Abstract
Determining the main sources of pollution (MSP) in groundwater is crucial to improve water quality (WQ) status. Field studies were conducted in this research, where five sampling campaigns were carried out from 36 wells in the southern Tehran aquifer. In all samples, WQ parameters were measured and evaluated regarding the Iranian drinking water standard (IDWS). Finally, by using the principal component factor analysis (PCFA), the probable MSP in the aquifer were determined. The results showed that all ions, total hardness, and total dissolved solids were above the IDWS. To analyze the PCFA results, only the first four of twenty rotated principal factors (RPFs) that conserved a high percentage of the variance of the data (about 90%) were considered. The results of the first PRF revealed that the geological structure was the MSP in the aquifer. Furthermore, the second RPF was mainly affected by nutrients (nitrate and orthophosphate) and microbial parameters (fecal and total coliforms), indicating the importance of agricultural activities and sewage effluents as another MSP in the aquifer. Finally, the remarkable share of heavy metals and pH in formation of the third and fourth RPFs, respectively, reflected the role of industrial activities as a probable MSP of groundwater.
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References
APHA. (2005). Standard methods for the examination of water and wastewater (21st ed.). Washingon, D. C: American public health association.
Appelo, C. A. J., & Postma, D. (2004). Geochemistry, groundwater and pollution. Amsterdam, Netherlands: CRC Press.
Ayvaz, M. (2010). A linked simulation–optimization model for solving the unknown groundwater pollution source identification problems. Journal of Contaminant Hydrology, 117(1–4), 46–59. https://doi.org/10.1016/j.jconhyd.2010.06.004.
Bhutiani, R., Khanna, D. R., Tyagi, B., Tyagi, P. K., & Kulkarni, D. B. (2015). Assessing environmental contamination of River Ganga using correlation and multivariate analysis. Pollution, 1, 265–273.
Bhutiani, R., Kulkarni, D., Khanna, D. R., & Gautam, A. (2016). Water quality, pollution source apportionment and health risk assessment of heavy metals in groundwater of an industrial area in north India. Exposure and Health, 8, 3–18. https://doi.org/10.1007/s12403-015-0178-2.
Butera, I., Giovanna, M., & Zanini, A. (2013). Simultaneous identification of the pollutant release history and the source location in groundwater by means of a geostatistical approach. Stochastic Environmental Research and Risk Assessment, 27(5), 1269–1280. https://doi.org/10.1007/s00477-012-0662-1.
Handa, B. K. (1988). Content of potassium in groundwater in India. Fertilizer News, 33(11), 5–27.
Idemitsu, R. (2003). Site survey report for reduction of environmental impact project in Tehran oil Refining Company of Iran. An unpublished technical report.
Ielpo, P., Cassano, D., Lopez, A., Pappagallo, G., Uricchio, V., & DeNapoli, P. (2012). Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: Case study of Foggia province. Chemistry Central Journal. https://doi.org/10.1186/1752-153X-6-S2-S5.
Jha, M., & Datta, B. (2013). Three-dimensional groundwater contamination source identification using adaptive simulated annealing. Journal of Hydrologic Engineering, 18(3), 307–317. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000624.
Li, A., Jang, J. A., & Scheff, P. (2003). Application of EPA CMB8.2 model for source apportionment of sediment PAHs in Lake Calumet, Chicago. Environment Science and Technology, 37(13), 2958–2965. https://doi.org/10.1021/es026309v.
Lü, J., Qiu, H., Lin, H., Yuan, Y., Chen, Z., & Zhao, R. (2016). Source apportionment of fluorine pollution in regional shallow groundwater at You’xi County southeast China. Chemosphere, 158, 50–55. https://doi.org/10.1016/j.chemosphere.2016.05.057.
Luo, Y., Fang, M. A. Z., Hou, Y., & Li, L. (2013). Water quality assessment and source apportionment of pollution in shallow groundwater system of Jiaozuo. Applied Mechanics and Materials, 295(298), 776–780. https://doi.org/10.4028/www.scientific.net/AMM.295-298.776.
Manly, B. F. J. (2004). Multivariate statistical methods, a primer (3rd ed.). London: Chapman & Hall.
Marie, A., & Vengosh, A. (2001). Sources of salinity in groundwater from Jericho area, Jordan valley. Ground Water, 39(2), 240–248. https://doi.org/10.1111/j.1745-6584.2001.tb02305.x.
Masoumi, F., & Kerachian, R. (2008). Assessment of the groundwater salinity monitoring network of the Tehran region: Application of the discrete entropy theory. Water Science and Technology, 58(4), 765–771. https://doi.org/10.2166/wst.2008.674.
Mondal, N. C., Singh, V. P., Singh, V. S., & Saxena, V. K. (2010). Determining the interaction between groundwater and saline water through groundwater major ions chemistry. Journal of Hydrology, 388(1), 100–111. https://doi.org/10.1016/j.jhydrol.2010.04.032.
Najar, I., Khan, A., & Hai, A. (2017). Evaluation of seasonal variability in surface water quality of Shallow Valley Lake, Kashmir, India, using multivariate statistical techniques. Pollution, 3(3), 349–362. https://doi.org/10.7508/PJ.2017.03.001.
Nasrabadi, T., & Maedeh, P. A. (2014a). Groundwater quality degradation of urban areas (case study: Tehran city, Iran). International Journal of Environmental Science and Technology, 11(2), 293–302. https://doi.org/10.1007/s13762-013-0340-y.
Nasrabadi, T., & Maedeh, P. A. (2014b). Groundwater quality assessment in southern parts of Tehran plain, Iran. Environmental Earth Sciences, 71(5), 2077–2086. https://doi.org/10.1007/s12665-013-2610-x.
Noori, R., Abdoli, M. A., Ghasrodashti, A. A., & Jalili Ghazizade, M. (2009a). Prediction of municipal solid waste generation with combination of support vector machine and principal component analysis: A case study of Mashhad. Environmental Progress & Sustainable Energy, 28(2), 249–258. https://doi.org/10.1002/ep.10317.
Noori, R., Abdoli, M. A., Ghazizade, M. J., & Samieifard, R. (2009b). Comparison of neural network and principal component-regression analysis to predict the solid waste generation in Tehran. Iranian Journal of Public Health, 38(1), 74–84.
Noori, R., Karbassi, A., Khakpour, A., Shahbazbegian, M., Badam, H. M. K., & Vesali-Naseh, M. (2012). Chemometric analysis of surface water quality data: Case study of the gorganrud river basin, Iran. Environmental Modeling and Assessment, 17(4), 411–420. https://doi.org/10.1007/s10666-011-9302-2.
Noori, R., Karbassi, A., & Sabahi, M. S. (2010a). Evaluation of PCA and Gamma test techniques on ANN operation for weekly solid waste prediction. Journal of Environmental Management, 91(3), 767–771. https://doi.org/10.1016/j.jenvman.2009.10.007.
Noori, R., Sabahi, M. S., Karbassi, A. R., Baghvand, A., & Zadeh, H. T. (2010b). Multivariate statistical analysis of surface water quality based on correlations and variations in the data set. Desalination, 260(1–3), 129–136. https://doi.org/10.1016/j.proenv.2010.10.133.
Ouyang, Y. (2005). Evaluation of river water quality monitoring stations by principal component analysis. Water Research, 39(12), 2621–2635. https://doi.org/10.1016/j.watres.2005.04.024.
Pujari, R., & Deshpande, V. (2005). Source apportionment of groundwater pollution around landfill site in Nagpur, India. Environmental Monitoring and Assessment, 111, 43–54. https://doi.org/10.1007/s10661-005-8037-4.
Rafique, N., & Tariq, S. R. (2016). Distribution and source apportionment studies of heavy metals in soil of cotton/wheat fields. Environmental Monitoring and Assessment. https://doi.org/10.1007/s10661-016-5309-0.
Ritzi, R. W., Wright, S. L., Mann, B., & Chen, M. (1993). Analysis of temporal variability in hydrogeochemical data used for multivariate analyses. Groundwater, 31(2), 221–229. https://doi.org/10.1111/j.1745-6584.1993.tb01814.x.
Selvakumar, S., Chandrasekar, N., & Kumar, G. (2017). Hydrogeochemical characteristics and groundwater contamination in the rapid urban development areas of Coimbatore, India. Water Resources and Industry, 17, 26–33. https://doi.org/10.1016/j.wri.2017.02.002.
Shammi, M., Karmakar, B., Rahman, M., Islam, M. S., Rahaman, R., & Uddin, K. (2016). Assessment of salinity hazard of irrigation water quality in monsoon season of Batiaghata Upazila, Khulna District, Bangladesh and adaptation strategies. Pollution, 2(2), 183–197. https://doi.org/10.7508/pj.2016.02.007.
Shariatpanahi, M., & Anderson, A. C. (1987). Survey of chemical constituents of Tehran’s groundwater. Environmental Geochemistry and Health, 9(3), 55–60. https://doi.org/10.1007/BF02057275.
Shrestha, S., & Kazama, F. (2007). Assessment of surface water quality using multivariate statistical techniques: A case study of the Fuji river basin, Japan. Environmental Modelling and Software, 22(4), 464–475. https://doi.org/10.1016/j.envsoft.2006.02.001.
Tariq, S. R., Shah, M. H., Shaheen, N., Khalique, A., Manzoor, S., & Jaffar, M. (2005). Multivariate analysis of selected metals in tannery effluents and related soil. Journal of Hazardous Materials, 122(1), 17–22. https://doi.org/10.1016/j.jhazmat.2005.03.017.
Tariq, S. R., Shaheen, N., Khalique, A., & Shah, M. (2010). Distribution, correlation, and source apportionment of selected metals in tannery effluents, related soils, and groundwater—A case study from Multan, Pakistan. Environment Monitoring and Assessment, 166, 303–312. https://doi.org/10.1007/s10661-009-1003-9.
Tiwari, A. K., & Singh, A. K. (2014). Hydrogeochemical investigation and groundwater quality assessment of Pratapgarh district, Uttar Pradesh. Journal of the Geological Society of India, 83(3), 329–343.
Vijay, R., Ramya, S. S., Pujari, P. R., & Mohapatra, P. K. (2013). Spatial and temporal assessment of groundwater quality in Puri City, India: A statistical analysis. Asian Journal of Water, Environment and Pollution, 10, 51–58.
Voltaggio, M., Spadoni, M., Sacchi, E., Sanam, R., Pujari, P. R., & Labhasetwar, P. K. (2015). Assessment of groundwater pollution from ash ponds using stable and unstable isotopes around the Koradi and Khaperkheda thermal power plants (Maharashtra, India). Science of the Total Environment, 518–519, 616–625. https://doi.org/10.1016/j.scitotenv.2015.02.083.
Yang, Y., Wang, C., Guo, H., Sheng, H., & Zhou, F. (2012). An integrated SOM-based multivariate approach for spatio-temporal patterns identification and source apportionment of pollution in complex river network. Environmental Pollution, 168, 71–79. https://doi.org/10.1016/j.envpol.2012.03.041.
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Ghahremanzadeh, H., Noori, R., Baghvand, A. et al. Evaluating the main sources of groundwater pollution in the southern Tehran aquifer using principal component factor analysis. Environ Geochem Health 40, 1317–1328 (2018). https://doi.org/10.1007/s10653-017-0058-8
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DOI: https://doi.org/10.1007/s10653-017-0058-8