Life cycle assessment demonstrates environmental co-benefits and trade-offs of low-carbon electricity supply options

Gibon, Thomas; Arvesen, Anders; Hertwich, Edgar G.

doi:10.1016/j.rser.2017.03.078

Cited by 91 publications

(64 citation statements)

References 81 publications

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“…In the consequential system model of ecoinvent v.3.4, the linking algorithm is replaced by a so-called Bmarket override^: electricity markets are determined by the procedure described in the previous section and manually 4 According to Gibon et al (2017), biopower technologies can generate life cycle climate change impacts ranging from 28 to 194 kg CO2 eq./MWh. This compares to an impact score of 37 kg CO2 eq./MWh for the created power only bio-energy unit.…”

Section: Comparison Of Methodologies Used In Consequential System Modmentioning

confidence: 99%

“…& A set of midpoint categories from the ReCiPe 2008 Midpoint (H) impact assessment method (Goedkoop et al 2008). The selection of impact categories is based on the work by Gibon and colleagues (Gibon et al 2017) in their assessment of low-carbon electricity supply options which are namely: freshwater ecotoxicity, freshwater eutrophication, human toxicity, metal depletion, particulate matter formation, photochemical oxidant formation, terrestrial acidification, and urban land occupation. & Finally, the single score method ReCiPe 2008 Endpoint (H,A) is used to obtain the overall environmental performance of the different marginal electricity supply mixes in a single weighted and normalized indicator (Goedkoop et al 2008).…”

Section: Market Mix/impact Assessment Calculations and Comparative Anmentioning

confidence: 99%

“…Electricity supply is a central parameter in the life cycle assessments (LCA) of numerous products and services (Reinhard et al 2016;Steubing et al 2016;Gibon et al 2017;Cox et al 2018). In version 3.4 of the ecoinvent consequential database, electricity contributes on average 36% of the climate change impact scores of all the activities covered.…”

Section: Introductionmentioning

confidence: 99%

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The integration of long-term marginal electricity supply mixes in the ecoinvent consequential database version 3.4 and examination of modeling choices

Vandepaer

Treyer

Mutel

et al. 2018

Int J Life Cycle Assess

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Purpose The long-term marginal electricity supply mixes of 40 countries were generated and integrated into version 3.4 of the ecoinvent consequential database. The total electricity production originating from these countries accounts for 77% of the current global electricity generation. The goal of this article is to provide an overview of the methodology used to calculate the marginal mixes and to evaluate the influence of key parameters and methodological choices on the results. Methods The marginal mixes are based on public energy projections from national and international authorities and reflect the accumulated effect of changes in demand for electricity on the installation and operation of new-generation capacities. These newly generated marginal mixes are first examined in terms of their compositions and environmental impacts. They are then compared to several sets of alternative electricity supply mixes calculated using different methodological choices or data sources. Results and discussion Renewable energy sources (RES) as well as natural gas power plants show the highest growth rates and usually dominate the marginal mixes. Nevertheless, important variations may exist between the marginal mixes of the different countries in terms of their technological compositions and environmental impacts. The examination of the modeling choices reveals substantial variations between the marginal mixes integrated into the ecoinvent consequential database version 3.4 and marginal mixes generated using alternative modeling options. These different modeling possibilities include changes in the methodology, temporal parameters, and the underlying energy scenarios. Furthermore, in most of the impact categories, average (i.e., attributional) mixes cause higher impact scores than marginal mixes due to higher shares of RES in marginal mixes. Conclusions Accurate and consistent data for electricity supply is integrated into a consequential database providing a strong basis for the development of consequential Life Cycle Assessments. The methodology adopted in this version of the database eliminates several shortcomings from the previous approach which led to unrealistic marginal mixes in several countries. The use of energy scenarios allows the evolution of the electricity system to be considered within the definition of the marginal mixes. The modeling choices behind the electricity marginal mix should be adjusted to the goal and scope of individual studies and their influence on the results evaluated. Keywords CLCA. Ecoinvent. Life cycle inventory (LCI) database. Long-term marginal electricity supply mix 1 Using the IPCC Global Warming Potentials (GWP) characterization factors with a time horizon of 100 years and the calculation approach detailed in Mutel (2018).

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Section: Comparison Of Methodologies Used In Consequential System Modmentioning

confidence: 99%

Section: Market Mix/impact Assessment Calculations and Comparative Anmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The integration of long-term marginal electricity supply mixes in the ecoinvent consequential database version 3.4 and examination of modeling choices

Vandepaer

Treyer

Mutel

et al. 2018

Int J Life Cycle Assess

View full text Add to dashboard Cite

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“…Studies taking this approach have developed LCAs of long term energy scenarios, developing dynamic life-cycle inventories that are fully consistent with the energy mix depicted in the scenario, focusing for example on wind power (Arvesen and Hertwich 2011), renewables in Australia (Wolfram et al 2016) or in Europe (Peter et al 2016), and low-carbon technologies more generally (Hertwich et al 2015). These scenarios are typically generated using energy system optimisation models, such as the IEA's ETP model, a member of the MARKAL/TIMES family, which was used by (Gibon et al 2015;Arvesen and Hertwich 2011;Hertwich et al 2015;Gibon et al 2017). These studies provide valuable insights into the relative environmental impacts associated with various technologies in different possible futures: they have shown that technologies with low use-phase carbon emissions also provide considerable co-benefits (Hertwich et al 2015), as well as performing well in terms of whole-life-cycle carbon emissions (Wolfram et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Is the optimal decarbonization pathway influenced by indirect emissions? Incorporating indirect life-cycle carbon dioxide emissions into a European TIMES model

McDowall¹,

Rodríguez²,

Usubiaga³

et al. 2018

Journal of Cleaner Production

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This paper first reviews previous relevant efforts to bring energy system models and life-cycle assessments together. In section 3, we set out the method we have used, including the details of the EEIO model, the TIMES model, the procedures for linking them, and the scenarios examined. Section 4 then provides results relating to each of the research questions, while section 5 draws key conclusions. The paper is accompanied by a supplementary file that includes considerable further detail on the modelling approach, the data used, and the results. 2 Literature review Bottom-up ESOMs (such as MARKAL [Loulou et al. 2004] and TIMES [Loulou et al. 2004]) and MESSAGE (Messner and Schrattenholzer 2000)) provide a detailed depiction of the energy system, with explicit representation of primary extraction of energy resources, processing and conversion, delivery to consumers, and end-use (DeCarolis et al. 2017). Such models account for some emissions associated with upstream extraction (flaring, for example), and they account for the efficiency losses and energy inputs associated with conversion and processing (e.g. in refineries and power stations), with transmission and distribution (losses in electricity transmission lines, energy use in fuel distribution, etc.), and efficiency losses in end use devices. Many sources of fossil fuel chain indirect emissions are thus already included in the default setup of TIMES (see the supplementary file for further details). ESOMs are "demand-driven" in the sense that the energy service demands across the economy are a key exogenous input into the models. Energy service demands associated with

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“…From the environmental point of view, emerging PVs are of interest since their thin-film technology is associated with savings of weight and materials. Therefore, the life-cycle impacts of emerging PVs are expected to be lower than those of commercial PVs of the first and second generations.PVs were investigated in a multitude of LCA studies which led to general insight into their life-cycle impacts [8][9][10][11][12][13][14][15], i.e., about 80% of total life-cycle GHG emissions can be attributed to the production stage [15]. However, different LCA studies on PV revealed large differences in results [11,12], an observation that was also made for LCAs of other electricity generation technologies.…”

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confidence: 99%

Environmental Performance of Emerging Photovoltaic Technologies: Assessment of the Status Quo and Future Prospects Based on a Meta-Analysis of Life-Cycle Assessment Studies

2019

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Emerging photovoltaic technologies are expected to have lower environmental impacts during their life cycle due to their extremely thin-film technology and resulting material savings. The environmental impacts of four emerging photovoltaics were investigated based on a meta-analysis of life-cycle assessment (LCA) studies, comprising a systematic review and harmonization approach of five key indicators to describe the environmental status quo and future prospects. The status quo was analyzed based on a material-related functional unit of 1 watt-peak of the photovoltaic cell. For future prospects, the functional unit of 1 kWh of generated electricity was used, including assumptions on the use phase, notably on the lifetime. The results of the status quo show that organic photovoltaic technology is the most mature emerging photovoltaic technology with a competitive environmental performance, while perovskites have a low performance, attributed to the early stage of development and inefficient manufacturing on the laboratory scale. The results of future prospects identified improvements of efficiency, lifetime, and manufacturing with regard to environmental performance based on sensitivity and scenario analyses. The developed harmonization approach supports the use of LCA in the early stages of technology development in a structured way to reduce uncertainty and extract significant information during development.

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Life cycle assessment demonstrates environmental co-benefits and trade-offs of low-carbon electricity supply options

Abstract: Printed by Skipnes Kommunikasjon as PREFACE i PREFACE Βουλεύου μὲν βραδέως, ἐπιτέλει δὲ ταχέως τὰ δόξαντα. Be slow in deliberation, but be prompt to carry out your resolves.Isocrates, To Demonicus, ca. 400 B.C.

Cited by 91 publications

References 81 publications

The integration of long-term marginal electricity supply mixes in the ecoinvent consequential database version 3.4 and examination of modeling choices

The integration of long-term marginal electricity supply mixes in the ecoinvent consequential database version 3.4 and examination of modeling choices

Is the optimal decarbonization pathway influenced by indirect emissions? Incorporating indirect life-cycle carbon dioxide emissions into a European TIMES model

Environmental Performance of Emerging Photovoltaic Technologies: Assessment of the Status Quo and Future Prospects Based on a Meta-Analysis of Life-Cycle Assessment Studies

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