Study of personal–indoor–ambient fine particulate matters among school communities in mixed urban–industrial environment in India

A sampling program was conducted to investigate the formation of disinfection by-products (DBPs) and dissolved organic carbon (DOC) at two advanced water treatment plants in Kaohsiung City, Taiwan. The results in this study can be used as a reference for the operational control of water treatment plants and the setting of regulations in Taiwan. Samples of drinking water were collected from two advanced water treatment plants from June 2007 to April 2008. Changes in the concentration of dissolved organic carbon, the trihalomethane formation potential, and the haloacetic acids formation potential were measured in raw water samples. Variations in the concentrations of trihalomethanes (THMs) and haloacetic acids (HAA₅) in finished drinking water were evaluated. The major species of HAA₅ were in the order of dichloroacetic acid and trichloroacetic acid and the THM was of trichloromethane. DOC was strongly related to DBPs in raw water. In this investigation, the removal efficiency of DBPs in Plant A (ultrafiltration/reverse osmosis system) exceeded that in Plant B (ozonation/biological activated carbon system). Both advanced water treatment plants greatly improved the quality of drinking water.     

Size and resin fractionations of dissolved organic matter and trihalomethane precursors from four typical source waters in China

Dissolved organic matter (DOM) and its potential to form disinfection by-products (DBPs) during drinking water treatment raise challenges to water quality control. Understanding both chemical and physical characteristics of DOM in source waters is key to better water treatment. In this study, the DOM from four typical source waters in China was fractionated by XAD resin adsorption (RA) and ultrafiltration (UF) techniques. The trihalomethane formation potential (THMFP) of all fractions in the DOM were investigated to reveal the major THM precursors. The fraction distributions of DOM could be related to their geographical origins in a certain extent. The dominant chemical fraction as THM precursors in the DOM from south waters (East-Lake reservoir in Shenzhen and Peal rivers in Guangzhou) was hydrophobic acid (HoA). The size fraction with molecular weight (MW) <1 kDa in both south waters had the highest THMFP. The results of cluster analysis showed that the parameters of fractions including DOC percentage (DOC%), UV₂₅₄%, SUVA₂₅₄ (specific UV₂₅₄ absorbance) and THMFP were better for representing the differences of DOM from the studied waters than specific THMFP (STHMFP). The weak correlation between SUVA₂₅₄ and STHMFP for either size or XAD fractions suggests that whether SUVA₂₅₄ can be used as an indicator for the reactivity of THM formation is highly dependent on the nature of organic matter.     

Reduction of dissolved organic matter in terms of DOC, UV-254, SUVA and THMFP in industrial estate wastewater treated by stabilization ponds

The aim of this research was to monitor the influent and effluent water quality of the aeration, facultative and oxidation water treatment ponds of an industrial estate. This industrial estate, the largest in northern Thailand, has proposed to utilization of reclaimed treated wastewater in their raw water supply so as to cope with the yearly water shortage during the dry season. Water samples were collected four times from four sampling points and evaluated for their dissolved organic matter (DOM) content in terms of dissolved organic carbon (DOC), ultraviolet light absorbance at 254 nm (UV-254), specific ultraviolet absorption (SUVA), trihalomethane formation potential (THMFP) and trihalomethane (THM) species. Average values of DOC, UV-254, SUVA and THMFP in the influent wastewater of 12.9 mg L⁻¹, 0.165 cm⁻¹, 1.29 L mg⁻¹m⁻¹ and 1.24 mg L⁻¹, respectively, were observed. The aeration ponds produced the best results: a 54% reduction of DOC, a 33% reduction of UV-254, and a 57% reduction of THMFP. However, SUVA in the aeration pond effluent showed a moderate increase. The facultative ponds and oxidation ponds did not take part in the reduction of DOC, UV-254, SUVA and THMFP. Average DOC, UV-254, SUVA and THMFP value of the treated wastewater were 5.8 mg L⁻¹, 0.107 cm⁻¹, 1.85 L mg⁻¹m⁻¹ and 468 μg L⁻¹, respectively. Chloroform, at 72.6% of total THMFP, was found to be the predominant THM species.     

Wet weather impact on trihalomethane formation potential in tributaries to drinking water reservoirs

During rain storm events, land surface runoff and resuspension of bottom sediments cause an increase in Trihalomethane (THM) precursors in rivers. These precursors, when chlorinated at water treatment facilities will lead to the formation of THMs and hence impact drinking water resources. In order to evaluate the wet weather impact on the potential formation of THMs, river samples were collected before, during and after three rain storms ranging from 15.2 to 24.9 mm precipitation. The samples were tested for THM formation potential and other indicators including UV254 absorbance, turbidity and volatile suspended solid (VSS). Average levels of THMs increased from 61 μg/l during dry weather to 131 μg/l during wet weather, and then went back to 81 μg/l after rain ended. Wet weather values of THM are well above the maximum contaminant level (MCL) 80 μg/l, set by EPA for drinking water. THM indicators also exhibited similar trends. Average levels increased from 0.6 to 1.8 abs; 2.6 to 6 ntu; and 7.5 to 15 mg/l respectively for UV254, turbidity and VSS. A positive correlation was observed between THM formation and THM indicators. The t-test of significance (p-value) was less than 0.05 for all indicators, and R values ranged from 0.85 to 0.92 between THMs and the indicators, and 0.72 to 0.9 among indicators themselves.     

Monitoring and modeling of disinfection by-products (DBPs)

In the United States, the newly promulgateddisinfectant/disinfection by-product (D/DBP) regulationsforce water treatment utilities to be more concerned withfinished and distributed water qualities. In this study,monitoring of DBP formation was conducted from three Frenchwater treatment plants trying to assess DBP variationsthrough time and space. Compared to the in-plant totaltrihalomethanes (TTHM) levels, TTHM levels in thedistribution system increased from less than 150% to morethan 300%. Significant variations for TTHM and bromate(BrO₃ ^-) levels throughout the seasons were alsoobserved; generally higher levels in the summer and lowerlevels in the winter. Combining chemical DBP models(empirical power functional models) and hydraulicsimulations, DBPs including TTHM and BrO₃ ^- weresuccessfully simulated from the full-scale monitoring data,indicating that empirical DBP model can be a potential toolto access DBP formation in actual plants. This study alsoprovides the protocols to assess DBP simulations in thewater treatment systems.     

N-nitrosodimethylamine and trihalomethane formation and minimisation in Southeast Queensland drinking water

This study assesses the prevalence of disinfection by-product (DBP) precursors in some Southeast Queensland drinking water sources by conducting formation potential experiments for the four regulated trihalomethanes (THMs), and the potent carcinogen, N-nitrosodimethylamine (NDMA). NDMA formation potentials were consistently low (<5-21 ng/L), and total THM (tTHM) formation potentials were consistently below the Australian Drinking Water Guideline (250 μg/L). NDMA concentration of finished drinking waters was also monitored and found to be <5 ng/L in all cases. The effect of coagulation and advanced oxidation on the formation of NDMA and THMs is also reported. UV/H(2)O(2) pre-treatment was effective in producing water with very low THMs concentrations, and UV irradiation was an effective method for NDMA degradation. H(2)O(2) was not required for the observed NDMA degradation to occur. Coagulation using alum, ferric chloride or poly(diallyldimethylammonium chloride) (polyDADMAC) was ineffective in removing DBPs precursors from the source water studied, irrespective of the low dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) attained. Rather, coagulation with polyDADMAC caused an increase in NDMA formation potential upon chloramination, and all coagulants led to an increased tTHM formation potential upon chlorination due to the high bromide concentration of the source water studied.     

Occurrence of haloacetic acids (HAAs) and trihalomethanes (THMs) in drinking water of Taiwan

In this study, water samples were collected from 86 water treatment plants for analysis of haloacetic acids (HAAs) and trihalomethanes (THMs) from February to March, 2007 and from July to August, 2007. Both seasonal and geographical variations of disinfection by-products (DBPs) in drinking water of Taiwan were presented. The results showed that the five HAA concentrations (HAA5) were 1.0–38.9 μg/L in the winter and 0.2–46.7 μg/L in the summer; and the total THMs were ND-99.4 μg/L in the winter and ND-133.2 μg/L in the summer. For samples taken from the main Taiwan island, dichloroacetic acid (29.4–31.7%) and trichloroacetic acid (25.3–27.6%) were the two major HAA species, and trichloromethane was the major THM species (49.9–62.2%) in finished water. For water treatment plants located on the offshore islands outside of Taiwan, high bromide concentration was found in raw water, and higher percentage of brominated THMs and HAAs were formed in the overall formation. A statistically significant (P?<?0.005) logarithmic linear regression model was found to be useful to describe the correlations between TTHM and HAA5 or nine HAAs (HAA5?=?1.219 ×TTHM ^0.754, R ²?=?0.658; HAA9?=?1.824 ×TTHM ^0.735, R ²?=?0.678). No apparent difference was observed for DBPs concentrations between finished water and distribution samples in this study.     

Monitoring the formation of trihalomethanes in the effluents from a shrimp hatchery

Formation of trihalomethanes (THM) was monitored at the Laboratório de Camarões Marinhos (LCM) from the Universidade Federal de Santa Catarina. THM could be present because chlorinated effluents from disinfection are discharged from the different hatchery rooms. THM quantification was done through an analytical methodology using Purge&;Trap coupled with a gas chromatograph equipped with an electron capture detector. Relative standard deviation (RSD), limit of detection (LOD) and limit of quantification (LOQ) for the methodology corresponded to the ranges of 8–17%; 0.01–0.03 μg L^?1 and 0.03–0.08 μg L^?1, respectively. Linear working range was of 0.1–8.0 μg L^?1 for all compounds. Enrichment and recovery method was applied to evaluate possible matrix effects and the results varied from 71.2% to 107.9%. LCM was monitored between August and December, 2004. This study showed that THM did not increase with the increase in postlarvae production and also that the aquatic life and the surrounding environment were not affected.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Isolation and fractionation of natural organic matter: evaluation of reverse osmosis performance and impact of fractionation parameters

Dissolved organic matter (DOM) from three surface waters was isolated using reverse osmosis (RO) and subsequently fractionated using resin adsorption chromatography (RAC). Efficacy of RO was evaluated by closing mass balances for dissolved organic carbon (DOC). RAC was evaluated by investigating the effect of column operational parameters (column capacity factor, k', and solute initial concentration, C0) on DOM fractionation and subsequent disinfection by-product formation. Efficacy of RO was dependent on both isolation conditions and source water characteristics. In general, RO more effectively isolated DOM in high specific ultraviolet absorbance (SUVA254) water than low SUVA254 water, and showed higher DOM recovery at ambient pH (approximately 7) than at low pH (approximately 4). The fractionation of the isolated DOM indicated that the relative amount of the hydrophobic fraction decreased with increasing k', thus affecting the overall distribution of DOM. However, the distribution of DOM fractions was not influenced by varying C0 up to 150 mg l(-1) at k' of 15. The effect of k' on the formation and speciation of trihalomethanes (THM) and haloacetic acids (HAA) was not significant up to k' of 30.     

Monitoring the Trihalomethanes Present in Water After Treatment with Chlorine Under Laboratory Condition

In this work assays involving chlorinated water samples, which were previous spiked with humic substances or algae blue green and following the production of the THMs for 30 days is described. To implement the assays, five portions of 1,000 ml of water were stored in glass bottles. The water samples were treated with solutions containing 2, 3, 4 and 5 mg l⁻¹ chlorine. The samples aliquots (60 ml) were transferred into the glass vials, 10 ml were removed to have a headspace and 100 μl of the 10 mg l⁻¹ pentafluortoluene bromide solution was added to each vial. The extraction step was performed by adding 10 g of Na₂SO₄ followed by 5 ml of n-pentane. The vials were stopped with a TFE-faced septum and sealed with aluminum caps. The generated THMs were determined by gas chromatography with electron capture detector using reference solutions with concentration ranging from 8 to 120 μg l⁻¹ THMs. Three assays were monitored during 30 days and chloroform was the predominant compound found in the water samples, while other species of THMs were not detected. The results showed that when the chlorine concentration was increased in water samples containing algae the concentration of THM varied randomly. Nevertheless, in water samples containing humic substances the increase of the THM concentration presented a relationship with the chlorine concentration. It was also observed that chloroform concentration increased with the elapsed time up to one and six days to water samples spiked with humic substances and algae blue green, respectively and decreased along 30 days. By other hand, assays performed using water samples containing decanted algae material showed that THM was not generated by the chlorine addition.     

Ecological risk analysis of polycyclic aromatic hydrocarbons (PAHs) in surface sediments from Laizhou Bay

The current research aims at developing predictive models for trihalomethane (THM) formation in Lebanon based on field-scale investigations as well as laboratory controlled experimentations. Statistical analysis on field data revealed significant correlations for TTHM with chlorine dose, Specific UV-A, and UV(254) absorbing organics. Simulated distribution system-THM tests showed significant correlations with applied chlorine dose, total organic carbon, bromides, contact time, and temperature. Predictive models, formulated using multiple regression approaches, exhibiting the highest coefficients of determination were quadratic for the directly after chlorination (DAC; r(2) = 0.39, p < 0.036) and network (r(2) = 0.33, p < 0.064) THM databases, and logarithmic for the laboratory simulated THM database (r(2) = 0.70, p < 0.001). Computed r(2) values implied low correlations for the DAC and network THM database, and high correlation for the laboratory simulated THM database. Significance of the models were at the 0.05 level for DAC database, 0.10 level for the network database, and very high (<0.01 level) for the laboratory simulated THM database. It is noteworthy to mention that no previous attempts to assess, monitor, and predict THM concentrations in public drinking water have been reported for the country although a large fraction of the population consumes chlorinated public drinking water.     

Predicting Water Quality Impaired Stream Segments using Landscape-Scale Data and a Regional Geostatistical Model: A Case Study in Maryland

In the United States, probability-based water quality surveys are typically used to meet the requirements of Section 305(b) of the Clean Water Act. The survey design allows an inference to be generated concerning regional stream condition, but it cannot be used to identify water quality impaired stream segments. Therefore, a rapid and cost-efficient method is needed to locate potentially impaired stream segments throughout large areas. We fit a set of geostatistical models to 312 samples of dissolved organic carbon (DOC) collected in 1996 for the Maryland Biological Stream Survey using coarse-scale watershed characteristics. The models were developed using two distance measures, straight-line distance (SLD) and weighted asymmetric hydrologic distance (WAHD). We used the Corrected Spatial Akaike Information Criterion and the mean square prediction error to compare models. The SLD models predicted more variability in DOC than models based on WAHD for every autocovariance model except the spherical model. The SLD model based on the Mariah autocovariance model showed the best fit (r² = 0.72). DOC demonstrated a positive relationship with the watershed attributes percent water, percent wetlands, and mean minimum temperature, but was negatively correlated to percent felsic rock type. We used universal kriging to generate predictions and prediction variances for 3083 stream segments throughout Maryland. The model predicted that 90.2% of stream kilometers had DOC values less than 5 mg/l, 6.7% were between 5 and 8 mg/l, and 3.1% of streams produced values greater than 8 mg/l. The geostatistical model generated more accurate DOC predictions than previous models, but did not fit the data equally well throughout the state. Consequently, it may be necessary to develop more than one geostatistical model to predict stream DOC throughout Maryland. Our methodology is an improvement over previous methods because additional field sampling is not necessary, inferences about regional stream condition can be made, and it can be used to locate potentially impaired stream segments. Further, the model results can be displayed visually, which allows results to be presented to a wide variety of audiences easily.     

Use of Water Clarity to Monitor the Effects of Climate Change and other Stressors on Oligotrophic Lakes

We present evidence from studies oflakes in Killarney Park, Ontario, Canada that waterclarity is a key variable for monitoring theeffects of climate change, high UV exposure andacidification. In small oligotrophic lakes, thesestressors affect water clarity primarily byaltering the concentration of DOC in lake water. Clear lakes (<2 mg L^-1 DOC) proved to be highlysensitive indicators of stressors, exhibiting largethermal and optical responses to small changes inDOC. Extremely clear (<0.5 mg L^-1 DOC) acidic lakesshowed the effects of climate change and solarbleaching in recent decades. These lakes becamemuch clearer even though they were slowlyrecovering from acidification.     

Selective and sensitive extractive spectrophotometric determination of micro amounts of palladium(II) in spiked samples: using a new reagent N-ethyl-3-carbazolecarbaxaledehydethiosemicarbazone

N-Ethyl-3-cabazolecarboxaldehydethiosemicarbazone (ECCT) is proposed as a new, sensitive and selective complexing reagent for the separation and extractive spectrophotometric determination of palladium(II) at pH: 4.0 to form a yellowish orange colored 1:1 chelate complex, which is very well extracted in to n-butanol. The absorbance was measured at a maximum wavelength, 410 nm. This method obeys Beer’s law in the concentration range 0.0–6.6 μg mL⁻¹ and the correlation coefficient of Pd(II)-ECCT complex is 0.998, which indicates an excellent linearity between the two variables with good molar absorptivity and Sandell’s sensitivity, 1.647 × 10⁴ l mol⁻¹cm⁻¹, 6.49 × 10⁻³ μg cm⁻², respectively. The instability constant of complex calculated from Edmond’s method, 2.724 × 10⁻⁵ was in good agreement with the value calculated from Asmus’ method 2.624 × 10⁻⁵, at room temperature. The precision and accuracy of the method is checked with calculation of relative standard deviation (n = 5), 0.839. Edmond’s method was observed to be a more selective method in the presence of EDTA, oxalate and phosphate ions. The method was successfully applied for the determination of Pd(II) in water samples, synthetic mixtures and hydrogenation catalysts, employing an atomic absorption spectrometer for comparing these results.     

Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China

Identification and quantification of dissolved oxygen (DO) profiles of river is one of the primary concerns for water resources managers. In this research, an artificial neural network (ANN) was developed to simulate the DO concentrations in the Heihe River, Northwestern China. A three-layer back-propagation ANN was used with the Bayesian regularization training algorithm. The input variables of the neural network were pH, electrical conductivity, chloride (Cl^?), calcium (Ca²⁺), total alkalinity, total hardness, nitrate nitrogen (NO₃-N), and ammonical nitrogen (NH₄-N). The ANN structure with 14 hidden neurons obtained the best selection. By making comparison between the results of the ANN model and the measured data on the basis of correlation coefficient (r) and root mean square error (RMSE), a good model-fitting DO values indicated the effectiveness of neural network model. It is found that the coefficient of correlation (r) values for the training, validation, and test sets were 0.9654, 0.9841, and 0.9680, respectively, and the respective values of RMSE for the training, validation, and test sets were 0.4272, 0.3667, and 0.4570, respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable. The most effective inputs were determined as pH, NO₃-N, NH₄-N, and Ca²⁺. Cl^? was found to be least effective variables on the proposed model. The identified ANN model can be used to simulate the water quality parameters.     

Trihalomethane formation potential in treated water supplies in urban metro city

Trihalomethane (THM) formation potential (TFP) is very useful test to assess the level of the formation of trihalomethanes in worst case scenario. Organics in water have the potential to generate harmful disinfection by-products (DBPs) such as THMs, as a result of their reaction with disinfectant chlorine used in drinking water. DBPs are increasingly recognized as cancerous agents. TFP of postchlorinated treated water were investigated at six water treatment plants (WTPs) in Delhi City (India). The present paper presents the current trends of TFP so that prevention and control measures can be initiated by the regulating agencies responsible for drinking water supply. Liquid–liquid extraction method, followed by qualitative and quantitative estimation by gas chromatograph equipped with electron capture detector, had been used for the determination of THMs in water samples collected at the outlet just before supplying to the consumers during 2000–2007. The TFP values from 2004 onward of all WTPs did not exceed the WHO guideline value of ≤1.     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

Use of fuzzy logic models for prediction of taste and odor compounds in algal bloom-affected inland water bodies

Mechanistic modeling of how algal species produce metabolites (e.g., taste and odor compounds geosmin and 2-methyl isoborneol (2-MIB)) as a biological response is currently not well understood. However, water managers and water utilities using these reservoirs often need methods for predicting metabolite production, so that appropriate water treatment procedures can be implemented. In this research, a heuristic approach using Adaptive Network-based Fuzzy Inference System (ANFIS) was developed to determine the underlying nonlinear and uncertain quantitative relationship between observed cyanobacterial metabolites (2-MIB and geosmin), various algal species, and physical and chemical variables. The model is proposed to be used in conjunction with numerical water quality models that can predict spatial–temporal distribution of flows, velocities, water quality parameters, and algal functional groups. The coupling of the proposed metabolite model with the numerical water quality models would assist various utilities which use mechanistic water quality models to also be able to predict distribution of taste and odor metabolites, especially when monitoring of metabolites is limited. The proposed metabolite model was developed and tested for the Eagle Creek Reservoir in Indiana (USA) using observations over a 3-year period (2008–2010). Results show that the developed models performed well for geosmin (R ²?=?0.83 for all training data and R ²?=?0.78 for validation of all 10 data points in the validation dataset) and reasonably well for the 2-MIB (R ²?=?0.82 for all training data and R ²?=?0.70 for 7 out of 10 data points in the validation dataset).     

Estimation Of Selenium Concentration In Shallow Groundwater In Alluvial Fan Area In Tsukui, Central Japan

Total selenium (Se) and water-soluble Se in soil, and Se in a shallow groundwater were hydrogeochemically researched in an alluvial fan area in Tsukui, Central Japan. The water-soluble Se was estimated at average level of 2.6 ± 1.2μg Se kg⁻¹ dry soil (± SD, n = 25), showing less than 1% of the total Se (349–508μg Se kg⁻¹ dry soil) in soil. The monthly Se concentration in groundwater was average 2.2μg,L⁻¹, ranging 1.6–2.4μg,L⁻¹ during 2001–2003. The Se in groundwater significantly decreased with increasing groundwater level after rainfall. This result indicated that Se-bearing water percolated with relatively low Se concentration through the soil layer. According to our prediction model of linear regression curve on the observation data, Se concentration in the groundwater was estimated to be increasing with the very low rate of 4.35 × 10⁻³μg Se L⁻¹,yr⁻¹. The hydrogeochemical research and the result of the prediction model showed that any explosive increase of Se will hardly occur in this groundwater without an anthropogenic Se contamination.