Application of a Fuzzy Logic Based Methodology to Validate the Hydrochemical Characterization and Determining Seasonal Influence of a Watershed Affected by Acid Mine Drainage

Chemical composition of arsenic-based acid mine drainage in the downstream of a gold mine: Fuzzy regression and clustering analysis

This study employs fuzzy regression and fuzzy multivariate clustering techniques to analyze arsenic-polluted water samples originating from acid rock drainage in waste rock dumps. The research focuses on understanding the complex relationships between variables associated with arsenic contamination, such as water arsenic concentration, pH levels, and soil characteristics. To this end, fuzzy regression models were developed to estimate the relationships between water arsenic concentration and independent variables, thus, incorporating the inherent uncertainties into the analysis. Furthermore, multivariate fuzzy k-means clustering analysis facilitated the identification of fuzzy-based clusters within the dataset, providing insights into spatial patterns and potential sources of arsenic pollution. The pairwise comparisons indicated the strongest correlation of 0.62 between soil total arsenic and pH, while the weakest correlation of 0.13 was observed between soil-soluble arsenic and soil iron, providing valuable insights into their relationships and impact on water arsenic levels. The associated uncertainties in the relationships among the variables were determined based on the degree of belongingness of each data point to various fuzzy sets. Three distinct clusters emerged from the analysis: Cluster 1 comprised Points 5, 6, and 7; Cluster 2 included Points 1, 2, 3, 4, 8, and 9; and Cluster 3 consisted of Points 10, 11, 12, and 13. The findings enhance our understanding of the factors influencing arsenic contamination to provide an effective mitigation strategy in acid rock drainage scenarios. This research also demonstrates the applicability and effectiveness of fuzzy regression and fuzzy multivariate clustering in the analysis of arsenic-polluted water samples.

Identifying sources of acid mine drainage and major hydrogeochemical processes in abandoned mine adits (Southeast Shaanxi, China)

Acid mine drainage (AMD) has resulted in significant risks to both human health and the environment of the Han River watershed. In this study, water and sediment samples from typical mine adits were selected to investigate the hydrogeochemical characteristics and assess the environmental impacts of AMD. The interactions between coexisting chemical factors, geochemical processes in the mine adit, and the causes of AMD formation are discussed based on statistical analysis, mineralogical analysis, and geochemical modeling. The results showed that the hydrochemical types of AMD consisted of SO4-Ca-Mg, SO4-Ca, and SO4-Mg, with low pH and extremely high concentrations of Fe and SO42-. The release behaviors of most heavy metals are controlled by the oxidation of sulfide minerals (mainly pyrite) and the dissolution/precipitation of secondary minerals. Along the AMD pathway in the adit, the species of Fe-hydroxy secondary minerals tend to initially increase and later decrease. The inverse model results indicated that (1) oxidative dissolution of sulfide minerals, (2) interconversion of Fe-hydroxy secondary minerals, (3) precipitation of gypsum, and (4) neutralization by calcite are the main geochemical reactions in the adit, and chlorite might be the major neutralizing mineral of AMD with calcite. Furthermore, there were two sources of AMD in abandoned mine adits: oxidation of pyrite within the adits and infiltration of AMD from the overlying waste rock dumps. The findings can provide deeper insight into hydrogeochemical processes and the formation of AMD contamination produced in abandoned mine adits under similar mining and hydrogeological conditions.

Temporal evolution of acid mine drainage (AMD) leachates from the abandoned tharsis mine (Iberian Pyrite Belt, Spain)

Acid mine drainage (AMD) due to the mining of sulfide deposits is one of the most important causes of water pollution worldwide. Remediation measures, especially in historical abandoned mines, require a deep knowledge of the geochemical characteristics of AMD effluents and metal fluxes, considering their high spatial and temporal evolution, and the existence of point and diffuse sources with a different response to rainfall events. This study investigates the temporal variations and hydrogeochemical processes affecting the composition of main AMD sources from the Tharsis mines (SW Spain), one of most important historical metal mining districts in the world. To address this, a fortnightly-monthly sampling was performed during two years in the main AMD sources and streams within the mine site covering different hydrological conditions. A seasonal pattern was observed linked to hydrological variations; higher pollutant concentrations were observed during the dry season (maximum values of 4,6 g/L of Al, 11,8 g/L of Fe, and 67 g/L of sulfate) and lower ones were observed during the rainy periods. Stream samples exhibited a negative correlation between electrical conductivity (EC) and flow, while positive values were observed in AMD sources, where groundwater fluxes were predominant. High flow also seems to be the main driver of Pb fluxes from AMD sources, as the concentration of Pb in waters increased notably during these events. The precipitation of secondary Fe minerals may limit the mobility of As and V, being retained in the proximity of mine sites. The concentration of Zn in waters seems to be controlled by the original grade in the metal deposit from which the waste is generated, together with the age of these wastes. The pollutant load delivered by the Tharsis mines to the surrounding water courses is very high; e.g., mean of 733 ton/yr of Al or 2757 ton/yr of Fe, deteriorating the streams and reservoirs downstream.