Environmental Engineering and Management Journal January 2012, Vol.11, No. 1, 55-60 http://omicron.ch.tuiasi.ro/eemj/ Gheorghe Asachi Technical University of Iasi, Romania PHYSICO-CHEMICAL CHARACTERISTICS AND DYNAMICS OF THE WELLS WATER IN GALATI COUNTY (ROMANIA) Maria Cioroi, Mirela Praisler Dunarea de Jos University of Galati, Faculty of Sciences and Environment, 47Domneasca Street, Galati, Romania Abstract The availability of good quality water is an indispensable condition for preventing diseases and improving the quality of life. Water is one of the most important renewable resources, which must be prevented from deterioration in quality. Various physicochemical parameters like ph, alkalinity, total hardness, total dissolved solids, calcium, magnesium, nitrate, have a significant role in determining the potability of drinking water. In this study, samples were collected from wells situated in villages located in the northern part of Galati (Tulucesti, Vanatori and Costi) in order to analyze the quality of water wells. Investigations on physico-chemical parameters such as temperature, ph, salinity, dissolved oxygen(do), chemical oxygen demand (COD), biochemical oxygen demand (BOD 5 ), hardness, total dissolved solids (TDS), conductivity (COND), turbidity (Turb), alkalinity, salinity, redox potential (E) including dissolved nutrients (Ca 2+, Mg 2+, Fe 2+, Al 3+, Mn 2+, Cl -, PO 4 -P, NO 2 -N, ) were carried out in the water wells, during the summer season in 2010. The results of the physico-chemical analysis were obtained are in the following range: ph (6.7-7.8), alkalinity (1.11-2.97 mg/l), total hardness (190.4-1864.8 mg/l), COD (oxidisability): 15.8-79 mg/l, BOD 5 (0.168-7.279 mg/l), TDS (850-3790 mg/l), conductivity (1435-6250 μs/cm), redox potential, E (-72mV- 1mV), Ca 2+ (48-520 mg/l), Mg 2+ (43.2-46.8 mg/l) Fe 2+ (0.13-0.67 mg/l), Al 3+ (0.001-0.071 mg/l), NO 2 (0-6.649 mg/l), Cl - (56.8-317.17 mg/l), PO 4 3- (0.358-4.026 mg/l) O 2 (0.335-8.88 mg/l). Key words: physico-chemical parameters, principal component analysis, wells water Received: September, 2011; Revised final: January 2012; Accepted: January, 2012 1. Introduction Drinking water needs to meet some quality standards, which refer to the fact that it must be free of microorganisms (pathogens) causing diseases, low in concentrations of compounds that are highly toxic or have serious long-term effects on health (according to Maximum Allowable Concentrations imposed by standards). The drinking water should also be clear, not salty, and free of compounds that can cause color, taste and smell. Nearly 80% of all diseases and over one third of deaths in developing countries are related to water (Palamuleni, 2001). A number of 1.3 billion people in the developing world are forced to use contaminated water for drinking and cooking and more than six million children die each year from diseases related to water (Carabet et al., 2011; Fernando, 2005; Mkandawire, 2008). The traditional method for extracting potable water from the ground is by drilling shallow wells in the existing water table to create a point of water (Pritchard et al., 2007). The need to assess the quality of water in some of these sources has become imperative, because they have a direct effect on the health of individuals (WHO, 1996). Although there is no source of anthropogenic contamination, naturally high levels of metals and other chemicals represent a potential risk to human health (Dascalescu et al., 2011; Nkansah et al., 2010). Groundwater is still and will continue to be the main source of safe drinking water, especially in rural areas. The water drawn from such sources (different Author to whom all correspondence should be addressed: e-mail: mcioroi@ugal.ro
Cioroi and Praisler/Environmental Engineering and Management Journal 11 (2012), 1, 55-60 types of deep and shallow wells) is often better quality than surface water or other water sources if the soil is finely grained and its bases have no cracks, crevices that allow the free passage of polluted water especially in metropolitan areas (Jain et al., 2010). Romania is counted among the countries facing serious problems due to high concentrations of naturally occurring arsenic in groundwater with more than 95 µg/l in some counties such as Arad and Bihor, located in Western Romania (Bissen and Frimmel, 2003; Lindberg, 2006). At this moment, very few data is available on the importance of chemical parameters in well water in the East in general and in the county of Galati, in particular. This study is among the first to examine the quality of well water in some localities of Galati County. 2. Experimental 2.1. Sample collection Twenty water samples were collected from each of the four different wells analyzed in different residences found in rural areas of Galati. In our study, samples were collected from wells situated in villages located in the northern part of Galati (Tulucesti-two wells, well codes T1 and T2), Vanatori (one well, well code V), Costi (one well, well code C) in order to analyze the quality of the water wells. Water samples were collected in pre-washed bottles of 1L for chemical analysis and in sterilized bottles for microbiological analysis. Water samples were kept in a cooler and were transported to the laboratory for further processing. The chemical tests were performed within 7 days of collection. 2.2. Chemical analyses The determination of physicochemical properties such as total hardness, Ca 2+, Mg 2+ was made by complexometric titration with EDTA. The oxidability was made by titrimetry using KMnO 4. The concentrations of Fe 2+, Al 3+, (PO 4 ) 3-, Mn 2+, (NO 2 ) -, (NH 4 ) + were determined by spectrophotometry and were calculated from their standard curve calibration. The determination of Cl - ion concentrations was made using the argentometric assay, while those of O 2, BOD 5 and alkalinity, respectively titrimetry with was performed with sodium hydroxide, sodium thiosulfate and hydrochloric acid (Cioroi, 2005). 2.3. Principal Component Analysis (PCA) Fig. 2 shows that we can discriminate between the water samples from location T1 and T2 by using the PC2 scores of the samples: the water quality of the samples from the location T1 (samples T11, T12, T13) have positive PC2 scores, while the water samples from the location T2 (T21, T22, T23, T25) have negative PC2 scores. Data analysis was performed based on Principal Component Analysis (PCA), one of the best statistical techniques for extracting multivariate relationships among a set of variables. No weighting was used in the modeling process (i.e. all weights were set to 1.0). The validation method has been full cross-validation. The analysis has been done initially with a number of 20 Principal Components (PCs). Data was centered on the mean. 3. Results and discussions The results shown in Table 1 present the averages values obtained for the samples from each location. The guidelines for the WHO drinking water and the percentage of samples containing concentrations above guideline values are also presented to allow a comparison with the characteristics of the analyzed water samples. The data indicates that the majority of chemical parameters are above the limits recommended by WHO for drinking water. Similar results have recently been shown by Craciun et al., 2009. The parameters that differ significantly from the standard values are the total hardness, the oxidisability, the Mg 2+, NO 2 -, Fe 2+ and Mn 2+ contents, while 87.2% and 100% water samples did not reach the minimum values for Cl - and Al 3+. The data was subjected to a PCA that was initiated with a number of 20 PCs. The analysis of the residual variance has indicated that it decreases significantly only up to the first two PCs. The new model, built only with 2 PCs, was characterized by a total explained variance of 99.54%, out of which PC1 corresponds to an explained variance of 98.84% (see Fig. 1), which confirms that the selected number of PCs was correct. The score plot PC1 vs. PC2 shows the formation of three well-defined clusters, formed by the water samples collected in the locations Vanatori (location code V), Tulucesti (location code T), and Costi (location code C), as presented in Fig. 2. The water samples from location C are characterized by large positive PC1 scores, as opposed to the samples from the locations T and V, which are characterized by negative PC1 scores. The discrimination between the water quality in the latter two locations can be done by the values of the PC1 scores of these samples: the V water samples are characterized by large PC1 scores (between -2215 and -2437), while the PC1 scores of the T water samples are much smaller (between -174 and -1016). It can be concluded that PC1 is modeling and discriminating the quality of the water found in different geographical locations, while PC2 accounts for the variations recorded for the quality of the water found in different collection points in the same geographical area. Moreover, the seasonal changes of the water properties can be more important than the variations found among different locations from the same geographical area. 56
Physico-chemical characteristics of the wells water in some areas of Galati County Table 1. Chemical analyses of the water wells Parameter Tulucesti 1 Tulucesti 2 Vinatori Costi WHO guide T C 14.5 15.5 19.0 15.0 Hardness (mg/l) 630.00 503.73 217.00 1497.44 500 Ca 2+ (mg/l) 285.00 193.33 67.00 408.80 Mg 2+ (mg/l) 99.00 100.00 52.80 396.48 50 Oxidisability (mg/l) 47.40 26.33 35.55 44.24 5 Cl - (mg/l) 260.038 155.490 62.658 163.300 250 Total alkalinity (mg/l) 1.855 1.261 2.821 2.019 NO - 2 (mg/l) 1.896 1.662 2.078 1.642 0.1 Fe 2+ (mg/l) 0.250 0.315 0.540 0.227 0.2 Al 3+ (mg/l) 0.027 0.007 0.007 0.005 0.2 Mn 2+ (mg/l) 0.424 0.660 1.139 2.431 0.05 PO 3-4 (mg/l) 1.897 0.615 1.557 2.128 Dissolved oxygen (mg/l) 1.405 2.18 0.365 4.38 BDO 5 (mg/l) 0.48 0.50 0.17 3.75 Fig. 1. Trend analysis of the explained variance of data for the selection of the number of principal components It can be seen that variations of the PC2 scores of the C4 and C6 water samples are larger than the differences between the PC2 scores of the samples T1 and T2. However, it could be argued that C4 and C6 may be outliers. The influence plot presented in Fig. 3 shows that, as opposed to all other samples, C6 and C4 have large values for both the residual X variance and for the leverage. In conclusion, the origin of these variations should be considered carefully, by including in the PCA a larger number of samples. The variables leading to the formation of the defined clusters have been identified by analyzing the loading plot presented in Fig. 4. It shows that the conductivity (variable code COND) and total dissolved solids (variable code TDS1) are the main variables responsible for the large positive PC1 scores. The hardness (variable code D), the Ca 2+ content, the Mg 2+ content, the Cl - content, and the redox potential (variable code E) are mainly responsible for the large positive PC2 scores, while oxidisability (variable code Ox) and turbidity (variable code Turb) are responsible for the formation of the clusters with large negative PC1 scores. From the loading plot it can also be noticed that the Cl - content and the redox potential (variable code E) are negatively correlated with the oxidability and with the turbidity. All four variables are practically independent of the total dissolved solids. The results show that the Ca 2+ and Mg 2+ content, the hardness, the redox potential E and the Cl - are present in the first quadrant. This indicates a reducing character of the analyzed water samples and a significant content of alkaline earth metals, conditions arising due to the composition of rocks watering. 57
Cioroi and Praisler/Environmental Engineering and Management Journal 11 (2012), 1, 55-60 Fig. 2. The score plot discriminating the quality of the water found in the analyzed geographical locations Fig. 3. Influence plot indicating the quality of the data for the elimination of the data affected by gross errors 58
Physico-chemical characteristics of the wells water in some areas of Galati County Fig. 4. Biplot showing the loadings of physico-chemical variables in wells water The other variables have less importance in modeling the water quality. 4. Conclusions Galati city is a big industrial point in a southeast of Romania. Because of the siderurgical industry, naval harbor and other polluting branches of industry, the quality of the environment in Galati and in the villages around it has been affected in the last 50 years. Investigations on physico-chemical parameters such as the temperature, ph, salinity, dissolved oxygen (variable code DO), chemical oxygen demand (variable code COD), biochemical oxygen demand (variable code BOD 5 ), hardness, total dissolved solids (variable code TDS), conductivity (variable code COND), turbidity (variable code Turb), alkalinity, salinity, redox potential (variable code E) including dissolved nutrients were carried out in the water wells, during the summer season in 2010. The concentrations of anions and cations determined in the water samples originating from wells located in the vicinity of Galati were found to be above the guidelines for drinking water supplied by the World Health Organization. In conclusion, the quality of ground water supplied by wells is unsatisfactory. The use of these waters may pose a hazard to users. Treatments such as boiling or treatment with a hypochlorite solution, chlorine dioxide can help disinfect them and should be imposed in the region. Further research on other communities in the area seems to be highly needed, in order to assess the quality of drinking water, as the level of contaminants can vary for different types of soils, water chemistry and various human activities. References Bissen M., Frimmel F. H., (2003), Arsenic - a review. Part I: Occurrence, toxicity, speciation, mobility, Acta Hydrochimica et Hydrobiologica, 31, 9 18. Lindberg A.L., Goessler W., Gurzau E., Koppova K., Rudnai P., Kumar R,. (2006), Arsenic exposure in Hungary, Romania and Slovakia, Journal of Environmental Monitoring, 8, 203 208. Carabeţ A., Mirel I., Florescu C., Stăniloiu C., Gîrbaciu A., Olaru I., (2011), Drinking water quality in watersupply networks, Environmental Engineering and Management Journal, 10, 1659-1665. Cioroi M., (2005), Quantitative Analysis of cations and anions, In: General Chemistry and Environmental Chemistry - Analytical Chemistry in Environmental Monitoring, Ed. Ars Docendi, Bucharest, 80-104. Craciun I., Giurma-Handley C.R., Giurma I., (2009), Quality risk evaluation of the groundwater resources on the moldavian area, Environmental Engineering and Management Journal, 8, 391-395. Dascalescu I.G., Cohl M., Teodosiu C., (2011), Investigation of drinking water quality changes in the distribution network of Iasi city by means of an on-line monitoring system, Environmental Engineering and Management Journal, 10, 1659-1665. Fernando T.S., (2005), The Ultimate Answer to Polluted Water. On line at: http://www.infolanka.com/org/diary/13.html. Jain C.K., Bandyopadhyay A., Bhadra A., (2010), Assessment of ground water quality for drinking purpose, District Nainital Utt arakhand, India, 59
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