Contamination of sediments is one of the emerging environmental issues in India. In river systems, sediment contributes both as a source and a sink of heavy metals depending upon water chemistry, river flow, and the level of saturation relative to overlying water column. Sources such as urban discharge, industrial effluents, and agricultural runoff enhance sediment metal levels in receiving water bodies. In the present study, metal concentrations increased consistently down the study gradient and were highest at site 9. Seasonally, metal concentrations in general were highest in summer followed by winter and rainy season (Fig. 2a–h). In summer at site 1, concentrations of Fe, Zn, Ni, Mn, Pb, Cd, Cu, and Cr were 35,623.2, 61.7, 14.9, 282.1, 14.9, 1.3, 15.4, and 54.9 µg g−1, respectively. The respective concentrations at site 9 were 41,170.1, 92.5, 44.9, 43.0, 32.6, 71.1, 40.8, and 93.3 µg g−1. Concentrations at site 2 were almost comparable to the values observed at site 1. Sites 1 and 2 are located in city upstream and receive rural and suburban influences. Downstream sites with urban influences showed concentrations higher by 1.8- to 4.10-fold.
As the river flow declines in summer, the rate of sedimentation and consequently the concentration is enhanced. In rainy season, on the other hand, increased river flow causes a dilution effect, and consequently, metal concentration in sediment declines. Although at the onset of rainy season the first flush effect may enhance the concentration, the dilution effect predominates as the season progresses. When concentrations were regressed with river discharge, significant negative relationships observed, indicating that the increased river discharge (from an average 445 m3 s−1 in summer to over 10,744 m3 s−1 in rainy season) reduces metal concentration in rainy season. Higher concentrations in winter than rainy season (Fig. 2a–h) could be linked similarly to decreased river flow during winter. While these results are difficult to directly translate to a basin level causation, they highlight the importance of precipitation-linked runoff reducing monsoon season metal levels in Ganga River sediments. Similar seasonal patterns have been reported by Kumar et al. (2013). On spatial scale, a rising trend was observed along the pollution gradient irrespective of season (Fig. 2; Table 2). Mann–Kendall time series analysis with Sen’s slope statistics (Fig. 3a–h) showed significant seasonality and a rising trend along the study gradient, indicating the influence of local control. Such trend could be expected due to urban releases of sewage and industrial effluents together with agricultural runoff. Further, the atmospherically deposited substances also reach the river directly or indirectly through land surface runoff (Pandey et al. 2013). Highest concentrations of heavy metals at site 9 indicate a possible effect of these sources. Relatively sharp increase in the concentration of heavy metals, especially Mn and Cu at site 3, seemed to be due to wastewater, in addition to domestic and agricultural causation, flushed from Bhagwanpur sewage treatment plant (10 MLD) situated close to this study site. Further, Cu is an important component of pesticide entering to river through agricultural runoff.
The overall trend in metal concentration was found to be: Fe > Mn > Zn > Cr > Cu > Ni > Pb > Cd. Almost similar trend has been reported by Ghrefat et al. (2011) at Kafrain dam, Jordan. Iron (Fe) appeared the most abundant element in Ganga River sediment with mean concentration ranging from 21,924 to 41,170 µg g−1 (Table 2). Still higher ranges of Fe have been reported by Biksham et al. (1991) in Godavari River and Singh et al. (2005) in Gomati River receiving anthropogenic release. The Fe abundance in these systems has been attributed, in addition to weathering, erosion and other natural sources, large-scale human activities such as urban–industrial release, municipal solid waste, construction and demolition wastes, and agricultural activities. Concentration of Zn (41.1–92.6 µg g−1) was found lower than the values (86.1–708.8 µg g−1) reported in Almendares River, Cuba (Olivares-Rieumont et al. 2005), receiving industrial release and agricultural wastes (Romic and Romic 2003). Concentration of Pb reported in this study was comparable to those reported by Singh et al. (2005) in Gomti River. This metal is mainly associated with Fe–Mn oxide fraction and shows high retention in sediments. Domestic sewage, industrial effluents, and vehicular emissions are the major anthropogenic sources of Pb. Concentration of Ni remained below its baseline (46 µg g−1), indicating less polluted condition with respect to this metal. However, a comparison with WHO (2004) and USEPA (1999) threshold values of 20 and 16 µg g−1, respectively, indicates that a system with this concentration is considered as a polluted system. Ni is commonly used in household products such as stainless steel, nonferrous alloys, electroplating, Ni–Cd batteries, and coins and thus, there is ample chance of enhanced input of Ni from urban areas. Concentration of Cu at upstream sites matches with the category of unpolluted status; the values however were found to be higher than WHO norms at downstream sites. Copper is widely used in electrical wiring, roofing, and production of alloys, pigments, cooking utensils, and piping. Further, input of pesticides enhances copper from urban and agricultural areas. Concentrations of Mn although slightly lower than those recorded by Goorzadi et al. (2009) exceeded the USEPA guidelines (30 µg g−1). Cadmium was considerably high at all study sites due to urban–industrial and agricultural wastes. Rivers continuously receive trace amount of heavy metals from terrigenous sources such as weathering of rocks. Continuous or intermittent but relatively higher input of heavy metals to rivers and streams is linked to anthropogenic sources such as urban and industrial waste water, fossil fuel combustion, and atmospheric deposition (Sekabira et al. 2010; Pandey et al. 2013; Singh and Pandey 2014). Therefore, heavy metal concentrations in river sediments are used to reveal the history and intensity of local controls. Coupled with over 150 million liters per day (MLD) of untreated sewage entering to the river, sources such as diesel locomotive works, fabrics, textile and dye industries, small- and medium-scale metal industries, and glass and paint industries (DIP 2013) add contaminants to Ganga River. Heavy metals may be immobilized within the river sediments and thus could enter in absorption, co-precipitation, and complex formation processes or they may be co-adsorbed with other elements such as oxides or hydroxides of Fe and Mn. For instance, Cd in sediment remains associated with adsorbed, exchangeable, and carbonate (AEC) fraction, thus being weakly bound shows intermittent remobilization (Laxen 1985). On the other hand, Fe, Mn, Cr, and Ni remain in residual phase, while Cu as amorphous Fe oxyhydroxide phases (Sharmin et al. 2010).
Such urban–industrial sources described as above generate strong local control enhancing metal accumulation in sediments particularly from sites 4 to 9. Such enhancement measured in terms of percent enrichment indicates the amount by which a particular metal has increased from its baseline concentration or a reference value. Granulometry of sediment is an important aspect for understanding dispersion and mobility of heavy metals in river systems. Fine-grained particles act as an efficient scavenger and hence regulate transport and sediment accumulation of heavy metals in rivers and streams (Zonta et al. 1994; Sharmin et al. 2010; Mohiuddin et al. 2010). In the present study, the overall proportion of fine sand was found higher (>65 %) at all sites. However, at site 4 and downstream, proportions of fine sand were >80 %, indicating the possible association of fine-grained particles with high concentration of heavy metals. Percent enrichment appeared highest for Cu (71 %) and lowest for Mn (33 %) (Table 2
). Singh et al. (2005) showed a comparable enrichment of Cu and Mn in the sediment of Gomati River. We also calculated enrichment factor (EF) used to predict the level of contamination and possible anthropogenic impact on the sediment (Esen et al. 2010). A metal with EF between 0.5 and 1.5 is considered in a crustal state, whereas EF > 1.5 indicates anthropogenic disturbances (Zhang and Liu 2002). In this study, except for Cd and Pb, the EF remained <1, indicating relatively smaller enrichment (Table 2). A comparison of our data with Chen et al. (2007) indicates Cd at Rajghat (site 9) has moderate to severe enrichment, and at sites 4, 5, 6, and 7, it has moderate enrichment. Lead (Pb) at sites 5, 6, 7, 8, and 9 showed small to moderate enrichments. Ghrefat et al. (2011) and Singh et al. (2005) also showed high enrichment of Pb and Cd in sediments receiving anthropogenic influences. When compared with USEPA (1999) and CCME (1999) (Canadian Water Quality Guidelines for Protection of Aquatic Life), concentrations of all the metals except Zn, in most of the cases, were found higher than the threshold values (Table 3). Concentrations although remained below the world averages (Martin and Meybeck 1979) (Table 4) of Cd, Ni, Cu, and Cr did exceed WHO (2004) standards. Accumulation of Zn in Ganga River was found higher than those reported in Tapti River (Marathe et al. 2011), and Pb, Cu, and Cr were higher than those reported in Cauvery (Raju et al. 2012) and Euphrates River (Salah et al. 2012). These observations indicate relatively higher input of heavy metals in Ganga River in Varanasi region.
It was found that there exists positive correlation (R
2 = 0.31–0.93; p < 0.05–0.01) between organic carbon (OC) and study metals. Metal pairs such as Fe–Zn, Pb–Fe, Pb–Zn, Ni–Fe, Ni–Zn, Ni–Pb, Cd–Fe, Cd–Zn, Cd–Pb, Cd–Ni, Cd–Mn, Cr–Fe, Cr–Zn, Cr–Pb, Cr–Ni, and Cr–Cd also showed significant positive relationships (Table 5). Relationship with organic carbon indicates possible chelation (Jayaprakash et al. 2008) while those between metal pairs show common sources of origin or similarity in geochemical behavior. Similar observations have been made by Dhanakumar et al. (2011) and Kumar et al. (2013). Principal component analysis (PCA) was used to identify principal drivers regulating spatial and temporal distribution patterns of heavy metals in the river sediments. This multivariate technique analyzes the interrelations between explanatory variables and response variables and extracts principal drivers by reducing the contribution of factors with minor significance. The PCA ordinates segregated sites into four groups. Relatively less polluted sites such as Chunar, Adalpura, and Ramna appeared in one group (Fig. 4). Gadwa, which receives higher pollution input than the first three upstream sites, appeared separate from the rest of the sites. This site receives, in addition to surface-borne inputs, massive amount of atmospherically deposited materials from the bypass highway. The analysis separates Ravidas Ghat, Assi Ghat, Dashashwamedh Ghat, and Manikarnika Ghat as third group showing the influence of urban release in downstream contamination. The most polluted site Rajghat did appear separately indicating the influence of urban input and downstream factors.