Next Article in Journal
Source Apportionment and Health Risk Assessment of Heavy Metals in Karst Water from Abandoned Mines in Zhangqiu, China
Previous Article in Journal
Effects of Urbanization on Changes in Precipitation Extremes in Guangdong-Hong Kong-Macao Greater Bay Area, China
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Phytoremediation of Cu and Mn from Industrially Polluted Soil: An Eco-Friendly and Sustainable Approach

Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan
Institute of Biotechnology and Microbiology, Bacha Khan University, Charsadda 24540, Pakistan
Department of Biosciences, COMSATS University Islamabad (CUI), Islamabad 45550, Pakistan
School of Resources and Environmental Engineering, East China University of Science and Technology, Shanghai 200237, China
Centre for Development Research (ZEF), Genscherallee 3, 53113 Bonn, Germany
Department of Botany and Microbiology, College of Science, King Saud University, Riyadh P.O. Box 11451, Saudi Arabia
Department of Geology, V.O. Chidambaram College, Thoothukudi 628008, India
Department of Microbiology, Shaheed Benazir Bhutto Women University, Peshawar 25120, Pakistan
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Water 2023, 15(19), 3439;
Submission received: 27 July 2023 / Revised: 11 September 2023 / Accepted: 15 September 2023 / Published: 29 September 2023
(This article belongs to the Section Soil and Water)


Water and soil polluted by heavy metals (HMs) are the primary problem due to rapidly increasing urbanization and industrialization. For the treatment of polluted soil, phytoremediation turns into a cost-effective and eco-friendly technique. The current research aimed to examine the load of pollution, specifically HMs, in sediment and wastewater (WW) of the GadoonAmazai Industrial Estate (GAIE), Pakistan and compare the ability of native grass species Cynodon dactylon and Digiteria sanguinalis for the phytoaccumulation of HMs. The industrially polluted soil was analysed for HMs using atomic absorption spectrophotometry (AAS) and compared with healthy soil (irrigated by freshwater), which served as a control. The HM accumulation was considerably higher in the soil irrigated with WW than in control soil samples. The most substantial metal pollutant was manganese (Mn), which accumulated up to 2491.7 mg/kg in the WW irrigated soil. For assessing the bioremoval efficiency of grass species, pot experimentation was performed for 90 days. Soil samples and grasses were collected from the pots to examine the HM removal efficiency. A significant reduction was noted in physicochemical characteristics of the soil, such as electrical conductivity, total organic matter, phosphorus, potassium, and saturation. The grasses removed up to 59.0% of the Cu and 59.9% of Mn from the soil. The highest bioconcentration factor (BCF) and translocation factor (TF) of Cu were observed for D. sanguinalis. While the highest BCF and TF of Mn were obtained for C. dactylon. The research showed that the grass significantly (p ≤ 0.05) reduced HM in soil samples. Moreover, the selected grasses found a higher capability to accumulate HM in the roots than in the shoot. The maximum Cu removal was obtained by D. sanguinalis and Mn by C. dactylon. The research study concluded that phytoremediation using D. sanguinalis and C. dactylon is an eco-friendly and cost-effective method that can be utilized for soil remediation.

1. Introduction

Soil is one of the most precious and important natural resources for humans. Civilization of society and agricultural sustainability enormously depend on it [1]. However, soil contamination due to heavy metals (HMs) is a global issue and is a major risk to mankind. Several regions of the world, like the USA, Eastern and Central Europe, and developing countries such as Bangladesh, Pakistan, India, and China, struggle to discover a solution for soil pollution with HMs [2]. Apart from natural processes like rock weathering, volcanic eruptions, etc., anthropogenic activities such as rapid urbanization and industrialization considerably contribute to the HM pollution in soil. Irresponsible discharge of HM-enriched waste sludge, municipal wastes, mine tailing and industrial wastewater (WW) are the primary causes of soil contamination [3]. Once HMs pollute the soil, they persist in the soil for several years due to its non-biodegradable nature. The availability and mobility of HM is controlled by biogeochemical process (protonation, adsorption, mineralization, and precipitation) and depends upon the nature of soil and rhizospheric effects [4]. Long-term HM contamination negatively affects microbial biodiversity and activity. Soil microbes considerably contribute to soil organic carbon transformation, which is important for soil fertility [5]. Therefore, soil fertility reduces with the decrease in soil microbial population.
Additionally, cereals intake, which is grown in HM-polluted soil, poses a health risk to mankind due to the accumulation of metals in food crops [6]. So, HM pollution affects agricultural productivity, degrades soil properties, ruins the balance of the ecosystem and damages human health by entering the food web or by direct exposure [7]. Mostly, the plant uptake of HMs badly hinders different physiological and biochemical routes, prompting a restriction of plant growth and, finally, leading to cell death [8].
Manganese (Mn) is one of the trace metals essential for normal life activities of plants [9]. Mn plays a vital role in maintaining the normal structure of plant chloroplasts, enzyme activities and participating in photosynthesis [10]. However, too much Mn pollutes the soil and inhibits plant development and growth. Due to Mn high solubility over a wide range of pH, it is not easy to remove from the water and, therefore, poses a series of problems to the soil, food chain, water industry, and human health [11]. Excessive Mn levels in plants can alter processes like enzyme activity, translocation, utilization, and absorption of other minerals (P, Fe, Mg and Ca), leading to oxidative stress [12]. Copper (Cu) is essential to living organisms as a trace element.
On the other hand, if the concentration of Cu exceeds the human tolerance range, it can cause adverse effects such as haemolysis, jaundice, nausea, liver and kidney damage, headaches, diarrhea, stomach upset and even death. Recent studies indicated that the excess amount of Cu can induce different toxicological activities such as hepatocirrhosis, renal dysfunction, changes in lipid profile and oxidative stress [13]. Aside from acute Cu toxicity in humans, adverse health effects and impaired growth have been observed in plants, animals, and a wide range of living organisms [14]. However, effective but inexpensive measures of remediating metal-contaminated soils or waters are still to be found.
Soils polluted with HMs can be treated by different techniques such as chemical oxidation, various heat treatments, cremation, soil isolation, soil removal, etc. These techniques have the limitation of being expensive, and in several cases, they include the movement of pollutants to processing sites, as well as risks of secondary pollution. Therefore, in-situ techniques are preferred as they are aesthetically and socially acceptable, less environmentally cumbersome and come at a much lower cost [15,16]. Many plants can perform this job with less involvement of labor and less cost by the method called phytoremediation. Various biological species have recently been utilized widely in developing and developed nations for cleaning HM-polluted ecosystems. Plants can eliminate HMs from the environment and, therefore, will reduce the noxious effects of HMs on living organisms. The various categories of phytoremediation are phytostimulation, phytostabilization, phytovolatilization, rhizosphere filtration, phytodegradation and phytoextraction [17,18]. The phytoremediation process eliminates pollutants from the environment and soil and yields biomass that can be utilized for biofumigation and biofuel production and will be a source of extra earnings [19]. Phytoremediation is about ten times less expensive as compared to other conventional approaches. Therefore, the need and significance of phytoremediation are emphasized in additional research to discover new HM accumulator species. Previous research described that the potential growth of local wild plants on polluted sites responds better to stress conditions than the species introduced from different environments [20]. A recent study was carried out to recognize the remittable grasses in industrially polluted soil and their remediation ability and also examined the effect of different HM on their growth. The research aimed to investigate HM accumulation in the root and shoot of native wild plant species (grasses) of Cynodon dactylon and Digiteria sanguinalis grown around and in wastewater effluent of Gadoon Amazai industrial areas of Swabi, Pakistan.

2. Materials and Methods

2.1. Materials

  • Chemical and reagents
H2SO4, MnSO4, Na2S2O3, HClO4, Aqua Regia, HF, 2NHCl, HNO3 and Strach indicator.
All chemicals and reagents used in chemical tests were of analytical grade and were obtained through Pak Chemicals, Abbottabad, Pakistan.
  • Instruments
Atomic absorption Spectrophotmeter (AAS-700 PerkinElmer: Norwalk, CT, USA), pH Meter ((Lutron Electronic Enterprise Co. Ltd., Model PH-208, Taipei, Taiwan), EC meter (InoLab, Cond Level 1, Weilheim, Germany), incubator (Model MIR-254, Sanyo, Osaka, Japan), Oven (DZF-6010, Zhengzhou, China), Centrifuge (Model # ALC-4227 R, Vilsbiburg, Germany) and Filter Paper (Wattman No. 42, Xi’an, China)

2.2. Study Area Description

The current study area (Gadoon Amazai Industrial Estate) is sited at an altitude of 325 m from sea level and between longitude 72°32′45″ to 72°35′45″ east and latitude 33°5′20″ to 33°7′20″ north [21]. The Gadoon Amazai Industrial Estate (GAIE) was established in 1987 and consists of 330 operational units. Major industrial units like steel, cooking oil, detergent and soap, ghee, textile, chemicals, plastic, and marble release large amounts of WW to the environment without any management and treatment, which is utilized for irrigation purposes [21]. Gadoon industrial area is a moist, fertile, plain area [22]. The soils of this area are categorized as muddy plain deposits of River Indus. The sample was collected in May when average temperatures was ranging from 78–103 F° and 3.3 inches of rainfall. The study area has topographically uneven ground and flood deposits and extensive gravel deposits with silt stratifications and shingle beds [23].

2.3. Sample Collection

To evaluate the pollution load of the reference (healthy soil) and target soil (industrially polluted), the samples were obtained from GAIE and adjacent areas in triplicate (n = 3). In the current study, the target areas were those areas that were irrigated with industrial WW. The reference areas were those regions watered with freshwater and not polluted by human actions. A random sampling technique was used to obtain samples from different sites. Three samples were obtained from the target and three from the reference sites. The samples were transported for further processing to the Geochemistry Laboratory of the National Centre of Excellence in Geology, University of Peshawar.

2.4. Soil Analysis

Soils (½ kg) were obtained (15 cm depth) randomly from the various locations of the canal to analyze for HMs (Cu and Mn), Moisture Content, Total Organic Matter, saturation, EC, phosphorus, potassium, and pH. The soil was first ground, dried, and screened by sieves (2 mm) for further laboratory analysis. In acids (HClO4 and HNO3), the soil samples were digested and quantified for HMs by atomic absorption spectrophotometry (AAS-700 PerkinElmer: Norwalk, CT, USA). The pH and the value of electrical conductivity (EC) were observed in the soil by a pH Meter (Model: pH208) and an EC meter (InoLab level-1), respectively.

2.5. Water Analysis

The samples of WW and freshwater were obtained in plastic bottles from the canal of GAIE and ground fresh water source (used for irrigation) in triplicate. The suspended solid contaminants were removed [24]. The water samples were investigated for various characteristics like temperature, biological oxygen demand (BOD), pH, total suspended solids (TSS), EC, chemical oxygen demand (COD), total dissolved solids (TDS), and HMs (Cu and Mn) [25].

2.5.1. pH and Electric Conductivity (EC)

The pH and EC of the water samples were analysed using a pH meter (Model: pH208) and an EC meter (InoLab), respectively.

2.5.2. Biological Oxygen Demand (BOD)

For the initial DO (dissolved oxygen), a titration flask water sample (200 mL) was taken, and 1 mL of each concentrated H2SO4, alkali iodide and MnSO4 was added. Then, a few drops of indicator (starch) were added. In the burette, the solution of Na2S203 was taken. The Na2S203 in the water sample was titrated till disappearance of the colour. 20 mL water samples were taken in BOD bottles to store the samples for five days in an incubator (Model MIR-254, Sanyo) at 20 °C. The same titration process was performed after five days for the final DO value. The difference between the initial and final DO is the BOD of the water sample [26].
BOD5 (mg/L) = DOi − DOf
DOi = initial DO.
DOf = final DO at 20 °C after five days of incubation.

2.5.3. Chemical Oxygen Demand (COD)

COD is a measure of water and WW quality. First, the sample blank was prepared. 2 mL of the sample was taken through a micropipette and poured into the COD reagent vial available in the market. The vial was inverted several times to mix it properly. The vial became hot during mixing. For blank preparation, the 2 mL of deionized water was poured into another COD reagent vial and mixed properly. The samples were then ready for digestion. Both the vials were placed into the COD reactor for digestion. The temperature was set at 150 °C for 2 h. After digestion, the samples were cooled. The blank vial was inserted into the adapter slowly with minimum shaking and placed into the spectrophotometer. The blank vial reading was noted as zero. The blank vial was removed from the adaptor, and the sample vial was inserted. The reading that appeared on the spectrophotometer was noted [27]

2.5.4. Total Suspended Solids (TSS)

Wattman No. 42 filter paper was placed in the oven at 101 °C for dryness and then was cooled and weighed. On this filter paper, a 10 mL water sample was filtered and kept in the oven for drying at 101 °C and then was cooled and weighed. The difference in the initial weight (Wi) and final weight (Wf) of the filter paper was the value of TSS [28].
TSS = Wf Wi × 1000 water   sample   mL
Wi = filter paper’s initial weight
Wf = filter paper’s final weight

2.5.5. Total Dissolved Solids (TDS)

In the oven, a clean crucible was placed at 105 °C. Using a desiccator, the crucible was cooled and weighed. For evaporation, the filtered 10 mL water sample in the crucible was kept at 105 °C in the oven. Then, after cooling, the crucible was weighed in a desiccator. The difference in initial (Wi) and final crucible weight (Wf) was TDS [28].
TDS = Wf Wi × 1000 water   sample   mL
Wi = Crucible’s initial weight
Wf = Crucible’s final weight

2.6. Pot Experiment

Pot experimentation was done to analyse Cu and Mn phytoextraction ability and bioremoval efficiency of locally dominant and accessible plant species (Cynodon dactylon and Digiteria sanguinalis) cultivated on HM-contaminated soil obtained from the effluent-fed sites and reference healthy soil. The soil (5 kg) was placed into pots (diameter: 20 cm and height: 25 cm). The pots were placed in the greenhouse under a temperature of 18–27 °C and humidity of up to 55–65%. Six plants in each pot were cultivated. There were a total of four pots, representing two treatment pots (T1 containing Cynodon dactylon and T2 containing Digiteria sanguinalis having contaminated/target soil) and two control pots (CT1 containing Cynodon dactylon and CT2 containing Digiteria sanguinalis having reference/healthy soil). The plants were regularly irrigated with fresh water when needed. After 90 days (three months; September–November 2022) of the experiment, shoots and roots of grass species were separately harvested.

2.7. Geochemical Analysis

After experimentation, the oil samples were analysed for Moisture Content, Total Organic Matter (TOM), saturation, EC, phosphorus, potassium and pH in the Geochemistry Laboratory of the National Centre of Excellence in Geology, University of Peshawar.
For the toxic and HMs analysis, 1 g of soil sample was placed in beakers. Hydrofluoric acid (10 mL HF) was supplemented to beakers and then heated (1 h) at low heat on a hot plate, and aqua regia (20 mL)(3HCl/1HNO3) was added to the beakers, and the solution was dried by heating. Again, 2NHCl (20 mL) was supplemented and heated. After wet digestion, the substances were filtered through filter paper (no. 42 Whatman). After digestion of the soil, the solutions were aspirated through AAS, and the HM concentrations were examined in the samples. The soil samples were also analysed for physiochemical parameters using standard methods as adapted by Ayaz et al. [25].

2.8. Laboratory Analysis of Plant Biomass

After harvesting, the plants were washed with distilled water. The plants were parted into root and shoot, the fresh weight was estimated, and the lengths (centimeter) of shoots and roots were also determined. The plant’s biomass was then oven-dried (80 °C), ground and weighed for dry biomass estimation. For the extraction of HMs, the dried samples in the digestion chamber were digested [24]. The dried and powdered 0.5 g of the plant’s samples were digested (160 °C) with 5 mL of the nitric acid. The obtained volume was first filtered and then enlarged to 50 mL by the addition of deionized water. The solutions were then assessed for HM through AAS [23].

2.9. Formula

2.9.1. Bioconcentration Factor (BCF) (%)

The plant’s competency for metal uptake from soil was obtained by a formula adopted by Gautam and Agrawal [29].
B C F   % = C   p l a n t C   s o i l × 100
C plant refers to metal concentration in plant tissues, and C soil represents the metal concentration in a soil sample.

2.9.2. Translocation Factor (TF) (%)

The value of the Translocation factor can be attained as the ratio of metal level in the shoot to roots through the following formula [25]:
T F   % = C   s h o o t C   r o o t × 100
C shoot refers to the concentrations of metal accumulated in the shoot, and C root represents the metal concentrations in the root parts of the plant.

2.9.3. Bioremoval Efficiency (%)

Bioremoval efficiency was evaluated by the formula adopted by Khan et al. [24].
R = C i C f C i × 100
R, Ci and Cf show the removal percentage, initial metal concentration and final metal concentration in soil samples, respectively.

2.10. Statistical Analysis

Statistical analysis was achieved by software like Sigma Plot and Microsoft Excel and a statistical package for social science (SPSS 16.0). Results are displayed as mean ± standard deviation. To confirm the statistical significance of the difference, data was analysed using SPSS with a t-test (p < 0.05).

3. Results and Discussion

3.1. Pollution Load of Water Samples

The parameters’ results of water samples are represented in Supplementary Information Table S1. The samples obtained from the target area (industrial wastewater: WW) and reference area (fresh water: FW) were observed for physiochemical properties. The values of pH (8.9) noted for WW did not exceed the maximum permissible limit (MPL) set by Pak-EPA (Pakistan Environmental Protection Agency). The values of EC, TDS, COD, BOD and TSS, potassium and phosphorus observed for WW were 7.27 mS/cm, 1286 mg/L, 862 mg/L, 519 mg/L, 414 mg/L, 15 mg/L and 5 mg/L, respectively. The values of TDS and TSS were noted below MPL (3500 mg/L and 150 mg/L, respectively). However, the COD value and BOD value exceeded the MPL (150 and 80 mg/L, respectively) as set by Pak-EPA (Table S1). Previously, different results (pH 6.53 and EC: 5.03 mS/cm) were determined by Khan et al. [24], who performed research on the WW of the Hayatabad Industrial Estate (HIE). The EC result agreed with the finding (6.35 mS/cm) of Farid et al. [23], who studied the characteristics of WW collected from GAIE. The present TSS values do not agree with the investigation (43 mg/L) of Shamshad et al. [30]. Irshad et al. [31] evaluated the phytoaccumulation of HMs in plant species thriving on WW at the Hattar industrial estate and observed similar findings (TDS: 1309 mg/L). Similarly, the present values are not in agreement with BOD (143 mg/L) and EC (5.04 mS/cm) values of the WW observed by Ayaz et al. [25], a remediation study performed on WW of HIE. The present findings are much higher than the values observed for the WW of HIE by Khan et al. [32]. Singh et al. [33] conducted a research study on textile WW in India and investigated higher BOD (790 mg/L) and COD values (3050 mg/L). The variations in the results can be ascribed to the variations in sampling regions.

3.2. Physicochemical Characteristics of Soil Sample

The soil samples collected from the target area (industrial area) and reference area (One kilometer away from the industrial area) were evaluated for physiochemical characteristics. A comparison of the parameters of reference and target soil of the GAIE area is given in Table S2 (Supplementary Information). The HM level of the target soil was greater compared to reference soil. Amin et al. [34] carried out an investigation on HM accumulation in soil Irrigated with WW of GAIE and its contrast with soil irrigated by fresh water. They found that HMs were significantly higher in the target soil irrigated with WW than in the control (p < 0.05). This variation in HM concentration of target and reference soil can be ascribed to the variable discharge of WW from the industries. The investigations showed lower levels of Cu and Mn (76.3 and 1201.4 mg/kg) in the reference soil sample. The Cu and Mn concentrations observed in the target soil were 161.9 and 2491.7 mg/kg, respectively. The HMs varied for their concentrations in the soil as Mn > Cu. The HM level of soil samples was like the findings of Irshad et al. [31]. In both WW and Soil samples, Mn was detected in higher concentration compared to Cu level. Previous studies also reported higher Mn concentration in polluted soil than Cu concentration in industrial polluted soil, but the concentration of Mn (9.95 mg/kg) and Cu (1.236 mg/kg) determined were much lower than the present study. However, the current findings do not agree with the outcomes of Ali et al. [35], research conducted on the health risk evaluation of HMs using vegetables using WW for irrigation in District Swabi. Ali et al. [35] determined a concentration of Mn (17.14 mg/kg) and Cu concentration (18.57 mg/kg) in the target soil. Moreover, unlike the present study, the Cu concentration was higher than the Mn concentration. The EC, pH, saturation, TOM, phosphorus, and potassium values determined for the target soil sample were 308 dS/m, 9.4, 26.76%, 0.39%, 97.21 mg/kg and 788.7 mg/kg, respectively. Similarly, the reference soil showed much lower values of EC (278.9 dS/m), pH (8.03), phosphorus (59.05 mg/kg) and potassium (498.6 mg/kg) and a higher percentage of TOM (0.47%) and saturation (31.9%). The EC and pH of soils are indicators of the chemical matrices of the background soil. In soils, the metal solubility is controlled mainly by pH, oxidation state of the system, number of metals, ion exchange capacity and organic carbon. According to previous studies, the permissible pH limit for WW is nine, and the optimum pH of irrigation water ranges from 6.5–8.5 [31]. Hussain et al. [22] studied the multi-statistical techniques for the geochemical assessment of soil pollutants of GAIE, Pakistan. They observed a lower value for Cu (144.7 mg/kg) and a higher Mn (2508 mg/kg) concentration in polluted soil. Shehnaz et al. [36] studied the bioremediation potential of selected local grasses and soil in Karachi city. They found different results for Cu (6.7 mg/kg), phosphorus (80.7 mg/kg), and potassium (806.7 mg/kg) in the target soil, while the percentage of saturation (28.3%) and TOM (0.3%) were much similar to the present results. The variation can be attributed to differences in the study area.

3.3. Growth of Grass Species at Various HM Concentrations

Grass contains an extended and fibrous root that enhances the degradation activity of microbes in the rhizosphere [28,29]. In recent studies, the production of greater biomass is a significant feature because the biomass can be utilized for various money-making purposes [30]. In the present case, maximum biomass, such as average dry (106.84 g) and fresh weight (119.15 g), was observed for C. dactylon (T1) in soil in the 90-day experiment (Figure 1). The D. sanguinalis was observed for the minimum average fresh (43.61 g) and dry weight (36.83 g) in CT2. The maximum average shoot (89.43 cm) and root length (204.33 cm) were observed for D. sanguinalis grown in the reference soil (CT2). Similarly, the lowest average root and shoot length were exhibited by C. dactylon, i.e., 103.5 cm and 31.2 cm in (T1) (Figure 2). The study revealed that the selected species competently survived in reference soils compared to contaminated soil and produced high biomass. The selected species were examined for their ability to accumulate HMs in the remediation process, where various plants exhibited different arrays of uptake for various metals, as previously described by several investigators [37,38,39,40]. Shehnaz et al. [36] observed the bioremediation ability of some local grass species of Karachi. The investigations of the current study agree with the results of Shehnaz et al. [36], such as the fresh weight of the plant (49–124 g) and dry weight of the plant (40–112 g), but the value of shoot length (35–91 cm) determined was different from the present study.

3.4. Effect of Plants on Soil Physiochemical Parameters

Table 1 shows the plants’ impact on various physicochemical properties of soil samples. The results revealed that C. dactylon had significantly reduced EC (48.9–61.5%), TOM (27.6–43.5%), phosphorus (58.1–66.7%), potassium (37.7–51.6%) and saturation (43.3–45.0%) during experimentation. In the current study, the effect of D. sanguinalis was observed to be lower than C. dactylon. The effect of D. sanguinalis on EC (38.8–46.9%), TOM (38.2–48.7%), phosphorus (49–57.6%), potassium (36.3–49.2%) and saturation (29.81–36.7%) was lower than C. dactylon. Different results (EC: 72%) were found in a study by Farid et al. [23] on algae and hydrophytes for HMs bioremediation from Industrial WW. The difference in the result can be accredited to using different biological species in both studies.

3.5. Metal Accumulation by Grass Species

The accumulation of Cu in the grass species varies in various species. The HM level was detected to be higher in the roots of grass species compared to the shoot. The Cu uptake by the shoots of the C. dactylon and D. sanguinalis was ranging 10.97–18.10 and 16.07–23.97 mg/kg, respectively. The higher uptake by the shoots of the grass was determined (23.97 mg/kg) in T2, and the minimum metal uptake (10.97 mg/kg) was observed in CT1. The Cu uptake by the roots of C. dactylon and D. sanguinalis was investigated in the range of 19.06–41.68 and 25.33–39.43 mg/kg, respectively (Table 2). The maximum Cu uptake was noted in D. sanguinalis from contaminated soil samples (T2). The Cu concentration noted in the grass after 90 days of the experiment is presented in Figure S1 (Supplementary Information). Wang and Liu [41] studied the subcellular distributions of HMs in accumulator and hyperaccumulator species. They found that D. sanguinalis accumulated a much lower concentration of Cu in root (2.43 mg/kg) and shoot (3.82 mg/kg) parts. The difference can be endorsed to the variation in study area and climate.
The accumulation of Mn in the grass species also varies in both grasses, and the Mn level was evaluated to be higher in the roots of the species, comparing shoots just like Cu uptake. The shoots of the C. dactylon and D. sanguinalis Mn uptake were ranging 209.48–441.09 and 112.37–299.76 mg/kg, respectively. The higher Mn accumulation by the shoot of the grasses was obtained (441.09 mg/kg) in T1, and the less uptake (112.37 mg/kg) was observed in CT2. The Mn uptakes by root tissues of C. dactylon and D. sanguinalis were investigated to be in the range of 501.12–837.18 and 381.03–671.19 mg/kg, respectively (Supplementary Information Figure S2). The maximum Mn uptake was noted in C. dactylon from contaminated soil samples (T1). The HM concentrations noted in the grass species after three months of the experiment are shown in Table 2.
D. sanguinalis was assessed to have comparatively high average Cu level, i.e., CT2 (28.04 mg/kg), T2 (31.7 mg/kg); likewise, C. dactylon was evaluated to have high average Mn concentration, i.e., CT1 (355.3 mg/kg) and T1 (639.14 mg/kg) (Table 2). Meanwhile, D. Sanguinalis and C. dactylon are proficient in accumulating metals at high levels; it is an effective phytoremediator species that could be cultivated as pioneer plants to ameliorate the soil. Singh et al. [42] studied biomonitoring-supported land restoration to decrease the degradation of land and observed a much lower concentration of Mn (3.405 mg/kg) in C. dactylon. Khan et al. [43] investigated the biomonitoring of HM accumulation in plants growing in the valley of Khushab. For this purpose, different plants were analyzed for HMs accumulation, and much higher values for Cu (12.44 mg/kg) and Mn (23.58 mg/kg) in biomass of D. sanguinalis were found. The differences in the results may be accredited to the difference in the study area.

3.6. Effect of Grasses on Metal Concentration

3.6.1. Copper

Cu concentration assessed in soil was ranging 76.3–161.9 and 31.27–97.77 mg/kg at the initial and final points of the pot experiment, respectively (Supplementary Information Figure S3). At the initial point, T1 and T2 soil samples and the final samples, T1 soil, were investigated for greater Cu levels. In the final stage, a considerable decrease in the Cu concentration of soil was observed by the plant species (Table 1). The removal efficiency of Cu ranges from 39.61–59.0%. The CT1, T1, CT2, and T2 removed 42.5, 39.6, 59.0 and 49.7% of Cu, respectively (Figure 3). The t-test showed that CT1, T1, CT2, and T2 significantly (p < 0.05) reduced Cu level in final samples. The grass species C. dactylon and D. sanguinalis were more competent in control (CT1 and CT2) than treatment (T1 and T2), as shown in Figure 3. The results propose that both grass species C. dactylon and D. sanguinalis are more effective at lower concentrations of Cu.

3.6.2. Manganese (Mn)

In the pot experiment, Mn mean level assessed at the initial and final point’s soil samples ranged from1201.4–2491.7 mg/kg and 481.11–1511.29 mg/kg, respectively (Supplementary Information Figure S4). The maximum Mn level was detected in the initial soil of T1 and T2 and the final point of T2. The decrease in Mn levels by plants in the final phases of soils was determined (Table 1). The competency of Mn removal was obtained in the range of 39.3 to 59.9%, whereas CT1, T1, CT2 and T2 removed 59.9, 53.0, 41.9, and 39.3% of Mn, respectively (Figure 3). The t-test results presented that the Mn concentration in final soil samples was significantly (p < 0.05) reduced than initial soil samples, representing that the grass species were competent in Mn removal from soil samples. Furthermore, the study investigated both the grass species (C. dactylon and D. sanguinalis) were more competent in control (CT1 and CT2) compared to treatment (T1 and T2), suggesting that C. dactylon is more competent at lower Mn levels.

3.7. Bioconcentration (BCF %) and Translocation Factor (TF %) of Metals

Figure 4 presents the metal level bioaccumulated in grass species from the soil. The BCF of Cu calculated for CT1, T1, CT2, and T2 were 39.3, 36.9, 54.0 and 39.9%, respectively. The results presented that D. sanguinalis (CT2: 54.0%) has the highest BCF, and C. dactylon (T1:36.9%) has the lowest BCF for Cu. Similarly, the BCF of Mn determined for the CT1, T1, CT2, and T2 were 59.1, 51.3, 41.0 and 38.9%, respectively. The data presented that C. dactylon has the maximum BCF of Mn (59.1%), and D. sanguinalis has the lowest BCF of Mn. Consequently, the bioaccumulation trend of C. dactylon for the particular HMs was observed in the order of Mn > Cu in soil samples after 90 days of the experiment. The results indicated that the Mn uptake potential of D. sanguinalis was lower than C. dactylon. The D. sanguinalis was the highest removal ability for Cu (39.1–54.0%), followed by Mn (38.9–41.0%). The bioaccumulation of this grass species for metals was in the order of Cu > Mn. Gautam and Agrawal [29] conducted a study on identifying metal-tolerant plants for viable phyto-management of the red mud and found different values of BCF from the recent research. The BCF results of Cu (7.5%) and Mn (32%) for C. dactylon were much less than the present results. Shehnaz et al. [36] studied the bioremediation ability of local grasses in Karachi. However, the BCF of the current study does not agree with the BCF (55%) of Cu determined by Shehnaz et al. [36]. Similarly, the BCF of Mn (34.7%) determined for Cynodon dactylon in a previous study [42] agreed with the current research. In another study by Campillo-Cora et al. [44], the BCF of Cu result (14%) was much lower than in the present study.
Figure 5 summarizes the translocation factor (TF) for selected grass species. The TF of Cu calculated for CT1, T1, CT2, and T2 were 57.5, 43.4, 63.44 and 60.79%, respectively. The results revealed that D. sanguinalis (CT2) has the highest TF for Cu (63.44%) grown in reference soil, and C. dactylon (T1) has the lowest TF for Cu (43.4%) grown in contaminated soil. The data showed that C. dactylon (CT1) has the highest TF for Mn (52.68%) compared to D. sanguinalis. Similarly, the TF of Mn calculated for CT1, T1, CT2, and T2 were 41.8, 52.6, 29.4 and 44.6%, respectively. The results revealed that C. dactylon (T1) has the highest TF for Mn (63.44%) (Figure 5), and D. sanguinalis (CT2) has the lowest TF for Mn (29.4%). Gautam and Agrawal [29] conducted a study on the identification of metal-tolerant plants for viable phytomanagement of red mud dumps. They found TF results of Cu and Mn for C. dactylon much higher than the current results. The TF value of Cu (70%) for D. sanguinalis determined by Campillo-Cora et al. [44] was consistent with the present study.
From 1996–2014, different studies reported on GAIE showed higher levels of toxic metals in groundwater, plants, and soil. Other physiochemical parameters like total dissolved solids (TDS), sulfate, nitrate, chemical oxygen demand (COD), chloride, total suspended solids (TSS), hardness and alkalinity were found to exceed their permissible limits [22]. Nasrullah et al. [45] studied the vegetation of the Gadoon Amazai area and observed the toxicity in soil and crops by WW. The contaminants can be a source of acute and chronic diseases. The adverse effects of WW on crops and soils have been studied intensively, but research on the HMs uptake by wild native species in WW of Pakistan has information gaps and is scanty. Geochemical examination of Gadoon areas has shown that the geogenic sources discharge nitrate and sulfate that accumulate in water and soil and pose risks to local populations [46]. As the GAIE was recently established at that time, the study of Baig did not especially emphasize the role of industrial estate in polluting different resources.
Similarly, Khan et al. [21] reported that the inlets of Gadoon had a noteworthy level of pollutants than outlets, and WW could be a cause of pollution, but the research was restricted to only wetlands. A study was carried out by Amin et al. [34] on GAIE for the identification of HMs discharged by only two industrial units (Shafi and Sardar Chemical units). They obtained only a few samples from a drain and did not examine the entire industrial estate. Hence, Amin et al. [34] have not explored the ecological risk and toxicity related to the whole industrial estate. Hussain et al. [22] use multi-statistical methods for the geochemical evaluation of contaminants in soils of GAIE but did not identify the possible remediation techniques for the treatment of soil and WW. Recently, Farid et al. [23] explored the pollution load of GAIE and used the best bioremediators (algae and hydrophytes) to treat WW.
Sonowal et al. [47] investigated C3 and C4 plants as potential bioenergy and phytoremediation crops for the stabilization of HM-polluted soils. They found that the species which exhibited maximum Mn accumulation was C. dactylon (14.5 mg/kg), followed by D. sanguinalis (0.1 mg/kg). Previous results revealed that despite the chlorosis under high Mn stress (30 mmol·L−1), root morphology, the diameter of the ground and the plant height were not significantly inhibited, and a high Mn level was accumulated in plants (translocation factor = 1.10) [48]. Huang et al. [49] studied the enhancement of Mn phytoremediation by Broussonetia papyrifera with plant growth-promoting Bacillus species. The results revealed that root length and activity and the biomass of B. papyrifera with inoculated bacterial strain were higher than the control group. The inoculation of Bacillus spp. improved the Mn absorption by B. papyrifera. Similarly, Gravand et al. [50] investigated the capability of vetiver grass in the phytoremediation of polluted soils with HMs, and it was found that the percentage of Mn adsorption was 61%. The results also showed that the plant roots have absorbed more HM concentration than the shoots, as the current study results. Shuaibu et al. [51] observed the phytoremediation potentials of C. dactylon on HM polluted soils from Challawa Industrial Estate, Nigeria. They found that the concentration of the metals in the C. dactylon from control and polluted sites were noted to be in the order of Cu (33.60 mg/kg) > Mn (12.67 mg/kg) and Cu (138.35 mg/kg) > Mn (28.40 mg/kg), respectively. Wang et al. [52] carried out a study on HM accumulator’s weeds and found that accumulation of Cu was relatively higher in the root parts (321.12 mg/kg) of D. sanguinalis than in the shoot parts (55.88 mg/kg). The findings of Wang et al. [52] agree with the current study. Da Silva et al. [53] investigated the potential of the phytoremediation of invasive and native grasses cohabiting Cu-polluted vineyards in Brazil. The study found that Cu pollution did not affect concentrations of chlorophyll a and b in C. dactylon but increased concentrations of carotenoid. Da Silva et al. [53] recorded higher Cu bioaccumulation in root parts and high production of C. dactylon biomass - compensates for comparatively low Cu concentration in its tissues by increasing Cu extraction from soil that makes C. dactylon more competent in the phytoremediation process. Ancheta et al. [54] observed Cu accumulation of C. dactylon in Cu -mine tailings. They analyzed that higher concentrations of metals accumulated in the root compared to the shoot, validating the current study. C. dactylon accumulated 2250 µg/g, and it was found that C. dactylon has been able to withstand higher concentrations of metals. Ozyigit et al. [55] (2021) determined the mineral nutrient compositions of field-grown weeds. They observed that higher concentrations of Mn (41.37) and Cu (8.939 mg/kg) were accumulated in the root parts of C. dactylon compared to the aerial parts.
Heavy metal pollution of agricultural soils is today’s chief health and environmental issue due to the potential risk of food chain contamination and associated health risks. In this condition, phytoremediation approaches may demonstrate an important means to deal with the problem. Other chemical and physical approaches to cleaning polluted soils seem reasonably unfeasible and time-consuming, with less efficient results. Phytoremediation is an eco-friendly approach applicable to various pollutants with numerous compensations, such as being low in cost, socially acceptable and aesthetically pleasing [56]. However, it also has some limitations, as it may take several years to remediate a polluted site; it can be time-consuming, making this approach inappropriate for restoring areas that may constitute a severe risk to the ecosystem and human beings [33,40]. Another noteworthy limitation of this technique is the essential contact between the root zone of plants and contaminants [39,56,57,58]. Therefore, the critical role played by roots in phytoremediation has usually limited its appliance to shallow, contaminated soils, with the only exemption being the utilization of some trees to reach zones in the range of one to several meters [59]. In addition, the age of plants seriously affects their physiological activity; certainly, the capability to take up ions is greater for the roots of younger plants. However, an older plant with larger biomass may balance its lower physiological activity [57]. Another constraining factor is the higher level of pollutants accumulated by plants that limit their use to sites with lower metal content. Fundamental research at a small scale is of chief importance to understand and control several metabolic processes in the plant and its various organs and the complex interactions between plant roots, soil, and pollutants. Though experimental conditions can alter plant biochemistry and physiology, it is not understandable if results obtained with small and young plantlets under definite conditions can be extended to full-scale and real fields. The experimentation at a small scale in a greenhouse or laboratory is highly important for a better knowledge of basic plant biochemical and molecular mechanisms implicated in the uptake, sequestration, detoxification, and translocation of contaminants, as well as their direct transposition in the field is a bit questionable.
Conversely, short-term conditions of experiments in small containers used to grow plantlets do not allow the normal development and growth of shoots and roots and, therefore, compel stress, which can have an effect on the plant’s performance and the phytoremediation efficiency. As a result, the implementation of phytoremediation on a large scale will be successful only if the right plant is used at the right place. Even basic biochemical and physiological knowledge is needed to choose the most suitable plant species, cultivar, or ecotype, tolerant to the pollutants to be treated and capable of detoxifying and accumulate them without affecting their survival and growth. Results obtained at laboratory scales should always be validated in the field. Eventually, the factors that play a main role in the field but cannot be evaluated in the laboratory are local climate, soil heterogeneity, spatial variability and concentrations of contaminants, meteorological uncertainty, depth and texture of soil layers, water and nutrient availability, differences in rooting density and depth, variability of soil moisture, impacts of herbivores, pathogens, and pests etc. Biochemical and molecular mechanisms of plant adaptation to real stress conditions are still poorly understood. However, plant adaptation to environmental changes is vital for plants and, therefore, for phytoremediation efficiency.
Genetic engineering techniques to develop transgenic plants with characters of tolerance against metal toxicity, more metal accumulation, high biomass production and well-adapted to various climatic situations might be more valuable in this respect. Several other modern phytoremediation methods, like microbial-assisted phytoremediation and chemical-assisted phytoextraction methods, may also be utilized to remediate polluted soils on large scales. Further research is required in genetic engineering to enhance the phytoremediation capabilities of transgenic plants and to understand the effectiveness and mechanisms of the phytoremediation process to make these techniques economically feasible, time-saving and more effective.

4. Conclusions and Recommendations

The grasses play an essential role in the remediation of soil. C. dactylon has the best Mn removal efficacy, and D. sanguinalis is the best Cu remediator. The HM (Cu and Mn) levels of soil are significantly decreased (p ≤ 0.05) after the pot experiment, clearly showing the importance of grasses in the HM removal. Furthermore, the grass species survived in stress environments activated by HM concentrations. Hence, this character can be an encouraging indication for grasses to be used for bioremediation. So, phytoremediation is an eco-friendly, inexpensive treatment that can remediate HMs polluted soil.
The results found here mandate appropriate legislation, imperative operation of suitable safety actions and reliable monitoring of HMs discharged into soil and water. Municipal and Industrial WW must be remediated before being discharged into sewage water to contest vegetable and soil pollution. Based on the current study, there would be a severe threat to consumers linked with vegetable consumption being cultured in the Gadoon Industrial Estate area. Thus, strict measures are recommended highly on the vegetable’s safety obtained from the study area.

Supplementary Materials

The following supporting information can be downloaded at:, Figure S1: Cu concentration accumulated in Species. Figure S2: Mn concentration accumulated in species. Figure S3: Cu concentration in Soil sample at initial and final stage of experiment. Figure S4: Mn concentration in Soil sample at initial and final stage of experiment. Table S1: Physicochemical parameters of water samples. Table S2: Physicochemical parameters of target and reference soil samples.

Author Contributions

Conceptualization, S.K. and S.D.; methodology, S.K. and A.U.; software, S.H. and S.K.; validation, F.A., S.D. and S.B.; formal analysis, A.U., S.S. and H.Y.; investigation, F.A. and T.A.; resources, A.U. and S.D.; data curation, S.D. and A.U.; writing—original draft preparation, S.K., S.B., S.D. and A.U.; writing—review and editing, A.-R.Z.G., A.U. and S.H.; visualization, S.S. and S.H.; supervision, A.U.; project administration, A.-R.Z.G. and A.U.; funding acquisition, A.-R.Z.G. All authors have read and agreed to the published version of the manuscript.


Researchers Supporting Project Number (RSPD2023R686), King Saud University, Riyadh, Saudi Arabia.

Data Availability Statement

All data are fully available and can be found within the manuscript or in the Supporting Information file.


The authors would like to extend their sincere appreciation to the Researchers Supporting Project Number (RSPD2023R686), King Saud University, Riyadh, Saudi Arabia.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Dabgar, S.; Bhavsar, S.; Modi, N. Effects of lead and cadmium on shoot length and root length of Cascabela thevetia (L.) lippold. Int. Assoc. Biol. Comput. Dig. 2023, 2, 301–306. [Google Scholar] [CrossRef]
  2. Jha, P.K.; Tripathi, P. Arsenic and fluoride contamination in groundwater: A review of global scenarios with special reference to India. Groundw. Sustain. Dev. 2021, 13, 100576. [Google Scholar] [CrossRef]
  3. Shah, V.; Daverey, A. Phytoremediation: A multidisciplinary approach to clean up heavy metal contaminated soil. Environ. Technol. Innov. 2020, 18, 100774. [Google Scholar] [CrossRef]
  4. Chen, A.; Arai, Y. A Review of the Reactivity of Phosphatase Controlled by Clays and Clay Minerals: Implications for Understanding Phosphorus Mineralization in Soils. Clays Clay Miner. 2023, 71, 119–142. [Google Scholar] [CrossRef]
  5. Liang, C.; Amelung, W.; Lehmann, J.; Kästner, M. Quantitative assessment of microbial necromass contribution to soil organic matter. Glob. Chang. Biol. 2019, 25, 3578–3590. [Google Scholar] [CrossRef]
  6. Ahmad, S.; Hadi, F.; Jan, A.U.; Ullah, R.; Albalawi, B.F.A.; Ditta, A. Appraisal of Heavy Metals Accumulation, Physiological Response, and Human Health Risks of Five Crop Species Grown at Various Distances from Traffic Highway. Sustainability 2022, 14, 16263. [Google Scholar] [CrossRef]
  7. Boregowda, N.; Jogigowda, S.C.; Bhavya, G.; Sunilkumar, C.R.; Geetha, N.; Udikeri, S.S.; Chowdappa, S.; Govarthanan, M.; Jogaiah, S. Recent advances in nanoremediation: Carving sustainable solution to clean-up polluted agriculture soils. Environ. Pollut. 2022, 297, 118728. [Google Scholar] [CrossRef]
  8. Keyster, M.; Niekerk, L.-A.; Basson, G.; Carelse, M.; Bakare, O.; Ludidi, N.; Klein, A.; Mekuto, L.; Gokul, A. Decoding Heavy Metal Stress Signalling in Plants: Towards Improved Food Security and Safety. Plants 2020, 9, 1781. [Google Scholar] [CrossRef]
  9. Huang, H.; Zhao, Y.; Xu, Z.; Zhang, W.; Jiang, K. Physiological responses of Broussonetia papyrifera to manganese stress, a candidate plant for phytoremediation. Ecotoxicol. Environ. Saf. 2019, 181, 18–25. [Google Scholar] [CrossRef]
  10. Rai, S.; Singh, P.K.; Mankotia, S.; Swain, J.; Satbhai, S.B. Iron homeostasis in plants and its crosstalk with copper, zinc, and manganese. Plant Stress 2021, 1, 100008. [Google Scholar] [CrossRef]
  11. Ljung, K.; Vahter, M. Time to Re-evaluate the Guideline Value for Manganese in Drinking Water? Environ. Health Perspect. 2007, 115, 1533–1538. [Google Scholar] [CrossRef]
  12. Faria, J.M.; Teixeira, D.M.; Pinto, A.P.; Brito, I.; Barrulas, P.; Alho, L.; Carvalho, M. Toxic levels of manganese in an acidic Cambisol alters antioxidant enzymes activity, element uptake and subcellular distribution in Triticum aestivum. Ecotoxicol. Environ. Saf. 2020, 193, 110355. [Google Scholar] [CrossRef] [PubMed]
  13. Alengebawy, A.; Abdelkhalek, S.T.; Qureshi, S.R.; Wang, M.-Q. Heavy Metals and Pesticides Toxicity in Agricultural Soil and Plants: Ecological Risks and Human Health Implications. Toxics 2021, 9, 42. [Google Scholar] [CrossRef]
  14. Cavalletti, E.; Romano, G.; Esposito, F.P.; Barra, L.; Chiaiese, P.; Balzano, S.; Sardo, A. Copper Effect on Microalgae: Toxicity and Bioremediation Strategies. Toxics 2022, 10, 527. [Google Scholar] [CrossRef]
  15. Rajoria, S.; Vashishtha, M.; Sangal, V.K. Treatment of electroplating industry wastewater: A review on the various techniques. Environ. Sci. Pollut. Res. 2022, 29, 72196–72246. [Google Scholar] [CrossRef] [PubMed]
  16. Charvalas, G.; Solomou, A.D.; Giannoulis, K.D.; Skoufogianni, E.; Bartzialis, D.; Emmanouil, C.; Danalatos, N.G. Determination of heavy metals in the territory of contaminated areas of Greece and their restoration through hyperaccumulators. Environ. Sci. Pollut. Res. 2021, 28, 3858–3863. [Google Scholar] [CrossRef]
  17. Bedair, H.; Ghosh, S.; Abdelsalam, I.M.; Keerio, A.A.; AlKafaas, S.S. Potential implementation of trees to remediate contaminated soil in Egypt. Environ. Sci. Pollut. Res. 2022, 29, 78132–78151. [Google Scholar] [CrossRef]
  18. Kristanti, R.A.; Hadibarata, T. Phytoremediation of contaminated water using aquatic plants, its mechanism and enhancement. Curr. Opin. Environ. Sci. Health 2023, 32, 100451. [Google Scholar] [CrossRef]
  19. Rapp, G.; Garcia-Montoto, V.; Bouyssière, B.; Thiebaud-Roux, S.; Montoya, A.; Trethowan, R.; Pratt, P.; Mozet, K.; Portha, J.F.; Coniglio, L. Indian mustard bioproducts dry-purification with natural adsorbents-A biorefinery for a green circular economy. J. Clean. Prod. 2021, 286, 125411. [Google Scholar] [CrossRef]
  20. Nedjimi, B. Phytoremediation: A sustainable environmental technology for heavy metals decontamination. SN Appl. Sci. 2021, 3, 286. [Google Scholar] [CrossRef]
  21. Khan, S.; Ahmad, I.; Shah, M.T.; Rehman, S.; Khaliq, A. Use of constructed wetland for the removal of heavy metals from industrial wastewater. J. Environ. Manag. 2009, 90, 3451–3457. [Google Scholar] [CrossRef]
  22. Hussain, R.; Khattak, S.A.; Shah, M.T.; Ali, L. Multistatistical approaches for environmental geochemical assessment of pollutants in soils of Gadoon Amazai Industrial Estate, Pakistan. J. Soils Sediments 2015, 15, 1119–1129. [Google Scholar] [CrossRef]
  23. Farid, N.; Ullah, A.; Khan, S.; Butt, S.; Khan, A.Z.; Afsheen, Z.; El-Serehy, H.A.; Yasmin, H.; Ayaz, T.; Ali, Q. Algae and Hydrophytes as Potential Plants for Bioremediation of Heavy Metals from Industrial Wastewater. Water 2023, 15, 2142. [Google Scholar] [CrossRef]
  24. Khan, S.; Ullah, A.; Ayaz, T.; Aziz, A.; Aman, K.; Habib, M.; Yilmaz, S.; Farid, A.; Yasmin, H.; Ali, Q. Phycoremediation of industrial wastewater using Vaucheria debaryana and Cladophora glomerata. Environ. Monit. Assess. 2023, 195, 825. [Google Scholar] [CrossRef]
  25. Ayaz, T.; Khan, S.; Khan, A.Z.; Lei, M.; Alam, M. Remediation of industrial wastewater using four hydrophyte species: A comparison of individual (pot experiments) and mix plants (constructed wetland). J. Environ. Manag. 2020, 255, 109833. [Google Scholar] [CrossRef] [PubMed]
  26. APHA. Compendium of Methods for the Microbiological Examination, 3rd ed.; American Public Health Association: Washington, DC, USA, 1992; pp. 105–119, 325–367, 371–415, 451–469, 637–658. [Google Scholar]
  27. Saidu, M.; Yuzir, A.; Salim, M.R.; Richard, A.; Afiz, B. Effect of operating parameter on the anaerobic digestion oil palm mesocarp fibre with cattle manure for biogas production. In IOP Conference Series: Earth and Environmental Science; IOP Publishing: Bristol, UK, 2020; Volume 476, p. 012085. [Google Scholar]
  28. American Public Health Association. Standard Methods for the Examination of Water and Waste Water, 10th ed.; American Public Health Association: Washington, DC, USA, 1985. [Google Scholar]
  29. Gautam, M.; Agrawal, M. Identification of metal tolerant plant species for sustainable phytomanagement of abandoned red mud dumps. Appl. Geochem. 2019, 104, 83–92. [Google Scholar] [CrossRef]
  30. Shamshad, I.; Khan, S.; Waqas, M.; Ahmad, N.; Ur-Rehman, K.; Khan, K. Removal and bioaccumulation of heavy metals from aqueous solutions using freshwater algae. Water Sci. Technol. 2015, 71, 38–44. [Google Scholar] [CrossRef]
  31. Irshad, M.; Ahmad, S.; Pervez, A.; Inoue, M. Phytoaccumulation of Heavy Metals in Natural Plants Thriving on Wastewater Effluent at Hattar Industrial Estate, Pakistan. Int. J. Phytoremediat. 2015, 17, 154–158. [Google Scholar] [CrossRef] [PubMed]
  32. Khan, S.; Shamshad, I.; Waqas, M.; Nawab, J.; Ming, L. Remediating industrial wastewater containing potentially toxic elements with four freshwater algae. Ecol. Eng. 2017, 102, 536–541. [Google Scholar] [CrossRef]
  33. Singh, D.; Singh, V.; Agnihotri, A.K. Study of textile effluent in and around Ludhiana district in Punjab, India. Int. J. Environ. Sci. 2013, 3, 1271–1278. [Google Scholar]
  34. Amin, N.; Ibrar, D.; Alam, S. Heavy Metals Accumulation in Soil Irrigated with Industrial Effluents of Gadoon Industrial Estate, Pakistan and Its Comparison with Fresh Water Irrigated Soil. J. Agric. Chem. Environ. 2014, 3, 80–87. [Google Scholar] [CrossRef]
  35. Ali, F.; Israr, M.; Rehman, S.U.; Azizullah, A.; Gulab, H.; Idrees, M.; Iqbal, R.; Khattak, A.; Hussain, M.; Al-Zuaibr, F.M. Health risk assessment of heavy metals via consumption of dietary vegetables using wastewater for irrigation in Swabi, Khyber Pakhtunkhwa, Pakistan. PLoS ONE 2021, 16, e0255853. [Google Scholar] [CrossRef]
  36. Shehnaz, H.; Naz, S.; Shahnaz, L.; Yasmine, K.; Naqqash, T.; Haider, A. Bioremediation potential of some local grasses of Karachi city. FUUAST J. Biol. 2019, 9, 1–7. [Google Scholar]
  37. Marchiol, L.; Assolari, S.; Sacco, P.; Zerbi, G. Phytoextraction of heavy metals by canola (Brassica napus) and radish (Raphanus sativus) grown on multicontaminated soil. Environ. Pollut. 2004, 132, 21–27. [Google Scholar] [CrossRef] [PubMed]
  38. Rascio, N.; Navari-Izzo, F. Heavy metal hyperaccumulating plants: How and why do they do it? And what makes them so interesting? Plant Sci. 2011, 180, 169–181. [Google Scholar] [CrossRef] [PubMed]
  39. Tangahu, B.V.; Sheikh Abdullah, S.R.; Basri, H.; Idris, M.; Anuar, N.; Mukhlisin, M. A review on heavy metals (As, Pb, and Hg) uptake by plants through phytoremediation. Int. J. Chem. Eng. 2011, 2011, 939161. [Google Scholar] [CrossRef]
  40. Laghlimi, M.; Baghdad, B.; El Hadi, H.; Bouabdli, A. Phytoremediation Mechanisms of Heavy Metal Contaminated Soils: A Review. Open J. Ecol. 2015, 5, 375–388. [Google Scholar] [CrossRef]
  41. Wang, X.W.; Liu, Z.F. The Subcellular Distributions of Cadmium, Chromium, Copper, Plumbum and Zinc in Hyperaccumulator and Accumulator. Adv. Mater. Res. 2013, 726, 2434–2437. [Google Scholar] [CrossRef]
  42. Singh, S.; Dhyani, S.; Janipella, R.; Chakraborty, S.; Pujari, P.R.; Shinde, V.M.; Singh, K. Biomonitoring-Supported Land Restoration to Reduce Land Degradation in Intensively Mined Areas of India. Sustainability 2022, 14, 13639. [Google Scholar] [CrossRef]
  43. Khan, Z.I.; Ugulu, I.; Zafar, A.; Mehmood, N.; Bashir, H.; Ahmad, K.; Sana, M. Biomonitoring of heavy metals accumulation in wild plants growing at Soon valley, Khushab, Pakistan. Pak. J. Bot. 2021, 53, 247–252. [Google Scholar] [CrossRef] [PubMed]
  44. Campillo-Cora, C.; Fernández-Calviño, D.; Pérez-Rodríguez, P.; Fernández-Sanjurjo, M.; Núñez-Delgado, A.; Álvarez-Rodríguez, E.; Arias-Estévez, M.; Nóvoa-Muñoz, J. Copper and zinc in rhizospheric soil of wild plants growing in long-term acid vineyard soils. Insights on availability and metal remediation. Sci. Total. Environ. 2019, 672, 389–399. [Google Scholar] [CrossRef]
  45. Nasrullah, R.N.; Bibi, H.; Iqbal, M.; Durrani, M.I. Pollution load in industrial effluent and ground water of Gadoon Amazai Industrial Estate (GAIE) Swabi, NWFP. J. Agric. Biol. Sci. 2006, 1, 18–24. [Google Scholar]
  46. Baig, Z.M. Environmental Geochemistry of Water, Rocks and Soil of Gadoon and Surrounding Area District Swabi, North West Frontier Pakistan (NWFP), Pakistan. Master’s Thesis, National Centre of Excellence in Geology, University of Peshawar, Peshawar, Pakistan, 1996. [Google Scholar]
  47. Sonowal, S.; Prasad, M.N.V.; Sarma, H. C3 and C4 plants as potential phytoremediation and bioenergy crops for stabilization of crude oil and heavy metal co-contaminated soils-response of antioxidative enzymes. Trop. Plant Res. 2018, 5, 306–314. [Google Scholar] [CrossRef]
  48. Bai, Y.; Zhou, Y.; Gong, J. Physiological mechanisms of the tolerance response to manganese stress exhibited by Pinus massoniana, a candidate plant for the phytoremediation of Mn-contaminated soil. Environ. Sci. Pollut. Res. 2021, 28, 45422–45433. [Google Scholar] [CrossRef] [PubMed]
  49. Huang, H.; Zhao, Y.; Fan, L.; Jin, Q.; Yang, G.; Xu, Z. Improvement of manganese phytoremediation by Broussonetia papyrifera with two plant growth promoting (PGP) Bacillus species. Chemosphere 2020, 260, 127614. [Google Scholar] [CrossRef]
  50. Gravand, F.; Rahnavard, A.; Pour, G.M. Investigation of Vetiver Grass Capability in Phytoremediation of Contaminated Soils with Heavy Metals (Pb, Cd, Mn, and Ni). Soil Sediment Contam. Int. J. 2021, 30, 163–186. [Google Scholar] [CrossRef]
  51. Shuaibu, L.; Abdullahi, U.; Yaradua, A.I.; Bungudu, J.I. Phytoremediation Potentials of Cynodon dactylon on Heavy Metal Contaminated Soils from Challawa Industrial Estate, Kano-Nigeria. Asian J. Appl. Chem. Res. 2021, 9, 25–36. [Google Scholar] [CrossRef]
  52. Wang, J.; Xiong, Y.; Zhang, J.; Lu, X.; Wei, G. Naturally selected dominant weeds as heavy metal accumulators and excluders assisted by rhizosphere bacteria in a mining area. Chemosphere 2020, 243, 125365. [Google Scholar] [CrossRef]
  53. Da Silva, I.C.B.; Somavilla, A.; Soares, V.M.; Tarouco, C.P.; Schwalbert, R.; Trentin, E.; de Quadros, F.L.F.; Nicoloso, F.T.; Ferreira, P.A.A.; Brunetto, G. Potential phytoremediation of Pampa biome native and invasive grass species cohabiting vineyards contaminated with Cu in Southern Brazil. Environ. Sci. Pollut. Res. 2022, 29, 85376–85388. [Google Scholar] [CrossRef] [PubMed]
  54. Ancheta, M.H.; Quimado, M.O.; Tiburan, C.L., Jr.; Doronila, A.; Fernando, E.S. Copper and arsenic accumulation of Pityrogramma calomelanos, Nephrolepis biserrata, and Cynodon dactylon in Cu-and Au-mine tailings. J. Degrad. Min. Lands Manag. 2020, 7, 2201. [Google Scholar] [CrossRef]
  55. Ozyigit, I.I.; Dogan, I.; Karadeniz, S.; Severoglu, Z.; Demir, G.; Yalcin, I.E.; Yarci, C. Mineral nutrient compositions of field-grown weed and maize (Zea mays L.) plants in terms of competition. Pak. J. Agric. Sci. 2021, 58, 115–123. [Google Scholar]
  56. Mwegoha, W.J. The use of phytoremediation technology for abatement soil and groundwater pollution in Tanzania: Opportunities and challenges. J. Sustain. Dev. Afr. 2008, 10, 140–156. [Google Scholar]
  57. Tu, S.; Ma, L.Q.; Fayiga, A.O.; Zillioux, E.J. Phytoremediation of Arsenic-Contaminated Groundwater by the Arsenic Hyperaccumulating Fern Pteris vittata L. Int. J. Phytoremediat. 2004, 6, 35–47. [Google Scholar] [CrossRef]
  58. Erakhrumen, A.A.; Agbontalor, A. Phytoremediation: An environmentally sound technology for pollution prevention, control and remediation in developing countries. Educ. Res. Rev. 2007, 2, 151–156. [Google Scholar]
  59. Vangronsveld, J.; Herzig, R.; Weyens, N.; Boulet, J.; Adriaensen, K.; Ruttens, A.; Thewys, T.; Vassilev, A.; Meers, E.; Nehnevajova, E.; et al. Phytoremediation of contaminated soils and groundwater: Lessons from the field. Environ. Sci. Pollut. Res. 2009, 16, 765–794. [Google Scholar] [CrossRef]
Figure 1. Biomass of grass species after pot experiment. CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Figure 1. Biomass of grass species after pot experiment. CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Water 15 03439 g001
Figure 2. Shoot and root length of selected species in centimeter. CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Figure 2. Shoot and root length of selected species in centimeter. CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Water 15 03439 g002
Figure 3. Bioremoval Efficiency of selected species. CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Figure 3. Bioremoval Efficiency of selected species. CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Water 15 03439 g003
Figure 4. The Bioconcentration Factor of HMs for selected species. CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Figure 4. The Bioconcentration Factor of HMs for selected species. CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Water 15 03439 g004
Figure 5. Translocation Factor of HMs for selected species. CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Figure 5. Translocation Factor of HMs for selected species. CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Water 15 03439 g005
Table 1. Initial and final results for physicochemical parameters of soil samples.
Table 1. Initial and final results for physicochemical parameters of soil samples.
Physiochemical ParametersCT1T1CT2T2
Mean ± SDEff%pMean ± SDEff%pMean ± SDEff%pMean ± SDEff%p
EC (dS/m)I278.9 ± 4.5261.50.04 *308 ± 2.9048.90.01 *278.9 ± 4.5246.90.007 *308 ± 2.9038.30.002 *
F107.21 ± 4.63157.18 ± 3.51147.98 ± 4.33189.74 ± 2.69
pHI8.03 ± 0.88470.4219.4 ± 1.21750.288.03 ± 0.8833.60.119.4 ± 1.21530.381
F8.41 ± 2.3410.11 ± 1.728.30 ± 1.999.90 ± 2.12
TOM%I0.47 ± 0.0327.60.008 *0.39 ± 0.0143.50.01 *0.47 ± 0.0338.20.004 *0.39 ± 0.0148.70.003 *
F0.34 ± 0.010.22 ± 0.020.29 ± 0.010.20 ± 0.01
Phosphorus (mg/kg)I59.05 ± 2.3166.70.002 *97.21 ± 2.2558.10.00 **59.05 ± 2.3157.60.011 *97.21 ± 2.25490.010 *
F19.61 ± 1.0640.73 ± 2.1325.01 ± 1.9749.55 ± 5.22
Potassium (mg/kg)I498.6 ± 4.0451.60.00 **788.7 ± 6.3237.70.00 **498.6 ± 4.0449.20.00 **788.7 ± 6.3236.30.00 **
F241.12 ± 5.48491.10 ± 7.60253.08 ± 5.30502.4 ± 3.01
Saturation.%I31.9 ± 1.79450.002 *26.76 ± 1.7643.30.002 *31.9 ± 1.7929.810.00 **26.76 ± 1.7636.70.029 *
F17.35 ± 4.8315.16 ± 1.6622.39 ± 1.8816.93 ± 1.44
Cu (mg/kg)I76.3 ± 4.2742.50.00 **161.9 ± 2.5139.60.00 **76.3 ± 4.2759.00.001 *161.9 ± 2.5149.70.00 **
F43.82 ± 3.1997.77 ± 4.0131.27 ± 2.5081.42 ± 1.49
Mn (mg/kg)I1201.4 ± 2.4859.90.00 **2491.7 ± 8.9153.00.00 **1201.4 ± 2.4841.90.00 **2491.7 ± 8.9139.30.00 **
F481.11 ± 8.321170.78 ± 4.29697.38 ± 2.761511.29 ± 9.46
Note: CT1: Control for Cynodon dactylon; T1: Treatment for Cynodon dactylon; CT2: Control for Digiteria sanguinalis; T2: Treatment for Digiteria sanguinalis; EC: electrical conductivity; TOM: Total Organic Matter; Mn: Manganese: Cu: copper; I: initial value (before experiment value); F: final value (after exepriment value); p: t test signigicance value; * p < 0.04 (significant to the scale p < 0.05); ** p < 0.0001 (which is highly significant to the scale p < 0.05).
Table 2. HM concentration in selected species.
Table 2. HM concentration in selected species.
Heavy MetalsCT1T1CT2T2
Mean ± SDMean ± SDMean ± SDMean ± SD
Cu (mg/kg)Root19.06 ± 1.2341.68 ± 1.8725.33 ± 2.7139.43 ± 4.15
Shoot10.97 ± 0.7818.10 ± 0.8816.07 ± 1.6523.97 ± 2.32
Mn (mg/kg)Root501.12 ± 4.09837.18 ± 3.45381.03 ± 2.11671.19 ± 5.29
Shoot209.48 ± 2.18441.09 ± 3.17112.37 ± 1.89299.76 ± 2.62
Note: CT1: Control pot for Cynodon dactylon; T1: Treatment pot for Cynodon dactylon; CT2: Control pot for Digiteria sanguinalis; T2: Treatment pot for Digiteria sanguinalis.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Khan, S.; Dilawar, S.; Hassan, S.; Ullah, A.; Yasmin, H.; Ayaz, T.; Akhtar, F.; Gaafar, A.-R.Z.; Sekar, S.; Butt, S. Phytoremediation of Cu and Mn from Industrially Polluted Soil: An Eco-Friendly and Sustainable Approach. Water 2023, 15, 3439.

AMA Style

Khan S, Dilawar S, Hassan S, Ullah A, Yasmin H, Ayaz T, Akhtar F, Gaafar A-RZ, Sekar S, Butt S. Phytoremediation of Cu and Mn from Industrially Polluted Soil: An Eco-Friendly and Sustainable Approach. Water. 2023; 15(19):3439.

Chicago/Turabian Style

Khan, Sara, Shabnam Dilawar, Said Hassan, Amin Ullah, Humaira Yasmin, Tehreem Ayaz, Fazlullah Akhtar, Abdel-Rhman Z. Gaafar, Selvam Sekar, and Sadia Butt. 2023. "Phytoremediation of Cu and Mn from Industrially Polluted Soil: An Eco-Friendly and Sustainable Approach" Water 15, no. 19: 3439.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop