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Introduction

Fly ash is a waste material generates on the combustion of coal in power station throughout the world. The increasing amount of fly ash being generated from thermal power plants can pose a serious environmental threat (Nalawade et al., 2012). Fly ash contains major elements like Silica, Aluminum and Iron with significant amount of Calcium, Magnesium, Potassium, Phosphorous and Sulphur (Ivanova et al., 2011; Aswar, 2001). It also contain trace amount of some heavy metals like Molybdenum, Mercury, Selenium and Cadmium etc. (Adriano et al., 1980). Fly ash in itself is a waste product and contains a huge problem for disposal. Fly ash is disposed off in ash pond by collecting it in the form of wet slurry (Singh et al., 2010). Disposal of fly ash in surface water bodies can damage the aquatic life. Mosquitoes and bacteria may grow in large number in slurry disposal lagoons/settling tank (Nawaz, 2013). The soil and water contamination from ash ponds has been a major subject of research all over the world (Theis et al., 1978; Theis and Richter, 1979; Theis and Gardner, 1990; Carlson and Adriano, 1993; Deshmukh et al., 1994; Deshmukh et al., 1995; Gulec et al., 2001; Praharaj et al., 2002; Singh et al., 2010; Ramya et al., 2013; Nawaz, 2013). The water quality plays a vital role for the mankind as it directly affects the human health. More than 90% population in India is dependent on groundwater for drinking purpose (Yadav et al., 2012; Ramachandraiah, 2004; Tank and Singh, 2010). The present study was done to assess the impact of fly ash disposal on groundwater quality near Parichha Thermal Power Plant at Jhansi.

Study Area

Locality near Parichha thermal power plant at Jhansi was selected as the study area. Parichha thermal power plant is located at 25°30'51.16"N and 78°45'37.40"E. Jhansi is located at 24°11' and 25°57' N and 78°10' and 79°25 E'. Jalaun lies on North to Jhansi, Mahoba and Hamirpur on East, Tikamgarh of Madhya Pradesh on South and Lalitpur on southwest which joins the Jhansi District by a narrow corridor. A map showing the sampling location of study area is depicted as figure-1.

Fig. 1: Location Map showing Sampling Locations of Study Area Click here to View figure

Collection of Sample

Groundwater samples were collected from 6 different locations near Parichha Thermal Power Plant during January to May 2014. The water samples were collected in polyethylene bottles which were pre-cleaned by nitric acid and distilled water in the laboratory. The pre-cleaned polyethylene bottles were also washed twice by water sample prior to collect the samples. The water samples were immediately taken to the laboratory and analyzed to minimize the physicochemical changes.

Physico-Chemical Analysis

Physico-chemical parameters like pH, turbidity, temperature, electrical conductivity, alkalinity, total hardness, calcium hardness, magnesium hardness and heavy metals like Lead and Cadmium were determined using standard methods of APHA (1995) and the methods by Trivedi and Goel (1986). The reagents of analytical grade were used for analysis and the instruments were calibrated.

Result and Discussion

The result of physico-chemical and heavy metal analysis of groundwater collected near Parichha Thermal Power Plant is given in Table-1.

Table 1: Average Results of Tested Parameters Click here to View table

pH value of studied samples ranges from 6.99 to 7.55 which conform to the IS 10500:2012 drinking water standard. High temperature may raise the alkalinity of water because it reduce solubility of CO₂. Temperature was ranges from 22ºC and 24.5ºC.

The turbidity was varied between 14.63 NTU to 15.78 NTU. It was found greater than the IS 10500:2012 standard in all the samples.

Table 2: Comparison of Groundwater Quality With Drinking Water Standard Click here to View table

Conductivity is a carrying capacity of electrical current of a solution through the water (Gupta et al., 2013). EC values were varied between 614 to 1317 µmhos/cm. It is directly proportional to the ionizable solids.

Alkalinity of water may be due to either the always presence of strong bases like sodium hydroxide or potassium hydroxide in water or the extreme low concentration of them. Maximum alkalinity of 455.5 mg/l was recorded in GW-1 and minimum i.e. 289.5 mg/l was recorded in GW-6 which exceeds the standard value. It may be due to the minimum rate of decomposition of salts caused by low temperature and low water table (Mahananda et al., 2010). The water is well buffered if it has high alkalinity.

The range of hardness analyzed is 143.84 – 725.20 mg/l. Some samples were within the standard of drinking water and some was exceeding the limit. Hardness caused excessive soap consumption and formation of scum due to the presence of calcium and magnesium in water.

Different type of rocks, sewage and industrial waste are responsible for the calcium and magnesium in water (Trivedy and Goel, 1984). The values of calcium varied from 39.91 – 188.57 mg/l and the values of magnesium ranged from 95.56 – 640.78 mg/l.

Total Dissolved Solids and conductivity usually related with each other. The water is not considered good for drinking if TDS of water is more than 500 mg/l (Jain, 2002). The values of investigated samples were ranged between 209.5 – 958.5 mg/l. Half samples were within the drinking water standard of IS 10500:2012 and half were exceeding the limit.

Table 3: Correlation Co-Efficient Of Different Parameters Click here to View table

The value of lead was ranged from 0.02 to 0.04 mg/l and the range of cadmium was 0.002 to 0.004 mg/l. Use of mineral phosphate fertilizer is important source of cadmium (Lambert et al., 2007). Both parameters were detected within the permissible limit of IS 10500:2012.

Table 4: Computation Of Regression Line For Various Samples Click here to View table

Correlation and Regression Analysis

The correlation study reduces the uncertainty range associated with decision making. The correlation co-efficient 'r' is used to know the relationship among the parameters. The co-efficient was calculated by using the below given formula:

Where, X and Y represents investigated parameters, N= Number of total observation.

在目前的研究中,相关系数(r) between two different parameters was calculated by considering the average values as shown in table 1. Correlation coefficient was calculated for pH, Turbidity, Temperature, EC, Alkalinity, Total Hardness, Calcium, Magnesium, Total dissolved solids, Lead and Cadmium of groundwater. The highest positive correlation (r = 0.960) was found between turbidity and temperature and the highest negative correlation (r = -0.803) was found between calcium hardness and pH. High values of the correlation coefficient between TH & EC (0.935), Mg & EC (0.955), Mg & TH (0.969), TH & pH (-0.797) as shown in table 3, were observed for the regression analysis, regression equations were formed and regression lines are drawn as shown in figures 2, 3, 4, 5, 6 and 7.

Fig. 2: Regression Line for Turbidity and Temperature Click here to View figure

Fig. 3: Regression Line for Total Hardness and Electrical Conductivity Click here to View figure

Fig. 4: Regression Line for Magnesium Hardness and Electrical Conductivity Click here to View figure

Fig. 5: Regression Line for Magnesium 硬度和总Hardness Click here to View figure

Fig. 6: Regression Line for pH and Total Hardness Click here to View figure

Fig. 7: Regression Line for pH and Calcium Hardness Click here to View figure

Conclusion

After the analysis and interpretation of numerical data, it can be concluded that the groundwater is contaminated in terms of Turbidity, alkalinity, magnesium, total hardness, calcium and TDS. This may be due to the disposal of fly ash near Parichha Thermal Power Station. The study shows that the groundwater needs attention for certain degree of treatment before drinking. Perfect positive correlation evolved between Turbidity and Temperature (0.960), TH & EC (0.935), Mg & EC (0.0.955), Mg & pH (0.969) and perfect negative correlation evolved between TH & pH (-0.797) and Ca & pH (-0.803). It shows that Turbidity, Total Hardness and Magnesium is permanent in nature however there is no relation between TH & pH and Ca & pH. Regression lines were drawn to get the value of one parameter from another parameter.

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