Processed Batch Experiment Dataset for Metal Immobilization from Actual Acid Mine Drainage Using Cow-Derived Biochar: Synthesis, Characterization, and Treatment Performance
Description
This Mendeley Data repository contains the raw and processed batch experiment dataset generated to test the hypothesis that cow-derived biochar can effectively immobilise dissolved metals in actual acid mine drainage (AMD) under controlled laboratory conditions. The dataset is organised into clearly defined directories that reflect successive stages of data generation, processing, and interpretation, enabling transparent reuse and reproducibility. Raw Data (Batch Experiment and Physicochemical Measurements) The Raw_Data directory contains the original analytical outputs generated during batch treatment experiments using untreated AMD and cow-derived biochar. These files include ICP-OES measurements of dissolved metal concentrations, recorded in triplicate to assess analytical precision, along with associated physicochemical parameters such as pH and electrical conductivity. These data represent the unprocessed experimental observations and form the basis for all subsequent calculations. Users may reuse these files to apply alternative statistical analyses, adsorption models, or kinetic interpretations without reliance on pre-computed results. Processed Data (Calculated Removal Efficiencies and Summary Tables) The Processed_Data directory contains derived datasets generated from the raw measurements, including mean metal concentrations, standard deviations, and percentage removal or immobilisation efficiencies. These processed tables describe the treatment performance of cow-derived biochar across experimental conditions and provide benchmark values for comparison with other remediation materials. While these summaries facilitate rapid interpretation, all calculations are traceable to the raw data to allow independent verification. Metadata and Experimental Context The Metadata directory provides structured contextual information ensuring that secondary users can correctly interpret the dataset, reproduce the experimental setup where needed, and integrate the data into comparative or meta-analytical studies.
Files
Steps to reproduce
Water samples were collected as grab samples from gold- and coal mine‐impacted dams using clean, acid-washed containers and transported to the laboratory under chilled conditions (4 °C). Upon arrival, samples were filtered through 0.45 µm membrane filters to remove suspended solids, followed by preservation through acidification (pH < 2) with analytical grade nitric acid prior to chemical analysis. Physicochemical parameters, including pH and electrical conductivity, were measured using a HANNA multiparameter probe calibrated according to the manufacturer’s guidelines. Dissolved metal concentrations were quantified by inductively coupled plasma–optical emission spectroscopy (ICP-OES) using external calibration with certified multi-element standards. Each sample was analysed in triplicate, and results were reported as mean ± standard deviation to assess analytical precision. Cow-derived biochar was produced via controlled pyrolysis and characterised for key physicochemical properties, including pH, ash content, and elemental composition, prior to use in batch experiments. Batch immobilisation experiments were conducted by equilibrating measured masses of biochar with defined volumes of untreated acid mine drainage in sealed reaction vessels under constant agitation at room temperature. Contact time, solid-to-liquid ratio, and experimental conditions were kept consistent across treatments. Following equilibration, suspensions were filtered, and residual metal concentrations were measured by ICP OES using the same analytical workflow as described above. Raw analytical outputs were compiled into structured spreadsheets. Processed datasets, including calculated metal removal efficiencies and summary statistics, were derived directly from the raw measurements using standard spreadsheet software and verified through independent recalculation. All processed outputs were organised into clearly labelled directories corresponding to raw data, processed data, biochar characterisation, and metadata. To reproduce the dataset, users should collect representative AMD samples; perform physicochemical and ICP OES analyses using equivalent instrumentation and calibration procedures; prepare cow-derived biochar following standard pyrolysis protocols; conduct batch immobilisation experiments under controlled conditions; and process the resulting analytical data using the same statistical and organisational workflow outlined above.
Institutions
- University of South AfricaGauteng, Pretoria