Nitrate-nitrogen leaching from agricultural areas is a major cause for groundwater pollution. Polluted groundwater with high levels of nitrate is hazardous and cause adverse health effects. Human consumption of water with elevated levels of NO3-N has been linked to the infant disorder methemoglobinemia and also to non-Hodgkin's disease lymphoma in adults. This research aims to study the temporal patterns and source apportionment of nitrate-nitrogen leaching in a paddy soil at Ladang Merdeka Ismail Mulong in Kelantan, Malaysia. The complex data matrix (128 x 16) of nitrate-nitrogen parameters was subjected to multivariate analysis mainly Principal Component Analysis (PCA) and Discriminant Analysis (DA). PCA extracted four principal components from this data set which explained 86.4% of the total variance. The most important contributors were soil physical properties confirmed using Alyuda Forecaster software (R2 = 0.98). Discriminant analysis was used to evaluate the temporal variation in soil nitrate-nitrogen on leaching process. Discriminant analysis gave four parameters (hydraulic head, evapotranspiration, rainfall and temperature) contributing more than 98% correct assignments in temporal analysis. DA allowed reduction in dimensionality of the large data set which defines the four operating parameters most efficient and economical to be monitored for temporal variations. This knowledge is important so as to protect the precious groundwater from contamination with nitrate.
Natural, inorganic arsenic contamination of groundwater threatens the health of more than 100 million people worldwide, including residents of the densely populated river deltas of South and Southeast Asia. Contaminated groundwater from tube wells in Cambodia was discovered in 2001 leading to the detection of the first cases of arsenicosis in 2006. The most affected area was the Kandal Province. The main objective of this study was to determine the prevalence of arsenicosis in Cambodia based on acceptable criteria, and to investigate the use of hair arsenic as a biomarker not only for arsenicosis-related signs but also for associated symptoms. A cross-sectional epidemiological study of 616 respondents from 3 purposely selected provinces within the Mekong River basin of Cambodia was conducted. The Kandal Province was chosen as a high arsenic-contaminated area, while the Kratie Province and Kampong Cham Province were chosen as moderate and low arsenic-contaminated areas, respectively. The most prevalent sign of arsenicosis was hypomelanosis with a prevalence of 14.5% among all respondents and 32.4% among respondents with a hair arsenic level of ≥1 μg/g. This was followed by hyperkeratosis, hyperpigmentation and mee's lines. Results also suggest a 1.0 μg/g hair arsenic level to be a practical cut off point for an indication of an arsenic contaminated individual. This hair arsenic level, together with the presence of one or more of the classical signs of arsenicosis, seems to be a practical criteria for a confirmed diagnosis. Based on these criteria, the overall prevalence of arsenicosis for all provinces was found to be 16.1%, with Kandal Province recording the highest prevalence of 35.5%. This prevalence is comparatively high when compared to that of other affected countries. The association between arsenicosis and the use of Chinese traditional medicine also needs further investigation.
A comprehensive study was conducted to identify the salinization origins and the major hydrogeochemical processes controlling the salinization and deterioration of the Gaza coastal aquifer system through a combination approaches of statistical and geostatistical techniques, and detailed hydrogeochemical assessments. These analyses were applied on ten physicochemical variables for 219 wells using STATA/SE12 and Surfer softwares. Geostatistical analysis of the groundwater salinity showed that seawater intrusion along the coastline, and saltwater up-coning inland highly influenced the groundwater salinity of the study area. The hierarchical cluster analysis (HCA) technique yielded seven distinct hydrogeochemical signature clusters; (C1&C2: Eocene brackish water invasion, C3 saltwater up-coning, C4 human inputs, C5 seawater intrusion, C6 & C7 rainfall and mixing inputs). Box plot shows a wide variation of most of the ions while Chadha's plot elucidates the predominance of Na-Cl (71.6%) and Ca/Mg-Cl (25%) water types. It is found that, the highest and the lowest levels of salinization and the highest level of nitrate pollution were recorded in the northern area. This result reflects the sensitivity of this area to the human activities and/or natural actions. Around 90.4% of the wells are nitrate polluted. The main source of nitrate pollution is the sewage inputs while the farming inputs are very limited and restricted mostly in the sensitive northern area. Among the hydrogeochemical processes, ion exchange process was the most effective process all over the study area. Carbonate dissolution was common in the study area with the highest level in clusters 6, 7, 4 and 2 in the north while Gypsum dissolution was significant only in cluster 1 in the south and limited in the other clusters. This integrated multi-techniques research should be of benefit for effective utilization and management of the Gaza coastal aquifer system as well as for future work in other similar aquifers systems.
Hydrogeochemical investigations had been carried out at the Amol-Babol Plain in the north of Iran. Geochemical processes and factors controlling the groundwater chemistry are identified based on the combination of classic geochemical methods with geographic information system (GIS) and geostatistical techniques. The results of the ionic ratios and Gibbs plots show that water rock interaction mechanisms, followed by cation exchange, and dissolution of carbonate and silicate minerals have influenced the groundwater chemistry in the study area. The hydrogeochemical characteristics of groundwater show a shift from low mineralized Ca-HCO3, Ca-Na-HCO3, and Ca-Cl water types to high mineralized Na-Cl water type. Three classes, namely, C1, C2, and C3, have been classified using cluster analysis. The spatial distribution maps of Na(+)/Cl(-), Mg(2+)/Ca(2+), and Cl(-)/HCO3 (-) ratios and electrical conductivity values indicate that the carbonate and weathering of silicate minerals played a significant role in the groundwater chemistry on the southern and western sides of the plain. However, salinization process had increased due to the influence of the evaporation-precipitation process towards the north-eastern side of the study area.