Characterizing land use effect on shallow groundwater contamination by using self-organizing map and buffer zone

Self-organizing map algorithm for assessing spatial and temporal patterns of pollutants in environmental compartments: A review

The evaluation of the spatial and temporal distribution of pollutants is a crucial issue to assess the anthropogenic burden on the environment. Numerous chemometric approaches are available for data exploration and they have been applied for environmental health assessment purposes. Among the unsupervised methods, Self-Organizing Map (SOM) is an artificial neural network able to handle non-linear problems that can be used for exploratory data analysis, pattern recognition, and variable relationship assessment. Much more interpretation ability is gained when the SOM-based model is merged with clustering algorithms. This review comprises: (i) a description of the algorithm operation principle with a focus on the key parameters used for the SOM initialization; (ii) a description of the SOM output features and how they can be used for data mining; (iii) a list of available software tools for performing calculations; (iv) an overview of the SOM application for obtaining spatial and temporal pollution patterns in the environmental compartments with focus on model training and result visualization; (v) advice on reporting SOM model details in a paper to attain comparability and reproducibility among published papers as well as advice for extracting valuable information from the model results is presented.

Microencapsulated reactor for simultaneous removal of calcium, fluoride and phenol using microbially induced calcium precipitation: Mechanism and functional characterization

Fluoride ions (F^-) and phenol in groundwater have become a great hurdle to the pursuit of a healthy drinking water source. This study established a microencapsulated immobilization reactor with Aquabacterium sp. CZ3 for the simultaneous removal of nitrate (NO₃^--N), calcium (Ca²⁺), F^-, and phenol from groundwater with 100%, 67.84%, 88.67%, and 100% removal efficiencies, respectively. The three-dimensional mesh structure of microcapsules facilitated the transport and metabolism of substances, while their synergistic effect with bacteria promoted the removal of contaminants. F^- was removed by co-precipitation to generate Ca₅(PO₄)₃F and CaF₂ and adsorption. On one hand, the phenol toxicity promoted the production of extracellular polymers and improved the tolerance of bacteria; on the other hand, the degradation of phenol provided a carbon source for bacteria and promoted the denitrification. The development of microencapsulated immobilized reactor provided a clear mechanism for phenol and F^- removal under the microbially induced calcium precipitation (MICP) technique, while providing a valuable solution for the treatment of complex groundwater resources.

Comprehensive assessment of the impact of land use and hydrogeological properties on the groundwater quality in Taiwan using factor and cluster analyses

This study aims at making a comprehensive assessment of the impact of land use and the hydrogeological properties on groundwater quality. First, factor analysis (FA) is applied to reveal the main pollutant sources and hydrogeological processes controlling the groundwater quality. FA identifies the four most important factors. Factor 1 (seawater salinization) is characterized by a medium loading of land use type of aquaculture. It is recognized that the high scores for factor 1 in coastal areas are due to over-pumping from aquafarms. Focused land use management is required to prevent saline-water intrusion in coastal aquifers. Factor 3 (nitrate pollution) shows high correlations with the land use type of fruit farming and the gravel thickness in unsaturated layers. High scores for factor 3 are also found in the proximal area of the Chuoshui River Alluvial Fan and the northeastern mountain area in the Pingtung Plain. Fruit farmers should be educated to reduce the application of fertilizers and promote the organic fruit farming. The impacts of land use and the hydrogeological properties on both Factor 2 (arsenic enrichment) and Factor 4 (reductive dissolution of Fe²⁺ and Mn²⁺) are negligible. Second, cluster analysis (CA) is performed on computed scores of the four main factors to separates 123 monitoring wells into cluster 1 (low polluted zone), cluster 2 (nitrate polluted zone) and cluster 3 (hybrid polluted zone). The results obtained from CA provide practical applications such as reduce agrichemical use in the areas of cluster 2 and enforce intensive monitoring in the prioritizing areas of cluster 3. This study successively uses the FA and CA to extract the meaningful information present by geographical visualization of scores for 4 main factors and 3 distinct clusters zones. The results are essential for formulating sound groundwater resource and land use management policies to ensure groundwater sustainability.