Heavy metal contamination and health risks assessment in soil-rice system irrigated with wastewater in northern Pakistan

doi:10.21203/rs.3.rs-5319547/v1

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Heavy metal contamination and health risks assessment in soil-rice system irrigated with wastewater in northern Pakistan

https://doi.org/10.21203/rs.3.rs-5319547/v1

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The study aimed to investigate the transfer of heavy metals from different wastewater flooding to the soil and consequently to plants in Northern Pakistan. Rice (Oryza sativa L.) was chosen due to its widespred consumption in the studied area. The concentration of different heavy metals (HMs) including cadmium (Cd), lead (Pb), copper (Cu), and zinc (Zn) were assessed in the irrigating water, the soil as well as in different parts of the plant (grain, shoot, and root) from various rice paddies. Health risk associated with these metals were evaluated using daily metal intake (DIM) and health risk index (HRI). Heavy metal concentrations varied across sampling locations, with Cd ranging from 0.1 and 0.49, Pb from 0.8 to 2.2, Cu from 4.2 to 18.2, and Zn from 7.0 to 25.1 mg/kg. DIM was found to be in the order of Zn < Cd < Cu < Pb while HRI was found to be below 1. The HRI was 0.612 and 0.533 for the adults and children, respectively. Cd was found to be in higher concentration than the suggested permissible limit. HMs concentration was higher (P < 0.05) in the soil and crops from paddy fields irrigated with contaminated water compared to the control site. The current study concluded that wastewater use for irrigation led to the accumulation of HMs in a higher concentration in rice grains, which consequently pose potential health risks to the consumers.

Daily metal intake

Heavy metals

Health risk assessment

Health risk index

Oryza sativa

Wastewater

Heavy metals (HMs) contamination is mainly due to certain anthropogenic activities including wastes from mining, industrial effluents, agricultural activities, and construction processes (Chandra et al. 2017; Zhu et al.2018). The most significant sources of HMs, which are directly affecting humans, are the improper disposal of the wastes and the overuse of pesticides and other chemicals in agriculture (Chen et al.2015; Zhao et al. 2012). Wastewater use for irrigation, in order to increase crop yield, is the principal source of contamination of agricultural soil (Raja et al.2015; Verma et al. 2015) The effluents from different industries are the rich source of toxic HMs and are the main contributor to HMs contamination in soils and crops (Mahmood, Malik,2014; Meng et al.2016). For assessing and monitoring HM pollution as a result of human activities, the soil is considered as an excellent medium because of being an important and primary dumping site (Govil, Krishna,2018; Pouyat et al.2015).

Most plants have natural capability to absorb and accumulate HMs in different parts, however, the uptake level and translocation varies from plant to plant and even for different cultivars of the same plant species (Hongjiang et al.2014; Zhou et al.2015). The absorption of HMs from the soil usually takes place through the roots of the plant, as the surface soil receives HMs from different anthropogenic over activities. The edible parts of the plants such as rice grains are responsible for the direct transfer of HMs to humans and consequently leading to different hostile effects and toxicological endpoints in them. HMs pollution is one of the most concerned issues on account of their persistence, bioaccumulation and biomagnification, and severe eco-toxic effects on humans, plants, and animals (Clemens, Ma,2016; Shahid et al.2017).

HMs enters into the human body through contaminated food crops, water, and dust inhalation (Mahmood, Malik,2014; Keshavarzi et al.2015). Food chain accounts for 70+% dietary intake of Cadmium (Cd) (Wagner 1993; Zaza et al.2015). Cd and Lead (Pb) are considered to be carcinogens and can lead to different health problems such as cardiovascular, kidney, bone, blood, and nervous diseases (Bonberg et al.2017; Chung et al.2017). Copper (Cu) and Zinc (Zn) is considered to be essential for normal physiology of the body but in excessive amount, they can be toxic to humans and animals, therefore, these metals are widely employed in health risk assessment and environmental monitoring studies (Pandey, Madhuri,2014; Prashanth et al.2015). Cultivating crops in HMs contaminated soil can lead to HMs uptake and their accumulation in various edible parts, subsequently leading to humans and animals upon consumption ( Verma et al.2015; Clemens, Ma,2016).

Rice (Oryza sativa L.) is a crucial source of Pb and Cd in Asia (Chen et al.2017; Ndong et al.2018). Therefore, the current study was undertaken to assess heavy metals including Cu, Cd, Zn, and Pb in rice, irrigating water, and soil samples from different parts of tehsil Adenzai, district Lower Dir, Khyber Pakhtunkhwa, Pakistan. The HMs in rice (Oryza sativa L.) was appraised, and the daily dietary exposures and health risk index via consumption of the contaminated rice were calculated for both adults and children of the local area.

2.1. Sampling Site

The current preliminary study was undertaken in summer 2015 (crop season), at district Lower Dir, Khyber Pakhtunkhwa, Pakistan (Fig. 1). Five different rice paddy fields, irrigated through various water sources, were selected. S1 (Site one) acted as a control, irrigated with clean groundwater, while the rest acted as experimental. The S2 (Site 2) was irrigated with the wastewater from the Swat river, S3 (Site three) were irrigated with water having marble wastes, S4 (Site four) were irrigated with red stone wastewater and white stone wastewater, whereas Site five (S5) was irrigated with sewage water.

2.2. Sampling

Soil samples were collected for HM analysis according to the method described by (Wu et al.2010). For each site, five samples were randomly collected, from topsoil to 20cm depth – representing the plow layer, using auger (steel). Samples were taken from mid of the fields, to avoid edge effects. The samples were mixed (for making one composite sample), air dried, mechanically ground, passed through steel made sieve mesh (2mm), and stored in Petri dishes for further analysis.

Rice plants of the same size and physiological age were collected from the specified sites and were washed with water (first with tap water and then with deionized water). The sub-samples (grain (dehusked), shoot, and root) were oven dried (70ºC, 24h), weighted, and ground to fine powder with a blinder. Water samples used for the irrigation in the selected sites were collected in clean polyethylene bottles, filtered, and were analyzed for the HMs.

2.3. Samples Analysis

The samples (soil and plant) were digested in the mixture of per-chloric acid, sulphuric acid, and nitric acid (0.5:1:5). Samples were kept in a 50ml flask, added with 6.5 ml tri-acid mixture, placed at 80ºC (hot plate) until the emergence of white fumes from the flask and complete digestion of the tissues of the plant (Liao et al.2016). The flasks were cooled down (room temperature) and were added distilled water to make volume up to 50ml. The filtered samples were analyzed through Atomic absorption spectrophotometer (Perkin Elmer USA, AAS-PEA-700).

2.4. Bioaccumulation Factor (BAF)

BAF (ratio of the concentration of HM in rice grains to corresponding soil), was calculated for quantifying the bioaccumulation effect of rice upon HMs uptake from soil (Cai et al.2015).

2.5. Enrichment Factor (EF)

The EF was calculated for observing the degree of soil contamination, and HM accumulation (both plants and soil) (Izah et al.2017).

EF = \(\:\:\frac{\:\left[\mathbf{M}\mathbf{e}\mathbf{t}\mathbf{a}\mathbf{l}\mathbf{s}\:\mathbf{c}\mathbf{o}\mathbf{n}\mathbf{c}\mathbf{e}\mathbf{n}\mathbf{t}\mathbf{r}\mathbf{a}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}\mathbf{s}\:\left(\mathbf{s}\mathbf{o}\mathbf{i}\mathbf{l}\right)\:\mathbf{a}\mathbf{t}\:\mathbf{c}\mathbf{o}\mathbf{n}\mathbf{t}\mathbf{a}\mathbf{m}\mathbf{i}\mathbf{n}\mathbf{a}\mathbf{t}\mathbf{e}\mathbf{d}\:\mathbf{s}\mathbf{i}\mathbf{t}\mathbf{e}\right]}{\:\left[\mathbf{M}\mathbf{e}\mathbf{t}\mathbf{a}\mathbf{l}\mathbf{s}\:\mathbf{c}\mathbf{o}\mathbf{n}\mathbf{c}\mathbf{e}\mathbf{n}\mathbf{t}\mathbf{r}\mathbf{a}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}\mathbf{s}\:\left(\mathbf{s}\mathbf{o}\mathbf{i}\mathbf{l}\right)\:\mathbf{a}\mathbf{t}\:\mathbf{u}\mathbf{n}\mathbf{c}\mathbf{o}\mathbf{n}\mathbf{t}\mathbf{a}\mathbf{m}\mathbf{i}\mathbf{n}\mathbf{a}\mathbf{t}\mathbf{e}\mathbf{d}\:\mathbf{s}\mathbf{i}\mathbf{t}\mathbf{e}\right]}\)

2.6. Approaches for Assessing Health Risks

Health risks were evaluated using Daily Intake of Metals and Health Risk Index via rice consumption.

2.6.1. Daily Intake of Metals

The DIM depends on two parameters, the concentration of metals in the food and its rate of daily consumption, and average body weight. The daily intake of contaminated rice was calculated by the following equation (Likuku, Obuseng, 2015; Hang et al.2009).

DIM = Cmetal × Cfactor × Dfood intake / Baverage weight

Where, C_metal represents HMs in the food source (rice, mg/kg), D_food represents a Daily intake of the food source (rice, g/person/day), while C_factor and B_{average weight} represent conversion factor (fresh weight to dry weight).

2.6.2. Health Risk Index (HRI)

Exposure to the HMs was through rice consumption. The HRI were considered separate for adults and children, as the exposure way changes age wise. An HRI value < 1 was considered to be normal, means there was no potential risk, but if its value was ≥ 1, then there was a potential risk. The HRI (ratio of daily metal intake (DIM) and oral reference dose (ORD) was calculated by using the following equation (Hang et al.2009; Tepanosyan et al.2017).

HRI = DIM ÷ ORD

ORD values (mg/kg of bw/day) are set to be 0.001, 0.0035, 0.04, 0.30 for Cd, Pb, Cu, and Zn respectively (USEPA 2009).

2.7. Statistical Analysis

The data (Mean ± S.D) were analyzed in Graph Pad Prism (V6.01) through ANOVA, followed by Tukey test. A p-value < 0.05 was considered as statistically significant.

3.1. pH, EC, and heavy metals in water

The highest pH was observed for S3 (marble wastewater) and the lowest for S5 (municipal wastewater) while the highest EC was observed for S5 (municipal wastewater) and the lowest for S1 (Groundwater, control) (Table 1). Cadmium was found to be higher than the suggested permissible limits. The highest concentration of Cd was observed for S5, while the lowest for S1. Similarly, the highest level of Pb was found to be in S4 (red stone and white stone wastewater), and Cu and Zn in S5 (Table 2).

Table 1

pH and EC (µS/cm) of the water samples, collected from the specified sites
	Sampling sites
	S1		S2		S3		S4		S5
	Range	Mean	Range	Mean	Range	Mean	Range	Mean	Range	Mean
pH	6.9–7.6	7.4 ± 0.21	6.7–7.8	7.6 ± 0.32	7.7–8.4	8.2 ± 0.29	7.6–8.2	7.9 ± 0.25	6.5–7.2	6.9 ± 0.19
EC	70.3-131.7	54.2 ± 10.4^c	89.2-172.8	72.3 ± 15.7^c	70.4-169.4	69.4 ± 12.3^c	104.4-234.5	104 ± 18.3^b	154-313.6	225.8 ± 22.3^a
Data is shown as Mean ± S.D.

Table 2

Concentration (µg/l) of HMs in the irrigation water used in the specified sampling sites
HMs	Sampling sites
	S1		S2		S3		S4		S5
	Range	Mean	Range	Mean	Range	Mean	Range	Mean	Range	Mean
Zn	59.5-110.8	90.6 ± 10.5^d	90.5-170.3	140.4 ± 28.7^c	130.4-201.9	190 ± 11.9^b	171-245.8	211.5 ± 12.8^a	177-271.6	231.5 ± 20.8^a
Cu	38.8–54.9	40.5 ± 15.8^d	8.91–15.30	12.8 ± 6.7^e	58.4–97.5	80.3 ± 22.7^c	150.5-240.4	210 ± 10.6^b	169-280.4	260.3 ± 15.6^a
Pb	20.3–41.7	30.2 ± 6.7^e	50.3–90.1	75.1 ± 20.6^c	79.3-138.8	110 ± 30.2^b	120.6-200.4	171.2 ± 23.8^a	20.9–58.6	40.4 ± 5.3^d
Cd	6.71–10.4	8.0 ± 4.5^d	8.4–16.3	13 ± 5.5^c	11.4–21.7	15.3 ± 6.2^c	14.3–25.2	17.7 ± 10.3^b	27.2–41.5	34.2 ± 12.3^a
Data is shown as Mean ± S.D. Different letters in rows show significant difference at P < 0.05

3.2. pH, EC and heavy metals in soil

The pH and EC of the contaminated soil samples were found higher than the control. The highest pH values were observed in S4 (red stone and while stone wastewater) followed by S3 (marble wastewater), and the lowest in S5 (municipal wastewater), while the highest EC was observed in S5 and the least EC in S1 (Table 3). The heavy metals were found to be in the order of Cd < Pb < Cu < Zn. The highest concentration of Cd was observed in S4 and the lowest in S1 (groundwater, control), while the highest level of Pb, Cu and Zn was observed in S5. The lowest concentration of Cu and Zn was found in background soil sample. The concentration of HMs observed in the soil samples is given in Table 4.

Table 3

pH and EC of the soil samples, collected from the specified sampling sites
	Units	Sampling sites
		S − 1		S – 2		S − 3		S − 4		S − 5
		Range	Mean	Range	Mean	Range	Mean	Range	Mean	Range	Mean
pH	------	6.7–7.8	7.5 ± 0.6	6.3–7.4	7.2 ± 0.8	7.7–8.1	7.8 ± 0.3	7.6–8.2	7.9 ± 0.5	6.2–7.6	6.6 ± 1.1
EC	µS/cm	263–403	360 ± 70.3^d	487–732	561 ± 201^c	382–872	740 ± 54^b	345–757	651 ± 105^c	579–921	822 ± 92.2^a
Data is shown as Mean ± S.D.

Table 4

Concentration (µg/l) of HMs in the soil samples collected from the specified sites
HMs	Sampling sites										Background soil HMs concentration
	S1		S2		S3		S4		S5		Background soil HMs concentration
	Range	Mean	Range	Mean	Range	Mean	Range	Mean	Range	Mean	Range	Mean
Zn	22.3–55.8	32.0 ± 10.5^d	56.3-121.2	84.0 ± 18.5^c	61–131	93.0 ± 13.7^c	80.5-154.3	127.3 ± 14.5^b	130.4-223.2	189.4 ± 21^a	6.4–15.9	10.7 ± 3.2^e
Cu	3.9–15.2	10.6 ± 4.3^c	8.5–18.6	14.8 ± 4.5^c	11.4–32.6	25.8 ± 8.3^b	14.4–40.3	32.8 ± 10.8^a	13.6–32.3	20.6 ± 7.4^b	1.6–3.21	2.4 ± 1.2^d
Pb	2.6–5.2	4.2 ± 0.9^c	6.3–9.7	8.4 ± 2.3^b	6.6–14.3	12.8 ± 2.2^b	5.8–17.8	14.6 ± 4.4^b	6.5–25.7	18.8 ± 3.2^a	1.46–3.4	2.0± 0.5^c
Cd	0.31–0.63	0.44 ± 0.19^d	0.5–1.30	0.9 ± 0.14^d	0.7–1.8	1.4 ± 0.32^b	1.1–1.8	1.73 ± 0.7^a	0.74–1.6	1.2 ± 0.6^c	0.11–0.33	0.27 ± 0.12^e
Data is shown as Mean ± S.D. Different letters in rows show significant difference at P < 0.05

The concentration of the HMs in the soil samples were compared against the suggested permissible limits, set by European Union (EU 2002) and State Environmental Protection Administration (SEPA 1995), shown in Fig. 2. The concentration of Cd was found to be within the safe tolerable limit set by both EU and SEPA for S1, but the concentration was higher than the suggested tolerable limit for the soil samples, irrigated with wastewater. The concentrations the others metals were within the permissible limits suggested by EU and SEPA.

Pearson’s correlation was used to determine the association between the studied HMs among the soil samples. A significant (P < 0.5) positive correlation was observed between Cu-Cd, Pb-Zn while weak but statistically significant correlation was observed between Cd-Pb and Cu-Zn, as shown in Table 5.

Table 5

Correlation Coefficient Matrix for the HMs in soil samples
	Cd	Pb	Cu	Zn
Cd	1
Pb	0.293	1
Cu	0.924	0.388	1
Zn	0.753	0.835	0.744	1
Bold figures show a positive significant correlation at P < 0.05 (2tailed)

3.3. The concentration of heavy metals in rice

The concentrations of HMs were observed to be following the order of Zn > Cu > Pb > Cd in the roots and shoots of the plant. The concentration of these HMs was found to be higher in the rice samples from the contaminated sites, while the lowest HMs level was observed in the samples from the control site. Table 6 shows the concentration of HMs observed in the roots and shoots of the plant samples.

Table 6

Concentration (µg/l) of HMs in the roots and shoots of the plant samples
Sites	Cd		Pb		Cu		Zn
Sites	Roots	Shoots	Roots	Shoots	Roots	Shoots	Roots	Shoots
S1	0.32 ± 0.8^d	0.23 ± 0.11^c	3.4 ± 2.1^c	2.62 ± 1.8^c	7.2 ± 1.9^d	5.9 ± 2.2^c	21.08 ± 8.2^d	19.23 ± 4.2^d
S2	0.5 ± 0.21^c	0.38 ± 0.11^b	6.8 ± 2.1^b	4.6 ± 1.5^b	12.6 ± 1.3^c	9.7 ± 3.2^c	55 ± 10.3^c	40.39 ± 8.9^c
S3	1.02 ± 0.7^b	0.78 ± 0.51^a	8.6 ± 3.8^b	6.2 ± 0.9^a	21.4 ± 6.7^b	17.6 ± 1.5^a	39.28 ± 11^c	23.92 ± 5.1^d
S4	1.29 ± 0.5^a	0.94 ± 0.41^a	10.4 ± 2.1^b	7.4 ± 1.8^a	23.2 ± 2.1^b	21.2 ± 4.2^a	79.89 ± 12.8^b	59.94 ± 11.8^b
S5	0.9 ± 0.48^c	0.46 ± 0.13^b	15.4 ± 3.1^a	10.4 ± 2.2^a	17.7 ± 4.7^a	14.8 ± 2.1^b	128.34 ± 15.3^a	88.3 ± 16.4^a
Data is shown as Mean ± S.D. Different letters in rows show significant difference at P < 0.05

The grain is considered the most important part of rice, as it is directly consumed by humans. The HMs were observed to be in the order Zn > Cu > Pb > Cd in the grains of the rice samples across all sampling sites. The highest concentration of HMs was observed to be in the rice grains collected from the contaminated sites, while the lowest in the control site, irrigated with groundwater. Table 7 shows the level of HMs observed in the grains of rice.

Table 7

Concentration of HMs in the grains of the rice samples
Sites	Cd		Pb		Cu		Zn
Sites	Range	Mean	Range	Mean	Range	Mean	Range	Mean
S1	0.08–0.13	0.1 ± 0.03^d	0.7–0.9	0.8 ± 0.12^e	2.9–5.5	4.2 ± 0.12^c	2.9–11.5	7.03 ± 1.08^b
S2	0.11–0.25	0.18 ± 0.09^c	0.9–1.9	1.4 ± 0.7^c	12.8–14.1	8.9 ± 3.6^b	13.7–18.2	15.92 ± 3.19^a
S3	0.08–0.4	0.25 ± 0.2^b	1.2–2.5	1.83 ± 0.3^b	10.2–18.5	14.2 ± 3.86^b	10.2–27.7	18.89 ± 6.5^a
S4	0.47–0.51	0.49 ± 0.03^a	0.5–2.17	1.3 ± 0.8^c	17.4–20.2	18.25 ± 2.1^a	18.4–25.2	22.04 ± 4.8^a
S5	0.25–0.32	0.29 ± 0.05^b	1.1–3.4	2.2 ± 1.1^a	7.5–13.8	10.76 ± 4.4^f	19.5–29.7	25.1 ± 3.2^a
Data is shown as Mean ± S.D. Different letters in rows show significant difference at P < 0.05

The comparison of the HMs concentration was carried out with the standard allowable limits set by SEPA (SEPA 2005), FAO/WHO (FAO 2001) and Indian Standards (Awashthi 2000), shown in Table 8. The Cd concentration was found to be within the safer limits of SEPA for S1 (control, groundwater) and S2 (river Swat’s wastewater), but the samples from S3 (marble wastewater), S4 (red and white stones wastewater) and S5 (municipal water) were surpassing the limits of SEPA, although these were lying within the suggested limits of Indian standard. The concentration of Pb was found to be within the safer limit according to the standard limits of SEPA and Indian Standards but was higher than the limits suggested by WHO for S2, S3, S4, and S5. The concentration of Cu was within the permissible limits across all sampling sites, while the concentration of Zn was surpassing the standard limits as suggested by SEPA, WHO and Indian Standard for all the contaminated sites.

Table 8

Comparison of the studied HMs for the soil samples against the permissible limits
HMs	Sampling sites					Standards
HMs	S1	S2	S3	S4	S5	SEPA^a	Indian Std.^c	WHO^b
Zn	7.03	15.9	18.9	22.1	25.1	100	50	9.4
Cu	4.2	8.9	14.2	18.2	10.8	20	30	73.3
Pb	0.8	1.4	1.8	1.3	2.2	9	2.5	0.3
Cd	0.1	0.18	0.25	0.49	0.29	0.1–0.2	1.5	NA^d
^aSEPA (2005) ; ^cIndian standards (Awashti 2000); ^bFAO/WHO (2001); ^dNA = not available

Pearson correlation coefficient analysis of the HMs in the grains showed a strong significant (P < 0.05) positive correlation between Cu-Cd, and Zn-Pb, while a weak correlation was observed between Zn-Cu, Cd-Zn, Cu-Pb, and Cd-Pb, as shown in Table 9.

Table 9

Correlation Coefficient Matrix for the HMs in grain samples
	Cd	Pb	Cu	Zn
Cd	1
Pb	0.764	1
Cu	0.981	0.682	1
Zn	0.623	0.966	0.519	1
Bold figures show a positive significant correlation at P < 0.05 (2tailed)

3.4. Bioaccumulation and Enrichment Factors

The bioaccumulation factors (BAFs) is the transfer of HMs from the soil to edible parts of the plants such as grains of the rice. The BAF values were observed to be within the range of 0.13–0.22, 0.39–0.60, 0.09–0.19 and 0.18–0.28 for Zn, Cu, Pb, and Cd respectively. The BAF was higher for the contaminated sites as compared to the control site. The BAF for the HMs were observed to be the highest for Cu, followed by Cd and were following the order Pb < Zn < Cd < Cu. Figure 3 shows the BAFs for the studied HMs.

The enrichment factors (EFs) of Cd was 1.6, Pb was 2.1, Cu 4.4 and Zn was 2.9 for S1, while these metals were ranging from 3.3 to 6.4, 4.2 to 9.4, 6.1 to 13.6 and from 7.8 to 17.7 respectively in the contaminated sites (S2-S5). The EFs for the contaminated sites were higher than the control site. The highest EFs for Zn and Pb were observed in the samples from S5, while Cu and Cd in the samples from S4. The EFs were in the order of Cd < Pb < Cu < Zn. Figure 4 shows the EFs for the studied HMs. Figure 5 shows the EFs for the studied HMs across the sampling sites.

3.5. Potential Health Risks Assessment

The potential health risks were assessed by calculating the values for daily intake of heavy metals (DIM), health risk index (HRI) and total health risk index. The DIM values for both adults and children were calculated as both are changed from each other due to the level of rice consumption. The DIM values were found to be higher for both adults and children in the area from the polluted areas (S2-S5), where rice is grown using wastewater for irrigation. The highest DIM value was observed for Zn followed by Cu and the Pb. For the adult population, the DIM values (mg/kg/day) were in varying ranges for all the HMs such as 4.2E-03 to 1.5E-02 for Zn, 2.5E-03 to 1.1E-02 for Cu, 4.7E-04 to 1.3E-03 for Pb and 5.9E-05 to 2.9E-04 for Cd. For the children the DIM values (mg/kg/day) for Zn was ranging from 3.6E-03 to 1.3E-02, for Cu 2.2E-03 to 9.4E-03, Pb 4.1E-04 to 1.1E-03 and for Cd was ranging from 5.2E-05 to 2.5E-04. The DIM values followed the order Zn > Cu > Pb > Cd for both adults and children. The DIM values were in different ranges for the adults and children and were within the tolerable limits (Table 10).

Table 10

DIM values for the HMs for adults and children across the sampling sites
HMs	Individuals	Sampling sites					ORD
HMs	Individuals	S1	S2	S3	S4	S5	ORD
Cd	Adults	5.9 x 10^− 5	1.1 x 10^− 4	1.5 x 10^− 4	2.9 x 10^− 4	1.7 x 10^− 4	(1.0 x 10^− 3)^a
Cd	Children	5.2 x 10^− 5	9.3 x10^− 5	1.3 x 10^− 4	2.5 x 10^− 4	1.5 x 10^− 4	(1.0 x 10^− 3)^a
Pb	Adults	4.7 x 10^− 4	8.3 x 10^− 4	1.1 x 10^− 3	7.7 x 10^− 4	1.3 x 10^− 3	(3.5 x 10^− 3)^b
Pb	Children	4.1 x 10^− 4	7.2 x 10^− 4	9.4 x 10^− 4	6.7 x 10^− 4	1.1 x 10^− 3	(3.5 x 10^− 3)^b
Cu	Adults	2.5 x 10^− 3	5.3 x 10^− 3	8.4 x 10^− 3	1.1 x 10^− 2	6.4 x 10^− 3	(4.0 x 10^− 2)^a
Cu	Children	2.2 x 10^− 3	4.6 x 10^− 3	7.3 x 10^− 3	9.4 x 10^− 3	5.5 x 10^− 3	(4.0 x 10^− 2)^a
Zn	Adults	4.2 x 10^− 3	9.4 x 10^− 3	1.1 x 10^− 2	1.3 x 10^− 2	1.5 x 10^− 2	(3.0 x 10^− 1)^a
Zn	Children	3.6 x 10^− 3	8.2 x10^− 3	9.7 x 10^− 3	1.1 x 10^− 2	1.3 x 10^− 2	(3.0 x 10^− 1)^a
Daily Intake (DI, mg/kg/day), Oral reference dose (ORD, mg/kg/day); ^a[80] ^b[81]

The HRI was calculated for both adults and children, as shown in Table 11. The HRI was found to be higher for the consumers of contaminated sites than the control site. The highest HRI was observed for Pb (3.7E-01 for adults and 3.2E-01 for children) in S5. The HRI values for the adults were ranging from 1.2E-02 to 5.0E-02, 6.2E-02 to 2.7E-01, 1.3E-01 to 3.7E-01 and 6.0E-02 to 2.9E-01 for Zn, Cu, Pb, and Cd respectively. The HRI values for the children were ranging from 1.2E-02 to 4.3E-02, 5.4E-02 to 2.4E-01, 1.2E-01 to 3.2E-01 and 5.2E-02 to 2.5E-01 for Zn, Cu, Pb, and Cd respectively. The HRI values for the rice grown at contaminated sites were following the order of Zn < Cd < Cu < Pb. The HI values were 0.6115 and 0.5329 for adults and children respectively, from the rice consumption in the study area.

Table 11

HRI from HMs consumption via rice for adults and children across all sampling sites
HMs	Individual	Sampling sites					Mean
HMs	Individual	S1	S2	S3	S4	S5	Mean
Cd	Adults	6.0 x 10^− 2	1.1 x 10^− 1	1.5 x 10^− 1	2.9 x 10^− 1	1.7 x 10^− 1	1.6 x 10^− 1
Cd	Children	5.2 x 10^− 2	9.3 x 10^− 2	1.3 x 10^− 1	2.5 x 10^− 1	1.5 x 10^− 1	1.3 x 10^− 1
Pb	Adults	1.3 x 10^− 1	2.4 x 10^− 1	3.1 x 10^− 1	2.2 x 10^− 1	3.7 x 10^− 1	2.5 x 10^− 1
Pb	Children	1.2 x 10^− 1	2.1 x 10^− 1	2.7 x 10^− 1	1.9 x 10^− 1	3.2 x 10^− 1	2.2 x 10^− 1
Cu	Adults	6.2 x 10^− 2	1.3 x 10^− 1	2.1 x 10^− 1	2.7 x 10^− 1	1.6 x 10^− 1	1.7 x 10^− 1
Cu	Children	5.4 x 10^− 2	1.2 x 10^− 1	1.8 x 10^− 1	2.4 x 10^− 1	1.4 x 10^− 1	1.4 x 10^− 1
Zn	Adults	1.2 x10^− 2	3.1 x 10^− 2	3.7 x 10^− 2	4.3 x 10^− 2	5.0 x 10^− 2	3.5 x 10^− 2
Zn	Children	1.2 x 10^− 2	2.7 x 10^− 2	3.2 x 10^− 2	3.8 x 10^− 2	4.3 x 10^− 2	3.1 x 10^− 2
∑ HI	Adults	0.6115
∑ HI	Children	0.5329

The total health risk index (THRI) was calculated in order to evaluate the relative contribution of individual HMs to the THRI due to consumption of the rice, grown at contaminated soil and irrigated at wastewater (Fig. 4). The result of the THRI showed Pb as the major risk contributor across all sampling sites following by Cd and Cu. The Cumulative HRI was observed to be higher for the rice grown at contaminated sites (S2-S5) than the control site (S1). The mathematical sum of THRI for S1 were 0.28 and 0.22, for S2 were 0.51 and 0.44, S3 0.71 and 0.62, S4 0.82 and 0.72 and THRI for S5 were 0.75 and 0.65 for the adults and children respectively.

4.1. Heavy metals in water and soil

The results clearly suggested that HMs were in higher concentration in contaminated water (wastewater) as compared to control (groundwater). The reduced conditions in paddies may further increase the mobility of these metals into the plants. From the sources, these heavy metals are being accumulated in soil over the years. The concentrations of the selected HMs, except Cd, were within the permissible limits. The concentration of Cd was higher in contaminated sites as compared to the control site.

The higher concentration of Cd in water samples were attributed to the discharge of different wastewater effluents flowing to the irrigating water sources. The levels of other HMs in the water samples were under permissible limits and were in agreement to previous studies (Mahmood, Malik,2014; Nafees, Amin,2014; Sultan et al.2008). The electrical conductivity (EC < 4.0 dS/m) revealed that there is no salinity issue in the soil and the results were in accordance with previous studies (Ahmed et al.2008). The pH of the soil is considered as one of the most critical factors for determining concentrations of HMs in soil and its bioavailability and subsequent mobility to plants. The pH of the soil at contaminated sites was slightly affected by the wastewater sources. The effect of pH on HMs mobility was found to be highly uneven. The intensity of HMs mobilization might be affected by hydrogen ions in higher concentration. Zn and Pb were observed to be accumulated in higher concentration in grains, shoot and roots of the plants sown in S5 (municipal wastewater), where the pH was relatively low (6.1–7.6). The higher absorption of these HMs might be attributed to low pH or might be due to higher concentrations of HMs in the soil from the S5 site (municipal wastewater).

HMs concentrations were significantly higher in the soil irrigated with wastewater as compared to the control (irrigated with groundwater). Only Cd concentration was found higher than the permissible safe limits while concentration of the other HMs in the soil samples were found to be within the safe limits as suggested by the State Environmental Protection Administration, China (SEPA 2005), European Union,( EU 2002) and Indian standard (Awashthi 2000). The heavy metals were in wide ranges of concentrations in the study area. Apart from the use of wastewater for field irrigation, the higher concentration of Cd might also be due to the use of compost (natural fertilizer) containing Cd batteries. The other reasons for the higher Cd concentration might be the extensive use of phosphate fertilizers and Cd containing pesticides (Nafees et al.2009). The results regarding HMs concentration in the soil were in congruence to previous studies (Mahmood, Malik,2014; Khan et al.2013; Khan et al.2010). When both the agricultural soil and non-agricultural soil (reference) were compared, the concentration of HMs was higher in the agricultural soil. The main sources of HMs in the sampling sites were wastewater from marble industries, car wash centers, petrol pumps, restaurants/hotels, municipality, household discharged water, industrial emissions and different agricultural practices such as the use of synthetic fertilizers, manure, liming materials, sewage sludge and composts as a fertilizer (Ullah et al.2016). Manure (compost and sewage sludge) is use as the main source of organic fertilizer and was commonly employed in the studied area.

4.2. Heavy Metals in the grains, shoot, and the root of Oryza sativa

Variations in the HMs concentration in the rice plants may be due to multiple factors including the concentration of HMs in the soil of the paddies, irrigation water, and atmospheric deposition. Variance in HMs concentration is also associated with the difference in potential of the plants to absorb and accumulate HMs under different conditions (Pandey et al.2012). The concentration of HMs was found to be higher in roots, followed by shoots, while the least HMs concentration was observed in the grains. The study revealed the presence of HMs in the grains from all sampling sites. If not managed properly, this might be a cause of serious concern in the future.

The heavy metals lead to the soil from the wastewater sources and then drive to the root, which is then passed up to the shoot and grains. The HMs might also lead to the paddies from other sources including emission from vehicles, Pd discharged from storage batteries, fossil fuel, sewage pigments, and paints. A considerable amount of vehicles are in use in the study area, most of these vehicles are outdated, damaged, and release too much smoke. The smoke deposits in the atmosphere and pose a serious concern regarding HMs toxicity to the local masses, either through air pollution or leading to edible crops such as paddies.

The correlation matrix is used to measure the association between the logs of the concentrations of elements (Okoro et al. 2017). In the current study, a highly significant and positive correlation was observed between the pairs of elements in the samples (both soil and rice grains), which suggested that probably their origin is from a common source such as wastewater used for irrigation, and agrochemicals including nitrate and phosphate fertilizers.

4.3. Bioaccumulation and Enrichment Factor

The enrichment factor (EF) > 1 indicated a higher availability and dispersal of heavy metals in the soil, which may increase their chances of accumulation in different parts of the plant (Izah eet al.2017). EF of HMs depends on several aspects such as concentration and bioavailability of the HMs in the soil, the chemical nature of metal, and growth rate and uptake capability of plant species (Almasoud et al.2015; Balkhair, Ashraf,2016). The value of EF was found to be much higher than the previously reported studies which might be due to the higher concentration of the HMs in the irrigation water or reduced condition or the bio-fortification. The food chain (HMs transfer from soil to humans via plants) is one of the key pathways of human exposure to HMs. Through this chain, HMs are transferred from soil to humans (Zhuang et al.2009). Higher BAF indicated that this plant can absorb and accumulates HMs.

4.4. Health Risk Assessment

Rice is used as a stapled food in the study area, by people of all ages, can be a potential source of toxic HMs to the local masses and unfortunately, most of the paddy fields in the studied area were irrigated with wastewater. Our study presently revealed no apparent risks by consuming this HM contaminated rice; however, it indicates an alarming satiation for the future and might be a serious concern, as the paddies were regularly irrigated from the same wastewater sources. These results were in accordance to the previous studies conducted in neighboring countries including India (Satpathy et al.2014) and China (Zhou et al. 2015; Liu et al.2011). Depending on the level of consumption, contaminated food contributes about 70% of Cd intake in humans (Zhang et al.2017; Zia et al. 2017). The DIM value for Cd was higher for adults as compared to children, which might be due to the higher consumption rate of rice by the adults. However, the DI of Cd was found to be lesser than the tolerable DI (1.0E-03 mg/person/day). The DIM value for Cd was observed to be in accordance with the results of the previous studies (Mahmood, Malik,2014; Ullah et al.2016; Khan et al.2013). The lowest DIM value for Pb was observed for the control site, while the highest value was found for the contaminated site (S5). The DIM value for Pb was also found to be lower than the tolerable daily intake set for Pb (3.5E-03 mg/person/day). The observed Pb DIM value in the current study was in congruence to previous studies (Khan et al. 2013). Similarly, the DIM values for Cu and Zn were also found to be lower than the tolerable daily intake (4.0E-02 and 3.0E-01 respectively) and currently pose no health risk. The DI values for the studied HMS were in congruence to previous studies (Mahmood, Malik, 2014; Khan et al.2013).

However, the risk assessment based on health risk index (HRI) does not offer a quantifiable estimation of probability for an exposed population facing reverse health effects. Though it certainly provides a useful method for the determination of risk level through contamination exposure and several investigators contemplate the risk estimation technique trustworthy, and its validity and usefulness has been verified (Mahmood, Malik,2014; Sridhara et al. 2008; Jiang et al.2017). The only drawback of this method is that it is only used for the determination of health risk exposure via contaminated food consumed, while the exposure method including soil ingestion and dermal contact, and other factors including the presence of agrochemicals such as insecticides, herbicides, fungicides, and bactericides are not taken into consideration.

For calculating the HRI of HMs contamination, it is vital to find exposure intensity and the exposure route. To find HRI for heavy metals via consumption of contaminated rice (through oral exposure), it is important to neglect other exposure routes (Khan et al.2008). In the present study, the observed HRIs were falling into nontoxic limits (HRI < 1), apparently indicating no health risks via rice consumption (USEPA 1999; Muhammad et al.2011). However, the health risk index of Pb was found to be higher than the other HMs, which might be concern in the future. The HRIs for all the metals were observed to be higher than the previous studies (Liu et al. 2011; Khan et al.2013), revealing a serious concern regarding the local people which might be at risk, due to exposure to several HMs in combination. The total HRI is the mathematical sum of each individual metal’s HRI. The toxic effects and adverse outcomes of HMs (singly and in combination) are previously studied, more specifically the additive and interactive effect of two or more HMs (Hallenbeck 1993; Ricci, Rowe,2006). The HI values were 0.612 and 0.533 for the adults and children respectively, indicating poor health risk effects in the near future which might get worse on account of bio-accumulation and biomagnification of HMs over a specific time period.

It is concluded that HMs were present in the soil and water samples in the order of Cd < Pb < Cu < Zn. The concentration of Cd in the wastewater and soil samples was observed to be higher than the suggested permissible limits. HMs concentration was significantly higher in sampling sites, irrigated with wastewater as compared to the control site. Furthermore, a strong significant correlation was observed in HMs concentrations between soil and grains. Cd and Zn concentration was found higher, while Pb and Cu concentrations were within permissible limits. However, the risk assessment showed that there were no health-risks in the studied region for most HMs except Pb, which showed a high level of HRI (2.5E-01 and 2.2E-01 for adults and children, respectively). This high value of HRI might pose a potential health risk to the consumers. It is hence recommended that the rice grains from the contaminated sites should not be consumed without appropriate treatment. Regular analysis of HMs should be carried out in all food crops to appraise any health-risks, guarantee food-safety, and protect local masses from potential health risks. The Government and environmental protection agencies/organizations should properly plan future environmental management strategies. Strict environmental laws should be implemented to avoid and control HMs contaminations. Moreover, further deterioration of the soil should also be assured in order to ensure health risks free agricultural foods/crops consumption.

Ahmed, M.; Khattak, R. A.; Mohammad, D., Soil evaluation of Kafoor Dheri farm for crop production. Soil & Environ (2008), 27, (1), 43-51.
Almasoud, F. I.; Usman, A. R.; Al-Farraj, A. S., Heavy metals in the soils of the Arabian Gulf coast affected by industrial activities: analysis and assessment using enrichment factor and multivariate analysis. Arabian Journal of Geosciences (2015), 8, (3), 1691-1703.
Awashthi, S. K., Prevention of Food Adulteration Act (Act no. 37 of 1954) along with Central and State Rules (as amended for 1999). 3rd ed. New Delhi: Ashoka Law House. (2000).
Balkhair, K. S.; Ashraf, M. A., Field accumulation risks of heavy metals in soil and vegetable crop irrigated with sewage water in western region of Saudi Arabia. Saudi Journal of Biological Sciences (2016), 23, (1, Supplement), S32-S44.
Bonberg, N.; Pesch, B.; Ulrich, N.; Moebus, S.; Eisele, L.; Marr, A.; Arendt, M.; Jöckel, K.-H.; Brüning, T.; Weiss, T., The distribution of blood concentrations of lead (Pb), cadmium (Cd), chromium (Cr) and manganese (Mn) in residents of the German Ruhr area and its potential association with occupational exposure in metal industry and/or other risk factors. International Journal of Hygiene and Environmental Health (2017), 220, (6), 998-1005.
Bourliva, A.; Christophoridis, C.; Papadopoulou, L.; Giouri, K.; Papadopoulos, A.; Mitsika, E.; Fytianos, K., Characterization, heavy metal content and health risk assessment of urban road dusts from the historic center of the city of Thessaloniki, Greece. Environmental geochemistry and health (2017), 39, (3), 611-634.
Cai, L.-M.; Xu, Z.-C.; Qi, J.-Y.; Feng, Z.-Z.; Xiang, T.-S., Assessment of exposure to heavy metals and health risks among residents near Tonglushan mine in Hubei, China. Chemosphere (2015), 127, 127-135.
Chandra, R.; Yadav, S.; Yadav, S., Phytoextraction potential of heavy metals by native wetland plants growing on chlorolignin containing sludge of pulp and paper industry. Ecological engineering (2017), 98, 134-145.
Chen, H.; Teng, Y.; Lu, S.; Wang, Y.; Wang, J., Contamination features and health risk of soil heavy metals in China. Science of the Total Environment (2015), 512-513, 143-153.
Chen, Z.; Tang, Y.-T.; Yao, A.-J.; Cao, J.; Wu, Z.-H.; Peng, Z.-R.; Wang, S.-Z.; Xiao, S.; Baker, A. J. M.; Qiu, R.-L., Mitigation of Cd accumulation in paddy rice (Oryza sativa L.) by Fe fertilization. Environmental Pollution (2017), 231, 549-559.
Chung, C.-J.; Chang, C.-H.; Liou, S.-H.; Liu, C.-S.; Liu, H.-J.; Hsu, L.-C.; Chen, J.-S.; Lee, H.-L., Relationships among DNA hypomethylation, Cd, and Pb exposure and risk of cigarette smoking-related urothelial carcinoma. Toxicology and Applied Pharmacology (2017), 316, 107-113.
Clemens, S.; Ma, J. F., Toxic Heavy Metal and Metalloid Accumulation in Crop Plants and Foods. Annual Review of Plant Biology (2016), 67, (1), 489-512.
Defarge, N.; Spiroux de Vendômois, J.; Séralini, G. E., Toxicity of formulants and heavy metals in glyphosate-based herbicides and other pesticides. Toxicology Reports (2018), 5, 156-163.
EU, (European Union) Heavy Metals in Wastes (ENV.E.3/ETU/2000/0058). Denmark: European Commission on Environment, (2002).
FAO/WHO, Food additives and contaminants. In Codex Alimentarius Commis- sion. Joint FAO/WHO Food Standards Program, ALI-NORM 01/12A, (2001); pp 1–289.
Govil, P. K.; Krishna, A. K., Chapter 22 - Soil and Water Contamination by Potentially Hazardous Elements: A Case History From India. In Environmental Geochemistry (Second Edition), De Vivo, B.; Belkin, H. E.; Lima, A., Eds. Elsevier: (2018); pp 567-597.
Hallenbeck, W., Quantitative risk assessment for environmental and occupational health in Chelsea, (MI)7 Levis. . (1993).
Hang, X.; Wang, H.; Zhou, J.; Ma, C.; Du, C.; Chen, X., Risk assessment of potentially toxic element pollution in soils and rice (Oryza sativa) in a typical area of the Yangtze River Delta. Environmental Pollution (2009), 157, (8), 2542-2549.
Hongjiang, Z.; Xizhou, Z.; Tingxuan, L.; Fu, H., Variation of cadmium uptake, translocation among rice lines and detecting for potential cadmium-safe cultivars. Environmental Earth Sciences (2014), 71, (1), 277-286.
Islam, M. S.; Ahmed, M. K.; Raknuzzaman, M.; Habibullah-Al-Mamun, M.; Kundu, G. K., Heavy metals in the industrial sludge and their ecological risk: A case study for a developing country. Journal of Geochemical Exploration (2017), 172, 41-49.
Izah, S. C.; Bassey, S. E.; Ohimain, E. I., Geo-accumulation index, enrichment factor and quantification of contamination of heavy metals in soil receiving cassava mill effluents in a rural community in the Niger Delta region of Nigeria. Molecular Soil Biology (2017), 8, (2), 7-20.
Jaishankar, M.; Tseten, T.; Anbalagan, N.; Mathew, B. B.; Beeregowda, K. N., Toxicity, mechanism and health effects of some heavy metals. (2014), 7, (2), 60.
Jan, F. A.; Ishaq, M.; Khan, S.; Ihsanullah, I.; Ahmad, I.; Shakirullah, M., A comparative study of human health risks via consumption of food crops grown on wastewater irrigated soil (Peshawar) and relatively clean water irrigated soil (lower Dir). Journal of Hazardous Materials. (2010), 179, (1), 612-621.
Jiang, Y.; Chao, S.; Liu, J.; Yang, Y.; Chen, Y.; Zhang, A.; Cao, H., Source apportionment and health risk assessment of heavy metals in soil for a township in Jiangsu Province, China. Chemosphere (2017), 168, 1658-1668.
Keshavarzi, B.; Tazarvi, Z.; Rajabzadeh, M. A.; Najmeddin, A., Chemical speciation, human health risk assessment and pollution level of selected heavy metals in urban street dust of Shiraz, Iran. Atmospheric Environment (2015), 119, 1-10.
Khan, A.; Javid, S.; Muhmood, A.; Mjeed, T., Heavy metal status of soil and vegetables grown on peri-urban area of Lahore district. Soil and Environ. (2013), 32, (1), 49-54.
Khan, K.; Lu, Y.; Khan, H.; Ishtiaq, M.; Khan, S.; Waqas, M.; Wei, L.; Wang, T., Heavy metals in agricultural soils and crops and their health risks in Swat District, northern Pakistan. Food and Chemical Toxicology (2013), 58, 449-458.
Khan, S.; Cao, Q.; Zheng, Y. M.; Huang, Y. Z.; Zhu, Y. G., Health risks of heavy metals in contaminated soils and food crops irrigated with wastewater in Beijing, China. Environmental Pollution (2008), 152, (3), 686-692.
Khan, S.; Rehman, S.; Khan, A. Z.; Khan, M. A.; Shah, M. T., Soil and vegetables enrichment with heavy metals from geological sources in Gilgit, northern Pakistan. Ecotoxicol Environ Saf (2010), 73, (7), 1820-7.
Korre, A.; Durucan, S.; Koutroumani, A., Quantitative-spatial assessment of the risks associated with high Pb loads in soils around Lavrio, Greece. Applied Geochemistry (2002), 17, (8), 1029-1045.
Liao, J.; Wen, Z.; Ru, X.; Chen, J.; Wu, H.; Wei, C., Distribution and migration of heavy metals in soil and crops affected by acid mine drainage: Public health implications in Guangdong Province, China. Ecotoxicology and Environmental Safety (2016), 124, 460-469.
Ličina, V.; Akšić, M. F.; Tomić, Z.; Trajković, I.; Antić Mladenović, S.; Marjanović, M.; Rinklebe, J., Bioassessment of heavy metals in the surface soil layer of an opencast mine aimed for its rehabilitation. Journal of Environmental Management (2017), 186, 240-252.
Likuku, A. S.; Obuseng, G., Health risk assessment of heavy metals via dietary intake of vegetables irrigated with treated wastewater around Gaborone, Botswana. Proceedings of the International Conference on Plant. Marine and Environmental Sciences (PMES-2015), Kuala Lumpur, Malaysia (2015), 1-2.
Liu, J.; Zhang, X.-H.; Tran, H.; Wang, D.-Q.; Zhu, Y.-N., Heavy metal contamination and risk assessment in water, paddy soil, and rice around an electroplating plant. Environmental Science and Pollution Research (2011), 18, (9), 1623.
Liu, W.; Zhou, Q.; An, J.; Sun, Y.; Liu, R., Variations in cadmium accumulation among Chinese cabbage cultivars and screening for Cd-safe cultivars. Journal of Hazardous Materials (2010), 173, (1), 737-743.
Lu, Y.; Song, S.; Wang, R.; Liu, Z.; Meng, J.; Sweetman, A. J.; Jenkins, A.; Ferrier, R. C.; Li, H.; Luo, W.; Wang, T., Impacts of soil and water pollution on food safety and health risks in China. Environment International (2015), 77, 5-15.
Ma, Y.; Egodawatta, P.; McGree, J.; Liu, A.; Goonetilleke, A., Human health risk assessment of heavy metals in urban stormwater. Science of the Total Environment (2016), 557-558, 764-772.
Mahmood, A.; Malik, R. N., Human health risk assessment of heavy metals via consumption of contaminated vegetables collected from different irrigation sources in Lahore, Pakistan. Arabian Journal of Chemistry (2014), 7, (1), 91-99.
Meite, F.; Alvarez-Zaldívar, P.; Crochet, A.; Wiegert, C.; Payraudeau, S.; Imfeld, G., Impact of rainfall patterns and frequency on the export of pesticides and heavy-metals from agricultural soils. Science of the Total Environment (2018), 616-617, 500-509.
Meng, W.; Wang, Z.; Hu, B.; Wang, Z.; Li, H.; Goodman, R. C., Heavy metals in soil and plants after long-term sewage irrigation at Tianjin China: A case study assessment. agricultural water management (2016), 171, 153-161.
Muhammad, S.; Shah, M. T.; Khan, S., Health risk assessment of heavy metals and their source apportionment in drinking water of Kohistan region, northern Pakistan. Microchemical Journal (2011), 98, (2), 334-343.
Nafees, M.; Amin, A., Evaluation of heavy metals accumulation in different parts of wheat plant grown on soil amended with sediment collected from Kabul river canal. J. Agric. Res. (2014), 52, 3.
Nafees, M.; Mohammad Rasul Jan.; Hizbullah Khan.; Najma Rashid.; Fouzia Khani., Soil contamination in Swat valley caused by cadmium and copper. Sarhad J. Agric. (2009), 25, (1), 37-43.
Ndong, M.; Mise, N.; Okunaga, M.; Kayama, F., Cadmium, arsenic and lead accumulation in rice grains produced in Senegal river valley. Fundamental Toxicological Sciences (2018), 5, (2), 87-91.
Okoro, H. K.; Ige, J. O.; Iyiola, O. A.; Ngila, J. C., Fractionation profile, mobility patterns and correlations of heavy metals in estuary sediments from olonkoro river, in tede catchment of western region, Nigeria. Environmental Nanotechnology, Monitoring & Management (2017), 8, 53-62.
Pandey, G.; Madhuri, S., Heavy metals causing toxicity in animals and fishes. Research Journal of Animal, Veterinary and Fishery Sciences (2014), 2, 17-23.
Pandey, R.; Shubhashish, K.; Pandey, J., Dietary intake of pollutant aerosols via vegetables influenced by atmospheric deposition and wastewater irrigation. Ecotoxicology and Environmental Safety (2012), 76, 200-208.
Pouyat, R. V.; Szlavecz, K.; Yesilonis, I. D.; Wong, C. P.; Murawski, L.; Marra, P.; Casey, R. E.; Lev, S., Multi-scale assessment of metal contamination in residential soil and soil fauna: A case study in the Baltimore–Washington metropolitan region, USA. Landscape and Urban Planning (2015), 142, 7-17.
Prashanth, L.; Kattapagari, K.; Chitturi, R.; Baddam, V.; Prasad, L., A review on role of essential trace elements in health and disease. Journal of Dr. NTR University of Health Sciences (2015), 4, (2), 75-85.
Qing, X.; Yutong, Z.; Shenggao, L., Assessment of heavy metal pollution and human health risk in urban soils of steel industrial city (Anshan), Liaoning, Northeast China. Ecotoxicology and Environmental Safety (2015), 120, 377-385.
Quinteros, E.; Ribó, A.; Mejía, R.; López, A.; Belteton, W.; Comandari, A.; Orantes, C. M.; Pleites, E. B.; Hernández, C. E.; López, D. L., Heavy metals and pesticide exposure from agricultural activities and former agrochemical factory in a Salvadoran rural community. Environmental Science and Pollution Research (2017), 24, (2), 1662-1676.
Raja, S.; Cheema, H. M. N.; Babar, S.; Khan, A. A.; Murtaza, G.; Aslam, U., Socio-economic background of wastewater irrigation and bioaccumulation of heavy metals in crops and vegetables. Agriculture Water Management (2015), 158, 26-34.
Rastegari Mehr, M.; Keshavarzi, B.; Moore, F.; Sharifi, R.; Lahijanzadeh, A.; Kermani, M., Distribution, source identification and health risk assessment of soil heavy metals in urban areas of Isfahan province, Iran. Journal of African Earth Sciences (2017), 132, 16-26.
Ricci, P. F.; Rowe, M. D., Health and environmental risk assessment. Elsevier: (2013).
Rietra, R. P. J. J.; Mol, G.; Rietjens, I. M. C. M.; Ro; mkens, P. F. A. M. Cadmium in soil, crops and resultant dietary exposure; 1566-7197; Wageningen Environmental Research: Wageningen, (2017).
Satpathy, D.; Reddy, M. V.; Dhal, S. P., Risk Assessment of Heavy Metals Contamination in Paddy Soil, Plants, and Grains (Oryza sativa L.) at the East Coast of India. BioMed Res. Int. (2014), 2014, 11.
SEPA, (State Environmental Protection Administration). The Limits of Pollutants in Food. Beijing, China: State Environmental Protection Administration. (2005).
SEPA, Environmental quality standard for soils. In State Environmental Protection Administration, China. GB15618 –1995, (1995).
SEPA, Report on the State of the Environment in China 2005, State Environmental Protection Administration :China. (2005).
Shahid, M.; Dumat, C.; Khalid, S.; Schreck, E.; Xiong, T.; Niazi, N. K., Foliar heavy metal uptake, toxicity and detoxification in plants: A comparison of foliar and root metal uptake. Journal of Hazardous Materials (2017), 325, 36-58.
Singh, P. K.; Deshbhratar, P. B.; Ramteke, D. S., Effects of sewage wastewater irrigation on soil properties, crop yield and environment. Agricultural water management (2012), 103, 100-104.
Sridhara Chary, N.; Kamala, C. T.; Samuel Suman Raj, D., Assessing risk of heavy metals from consuming food grown on sewage irrigated soils and food chain transfer. Ecotoxicology and Environmental Safety (2008), 69, (3), 513-524.
Sultan Alam; Ahmad, S.; Bangash, F. K., Drinking Water Quality of Swat District. . J. Chem. Soc. Pak. (2008), 30, (1).
Sultana, M. S.; Rana, S.; Yamazaki, S.; Aono, T.; Yoshida, S., Health risk assessment for carcinogenic and non-carcinogenic heavy metal exposures from vegetables and fruits of Bangladesh. Cogent Environmental Science (2017), 3, (1), 1291107.
Tepanosyan, G.; Maghakyan, N.; Sahakyan, L.; Saghatelyan, A., Heavy metals pollution levels and children health risk assessment of Yerevan kindergartens soils. Ecotoxicology and Environmental Safety (2017), 142, 257-265.
Ullah, I.; Khan, A.; Rahim, M.; Haris, M. R. H. M., Health Risk from Heavy Metals via Consumption of Food Crops in the Vicinity of District Shangla. J. Chem. Soc. Pak. (2016), 38, (1), 177-185.
Ullah, S.; Hasan, Z.; Zuberi, A., Heavy metals in three commercially valuable cyprinids in the river Panjkora, district Lower Dir, Khyber Pakhtunkhwa, Pakistan. Toxicological & Environmental Chemistry (2016), 98, (1), 64-76.
US-EPA IRIS., United States Environmental Protection Agency. [cited Retrieved on 12 January 2016 Available from: from http://www.epa.gov/iris/substS. (2006).
USEPA, (United States Environmental Protection Agency), Guidance for Performing Aggregate Exposure and Risk Assessments, Office of Pesticide Programs, Washington, DC. 1999,. (1999).
USEPA, (US Environmental Protection Agency) Risk-based Concentration Table. Philadelphia PA: United States Environmental Protection Agency. Washington, DC, USA, (2009).
Verma, P.; Agrawal, M.; Sagar, R., Assessment of potential health risks due to heavy metals through vegetable consumption in a tropical area irrigated by treated wastewater. Environment Systems and Decisions (2015), 35, (3), 375-388.
Wagner, G. J., Accumulation of cadmium in crop plants and its consequences to human health. Advances in Agronomy (1993), 51, 173-212.
Wu, Y.-g.; Xu, Y.-n.; Zhang, J.-h.; Hu, S.-h., Evaluation of ecological risk and primary empirical research on heavy metals in polluted soil over Xiaoqinling gold mining region, Shaanxi, China. The Transactions of Nonferrous Metals Society of China (2010), 20, (4), 688-694.
Zaza, S.; de Balogh, K.; Palmery, M.; Pastorelli, A. A.; Stacchini, P., Human exposure in Italy to lead, cadmium and mercury through fish and seafood product consumption from Eastern Central Atlantic Fishing Area. ournal of Food Composition and Analysis (2015), 40, 148-153.
Zhang, Y.; Liu, P.; Wang, C.; Wu, Y., Human health risk assessment of cadmium via dietary intake by children in Jiangsu Province, China. Environmental Geochemistry and Health (2017), 39, (1), 29-41.
Zhao, H.; Xia, B.; Fan, C.; Zhao, P.; Shen, S., Human health risk from soil heavy metal contamination under different land uses near Dabaoshan Mine, Southern China. Science of the Total Environment (2012), 417-418, 45-54.
Zhou, H.; Zeng, M.; Zhou, X.; Liao, B.-H.; Peng, P.-Q.; Hu, M.; Zhu, W.; Wu, Y.-J.; Zou, Z.-J., Heavy metal translocation and accumulation in iron plaques and plant tissues for 32 hybrid rice (Oryza sativa L.) cultivars. Plant and soil (2015), 386, (1-2), 317-329.
Zhou, X.-M.; Zheng, N.-J.; Li, Y.-H.; Duan, J.-C.; Tan, J.-H.; Zhang, Y.-X.; He, K.-B.; Ma, Y.-L., [Chemical Characteristics and Sources of Heavy Metals in Fine Particles in Beijing in 2011-2012]. Huan Jing Ke Xue (2017), 38, (10), 4054-4060.
Zhu, D.; Wei, Y.; Zhao, Y.; Wang, Q.; Han, J., Heavy Metal Pollution and Ecological Risk Assessment of the Agriculture Soil in Xunyang Mining Area, Shaanxi Province, Northwestern China. Bulletin of Environmental Contamination and Toxicology (2018), 101, (2), 178-184.
Zhuang, P.; McBride, M. B.; Xia, H.; Li, N.; Li, Z., Health risk from heavy metals via consumption of food crops in the vicinity of Dabaoshan mine, South China. Science of the Total Environment (2009), 407, (5), 1551-1561.
Zia, M. H.; Watts, M. J.; Niaz, A.; Middleton, D. R. S.; Kim, A. W., Health risk assessment of potentially harmful elements and dietary minerals from vegetables irrigated with untreated wastewater, Pakistan. Environmental geochemistry and health (2017), 39, (4), 707-728.

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Heavy metal contamination and health risks assessment in soil-rice system irrigated with wastewater in northern Pakistan

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Abstract

Figures

1. Introduction

2. Materials and methods

2.1. Sampling Site

2.2. Sampling

2.3. Samples Analysis

2.4. Bioaccumulation Factor (BAF)

2.5. Enrichment Factor (EF)

2.6. Approaches for Assessing Health Risks

2.6.1. Daily Intake of Metals

2.6.2. Health Risk Index (HRI)

2.7. Statistical Analysis

3. Results

3.1. pH, EC, and heavy metals in water

3.2. pH, EC and heavy metals in soil

3.3. The concentration of heavy metals in rice

3.4. Bioaccumulation and Enrichment Factors

3.5. Potential Health Risks Assessment

4. Discussion

4.1. Heavy metals in water and soil

4.2. Heavy Metals in the grains, shoot, and the root of Oryza sativa

4.3. Bioaccumulation and Enrichment Factor

4.4. Health Risk Assessment

5. Conclusion

References

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