Purpose
Lithium-ion (Li-ion) battery packs recovered from end-of-life electric vehicles (EV) present potential technological, economic and environmental opportunities for improving energy systems and material efficiency. Battery packs can be reused in stationary applications as part of a “smart grid”, for example to provide energy storage systems (ESS) for load leveling, residential or commercial power. Previous work on EV battery reuse has demonstrated technical viability and shown energy efficiency benefits in energy storage systems modeled under commercial scenarios. The current analysis performs a life cycle assessment (LCA) study on a Li-ion battery pack used in an EV and then reused in a stationary ESS.

A cascaded life cycle: reuse of electric vehicle lithium-ion battery packs in energy storage systems

Despite 20 years of research, there remains no robust, globally agreed upon method—or even problem statement—for assessing mineral resource inputs in life cycle impact assessment (LCIA). As a result, inclusion of commonly used methods such as abiotic depletion potential (ADP) in life cycle assessment (LCA)-related evaluation schemes could lead to incorrect decisions being made in many applications. In this paper, we explore in detail how to improve the way that life cycle thinking is applied to the acquisition of mineral resources and their metal counterparts. This paper evaluates the current body of work in LCIA with regard to “depletion potential” of mineral resources. Viewpoints from which models are developed are described and analyzed. The assumptions, data sources, and calculations that underlie currently used methods are examined. A generic metal-containing product is analyzed to demonstrate the vulnerability of results to the denominator utilized in calculating ADP. The adherence to the concept of the area of protection (AOP) is evaluated for current models. The use of ore grades, prices, and economic availability in LCIA is reviewed. Results demonstrate that any work on resource depletion in a life cycle context needs to have a very clear objective or LCIA will not accurately characterize mineral resource use from any perspective and decision-making will continue to suffer. New, harmonized terminology is proposed so that LCA practitioners can build better mutual understanding with the mineral industry and recommendations regarding more promising tools for use in life cycle sustainability assessment (LCSA) are given. The economic issue of resource availability should be evaluated in parallel with traditional LCA, not within. LCIA developers should look to economists, the market, and society in general, for broader assessments that consider shorter-time horizons than the traditional LCIA methods. To do so, the concept of the AOP in LCA needs to be redefined for LCSA to ensure that models estimate what is intended. Finally, recommendations regarding mineral resource assessment are provided to ensure that future research has a sound basis and practitioners can incorporate the appropriate tools in their work.

/pdf/mineral-resources-in-life-cycle-impact-assessment-defining-32gha9duoa.pdf

Mineral resources in life cycle impact assessment—defining the path forward

Does material circularity rhyme with environmental efficiency? Case studies on used tires

Purpose The safeguard subject of the Area of Protection "natural Resources," particularly regarding mineral resources, has long been debated. Consequently, a variety of life cycle impact assessment methods based on different concepts are available. The Life Cycle Initiative, hosted by the UN Environment, established an expert task force on "Mineral Resources" to review existing methods (this article) and provide guidance for application-dependent use of the methods and recommendations for further methodological development (Berger et al. in Int J Life Cycle Assess, 2020). Methods Starting in 2017, the task force developed a white paper, which served as its main input to a SETAC Pellston Workshop (R) in June 2018, in which a sub-group of the task force members developed recommendations for assessing impacts of mineral resource use in LCA. This article, based mainly on the white paper and pre-workshop discussions, presents a thorough review of 27 different life cycle impact assessment methods for mineral resource use in the "natural resources" area of protection. The methods are categorized according to their basic impact mechanisms, described and compared, and assessed against a comprehensive set of criteria. Results and discussion Four method categories have been identified and their underlying concepts are described based on existing literature: depletion methods, future efforts methods, thermodynamic accounting methods, and supply risk methods. While we consider depletion and future efforts methods more "traditional" life cycle impact assessment methods, thermodynamic accounting and supply risk methods are rather providing complementary information. Within each method category, differences between methods are discussed in detail, which allows for further sub-categorization and better understanding of what the methods actually assess. Conclusions We provide a thorough review of existing life cycle impact assessment methods addressing impacts of mineral resource use, covering a broad overview of basic impact mechanisms to a detailed discussion of method-specific modeling. This supports a better understanding of what the methods actually assess and highlights their strengths and limitations. Building on these insights, Berger et al. (Int J Life Cycle Assess, 2020) provide recommendations for application-dependent use of the methods, along with recommendations for further methodological development.

/pdf/mineral-resources-in-life-cycle-impact-assessment-part-i-a-2jy9v0s65f.pdf

Mineral resources in life cycle impact assessment—part I: a critical review of existing methods

Assessing impacts of abiotic resource use has been a topic of
persistent debate among life cycle impact assessment (LCIA) method developers
and a source of confusion for life cycle assessment (LCA) practitioners
considering the different interpretations of the safeguard subject for mineral
resources and the resulting variety of LCIA methods to choose from. Based on the
review and assessment of 27 existing LCIA methods, accomplished in the first
part of this paper series (Sonderegger et al. 2020), this paper provides recommendations regarding the
application-dependent use of existing methods and areas for future method
development. Within the “global guidance for LCIA indicators and
methods” project of the Life Cycle Initiative hosted by UN Environment,
62 members of the “task force mineral resources” representing
different stakeholders discussed the strengths and limitations of existing LCIA
methods and developed initial conclusions. These were used by a subgroup of
eight members at the Pellston Workshop® held in Valencia, Spain, to
derive recommendations on the application-dependent use and future development
of impact assessment methods. First, the safeguard subject for mineral resources within the area
of protection (AoP) natural resources was defined. Subsequently, seven key
questions regarding the consequences of mineral resource use were formulated,
grouped into “inside-out” related questions (i.e., current
resource use leading to changes in opportunities for future users to use
resources) and “outside-in” related questions (i.e., potential
restrictions of resource availability for current resource users). Existing LCIA
methods were assigned to these questions, and seven methods
(ADPultimate reserves, SOPURR,
LIME2endpoint, CEENE, ADPeconomic reserves, ESSENZ, and GeoPolRisk) are recommended for use in
current LCA studies at different levels of recommendation. All 27 identified
LCIA methods were tested on an LCA case study of an electric vehicle, and
yielded divergent results due to their modeling of impact mechanisms that
address different questions related to mineral resource use. Besides
method-specific recommendations, we recommend that all methods increase the
number of minerals covered, regularly update their characterization factors, and
consider the inclusion of secondary resources and anthropogenic stocks.
Furthermore, the concept of dissipative resource use should be defined and
integrated in future method developments. In an international consensus-finding process, the current
challenges of assessing impacts of resource use in LCA have been addressed by
defining the safeguard subject for mineral resources, formulating key questions
related to this safeguard subject, recommending existing LCIA methods in
relation to these questions, and highlighting areas for future method
development.

/pdf/mineral-resources-in-life-cycle-impact-assessment-part-ii-749crkbj7f.pdf

Mineral resources in life cycle impact assessment: part II – recommendations on application-dependent use of existing methods and on future method development needs

From a critical review to a conceptual framework for integrating the criticality of resources into Life Cycle Sustainability Assessment

The significance of product design in the circular economy: A sustainable approach to the design of data centre equipment as demonstrated via the CEDaCI design case study

Nowadays, product designers, manufacturers, and consumers consider the environmental impacts of products, processes, and services in their decision-making process. Life Cycle Assessment (LCA) is a tool that assesses the environmental impacts over a product’s life cycle. Conducting a life cycle assessment (LCA) requires meticulous data sourcing and collection and is often time-consuming for both practitioner and verifier. However, predicting the environmental impacts of products and services can help stakeholders and decision-makers identify the hotspots. Our work proposes using Artificial Intelligence (AI) techniques to predict the environmental performance of a product or service to assist LCA practitioners and verifiers. This approach uses data from environmental product declarations of construction products. The data is processed utilizing natural language processing (NLP) which is then trained to random forest algorithm, an ensemble tree-based machine learning method. Finally, we trained the model with information on the product and their environmental impacts using seven impact category values and verified the results using a testing dataset (20% of EPD data). Our results demonstrate that the model was able to predict the values of impact categories: global warming potential, abiotic depletion potential for fossil resources, acidification potential, and photochemical ozone creation potential with an accuracy (measured using R2 metrics, a measure to score the correlation of predicted values to real value) of 81%, 77%, 68%, and 70%, respectively. Our method demonstrates the capability to predict environmental performance with a defined variability by learning from the results of the previous LCA studies. The model’s performance also depends on the amount of data available for training. However, this approach does not replace a detailed LCA but is rather a quick prediction and assistance to LCA practitioners and verifiers in realizing an LCA.

https://www.mdpi.com/2071-1050/14/6/3699/pdf?version=1647871367

Implementing Artificial Intelligence Techniques to Predict Environmental Impacts: Case of Construction Products

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From a critical review to a conceptual framework for integrating the criticality of resources into Life Cycle Sustainability Assessment

The significance of product design in the circular economy: A sustainable approach to the design of data centre equipment as demonstrated via the CEDaCI design case study

Implementing Artificial Intelligence Techniques to Predict Environmental Impacts: Case of Construction Products