Systematic Risks\nof the Global Lithium Supply Chain\nNetwork: From Static Topological Structures to Cascading Failure Dynamics

Recent years have seen increasing concerns on supply\nchain risks\nof lithium, a critical material for achieving e-mobility transition\nand climate ambitions. These risks propagate both along the life cycle\nand across national boundaries in a multilayer network. However, most\nprevious studies are either only based on static network measures\nor focused on individual layers, ignoring dynamic cascading risks\nand interconnected and interdependent relationships along life cycle\nstages and across economies. Here, we integrated trade-linked material\nflow and complex network analyses to investigate intricate interconnections,\ninterdependencies, and systematic risks of the global lithium supply\nchain. Both static and dynamic measures of the global lithium supply\nchain network exhibit a “robust-yet-fragile” property:\nrobust for random shocks yet fragile for targeted shocks and robust\nfor small or local disruptions yet fragile for large or cascading\nfailures. Portugal, Brazil, Singapore, Canada, Finland, Norway, South\nAfrica, Israel, Hungary, and the United Arab Emirates are most likely\nto be affected by supply disruptions. A hypothetical USA-China trade\ndecoupling will increase the severity and susceptibility of network-wide\nfailures by around 5%. Our results call for global collaborations\nand collective efforts to balance efficiency and security and avoid\na “zero-sum game” in securing the lithium supply chain.

Publication Details

Journal
Figshare
Published
2024-12-06
DOI
https://doi.org/10.1021/acs.est.4c10523.s001
Primary Topic
Extraction and Separation Processes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Systematic Risks\nof the Global Lithium Supply Chain\nNetwork: From Static Topological Structures to Cascading Failure Dynamics

Figshare
Extraction and Separation Processes
article

Systematic Risks\nof the Global Lithium Supply Chain\nNetwork: From Static Topological Structures to Cascading Failure Dynamics

article en

Abstract

Recent years have seen increasing concerns on supply\nchain risks\nof lithium, a critical material for achieving e-mobility transition\nand climate ambitions. These risks propagate both along the life cycle\nand across national boundaries in a multilayer network. However, most\nprevious studies are either only based on static network measures\nor focused on individual layers, ignoring dynamic cascading risks\nand interconnected and interdependent relationships along life cycle\nstages and across economies. Here, we integrated trade-linked material\nflow and complex network analyses to investigate intricate interconnections,\ninterdependencies, and systematic risks of the global lithium supply\nchain. Both static and dynamic measures of the global lithium supply\nchain network exhibit a “robust-yet-fragile” property:\nrobust for random shocks yet fragile for targeted shocks and robust\nfor small or local disruptions yet fragile for large or cascading\nfailures. Portugal, Brazil, Singapore, Canada, Finland, Norway, South\nAfrica, Israel, Hungary, and the United Arab Emirates are most likely\nto be affected by supply disruptions. A hypothetical USA-China trade\ndecoupling will increase the severity and susceptibility of network-wide\nfailures by around 5%. Our results call for global collaborations\nand collective efforts to balance efficiency and security and avoid\na “zero-sum game” in securing the lithium supply chain.

Figshare
Responsible consumption and production
Openalex Percentile: Top 68%
Extraction and Separation Processes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.