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Conditions for the broad application of prospective life cycle inventory databases
Major technological transitions are necessary to avoid the catastrophic consequences of climate change and other environmental damage (IPCC 2021). However, many of the technologies needed to achieve net zero greenhouse gas emissions by 2050 are still in the early stages of development (IEA 2021a). The implementation of these technologies is expected to occur once they are mature enough to enter the market. Some technologies will require significant capital and time to develop. Therefore, a good understanding of these technologies’ potential environmental impacts and guidance to minimize these impacts before such investments are made are crucial to meet environmental targets.
Prospective LCA (pLCA, similar terms are ex-ante and anticipatory LCA) assesses the potential environmental impacts of products and services of future technologies and guides their development (van der Giesen et al. 2020). Assessing the environmental impacts of future technologies often requires placing the temporal scope of the analysis in the mid- to long-term future, when the global economy, society, and environment will differ from today (Moss et al. 2010; Riahi et al. 2017; van Vuuren et al. 2011). It has been widely acknowledged that it is crucial to avoid a temporal mismatch between the foreground system (i.e., the technology under study) and the background system (i.e., the economic system the technology operates in) to support sustainable technology design and policymaking (Arvidsson et al. 2018; Buyle et al. 2019; Joyce and Björklund 2021; Knobloch et al. 2020; Thonemann et al. 2020; van der Giesen et al. 2020; Vandepaer et al. 2020).
Although LCA practitioners can typically obtain information on the development of the foreground system from technology developers, capturing systemic changes in the background is more complicated. Therefore, prospective life cycle inventory (pLCI) databases were developed: for example, within the NEEDS project (NEEDS 2009), the THEMIS model (Gibon et al. 2015; Hertwich et al. 2015), and more recently, in the work that led to the premise framework (Cox et al. 2020; Mendoza Beltran et al. 2018; Sacchi et al. 2022). These pLCI databases were derived from a combination of the ecoinvent database (Wernet et al. 2016) and exogenous scenario data to represent future technology and supply chains in specific sectors. Scenario data sources have included energy system models, input–output models, macro-economic models, integrated assessment models (IAMs), scientific literature, and expert judgment, depending on the availability of data for different technologies, economic sectors, and world regions.
Despite the importance of considering future scenarios for key economic sectors in pLCAs, and despite a recent increase in the use of pLCI databases in the academic literature (see Appendix), the use of pLCI databases remains the exception rather than the rule in future-oriented LCAs. This situation involves several issues relating to how pLCI databases are being generated, shared, and used. For example, pLCI databases remain difficult to obtain and use in standard LCA software. Furthermore, guidance for practitioners regarding content and the appropriate usage of pLCI databases is scarce. Also, the technological, sectoral, regional, and environmental coverage remains limited. Finally, a broader discussion to reach a consensus on the models and data sources pLCI databases should be based on has not yet occurred. Recent literature has discussed some of these issues. For example, Adrianto et al. (2021) highlight the need to streamline the process of including future background scenarios in pLCA. Bisinella et al. (2021) also stress the need for improved guidance when using future scenarios. Therefore, these issues need to be addressed to foster the more widespread use of pLCI databases.
To support these efforts, we provide an overview of the generation, sharing, and use of pLCI databases in this paper. We then discuss the conditions for a broad application of pLCI databases with the ultimate aim of improving environmental guidance for future technologies. Finally, we prioritize the challenges to be addressed to enable the widespread use of pLCI databases within pLCA.
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- Steubing, B.R.P.; Mendoza Beltran, A.; Sacchi, R.
- Date
- 2023-07-02
- Volume
- 28
- Pages
- 1092 - 1103