Abstract
This study was conducted to investigate the impact of industrial activities on heavy metals status in wastewater, sludge and flora on the bank of selected main drains of the Hayatabad Industrial estate, Peshawar. Plants, sludge and wastewater samples of selected sites were collected and analyzed for heavy metals distribution; cadmium (Cd), chromium (Cr), lead (Pb) and zinc (Zn) levels. Bioconcentration factor (BCF) values were calculated for plants (Phalaris minor) grass species found naturally at all sites. The results showed that the levels of metals in wastewater were lower than permissible limits except Cd and the concentration of metals in plants and sludge were within permissible limits when compared to their respective standards. Metal distribution was in the following order; sludge > plants > wastewater and the concentration of metals varied according to the distance from the source with no specific pattern. Sludge samples for all sites showed a high concentration of metals as compared to plants and wastewater samples. In grass samples, Zn was highest and Cd was low for all sites. Metals accumulation in plants was in order of; roots > shoot. Pearson's coefficient correlation showed that Cr in plant roots and Zn in shoots showed significantly high correlation with Cd in sludge while Pb in roots showed significant negative correlation with Zn in sludge. BCF values for Cr, Pb and Zn were >1, showing the phytoremediation potential of plants.
Keywords: Heavy metals, Wastewater, Sludge, Phalaris minor, Bio-accumulation, Bioconcentration factor, Pollution indicator
Highlights
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In wastewater, Cadmium (Cd) exceeded the limits set for irrigation purpose.
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In sludge, the concentration of selected heavy metals was high in comparison with wastewater.
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Chemical characteristics of sludge correlated with wastewater quality.
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Phalaris minor accumulates heavy metals and can be used as pollution indicator and potential risk.
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Metals concentration in Phalaris minor was correlated with heavy metal contents of the sludge.
1. Introduction
Heavy metals occur naturally in soil, water, air and various organisms in low concentrations. If its level exceeds certain limits, it may cause a number of ecological and health problems [1,2]. Heavy metals are famous for toxicity, persistence in the environment (both abiotic and biotic components), non-biodegradable in nature and are of great concern [3,4]. Agriculture, development, population increase, urbanization, and industrialization are various causes that are continuous sources of heavy metal pollution in the environment [[5], [6], [7]].
Rapid industrialization has direct and indirect effects on the environment. Industries release harmful gases and toxic waste (solid and liquid) polluting the environment by affecting air, water and soil quality [[8], [9], [10]]. The presence of heavy metals in wastewater can greatly affect different segments of the environment. Sludge is the main source from where heavy metal can seep through water into an aquifer [11,12]. Wastewater containing heavy metals, if used for irrigation, can affect the soil properties and accumulate in soil and plants [13]. In order to understand the pollution level in the aquatic system, it is necessary to assess its distribution in various segments of the environment [14].
Sludge also contains microorganisms, organic matter, pathogens, pharmaceuticals, organic and inorganic pollutants depending upon the inputs in effluents (industrial and domestic wastewater) [15]. Zn, Hg, Pb, Cd, Cr, Ni and Cu are the main elements that restrict the use of sludge for land application as it contaminates ground water and soil, which in turn affects human health [16]. As it is a sink and source for different contaminants, it can provide useful information on heavy metals status and ecological risks related to them [17,18].
Over 400 species of plants have been identified as hyper accumulators as they can accumulate high concentrations of heavy metals [19]. The morphology of plants is a contributing factor in accumulating heavy metals [20]. Evaluation of heavy metals in plants is important as it indicates the pollution status of the site or soil and shows the ability of the plant to uptake and accumulate heavy metals [21]. Grasses, which can easily and quickly grow naturally, can be used to monitor pollution [22]. It is necessary to monitor toxic heavy metals in different environmental media to identify associated risk [23].
This study was conducted to find out heavy metals in wastewater and sludge and find out their association and correlation with heavy metals accumulated in the grass. The objective of this study was to investigate heavy metals concentration and distribution in different media; wastewater, sludge and plants of main drains.
2. Materials and method
2.1. Study area/sampling sites
The study was conducted to evaluate the contamination level of effluents of the Hayatabad Industrial estate (HIE), Peshawar. HIE, Peshawar was established in 1963 and covers an area of about 868 acres. It comprises 372 industrial units, of which 242 are functional [24]. Literature showed that industrial effluents from the industrial estate discharged in Budni Nala (main drain) which falls into the Kabul River, thus contaminating water bodies and affecting flora and fauna [25]. In order to monitor the impact of industrial effluents, different environmental media (wastewater, sludge and plants) were collected for analysis. For sampling, five main drains were selected. 4 (sampling sites: 1, 2, 3, 4) of these main drains received effluents (Organic and inorganic wastewater) from a cluster of different industries (steel, marble, wood, match, plastic, glass, rubber, mineral, leather, metal, paper, pharmaceutical and food) and the fifth drain (sampling site: 5) was located far away from industrial area as shown in Fig. 1, was selected as control. Geographical coordinates of main drains are; 33°58′51.9″N 71°25′46.7″E (site 1), 33°59′16.3″N 71°25′33.4″E (site 2), 33°59′40.7″N 71°25′24.4″E (site 3), 33°59′45.6″N 71°26′07.5″E (site 4) and 33°59′49.6″N 71°26′36.6″E (control) respectively.
Fig. 1.
Map showing drains, sampling areas and distribution of different industries contributing to main drains.
2.2. Samples collection and preparation
Wastewater samples were collected from 5 points of the main drains in clean plastic bottles, 24 grab samples were collected from each site at a 30 min interval and transferred to the laboratory immediately. In this way, 120 samples were collected and analyzed for different water quality parameters. The samples were analyzed for pH, EC, TSS, TDS and heavy metals according to standard methods. pH was measured using a PHS- 3C pH meter, for EC a digital conductivity meter was used, TDS and TSS were measured using gravimetric method. The wastewater samples were analyzed for heavy metals after filtration [26] using atomic absorption spectrometry (PerkinElmer AAS-700).
Sludge samples (1 kg) from each drain were collected in a clean bag with 3 replications from each site and taken to the laboratory for further analysis. The samples were air dried in the laboratory and sieved (63 μm mesh size). Debris and stone, if present, were removed. The samples were dried further in oven until no change in weight was observed. 1 g of sludge sample was digested using a mixture of 12 ml HNO3 and 4 ml HCl. The samples were boiled on a hot plate for 2 h and transferred to volumetric flasks and with deionized water volume was made up to 100 ml [27] and analyzed for heavy metals using atomic absorption spectrometry.
Phalaris minor, a grass species, was found commonly at all sample sites of the drain. Samples were collected from all sites and were stored in polyethylene bags. Samples were washed with tap water and rinsed with distilled water and dried in oven at 70 °C for 24 h. The samples were separated into roots and shoot and powdered. 0.5 g sample was transferred to 100 ml Pyrex digestion tube. 10 ml of acid mixture of 1:5 perchloric acid-nitric acid, was added to the sample and placed in a digester block. Starting from 100 °C temperature was gradually increased until dense white fumes appeared, the digestion was completed and, after cooling, deionized water was added to bring the volume to 50 ml. Each batch of samples for analysis also contained reagent blank (no sample) [28]. The plant samples (roots and stem) were analyzed for selected heavy metals (Cd, Cr, Pb and Zn) using atomic absorption spectrometry.
For determination of heavy metals (Cd, Cr, Pb, Pb), standard solutions of the analyte at different concentrations were prepared by diluting stock solution (1000 mg/l) for each element with deionized water. The quality was assessed by examining the linearity and slope of the calibration curve. Each sample was analyzed in triplicate to ensure the quality of data of samples for research. Blank and standard samples were digested and analyzed using the same procedure [26].
In order to ascertain their bioindicator value, the bioconcentration factor was calculated; BCF = [Metal]plant/[Metal]sludge, and to find out the ability of plants to remove heavy metals from the surrounding environment and accumulate them.
2.3. Statistical analysis
The correlation was calculated for properties of wastewater, heavy metals in wastewater, sludge and plants using Excel. Pearson's correlation coefficient was used to identify the relationship between metals concentration in plants and sludge, sludge and wastewater using SPSS 17.0 at p < 0.05.
3. Results and discussion
3.1. Physicochemical properties of wastewater
3.1.1. pH
pH values for mixed drains of industrial effluents and main drains ranged from 6.44 to 7.31. The lowest value was reported for site 1 and the highest was recorded for the control site (Table 1). In comparison with Pakistan National Environmental Quality Standards (Pak-NEQS) [29], the results of all 5 sites were found within permissible limits.
Table 1.
Physicochemical parameters of 5 main effluent drains of Hayatabad Industrial Estate, Peshawar.
| Sampling sites | pH |
EC |
TSS |
TDS |
||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min | Max | AVG | Min | Max | AVG | Min | Max | AVG | Min | Max | AVG | |
| 1 | 6 | 6.67 | 6.44 | 1600 | 1700 | 1627 | 38 | 510 | 271 | 785 | 846 | 813 |
| 2 | 6.01 | 7.49 | 6.64 | 1400 | 1500 | 1480 | 54 | 1664 | 469 | 703 | 980 | 819 |
| 3 | 6.66 | 7.1 | 6.92 | 1000 | 1000 | 1000 | 18 | 2946 | 901 | 486 | 660 | 560 |
| 4 | 6.53 | 6.87 | 6.72 | 1700 | 1900 | 1800 | 688 | 1524 | 1089 | 840 | 1183 | 942 |
| Control | 7.13 | 7.4 | 7.31 | 1200 | 1200 | 1200 | 310 | 394 | 347 | 574 | 799 | 673 |
| Pak-NEQSa | 6–10 | – | 150 mg/L | 3500 mg/L | ||||||||
Values represent maximum permissible limits of parameters according to Pak-NEQS (Pakistan National Environmental Quality Standards).
pH is the measure of acidity and alkalinity of water. It is an important factor as aquatic life and chemical reactions are affected by any change in it. It determines the quality of water and small changes in it make it unfit for use. pH at the control site (main drain) was reported high as compared to other sites. The results of this study are in contrast to a previous study conducted on combined drains of different industries of Hattar industrial estate, which revealed that pH of effluents was found between 4.6 and 10.9 (acidic to alkaline) and some of them exceeded permissible limits. This range was observed due to different sampling periods [30]. [31] reported similar results of pH for wastewater effluents of different industries. Toxicity and solubility of many substances depend on pH. At low pH many substances are readily available for adsorption as the solubility of insoluble substances increases [30,31].
3.1.2. Electrical conductivity (EC)
The EC for main drains ranged between 1000 and 1800 μS/m. The lowest value was found for the main drain of site 3 with a mean value of 1000 μS/m and the highest for site 4 with a mean value of 1800 μS/m (Table 1).
Electrical conductivity is the ability of water to conduct electric current which shows the concentration of ions and their mobility. Inorganic compounds tend to be good conductors of electricity as compared to organic compounds. Highest EC at site 4 is due to the combined effluents of all industries, resulting in an increase in salt concentration. The ion concentration is the result of dissolved solids mainly and at control site EC reduced to 1200 μS/m which might be due to the ions precipitation and settling. The results are supported by Ref. [32] work which showed a decrease in EC with the increase in distance from industries and with the change in total dissolved solids (TDS).
3.1.3. Total suspended solids (TSS)
Total suspended solids for the effluents ranged from 271 to 1089 mg/L. The lowest value was observed for main drain of site 1 (271 mg/L) and the highest value for main drain of site 4 (1089 mg/L) (Table 1).
When compared with [29] Pak-NEQ’S, the effluents of all 5 sites exceeded permissible limits. Highest TSS for site 4 may be due to collective industrial effluent. The highest values reported for site 3 were due to the effluents from marble industries as they carry solid particles after being used during the crushing process. Similar results were reported by Refs. [30,33] for high levels of TSS in effluents of different industries.
3.1.4. Total dissolved solids (TDS)
TDS of effluent for 5 different sites ranged between 560 and 942 mg/L. The lowest value was recorded for the main drain of site 3 and the highest for main drain of site 4 (Table 1). It is evident from the results that TDS for all sites were within limits.
Total dissolved solid is the measure of salinity in water. A high concentration of TDS changes its density, decreases the solubility of gases, affects aquatic organisms and, when discharged into water used for irrigation purpose, may cause salinity. As TDS values were in compliance with [29] Pak-NEQ’S, site 4 was high in TDS content. That may be due to the collective effluent of all contributing industries which resulted in high ion concentration in water. After a careful look, it seems that the steel re-rolling mill and the match industry are the main contributing industries. In the steel re-rolling mill, water is used to remove dust to treat blast furnace gas during smelting, as well as a cooling agent, while in the match industry, water is used during chemical mixing and washing of waste [24,34,35].
EC and TDS were significantly correlated (r = 0.990) which shows that TDS increased with increase in EC (Table 2). EC and TDS give values for ionic load and contaminants in water. TDS is mineral salt dissolved in water and EC is the ability of water to conduct electricity which depends upon the ionic strength of water thus, EC is a function of salt concentration. pH and EC (r = - 0.642), pH and TDS (r = - 0.573) showed moderate but negative correlation. An increase in one parameter resulted in a decrease in the other. pH depends on H+ and OH- ions concentration only, which comprises a small part of conductivity. There is a direct relation between EC and TDS, an increase in TDS results in an increase in EC. The end products of organic and inorganic compounds used in industries can affect pH, EC and TDS of effluents [36]. Metals, Na+, Ca2+, SO42−, Mg2+, HCO3− and K+ are contributing factors to high EC and TDS [37].
Table 2.
Correlation of physicochemical parameters in wastewater of HIE, Peshawar.
| pH | EC | TSS | TDS | |
|---|---|---|---|---|
| pH | 1 | |||
| EC | −0.642 | 1 | ||
| TSS | 0.015 | 0.099 | 1 | |
| TDS | −0.573 | 0.990 | 0.120 | 1 |
3.2. Heavy metals concentration in wastewater
The average concentrations of Cd, Cr, Pb and Zn for each site are given in Table 3. Cd concentration in wastewater samples ranged from 8 to 38 μg/L. The lowest value of Cd was observed for the control site and the highest for site 2 industries. The level of Cr in wastewater samples ranged from 40 to 254 μg/L. The lowest value of Cr was recorded for the control site and the highest for site 2. Pb ranged from 46 to 96 μg/L in wastewater. The lowest value for Pb was noted for control and the highest for site 2. Concentration of Zn ranged between 43 and 1355 μg/L. The lowest was recorded for control and higher for Site 4 (Table 3). Site 5 which receives wastewater from streams carrying contaminated water, showed low metal concentration is because of dilution effect. Dilution plays an important role in reducing/dispersing contaminants, due to mixing of these effluents with a large volume of water. At this point, the North nullah a natural transport system, which crosses the industrial estate. It helps in taking effluent away from industrial estate to Budhni nullah which joins Shah Alam and then eventually into Kabul river.
Table 3.
Heavy metal concentration in effluents of 5 main drains of Hayatabad Industrial Estate, Peshawar.
| Sites | Cd μg/L |
Cr μg/L |
Pb μg/L |
Zn μg/L |
||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min | Max | Avg | Min | Max | Avg | Min | Max | Avg | Min | Max | Avg | |
| 1 | 2 | 69 | 16 | 3 | 91 | 45 | 5 | 185 | 61 | 3 | 106 | 47 |
| 2 | 5 | 77 | 38 | 62 | 541 | 254 | 24 | 187 | 96 | 84 | 911 | 436 |
| 3 | 4 | 42 | 16 | 2 | 99 | 48 | 14 | 111 | 64 | 19 | 186 | 95 |
| 4 | 2 | 17 | 8 | 13 | 96 | 51 | 22 | 177 | 95 | 843 | 1904 | 1355 |
| Control | 1 | 19 | 8 | 15 | 71 | 40 | 11 | 99 | 46 | 12 | 84 | 43 |
| WHO/FAO limits (2007) [38] | 10 μg/L | 100 μg/L | 5000 μg/L | 2000 μg/L | ||||||||
| Pak-NEQSa [29] | 100 μg/L | 1000 μg/L | 500 μg/L | 5000 μg/L | ||||||||
Values represent maximum permissible limits of parameters according to Pak-NEQS (Pakistan National Environmental Quality Standards).
By comparing the results with [29] Pak-NEQS, wastewater samples were found within permissible limits for Cd, Cr, Pb and Zn. In comparison with FAO limits [38] for the use of wastewater for crop production, heavy metals concentration was within permissible limits except Cd which was recorded high for all sites and Cr for site 2. Contamination level in the 4 main industrial effluent drains and Cd use source can be attributed to steel, plastic, marble and metal plating industries. Average Cd concentration is recorded lowest as compared to Cr, Pb and Zn for all sites. Cr sources at site 1 can be attributed to steel, wood and food preservative industries. The order of heavy metals for all sites were different, which was due to the different industries. Metals concentration was lowest at control site, which may be due to high pH, as heavy metals at high pH are removed from water and adsorb to sediments. In this study, the control site showed the highest pH with an average value of 7.31 as compared to other 4 sites. Higher pH can remove heavy metals from water by precipitation process resulting in hydroxide formation and adsorb to sediments [39].
The results of this study are in line with the results of previous study [33] conducted on wastewater of marble, match, steel, pharmaceutical industries and main drain of HIE, Peshawar that showed Cd, Cr and Zn concentration in effluents of respective industries were within permissible limits when compared to Ref. [29] Pak-NEQS except for Pb in effluents of marble, match, steel and main drain exceeded limits [31]. reported high concentration of metals Cd, Cr, Pb and Zn in effluents of the match, paper mill, marble, woolen mill and glass industries when compared with [29] Pak-NEQS which is contrary to this study. Cd and Cr showed significant positive correlation (r = 0.946, p < 0.05) (Table 4). Similarly a positive correlation between Cd with Pb, Cr with Pb, and Pb with Zn suggest that these metals might have originated from the same source [40].
Table 4.
Correlation of heavy metals in wastewater of HIE, Peshawar.
| Cd | Cr | Pb | Zn | |
|---|---|---|---|---|
| Cd | 1 | |||
| Cr | 0.946 | 1 | ||
| Pb | 0.504 | 0.627 | 1 | |
| Zn | −0.144 | 0.073 | 0.773 | 1 |
3.3. Heavy metals concentration in sludge
The average concentrations of heavy metals in sludge samples of the five sites are presented in Table 5. Cd concentration was found in the range of 27–1101 μg/kg, the highest concentration was found at site 2 (1101 μg/kg). Cr concentration was found in the range of 622–4120 μg/kg; the highest concentration was found at site 1. Pb concentration in sludge ranged from 168 to 4901 μg/kg; the highest concentration of Pb (4901 μg/kg) was found at site 3. Zn concentration ranged from 1084 to 3337 μg/kg; the highest concentration was found at site 1 (Table 5). The results showed that metal concentration varied at each site and was recorded higher for site 1, 2, 3 and 4 which are main drains which directly receive industrial effluents as compared to control. Metals concentration in the sludge was compared with [41] permissible limits for metals in sludge and the values were within limits.
Table 5.
Heavy metals concentration μg/kg in sludge sample of HIE, Peshawar.
| Sampling sites | Cd μg/kg | Cr μg/kg | Pb μg/kg | Zn μg/kg |
|---|---|---|---|---|
| 1 | 1006 | 622 | 2788 | 3337 |
| 2 | 1101 | 2974 | 1132 | 2015 |
| 3 | 55 | 2101 | 4901 | 2029 |
| 4 | 1013 | 4120 | 1392 | 1621 |
| Control | 27 | 1045 | 168 | 1084 |
| USEPA, (2018) [39] | 39000 μg/kg | 1200000 μg/kg | 300000 μg/kg | 2800000 μg/kg |
The concentrations of heavy metals recorded in sludge samples were higher than wastewater, as heavy metals from water accumulate in sludge [42]. The reason might be adsorption of heavy metals to particles suspended in water which settle down and become a secondary source of contamination [43]. The order of heavy metals in sludge was not similar to that of wastewater. pH affects the heavy metals concentration in sludge. As pH increases, heavy metals precipitates due to hydroxide production and adsorbs to sediment [39]. Under slightly acidic pH, soluble Zn is found high and is mobile and bioavailable as compared to basic pH [44]. In this study, pH of wastewater ranged from 6 to 7.49, so the level of Zn was found high as compared to Pb, Cr and Cd in sludge in this study. As a by-product of wastewater treatment plant, the quality of sludge depends upon the chemical properties of wastewater and the treatment process involved [45]. Table 6, shows weak and moderate correlation of heavy metals in sludge samples. It can be assumed that moderate correlation might be due to metals originating from the same source or similar accumulation behaviour in sludge and the negative correlation may reflect similar behavior and competitive adsorption [43]. Similar results were also reported by Ref. [40] in sludge samples.
Table 6.
Correlation of heavy metals in sludge samples.
| Cd | Cr | Pb | Zn | |
|---|---|---|---|---|
| Cd | 1 | |||
| Cr | 0.404 | 1 | ||
| Pb | −0.227 | −0.119 | 1 | |
| Zn | 0.493 | −0.373 | 0.495 | 1 |
3.4. Heavy metals concentration in plants
The concentrations of heavy metals in different parts of the plants collected from study area are given in Table 7. In plants Cd, Cr, Pb and Zn concentrations ranged from 0 to 19 μg/kg, 11–3021 μg/kg, 1–2813 μg/kg and 72–2733 μg/kg. Similar results were reported in a previous study [46]; an increase in heavy metals concentration (Pb. Cd, Co) was recorded in Phalaris minor with an increase in soil concentration and was lower as compared to P. monospensis.
Table 7.
Heavy metals concentration μg/kg in plants samples of HIE, Peshawar.
| Sampling sites | Cd μg/kg |
Cr μg/kg |
Pb μg/kg |
Zn μg/kg |
||||
|---|---|---|---|---|---|---|---|---|
| Root | Shoot | Root | Shoot | Root | Shoot | Root | Shoot | |
| 1 | 19 | 3 | 3021 | 1015 | 215 | 7 | 2308 | 2002 |
| 2 | 7 | 1 | 2611 | 1038 | 10 | 12 | 1920 | 1991 |
| 3 | 1 | 0 | 1042 | 11 | 2813 | 1109 | 968 | 72 |
| 4 | 11 | 5 | 834 | 1010 | 1015 | 781 | 2733 | 1519 |
| Control | 3 | 0 | 201 | 702 | 399 | 1 | 2501 | 36 |
| WHO/FAO Limits (2007) [36] | 200 μg/kg | 5000 μg/kg | 5000 μg/kg | 60000 μg/kg | ||||
In this study, roots showed a higher concentration of heavy metals as compared to shoots. This is because roots act as a barrier for translocation of metals in order to protect the shoots from the effects of metals [47]. Same plant species having different levels of heavy metals at different sites show that plant's uptake and transport depend upon the level of heavy metals in the soil and the ability of plants to accumulate such heavy metals. The results of this study are in line with previous studies reporting high retention of heavy metals in roots [48,49]. In shoots Cr and Zn showed significant positive correlation (0.810) (Table 8), this could be due to the same path for transport and requirement of essential nutrients for plants [50]. In roots Cr and Pb (−0.740) and Zn with Pb (-0.722) showed negative correlation which could be due to competition between heavy metals (Cd, Pb and Zn) of similar chemical properties for uptake [51]. Cd showed weak correlation with Cr, Pb and Zn in both root and shoot. Different capabilities of plants to uptake heavy metals might have resulted in weak correlation between metals in plants [52]. Metals distribution in plants mainly depends upon plant species, water transport, availability and form [53]. Translocation of metals and compartmentalization in plant tissues are the reasons for variations in concentration of metals and stem acts as a pathway for transfer of metals thus low metals concentration is recorded in shoots [54].
Table 8.
Correlation matrix of heavy metals in roots of plants samples.
| Cd | Cr | Pb | Zn | |
|---|---|---|---|---|
| Cd | 1 | |||
| Cr | 0.508 | 1 | ||
| Pb | −0.527 | −0.740 | 1 | |
|
Zn |
0.520 |
0.169 |
−0.722 |
1 |
| Correlation of heavy metals in shoot of plants samples | ||||
|
Cd |
Cr |
Pb |
Zn |
|
| Cd | 1 | |||
| Cr | 0.614 | 1 | ||
| Pb | 0.109 | −0.672 | 1 | |
| Zn | 0.634 | 0.810 | −0.402 | 1 |
Heavy metals can easily accumulate in the surrounding environment and are of concern due to their toxicity [55]. Weed plants have been used to remediate heavy metal contaminated sites due to high biomass, growth rate and tolerance to toxic pollutants [56]. Studies conducted on five different plant species (L. spartum, G. decander, A. serratuloides, E. Glaucophyllum, H. Kahirikum) colonized closely to the cement industry showed higher translocation and bioaccumulation of heavy metals in perennial against annual species and was reported that plants could be potential indicator of heavy metals. L. spartum, G. decander, A. serratuloides were identified as pollution indicators [57]. The identification of plants growing at sites contaminated with heavy metals, can provide information about the mechanism of tolerance to heavy metals and their accumulation in plants [58]. On one hand, heavy metals are accumulated in plants specifically in their roots and their correlation with heavy metals in substrate may represent the level of contamination, but on the other hand, these accumulated heavy metals upon subsequent release into the environment during decomposition results in recycling of heavy metals in the environment. Such a pathway can have an important effect on the level of toxic heavy metals in the surrounding environment [59].
3.5. Bioconcentration factors (BCF) for metals in plants
Table 9 showed bioconcentration factors, the ratio of metal concentration in plants to that in sludge. BCF greater than 1 shows the ability of plants to accumulate metals from the environment and shows the ability for accumulation in tissues. As Cd in some plant samples was below detectable limit BCF was not available. The highest BCF was observed for Cr (4.8) in roots. BCF greater than 1 was observed for Cr (root, shoot), Pb (root) and Zn (root), which showed high phytoremediation potential and Cd showed the lowest < 1 BCF. BCF for Cd was <1, which indicated that this species cannot be used as bioindicator for Cd but BCF >1 was observed for Cr, Pb and Zn, which showed that this plant species can be used as bioindicator for Cr, Pb and Zn. The results of this study revealed that Phalaris minor can be used for biomonitoring purposes. In previous studies, greater BCF values were also reported for Pb and Zn in other grass species (C. pennisetiformis, C. dactylon, and B. reptans) which showed the phytostabilizing potential of grasses and availability of metals to plants [60].
Table 9.
Bioconcentration factors for heavy metals.
| Sampling sites | Cd |
Cr |
Pb |
Zn |
||||
|---|---|---|---|---|---|---|---|---|
| Root | Shoot | Root | Shoot | Root | Shoot | Root | Shoot | |
| 1 | 0.018 | 0.002 | 4.8 | 1.631 | 0.077 | 0.002 | 0.692 | 0.599 |
| 2 | 0.006 | 0.009 | 0.877 | 0.34 | 0.008 | 0.01 | 0.95 | 0.988 |
| 3 | 0.018 | – | 0.49 | 0.005 | 0.573 | 0.226 | 0.477 | 0.035 |
| 4 | 0.01 | 0.004 | 0.202 | 0.245 | 0.729 | 0.561 | 1.685 | 0.937 |
| Control | 0.111 | – | 0.923 | 0.671 | 2.375 | 0.005 | 2.307 | 0.033 |
3.6. Correlation of heavy metals between plants (root, shoot) and sludge
The high correlation of heavy metals between sludge and roots were observed for Cd (0.754) and for Pb (0.793) (Table 10), which indicates that increase in Cd and Pb in sludge resulted in an increase in plant roots. The strong correlation of plant tissues with that of sludge indicated heavy metal bioavailability [61]. Zn and Pb showed a highly negative correlation (-0.802) which shows that with the increasing Zn in sludge Pb uptake in plant roots, reduced. The rest of the elements showed non-significant and weak correlation. The reason for the weak correlation between plants and sludge might be due to the fact that correlation was calculated with total metal concentrations rather than the bioavailable fraction in sludge [62]. Metal concentration in plants is mainly affected by their availability in sludge and high concentration of metals in sludge [21]. Metal accumulation in plants generally depends upon plant species, heavy metal properties, uptake, translocation of metals, pH of soil, metals concentration in soil and organic matter [21,63]. Similar results for weak correlation in soil and plants (grass) were also reported by Refs. [22,64]. [65] also reported the absence of correlation of metals in plants with sediment.
Table 10.
Pearson's correlation matrix between heavy metals of sludge and roots of plants of HIE.
| Heavy metals in sludge | Heavy metals in plant roots |
||||
|---|---|---|---|---|---|
| Cd | Cr | Pb | Zn | ||
| Cd | Pearson Correlation | 0.754 | 0.37 | −0.572 | 0.425 |
| Sig. (2-tailed) | 0.141 | 0.54 | 0.313 | 0.476 | |
| N | 5 | 5 | 5 | 5 | |
| Cr | Pearson Correlation | −0.144 | −0.608 | 0.154 | 0.1 |
| Sig. (2-tailed) | 0.817 | 0.277 | 0.804 | 0.873 | |
| N | 5 | 5 | 5 | 5 | |
| Pb | Pearson Correlation | −0.067 | −0.253 | 0.793 | −0.802 |
| Sig. (2-tailed) | 0.915 | 0.681 | 0.109 | 0.103 | |
| N | 5 | 5 | 5 | 5 | |
| Zn | Pearson Correlation | 0.752 | 0.562 | −0.121 | −0.158 |
| Sig. (2-tailed) | 0.142 | 0.324 | 0.847 | 0.8 | |
| N | 5 | 5 | 5 | 5 | |
* Correlation is significant at the 0.05 level (2-tailed).
Correlation of heavy metals in sludge and shoots showed significantly strong and positive correlation was found between Cd and Zn (r = 0.984**, p < 0.01). Cd showed strong and positive correlation with Cr (0.82) and weak and negative correlation with Pb (-0.303) (Table 11). The significantly strong and positive correlation between Cd and Zn shows that Cd concentration in sludge influenced Zn uptake in plants. The strong correlation of heavy metals in soil with plants shows availability of that metal in soil and its transport and accumulation in shoot also depend on being essential for it [66]. The present study showed that most of the heavy metals in sludge showed positive correlation with those in plants except Pb. Positive correlations indicate the effect of metals in sludge on metals absorbed by plants. Such correlation can be supported by several other studies in which the total quantity of metals in sludge and soil correlated with metals in plants [67,68].
Table 11.
Pearson's correlation matrix between heavy metals of sludge and shoots of plants of HIE.
| Heavy metals in sludge | Heavy metals in plant shoots |
||||
|---|---|---|---|---|---|
| Cd | Cr | Pb | Zn | ||
| Cd | Pearson Correlation | 0.719 | 0.82 | −0.303 | 0.984** |
| Sig. (2-tailed) | 0.171 | 0.09 | 0.62 | 0.002 | |
| N | 5 | 5 | 5 | 5 | |
| Cr | Pearson Correlation | 0.477 | 0.173 | 0.48 | 0.248 |
| Sig. (2-tailed) | 0.417 | 0.78 | 0.414 | 0.688 | |
| N | 5 | 5 | 5 | 5 | |
| Pb | Pearson Correlation | −0.14 | −0.701 | 0.669 | −0.186 |
| Sig. (2-tailed) | 0.822 | 0.187 | 0.217 | 0.765 | |
| N | 5 | 5 | 5 | 5 | |
| Zn | Pearson Correlation | 0.274 | 0.193 | −0.164 | 0.604 |
| Sig. (2-tailed) | 0.656 | 0.755 | 0.792 | 0.281 | |
| N | 5 | 5 | 5 | 5 | |
** Correlation is significant at the 0.01 level (2-tailed).
3.7. Correlation of heavy metals between sludge and wastewater
Table 12 shows the correlation of heavy metals in sludge with wastewater, which revealed a significantly strong and positive correlation between Cr and Pb (r = 0.879, p = 0.05), and Cr and Zn (r = 0.895, p < 0.05) and high correlation of Cd with Pb in wastewater (r = 0.745, p > 0.05). The results revealed that increase in one element corresponded to increase in other, which indicated close association of heavy metals in sludge and wastewater. Negative correlation was also observed for Pb with Cr, Pb and Zn in wastewater. The results of correlation of heavy metals suggest that a positive correlation between different metals might be due to the fact that these metals either have similar pollution levels, transport and common sources (industries) or a single source from which these heavy metals originated [69]. Industries such as steel mills, mechanical processing, dyeing are the main sources of heavy metals (Cd, Cr, Pb and Zn). The results similar to this study were also reported by Ref. [70].
Table 12.
Pearson's correlation matrix between heavy metals in sludge and wastewater of HIE.
| Heavy metals in sludge | Heavy metals in wastewater |
||||
|---|---|---|---|---|---|
| Cd | Cr | Pb | Zn | ||
| Cd | Pearson Correlation | 0.447 | 0.489 | 0.745 | 0.521 |
| Sig. (2-tailed) | 0.45 | 0.404 | 0.148 | 0.368 | |
| N | 5 | 5 | 5 | 5 | |
| Cr | Pearson Correlation | 0.158 | 0.348 | .879* | .895* |
| Sig. (2-tailed) | 0.8 | 0.566 | 0.05 | 0.04 | |
| N | 5 | 5 | 5 | 5 | |
| Pb | Pearson Correlation | 0 | −0.268 | −0.118 | −0.272 |
| Sig. (2-tailed) | 1 | 0.663 | 0.85 | 0.658 | |
| N | 5 | 5 | 5 | 5 | |
| Zn | Pearson Correlation | 0.259 | 0.006 | 0.007 | −0.276 |
| Sig. (2-tailed) | 0.674 | 0.992 | 0.992 | 0.653 | |
| N | 5 | 5 | 5 | 5 | |
*. Correlation is significant at the 0.05 level (2-tailed).
4. Conclusion
Despite the fact that heavy metals in wastewater meet the Pak-NEQS but can still pose a threat to human health and the environment due to Cd and Cr excess, when compared with FAO limits for irrigation of crops. Heavy metals were differently distributed among studied compartments; sludge > plants > wastewater. For wastewater and sludge, heavy metals concentration was highest at sites within industrial estate and compared to control. In plants, the order of metals was different for each site as compared to control, and most metals accumulated highest in roots as compared to shoots. Positive correlation of heavy metals in sludge with plant roots and shoots, revealed that accumulation of heavy metals in plants was through sludge. The BCF for Cr, Pb and Zn was greater than 1 except for Cd, and can be used as bioindicator for Cr, Pb and Zn. The findings in this study revealed that the total metals concentration in the grass Phalaris minor can give information about pollution level. The grass is also useful to find out bioavailability, toxicity and mobility of metals and as an indicator of potential risk. Thus, monitoring the impacts of industrial activities is important to find out its trend and pattern of distribution in different compartments of the environment. It is important to note that the present study focused specifically on analysis and distribution of Cd, Cr, Pb, and Zn in different compartments of the environment and their accumulation in plants. The research did not include other heavy metals. The inclusion of additional heavy metals in future research would provide valuable insights into their respective uptake mechanisms in plants and their relationship with the aforementioned elements.
Author contribution statement
Sara Nawaz Khan; Dr Mohammad Nafees; Dr Muhammad Imtiaz: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.
Data availability statement
Data included in article/supplementary material/referenced in article.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
References
- 1.Mitra S., Chakraborty A.J., Tareq A.M., Emran T.B., Nainu F., Khusro A., Simal-Gandara J. Impact of heavy metals on the environment and human health: Novel therapeutic insights to counter the toxicity. J. King Saud Univ. Sci. 2022;34 doi: 10.1016/j.jksus.2022.101865. [DOI] [Google Scholar]
- 2.Ghaedi M., Niknam K., Kokhdan S.N., Soylak M. Combination of flotation and flame atomic absorption spectrometry for determination, preconcentration and separation of trace amounts of metal ions in biological samples. Hum. Exp. Toxicol. 2013;32:504–512. doi: 10.1177/0960327112444936. [DOI] [PubMed] [Google Scholar]
- 3.Alloway B.J. Soil processes and the behaviour of metals. Heavy metals in soils. 1995;13:3488. doi: 10.1007/978-94-011-1344-1_2. [DOI] [Google Scholar]
- 4.Gray C.W., Dunham S.J., Dennis P.G., Zhao F.J., McGrath S.P. Field evaluation of in situ remediation of a heavy metal contaminated soil using lime and red-mud. Environ. Pollut. 2006;142:530–539. doi: 10.1016/j.envpol.2005.10.017. [DOI] [PubMed] [Google Scholar]
- 5.Sarwar N., Imran M., Shaheen M.R., Ishaque W., Kamran M.A., Matloob A., Hussain S. Phytoremediation strategies for soils contaminated with heavy metals: modifications and future perspectives. Chemosphere. 2017;171:710–721. doi: 10.1016/j.chemosphere.2016.12.116. [DOI] [PubMed] [Google Scholar]
- 6.Chen J. Rapid urbanization in China: a real challenge to soil protection and food security. Catena. 2007;69:1–15. doi: 10.1016/j.catena.2006.04.019. [DOI] [Google Scholar]
- 7.Perrin J.L., Raïs N., Chahinian N., Moulin P., Ijjali M. Water quality assessment of highly polluted rivers in a semi-arid Mediterranean zone Oued Fez and Sebou River (Morocco) J. Hydrol. (Wellingt. North) 2014;510:26–34. doi: 10.1016/j.jhydrol.2013.12.002. [DOI] [Google Scholar]
- 8.Sharma R.K., Agrawal M., Marshall F. Heavy metal contamination of soil and vegetables in suburban areas of Varanasi, India. Ecotoxicol. Environ. Saf. 2007;66:258–266. doi: 10.1016/j.ecoenv.2005.11.007. [DOI] [PubMed] [Google Scholar]
- 9.Amin N., Ayaz M., Alam S., Gul S. Heavy metals contamination through industrial effluent to irrigation water in Gadoon Amazai (Swabi) and Hayatabad (Peshawar) Pakistan. J. Scientific. Res. 2014;6:111–124. doi: 10.3329/jsr.v6i1.16336. [DOI] [Google Scholar]
- 10.Sharma P., Tripathi S., Chandra R. Phytoremediation potential of heavy metal accumulator plants for waste management in the pulp and paper industry. Heliyon. 2020;6 doi: 10.1016/j.heliyon.2020.e04559. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Marani D., Braguglia C.M., Mininni G., Maccioni F. Behaviour of Cd, Cr, Mn, Ni, Pb, and Zn in sewage sludge incineration by fluidised bed furnace. Waste Manag. 2003;23:117–124. doi: 10.1016/S0956-053X(02)00044-2. [DOI] [PubMed] [Google Scholar]
- 12.Dey M., Akter A., Islam S., Dey S.C., Choudhry T.R., Fatema K.J., Begum B.A. Assessment of contamination level, pollution risk and source apportionment of heavy metals in the Halda River water, Bangladesh. Heliyon. 2021;7 doi: 10.1016/j.heliyon.2021.e08625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Singh A., Sharma R.K., Agrawal M., Marshall F.M. Health risk assessment of heavy metals via dietary intake of foodstuffs from the wastewater irrigated site of a dry tropical area of India. Food Chem. Toxicol. 2010;48:611–619. doi: 10.1016/j.fct.2009.11.041. [DOI] [PubMed] [Google Scholar]
- 14.Mukherjee D.P. Dynamics of metal ions in suspended sediments in Hugli estuary, India and its importance towards sustainable monitoring program. J. Hydrol. 2014;517:762–776. doi: 10.1016/j.jhydrol.2014.05.069. [DOI] [Google Scholar]
- 15.Urbaniak M., Wyrwicka A., Tołoczko W., Serwecińska L., Zieliński M. The effect of sewage sludge application on soil properties and willow (Salix sp.) cultivation. Science. Total. Environ. Sci. 2017;586:66–75. doi: 10.1016/j.scitotenv.2017.02.012. [DOI] [PubMed] [Google Scholar]
- 16.Tyagi V.K., Lo S.L. Sludge: a waste or renewable source for energy and resources recovery? Renew. Sustain. Energy Rev. 2013;25:708–728. doi: 10.1016/j.rser.2013.05.029. [DOI] [Google Scholar]
- 17.Onchoke K.K., Franclemont C.M., Weatherford P.W. Structural characterization and evaluation of municipal wastewater sludge (biosolids) from two rural wastewater treatment plants in East Texas, USA. Spectrochim. Acta Mol. Biomol. Spectrosc. 2018;204:514–524. doi: 10.1016/j.saa.2018.06.096. [DOI] [PubMed] [Google Scholar]
- 18.Varol M. Assessment of heavy metal contamination in sediments of the Tigris River (Turkey) using pollution indices and multivariate statistical techniques. J. Hazard Mater. 2011;195:355–364. doi: 10.1016/j.jhazmat.2011.08.051. [DOI] [PubMed] [Google Scholar]
- 19.Cicek A., Malkoc S., Koparal A.S. An investigation on the usability of grass in short term detection of traffic-related pollution. Arab. J. Sci. Eng. 2012;37:1239–1245. doi: 10.1007/s13369-012-0244-z. [DOI] [Google Scholar]
- 20.Kim I.S., Kang K.H., Johnson-Green P., Lee E.J. Investigation of heavy metal accumulation in Polygonum thunbergii for phytoextraction. Environ. Pollut. 2003;126:235–243. doi: 10.1016/S0269-7491(03)00190-8. Medline. [DOI] [PubMed] [Google Scholar]
- 21.Eid E.M., Shaltout K.H. Bioaccumulation and translocation of heavy metals by nine native plant species grown at a sewage sludge dump site. Int. J. Phytoremediation. 2016;18:1075–1085. doi: 10.1080/15226514.2016.1183578. [DOI] [PubMed] [Google Scholar]
- 22.Pugh R.E., Dick D.G., Fredeen A.L. Heavy metal (Pb, Zn, Cd, Fe and Cu) contents of plant foliage near the Anvil range lead/zinc mine, Faro, Yukon territory. Ecotoxicol. Environ. Safety. 2002;52:273–279. doi: 10.1006/eesa.2002.2201. Medline, [DOI] [PubMed] [Google Scholar]
- 23.Ali H., Khan E., Ilahi I. Environmental chemistry and ecotoxicology of hazardous heavy metals: environmental persistence, toxicity, and bioaccumulation. J. Chem. 2019 doi: 10.1155/2019/6730305. [DOI] [Google Scholar]
- 24.Khan N.H. Doctoral dissertation, University of Peshawar; Peshawar, Pakistan: 2015. On-site Waste Management and Industrial Symbiosis of Hayatabad Industrial Estate, Peshawar, Pakistan.http://173.208.131.244:9060/xmlui/handle/123456789/5763 [Google Scholar]
- 25.Nafees M. Role of Kabul River in socio-economic activities and associated environmental problems. Journal of Area Study Center, University of Peshawar. 2010;67:101–112. http://asc-centralasia.edu.pk/old_site/Issue_67/07_Mohammad_Nafees.html [Google Scholar]
- 26.APHA . American Public Health Association; Washington, DC: 1999. Standard Methods for the Examination of Water and Wastewater. [Google Scholar]
- 27.Turek A., Wieczorek K., Wolf W.M. Digestion procedure and determination of heavy metals in sewage sludge-An analytical problem. Sustain. Times. 2019;11:1753. doi: 10.3390/su11061753. [DOI] [Google Scholar]
- 28.Uddin A.B.M., Khalid R.S., Alaama M., Abdualkader A.M., Kasmuri A., Abbas S.A. Comparative study of three digestion methods for elemental analysis in traditional medicine products using atomic absorption spectrometry. J. Anal. Sci. Technol. 2016;7:1–7. doi: 10.1186/s40543-016-0085-6. [DOI] [Google Scholar]
- 29.National environmental quality standards (NEQS) The gazette of Pakistan, Pakistan Environmental Protection Act-97. PEPA; 1997. pp. 1290–1294.https://environment.gov.pk/SiteImage/Misc/files/SRO742I93SRO1023I95NEQS.pdf [Google Scholar]
- 30.Mahmood Q., Shaheen S., Bilal M., Tariq M., Zeb B.S., Ullah Z., Ali A. Chemical pollutants from an industrial estate in Pakistan: a threat to environmental sustainability. App. Water. Sci. 2019;9:1–9. doi: 10.1007/s13201-019-0920-1. [DOI] [Google Scholar]
- 31.Kaur A., Vats S., Rekhi S., Bhardwaj A., Goel J., Tanwar R.S., Gaur K.K. Physico-chemical analysis of the industrial effluents and their impact on the soil microflora. Procedia. Environ. Sci. 2010;2:595–599. doi: 10.1016/j.proenv.2010.10.065. [DOI] [Google Scholar]
- 32.Chinhanga J.R. Impact of industrial effluent from an iron and steel company on the physico-chemical quality of Kwekwe River water in Zimbabwe. Int. J. Eng. Sci. Technol. 2010;2 doi: 10.4314/ijest.v2i7.63754. [DOI] [Google Scholar]
- 33.Tariq S.R., Shah M.H., Shaheen N., Khalique A., Manzoor S., Jaffar M. Multivariate analysis of trace metal levels in tannery effluents in relation to soil and water: a case study from Peshawar, Pakistan. J. Environ. Manag. 2006;79:20–29. doi: 10.1016/j.jenvman.2005.05.009. [DOI] [PubMed] [Google Scholar]
- 34.Nafees M., Zahid Z., Naz R. Study of steel Re-rolling mill for mitigation measures with special reference to water recycling. Int. J. Recent. Scientific. Res. 2012;3:747–752. http://www.recentscientific.com [Google Scholar]
- 35.Khan N.H., Nafees M., Saeed Tooba. A Gate-to-Gate Life Cycle Assessment of Match Industry for Wood Consumption and Wood Waste Generation. 2020;7(2020):832–837. doi: 10.31031/EAES.2020.07.000671. [DOI] [Google Scholar]
- 36.Iloms E., Ololade O.O., Ogola H.J., Selvarajan R. Investigating industrial effluent impact on municipal wastewater treatment plant in vaal, South Africa. Int. J. Environ. Res. Publ. Health. 2020;17:1096. doi: 10.3390/ijerph17031096. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Cañedo-Argüelles M., Kefford B.J., Piscart C., Prat N., Schäfer R.B., Schulz C.J. Salinisation of rivers: an urgent ecological issue. Environ. Pollut. 2013;173:157–167. doi: 10.1016/j.envpol.2012.10.011. [DOI] [PubMed] [Google Scholar]
- 38.WHO/FAO . 2007. Wastewater Treatment and Use in Agriculture-Irrigation. [Google Scholar]
- 39.Li X., Wu Y., Zhang C., Liu Y., Zeng G., Tang X., Lan S. Immobilizing of heavy metals in sediments contaminated by nonferrous metals smelting plant sewage with sulfate reducing bacteria and micro zero valent iron. Chem. Eng. J. 2016;306:393–400. doi: 10.1016/j.cej.2016.07.079. [DOI] [Google Scholar]
- 40.Zhou J., Ma D., Pan J., Nie W., Wu K. Application of multivariate statistical approach to identify heavy metal sources in sediment and waters: a case study in Yangzhong, China. Environ. Geol. 2008;54:373–380. doi: 10.1007/s00254-007-0824-5. [DOI] [Google Scholar]
- 41.Usepa A. U.S. Environmental Protection Agency Office of Wastewater Management; Washington, DC, USA: 1995. Guide to the Biosolids Risk Assessments for the EPA Part 503 Rule. [Google Scholar]
- 42.Agoro M.A., Adeniji A.O., Adefisoye M.A., Okoh O.O. Heavy metals in wastewater and sewage sludge from selected municipal treatment plants in eastern cape province, South Africa. Water. 2020;12(2020):2746. doi: 10.3390/w12102746. [DOI] [Google Scholar]
- 43.Titilawo Y., Adeniji A., Adeniyi M., Okoh A. Determination of levels of some metal contaminants in the freshwater environments of Osun State, Southwest Nigeria: a risk assessment approach to predict health threat. Chemosphere. 2018;211:834–843. doi: 10.1016/j.chemosphere.2018.07.203. [DOI] [PubMed] [Google Scholar]
- 44.Planquart P., Bonin G., Prone A., Massiani C. Distribution, movement and plant availability of trace metals in soils amended with sewage sludge composts: application to low metal loadings. Sci. Total Environ. 1999;241:161–179. doi: 10.1016/S0048-9697(99)00338-1. [DOI] [Google Scholar]
- 45.Tytła M. Assessment of heavy metal pollution and potential ecological risk in sewage sludge from municipal wastewater treatment plant located in the most industrialized region in Poland-case study. Int. J. Environ. Res. Publ. Health. 2019;16:2430. doi: 10.3390/ijerph16132430. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Ramadan W.F., Balah M.A. The use of some weeds type in the disposal of heavy metals in contaminated soil. J. Saudi. Soc. Agric. Sci. 2022;21:289–295. doi: 10.1016/j.jssas.2021.09.008. [DOI] [Google Scholar]
- 47.Liu W.X., Liu J.W., Wu M.Z., Li Y., Zhao Y., Li S.R. Accumulation and translocation of toxic heavy metals in winter wheat (Triticum aestivum L.) growing in agricultural soil of Zhengzhou, China. Bull. Environ. Contam. Toxicol. 2009;82:343–347. doi: 10.1007/s00128-008-9575-6. [DOI] [PubMed] [Google Scholar]
- 48.Eid E.M., Shaltout K.H. Monthly variations of trace elements accumulation and distribution in above-and below-ground biomass of Phragmites australis (Cav.) Trin. ex Steudel in Lake Burullus (Egypt): a biomonitoring application. Ecol. Eng. 2014;73:17–25. doi: 10.1016/j.ecoleng.2014.09.006. [DOI] [Google Scholar]
- 49.Bonanno G. Comparative performance of trace element bioaccumulation and biomonitoring in the plant species Typha domingensis, Phragmites australis and Arundo donax. Ecotoxicol. Environ. Saf. 2013;97:124–130. doi: 10.1016/j.ecoenv.2013.07.017. [DOI] [PubMed] [Google Scholar]
- 50.Bhatti S.S., Kumar V., Sambyal V., Singh J., Nagpal A.K. Comparative analysis of tissue compartmentalized heavy metal uptake by common forage crop: a field experiment. Catena. 2018;160:185–193. doi: 10.1016/j.catena.2017.09.015. [DOI] [Google Scholar]
- 51.Ghori Z., Iftikhar H., Bhatti M.F., Sharma I., Kazi A.G., Ahmad P. Phytoextraction: the use of plants to remove heavy metals from soil. Plant Metal Interact. 2016:385–409. doi: 10.1016/B978-0-12-803158-2.00015-1. [DOI] [Google Scholar]
- 52.Yan X., Zhang F., Zeng C., Zhang M., Devkota L.P., Yao T. Relationship between heavy metal concentrations in soils and grasses of roadside farmland in Nepal. Int. J. Environ. Res. Publ. Health. 2012;9:3209–3226. doi: 10.3390/ijerph9093209. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Gómez‐Bernal J.M., Ruiz‐Huerta E.A., Armienta Hernández M.A., Ramirez Romero P., Gallegos‐Martínez M.E. Evaluation of the accumulation of heavy metals in water, sediments and plants of a coastal zone of Mexico. Water. Environ. J. 2021;35:606–616. doi: 10.1111/wej.12655. [DOI] [Google Scholar]
- 54.Kim I.S., Kang K.H., Johnson-Green P., Lee E.J. Investigation of heavy metal accumulation in Polygonum thunbergii for phytoextraction. Environ. Pollut. 2003;126:235–243. doi: 10.1016/S0269-7491(03)00190-8. [DOI] [PubMed] [Google Scholar]
- 55.An B., Lee C.G., Song M.K., Ryu J.C., Lee S., Park S.J., Choi J.W. Applicability and toxicity evaluation of an adsorbent based on jujube for the removal of toxic heavy metals. React. Funct. Polym. 2015;93(2015):138–147. doi: 10.1016/j.reactfunctpolym.2015.06.009. [DOI] [Google Scholar]
- 56.Prasad M.N.V., Greger M., Landberg T. Acacia nilotica L. bark removes toxic elements from solution: corroboration from toxicity bioassay using Salix viminalis L. in hydroponic system. Int. J. Phytoremediation. 2001;3:289–300. doi: 10.1080/15226510108500060. [DOI] [Google Scholar]
- 57.Bayouli I.T., Bayouli H.T., Dell'Oca A., Meers E., Sun J. Ecological indicators and bioindicator plant species for biomonitoring industrial pollution: eco-based environmental assessment. Ecol. Indicat. 2021;125 doi: 10.1016/j.ecolind.2021.107508. [DOI] [Google Scholar]
- 58.Gómez‐Bernal J.M., Ruiz‐Huerta E.A., Armienta Hernandez M.A., Ramirez Romero P., Gallegos‐Martínez M.E. Evaluation of the accumulation of heavy metals in water, sediments and plants of a coastal zone of Mexico. Water. Environ. J. 2011;35:606–616. doi: 10.1111/wej.12655. [DOI] [Google Scholar]
- 59.Kim I.S., Kang K.H., Johnson-Green P., Lee E.J. Investigation of heavy metal accumulation in Polygonum thunbergii for phytoextraction. Environ. Pollut. 2003;126:235–243. doi: 10.1016/s0269-7491(03)00190-8. [DOI] [PubMed] [Google Scholar]
- 60.Malik R.N., Husain S.Z., Nazir I. Heavy metal contamination and accumulation in soil and wild plant species from industrial area of Islamabad, Pakistan. Pakistan J. Bot. 2010;42:291–301. http://www.pakbs.org/pjbot/PDFs/42(1)/PJB42(1)291.pdf [Google Scholar]
- 61.Alyemeni M.N., Almohisen I.A. Traffic and industrial activities around Riyadh cause the accumulation of heavy metals in legumes: a case study. Saudi J. Biol. Sci. 2014;21:167–172. doi: 10.1016/j.sjbs.2013.09.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Cardwell A.J., Hawker D.W., Greenway M. Metal accumulation in aquatic macrophytes from southeast Queensland, Australia. Chemosphere. 2002;48:653–663. doi: 10.1016/S0045-6535(02)00164-9. [DOI] [PubMed] [Google Scholar]
- 63.Liu J., Wang J., Qi J., Li X., Chen Y., Wang C., Wu Y. Heavy metal contamination in arable soils and vegetables around a sulfuric acid factory, China. CLEAN–Soil. Air, Water. 2012;40:766–772. doi: 10.1002/clen.201100550. [DOI] [Google Scholar]
- 64.Sungur A., Soylak M., Ozcan H. Investigation of heavy metal mobility and availability by the BCR sequential extraction procedure: relationship between soil properties and heavy metals availability. Chem. Speciat. Bioavailab. 2014;26:219–230. doi: 10.3184/095422914X14147781158674. [DOI] [Google Scholar]
- 65.Peng K., Lou C., Lou L., Li X., Shen Z. Bioaccumulation of heavy metals by the aquatic plants Potamogeton pectinatus L. and Potamogeton malaianus Miq. and their potential use for contamination indicators and in wastewater treatment. Sci. Total Environ. 2008;392:22–29. doi: 10.1016/j.scitotenv.2007.11.032. [DOI] [PubMed] [Google Scholar]
- 66.Bashir F., Kashmiri M.A., Shafiq T., Tariq M.F. Heavy metals uptake by vegetables growing in sewage irrigated soil: relationship with heavy metal fractionation in soil. Chem. Speciat. Bioavailab. 2009;21:199–209. doi: 10.3184/095422909X12471558119088. [DOI] [Google Scholar]
- 67.Bonanno G., Giudice R.L. Heavy metal bioaccumulation by the organs of Phragmites australis (common reed) and their potential use as contamination indicators. Ecol. Indicat. 2010;10:639–645. doi: 10.1016/j.ecolind.2009.11.002. [DOI] [Google Scholar]
- 68.Bonanno G. Trace element accumulation and distribution in the organs of Phragmites australis (common reed) and biomonitoring applications. Ecotoxicol. Environ. Saf. 2011;74:1057–1064. doi: 10.1016/j.ecoenv.2011.01.018. [DOI] [PubMed] [Google Scholar]
- 69.Suresh G., Ramasamy V., Meenakshisundaram V., Venkatachalapathy R., Ponnusamy V. Influence of mineralogical and heavy metal composition on natural radionuclide concentrations in the river sediments. Appl. Radiat. Isot. 2011;69:1466–1474. doi: 10.1016/j.apradiso.2011.05.020. [DOI] [PubMed] [Google Scholar]
- 70.Zhang H., Huang Y., Zhou S., Wei L., Guo Z., Li J. Pollution level and risk assessment of heavy metals in sewage sludge from eight wastewater treatment plants in Wuhu City, China. Span. J. Agric. Res. 2020;18 doi: 10.5424/sjar/2020182-15796. e1103-e1103. [DOI] [Google Scholar]
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