Next Article in Journal
Structural Relationship between Psychological Needs and Sport Adherence for Students Participating in Physical Education Class
Previous Article in Journal
Evolution of Tourism Risk Communication: A Bibliometric Analysis and Meta-Analysis of the Antecedents of Communicating Risk to Tourists
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 15
Issue 12
10.3390/su15129694
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Biomonitoring of Heavy Metal and Metalloid Contamination in Industrial Wastewater Irrigated Areas Using Sugar Beet (Brassica oleracea L.)

by
Ilker Ugulu
1,*,
Shehnaz Bibi
2,
Zafar Iqbal Khan
2,
Kafeel Ahmad
2,
Mudasra Munir
2,
Ifra Saleem Malik
2,
Abid Ejaz
2,3 and
Abdulwahed Fahad Alrefaei
4
1
Faculty of Education, Usak University, Usak 64000, Turkey
2
Department of Botany, University of Sargodha, Sargodha 40100, Pakistan
3
School of Geographical Sciences, Fujian Normal University, Fuzhou 350117, China
4
Department of Zoology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(12), 9694; https://doi.org/10.3390/su15129694
Submission received: 18 May 2023 / Revised: 14 June 2023 / Accepted: 15 June 2023 / Published: 16 June 2023
Browse Figures
Review Reports Versions Notes

Abstract

:
In Pakistan, wastewater such as industrial and urban wastewater is widely used for agricultural irrigation despite its chemical and pollutant content. In this respect, it is important to determine the risks of heavy metal accumulation in various agricultural products and the risks to human health. The aims of this study were to assess the heavy metal(loid)s contamination in soil and sugar beet samples and to assess the health risks of heavy metal(loid)s to the population via the consumption of sugar beet. The heavy metal(loid) values in the wastewater-irrigated soil samples ranged from 0.260 to 4.053 mg/kg, and wastewater-irrigated sugar beet samples ranged from 0.051 to 1.666 mg/kg. In contrast to Cd, Ni, Cu, Fe, Mn, Cr and Zn, which appeared to pose a health risk, Pb, Co, and Cr had Health Risk Index (HRI) values lower than 1.0 and did not appear to pose a threat to human health. Cd accumulation with HRI values over 1 (144.8) indicated that this metal is likely to have a major negative impact on local health.

1. Introduction

The concept of sustainability emerged due to environmental problems brought about by rapidly increasing industrialization after the Industrial Revolution [1]. While production increased with industrialization, the uncontrolled increase in waste caused pollution, disrupting the natural balance of air, water, soil, noise, and electromagnetic pollution. For example, pollutants such as nitrogen oxides, sulfur oxides, acidic gases and heavy metals create cumulative pollution in the atmosphere [2]. In addition, Potentially Harmful Elements (PHEs), led by heavy metals, are an important pollution threat to water resources, soil and living things [3].
Numerous studies have shown that industrial wastes from a variety of sectors, including from sugar processing, energy and power generation, cement manufacture and petrochemicals, are the primary contributors to environmental degradation, including water, soil, and food contamination [4,5]. Although the sugar industry, which is among these sectors, is seasonal and does not operate more than 150/160 days a year, a large amount of waste material is produced during sugar production, including many xenobiotics such as heavy metals [6,7]. Heavy metals can easily accumulate in water and soil and can accumulate in the edible parts of vegetables at high rates as they are easily absorbed by plant roots [8]. As a result of the uncontrolled discharge of wastes to the environment, especially, heavy metals are transmitted to the food production chain because pollutants in polluted soil, air and water are absorbed by plants. In general, heavy metals are not biodegradable and therefore also penetrate important human organs [9,10]. Contamination with heavy metals is of great importance for human health due to the metals’ capacity to enter the food chain. These substances can remain in ecosystems at dangerous concentrations for long periods of time, accumulating in living organisms and circulating through food chains. The products obtained due to these concentrations are extremely dangerous in terms of health [11].
Vegetables are indispensable for people’s nutrition programs because they contain many nutrients, including protein, carbohydrates, vitamins and minerals [12]. In places where water scarcity and land degradation occur, such as Pakistan, it is especially necessary to increase vegetable production to meet people’s nutritional needs [13,14,15]. Sugar beet (Beta vulgaris L.) is one of the plants that has an important place in terms of nutrition. Sugar Beet is a plant with rosette and flat leaves and a fleshy root. The sugar produced in the leaves by photosynthesis is intensely stored in the roots. The root of the sugar beet contains 5% pulp, 20% sugar and 75% water. Sugar Beet is an important cash crop worldwide due to the primary value of sugar. Water-insoluble sugar beet pulp is mainly composed of cellulose, hemicellulose, pectin and lignin and is used in animal nutrition. Molasses and pulp are by-products of sugar beet and constitute 10% of the harvest value due to their place in animal nutrition [16,17].
In Pakistan, wastewater such as industrial and urban wastewater is widely used for agricultural irrigation despite its chemical and pollutant content [18,19,20]. In this respect, it is important to determine the risks of heavy metal accumulation in various agricultural products and the risks to human health. The aims of this study were to assess the heavy metal(loid)s contamination in soil and sugar beet samples and to assess the health risks of heavy metal(loid)s to the population via the consumption of sugar beet.

2. Materials and Methods

2.1. Study Area

The Sargodha District is bordered to the north by the District of Jhelum, to the east by the Chenab River, and beyond that by the District of Mandi Bahauddin (Figure 1). The District of Hafizabad is bordered to the south by Jhang District and to the west by Khushab District, with the Jhelum River dividing the two Districts. The Sargodha District’s highest recorded temperatures are 450 °F in the summer and 0 °F in the winter. Sargodha currently has 24 husking units, 12 flour mills, 4 sugar mills, 7 textile mills, and 4 sugar mills in operation. Sargodha is also famous for handicrafts, citrus processing, agricultural machinery, light oven electrical industry, homemade fabrics and various agricultural and industrial products.

2.2. Sample Collection

For the research, the region in the Chishtia Sugar Mill Limited domain was selected as the sampling area. It is situated in the village of Sillanwali, tehsil Farooka.
A total of 100 mL of each source’s groundwater and wastewater from the sugar industry that was used to irrigate Site 1 (groundwater irrigated site) and Site 2 (wastewater irrigated site) was sampled to determine their metal concentrations. To prevent microbial growth, acid polypropylene was used to wash the bottles, and 1 mL of HNO3 was added. Before further analysis, the samples were chilled.
Each of Sites 1 and 2, which are irrigated by groundwater and wastewater from the sugar industry, respectively, had 25 soil samples taken. A stainless-steel drill was used to drill the planned locations for the soil samples to a depth of 10–15 cm, and all soil layers were partially cleaned. All materials were compressed into 2 mm crush strainers after being dried and crumpled. Soil samples were stored on croft paper until analysis.
In the same locations where soil samples were obtained, sugar beet samples were also taken. During sampling, 25 samples of these vegetables were collected from Sites 1 and 2. Samples of sugar beet were cleaned with deionized water to get rid of any particles, and they were then dried at 80 degrees centigrade until a consistent weight was obtained.

2.3. Sample Preparation

For digestion, one gram of soil was collected and combined with nitric acid (HNO3) in a beaker. The next day, hydrogen peroxide (H2O2) was added to the left-overnight combination and it was cooked in the digestive tube for an hour at 750 degrees Celsius until the solution was clear. After digestion was finished, the material was taken out of the digestion tube, filtered through filter paper, and then combined with distilled water to form a volume of 50 mm.
Nitric acid (HNO3) was added to a digestion tube along with a sample of 1 g of each vegetable. The following day, the digestive tube was placed on a hot plate set to 750 degrees. Hydrogen peroxide (H2O2) was added to the tube after 35 min, and the ensuing solution was boiled until clear. When digestion was finished, the digested material was taken out of the digestion tube, filtered using Whatman No. 42 filter paper, and then given a 50 mm volume raise with deionized water.

2.4. Analysis of Physicochemical Properties of Soil Samples

The electrical conductivity (EC), pH, and organic matter (OM), which are physical and chemical properties of soil, were studied. A pH meter was used to measure the pH of the soil [18]. A calculation of electrical conductivity was made based on Richard [19]. By using the Walkley and Black acid digestion technique, the OM of the soil was determined [20].

2.5. Metal(loid) Analysis

A PerkinElmer AAS-300 atomic absorption spectrophotometer was used to conduct a metal analysis on soil and vegetable samples. Lead (Pb), Cadmium (Cd), Manganese (Mn), Nickel (Ni), Copper (Cu), Iron (Fe), Chromium (Cr), Zinc (Zn) and Cobalt (Co) were the metals and metalloids that were the subject of the current research. Limit of Detection (LOD) values were assessed in accordance with the accepted procedures outlined in the literature [21]. The blank solution’s standard deviation (SD) and signal-to-noise ratio were both found to be 10; the value was therefore identified as LOD. Table 1 provides the detection thresholds for the pertinent heavy metals. The extremely sensitive hydride method was used to find the presence of nickel (Ni) and chromium (Cr).

2.6. Quality Control

Diagnostic marker standardization data from Merck (Darmstadt, Germany) were utilized to calibrate the device. The crystalline pupillages were methodically cleaned throughout the study using deionized water. Specialized Position Quantifiable assessments (SRM-2711 for soil and SRM NIST 1577b for vegetables) were used to complete the statement of value and ensure that the results were consistent. The mean SRM recoveries for Pb, Cu, Co, Mn, Cd, Cr, Zn and Fe in soil were 102%, 95%, 101%, 97%, 97%, 95% and 98%, respectively. The mean SRM recoveries for these metals in sugar beet were 95%, 95%, 98%, 102%, 102%, 96% and 99%, respectively.

2.7. Statistical Analysis

Using IBM SPSS 24.0 (Statistical Package for Social Sciences), a one-way analysis of variance (One-way ANOVA) was utilized to estimate the significant difference in metal/metalloid values between irrigation zones. The differences between values were tested statistically at the 0.05, 0.01 and 0.001 levels [22,23,24,25,26]. Furthermore, using IBM SPSS 24.0 software’s Hierarchical Clustering Analysis, the relationships between metal/metalloid values in the samples were compared and contrasted.

2.8. Bioconcentration Factor

The BCF values for each metal in this study were computed using the formula:
BCF = Cveg/Csoil
Metal values in plant tissues are denoted by the acronym Cveg (mg/kg, dry weight), whereas the term Csoil (mg/kg, dry weight) refers to metal concentration in soil [27,28,29].

2.9. Enrichment Factor

The enrichment factor (EF) was computed using the following formula:
EF = Cplant × Cref.plant/Csoil × Cref.soil
Standard reference amounts of Co, Zn, Cd, Fe, Pb, Cu, Ni, Mn and Cr for soil were employed in this study as 9.1, 44.19, 1.49, 56.9, 8.15, 8.39, 1.5 and 9.07 mg/kg, respectively [30,31]. Standard metal concentrations of 0.01, 0.6, 2.02, 20, 2, 10, 9.06, 80 and 1.3 mg/kg were used for the plant [32].

2.10. Daily Intake of Metals

The DIM values in this study were determined in accordance with Sajjad’s [33] definition:
DIM = Cmetal × Dfood intake/Baverage weight
The average body weight is indicated by Baverage weight, where Cmetal stands for the concentration of metal ingrains, Dfood intake for daily caloric intake, and Cmetal for the concentration of metals. The average daily vegetable intake rate for adults was calculated using 0.345 kg/person/day and an average body mass of 55.9 kg, from the literature [34].

2.11. Health Risk Index

The ratio of the oral reference dose (RfD) to the daily intake of metals (DIM) in food products is known as the HRI [35]:
HRI = DIM/RfD
The RfD values for Cd, Co, Cr, Cu, Fe, Ni, Pb, Zn and Mn, as reported by the USEPA [36], were 0.001, 0.04, 1.5, 0.04, 0.7, 0.02, 0.003, 0.3 and 0.04 mg/kg/day, respectively.

3. Results and Discussion

3.1. Toxicity of Heavy Metal(loid)s in Water

The heavy metal(loid)s values in the water samples of Site 1 (groundwater irrigated site) and Site 2 (wastewater irrigated site) varied from 0.768 to 1.733, 0.079 to 0.356, 0.382 to 0.649, 0.517 to 0.791, 2.369 to 9.138, 0.758 to 0.837, 1.167 to 1.816, 0.033 to 0.219 and 1.711 to 9.693 mg/kg for Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn, respectively (Figure 2). In both samples, the concentrations of Fe and Zn were higher than the other metal values. No metals, except for Fe and Zn, had statistically significant differences in terms of wastewater type (p > 0.05) (Table 2).
Since there are not many clean water sources in Pakistan, groundwater and wastewater from different sources are combined in a certain ratio and used as canal waters for the irrigation of crops [37,38,39,40,41,42,43]. The allowable limits for Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn in water were reported by FAO, WHO, Standard Guidelines in Europe [44] and USEPA [36] as 0.01, 0.05, 0.5, 0.2, 5, 0.2, 0.2, 0.065 and 2 mg/L, respectively. The heavy metal(loid) values in this study were higher than these limits in the water, except for Mn. The results demonstrate that there is a high risk of pollution due to the high metal values in low-quality irrigation water. The high metal(loid) concentrations in wastewater from the sugar industry are of industrial origin, but they may also be caused by other elements like soil erosion, urban runoff, vehicular traffic, industry and aerosol particles in groundwater [45].

3.2. Biochemical Composition and Toxicity of Heavy Metal(loid)s in Soil

The metal(loid) concentrations in the soil samples ranged from 1.852 to 2.106, 0.726 to 0.767, 1.206 to 1.837, 1.485 to 2.206, 3.274 to 4.053, 0.810 to 1.090, 1.345 to 1.546, 0.346 to 0.383 and 0.260 to 0.907 mg/kg for Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn, respectively (Figure 3). Except for Co and Pb values, there was no significant site effect on the metal values in the soil samples (p > 0.05) (Table 3).
Heavy metal(loid)s in wastewater are easily transferred from the soil to vegetables [46,47,48]. The metal(loid) values in this study were lower than the maximum limits for Co (9.1), Cr (9.07), Cu (8.39), Fe (56.9), Mn (46.74), Ni (9.06), Pb (3.50) and Zn (44.19) mg/kg [30], while values of Cd (1.96 to 2.01 mg/kg) were higher than the maximum limit (1.49 mg/kg) reported by Singh et al. [31]. As a result of many studies carried out in different plant samples, wastewater types, seasons and environments in the region, results similar to this study and above the allowable limit were reported for Cd. These findings support the findings obtained in this study [49].
Both sample regions contained loamy soils, and Site 1’s soil acidity was 8.06 while Site 2’s was 7.64. Electrical conductivities of the soil samples were determined to be 1.80 in Site 1 and 7.66 in Site 2. The proportion of organic matter in the soil samples was 0.55 for Site 1 and 0.69 for Site 2, respectively (Table 4). According to Khan et al. [50], one of the most significant factors affecting the availability of metals in the soil is the soil surface. Loamy soil has large pore diameters and a weak ability to retain particles. The soil in the research region can be considered to be more permeable to heavy metals as a result, allowing them to infiltrate into the deeper soil layers. The pH of the soil was found to be lower at Site 2, which received wastewater irrigation. This may be because wastewater irrigation results in the deterioration of organic matter and the formation of organic acids in the soil [48]. Additionally, Siddique et al. [51] reported that wastewater-irrigated sites had relatively higher organic matter levels than other sites. The formation of salinity, which is the most significant indicator in wastewater irrigation fields [32], is influenced by electrical conductivity.

3.3. Toxicity of Heavy Metal(loid)s on Sugar Beet

The heavy metal(loid) values in the sugar beet samples ranged from 1.273 to 1.357, 0.051 to 0.115, 0.407 to 0.465, 0.783 to 0.970, 0.931 to 1.288, 0.498 to 0.837, 0.670 to 0.805, 0.088 to 0.143 and 1.482 to 1.666 mg/kg for Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn, respectively (Figure 4). As a result of the statistical analysis, the difference between the metal values in the sugar beet samples irrigated with groundwater and wastewater was statistically significant for Cd, Co, Cr, Ni and Pb (p > 0.05, 0.01, 0.001 levels) (Table 5).
The current values for Co, Cr, Cu, Fe, Ni, Pb, Zn and Mn in the sugar beet samples were lower than the maximum limits of Co (50 mg/kg), Cr (2.3 mg/kg), Cu (73.3 mg/kg), Fe (425.5 mg/kg), Mn (500 mg/kg), Ni (67 mg/kg), Pb (0.3 mg/kg) and Zn (99.4 mg/kg) as reported by FAO/WHO [32]. However, the Cd values (1.273 to 1.357 mg/kg) in sugar beet samples were above the maximum limit (0.2 mg/kg) as indicated by FAO/WHO [32]. The main sources of Cd in environmental components including soil and plants include phosphate fertilizers, irrigation wastewater, air pollution from factories and sprays from such sectors [52]. The high Cd values in sugar beet samples cultivated in the research region can be explained by the listed sources. In addition, Rai et al. [53] came to the conclusion that the complex process of heavy metals and other pollution uptake by plants is influenced by soil characteristics, the physicochemical characteristics of irrigated wastewater and heavy metal properties.

3.4. Assessments of Contamination and Associated Health Risk

3.4.1. Hierarchical Clustering Analysis

According to Average Linkage cluster analysis, the dendrogram for the measured metal(loids) in the soil samples was divided into two major groups. Only Fe was part of the first main group, while the other eight metal(loids) were part of the second main group (Figure 5). Two major groups could be seen in the dendrogram for the measured metal(loids) in the sugar beet samples according to the Average Linkage cluster analysis (Figure 6). Fe, Zn and Cd were included in the first main group, and the remaining six metal(loids) were included in the second main group. The fourth metal(loid)s were divided into the second main group’s two subgroups, with the first subgroup including Cu, Mn and Ni. The second subgroup was further divided into two subgroups, the first of which only contained Cr and the second of which only contained the remaining metal(loids) (Figure 6).
The dendrograms produced by the Hierarchical Cluster Analysis (Figure 5 and Figure 6) show that Fe was divided into a distinct group among the metals in the soil samples, whereas Fe, Cd and Zn were split into a distinct group in the sugar beet samples. In contrast to soil samples, characteristics of the plant species and the mobility of zinc from the soil to plants may have an impact on whether zinc is included in the group with Fe and Cd in plant samples. In a study on the impact of various organic fertilizers on metal accumulation in vegetables in Sargodha, Pakistan, Ugulu et al. [54] reported that Fe and Zn accumulations were distinguished from other metals using hierarchical cluster analysis. In this way, the results and scope of the present study are comparable to those of Ugulu et al. [54].

3.4.2. Bioconcentration Factor

The lowest BCF value was recorded for Co at Site 1, and the highest BCF was recorded for Zn at Site 1 (Table 6). The bioavailability of metals and metalloids at a certain place in a plant species might be referred to as the bioconcentration factor [55]. The maximum BCF in the current study was found for Zn, whereas the lowest BCF was found for Co. The relative abundance of heavy metals in the higher layers of the soil and the earth’s crust can be used to explain the high Zn concentration seen in plants (Zn > Cr > Pb > Ni > Cu > Cd) [56]. The long-term use of wastewater for irrigation in agriculture, however, may result in a rise in the concentration of Zn and other heavy metals [57]. These conclusions are supported by the high BCF values for Zn that were found in this investigation.

3.4.3. Enrichment Factor

The highest EF values were found for Cd at both sites and the lowest EF value was found for Co at Site 1 (Table 7). The enrichment factor is influenced by a variety of factors, including edaphic conditions, the abundance of metals in the environment, plants’ ability to absorb metals, their physiological composition, and growth phenomena [58,59,60]. The highest EF value in the current study was found for Cd (22.91). Additionally, the EF values for Ni, Mn and Zn exceeded 1.0. Khan et al. [61] examined the build-up of heavy metals in Luffa samples in Bhakkar, another city in Pakistan, and found EF values exceeding 1.00 for Pb, Zn and Cd. The discrepancies in results may be due to the fact that metal absorption and build-up from soil to root, root to stem and grains differ from site to site in plants [50].

3.4.4. Daily Intake of Metals and Health Risk Index

The highest DIM value, measured at Site 1, was 7.00 mg/kg/day of Co, while the lowest value, measured at Site 2, was 0.002 mg/kg/day of Co. Cd at Site 2 had the highest HRI value, which was 144.8, and Co at Site 2 had the lowest HRI value, which was 0.002 (Table 8).
The tolerated daily metal limits for Cd, Pb, Cr, Co, Zn and Fe were published as 0.0007 0.0005, 0.3, 0.023, 0.43 and 0.8 mg/kg/day, respectively, by EFSA [62], FAO/WHO [32] and WHO [63]. The Fe value for Site 2, as well as the DIM values of Cd, Co and Zn for both sites, was greater than these acceptable thresholds. In S. oleracea samples irrigated with wastewater in Beijing, China, Khan et al. [64] reported DIM values of 0.032, 0.008, 0.002, 0.0003, 0.005 and 0.005 for Zn, Cu, Pb, Cd, Cr and Ni, respectively. The present DIM values were higher than those obtained by Khan et al. [64]. The differences in the outcomes may be caused by the characteristics of the wastewater, as well as by geographical characteristics and plant type [34].
Sugar beet samples from locations that were irrigated with groundwater and wastewater from the sugar industry ranged in health risk index (HRI) value from 0.002 to 144.8. In contrast to Cd, Ni, Cu, Fe, Mn, Cr and Zn, which appeared to pose a health risk, Pb, Co and Cr had HRI values lower than 1.0 and did not appear to pose a threat to human health. Cd accumulation with HRI values over 1 (144.8) indicated that this metal is likely to have a major negative impact on local health. Cadmium (Cd), a multi-tissue carcinogen, is very harmful to both people and animals. Physical, chemical and biological components including water, soil, plant species and the amount of metals utilized by plants all have an impact on how health hazards are assessed [54].

4. Conclusions

The goals of this study were to analyze the levels of heavy metal(loid)s in the soil–sugar beet system in regions that were irrigated with industrial effluent, to evaluate the heavy metal(loid)s contamination of sugar beet samples using pollution indices and to estimate the health hazards of heavy metal(loid)s to the local people from eating sugar beet. Firstly, except for Mn, the heavy metal(loid) values in the water samples in the area were higher than the maximum permitted limits. However, it was found that, except for Cd, the heavy metal levels in the soil and sugar beet samples watered with these waters were lower than the maximum allowed limits. From this perspective, there is a risk associated with the irrigation of vegetables like sugar beet, cauliflower, radish, lettuce and cabbage using water from the sugar sector that contains a certain level of heavy metals. According to the findings of the Health Risk Index evaluation carried out for this study, the accumulations of Co, Cu, Fe, Mn, Cr, Zn and particularly Cd provide a health risk when consumed. Wastewater irrigation is widely employed throughout the world, especially in underdeveloped countries. Therefore, it is suggested that wastewater treatment facilities be built and used effectively to reduce the risk. In locations where these opportunities are uncommon, the use of appropriate bioremediation techniques and the cultivation of plants with decreased accumulation may be beneficial. The potential health concerns linked to exposure to heavy metals through diverse pathways should be the main topic of future study in any case.

Author Contributions

Formal analysis, S.B., M.M. and I.S.M.; Investigation, S.B., Z.I.K. and K.A.; Methodology, I.U. and Z.I.K.; Project administration, Z.I.K., K.A. and A.E.; Resources, I.S.M. and A.F.A.; Software, I.U. and A.F.A.; Supervision, Z.I.K. and K.A.; Validation, K.A.; Visualization, K.A.; Writing—original draft, I.U. and Z.I.K.; Writing—review and editing, I.U. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

We extend our appreciation to the Researchers Supporting Project (no. RSP2023R218), King Saud University, Riyadh, Saudi Arabia, and also to the valuable researchers, Asma Ashfaq, Shahzadi Mahpara, Ijaz Rasool Noorka, Hafsa Memona and Tasneem Ahmad.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Deh-Haghi, Z.; Bagheri, A.; Fotourehchi, Z.; Damalas, C.A. Farmers’ acceptance and willingness to pay for using treated wastewater in crop irrigation: A survey in western Iran. Agric. Water Manag. 2020, 239, 106262. [Google Scholar] [CrossRef]
  2. Nawaz, H.; Anwar-ul-Haq, M.; Akhtar, J.; Arfan, M. Cadmium, chromium, nickel and nitrate accumulation in wheat (Triticum aestivum L.) using wastewater irrigation and health risks assessment. Ecotoxicol. Environ. Saf. 2021, 208, 111685. [Google Scholar] [CrossRef]
  3. Di Baccio, D.; Kopriva, S.; Sebastiani, L.; Rennenberg, H. Does glutathione metabolism have a role in the defence of poplar against zinc excess? New Phytologist. 2005, 167, 73–80. [Google Scholar] [CrossRef] [PubMed]
  4. 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] [PubMed]
  5. Seaman, J.C.; Arey, J.; Bertsch, P.M. Immobilization of Nickel and Other Metals in Contaminated Sediments by Hydroxyapatite Addition. J. Environ. Qual. 2001, 30, 460–469. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Ofori, S.; Puskacova, A.; Růzickova, I.; Wanner, J. Treated wastewater reuse for irrigation: Pros and Cons. Sci. Total Environ. 2020, 760, 144026. [Google Scholar] [CrossRef]
  7. Lorestani, B.; Cheraghi, M.; Yousefi, N. Accumulation of Pb, Fe, Mn, Cu and Zn in plants and choice of hyper accumulator plants in the industrial town of Vian, Iran. Arch. Biol. Sci. 2011, 63, 739–745. [Google Scholar] [CrossRef]
  8. Karak, T.; Paul, R.K.; Sonar, I.; Sanyal, S.; Ahmed, K.Z.; Boruah, R.K.; Das, D.K.; Dutta, A.K. Chromium in soil and tea (Camellia sinensis L.) infusion: Does soil amendment with municipal solid waste compost make sense? Food Res. Int. 2014, 64, 114–124. [Google Scholar] [CrossRef]
  9. Yap, D.W.; Adezrian, J.; Khairiah, J.; Ismail, B.S.; Ahmad-Mahir, R. The uptake of heavy metals by paddy (Oryza sativa) in Kota Marudu, Sabah, Malaysia. Am.-Eurasian J. Agric. Environ. Sci. 2009, 6, 16–19. [Google Scholar]
  10. Atamaleki, A.; Yazdanbakhsh, A.; Fakhri, Y.; Mahdipour, F.; Khodakarim, S.; Khaneghah, A.M. The concentration of potentially toxic elements (PTEs) in the onion and tomato irrigated by wastewater: A systematic review; meta-analysis and health risk assessment. Food Res. Int. 2019, 125, 108518. [Google Scholar] [CrossRef]
  11. Khanam, R.; Kumar, A.; Nayak, A.K.; Shahid, M.; Tripathi, R.; Vijayakumar, S.; Bhaduri, D.; Kumar, U.; Mohanty, S.; Panneerselvam, P.; et al. Metal (loid) s (As, Hg, Se, Pb and Cd) in paddy soil: Bioavailability and potential risk to human health. Sci. Total Environ. 2020, 699, 134330. [Google Scholar] [CrossRef]
  12. Ugulu, I.; Baslar, S.; Dogan, Y.; Aydin, H. The determination of colour intensity of Rubia tinctorum and Chrozophora tinctoria distributed in Western Anatolia. Biotechnol. Biotechnol. Equip. 2009, 23, 410–413. [Google Scholar] [CrossRef] [Green Version]
  13. Hussain, M.I.; Muscolo, A.; Farooq, M.; Ahmad, W. Sustainable use and management of non-conventional water resources for rehabilitation of marginal lands in arid and semiarid environments. Agric. Water Manag. 2019, 221, 462–476. [Google Scholar] [CrossRef]
  14. 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]
  15. Ugulu, I.; Bibi, S.; Khan, Z.I.; Ahmad, K.; Munir, M.; Malik, I.S. Potentially Toxic Metal Accumulation in Spinach (Spinacia oleracea L.) Irrigated with Industrial Wastewater and Health Risk Assessment from Consumption. Bull. Environ. Contam. Toxicol. 2022, 109, 1117–1125. [Google Scholar] [CrossRef] [PubMed]
  16. Eticha, T.; Hymete, A. Determination of some heavy metals in barley locally grown for brewing and its malt in Ethiopia. J. Bioanal. Biomed. 2015, 7, 171–173. [Google Scholar]
  17. Atabaki, N.; Shaharuddin, N.A.; Ahmad, S.A.; Nulit, R.; Abiri, R. Assessment of water mimosa (Neptunia oleracea lour.) morphological, physiological, and removal efficiency for phytoremediation of arsenic-polluted water. Plants 2020, 9, 1500. [Google Scholar] [CrossRef]
  18. Mclean, E.O. Soil pH and lime requirement. In Methods of Soil Analysis, Part 2. Chemical and Microbiological Properties; Page, A.L., Miller, R.H., Keeney, D.R., Eds.; American Society of Agronomy: Madison, WI, USA, 1982; pp. 199–223. [Google Scholar]
  19. Page, A.L. Methods of Soil Analysis, Part 2. Chemical and Microbiological Properties; Agronomy Society of America; Soil Science Society of America: Madison, WI, USA, 1982. [Google Scholar]
  20. Richard, L.A. Diagnosis and improvement of saline and alkali soils. In Agriculture Handbook; United States Department of Agriculture: Washington, DC, USA, 1954; Volume 60. [Google Scholar]
  21. Armbruster, D.A.; Tillman, M.D.; Hubbs, L.M. Limit of detection (LQD)/limit of quantitation (LOQ): Comparison of the empirical and the statistical methods exemplified with GC–MS assays of abused drugs. Clin. Chem. 1994, 40, 1233–1238. [Google Scholar] [CrossRef]
  22. Ugulu, I. A quantitative investigation on recycling attitudes of gifted/talented students. Biotechnol. Biotechnol. Equip. 2015, 29, 20–26. [Google Scholar] [CrossRef]
  23. Zhuang, P.; McBride, M.B.; Xia, H.; Li, N.; Li, Z. Health risk from heavy metals via consumption of food crops in the vicinity of Dabaoshan mine, South China. Sci. Total Environ. 2009, 407, 1551–1561. [Google Scholar] [CrossRef]
  24. Yorek, N.; Sahin, M.; Ugulu, I. Students’ representations of the cell concept from 6 to 11 grades: Persistence of the “fried-egg model”. Int. J. Physic. Sci. 2010, 5, 15–24. [Google Scholar]
  25. Praspaliauskas, M.; Pedišius, N. A review of sludge characteristics in Lithuania’s wastewater treatment plants and perspectives of its usage in thermal processes. Renew. Sustain. Energy Rev. 2017, 67, 899–907. [Google Scholar] [CrossRef]
  26. Ugulu, I. Efficacy of recycling education integrated with ecology course prepared within the context of enrichment among gifted students. Int. J. Educ. Sci. 2019, 26, 49–58. [Google Scholar] [CrossRef] [Green Version]
  27. Domańska, J.; Leszczyńska, D.; Badora, A. The Possibilities of Using Common Buckwheat in Phytoremediation of Mineral and Organic Soils Contaminated with Cd or Pb. Agriculture 2021, 11, 562. [Google Scholar] [CrossRef]
  28. Rocha, C.S.; Rocha, D.C.; Kochi, L.Y.; Carneiro, D.N.M.; dos Reis, M.V.; Gomes, M.P. Phytoremediation by ornamental plants: A beautiful and ecological alternative. Environ. Sci. Pollut. Res. Int. 2022, 29, 3336–3354. [Google Scholar] [CrossRef]
  29. Gohain, S.B.; Bordoloi, S. Impact of municipal solid waste disposal on the surface water and sediment of adjoining wetland Deepor Beel in Guwahati, assam, India. Environ. Monit. Assess. 2021, 193, 278. [Google Scholar] [CrossRef]
  30. Dutch Standard. Circular on Target Values and Intervention Values for Soil Remediation; Dutch Standard: Amsterdam, The Netherlands, 2000. [Google Scholar]
  31. 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. [Google Scholar] [CrossRef]
  32. ALINORM 01/ 12A; Food Additive and Contaminants. Joint FAO/WHO Food Standards Programme. Codex Alimentarius Commission: Rome, Italy, 2001; pp. 1–289.
  33. Sajjad, K.; Farooq, R.; Shahbaz, S.; Khan, M.A.; Sadique, M. Health risk assessment of heavy metals for population via consumption of vegetables. World Appl. Sci. J. 2009, 6, 1602–1606. [Google Scholar]
  34. Wajid, K.; Ahmad, K.; Khan, Z.I.; Nadeem, M.; Bashir, H.; Chen, F.; Ugulu, I. Effect of organic manure and mineral fertilizers on bioaccumulation and translocation of trace metals in maize. Bull. Environ. Contam. Toxicol. 2020, 104, 649–657. [Google Scholar] [CrossRef]
  35. Ippolito, J.A.; Laird, D.A.; Busscher, W.J. Environmental Benefits of Biochar. J. Environ. Qual. 2012, 41, 967–972. [Google Scholar] [CrossRef] [Green Version]
  36. USEPA. Volume II-Food Ingestion Factors. In Exposure Factors Handbook; EPA/ 600//P-95/002Fa; Office of Research and Development; US Environmental Protection Agency: Washington, DC, USA, 1997. [Google Scholar]
  37. Olaniran, A.O.; Balgobind, A.; Pillay, B. Bioavailability of Heavy Metals in Soil: Impact on Microbial Biodegradation of Organic Compounds and Possible Improvement Strategies. Int. J. Mol. Sci. 2013, 14, 10197–10228. [Google Scholar] [CrossRef] [Green Version]
  38. Badawy, K.R.; Abd El-Gawad, A.M.; Osman, H.E. Health risks assessment of heavy metals and microbial contamination in water, soil and agricultural foodstuff from wastewater irrigation at Sahl El-Hessania area, Egyptian. J. Appl. Sci. Res. 2013, 9, 3091–3107. [Google Scholar]
  39. Chabukdhara, M.; Nema, A.K. Heavy Metals in Water, Sediments, and Aquatic Macrophytes: River Hindon, India. J. Hazard. Toxic Radioact. Waste 2012, 16, 273–281. [Google Scholar] [CrossRef]
  40. Vardhan, K.H.; Ponnusamy, S.K.; Panda, R.C. A review on heavy metal pollution, toxicity and remedial measures: Current trends and future perspectives. J. Mol. Liq. 2019, 290, 111197. [Google Scholar] [CrossRef]
  41. Tariq, F.; Wang, X.; Saleem, M.H.; Khan, Z.I.; Ahmad, K.; Saleem Malik, I.; Munir, M.; Mahpara, S.; Mehmood, N.; Ahmad, T.; et al. Risk Assessment of Heavy Metals in Basmati Rice: Implications for Public Health. Sustainability 2021, 13, 8513. [Google Scholar] [CrossRef]
  42. Chary, N.; Kamala, C.T.; Raj, D.S. Assessing risk of heavy metals from consuming food grown on sewage irrigated soils and food chain transfer. Ecotoxicol. Environ. Saf. 2008, 69, 513–524. [Google Scholar] [CrossRef]
  43. Othman, A.A.; Ali, R.; Othman, A.M.; Ali, J.; Habila, M.A. Assessment of toxic metals in wheat crops grown in selected soils, irrigated by different water sources. Arab. J. Chem. 2016, 9, 1555–1562. [Google Scholar] [CrossRef] [Green Version]
  44. Chiroma, T.M.; Ebewele, R.O.; Hymore, F.K. Comparative assessment of heavy metal levels in soil, vegetables and urban grey wastewater used for irrigation in Yola and Kano. Int. Ref. J. Eng. Sci. 2014, 3, 1–9. [Google Scholar]
  45. Zuo, S.; Dai, S.; Li, Y.; Tang, J.; Ren, Y. Analysis of heavy metal sources in the soil of riverbanks across an urbanization gradient. Int. J. Environ. Res. Public Health 2018, 15, 2175. [Google Scholar] [CrossRef] [Green Version]
  46. Clemens, S.; Ma, J.F. Toxic Heavy Metal and Metalloid Accumulation in Crop Plants and Foods. Annu. Rev. Plant Biol. 2016, 67, 489–512. [Google Scholar] [CrossRef] [Green Version]
  47. Barčauskaitė, K.; Mažeika, R. Chemical composition and risk assessment of spring barley grown in artificially contaminated soil. Environ. Sci. Pollut. Res. 2021, 28, 21684–21695. [Google Scholar] [CrossRef]
  48. Vymazal, J. Concentration is not enough to evaluate accumulation of heavy metals and nutrients in plants. Sci. Total Environ. 2016, 544, 495–498. [Google Scholar] [CrossRef]
  49. Ugulu, I.; Unver, M.C.; Dogan, Y. Potentially toxic metal accumulation and human health risk from consuming wild Urtica urens sold on the open markets of Izmir. Euro-Mediterr. J. Environ. Integr. 2019, 4, 36. [Google Scholar] [CrossRef]
  50. Teschke, R. Aluminum, Arsenic, Beryllium, Cadmium, Chromium, Cobalt, Copper, Iron, Lead, Mercury, Molybdenum, Nickel, Platinum, Thallium, Titanium, Vanadium, and Zinc: Molecular Aspects in Experimental Liver Injury. Int. J. Mol. Sci. 2022, 23, 12213. [Google Scholar] [CrossRef]
  51. Masindi, V.; Muedi, K.L. Environmental contamination by heavy metals. Heavy Met. 2018, 10, 115–132. [Google Scholar]
  52. Qadir, M.; Ghafoor, A.; Murtaza, G.; Murtaza, G. Cadmium concentration in vegetables grown on urban soils irrigated with untreated municipal sewage. Environ. Dev. Sustain. 2000, 2, 13–21. [Google Scholar] [CrossRef]
  53. Rai, P.K.; Lee, S.S.; Zhang, M.; Tsang, Y.F.; Kim, K.-H. Heavy metals in food crops: Health risks, fate, mechanisms, and management. Environ. Int. 2019, 125, 365–385. [Google Scholar] [CrossRef]
  54. Song, T.; An, Y.; Cui, G.; Tong, S.; He, J. Bioconcentrations and health risk assessment of heavy metals in crops in the Naoli River Basin agricultural area, Sanjiang Plain, China. Environ. Earth Sci. 2021, 80, 452. [Google Scholar] [CrossRef]
  55. Dvořáková, T.B.; Vymazal, J. Distribution of heavy metals in Phragmites australis growing in constructed treatment wetlands and comparison with natural unpolluted sites. Ecol. Eng. 2022, 175, 106505. [Google Scholar]
  56. Alloway, B.J. Heavy Metals in Soils; Springer: Dordrecht, The Netherlands, 2013. [Google Scholar]
  57. Rattan, R.K.; Datta, S.P.; Chhonkar, P.K.; Suribabu, K.; Singh, A.K. Long-term impact of irrigation with sewage effluents on heavy metal content in soils, crops and groundwater—A case study. Agric. Ecosyst. Environ. 2005, 109, 310–322. [Google Scholar] [CrossRef]
  58. Klink, A. A comparison of trace metal bioaccumulation and distribution in Typha latifolia and Phragmites australis: Implication for phytoremediation. Environ. Sci. Pollut. Res. 2017, 24, 3843–3852. [Google Scholar] [CrossRef]
  59. Mondal, S.C.; Sarma, B.; Farooq, M.; Nath, D.J.; Gogoi, N. Cadmium bioavailability in acidic soils under bean cultivation: Role of soil additives. Int. J. Environ. Sci. Technol. 2020, 17, 153–160. [Google Scholar] [CrossRef]
  60. Ugulu, I.; Khan, Z.I.; Rehman, S.; Ahmad, K.; Munir, M.; Bashir, H.; Nawaz, K. Trace metal accumulation in Trigonella foenum-graecum irrigated with wastewater and human health risk of metal access through the consumption. Bull. Environ. Contam. Toxicol. 2019, 103, 468–475. [Google Scholar] [CrossRef]
  61. Briffa, J.; Sinagra, E.; Blundell, R. Heavy metal pollution in the environment and their toxicological effects on humans. Heliyon 2020, 6, e04691. [Google Scholar] [CrossRef]
  62. EFSA, European Food Safety Authority. Panel on Additives and Products or Substances used in Animal Feed (FEEDAP). EFSA J. 2013, 11, 3287. [Google Scholar]
  63. WHO. Trace Elements in Human Nutrition and Health; World Health Organization: Geneva, Switzerland, 1996.
  64. Khan, S.; Cao, Q.; Zheng, Y.M.; Huang, Y.Z.; Zhu, Y.G. Health risks of heavy metals in contaminated soils and food crops irrigated with wastewater in Beijing, China. Environ. Pollut. 2008, 152, 686–692. [Google Scholar] [CrossRef]
Sustainability 15 09694 g001 550
Figure 1. The map of Sargodha.
Figure 1. The map of Sargodha.
Sustainability 15 09694 g001
Sustainability 15 09694 g002 550
Figure 2. Heavy metal concentrations in water samples.
Figure 2. Heavy metal concentrations in water samples.
Sustainability 15 09694 g002
Sustainability 15 09694 g003 550
Figure 3. Heavy metal concentrations in soil samples.
Figure 3. Heavy metal concentrations in soil samples.
Sustainability 15 09694 g003
Sustainability 15 09694 g004 550
Figure 4. Heavy metal concentrations in sugar beet samples.
Figure 4. Heavy metal concentrations in sugar beet samples.
Sustainability 15 09694 g004
Sustainability 15 09694 g005 550
Figure 5. Dendrogram based on the soil samples from two areas.
Figure 5. Dendrogram based on the soil samples from two areas.
Sustainability 15 09694 g005
Sustainability 15 09694 g006 550
Figure 6. Dendrogram based on the sugar beet samples from two areas.
Figure 6. Dendrogram based on the sugar beet samples from two areas.
Sustainability 15 09694 g006
Table
Table 1. Detection limits of Atomic Absorption Spectrophotometer (mg/L).
Table 1. Detection limits of Atomic Absorption Spectrophotometer (mg/L).
ElementDetection Limit
Lead (Pb)0.008 (Flame AA)
Cadmium (Cd)0.001 (Flame AA)
Nickel (Ni)0.003 (Flame AA)
Iron (Fe)0.006 (Flame AA)
Copper (Cu)0.002 (Flame AA)
Manganese (Mn)0.002 (Flame AA)
Zinc (Zn)0.001 (Flame AA)
Cobalt (Co)0.003 (Flame AA)
Table
Table 2. Analysis of variance for heavy metal/metalloid values in water samples.
Table 2. Analysis of variance for heavy metal/metalloid values in water samples.
Source of VariationDegree of FreedomMean Squares
CdCoCrCuFeMnNiPbZn
Treatments10.244 ns0.002 ns0.004 ns0.482 ns7.964 *0.388 ns0.246 ns0.001 ns0.009 ***
Error60.0270.0660.0030.0310.5310.0710.2390.0220.003
Note: *, *** significant at 0.05, and 0.001 levels; ns, non-significant.
Table
Table 3. Analysis of variance for heavy metal/metalloid values in soil samples.
Table 3. Analysis of variance for heavy metal/metalloid values in soil samples.
Source of VariationDegree of FreedomMetal
PbCdNiFeCuMnCrZnCo
Sites10.03 ***0.13 ns0.08 ns121.41 ns1.04 ns0.16 ns0.79 ns0.84 ns0.03 ***
Error60.0030.0030.0061.4090.0330.0900.0320.1950.002
Note: *** significant at 0.001 levels; ns, non-significant.
Table
Table 4. Physico-chemical parameters of the soil samples at two sites.
Table 4. Physico-chemical parameters of the soil samples at two sites.
Physico-Chemical ParameterspHEC (dsm−1)Organic Matter (%)Texture Class
Site 18.060 ± 0.01291.8040 ± 0.00120.5565 ± 0.0006Loamy soil
Site 27.640 ± 0.01297.660 ± 0.01290.694 ± 0.0020Loamy soil
MS0.353 ns68.585 ns0.038 **Loamy soil
Note: ** significant at 0.01 level; ns, non-significant.
Table
Table 5. Analysis of variance for heavy metal/metalloid values in sugar beet samples.
Table 5. Analysis of variance for heavy metal/metalloid values in sugar beet samples.
Source of VariationDegree of FreedomMetal
PbCdNiFeCuMnCrZnCo
Sites10.006 ***0.01 *0.03 **0.2 ns0.06 ns0.23 ns0.007 ***0.06 ns0.008 ***
Error60.0000.0020.0070.0340.0330.0260.0030.0420.001
*, **, *** significant at 0.05, 0.01 and 0.001 levels; ns, non-significant.
Table
Table 6. Bioconcentration factor for metal(loid)s.
Table 6. Bioconcentration factor for metal(loid)s.
Study SiteMetal/Metalloid
PbCdNiFeMnCuCrZnCo
Site 10.2560.6870.4980.2840.6150.5270.3375.7020.070
Site 20.3740.6440.5200.3170.7630.4390.2531.8360.149
Table
Table 7. Enrichment factor for metals in sugar beet.
Table 7. Enrichment factor for metals in sugar beet.
Study SiteMetal/Metalloid
PbCdNiFeMnCuCrZnCo
Site 10.41622.913.0070.0381.4070.5160.6754.1990.070
Site 20.61021.483.1440.0421.1720.6400.5061.3520.149
Table
Table 8. Daily intake of metal and health risk index of sugar beet.
Table 8. Daily intake of metal and health risk index of sugar beet.
Study SiteMetalPbCdNiFeMnCuCrZnCo
Site 1DIM (mg/kg/day)0.0030.1350.0150.6980.1430.0240.0071.4827.000
HRI0.090135.60.7810.9973.5040.6230.0044.9410.002
Site 2DIM (mg/kg/day)0.0050.1440.0180.9660.1780.0410.0081.6660.002
HRI0.146144.80.9391.3804.3371.0460.0055.5540.003
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

Ugulu, I.; Bibi, S.; Khan, Z.I.; Ahmad, K.; Munir, M.; Malik, I.S.; Ejaz, A.; Alrefaei, A.F. Biomonitoring of Heavy Metal and Metalloid Contamination in Industrial Wastewater Irrigated Areas Using Sugar Beet (Brassica oleracea L.). Sustainability 2023, 15, 9694. https://doi.org/10.3390/su15129694

AMA Style

Ugulu I, Bibi S, Khan ZI, Ahmad K, Munir M, Malik IS, Ejaz A, Alrefaei AF. Biomonitoring of Heavy Metal and Metalloid Contamination in Industrial Wastewater Irrigated Areas Using Sugar Beet (Brassica oleracea L.). Sustainability. 2023; 15(12):9694. https://doi.org/10.3390/su15129694

Chicago/Turabian Style

Ugulu, Ilker, Shehnaz Bibi, Zafar Iqbal Khan, Kafeel Ahmad, Mudasra Munir, Ifra Saleem Malik, Abid Ejaz, and Abdulwahed Fahad Alrefaei. 2023. "Biomonitoring of Heavy Metal and Metalloid Contamination in Industrial Wastewater Irrigated Areas Using Sugar Beet (Brassica oleracea L.)" Sustainability 15, no. 12: 9694. https://doi.org/10.3390/su15129694

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