A global review of factors influencing decision-making on landfill mining and composition of mined residues

Landfill mining (LFM) has gained momentum worldwide as a strategy to remediate legacy landfills ( LeLa s). Despite growing global interest, a systematic understanding of the factors guiding LFM suitability and composition of landfill mined residues (LMRs) has been meagre. Whether a LeLa is considered suitable for LFM depends on factors, including motivations for LFM, environmental impacts, economic impacts, the usability of LMRs, and the availability of alternative remediation strategies. Our review shows that LFM projects and studies worldwide are primarily driven by environmental remediation and resource recovery, with these motivations accounting for 34% and 25%, respectively. Key motivations in developing countries are less diverse than in developed countries, largely due to the severe environmental impacts caused by dumpsites in former setups. The availability of alternative remediation strategies could act in favour of or opposition to mining a landfill and is discussed for case studies in India and Estonia. The composition of LMRs, which is relevant to evaluating environmental and economic impacts, varies from one project to another. Based on data from 73 LeLa s, age and depth of LMRs, geographical location, and income levels are identified as major factors influencing the composition of LMRs. Regardless of these factor dependencies, landfill-mined-soil-like-fraction is the major fraction (accounting for 35% and 75%) of LMRs. These findings support estimating material stocks in LeLa s and prospective material flows from field-scale projects as a basis for developing effective LFM strategies. The novelty of this review includes (i) the first systematic distinction between major LFM motivations in developed and developing countries, and (ii) the first global quantification of LMRs’ composition dependencies on-site-specific factors (age and depth) and system-specific factors (geographical settings and income level). Overall, these insights establish a strong empirical basis for assessing LFM feasibility and supporting informed decision-making.