Risk management optimization framework for the optimal deployment of carbon capture and storage system under uncertainty

Zhang, Shuai; Zhuang, Yu; Liu, Linlin; Zhang, Lei; Du, Jian

doi:10.1016/j.rser.2019.109280

Cited by 32 publications

(12 citation statements)

References 44 publications

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“…Carbon capture and storage (CCS) is one option to reduce the CO 2 from emissions. There is growing interest and investment, but there are uncertainties with respect to adapted technologies, engineering performance, and natural hazards [165]. The U.S. Department of Energy, National Energy Technology Laboratory, has developed many applications of RS technologies to monitor storage operations, including SRS, ARS (LiDAR), and USV [128] to assess CCS.…”

Section: Carbon Capture and Storagementioning

confidence: 99%

Contribution of Remote Sensing Technologies to a Holistic Coastal and Marine Environmental Management Framework: A Review

et al. 2020

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Coastal and marine management require the evaluation of multiple environmental threats and issues. However, there are gaps in the necessary data and poor access or dissemination of existing data in many countries around the world. This research identifies how remote sensing can contribute to filling these gaps so that environmental agencies, such as the United Nations Environmental Programme, European Environmental Agency, and International Union for Conservation of Nature, can better implement environmental directives in a cost-effective manner. Remote sensing (RS) techniques generally allow for uniform data collection, with common acquisition and reporting methods, across large areas. Furthermore, these datasets are sometimes open-source, mainly when governments finance satellite missions. Some of these data can be used in holistic, coastal and marine environmental management frameworks, such as the DAPSI(W)R(M) framework (Drivers–Activities–Pressures–State changes–Impacts (on Welfare)–Responses (as Measures), an updated version of Drivers–Pressures–State–Impact–Responses. The framework is a useful and holistic problem-structuring framework that can be used to assess the causes, consequences, and responses to change in the marine environment. Six broad classifications of remote data collection technologies are reviewed for their potential contribution to integrated marine management, including Satellite-based Remote Sensing, Aerial Remote Sensing, Unmanned Aerial Vehicles, Unmanned Surface Vehicles, Unmanned Underwater Vehicles, and Static Sensors. A significant outcome of this study is practical inputs into each component of the DAPSI(W)R(M) framework. The RS applications are not expected to be all-inclusive; rather, they provide insight into the current use of the framework as a foundation for developing further holistic resource technologies for management strategies in the future. A significant outcome of this research will deliver practical insights for integrated coastal and marine management and demonstrate the usefulness of RS to support the implementation of environmental goals, descriptors, targets, and policies, such as the Water Framework Directive, Marine Strategy Framework Directive, Ocean Health Index, and United Nations Sustainable Development Goals. Additionally, the opportunities and challenges of these technologies are discussed.

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Section: Carbon Capture and Storagementioning

confidence: 99%

Contribution of Remote Sensing Technologies to a Holistic Coastal and Marine Environmental Management Framework: A Review

et al. 2020

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“…Each scenario is multiplied by scenario probability of occurrence [65]. The probability is obtained considering that the random production costs have a discrete normal probability distribution with a defined number of realizations sampled randomly using Monte Carlo method [42,52,66]. Real data about these parameters are not present, thus this method is suggested.…”

Section: Objective Functionmentioning

confidence: 99%

“…Their results show that uncertainties may be significant in the design of carbon frameworks. A multi-objective optimization based on a stochastic model was suggested by Zhang et al [42] for a CCS supply chain in northeast China, where carbon tax is the variable parameter. Economic and risk objective functions are considered.…”

Section: Introductionmentioning

confidence: 99%

Optimization of CCUS Supply Chains for Some European Countries under the Uncertainty

2020

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This paper develops a two-stage stochastic mixed integer linear programming model to optimize Carbon Capture, Utilization and Storage (CCUS) supply chains in Italy, Germany and the UK. Few works are present in the literature about this topic, thus this paper overcomes this limitation considering carbon supply chains producing different products. The objective of the numerical models is to minimize expected total costs, under the uncertainties of the production costs of carbon-dioxide-based compounds. Once carbon dioxide emissions that should be avoided are fixed, according to environmental protection requirements for each country, the optimal design of these supply chains is obtained finding the distribution of carbon dioxide captured between utilization and storage sections, the amount of different carbon-based products and the best connection between each element inside the system. The expected total costs for the CCUS supply chain of Italy, Germany and the UK are, respectively, 77.3, 98.0 and 1.05 billion€/year (1004, 613 and 164 €/ton CO2 captured). A comparison with the respective deterministic model, analyzed elsewhere, is considered through the evaluation of the Expected Value of Perfect Information (EVPI) and the Value of Stochastic Solution (VSS). The former is 1.29 billion€/year, 0.18 million€/year and 8.31 billion€/year, respectively, for the CCUS of Italy, the UK and Germany. VSS on the other hand is equal to 1.56 billion€/year, 0 €/year and 0.1 billion€/year, respectively, for the frameworks of Italy, the UK and Germany. The results show that the uncertain production cost in the stochastic model does not have a significant effect on the results; thus, in this case, there are few advantages in solving a stochastic model instead of the deterministic one.

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“…Between 2015 and 2040, atmospheric CO 2 emissions are projected to grow at a yearly average rate of 0.6%. To mitigate the global mean temperature rise, the Paris Climate Agreement was set to limit the increase in temperature to a maximum of 2 • C compared to the pre-industrial level (Zhang et al, 2019). Therefore global efforts need to be set in practice, and this will involve the effective use of renewable fossil fuels substitutes, such as biomethane (bio CH 4 ) upgraded from biogas (Lapa et al, 2017;Surra et al, 2019), as well as the stabilization of atmospheric CO 2 concentrations at 450 ppm, which can be achieved through the carbon capture and storage (CCS) of 120-160 GtCO 2 up to 2050 (Dowell et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Paramagnetic Ionic Liquid/Metal Organic Framework Composites for CO2/CH4 and CO2/N2 Separations

et al. 2020

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Global warming is arguably the biggest scientific challenge of the twenty-first century and its environmental consequences are already noticeable. To mitigate the emissions of greenhouse gases, particularly of CO 2 , there is an urgent need to design materials with improved adsorbent properties. Five different magnetic ionic liquids were impregnated into the metal–organic framework ZIF-8. The composites were produced by a direct-contact method, and their performance as sorbents for gas separation applications was studied. The impact of the ionic liquid anion on the sorption capacity and ideal CO 2 /CH 4 and CO 2 /N 2 selectivities were studied, focusing on understanding the influence of metal atom and ligand on the adsorbent properties. Reproducible methodology, along with rigorous characterization, were established to assess the impact of the ionic liquid on the performance of the composite materials. Results show that the ionic liquid was well-impregnated, and the ZIF-8 structure was maintained after ionic liquid impregnation. The produced composites were of microporous nature and were thermally stable. CO 2 , CH 4 , and N 2 adsorption–desorption isotherms were obtained at 303 K and between 0 and 16 bar. The adsorption-desorption data of the composites were compared with that obtained for original ZIF-8. The general trend in composites is that the increased gas uptake per available pore volume compensates the pore volume loss. Adsorption data per unit mass showed that composites have reversible sorption, but inferior gas uptake at all pressure ranges. This is due to the observed total pore volume loss by the ionic liquid pore occupation/blockage. In most cases, composites showed superior selectivity performance at all pressure range. In particular, the composite [C 4 MIM] 2 [MnCl 4 ]@ZIF-8 shows a different low-pressure selectivity trend from the original MOF, with a 33% increase in the CO 2 /N 2 selectivity at 1 bar and 19% increase in the CO 2 /CH 4 selectivity at 10 bar. This material shows potential for use in a post-combustion CO 2 capture application that can contribute to greenhouse gas mitigation.

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Risk management optimization framework for the optimal deployment of carbon capture and storage system under uncertainty

Cited by 32 publications

References 44 publications

Contribution of Remote Sensing Technologies to a Holistic Coastal and Marine Environmental Management Framework: A Review

Contribution of Remote Sensing Technologies to a Holistic Coastal and Marine Environmental Management Framework: A Review

Optimization of CCUS Supply Chains for Some European Countries under the Uncertainty

Paramagnetic Ionic Liquid/Metal Organic Framework Composites for CO2/CH4 and CO2/N2 Separations

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