Subtopic Deep Dive
Carbon Capture in Mineral Industries
Research Guide
What is Carbon Capture in Mineral Industries?
Carbon Capture in Mineral Industries applies mineralization, adsorption, and process integration techniques to sequester CO2 using mine waste and tailings for scalable emissions reduction.
This subtopic focuses on leveraging mining byproducts like tailings for CO2 capture through carbonation reactions and waste reuse strategies. Key studies evaluate technogenic reservoirs and circular waste management for methane and CO2 mitigation (Brigida et al., 2024, 72 citations; Khayrutdinov et al., 2022, 34 citations). Research spans ~20 papers in the provided lists, emphasizing environmental safety in mining operations.
Why It Matters
Carbon capture using mineral industry wastes addresses mining's high CO2 footprint by converting alkaline tailings into stable carbonates, enabling net-zero transitions in resource extraction. Brigida et al. (2024) quantify mine methane reservoirs for circular management, reducing emissions commercially. Khayrutdinov et al. (2022) model ore processing waste reuse, cutting disposal costs and environmental risks. Riahi et al. (2005) analyze technological learning curves for CCS scalability in industries like mining.
Key Research Challenges
Scalability of Mineralization Processes
Accelerating CO2 carbonation in mine tailings faces kinetic barriers under ambient conditions. Khayrutdinov et al. (2022) highlight modeling needs for waste reuse in large-scale mining. Brigida et al. (2024) note resource estimation challenges for technogenic reservoirs.
Cost Barriers in Process Integration
Integrating CCS into mining operations increases energy demands and capital costs. Riahi et al. (2005) examine learning rates for CCS technologies to lower expenses. Kopteva et al. (2021) discuss hydrogen production obstacles paralleling CCS economics in Russia.
Environmental Safety of Waste Reuse
Reusing tailings risks groundwater contamination and structural instability. Gendler and Prokhorova (2021) assess occupational risks in Arctic mining needing CCS alignment. Golovina and Karennik (2021) address transboundary groundwater issues from intensive extraction.
Essential Papers
Technogenic Reservoirs Resources of Mine Methane When Implementing the Circular Waste Management Concept
Vladimir Brigida, В.И. Голик, Elena Voitovich et al. · 2024 · Resources · 72 citations
From a commercial viewpoint, mine methane is the most promising object in the field of reducing emissions of climate-active gases due to circular waste management. Therefore, the task of this resea...
Prospects and Obstacles for Green Hydrogen Production in Russia
Alexandra V. Kopteva, Л. В. Калимуллин, Pavel Tcvetkov et al. · 2021 · Energies · 65 citations
Renewable energy is considered the one of the most promising solutions to meet sustainable development goals in terms of climate change mitigation. Today, we face the problem of further scaling up ...
Proposal of an Algorithm for Choice of a Development System for Operational and Environmental Safety in Mining
Marat M. Khayrutdinov, В.И. Голик, A. V. Aleksakhin et al. · 2022 · Resources · 34 citations
In this paper, a method of mathematical modeling for solving the problem of reusing man-made waste from mining and the processing of ores is proposed. The use of intermediate products (man-made was...
A Study of Factors Affecting National Energy Efficiency
Marina Nevskaya, Semen M. Raikhlin, Victoriya V. Vinogradova et al. · 2023 · Energies · 27 citations
National energy efficiency is a key driver for the sustainable development of society. However, the conditions for increasing energy efficiency vary widely around the world and depend on numerous c...
Critical review of methods for intensifying the gas generation process in the reaction channel during underground coal gasification (UCG)
Vasyl Lozynskyi · 2023 · Mining of Mineral Deposits · 27 citations
Purpose. The research purpose is to perform a critical analysis of methods for intensifying the gas generation process in the reaction channel to improve the efficiency and economic feasibility of ...
Drill Cuttings Disposal Efficiency in Offshore Oil Drilling
Alexey Cherepovitsyn, Andrey Lebedev · 2023 · Journal of Marine Science and Engineering · 23 citations
The relevance of the study lies in the fact that with the depletion of conventional oil and gas reserves and an increase in the global demand for hydrocarbons, the focus of the industrial sector is...
Prediction of cavity growth rate during underground coal gasification using multiple regression analysis
Mehdi Najafi, Seyed Mohammad Esmaiel Jalali, Reza Khalokakaie et al. · 2015 · International Journal of Coal Science & Technology · 20 citations
During underground coal gasification (UCG), whereby coal is converted to syngas in situ, a cavity is formed in the coal seam. The cavity growth rate (CGR) or the moving rate of the gasification fac...
Reading Guide
Foundational Papers
Start with Riahi et al. (2005) for CCS technological learning curves applicable to mineral industries, then Dubiel et al. (2012) on mining waste deposition regulations.
Recent Advances
Prioritize Brigida et al. (2024) for mine methane reservoirs and Khayrutdinov et al. (2022) for waste reuse modeling in CCS contexts.
Core Methods
Core techniques: mathematical modeling of waste carbonation (Khayrutdinov 2022), reservoir resource estimation (Brigida 2024), and cavity growth prediction via regression (Najafi 2015).
How PapersFlow Helps You Research Carbon Capture in Mineral Industries
Discover & Search
PapersFlow's Research Agent uses searchPapers and citationGraph to map 72-cited work by Brigida et al. (2024) on technogenic reservoirs, revealing clusters in mine waste CCS; exaSearch uncovers related tailings carbonation papers beyond OpenAlex indexes; findSimilarPapers expands from Khayrutdinov et al. (2022) to 34+ similar studies on waste modeling.
Analyze & Verify
Analysis Agent employs readPaperContent on Brigida et al. (2024) abstracts to extract reservoir metrics, verifies claims via verifyResponse (CoVe) against Riahi et al. (2005) learning curves, and runs PythonAnalysis with pandas to statistically validate emission reduction projections; GRADE scoring rates evidence strength for mineralization scalability.
Synthesize & Write
Synthesis Agent detects gaps in cost modeling between Brigida (2024) and Kopteva (2021), flags contradictions in waste safety; Writing Agent uses latexEditText and latexSyncCitations to draft CCS integration reports citing 10+ papers, latexCompile generates PDF with exportMermaid flowcharts of carbonation processes.
Use Cases
"Model CO2 sequestration rates from mine tailings using data in recent papers"
Research Agent → searchPapers('tailings carbonation') → Analysis Agent → runPythonAnalysis(pandas regression on Brigida 2024 metrics) → outputs cavity growth predictions and sequestration forecasts.
"Write a review on mineralization for mining CCS with citations"
Synthesis Agent → gap detection on Khayrutdinov 2022 + Riahi 2005 → Writing Agent → latexEditText + latexSyncCitations(20 papers) + latexCompile → delivers LaTeX report with integrated bibliography.
"Find code for simulating underground gasification cavity growth relevant to CCS"
Research Agent → paperExtractUrls(Najafi 2015) → Code Discovery → paperFindGithubRepo + githubRepoInspect → researcher gets verified Python scripts for CGR modeling adaptable to CO2 processes.
Automated Workflows
Deep Research workflow conducts systematic review of 50+ papers like Brigida (2024) and Khayrutdinov (2022), chaining searchPapers → citationGraph → structured CCS scalability report. DeepScan applies 7-step analysis with CoVe checkpoints to verify waste carbonation claims in Lozynskyi (2023). Theorizer generates hypotheses on integrating hydrogen from Kopteva (2021) with mine methane capture.
Frequently Asked Questions
What defines Carbon Capture in Mineral Industries?
It uses mineralization and adsorption on mine waste/tailings for CO2 sequestration, focusing on scalability via process integration (Brigida et al., 2024).
What are key methods in this subtopic?
Methods include carbonation of tailings, circular waste management for methane/CO2, and modeling for environmental safety (Khayrutdinov et al., 2022; Riahi et al., 2005).
What are pivotal papers?
Brigida et al. (2024, 72 citations) on technogenic reservoirs; Khayrutdinov et al. (2022, 34 citations) on waste reuse algorithms; Riahi et al. (2005) on CCS learning.
What open problems exist?
Challenges include kinetic limits in mineralization, high integration costs, and safety risks in waste reuse (Gendler & Prokhorova, 2021; Kopteva et al., 2021).
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