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@article{Sacchi:2022,
abstract = {Prospective Life Cycle Assessment (pLCA) is useful to evaluate the environmental performance of current and emerging technologies in the future. Yet, as energy systems and industries are rapidly shifting towards cleaner means of production, pLCA requires an inventory database that encapsulates the expected changes in technologies and the environment at a given point in time, following specific socio-techno-economic pathways. To this end, this study introduces premise, a tool to streamline the generation of prospective inventory databases for pLCA by integrating scenarios generated by Integrated Assessment Models (IAM). More precisely, premise applies a number of transformations on energy-intensive activities found in the inventory database ecoinvent according to projections provided by the IAM. Unsurprisingly, the study shows that, within a given socioeconomic narrative, the climate change mitigation target chosen affects the performance of nearly all activities in the database. This is illustrated by focusing on the effects observed on a few activities, such as systems for direct air capture of CO 2 , lithium-ion batteries, electricity and clinker production as well as freight transport by road, in relation to the applied sector-based transformation and the chosen climate change mitigation target. This work also discusses the limitations and challenges faced when coupling IAM and LCA databases and what improvements are to be brought in to further facilitate the development of pLCA.},
author = {Sacchi, Romain and Terlouw, T and Siala, K and Dirnaichner, A. and Bauer, C and Cox, B and Mutel, C. and Daioglou, V and Luderer, G},
doi = {10.1016/j.rser.2022.112311},
issn = {13640321},
journal = {Renewable and Sustainable Energy Reviews},
month = {may},
pages = {112311},
title = {{PRospective EnvironMental Impact asSEment (premise): A streamlined approach to producing databases for prospective life cycle assessment using integrated assessment models}},
url = {https://linkinghub.elsevier.com/retrieve/pii/S136403212200226X},
volume = {160},
year = {2022}
}
@article{Mutel:2017,
abstract = {Brightway is an open source framework for Life Cycle Assessment (LCA) calculations in Python. The combination of a modular structure, the expressiveness and interactivity of Python and in particular Jupyter notebooks, and tuned calculation pathways allows for new research directions in Life Cycle Assessment. Brightway has been used in papers on meta-analysis of many inventory datasets (Wernet et al. 2011), regionalized LCA (Mutel, Pfister, and Hellweg 2011), and sensitivity analysis (Mutel, Baan, and Hellweg 2013). Brightway consists of three main modules: Brightway2-data (Mutel 2012c) manages how data is stored and accessed; Brightway2-calc (Mutel 2012b) does static and Monte Carlo calculations; and Brightway2-IO (Mutel 2015c) handles the import and export of LCA data from various sources. In addition to these libraries, helper libraries provide documentation and application examples (Mutel 2012a), support for parameterized inventories (Mutel 2015b), and a format for LCA data in arrays (Mutel 2013). A web page (Mutel 2016), documentation (Mutel 2015a), and a development blog (Mutel 2014) are also available.},
author = {Mutel, Chris},
doi = {10.21105/joss.00236},
journal = {The Journal of Open Source Software},
number = {12},
pages = {236},
title = {{Brightway: An open source framework for Life Cycle Assessment}},
volume = {2},
year = {2017}
}
@article{Riahi:2017,
abstract = {This paper presents the overview of the Shared Socioeconomic Pathways (SSPs) and their energy, land use, and emissions implications. The SSPs are part of a new scenario framework, established by the climate change research community in order to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The long-term demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature. A multi-model approach was used for the elaboration of the energy, land-use and the emissions trajectories of SSP-based scenarios. The baseline scenarios lead to global energy consumption of 400–1200 EJ in 2100, and feature vastly different land-use dynamics, ranging from a possible reduction in cropland area up to a massive expansion by more than 700 million hectares by 2100. The associated annual CO2 emissions of the baseline scenarios range from about 25 GtCO2 to more than 120 GtCO2 per year by 2100. With respect to mitigation, we find that associated costs strongly depend on three factors: (1) the policy assumptions, (2) the socio-economic narrative, and (3) the stringency of the target. The carbon price for reaching the target of 2.6 W/m2 that is consistent with a temperature change limit of 2 °C, differs in our analysis thus by about a factor of three across the SSP marker scenarios. Moreover, many models could not reach this target from the SSPs with high mitigation challenges. While the SSPs were designed to represent different mitigation and adaptation challenges, the resulting narratives and quantifications span a wide range of different futures broadly representative of the current literature. This allows their subsequent use and development in new assessments and research projects. Critical next steps for the community scenario process will, among others, involve regional and sectoral extensions, further elaboration of the adaptation and impacts dimension, as well as employing the SSP scenarios with the new generation of earth system models as part of the 6th climate model intercomparison project (CMIP6).},
author = {Riahi, Keywan and van Vuuren, Detlef P. and Kriegler, Elmar and Edmonds, Jae and O'Neill, Brian C. and Fujimori, Shinichiro and Bauer, Nico and Calvin, Katherine and Dellink, Rob and Fricko, Oliver and Lutz, Wolfgang and Popp, Alexander and Cuaresma, Jesus Crespo and KC, Samir and Leimbach, Marian and Jiang, Leiwen and Kram, Tom and Rao, Shilpa and Emmerling, Johannes and Ebi, Kristie and Hasegawa, Tomoko and Havlik, Petr and Humpen{\"{o}}der, Florian and Da Silva, Lara Aleluia and Smith, Steve and Stehfest, Elke and Bosetti, Valentina and Eom, Jiyong and Gernaat, David and Masui, Toshihiko and Rogelj, Joeri and Strefler, Jessica and Drouet, Laurent and Krey, Volker and Luderer, Gunnar and Harmsen, Mathijs and Takahashi, Kiyoshi and Baumstark, Lavinia and Doelman, Jonathan C. and Kainuma, Mikiko and Klimont, Zbigniew and Marangoni, Giacomo and Lotze-Campen, Hermann and Obersteiner, Michael and Tabeau, Andrzej and Tavoni, Massimo},
doi = {10.1016/j.gloenvcha.2016.05.009},
issn = {09593780},
journal = {Global Environmental Change},
month = {1},
pages = {153-168},
title = {{The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview}},
volume = {42},
url = {https://www.sciencedirect.com/science/article/pii/S0959378016300681},
year = {2017}
}
@article{Bisinella:2021,
abstract = {Purpose: Future scenarios and life cycle assessment (LCA) are powerful tools that can provide early sustainability assessments of novel products, technologies and systems. The combination of the two methods involves practical and conceptual challenges, but formal guidance and consensus on a rigorous approach are currently missing. This study provides a comprehensive overview of how different topic areas use future scenarios and LCA in order to identify useful methods and approaches, and to provide overall recommendations. Methods: This study carried out a systematic literature review that involved searching for peer-reviewed articles on Web of Science, Scopus and Science Direct, utilising a rigorous set of keywords for future scenarios and for LCA. We identified 514 suitable peer-reviewed articles that were systematically analysed according to pre-defined sets of characteristics for the combined modelling of future scenarios and LCA. Results and discussion: The numbers of studies combining future scenarios and LCA increase every year and in all of the 15 topic areas identified. This combination is highly complex, due to different sequences in the modelling between future scenarios and LCA, the use of additional models and topic area-specific challenges. We identify and classify studies according to three archetypal modelling sequences: input, output and hybrid. More than 100 studies provide methods and approaches for combining future scenarios and LCA, but existing recommendations are specific to topic areas and for modelling sequences, and consensus is still missing. The efficacy of many studies is hampered by lack of quality. Only half of the articles complied with the LCA ISO standards, and only one quarter demonstrated consistent knowledge of future scenario theory. We observed inconsistent use of terminology and a considerable lack of clarity in the descriptions of methodological choices, assumptions and time frames. Conclusions and Recommendations: The combined use of future scenarios and LCA requires formal guidance, in order to increase clarity and communicability. Guidance should provide unambiguous definitions, identify minimum quality requirements and produce mandatory descriptions of modelling choices. The goal and scope of future scenarios and LCA should be in accordance, and quality should be ensured both for the future scenarios and the LCA. In particular, future scenarios should always be developed contextually, to ensure effective assessment of the problem at hand. Guidance should also allow for maintaining current modelling complexity and topic area differences. We provide recommendations from the reference literature on terminology, future scenario development and the combined use of future scenarios and LCA that may already constitute preliminary guidance in the field. Information collected and recommendations provided will assist in a more balanced development of the combined use of future scenarios and LCA in view of the urgent challenges of sustainable development.},
author = {Bisinella, V. and Christensen, T. H. and Astrup, T. F.},
doi = {10.1007/s11367-021-01954-6},
issn = {16147502},
journal = {International Journal of Life Cycle Assessment},
keywords = {Archetypes,Ex-ante,Foresight,Future scenarios,LCA,Life cycle assessment,Prospective},
number = {11},
pages = {2143--2170},
title = {{Future scenarios and life cycle assessment: systematic review and recommendations}},
volume = {26},
year = {2021}
}
@article{MendozaBeltran:2018,
author = {{Mendoza Beltran}, Angelica and Cox, Brian and Mutel, Chris and van Vuuren, Detlef and Vivanco, David Font and Deetman, Sebastiaan and Edelenbosch, Oreane and Guin{\'{e}}e, Jeroen and Tukker, Arnold},
doi = {10.1111/jiec.12825},
journal = {Journal of Industrial Ecology},
mendeley-groups = {Carculator},
title = {{When the Background Matters: Using Scenarios from Integrated Assessment Models in Prospective Life Cycle Assessment}},
year = {2018}
}
@article{Xu:2020,
abstract = {Coupling life cycle assessment (LCA) and energy systems models (ESM) is a suitable approach to assess energy systems from both life cycle and energy systems perspectives. However, methodological challenges need to be taken into account due to differences between both modeling approaches considering system boundaries, databases, and different levels of detail of their input data. This paper brings these challenges into discussion and introduces the Environmental Assessment Framework for Energy System Analysis (EAFESA), which enables to identify life cycle based non-climate environmental impacts of energy scenarios consistently. EAFESA is applied to analyze potential future decarbonized European electricity systems with a focus on flexibility options using ELTRAMOD as an example of an ESM to test the conceptual approach of combining ESM and LCA. The application confirms the importance and benefits of “integrated thinking” proposed by EAFESA, which allows minimizing the pitfalls of combining both models comprehensively. At the same time, EAFESA has the potential to bring awareness of issues not discussed among policy-makers. One example is the insight that the decarbonized electricity system will be accompanied by increased metal demand and urban land occupation.},
author = {Xu, Lei and Fuss, Maryegli and Poganietz, Witold Roger and Jochem, Patrick and Schreiber, Steffi and Zoephel, Christoph and Brown, Nils},
doi = {10.1016/j.jclepro.2019.118614},
issn = {09596526},
journal = {Journal of Cleaner Production},
keywords = {Energy scenarios,Energy system modeling,Life cycle assessment,Prospective analysis},
title = {{An Environmental Assessment Framework for Energy System Analysis (EAFESA): The method and its application to the European energy system transformation}},
volume = {243},
year = {2020}
}
@article{Pehl:2017,
abstract = {Both fossil-fuel and non-fossil-fuel power technologies induce life-cycle greenhouse gas emissions, mainly due to their embodied energy requirements for construction and operation, and upstream CH4 emissions. Here, we integrate prospective life-cycle assessment with global integrated energy-economy-land-use-climate modelling to explore life-cycle emissions of future low-carbon power supply systems and implications for technology choice. Future per-unit life-cycle emissions differ substantially across technologies. For a climate protection scenario, we project life-cycle emissions from fossil fuel carbon capture and sequestration plants of 78-110 gCO2eq kWh-1, compared with 3.5-12 gCO2eq kWh-1 for nuclear, wind and solar power for 2050. Life-cycle emissions from hydropower and bioenergy are substantial ($\sim$100 gCO2eq kWh-1), but highly uncertain. We find that cumulative emissions attributable to upscaling low-carbon power other than hydropower are small compared with direct sectoral fossil fuel emissions and the total carbon budget. Fully considering life-cycle greenhouse gas emissions has only modest effects on the scale and structure of power production in cost-optimal mitigation scenarios.},
author = {Pehl, Michaja and Arvesen, Anders and Humpen{\"{o}}der, Florian and Popp, Alexander and Hertwich, Edgar G. and Luderer, Gunnar},
doi = {10.1038/s41560-017-0032-9},
issn = {20587546},
journal = {Nature Energy},
number = {12},
pages = {939--945},
title = {{Understanding future emissions from low-carbon power systems by integration of life-cycle assessment and integrated energy modelling}},
volume = {2},
year = {2017}
}
@article{Rauner:2017,
abstract = {Making the global energy system more sustainable has emerged as a major societal concern and policy objective. This transition comes with various challenges and opportunities for a sustainable evolution affecting most of the UN's Sustainable Development Goals. We therefore propose broadening the current metrics for sustainability in the energy system modeling field by using industrial ecology techniques to account for a conclusive set of indicators. This is pursued by including a life cycle based sustainability assessment into an energy system model considering all relevant products and processes of the global supply chain. We identify three pronounced features: (i) the low-hanging fruit of impact mitigation requiring manageable economic effort; (ii) embodied emissions of renewables cause increasing spatial redistribution of impact from direct emissions, the place of burning fuel, to indirect emissions, the location of the energy infrastructure production; (iii) certain impact categories, in which more overall sustainable systems perform worse than the cost minimal system, require a closer look. In essence, this study makes the case for future energy system modeling to include the increasingly important global supply chain and broaden the metrics of sustainability further than cost and climate change relevant emissions.},
author = {Rauner, Sebastian and Budzinski, Maik},
doi = {10.1088/1748-9326/aa914d},
issn = {17489326},
journal = {Environmental Research Letters},
keywords = {co-benefits,energy system modeling,hybrid modeling,life cycle assessment,multi-objective,sustainability},
number = {12},
title = {{Holistic energy system modeling combining multi-objective optimization and life cycle assessment}},
volume = {12},
year = {2017}
}
@article{Gibon:2015,
abstract = {Climate change mitigation demands large-scale technological change on a global level and, if successfully implemented, will significantly affect how products and services are produced and consumed. In order to anticipate the life cycle environmental impacts of products under climate mitigation scenarios, we present the modeling framework of an integrated hybrid life cycle assessment model covering nine world regions. Life cycle assessment databases and multiregional input-output tables are adapted using forecasted changes in technology and resources up to 2050 under a 2 °C scenario. We call the result of this modeling "technology hybridized environmental-economic model with integrated scenarios" (THEMIS). As a case study, we apply THEMIS in an integrated environmental assessment of concentrating solar power. Life-cycle greenhouse gas emissions for this plant range from 33 to 95 g CO2 eq./kWh across different world regions in 2010, falling to 30-87 g CO2 eq./kWh in 2050. Using regional life cycle data yields insightful results. More generally, these results also highlight the need for systematic life cycle frameworks that capture the actual consequences and feedback effects of large-scale policies in the long term.},
author = {Gibon, Thomas and Wood, Richard and Arvesen, Anders and Bergesen, Joseph D. and Suh, Sangwon and Hertwich, Edgar G.},
doi = {10.1021/acs.est.5b01558},
issn = {15205851},
journal = {Environmental Science and Technology},
number = {18},
pages = {11218--11226},
pmid = {26308384},
title = {{A Methodology for Integrated, Multiregional Life Cycle Assessment Scenarios under Large-Scale Technological Change}},
volume = {49},
year = {2015}
}
@article{Wernet:2016,
author = {Wernet, G. and Bauer, C. and Steubing, B. and Reinhard, J. and Moreno-Ruiz, E. and Weidema, B.},
doi = {10.1007/s11367-016-1087-8},
journal = {The International Journal of Life Cycle Assessment},
number = {9},
pages = {1218--1230},
title = {{The ecoinvent database version 3 (part I): overview and methodology.}},
url = {http://link.springer.com/10.1007/s11367-016-1087-8},
volume = {21},
year = {2016}
}
@article{Volkart:2018,
author = {Volkart, Kathrin and C.L. Mutel and Panos, E.},
doi = {10.1016/j.spc.2018.07.001},
journal = {Sustainable Production and Consumption},
pages = {121-133},
title = {{Integrating life cycle assessment and energy system modelling:
Methodology and application to the world energy scenarios}},
url = {https://www.sciencedirect.com/science/article/pii/S235255091830071X?via%3Dihub},
volume = {16},
year = {2018}
}
@article{Vandepaer:2020,
author = {Vandepaer, Laurent and Panos, Evangelos and Bauer, Christian and Amor, Ben},
doi = {10.1021/acs.est.9b06484},
journal = {Environmental Science & Technology},
pages = {5081-5092},
title = {{Energy system pathways with low environmental impacts and limited costs: Minimizing climate change impacts produces environmental cobenefits and challenges in toxicity and metal depletion categories}},
url = {https://pubs.acs.org/doi/10.1021/acs.est.9b06484},
volume = {54},
year = {2020}
}
@article{Iwanaga2022,
title = {Toward {SALib} 2.0: {Advancing} the accessibility and interpretability of global sensitivity analyses},
volume = {4},
url = {https://sesmo.org/article/view/18155},
doi = {10.18174/sesmo.18155},
journal = {Socio-Environmental Systems Modelling},
author = {Iwanaga, Takuya and Usher, William and Herman, Jonathan},
month = may,
year = {2022},
pages = {18155},
}
@article{Herman2017,
doi = {10.21105/joss.00097},
url = {https://doi.org/10.21105/joss.00097},
year = {2017},
month = {jan},
publisher = {The Open Journal},
volume = {2},
number = {9},
author = {Jon Herman and Will Usher},
title = {{SALib}: An open-source Python library for Sensitivity Analysis},
journal = {The Journal of Open Source Software}
}
@article{BORGONOVO2007771,
abstract = {Uncertainty in parameters is present in many risk assessment problems and leads to uncertainty in model predictions. In this work, we introduce a global sensitivity indicator which looks at the influence of input uncertainty on the entire output distribution without reference to a specific moment of the output (moment independence) and which can be defined also in the presence of correlations among the parameters. We discuss its mathematical properties and highlight the differences between the present indicator, variance-based uncertainty importance measures and a moment independent sensitivity indicator previously introduced in the literature. Numerical results are discussed with application to the probabilistic risk assessment model on which Iman [A matrix-based approach to uncertainty and sensitivity analysis for fault trees. Risk Anal 1987;7(1):22–33] first introduced uncertainty importance measures.},
author = {Borgonovo, E},
doi = {10.1016/j.ress.2006.04.015},
issn = {0951-8320},
journal = {Reliability Engineering & System Safety},
keywords = { Global sensitivity analysis, Probabilistic risk assessment, Uncertainty analysis, Uncertainty importance measures,Importance measures},
number = {6},
pages = {771--784},
title = {{A new uncertainty importance measure}},
url = {https://www.sciencedirect.com/science/article/pii/S0951832006000883},
volume = {92},
year = {2007}
}
@article{RECC:2021,
author = {Pauliuk, S. and Fishman, T. and Heeren, N. and Berrill, P. and Tu, Q. and Wolfram, P. and Hertwich, E.G.},
doi = {10.1111/jiec.13023},
journal = {Journal of Industrial Ecology},
pages = {260--273},
title = {{Linking service provision to material cycles: A new framework for studying the resource efficiency–climate change (RECC) nexus}},
url = {https://onlinelibrary.wiley.com/doi/full/10.1111/jiec.13023},
volume = {25},
year = {2021}
}
@article{Mat-dp:2022,
author = {Cervantes Barron, K. and Cullen, J.M.},
doi = {10.21105/joss.04460},
journal = {Journal of Open Source Software},
pages = {4460},
title = {{Mat-dp: An open-source Python model for analysing material demand projections and their environmental implications, which result from building low-carbon systems.}},
url = {https://joss.theoj.org/papers/10.21105/joss.04460},
volume = {7},
number = {76},
year = {2022}
}
@article{Mat-dp:2024,
author = {Cervantes Barron, K. and Cullen, J.M.},
doi = {10.1016/j.resconrec.2024.107803},
journal = {Resources, Conservation and Recycling},
pages = {107803},
title = {{Using open-source tools to project bulk and critical material demand and assess implications for low-carbon energy and transport systems: Introducing Mat-dp model tools.}},
url = {https://joss.theoj.org/papers/10.21105/joss.04460},
volume = {209},
year = {2024}
}