EODC

paper.bib

@@ -36,4 +36,85 @@ @article{Riahi:2017
 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 = {https://doi.org/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}
+}
+
+
+
+
+
+

paper.md

@@ -43,25 +43,52 @@ toxicity impacts, etc.
 
 # Statement of need
 
-IAMs, frequently based on Shared Socioeconomic Pathways (SSPs), offer cost-optimized projections of future scenarios. 
-These scenarios highlight, for example, the necessary changes in regional electricity mixes and different means of 
-transport to meet global warming mitigation objectives [@Riahi:2017]. This scenario analysis exercise enables us to 
-consider future system changes and their effects on the environmental performance of different technologies 
-along the different supply chains. In this context, prospective Life Cycle Assessment (pLCA) emerges as a unique tool 
-to provide a robust evaluation of the environmental performance of both existing and anticipated production systems. 
-At the methodological level, [@Sacchi:2022] has recently laid the foundations for extending present-day process-based 
-life-cycle inventory into the future using the output from IAMs. Meanwhile, most efforts in pLCA have been centred 
-around improving the ability to forecast future life cycle inventories accurately.
-
-At this juncture, performing an LCA of the transition scenarios using the updated life cycle inventories at each time step
-uncaps excellent potential to improve the sustainability assessment of these scenarios. LCA would expand the 
-conventional focus on GHG emissions to broader environmental impacts, such as land use, water consumption, and toxicity 
-while considering direct and indirect emissions. However, running LCAs of the transition scenarios provided by IAMs -
-or energy system models - at the system level remains challenging. Mainly because of the computational expense of running 
-LCAs for each time step and region of each scenario and the methodological complexity of consistently defining the 
-functional unit of the LCA based on the IAMs outputs while dealing with issues such as double-counting. 
-`pathways`, using the LCA framework `brightway2` [@Mutel:2017] and building on `premise`, offers a solution to these 
-challenges by providing a tool to evaluate the environmental impacts of transition scenarios systematically.
+Most IAMs and ESMs project future energy supply optimized for cost under a given 
+greenhouse gas emissions trajectory. These scenarios outline changes 
+required in regional energy mixes to achieve global warming mitigation goals 
+[@Riahi:2017]. By analyzing these scenarios, we can assess how future system 
+changes will affect the environmental performance of various technologies across 
+supply chains. 
+
+Prospective LCA (pLCA) emerges as a valuable tool for evaluating 
+the environmental performance of both existing and emerging production systems.
+The body of literature applying scenario-based pLCA to emerging technologies has 
+flourished in the past decade -- see literature review of [@Bisinella:2021].
+
+Extending present-day process-based life-cycle inventories into the future using 
+IAM outputs lays the methodological groundwork for pLCA. Such approach was 
+initially started with the work of [@MendozaBeltran:2018], and more recently 
+formalized with the Python library `premise` [@Sacchi:2022]. 
+
+However, efforts in pLCA have primarily focused on improving the accuracy of 
+forecasting future life cycle inventories. Performing scenario-wide LCAs
+with life cycle inventories adjusted to each time step of the scenario has 
+significant potential to enhance sustainability assessments. This approach broadens 
+the focus beyond greenhouse gas emissions to encompass broader environmental 
+impacts like land use, water consumption, and toxicity, accounting for both 
+direct and indirect emissions. Nonetheless, conducting system-wide LCA remains 
+challenging due to computational costs and methodological complexities, such as 
+defining the functional unit based on IAM outputs and addressing issues like 
+double-counting. 
+
+Several studies have attempted to address the challenges of coupling
+ESM/IAM with LCA, with notable contributions from [@Gibon:2015], [@Rauner:2017] and
+[@Pehl:2017], who quantified the outputs of an ESM or IAM scenario, 
+with a hybrid-LCA framework. The comprehensive and ambitious framework EAFESA 
+developed by Xu and colleagues [@Xu:2020], which aimed at a bidirectional coupling
+between ESM and LCA is also worth mentioning. However, these studies have
+focused on specific sectors or technologies, and have not yet been generalized
+to a broader range of scenarios and indicators. Also, to the authors' knowledge,
+their implementation has not been made available to the broader scientific community.
+
+To tackle these challenges, the open-source library `pathways` leverages the 
+LCA framework `brightway2` [@Mutel:2017] and offers a systematic tool for 
+evaluating the environmental impacts of energy transition scenarios. `pathways` is
+designed to work with data packages containing LCA matrices which have been
+adjusted to each time step of the ESM/IAM scenario. The library calculates the 
+environmental impacts of the scenario (or a subset of it) over time, 
+providing a more detailed and transparent view of the environmental impacts implied
+by the scenario.
 
 # Description