--- title: "Geochemistry – Part II: Predicting metal leaching and acid rock drainage (ML/ARD) chemistry" date: 2024-05-01T11:19:00-04:00 author: jessica napert canonical_url: "https://www.bbaconsultants.com/en-ca/publications/geochemistry-part-ii-predicting-metal-leaching-and-acid-rock-drainage-ml-ard-chemistry" section: Publications --- As discussed in detail in the previous article entitled **“[Geochemistry Part I: What is metal leaching and acid rock drainage (ML/ARD), and how does it occur?](https://www.bbaconsultants.com/en-ca/publications/geochemistry-part-i-what-is-metal-leaching-and-acid-rock-drainage-ml-ard-and-how-does-it-occur)”**, ML/ARD starts with the production of acidic waters, often stemming from improperly managing sulphidic mine materials (i.e., waste rock, tailings, ore, etc.). Acidic waters can dissolve and transport heavy metals, such as copper (Cu), lead (Pb) and zinc (Zn), which are toxic to plant and animal life in high concentrations. 1. While the environmental impacts can be devastating, very costly and difficult to remediate, a scientific and multidisciplinary approach can be used to predict ML/ARD chemistry. With effective predictions, solutions can be engineered to manage and prevent ML/ARD from occurring in the first place, thereby protecting the environment, and potentially saving mining companies several millions of dollars in environmental liabilities. A summary of the common methods and analytical techniques used in predicting ML/ARD chemistry is presented in Figure 1. These methods and techniques can be classified within the following general approaches to prediction: - Static testing - Kinetic testing - Model predictions - Iterative data review 2. [ ![Figure 1: Summary of the common methods and analytical techniques used to guide the prediction of ML/ARD chemistry.](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/Figure-1_image-cms_geochemistry-part-2_EN_2024-04-30-142201_llxd.png) Figure 1: Summary of the common methods and analytical techniques used to guide the prediction of ML/ARD chemistry. ](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/Figure-1_image-cms_geochemistry-part-2_EN_2024-04-30-142201_llxd.png) 3. ## Static testing Static tests are used to quantify fundamental geochemical parameters (i.e., metal concentration, mineralogy, risk of acid generation, etc.). These tests serve as an excellent first step to assess the ML/ARD risk caused by an abundance of information, a relatively short testing period and relatively low costs. However, while static tests are integral for prediction, they do not provide any information concerning the rate of weathering reactions, which will determine actual risk of ML/ARD on site and in the field. - Acid-base accounting (ABA) – Analyses and calculations used to assess the risk of acid generation from the oxidation of sulphide minerals. ABA quantifies the acid potential (AP) and the neutralizing potential (NP) of a sample material. Based on the determination of AP and NP, a sample is classified as potentially acid generating (PAG) or non-potentially acid generating (NPAG). - Bulk chemistry analysis – An elemental analysis used to screen samples for substantial enrichment in particular metals or elements by comparative analysis with background concentrations (i.e., average crustal abundances). - Shake flask extraction (SFE) – A solubility test procedure whereby solid material is agitated with water for a given duration. The SFE method is used to determine the stored concentration of metals and elements in the extracted water. - Mineralogical analysis – Analytical techniques such as Reitveld X-ray diffraction (XRD) and quantitative evaluation of materials by scanning electron microscopy (QEMSCAN) are used to quantify minerals contributing to AP, NP and elements of concern. These techniques may also provide insight into mineral grain size, shape and surface area exposure (reactivity). 4. ## Kinetic testing Kinetic tests are used to quantify the rates of metal leaching, acid generation and neutralization potential. These tests provide insight into the rates of natural weathering reactions, which more accurately predict the site-specific risk of ML/ARD. The rates derived from kinetic tests are also essential inputs for site-wide water quality model predictions required for project permitting. Kinetic tests often take a long time to complete (from several weeks to years), as chemical equilibrium must be attained to accurately quantify reaction rates. - Humidity cell tests (HCT) – Bench-scale laboratory testing used to simulate and quantify reaction leaching rates of waste rock or tailings under atmospheric weathering conditions. - Column leach tests – Bench-scale laboratory testing used to simulate and quantify leaching rates of covered and/or underwater waste rock or tailings disposal. - Field barrel tests (FBT) – Similar to HCT, reaction rates are simulated and quantified under atmospheric weathering conditions. However, FBT are employed directly at the mine development site with large quantities of material (hundreds of kg) per sample, and the natural climate conditions help provide more realistic predictions. 5. ## Model Predictions - Geochemical modelling – Model predictions with computer software, such as PHREEQC, use a combination of chemical thermodynamics and experimental results to provide insight into mineral-water interactions within aqueous environments. For example, modelling may be used to simulate the physicochemical conditions (e.g., temperature, pH, redox conditions, chemical composition) to assess the stability and dissolution of acid generating minerals in mine waste. 6. ## Iterative data review - Onsite data monitoring – Routine collection of data and analysis during mining operations provides iterative feedback and validates initial ML/ARD chemistry predictions. This allows for rapid identification, if engineering design is required. 7. ## Conclusions Effective ML/ARD prediction starts with early integration of geochemistry into the design of a mine development plan, beginning with the advanced exploration stages and sustaining geochemical practice through to the final mine closure stages. These predictions help guide the engineering design for mine waste and water management plans by understanding the environmental compliance risk and providing insight into design cost‑benefit analyses. As discussed, there are several tools available to support ML/ARD chemistry prediction. However, a well-rounded approach through static testing, kinetic testing and model predictions is required for confidence in such predictions. Moreover, iterative feedback from onsite monitoring throughout mining operations validates predictions and allows for early identification, if design modification is required. **This blog article was written in collaboration with Neal Sullivan.** This content is for general information purposes only. All rights reserved ©BBA 1. ![Mm employee men todd mccracken retouch web SQ LR BBA](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/avatars/_size_avatar/204324/mm_employee_men_todd-mccracken_retouch_web_SQ_LR_BBA.webp) Todd McCracken, P.Geo. Department Manager, Mining and Geology Read bio [ ](https://www.linkedin.com/in/todd-mccracken-921b6927/) **Todd McCracken has been leveraging 30+ years of expertise to secure resource estimation and economic studies,** reducing risks and maximizing the value of mining projects. **Key expertise and certifications** - Advanced economic studies (PEA, PFS, FS) and project optimization - Qualified Person under NI 43-101 and S-K 1300 - Project management and QA/QC programs - Associations: PGO, QOG, PEGNL **Major achievements:** Over 55 multi-commodity projects in more than 10 countries across the Americas, Europe, Asia and Africa, integrating advanced modelling and regulatory compliance. **Approach and added value:** Todd employs a methodical and cooperative strategy, combining regulatory compliance with comprehensive strategic analysis to safeguard investments, mitigate risks and maximize the value of mining ventures. - [ 27 Jul 2026 Mining and Metals Early tailings decisions shape long-term mine performance - ![Geraldine Cosset](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/avatars/_size_avatar/206707/Geraldine-Cosset.webp) - ![Jared Purdy](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/avatars/_size_avatar/212424/Jared-Purdy.webp) ](https://www.bbaconsultants.com/en-ca/insights/early-tailings-decisions-shape-long-term-mine-performance "Early tailings decisions shape long-term mine performance") - [ 02 Jul 2026 Mining and Metals Python: A key tool for data analysis in mineral processing - ![Charles Blais](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/avatars/_size_avatar/211197/Charles-Blais.webp) - ![Juan Pablo Vergara](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/avatars/_size_avatar/211266/Juan-Pablo-Vergara.webp) ](https://www.bbaconsultants.com/en-ca/insights/python-a-key-tool-for-data-analysis-in-mineral-processing "Python: A key tool for data analysis in mineral processing") - [ 19 Jun 2026 Mining and Metals Speed is earned early in projects - ![Mm employee men jean lheureux retouch web SQ LR BBA](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/avatars/_size_avatar/204266/mm_employee_men_jean-lheureux_retouch_web_SQ_LR_BBA.webp) - ![Mm employee men benoit richard retouch web SQ LR BBA](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/avatars/_size_avatar/203602/mm_employee_men_benoit-richard_retouch_web_SQ_LR_BBA.webp) ](https://www.bbaconsultants.com/en-ca/insights/speed-is-earned-early-in-projects "Speed is earned early in projects") - [ 17 Jun 2026 Industrial data platforms: building a solid foundation to optimize your operations - ![Pierre Boucher](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/avatars/_size_avatar/2671/Pierre-Boucher.webp) Pierre Boucher, P.Eng. Senior Engineer, Operational Technology and Infrastructure ](https://www.bbaconsultants.com/en-ca/insights/industrial-data-platforms-building-a-solid-foundation-to-optimize-your-operations "Industrial data platforms: building a solid foundation to optimize your operations") [ See all ](https://www.bbaconsultants.com/en-ca/insights "Go to Publications listing page") - [ 15 Apr 2024 Mining and Metals Geochemistry – Part I: What is metal leaching and acid rock drainage (ML/ARD), and how does it occur? - ![Mm employee men todd mccracken retouch web SQ LR BBA](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/avatars/_size_avatar/204324/mm_employee_men_todd-mccracken_retouch_web_SQ_LR_BBA.webp) Todd McCracken, P.Geo. Department Manager, Mining and Geology ](https://www.bbaconsultants.com/en-ca/publications/geochemistry-part-i-what-is-metal-leaching-and-acid-rock-drainage-ml-ard-and-how-does-it-occur "Geochemistry – Part I: What is metal leaching and acid rock drainage (ML/ARD), and how does it occur?") [ See all ](https://www.bbaconsultants.com/en-ca/insights) Let’s think it further together [ Contact us ](https://www.bbaconsultants.com/en-ca/contact) As discussed in detail in the previous article entitled **“[Geochemistry Part I: What is metal leaching and acid rock drainage (ML/ARD), and how does it occur?](https://www.bbaconsultants.com/en-ca/publications/geochemistry-part-i-what-is-metal-leaching-and-acid-rock-drainage-ml-ard-and-how-does-it-occur)”**, ML/ARD starts with the production of acidic waters, often stemming from improperly managing sulphidic mine materials (i.e., waste rock, tailings, ore, etc.). Acidic waters can dissolve and transport heavy metals, such as copper (Cu), lead (Pb) and zinc (Zn), which are toxic to plant and animal life in high concentrations. 1. While the environmental impacts can be devastating, very costly and difficult to remediate, a scientific and multidisciplinary approach can be used to predict ML/ARD chemistry. With effective predictions, solutions can be engineered to manage and prevent ML/ARD from occurring in the first place, thereby protecting the environment, and potentially saving mining companies several millions of dollars in environmental liabilities. A summary of the common methods and analytical techniques used in predicting ML/ARD chemistry is presented in Figure 1. These methods and techniques can be classified within the following general approaches to prediction: - Static testing - Kinetic testing - Model predictions - Iterative data review 2. [ ![Figure 1: Summary of the common methods and analytical techniques used to guide the prediction of ML/ARD chemistry.](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/Figure-1_image-cms_geochemistry-part-2_EN_2024-04-30-142201_llxd.png) Figure 1: Summary of the common methods and analytical techniques used to guide the prediction of ML/ARD chemistry. ](https://www.assets.bbaconsultants.com/bba-production-assets/production/images/Figure-1_image-cms_geochemistry-part-2_EN_2024-04-30-142201_llxd.png) 3. ## Static testing Static tests are used to quantify fundamental geochemical parameters (i.e., metal concentration, mineralogy, risk of acid generation, etc.). These tests serve as an excellent first step to assess the ML/ARD risk caused by an abundance of information, a relatively short testing period and relatively low costs. However, while static tests are integral for prediction, they do not provide any information concerning the rate of weathering reactions, which will determine actual risk of ML/ARD on site and in the field. - Acid-base accounting (ABA) – Analyses and calculations used to assess the risk of acid generation from the oxidation of sulphide minerals. ABA quantifies the acid potential (AP) and the neutralizing potential (NP) of a sample material. Based on the determination of AP and NP, a sample is classified as potentially acid generating (PAG) or non-potentially acid generating (NPAG). - Bulk chemistry analysis – An elemental analysis used to screen samples for substantial enrichment in particular metals or elements by comparative analysis with background concentrations (i.e., average crustal abundances). - Shake flask extraction (SFE) – A solubility test procedure whereby solid material is agitated with water for a given duration. The SFE method is used to determine the stored concentration of metals and elements in the extracted water. - Mineralogical analysis – Analytical techniques such as Reitveld X-ray diffraction (XRD) and quantitative evaluation of materials by scanning electron microscopy (QEMSCAN) are used to quantify minerals contributing to AP, NP and elements of concern. These techniques may also provide insight into mineral grain size, shape and surface area exposure (reactivity). 4. ## Kinetic testing Kinetic tests are used to quantify the rates of metal leaching, acid generation and neutralization potential. These tests provide insight into the rates of natural weathering reactions, which more accurately predict the site-specific risk of ML/ARD. The rates derived from kinetic tests are also essential inputs for site-wide water quality model predictions required for project permitting. Kinetic tests often take a long time to complete (from several weeks to years), as chemical equilibrium must be attained to accurately quantify reaction rates. - Humidity cell tests (HCT) – Bench-scale laboratory testing used to simulate and quantify reaction leaching rates of waste rock or tailings under atmospheric weathering conditions. - Column leach tests – Bench-scale laboratory testing used to simulate and quantify leaching rates of covered and/or underwater waste rock or tailings disposal. - Field barrel tests (FBT) – Similar to HCT, reaction rates are simulated and quantified under atmospheric weathering conditions. However, FBT are employed directly at the mine development site with large quantities of material (hundreds of kg) per sample, and the natural climate conditions help provide more realistic predictions. 5. ## Model Predictions - Geochemical modelling – Model predictions with computer software, such as PHREEQC, use a combination of chemical thermodynamics and experimental results to provide insight into mineral-water interactions within aqueous environments. For example, modelling may be used to simulate the physicochemical conditions (e.g., temperature, pH, redox conditions, chemical composition) to assess the stability and dissolution of acid generating minerals in mine waste. 6. ## Iterative data review - Onsite data monitoring – Routine collection of data and analysis during mining operations provides iterative feedback and validates initial ML/ARD chemistry predictions. This allows for rapid identification, if engineering design is required. 7. ## Conclusions Effective ML/ARD prediction starts with early integration of geochemistry into the design of a mine development plan, beginning with the advanced exploration stages and sustaining geochemical practice through to the final mine closure stages. These predictions help guide the engineering design for mine waste and water management plans by understanding the environmental compliance risk and providing insight into design cost‑benefit analyses. As discussed, there are several tools available to support ML/ARD chemistry prediction. However, a well-rounded approach through static testing, kinetic testing and model predictions is required for confidence in such predictions. Moreover, iterative feedback from onsite monitoring throughout mining operations validates predictions and allows for early identification, if design modification is required. **This blog article was written in collaboration with Neal Sullivan.** This content is for general information purposes only. All rights reserved ©BBA