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Related Experiment Video

Updated: Jun 17, 2026

TD-DFT Guided Advanced E-Eye Sensing Technique for On-site Quantification of Fe, Cr, F, and As in the Environmental, Biological, and Food Samples

TD-DFT Guided Advanced E-Eye Sensing Technique for On-site Quantification of Fe, Cr, F, and As in the Environmental, Biological, and Food Samples

Published on: September 19, 2025

Dynamic factor analysis for estimating ground water arsenic trends.

Yi-Ming Kuo¹, Fi-John Chang

¹Dep. of Design for Sustainable Environment, MingDao Univ., 369 Wen-Hua Rd., Peetow, Chang-Hua 52345, Taiwan, R.O.C.

Journal of Environmental Quality

|January 6, 2010

Summary

High arsenic in groundwater is linked to health issues. Dynamic Factor Analysis revealed rainfall and geochemical factors influence arsenic levels, suggesting surface water recharge can dilute contamination.

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Determination of Inorganic Arsenic in a Wide Range of Food Matrices using Hydride Generation - Atomic Absorption Spectrometry.

Determination of Inorganic Arsenic in a Wide Range of Food Matrices using Hydride Generation - Atomic Absorption Spectrometry.

Published on: September 1, 2017

Area of Science:

Environmental Science
Hydrogeology
Public Health

Background:

Groundwater arsenic (As) contamination is a significant environmental and health concern, particularly along Taiwan's southwestern coast, where it's linked to blackfoot disease and cancer.
High arsenic concentrations in drinking water pose serious health risks, necessitating effective monitoring and management strategies.

Purpose of the Study:

To monitor groundwater quality and identify factors influencing arsenic (As) concentrations in decommissioned wells.
To investigate the impact of explanatory variables like total organic carbon (TOC), alkalinity, groundwater elevation, and rainfall on temporal variations in groundwater As concentration using Dynamic Factor Analysis (DFA).

Main Methods:

Installation and monitoring of 28 groundwater observation wells.
Application of Dynamic Factor Analysis (DFA) to identify common trends and unexplained variability in groundwater As concentrations.
Analysis of geochemical variables (TOC, As, alkalinity) and environmental factors (groundwater elevation, rainfall) to assess their influence on As levels.

Main Results:

DFA indicated that rainfall effectively dilutes arsenic concentrations in areas with aquacultural and agricultural use.
Geochemical variables from nearby monitoring wells significantly affected arsenic concentrations in most decommissioned wells.
The DFA model demonstrated acceptable performance for 52% of the decommissioned wells, indicating its utility in understanding arsenic variability.

Conclusions:

Surface water recharge is inferred to be an effective method for diluting arsenic concentrations, especially in areas distant from the coastline.
DFA successfully identified key factors influencing groundwater arsenic variations and demonstrated the potential to extrapolate data from existing monitoring wells to nearby decommissioned ones.