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Record W4293282418 · doi:10.1016/j.ecoleng.2022.106740

Challenges and avenues for acid mine drainage treatment, beneficiation, and valorisation in circular economy: A review

2022· review· en· W4293282418 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEcological Engineering · 2022
Typereview
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsnot available
FundersUniversity of South AfricaCouncil of Scientific and Industrial Research, IndiaUniversity of the Witwatersrand, Johannesburg
KeywordsBeneficiationAcid mine drainageValorisationCircular economyWaste managementEnvironmental scienceReuseDredgingLand reclamationResource recoveryEnvironmental engineeringEnvironmental protectionEngineeringWastewaterGeologyChemistryGeography

Abstract

fetched live from OpenAlex

Mining activities are notorious for their environmental impact, with acid mine drainage (AMD) being among the most significant issues. Specifically, AMD has recently been a topical issue of prime concern, primarily due to the magnitude of its environmental, ecotoxicological, and socioeconomic impacts. AMD originates from both active and abandoned mines (primarily gold and coal) and is encountered in Canada, China, Russia, South Africa, USA, and other countries with strong mining industry. Owing to its acidity, AMD contains elevated levels of dissolved (toxic) metals, metalloids, rare-earth elements, radionuclides, and sulfates. Practical and cost-effective solutions to prevent its formation are still pending, while for its treatment active (driven by frequent input of chemicals and energy) or passive (based on oxidation/reduction) technologies are typically employed with the first being more efficient in contaminants removal, however, at the expense of process complexity, cost, and materials and energy consumption. More recently, and under the circular economy concept, hybrid (combination of active and passive technologies) and particularly integrated (sequential or stepwise treatment) systems have been explored for AMD beneficiation and valorisation. These systems are costly to install and operate but are cleaner production systems since they can effectively prevent pollution and can be used for closed-loop and sustainable AMD management (e.g., zero liquid discharge (ZLD) systems). Herein, the body of knowledge on AMD treatment, beneficiation (metals/minerals recovery), valorisation (water reclamation), and life cycle assessment (LCA) is comprehensively reviewed and discussed, with focus placed on circular economy. Future research directions to introduce reuse, recycle, and resource recovery paradigms in wastewater treatment and to inspire innovation in valorising this toxic and hazardous effluent are also provided. Overall, AMD beneficiation and valorisation appears promising since the reclaimed water and the recovered minerals/metals could offset treatment costs and environmental impacts. However, the main challenges include high-cost, complexity, co-contamination in the recovered minerals, and the generation of a higly heterogeneous and mineralised sludge.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.277
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it