Freely dissolved OCPs and PCBs
Sampling rates (Rs) for water passive samplers are given in (Table S2). The value of sampling rate for polyethylene passive water samplers were ranging from 7.4 to 91 L/day at all sampling sites. These values of sampling rate are consistent with the sampling rate of study done from water at wetland mountain sites of S-SE Brazil (Meire et al. 2016). Rs value for Hyderabad site (S-15) of low-lying zones (LLZ) showed highest values (91 L/day) while Gilgit site (S-2) of frozen mountain zones (FMZ) showed low sampling rate i.e., 1.0 L/day.
Freely dissolved OCPs levels ranged from 34-1600 pg/L throughout Indus River as shown in Table 1 & Fig. 1. Among the studied OCPs, DDTs (0.48–220) were dominated, followed by endosulfan (0.20–14), HCBs (0.23–6.4), chlordane (0.09–4.58) and HCH (BDL-2.64). p,p′-DDE accounted for higher frequency among the studied OCPs at most of studied site locations. In contrast, trans nonachlor (0.09 pg/L) was among the less frequently detected pesticide into the surface water of the Indus River. The freely dissolved levels of OCPs in various zones showed the trends as follows; Alluvial Riverine zone (ARZ) ranged from (19.28–259.7 pg/L) > Frozen mountain zone (FMZ) (2.77–201.8 pg/L) > Low lying zone (LLZ) (1.67–58.05 pg/L) and > Wet mountain zone (WMZ) (1.35–42.24 pg/L) in descending order, respectively. The concentrations OCPs measured at WMZ and FMZ are in accordance with those of reported in water of Glacial-fed lakes, Ice melting-fed lake and Rain-fed lake in remote alpine lakes located in Himalayas, Pakistan (Nawab et al. 2020) and valley of Kashmir (Ullah et al., 2019). The current OCPs values are much lower than those detected from the previously studied surface water samples from River Chenab (Eqani et al. 2012b), and River Ravi, Pakistan (Baqar et al. 2018). The previously reported high levels from Pakistan may be due to use of outdated sampling/analytical techniques, which resulted into overestimated values of studied OCPs and PCBs. In previous studies conducted at Pakistan, the authors (Baqar et al. 2018, Eqani et al. 2012b) documented the active water sampling followed by the liquid-liquid extraction method, which reflected both dissolved and suspended particulate material associated POPs level.
Table 1
Freely dissolved OCPs (pg/L) from the four different studied zones along the Indus River, Pakistan.
Freely Dissolved OCPs
(pg/L)
|
|
Studied Zone
|
Overall
|
FMZ
|
WMZ
|
ARZ
|
LLZ
|
HCBs
|
Mean ± Std
|
2.89 ± 2.06
|
0.50 ± 0.22
|
3.11 ± 0.63
|
0.45 ± 0.31
|
2.26 ± 1.77
|
|
Min-Max
|
0.71–6.41
|
0.34–0.66
|
2.62–3.98
|
0.23–0.67
|
0.23–6.41
|
γ-HCH
|
Mean ± Std
|
<BDL
|
<BDL
|
0.66 ± 1.32
|
<BDL
|
0.19–0.71
|
|
Min-Max
|
<BDL
|
<BDL
|
0-2.64
|
<BDL
|
0-2.64
|
Transchlordane
|
Mean ± Std
|
0.19 ± 0.30
|
0.51 ± 0.72
|
1.03 ± 0.76
|
0.34 ± 0.17
|
0.50 ± 0.58
|
|
Min-Max
|
<BDL − 0.65
|
0-1.02
|
0.22–2.05
|
0.22–0.46
|
0-2.05
|
Cischlordane
|
Mean ± Std
|
0.40 ± 0.64
|
<BDL
|
<BDL
|
0.17 ± 0.14
|
0.20 ± 0.44
|
|
Min-Max
|
<BDL − 1.42
|
<BDL
|
<BDL
|
0.06–0.27
|
0-1.42
|
Transnonachlor
|
Mean ± Std
|
0.18 ± 0.29
|
<BDL
|
0.59 ± 0.43
|
0.10–0.14
|
0.26 ± 0.36
|
|
Min-Max
|
0-0.69
|
<BDL
|
0.09–1.11
|
<BDL − 0.19
|
0-1.11
|
Dieldrin
|
Mean ± Std
|
<BDL
|
<BDL
|
4.61 ± 9.22
|
<BDL
|
1.32 ± 4.93
|
|
Min-Max
|
<BDL
|
<BDL
|
0-18.45
|
<BDL
|
0-18.45
|
α-Endosulfane
|
Mean ± Std
|
0.91 ± 1.53
|
6.41 ± 9.07
|
2.31 ± 1.16
|
1.27 ± 0.90
|
3.53 ± 0.94
|
|
Min-Max
|
<BDL − 3.69
|
<BDL − 12.83
|
0.80–5.22
|
<BDL − 1.80
|
0-12.83
|
Endosulfane Sulfate
|
Mean ± Std
|
0.26 ± 0.34
|
0.43 ± 0.61
|
0.30 ± 0.61
|
0.10 ± 0.14
|
0.27 ± 0.41
|
|
Min-Max
|
<BDL − 0.83
|
<BDL − 0.87
|
<BDL − 1.22
|
<BDL − 0.20
|
<BDL − 1.22
|
OP-DDE
|
Mean ± Std
|
1.35 ± 2.58
|
0.29 ± 0.41
|
4.67 ± 5.52
|
1.13 ± 1.59
|
2.11 ± 3.43
|
|
Min-Max
|
<BDL − 6.57
|
0-0.58
|
1.28–12.21
|
<BDL − 2.25
|
0-12.21
|
PP-DDE
|
Mean ± Std
|
29.31 ± 60.82
|
3.35 ± 4.74
|
50.14 ± 67.44
|
17.67 ± 24.63
|
29.89 ± 52.71
|
|
Min-Max
|
0.36-152.96
|
<BDL − 6.70
|
8.18-150.38
|
0.26–37.09
|
<BDL − 152.96
|
OP-DDD
|
Mean ± Std
|
1.74 ± 2.30
|
0.45 ± 0.63
|
3.52 ± 3.83
|
0.61 ± 0.77
|
1.90 ± 2.63
|
|
Min-Max
|
<BDL − 5.96
|
<BDL − 0.90
|
0.27–8.88
|
0.06–1.15
|
<BDL − 8.88
|
PP-DDD/OP-DDT
|
Mean ± Std
|
4.24 ± 5.04
|
0.65 ± 0.55
|
6.51 ± 7.79
|
1.58 ± 2.19
|
4.00 ± 5.33
|
|
Min-Max
|
0.16–12.75
|
0.27–1.04
|
0.63–17.43
|
0.04–3.13
|
0.04–17.43
|
PP-DDT
|
Mean ± Std
|
11.50 ± 13.46
|
1.84 ± 2.00
|
12.30 ± 15.96
|
5.31 ± 7.34
|
9.47 ± 12.20
|
|
Min-Max
|
0.29–34.75
|
0.42–3.25
|
1.46 ± 35.34
|
0.12–10.51
|
0.12–35.34
|
DDTs
|
Mean ± Std
|
48.14 ± 75.24
|
6.58 ± 8.33
|
77.13 ± 99.73
|
26.31 ± 36.53
|
47.37 ± 71.95
|
|
Min-Max
|
0.81-197.89
|
0.69–12.47
|
11.82-224.24
|
0.48–52.14
|
0.48-224.24
|
Historically, DDTs has been reported to be widely used OCPs for controlling the crop pests and malarial outbreaks in Pakistan (Eqani et al. 2012a, Malik et al. 2011). Along the Indus River, DDT and its metabolites (p,p′-DDE) were frequently detected as shown in Fig. 2a. The freely dissolved concentration of DDTs ranged from 0.48–224.2 pg/L. Moreover, the dissolved p,p′-DDE concentration ranged from 0.36–152.9 pg/L ( mean: 29) and consistent with already reported values of p,p′-DDE in Lake Erie (19 pg/L) (Blanchard et al. 2008). Other DDTs followed the occurrence order in descending order as; p,p′-DDT (0.12–35.34; mean: 9.47), p,p′-DDD/o,p′-DDT (0.04–17.43; 4.2), o,p′-DDE (0.6-12.21; 2.11) and o,p′-DDD (0.06–8.88; 1.90). Our DDTs levels are relatively higher than those of wetland mountain region of S-SE Brazil (0.2–0.3 pg/L) (Meire et al. 2016). (Schreiber et al. 2013) reported the analogous DDTs levels to current study, as dissolved p,p′-DDEs fraction in the upland surface water of the River Xanaes in the Central Argentina was measured as 70–340 pg/L. Nevertheless, various ratios between parent compound and their metabolites are reported into the literature, to track/fingerprint the possible sources, their age and usage patterns at specific areas/region (Jiang et al. 2009). It has been documented that dechlorination of DDTs may convert their isomers to its metabolites e.g., p, p′-DDT into p, p′-DDE in the presence of aerobic condition and reductively converted into the p, p′-DDD in the presence of anaerobic conditions (Zhang et al. 2006). Hence, DDT/(DDD + DDE) < 1, showed the historical usage of DDTs whereas value greater than unity indicated fresh/current usage (Gao et al. 2013, Jiang et al. 2009). In present study, p,p′-DDT /( p,p′-DDE + p,p′-DDD) value is lower than unity at most of the studied location with few exceptions included the sites of Swat, Hunza and Gilgit of FMZ, where DDTs diagnostic ratios indicating the current as well historical usage of this banned pesticide. Additionally, the values for the DDD/DDE ranging from 0.09–5.95 (with mean value of 0.65). Generally, all the sites showed the values below unity and reflected the aerobically degradation of DDTs in these areas, might be due to the frequent ploughing/crop cultivation in the agricultural field. In contrary, Hunza site showed the DDD/DDE as 5.95 and indicating that the DDT in the soil is metabolized in anaerobic environment, which can be explained by high organic matter contents and its microbial degradation in these forests covered areas. The o,p′-DDT/p,p′-DDT ratio has reported to assess the usage of dicofol as possible additional source of DDTs in the environment. The ratio of the o,p′-DDT / p,p′-DDT ranged from 0.2 to 0.3 in the technical DDT and is 7.0 ± 2.2 in dicofol (Qiu et al. 2005). In the current study, ratio of the o,p′-DDT / p,p′-DDT ranged from 0.23 to 0.98 and highlighted that the major usage of technical DDT in the Indus flood plain (Fig. S2).
Among the HCHs, γ-HCH contributed significantly among all dissolved HCHs and ranged between 0.20–2.34 pg/L. These trends for HCHs occurrence into the surface water of Indus water can be justified due to higher water solubility of γ-HCH. Moreover, lindane (containing 90% of γ-HCH) has also been reported to be used in current study areas (Eqani et al. 2012a, Eqani et al. 2012b) which resulted to find its way into the aquatic ecosystem through surface runoff. In contrary to this, other HCHs (β-HCH and α-HCH) have more affinity (Kow ~ 3.8 and 3.72) to bind/adsorb onto the surface of suspended particulate material and finally deposited into the bed sediments (Eqani et al. 2011). The value of HCHs were consistent with those values observed into the Great Lake (4 pg/L) (Khairy et al. 2014). The current values are lower than those detected from the surface water of River Chenab (Eqani et al. 2012b), and River Ravi, Pakistan (Baqar et al. 2018) and Chinese fresh water resources (Luo et al. 2004, Tang et al. 2008) and from Kolleru Lake, India (Sreenivasa Rao &Ramamohana Rao 2000). Nevertheless, freely dissolved chlordanes (trans-, cis-, and trans-nonachlor isomers) detected at many instances (> 50 % of total samples) along the Indus River. Concentrations of trans-chlordane were slightly higher than cis-chlordane and the ratio of TC/CC > 1 were taken generally to be indicative of recent usage of chlordanes. Trans-nonachlor (TN)/TC ratio in technical chlordane is reported as 0.42 and the ratio TN/TC is 0.52 in Indus River indicating the lower concentration of trans-nonachlor as compared to trans-clordane. The concentration of freely dissolved total chlordane (0.96 pg/L) into the Indus River is lower than those compared with the lake Erie (56 pg/L) (Khairy et al. 2014). In Pakistan, wide scale application of endosulfan have been reported for the crop protection, which cause variety of health abnormalities (Eqani et al. 2012a, Islam et al. 2018). In our study, ∑endosulphans ranged from BDL–12.83 pg/L as dissolved fraction throughout the Indus river. Among the various zones, WMZ (6.41 pg/L) showed higher concentration of dissolved endosulfan followed by ARZ (2.89 pg/L) > FMZ (0.91 pg/L) > LLZ (0.90 pg/L). In general, endosulphans compositional trends showed the dominance of endosulfan-I and endosulfan sulphates and reflected the current as well as aged use of this insecticide (Weber et al. 2010). However, our measured levels are much lower than those found in Pakistani water bodies (Ahad et al. 2006, Baqar et al. 2018, Eqani et al. 2012b) and in mountain water and snowpack sample of the Western USA National Park (44-1500 pg/L) (Blais et al. 1998, Blais et al. 2001). Similarly, HCB were also detected at most of the sampling sites throughout the studied stretch of the Indus River, Pakistan and its concentrations (pg/L) ranged as 0.23 to 6.41. The mean values of HCBs in various studied zones followed the trends as; ARZ (3.11 pg/L) followed by > FMZ (2.89 pg/L) > WMZ (0.50 pg/L) > LLZ (0.45 pg/L) in descending order. These HCB concentrations are consistent with the HCB concentration in the South Atlantic (1.9–3.3 pg/L), and South Pacific (0.4–0.8 pg/L) open water transects (Zhang &Lohmann 2010). However, these HCB values are relatively lower than those reported from River Chenab, Pakistan (0.29–87 ng/L and 0.43–87 ng/L during summer and winter seasons, respectively) (Eqani et al. 2012b). These concentration are also lower from the Baiertang waters, China and Yellow river, China (Luo et al. 2004, Tang et al. 2008) and from Kolleru Lake, India (Sreenivasa Rao &Ramamohana Rao 2000). Moreover, these HCBs concentration were also much lower as compared to the concentrations reported in the South American freshwater bodies i.e. 1000-10,000 ng/L (UNEP, 2002).
In Indus River water, total freely dissolved concentration (pg/L) of ∑21 PCBs measured at frozen mountain zone (FMZ) as 7.44–226 (average value: 95.36) followed by at wet mountain zone (WMZ) as 41.91–199 pg/L (120.54), at alluvial riverine zone (ARZ) 30.88–144.96 (82.02) and at low lying zone (LLZ) as 3.02–26.69 (14.86). The descriptive statistic of total concentration of freely dissolved ∑21 PCBs are given in Table 2. The occurrence trends of different PCBs homologues into Indus River follows the order as: tri-CBs (~ 29–71%) > penta-CB (~ 3–9%) > tetra-CB (~ 3–8%) > octa-CBs (~ 3–6%) > hexa-CBs (~ 2–3%) > hepta-CBs (~ 1–2%) (Fig. 2b). The present study has shown that levels of PCBs at FMZ, WMZ and ARZ were consistent with the levels reported for Lake Erie (52–330 pg/L) and Lake Ontario 110–190 pg/L (Anderson et al. 1999, Khairy &Lohmann 2013) and high-mid altitude remote areas of Himalayas, Pakistan (Nawab et al. 2020). The concentration of ∑21 PCBs (7.44–226) were relatively lower than those reported for River Chenab, Pakistan (Eqani et al., 2018), Minjiang Estuary, China (203.9–2473 ng/L) (Zhang et al. 2003), Tonghui River, China (31.58–344.9 ng/L) (Zhang et al. 2004) and Daya Bay, China (91.1–1355.3 ng/L) (Zhou et al. 2001). The current compositional profiles into Indus River complement the commercial PCBs formulation of arochlor-1242 -1260, -1262 and 1248 (Fig. S3). The ∑7dioxin like PCBs levels ranged from 0.07–0.81 pg/L (median: 0.35 pg/L) with higher value found into the urban areas of ARZ (nearby D.G Khan site) due to extensive urbanization and industrial activities in this region. Fingerprinting of these contaminants has suggested to be very important because of their tetrachlorodibenzo -p-dioxins (TCDDs) like carcinogenic properties (Eqani et al. 2012b, Zhao et al. 2006). WHO05-TEQs of the mono-ortho dioxins like PCBs (-105, -114, -118, and − 156) and non-ortho dioxin like PCBs (-77, − 126, -169) were calculated which ranged from 0.000009-0.000043 (median: 0.000012) and 0.000009-0.00032 (median: 0.00015) pg TEQ L− 1 into all samples (Table S5). Among the individual mono-ortho DL-PCBs and the non-ortho DL- PCBs, PCB-105 and − 169 contributed very significantly toward total calculated TEQs. Higher TEQs for mono-ortho DL-PCBs were calculated at ARZ followed by LLZ, FMZ and WMZ which showed the higher industrial activity at ARZ.
Table 2
Freely dissolved PCBs (pg/L) from the four different studied zones along the Indus River, Pakistan.
Freely dissolved PCBs
|
|
Studied Zones
|
Overall
|
FMZ
|
WMZ
|
ARZ
|
LLZ
|
PCB-8
|
Mean ± Std
|
1.85 ± 2.03
|
0.84 ± 0.92
|
2.27 ± 3.20
|
0.36 ± 0.08
|
1.61 ± 2.12
|
|
Min-Max
|
0.14–5.16
|
0.20–1.49
|
0.49–7.06
|
0.30–0.41
|
0.14–7.06
|
PCB-11
|
Mean ± Std
|
3.76 ± 4.00
|
5.08 ± 6.27
|
8.97 ± 9.61
|
1.41 ± 0.80
|
5.10 ± 6.17
|
|
Min-Max
|
0.29–9.42
|
0.65–9.51
|
1.04 ± 22.86
|
0.84–1.98
|
0.29–22.86
|
PCB-18
|
Mean ± Std
|
1.69 ± 1.90
|
0.89 ± 1.05
|
1.11 ± 1.09
|
0.24 ± 0.10
|
1.20 ± 1.42
|
|
Min-Max
|
0.23–4.76
|
0.14–1.63
|
0.48–2.75
|
0.17–0.31
|
0.14–4.76
|
PCB-28
|
Mean ± Std
|
2.48 ± 2.00
|
1.79 ± 2.53
|
4.81 ± 4.73
|
1.37 ± 1.28
|
2.89 ± 3.01
|
|
Min-Max
|
0.48–4.84
|
0.00-3.58
|
1.37–11.71
|
0.46–2.28
|
0.00-11.71
|
PCB-44
|
Mean ± Std
|
0.07 ± 0.14
|
0.03 ± 0.04
|
0.07 ± 0.14
|
0.01 ± 0.01
|
0.06 ± 0.11
|
|
Min-Max
|
<BDL − 0.35
|
<BDL − 0.06
|
<BDL − 0.29
|
<BDL − 0.02
|
<BDL − 0.35
|
PCB-66
|
Mean ± Std
|
0.7 ± 0.61
|
0.39 ± 0.55
|
1.83 ± 1.04
|
1.38 ± 1.69
|
1.07 ± 0.98
|
|
Min-Max
|
0.25–1.88
|
<BDL − 0.78
|
0.90–3.26
|
0.18–2.57
|
<BDL − 3.26
|
PCB-101
|
Mean ± Std
|
0.72 ± 0.51
|
1.19 ± 0.06
|
1.57 ± 0.84
|
0.09 ± 0.13
|
0.94 ± 0.73
|
|
Min-Max
|
<BDL − 1.47
|
1.14–1.23
|
0.49–2.49
|
0.00-0.18
|
0.00-2.49
|
PCB-123
|
Mean ± Std
|
<BDL
|
<BDL
|
0.07 ± 0.13
|
0.09 ± 0.12
|
0.03 ± 0.08
|
|
Min-Max
|
<BDL
|
<BDL
|
0.00-0.26
|
0.00-0.18
|
0.00-0.26
|
PCB-118
|
Mean ± Std
|
0.22 ± 0.15
|
<BDL
|
0.46 ± 0.19
|
0.43 ± 0.54
|
0.29 ± 0.26
|
|
Min-Max
|
<BDL − 0.43
|
<BDL
|
0.24–0.71
|
0.04 ± 0.81
|
<BDL − 0.81
|
PCB-105
|
Mean ± Std
|
0.08 ± 0.10
|
0.08 ± 0.11
|
0.08 ± 0.10
|
0.02 ± 0.02
|
0.07 ± 0.09
|
|
Min-Max
|
<BDL − 0.23
|
<BDL − 0.16
|
<BDL − 0.21
|
<BDL − 0.03
|
<BDL − 0.23
|
PCB-126
|
Mean ± Std
|
0.01 ± 0.02
|
<BDL
|
<BDL
|
<BDL
|
<BDL ± 0.01
|
|
Min-Max
|
<BDL − 0.06
|
<BDL
|
<BDL
|
<BDL
|
<BDL − 0.06
|
PCB-153
|
Mean ± Std
|
0.22 ± 0.29
|
0.20 ± 0.28
|
0.11 ± 0.22
|
0.03 ± 0.05
|
0.16 ± 0.23
|
|
Min-Max
|
<BDL − 0.63
|
<BDL − 0.40
|
<BDL − 0.44
|
<BDL − 0.06
|
<BDL − 0.63
|
PCB-138
|
Mean ± Std
|
0.21 ± 0.13
|
0.22 ± 0.31
|
0.44 ± 0.27
|
0.32 ± 0.45
|
0.29 ± 0.24
|
|
Min-Max
|
0.04–0.41
|
<BDL − 0.43
|
0.14–0.77
|
<BDL − 0.64
|
<BDL − 0.77
|
PCB-128
|
Mean ± Std
|
0.02 ± 0.05
|
<BDL
|
<BDL
|
<BDL
|
0.01 ± 0.03
|
|
Min-Max
|
<BDL − 0.12
|
<BDL
|
<BDL
|
<BDL
|
<BDL − 0.12
|
PCB-156
|
Mean ± Std
|
<BDL
|
<BDL
|
0.05 ± 0.15
|
<BDL
|
0.02 ± 0.08
|
|
Min-Max
|
<BDL
|
<BDL
|
<BDL − 0.30
|
<BDL
|
<BDL − 0.30
|
PCB-169
|
Mean ± Std
|
<BDL
|
<BDL
|
<BDL − 0.01
|
<BDL
|
<BDL
|
|
Min-Max
|
<BDL
|
<BDL
|
<BDL − 0.01
|
<BDL
|
<BDL − 0.01
|
PCB-187
|
Mean ± Std
|
0.58 ± 1.34
|
0.16 ± 0.23
|
0.06 ± 0.08
|
0.06 ± 0.09
|
0.30 ± 0.87
|
|
Min-Max
|
<BDL − 3.31
|
<BDL − 0.32
|
0.00-0.16
|
<BDL − 0.13
|
<BDL − 3.31
|
PCB-180
|
Mean ± Std
|
0.06 ± 0.06
|
0.14 ± 0.19
|
0.24 ± 0.19
|
0.10 ± 0.06
|
0.13 ± 0.14
|
|
Min-Max
|
<BDL − 0.14
|
<BDL − 0.27
|
<BDL − 0.42
|
0.06–0.14
|
<BDL − 0.42
|
PCB-170
|
Mean ± Std
|
0.04 ± 0.09
|
<BDL
|
0.02 ± 0.03
|
0.04 ± 0.06
|
0.03 ± 0.06
|
|
Min-Max
|
<BDL − 0.21
|
<BDL
|
<BDL − 0.06
|
<BDL − 0.09
|
<BDL − 0.21
|
PCB-195
|
Mean ± Std
|
1.07 ± 2.29
|
1.24 ± 1.75
|
1.22 ± 1.12
|
0.01 ± 0.01
|
0.98 ± 1.65
|
|
Min-Max
|
<BDL − 5.70
|
<BDL − 2.48
|
<BDL − 2.64
|
<BDL − 0.01
|
<BDL − 5.70
|
PCB-206
|
Mean ± Std
|
81.6 ± 91.72
|
108.30 ± 97.02
|
58.63 ± 38.50
|
8.92 ± 11,66
|
68.47 ± 72.19
|
|
Min-Max
|
3.54-219.15
|
39.70-176.91
|
20.53–93.01
|
0.67–17.16
|
0.67-219.15
|
∑PCBs
|
Mean ± Std
|
95.36 ± 92.7
|
120.54 ± 111.2
|
82.02 ± 51.90
|
14.86 ± 16.73
|
83.65 ± 76.83
|
|
Min-Max
|
7.44–226.40
|
41.91-199.17
|
30.88-144.96
|
3.02–26.69
|
3.02–226.40
|
Table 3
Chemical daily intake (CDI pg/person/day) of OCPs and PCBs through Oral and dermal exposure from surface water of Indus River.
Studied POPs
|
FMZ
|
WMZ
|
ARZ
|
LLZ
|
CDI oral
|
CDI dermal
|
CDI oral
|
CDI dermal
|
CDI oral
|
CDI dermal
|
CDI oral
|
CDI dermal
|
p,p′-DDD
|
8.26
|
0.02
|
1.26
|
0.003
|
12.65
|
0.03
|
3.07
|
0.007
|
p,p′-DDE
|
56.99
|
0.13
|
6.51
|
0.01
|
97.49
|
0.23
|
34.35
|
0.08
|
p,p′-DDT
|
22.36
|
0.05
|
3.57
|
0.008
|
23.91
|
5.82
|
10.32
|
0.02
|
γ-HCH/lindane
|
|
|
|
|
1.28
|
0.003
|
|
|
ΣChlordane
|
1.49
|
0.003
|
0.99
|
0.0024
|
3.15
|
0.0076
|
1.18
|
0.0045
|
ΣPCBs
|
185.42
|
0.45
|
233.33
|
0.57
|
159.48
|
0.38
|
28.89
|
0.07
|
PCA/MLR based source appointment for OCPs and PCBs in the surface water of Indus River
Principal component analysis/multiple linear regression (PCA/MLR) describes and identifies between the related and the unrelated source tracer and also percentage contribution from the various sites along the Indus River, Pakistan. PCR/MLR was performed on the data of OCPs and PCBs for individual metabolites of DDTs, HCHs and PCBs homologues (i.e., tri-CB, tetra-CB, penta-CB, hexa-CB, hepta-CB and octa-CB) using varimax rotation method (Fig. S7).
In frozen mountain zone (FMZ), the PCA extracted four components (explaining 33.33, 26.18, 23.80 and 13.02 variability, respectively) and also shown as Table S8. The PC-1 accounted for 33.33 % variance and highlighted the p,p′-DDD, o,p′-DDT, o,p′-DDE, and p,p′-DDE. In the past, DDTs were used for agricultural purposes and malarial control program and PCA-MLR has also indicated the historical as well as current illegally use of DDTs in agriculture and health sector in the studied area. Diagnostic ratios for DDTs in these areas has also indicated its fresh and/or aged uses of DDTs in these areas. Moreover, wet and dry deposition of atmospheric dust particles through the process of altitudinal fractionation can also justify the DDTs contamination in these areas (Khan et al. 2017, Sohail et al. 2018). Atmospheric DDT fallout into the freshwater ecosystem has also been reported worldwide as > 150 Kg ΣDDT dust borne contamination has been estimated to the Great Lakes, USA and which was due to wet and dry deposition (Hoff et al. 1996). The PC-1 also dominated by various polychlorinated biphenyles including octa-CB, hepta-CB and penta-CB, which reflected the long range dust borne PCBs contamination into this area (Eqani et al. 2012b). The PC-2 was accounted for 26.18% of the total variance and dominated by HCBs, hexa-CB and tri-CB. HCB act as intermediate product used in preparation of the OCPs and other industrial activities (Tolosa et al. 2010, Zhao et al. 2010). In the studies area, HCB might find their way into surface water via run off from contaminated soils and/or via dry and wet deposition of long range atmospheric particulate material. The PC-2 has also highlighted the hexa-CB and tri-CB and indicated the dry and wet deposition of long range atmospheric particulate material from surrounding countries (China and India and low-lying areas of Pakistan) into these high altitudinal areas as source of these pollutants. The presence of lower molecular weight PCBs can be linked through the gaseous deposition of these contamination via cold trapping process (Ali et al. 2017). The PC-3 accounted for 23.80 % of the total variance and dominated by octa and penta-CB, which are industrial chemicals used for paints, plastics, electronic goods such as capacitors and transformer oil and can present into these areas due to long term dust particles deposition from nearby regions. The PC-4 was accounted for 13.02 % of the total variance and dominated by p,p′-DDT and indicated fresh usage of DDTs in these areas.
PCA/MLR results for the wet mountain zone (WMZ) showed that only one factor explained > 90 % of the variation in data and highlighted the DDTs metabolites, HCBs and all CBs, originating from the common source. As mentioned earlier that lower Himalayans areas are historically receiving POPs/metals contaminated dust from Indus floodplain and low-lying areas, which build up POPs/metals levels in these areas and now in context of rapid urbanization these contaminants are continually emitting into the environment (Alamdar et al. 2016, Eqani et al. 2016). Moreover, rapid urbanization in these mountainous areas is also associated to various environmental problems and wide range of chemicals are being used in these areas for industrial purposes and emit PCBs and HCBs from painted surfaces, electrical appliances, plastics, PVC materials etc. (Khan et al. 2017, Sohail et al. 2018). DDTs emission in these areas may also be the consequence of urbanization and emitted via dry/wet depositional from nearby areas, where the usage of these chemicals are suspected for different purposes including malarial control, protection of timber and indoor environments (Ali et al. 2014, Nasir et al. 2014, Sohail et al. 2018). Moreover, historical usage of DDTs and presence of obsolete pesticide store and abandoned DDT factories in these areas may also contributed towards the high levels of its metabolites (DDD, DDE) and find its way into Indus river via surface run off (Sohail et al., 2018).
For the alluvial riverine zone (ARZ), two extracted components (PC-1 and PC-2) accounted 93 % of the total variance in the POPs data from the Indus River. PC-1 factor accounted 54.18 % of the total variance and was dominated by p,p′-DDE, followed by o,p′-DDE, p,p′-DDT, p,p′-DDD/o,p′-DDT, and o,p′-DDD and highlighted the current and/or aged usage of DDTs in these well-known agricultural areas. Moreover, hepta-CBs highlighted by PC1 and points the industrial activities in these areas, which resulted into contamination of Indus river via various local drains and posed several ecological risks to Indus river ecosystem. The PC-2 has accounted 39.28 % of the total variance and highlighted tri-CB, tetra-CB, penta-CB, octa-C and HCBs and reflected the industrial activities in these areas as major sources of these chemicals.
For the low-lying zone (LLZ), we considered PC-1 which explained more than 90% of the variance in data obtained from the Indus River and highlighted a mixed source containing of pesticides and electronics. Agricultural application of pesticides as well as industrial activities are the main reasons for the contamination of this zone. All districts included in LLZ zones are characterized by harsh climatic conditions (i.e. wind storms, high temperature, less vegetation cover and low rainfall) and historical agricultural background. Moreover, these low-lying areas are also receiving industrial, agricultural and urban waste from other parts of the country via local stream network and Indus river system, which may further flush out into Arabian sea or re-emitted through volatilization (Eqani et al. 2016).
Air-Water exchange gradients of OCPs and PCBs
In general, considering zone wise results of air-water exchange of OCPs, there were net deposition of DDT isomers (p,p/-DDT) and its metabolites at all studied zones, which might be due to its current illegal use in the region for crop protection and malarial control, and resulted into elevated levels of atmospheric OCPs and finally deposition into surrounding water bodies. However, few exceptions of net volatilization of DDTs metabolites into FMZ highlighted its re-emission from POPs repositories (via historical cold trapping) at various colder sites as also described by (Chen et al. 2008, Wania &Westgate 2008) and entered into Indus water via melt down of glaciers and ice masses located in the FMZ and WMZ and continually volatilizing into ambient air in these pristine areas (Nasir et al. 2014). This study implies that the trend of air-water exchange of PCBs is volatilization from water to the air at most of the sites. Considering zone wise results of air-water exchange of PCBs, there were net volatilization of all the different PCBs at the FMZ, WMZ and ARZ, which highlighted the re-emission of PCBs from POPs repositories (via historical cold trapping) at various colder sites (Chen et al. 2008, Daly &Wania 2005, Wania &Westgate 2008) and entered into Indus water via melt down of glaciers and ice masses located in the FMZ and WMZ and continually volatilizing into ambient air in these pristine areas. In case of ARZ, the industrial waste/effluent into Indus River are also significantly adding up levels of PCBs, which continually volatilizing into ambient air via temperature rise in summer season (Eqani et al. 2012b). However, net deposition at LLZ might be due to huge amount of industrial activities in the region and due to current usage.
Toxicity assessment due to OCPs and PCBs
Toxicity assessment showed that PCB and DDTs metabolites are well below the Criterion Continuous Concentration (CMC) and Criterion Continuous Concentration (CCC) values for all the studied zones (Table. S4). Similarly, none of the other OCPs isomers exceeded the established Maximum admissible concentrations (MAC) and Annual Average concentrations (AA) values by the European Council (Table. S4), suggesting low ecological risk associated with the levels of OCPs/PCBs into the Indus River. However, it is well known that these chemicals have potential to bioaccumulate due to their lipophilic characteristics (log Kow) and even at very low levels into the fresh water system, contributed significantly towards the total body burdens into the aquatic organisms (fish) and subsequent food chain and finally associated humans.
We calculated the chemical daily intake (CDI) estimates for the assessment of intake of chemicals via various routes (i.e., ingestion and dermal) contact into the associated human body. Using values of dissolved OCPs and PCBs in the Indus River, CDI (pg/person/day) for oral and dermal exposure for p,p′-DDD ranged from 1.26 − 12.65 and 0.003 − 0.03, for p,p′-DDE 6.51 − 97.49 and 0.01 − 0.23, for p,p′-DDT 3.51 − 23.97 and 0.008 − 5.82, for γ-HCH/lindane 1.28 and 0.003, for ΣChlordane 0.99 − 3.15 and 0.002 − 0.007 and for ΣPCBs 28.89 − 233.33 and 0.07 − 0.57 (Table. 3). The Hazard Quotient (HQ) for OCPs and PCBs exposure were taken by dividing the CDIs value with reference doses (RfoDs) and for cancer risk (CR) multiplying CDIs value by SFs (USEPA, 2011). In health risk assessment for human when HQ or HI > 1, is considered as benchmark for sub-chronic and chronic (non-carcinogenic) human health risk of OCPs/PCBs (USEPA, 2005). HI values (even less than unity) could be useful to estimate the water matrix contribution to develop non-cancer health risks, which along with the other sources (i.e. dust and diet) adding cumulative risk of OCPs/PCBs into the associated exposed population (USEPA, 2001). Furthermore, exposure to low-level of OCPs/PCBs (oral or dermal) by the drinking water may also result into carcinogenic effects into human which is an indicator for potential cancer risk (CR). If CR is greater than 10− 6 then CR exists in the exposed population due to OCPs/PCBs-contaminated water intake (US-EPA, 2005). The potential carcinogenic risk (CR) values for oral and dermal from FMZ ranged from 1.66 x 10− 10−5.96 x 10− 12 and 2.64 x 10− 13−6.8 x 10− 14, WMZ 1.73 x 10− 11−4.95 x 10− 12 and 1.07 x 10− 14−7.77 x 10− 14, ARZ 4.95 x 10− 12−4.34 x 10− 1 and 1.15 x 10− 12−5.80 x 10− 14 and for LLZ 1.63 x 10− 10−5.93 x 10− 12 and 1.22 x 10− 13−2.56 x 10− 14 for all studied OCPs. The carcinogenic risk (CR) for ΣPCBs 1.059 x 10− 9−9.13 x 10− 10 from oral exposure and 2.227 x 10− 12−4.2 x 10− 13 for dermal exposure. Although, it has been observed that their no/low known carcinogenic risk from both OCPs and PCBs through oral and dermal exposure of water from the different studied zone in Indus River (Fig. S5 & S6). Nevertheless, according to recent report describing the effects of toxic stimuli combinations on determination of safe exposure limits has been published and concluded that there is no reason to believe today that any of the Exposure Limits on potentially toxic stimuli that have been set by any of the regulatory agencies are fully protective against serious adverse health effects (Kostoff 2018). Moreover, this study highlighted the contribution of water matrix via non-carcinogenic and carcinogenic risk, which in addition to dust, soil and biota (diet), may pose several health problems to associated human population.