacts, such as parasitic ions, memory effects and real trace impurities contained in inert gases. Three different proton transfer reaction mass spectrometers were used in order to identify instrument‐specific parasitic ions. The methodology reveals new nitrogen‐ and metal‐containing ions, which up to date have not been reported. The parasitic ion signal was dominated by [N2]H+ and [NH3]H+ rather than by the common ions NO+ and O2+. Under dry conditions in a PTR‐QiTOF the ion abundances of [N2]H+ were elevated compared to the signals in the presence of humidity. In contrast, the [NH3]H+ ion did not show a clear humidity dependency. On the other hand, two PTR‐TOF1000 instruments showed no significant contribution of the [N2]H+ ion, which supports the idea of [N2]H+ formation in the quadrupole interface of the PTR‐QiTOF. Many new nitrogen‐containing ions were identified and three different reaction sequences showing a similar reaction mechanism were established. Additionally, several metal‐containing ions, their oxides and hydroxides were formed in the three PTR instruments. However, their relative ion abundancies were below 0.03% in all cases. Within the series of metal‐containing ions, the highest contribution under dry conditions was assigned to the [Fe (OH)2]H+ ion. Only in one PTR‐TOF1000 the Fe+ ion appeared as dominant species compared to the [Fe (OH)2]H+ ion. The present analysis and the resulting database can be used as a tool for the elucidation of artefacts in mass spectra and, especially in cases, where dilution with inert gases play a significant role, preventing misinterpretations.
Every decision-oriented life cycle assessment (LCAs) entails, at least to some extent, a future-oriented feature. However, apart from the ex-ante LCAs, the majority of LCA studies are retrospective in nature and do not explicitly account for possible future effects. In this review a generic theoretical framework is proposed as a guideline for ex-ante LCA. This framework includes the entire technology life cycle, from the early design phase up to continuous improvements of mature technologies, including their market penetration. The compatibility with commonly applied system models yields an additional aspect of the framework. Practical methods and procedures are categorised, based on how they incorporate future-oriented features in LCA. The results indicate that most of the ex-ante LCAs focus on emerging technologies that have already gone through some research cycles within narrowly defined system boundaries. There is a lack of attention given to technologies that are at a very early development stage, when all options are still open and can be explored at a low cost. It is also acknowledged that technological learning impacts the financial and environmental performance of mature production systems. Once technologies are entering the market, shifts in market composition can lead to substantial changes in environmental performance.
With the advances in new generation information technologies (New IT), especially big data and digital twin, smart manufacturing is becoming the focus of global manufacturing transformation and upgrading. Intelligence comes from data. Integrated analysis for the manufacturing big data is beneficial to all aspects of manufacturing. Besides, the digital twin paves a way for the cyber-physical integration of manufacturing, which is an important bottleneck to achieve smart manufacturing. In this paper, the big data and digital twin in manufacturing are reviewed, including their concept as well as their applications in product design, production planning, manufacturing, and predictive maintenance, etc. On this basis, what similarities and differences there are between big data and digital twin are compared from the general and data perspectives. Since the big data and digital twinning can be complementary, so how they can be integrated to promote smart manufacturing are discussed.
Epitaxial growth is a potential production process for the new material graphene, where it is grown on silicon carbide (SiC) wafers at high temperatures. We provide first estimates of the life cycle cumulative energy demand, climate change, terrestrial acidification, and eco-toxicity of this production. For this purpose, we applied prospective life cycle assessment (LCA) for three production scenarios (lab, pilot, and an industrial scenario), which reflect different production scales and technological maturity. The functional unit was one square centimeter of graphene. Results show that the three scenarios have similar impacts, which goes against previous studies that have suggested a decrease with larger production scale and technological maturity. The reason for this result is the dominance of electricity use in the SiC wafer production for all impacts (>99% in the worst case, >76% in the best case). Only when assuming thinner SiC wafers in the industrial scenario is there a reduction in impacts by around a factor of 10. A surface-area–based comparison to the life cycle energy use of graphene produced by chemical vapor deposition showed that epitaxial graphene was considerably more energy intensive—approximately a factor of 1,000. We recommend producers of epitaxial graphene to investigate the feasibility of thinner SiC wafers and use electricity based on wind, solar, or hydropower. The main methodological recommendation from the study is to achieve a temporal robustness of LCA studies of emerging technologies, which includes the consideration of different background systems and differences in production scale and technological maturity.
PurposeThis study aims at accounting for the variation in electricity production, processes and related impacts depending on season (heating, cooling), day of the week (tertiary building) and hour of the day. In this context, this paper suggests two alternative methods to integrate grid-building interaction in life cycle assessment of buildings and districts. Methods
An attributional dynamic method (AD) and a marginal dynamic method (MD) are compared with an annual average method (AA), representative of standard practice, using electric space heating as an illustrative case. The different methods are based on a dispatch model simulating electricity supply on an hourly basis, averaging historically observed climatic and economic variability. The meteorological inputs of the model are identical to those of the building energy simulation. Therefore, the environmental benefits from smart buildings and onsite renewable energy production are more accurately evaluated. Results and discussionUsing electricity production (or supply) data for a specific past year is a common practice in building LCA. This practice is sensitive to economic and meteorological hazards. The suggested methodology is based on a proposed reference year mitigating these hazards and thus could be seen as more representative of average impacts. Depending on the chosen approach (average or marginal) to evaluate electricity supply related impacts, the carbon footprint of the electric space heating option for the studied low-energy house in France is evaluated to 61.4 to 84.9 g CO2eq kWh−1 (AA), 78.8 to 110.2 g CO2eq kWh−1 (AD) and 765.1 to 928.7 g CO2eq kWh−1 (MD). Compared to wood and gas boiler, 22–107 and 218–284 g CO2eq kWh−1 respectively, the ranking between the different technical options depends on the chosen approach. Uncertainty analysis does not undermine the interpretation of the results. Conclusions
The proposed electricity system model allows a more precise and representative evaluation of electricity supply related impacts in LCA compared to standard practices. Two alternative methods are suggested corresponding to attributional and consequential LCA. The approach has to be chosen in line with the assessment objectives (e.g. certification, ecodesign). Prospective assessment integrating long-term evolution of the electric system and influence of global warming on buildings behaviour are identified as relevant future research subjects.
This paper assesses two different carbon capture and utilization (CCU) routes as disposal options for captured CO2 emissions. The adopted methodology is presented and applied to the study of urea synthesis and methanol production. Process flow modelling is used to analyze their technological performances. The adopted conceptual design strategy allows for the contextualization of the modelled technologies and their comparison in terms of selected scales and process configurations. The results highlight the potential benefit of CO2 utilization, by avoiding CO2 emissions. The proposed approach is amenable for the screening of other prospective technologies: polymer synthesis, CO2 mineralization and formic acid production, which will be addressed by the Joint Research Centre (JRC) in a follow-up study of CCU.
This comprehensive work shows how to design and develop innovative, optimal and sustainable chemical processes by applying the principles of process systems engineering, leading to integrated sustainable processes with 'green' attributes. Generic systematic methods are employed, supported by intensive use of computer simulation as a powerful tool for mastering the complexity of physical models.
New to the second edition are chapters on product design and batch processes with applications in specialty chemicals, process intensification methods for designing compact equipment with high energetic efficiency, plantwide control for managing the key factors affecting the plant dynamics and operation, health, safety and environment issues, as well as sustainability analysis for achieving high environmental performance. All chapters are completely rewritten or have been revised.
This new edition is suitable as teaching material for Chemical Process and Product Design courses for graduate MSc students, being compatible with academic requirements world-wide. The inclusion of the newest design methods will be of great value to professional chemical engineers.
Systematic approach to developing innovative and sustainable chemical processes
Presents generic principles of process simulation for analysis, creation and assessment
Emphasis on sustainable development for the future of process industries
Cement manufacturing is an energy intensive and heavy pollutant emissions process. It is accountable for CO2, NOX, SO2 emissions and some heavy metal discharge from the manufacturing process which causes severe greenhouse effects. Waste derived alternative fuels are widely used for substituting the thermal energy requirement from fossil fuels and reducing the pollutant emission. In the current study, a process model of the preheater tower is developed using Aspen Plus simulation software based on the combustion mechanism. Preheater tower is part of the modern energy efficient cement plant which is responsible for most of the CO2 release as the calcination of the raw material occurs at high temperature in this section. The model is verified against measured data from industry and data available in the literature. This paper presents the effects of the flow rate of waste derived fuels on the energy efficiency and emission from the preheater tower. Three different waste derived fuels, namely tyre derived fuel, meat and bone meal and refuse derived fuel are considered for this study. Fixed substitution rate of conventional fuel by the alternative one has been considered to identify the differences among the selected alternative fuels. Results show that maximum 3% increase of energy efficiency and 2.5% reduction of CO2 can be achieved by using tyre for about 25% of thermal energy requirement. Simulation results presented in this paper offer a guideline for implementing selected waste derived fuels in cement industry.
Global concentration of CO2 in the atmosphere is increasing rapidly. CO2 emissions have an impact on global climate change. Effective CO2 emission abatement strategies such as Carbon Capture and Storage (CCS) are required to combat this trend. There are three major approaches for CCS: post-combustion capture, pre-combustion capture and oxyfuel process. Post-combustion capture offers some advantages as existing combustion technologies can still be used without radical changes on them. This makes post-combustion capture easier to implement as a retrofit option (to existing power plants) compared to the other two approaches. Therefore, post-combustion capture is probably the first technology that will be deployed. This paper aims to provide a state-of-the-art assessment of the research work carried out so far in post-combustion capture with chemical absorption. The technology will be introduced first, followed by required preparation of flue gas from power plants to use this technology. The important research programmes worldwide and the experimental studies based on pilot plants will be reviewed. This is followed by an overview of various studies based on modelling and simulation. Then the focus is turned to review development of different solvents and process intensification. Based on these, we try to predict challenges and potential new developments from different aspects such as new solvents, pilot plants, process heat integration (to improve efficiency), modelling and simulation, process intensification and government policy impact.
The effect of the increasing concentration of CO2 in the atmosphere on climate change is a major driving force for the development of advanced energy cycles incorporating CO2 management options. Growing interest in the technical and economic feasibility of CO2 capture from large coal-based power plants has led to increased efforts worldwide to develop new concepts for greater CO2 reductions in the future. Greenhouse gas emissions, especially CO2, have to be reduced by 50–80% by 2050, according to the IPCC [1].The type of fuel used in cement manufacture directly impacts on CO2 emissions, with coal accounting for around 60–70% of CO2 emissions from cement installations. Therefore, the large amount of carbon dioxide emitted during cement manufacturing process - 5% of the total emissions of CO2 from stationary sources worldwide - is a cause of great concern and has to be tack led in order to comply with current legislation.Several technologies are available and have been proposed for the separation of CO2 from the flue gases from new and existing plants with retrofit capture units. Few studies have been undertaken on CO2 capture in cement plants to assess the suitable technologies, with oxy-combustion and amine scrubbing as the possible options (pre-combustion capture not being viable). This paper summarises the different CO2 capture technologies suitable for cement industry and assesses the potential of the calcium looping cycle [2,3] as a new route for CO2 capture in the cement industry. The potential advantage of this system is the very low efficiency penalty expected (
In the Carbon2Chem® joint research project, mathematical models are involved to simulate operation scenarios of cross‐industrial networks, especially chemical plants implemented in a steel mill environment. In order to achieve an optimal model‐based system integration approach, a distributed co‐simulation environment is introduced. In particular this enables model suppliers and integrators to exchange co‐simulation units without having to disclose sensitive information and intellectual property. Here, the architecture and preliminary results of such an environment which is based on a classical waveform relaxation algorithm are described.
CO2-based production technologies unveil the possibility of sustainable production in the chemical industry. However, so-called carbon capture and utilization (CCU) options do not inevitably lead to improved environmental performance, which is especially uncertain for emerging technologies compared to present production practices. Thus far, emerging CCU technologies have been environmentally assessed with conventional life cycle assessment (LCA). Therefore, this study aims to develop a methodology for applying prospective LCA to emerging production technologies from the laboratory to industrial scale. The developed four-step approach for implementing prospective LCA is applied to the case of electrochemical formic acid (FA) production via supercritical CO2 (scCO2) under consideration of different reactor designs to guide process engineers from an environmental standpoint. While using prospective LCA, the underlying modeling approach relies on consequential LCA (cLCA). Fourteen out of the fifteen analyzed impact categories (IC) reveal lower environmental impacts for the scale-ups, which are based on the best-case assumptions and on a flow-through regime compared to the conventional FA production. Nevertheless, the impacts of the scale-ups that are based on a batch reactor (BR) and a three compartment cell (TCC) are higher than for the best case and the flow-through reactor scale-up.
Low carbon options for the chemical industry include switching from fossil to renewable energy, adopting new low-carbon production processes, along with retrofitting current plants with carbon capture for ulterior use (CCU technologies) or storage (CCS). In this paper, we combine a dynamic Life Cycle Assessment (d-LCA) with economic analysis to explore a potential transition to low-carbon manufacture of formic acid. We propose new methods to enable early technical, environmental and economic assessment of formic acid manufacture by electrochemical reduction of CO2 (CCU), and compare this production route to the conventional synthesis pathways and to storing CO2 in geological storage (CCS). Both CCU and CCS reduce carbon emissions in particular scenarios, although the uncertainty in results suggests that further research and scale-up validation are needed to clarify the relative emission reduction compared to conventional process pathways. There are trade-offs between resource security, cost and emissions between CCU and CCS systems. As expected, the CCS technology yields greater reductions in CO2 emissions than the CCU scenarios and the conventional processes. However, compared to CCS systems, CCU has better economic potential and lower fossil consumption, especially when powered by renewable electricity. The integration of renewable energy in the chemical industry has an important climate mitigation role, especially for processes with high electrical and thermal energy demands.
Keeping carbon in the loop is a short sentence that describes the Carbon2Chem® project. Climate protection requires a reduction of CO2 emissions as well as less use of fossil fuels. In the project, a consortium from industry and science works on implementing a flexible carbon capture and utilization (CCU) concept for the carbon‐based industry. An example is the cross‐industrial network of steel industry, chemical industry, and energy industry. Instead of being harmful waste, top gases from the steel mill now serve as raw material for the production of synthetic fuels, plastics, and basic chemicals. This is possible through the systemic use of renewable energy.
Effective natural gas utilization while balancing profitability and CO2 footprints is of increasing importance in many regions of the world. This work addresses natural gas utilization in industrial clusters, where decisions are required on the allocation of available feedstock across possible processing options to convert natural gas into marketable products. In light of expected future requirements to significantly reduce CO2 emissions, such decisions should achieve utilization schemes that maximize economic returns but do not exceed acceptable emission limits. This work proposes a systematic, optimization-based approach to simultaneously determine natural gas utilization and CO2 management through carbon capture, utilization and storage as well as renewable energy strategies. The paper defines the problem and outlines the proposed approach before a case study is solved to illustrate its application.
Life cycle assessments (LCA) of an early research state reaction process only have laboratory experiments data available. While this is helpful in understanding the laboratory process from an environmental perspective, it gives only limited indication on the possible environmental impact of that same material or process at industrial production. Therefore, a comparative LCA study with materials that are already produced at industrial scales is not very meaningful. The scale-up of chemical processes is not such a trivial process and requires a certain understanding of the involved steps. In this paper, we elaborated a framework that helps to scale up chemical production processes for LCA studies when only data from laboratory experiments are available. Focusing on heated liquid phase batch reactions, we identified and simplified the most important calculations for the reaction step's energy use as well as for certain purification and isolation steps. For other LCA in- and output values, we provide estimations and important qualitative considerations to be able to perform such a scale-up study. Being an engineering-based approach mainly, it does not include systematically collected empirical data which would give a better picture about the uncertainty. However, it is a first approach to predict the environmental impact for certain chemical processes at an industrial production already during early laboratory research stage. It is designed to be used by LCA practitioners with limited knowledge in the field of chemistry or chemical engineering and help to perform such a scale-up based on a logical and systematic procedure.
Carbon dioxide capture and storage (CCS) is a technology aimed at reducing greenhouse gas emissions from burning fossil fuels during industrial and energy-related processes. CCS involves the capture, transport and long-term storage of carbon dioxide, usually in geological reservoirs deep underground that would otherwise be released to the atmosphere. Carbon dioxide capture and storage offers important possibilities for making further use of fossil fuels more compatible with climate change mitigation policies. The largest volumes of CO2 could be captured from large point sources such as from power generation, which alone accounts for about 40 per cent of total anthropogenic CO2 emissions. The development of capture technologies in the power generation sector could be particularly important in view of the projected increase in demand for electricity in fast developing countries with enormous coal reserves (IEA 2002a). Although, this prospect is promising, more research is needed to overcome several hurdles such as important costs of capture technology and the match of large capture sources with adequate geological storage sites. The book will provide a comprehensive, detailed but non-specialist overview of the wide range of technologies involved in carbon dioxide capture and sequestration.
With the growing environmental concern, there is evidence that increasing symbiotic relationship between plants in the same industrial area, highly contributes to a more sustainable development of industrial activities. The concept of industrial ecology extended to the terms of eco-industrial park (or ecopark) or industrial symbioses is the topic of extensive research since the five last years. More particularly, even if a lot of ecopark examples and realizations already exist throughout the world, a lot of ecopark proposals are in progress but not achieved. Recently, this vision leads the research community to focus on works proposing methods to optimize the exchanges of an ecopark prior to its design and construction. We find it especially interesting for the scientific community to propose a detailed paper review focused on optimization works devoted to the design of eco industrial parks.
Studies on leading technologies for industrial CO2 capture are performed. Each technology includes flue gas dehydration, capture of at least 90% of CO2 from the feed, and compression to almost pure CO2 for sequestration at 150 bar. This paper presents the modeling, simulation, optimization, and energy integration of a monoethanolamine (MEA)-based chemical absorption process and a multistage membrane process over a range of feed compositions (1–70% CO2, 5.5–15% H2O, 5.5% O2, and the balance N2) and flow rates (0.1, 1, 5, and 10 kmol/s). A superstructure of process alternatives is developed to select the optimum dehydration strategy for the feed to each process. A rigorous simulation-based optimization model is proposed to determine the minimum annualized cost of the MEA-absorption process. The MEA-absorption process is energy integrated through heat exchanger network optimization. A novel mathematical model is developed for the optimization of multistage and multicomponent separation of CO2 using membranes, which can be also used for a range of membrane-based gas separation applications. The results showing the optimum investment, operating, and total costs provide a quantitative approach toward technology comparison and scaling up the absorption- and membrane-based CO2 capture from various CO2 emitting industries. Explicit expressions for the investment and operating costs of each alternative postcombustion CO2 capture process as functions of feed flow rate and CO2 composition are also developed for the first time. This may assist the decision-makers in selecting the cost-appropriate technology for comprehensive carbon management by taking the diverse emission scenarios into consideration.
In the modern economy, international value chains—production, use, and disposal of goods—have global environmental impacts.
Life Cycle Assessment (LCA) aims to track these impacts and assess them from a systems perspective, identifying strategies
for improvement without burden shifting. We review recent developments in LCA, including existing and emerging applications
aimed at supporting environmentally informed decisions in policy-making, product development and procurement, and consumer
choices. LCA constitutes a viable screening tool that can pinpoint environmental hotspots in complex value chains, but we
also caution that completeness in scope comes at the price of simplifications and uncertainties. Future advances of LCA in
enhancing regional detail and accuracy as well as broadening the assessment to economic and social aspects will make it more
relevant for producers and consumers alike.
An analysis of the integration of a Ca-looping process into a cement plant is presented. The capture process, based on selective absorption of CO2 by calcium oxide, has two interconnected reactors where the carbonator captures CO2 from the preheater flue gases and the calciner regenerates the CaCO3 into CaO by oxy-combustion. The study also considers the purge rate of part of the circulating CaO, given the tendency of the material to sinter and reduce its capture capacity. Fresh CaCO3 is added to maintain reactivity in the carbonator, while the purged sorbents are utilised as a cement kiln feed. The detailed carbonator model has been implemented using Matlab and incorporated into Unisim to provide a full flowsheet simulation for an exemplary dry-feed cement plant as a user-defined operation. The effect of molar flowrate ratio of lime make-up to feed CO2 (F-0/FCO2) between two operational limits has been investigated. This process configuration is capable of achieving over 90% CO2 capture with additional fuel consumption of 2.5-3.0 GJ(th)/ton CO2 avoided which depends on the F-0/F-CO2 ratio. It is found that a proper heat recovery system supplementary to the Ca-looping process makes the Ca-looping process more competitive than the traditional low temperature absorption process based on amine solvents.
Utrecht University has conducted a pilot sustainability assessment for the executive board of the chemistry program ACTS (Advanced Chemical Technologies for Sustainability) of the Netherlands’ Organization for Scientific Research (NWO). These assessments represent prospective, i.e. ’ex-ante’ studies on the production of caprolactam by an improved catalyst and on different hydrogen storage options (i.e. compressed and liquefied hydrogen, storage in metal hydrides and storage in a metal organic framework). The pilot sustainability assessments followed the principles of environmental life cycle assessment (LCA), thereby focusing on non-renewable energy use (NREU) and climate change (GWP100). It was found that caprolactam with the novel catalyst has lower impacts than petrochemical caprolactam production from benzene but higher impacts than bio-based caprolactam produced via fermentation. Regarding hydrogen storage, it was found that compressed and liquid hydrogen have the highest impacts. The impacts of the metal hydrides and the metal organic frameworks show by far the lowest environmental impacts. The main reason is that these materials can be reused up to 1500 times (refilling of tank), while for compressing and liquefaction of hydrogen energy is needed each time a tank needs to be refilled. The study demonstrates the successful application of ex-ante technology assessment.
This book brings together all the information engineers and researchers need to develop efficient, cost-effective chemical production processes. The book presents a systematic approach to chemical process design, covering both continuous and batch processes. Starting with the basics, the book then moves on to advanced topics. Among the topics covered are: flowsheet synthesis, mass and energy balances, equipment sizing and costing, economic evaluation, process simulation and optimization. The book also covers specific chemical processes such as distillation systems, reactor networks, separation, and heat exchange networks. It shows how to build more flexible processes, including multiproduct batch processes.
A new method for analyzing an industrial energy system has been introduced in this paper. This method is based on the development and modifications of the R-curve concept. It consists of three graphical tools, namely, “R-curve”; “R-ratio vs. Total Annual Cost (TAC) curve” and “R-ratio vs. Emissions (EM) curve”. This new method can be applied to different scenarios which may include: retrofitting the utility system of a total site; and choosing the cleanest and most efficient and economical fuel for the boiler(s) of the utility system. Originally, “R-curve” indicates how the existing operation of utility system of the total site may be improved without any capital investments. “R-ratio vs. TAC curve” has been introduced to determine total annual cost of the utility system of a total site in each R-ratio value. “R-ratio vs. EM curve”, demonstrates the emission values of each pollutant in each R-ratio value.Therefore; these curves give a good sense for improving the operation, cost and emission values of any operating or under design total site. These curves are easy to be constructed and simple to be understood, they are also too powerful in providing insights for improving existing energy systems.
The adsorption of ammonia in four metal-organic frameworks modified with different functional groups (-OH, -C=O, -Cl, -COOH) was investigated using a hierarchical molecular modeling approach. To describe the hydrogen bonding and other strong interactions between NH(3) and the surface functional groups, a set of Morse potential parameters were obtained by fitting to energies from quantum chemical calculations at the MP2 level of theory. We describe a systematic force field parameterization process, in which the Morse parameters were fitted using simulated annealing to match a large number of single-point MP2 energies at various distances and angles. The fitted potentials were then used in grand canonical Monte Carlo simulations to predict ammonia adsorption isotherms and heats of adsorption in functionalized MIL-47, IRMOF-1, IRMOF-10, and IRMOF-16. The results show that ammonia adsorption can be significantly enhanced by using materials with appropriate pore size, strongly interacting functional groups, and high density of functional groups.
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