POLLUTION CLASS AND ECO-TOXICOLOGICAL RISK ASSESSMENT OF HEAVY METALS IN SEDIMENT ALONG EL-KHADRAWIA DRAIN

POLLUTION CLASS AND ECO-TOXICOLOGICAL RISK ASSESSMENT OF HEAVY METALS IN SEDIMENT ALONG EL-KHADRAWIA DRAIN

Safaa I.M. Rady* and Shereen S. Yousif

Central Laboratory for Environmental Quality Monitoring (CLEQM), National Water Research Center (NWRC)

*Corresponding Author: E-mail-msafaa300@yahoo.com

ABSTRACT

El-Khadrawia drain has number of anthropogenic activities including fishing, irrigation and discharge of Qusena industrial zone and industrial Mubark city that pose a risk of heavy metals in the drain and reduce economic environment. Field and l

aboratory analyses were carried out to assess contamination level and potential environmental risk on sediment along El-Khadrawia drain. Steel grab sampler was used to collect six sediment samples in triplicate sediment layers with 0-20 cm for quality control and quality assurance of sampling technique. Procedures of sediment chemistry characterization including extraction (Suspension extraction (decantation method) & microwave digestion technique)and geochemical analysis for eco-toxicologyusing Sediment Quality Guideline (SQGs), Sediment Contamination Index (SCI) and Potential Ecological Risk Index (PERI) were carried out for trace elements Aluminum: (Al), Nickel (Ni), Iron (Fe), Manganese (Mn), Cobalt (Co), Cadmium (Cd), Chromium (Cr), Zinc (Zn), Cupper (Cu) and Lead (Pb) in sediment samples along El-Khadrawia drain and El-Rayah El-Menoufy (self-investment development) to assess and predict risk for the environment and public. The research showed all metal concentrations in sediment samples, except Cr in all samples were greater than the permission limits of (SQGs) and had effect low range for adverse biology for organisms. Sediment Contamination Index (SCI) and Potential ecological Risk Index (PERI) reported all sites samples were dangers and had high rank of toxicology. The other metals concentration had variables incidence of adverse biological effect (6-70%).

Key Words:    Trace elements; El-Khadrawia drain; sediment quality; sediment contamination index.

1. INTRODUCTION

Sediment deposited naturally at the bottom of water resources by precipitation, ion exchange, adsorption, hydrolysis and chelation processes. Environmentally, sediment is a sensitive indicator and geochemical contaminations for toxic trace elements ranks and sources that clarified recent environmental changes of chemical pollutants in aquatic ecosystem (Zhou et al., 2021). Anthropogenic human activity and industrialization lead to serious environmental contamination by trace elements along ecological system (Sun, et al., 2020). It represents serious environmental hazard impacts and significant source of commonly 23 heavy metals in high concentrations and their special property of bio-accumulation to aquatic biodiversity of many species organisms in aquatic environment that transfer from sediments causing ecological imbalances (Uzairu et al., 2009; Javed et al., 2018 and Yang, et al., 2018)

High ranks of heavy metals discharge in water column from sediment based on sediment pH, physical and chemical characterization of the aquatic environment andabsorption & sedimentation processes of metals that depend on the composition including grain size, carbonate content, level of organic matter and Fe–Mn oxy-hydroxides (Yao & Gao, 2007 and Hazrat et al., 2019). Currently, growing movement for industry leads to reduce its wastewater and treat it before discharge to achieve societal and environmental pressures and provide economic and financial benefits which consider wastewater as the potential non-convention resource for recycling after suitable treatment (UN-Water, 2015; UN-Water, 2016 and UN-Water, 2021). Recently, many studies focused on research along biological half-life of heavy metals in the aquatic environment that reported a major problem to reduce pollution sources and toxic action of heavy metals on different types of aquatic life (Yaroshenko et al., 2017). Several studies had highlighted the significance of periodic examination of pollutants measurements in aquatic ecosystems using various analysis techniques including in-situ (sensor technology such as pH, EC, DO) and ex-situ (spectrometric and chromatographic methods) (Peyravi et al., 2020 & Sambito and Freni, 2021) to perform a complex environmental assessment.

Many researches highlighted the guidelines, references and transport mechanisms and chemical speciation of heavy metals for aquatic sediment quality in water body using various indices (Usha & Ranga, 2011 and Shafaqat et al., 2020). Consequently, potential ecological risk index (PERI) (Zhu et al., 2013), sediment pollution index (SCI) (Singh et al. 2002) and sediment quality guidelines (CSQG, 2001) are vital for the assessment of metal pollution in sediments and water resource that has a great socio-economic potential. El-Khadrawia drain has number of anthropogenic activities including fishing, irrigation and discharge of Qusena industrial zone and industrial Mubark city that pose a risk of heavy metals in the drain and reduce economic environment.

The objective of this research was to study heavy metal in sediment of El-Khadrawia drain, Menoufiya governorate usingpotential ecological risk index (PERI), sediment pollution index (SCI)and sediment quality guidelines. These indices will highlight the sediment contamination in terms of trace elements and evaluate the potential ecological risk.

2.  MATERIALS AND METHODS

2.1       Study Area

El-Khadrawia drain starts in Menoufiya governorate passing districts including Brket El-Saba and Quesna ending in the Western Province center Zifta as located in the classification of the Ministry of Water Resources and Irrigation in Zifta as shown in Fig.(1). Quesna industrial zone include different industrial activities such as leather, foods, paper, coating, dyes and many other industries as shown in Fig.(1D). Some factories through self-investment development have constructed private sewer systems without wastewater treatment plant which dumped as raw sewage into left El-Khadrawia drain. Morever, Mubarak industrial zone is located on the left El-Khadrawia drain at km 19,600 until at km 29 of El-Khadrawia drain at the intersection of the drain with the Cairo-Alexandria agricultural road as shown in Fig.(1C). While El Rayah El Menoufy supplement from Rosetta Brach El Mansoura and Zifta cities, its length 170 Km (Ghannam et al., 2015). (Fig. 1B).

El-Rayah El Menoufy is about 170 Km in length, 50m width and 3 m depth that begins from El-Kanater El-khayria city - Rosetta Branch that crosses Monifia, Dakahlia and El Gharbiah governorates with maximum discharge 25 M.m³/day (Fathy et al., 2013). It expands into the middle of Delta, then direction north to south of Burullus Lake. El Rayah El Menoufy characterized by a number of small branches especially at Menoufiya governorate.

2.2       Sampling Program and Management

Samples: triplicate sediment layers of 0-20 cm are composed using a suitable stainless steel grab sampler from the bottom of El-Khadrawia drain that is affected by various anthropogenic activities (Qusena industrial zone discharge and industrial Mubark city) as shown in Fig. (1C), Fig. (1D) and El Rayah El Menoufy as demonstrated in Fig.(1B). The sediment samples were packed in a cooler bag during winter and summer seasons, stored in an ice box at 4⁰C and transported to laboratory (Central Laboratory for Environmental Quality Monitoring, National Water Research Center “CLEQM-NWRC”) to be analyzed.

                   (A)                                                                                 (B)

                          (C)                        (ES₁)                   (D)

                   (E) - (ES_2-3)                                                          (F) - (ES_4-5)

Fig.1 Study area showing sampling locations (ES₁, ES_2-3, ES_4-5& ES₆) along El-Khadrawia drain and El Rayah El Menoufy

The locations sited along El-Khadrawia drain as planned in Table (1). All preservations were taken to avoid samples impurity during sampling, drying, grinding, sieving and storage process.

Table (1) : Locations of sediment samples

2.3              Sampling Preparation

 The collected samples were air-dried, grounded and sieved to give sediment with particle size < 2 mm, bulked up to get a composite sample for texture, organic matter and heavy metal concentrations using the standard procedures for each parameter.

2.4       Chemicals, Reagents and Instruments

Merck analytical grades (Darmstadt, Germany) of all reagents were used to prepare standard solutions and instrument calibration solutions under satisfying a clean laboratory environment. Liquid  reagent (de-ionized and free organics) was used for stock standard solutions of multi trace elements (1000 mg/L) including Aluminum (Al), Barium (Ba), Boron (B), Chromium (Cr), Copper (Cu), Iron (Fe), Manganese (Mn), Lead (Pb) and Zinc (Zn) that measured using Inductively Coupled Plasma- Emission spectrometry (ICP-ES) with Ultra Sonic Nebulizer (USN) model Perkin Elmer optima 3000, USA. The samples were filtered through filtration system via membrane filter of pore size 0.45 um before analysis (APHA, 2017).

2.4       Procedure of Sediment Characterization

 Texture Analysis (TA)        

Textural analyses of sediment samples was performed in soil laboratory to determine particles size distribution (PSD) through two steps as following:

­                Step (1): Oxidization and heating were utilized to eliminate organic matter and calcium carbonate from air-dried sediment samples that were primarily pretreated with hydrogen peroxide 30% and diluted with 2N HCl acid.

­                Step (2): Mechanical analysis (pipette method) was carried out asdescribed by Griffiths, 1951 andmodified by Carver, 1971 to determine texture by the texture triangle. The sediment texture was classified based on the mud content classification proposed by Folk, 1954 and the modified classification by Pejrup, 1988 and Fleming, 2000.

Suspension extraction (decantation method)

Sediment samples were air dried at 25-35˚C to eliminate moisture until constant weight, grinded as described by Folk, 1980 using sieving technique that collected through a 2 mm mesh, sealed in a clean plastic bags and equilibrated for 24 hours (Bandyopadhyay et al., 2012 and State of Queensland, 2021) for pH and trace elements analysis. Mixing 200 gm of sediment shaken with 1000 ml of de-ionized water (DI) in ratio (1:5) under laboratory conditions using a shaker model RUMO 3015 min to obtain suspension extract of sediment and then stand for 30-60 minutes. The extracts were spilted for two portions for pH analysis using WTW inolab pH level 1.

Microwave Digestion Technique

Digestion of sediment samples was carried out using microwave digestion techniques (Clive et al., 2019). 3 ml of nitric acid , 3 ml of hydrofluoric acid and 2ml of hydrogen peroxide (Fisher 37% H₂O₂) were added to 0.5 gm of sieves sediment material into Teflon vessel of MILESTONE MLS – 1200 MEGA microwave digestion system with MDR (microwave digestion rotor) technology for 30 minutes. The De-ionized distilled water was added to digested samples, filtrated through filtration system via membrane filter of pore size of  0.45 um (ALBET® cellulose nitrate, gridded, sterile) and was completed to 100ml in a volumetric flask. The extracted solution was prepared for trace elements analysis.

Geochemical Analysis

Trace elements (Co, Pb, Al, Cd, Cr, Cu, Ni, Zn, Fe and Mn) were analyzed by Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) with Ultra Sonic Nebulizer (USN) model Perkin Elmer Optima 3000 according to the 3050B method (EPA, 1996 and APHA, 2017). The concentrations were recorded in mg/kg dry weight. The detection limit was

2.5       Statistical Analysis

Statistical analysis (ANOVA one-way) was used to estimate mean value, minimum value and maximum value which were reported when appropriate using IBM SPSS (Statistical Package for the Social sciences) Statistics 22 software package.

2.6       Pollution Assessment Method

There are many methods to quantify the degree of contamination in sediment comparing with the pre-industrial reference. Two indices discussed deposition and strength of heavy metals levels in sediment of El-Khadrawia Drain. These pollutants levels may have a toxic effect for bio-species and affect on food chain as serious problem on the microbiological balance of environment. The pollution indices are potential ecological risk index (PERI), sediment contamination index (SCI) and sediment quality guideline (SQG).

Potential Ecological Risk Index (PERI)

PERI evaluates the force of heavy metals on sediment environment through ecological analysis and categorized (Liu et al., 2021)into five classes as shown in (Table 2). Standard PERI index reflect toxicity classification for organic and inorganic eight contaminants that are PCBs, Hg, Cd, As, Pb, Cu, Cr and Zn. The present study used to the ranking standard of heavy metals’ ecological risk indices based on the types and quantity of pollutants by previous studies for Cd, Pb, Cu, Cr and Zn (Li et al., 2012, Zhu et al., 2013 & Zhang and Liu, 2014) and PERI index can be deduced as follows formulas:

PERI = ∑ Eⁱ_r                 ,               Eⁱ_r = Cⁱ_f  X  Tⁱ_f

Where

Eⁱ_r: The potential ecological risk factor of single heavy metal pollution

Cⁱ_f : The value of the concentration of heavy metal divided by the background value (Control sample).

Tⁱ_f : The toxic factor of heavy metal, the values that are Cr and Zn  (1), Cu and Pb (5), and Cd  (30) (Hakanson, 1980).

Table (2) : Grade standards for potential ecological risks

Sediment Contamination Index (SCI)

Singh et al. 2002 assess sediment quality respect to heavy metal concentrations along metal toxicity using sediment contamination index (SCI) which is classified based on SCI contamination classification

As shown in Table 3, it can be expressed as:              SCI = ∑(EF_m X W_m) / ∑W_m      ,        EF_m = C_n / C_R

Where

Cn: The concentration of analyzed metal

C_R: The background metal concentration (control sample)

W_m: Toxicity weight (Cr and Zn (1), Cu and Pb (5), and Cd (30)).

Table (3)  – Classes of sediment contamination index

Sediment Quality Guideline (SQGs)

Bureau of Habitat, 2014 reported that sediment quality guidelines and mean ERM quotient are useful tools to assess possible risk, quality of sediments and provide acceptable concentrations of sediment bound pollutants to protect bio-species living in or near the sediments (Zhao et al., 2014).

The investigated metal concentrations were measured up to the numerical sediment quality guidelines that are effect range low (ERL) and effect range median (ERM) (MacDonald et al., 2000 and Long et al., 2006), severe effect level and (SEL) (Persuad et al., 1993) as tabulated in Table (4).

The work balance land sediments with Canadian soil quality guidelines (CSQG) of Canadian Council of Ministers of the Environment (CCME, 2001) as listed in Table (4).

Table (4)  –  Sediment guidelines standards for metals(mg kg^-1)

3. RESULTS AND DISCUSSION

3.1       Disturbing Factors

Texture of sediment is an important factor that shows the increase trend of clean water body from the upstream to downstream while pollution sources is usually shows a decrease trend of contaminated water body by dilution.  Based on the monitoring data of sediment quality in the study area, quantitative analysis of trace elements contamination in sediment from the bottom of El-Khadrawia drain was piloted using three indexes.

These indexes demonstratedtheir standards the differe significantly among toxic trace elements that affected by anthropogenic sources in terms of wastewater discharges, agricultural and urban activities (Gulten Gunes, 2021).

3.2       Sediment Properties and Classification

Mechanical methods for six samples of investigated sites provided the distribution of dissimilar sizes of sediment particles and wrere classified into coarse fragments, gravel, sand, silt and clay which is demonstrated in Fig.(2).

Fig.(2)   PSD of sediment samples along El-Khadrawia drain and El-Rayah El-Menoufy

The data showed the sites that have two different shelf grain sizes, of clay, loamy and sand particles. Clay layer can be adsorb water, inorganic ions, organic matter and gases on their surfaces as storage of pollutants as shown in Fig. (2). Figure (3) showed the clarification of textural composition of all sites that was clay except El-Rayah El-Menoufy, as Control sample (El-Kanater El-Khayria) were loamy sandy and they did not have the ability to adsorb any components.

Fig. (3)   Classification of sediment along study area (El-Khadrawia drain and El-Rayah El-Menoufy)

3.3       Assessment of Heavy Metal Contamination

pH value of sediment was generally divided into five categories that are slightly acidic (pH < 5.0), mildly acidic (5.0 - 6.5), neutral (6.5 - 7.5), mildly alkaline (7.5 - 8.5) and the strongly alkaline (pH > 8.5). pH values of studied samples ranged from 8.19 to 8.79 which implicit a gradual mildly alkaline and the trend of pH is similar along environmental sampling. The average of pH values in El-Khadrawia drain and El-Rayah El-Menoufy samples was 8.4 showing a mildly alkaline property (Fig. 3). Many procedures by researches have been used to assess heavy metal contamination in sediment to understand anthropogenic activities ability, variation the concentrations of potentially toxic metals to aquatic life and ecology inference.

Table (5) and Fig. (4) summarize the minimum, maximum, and average concentrations (mg kg⁻¹) of ten heavy metals in bottom sediment samples collected from El-Khadrawia drain and El-Rayah El-Menoufy. The concentration of ten heavy metals were Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn ranged in 411-53490, <0.001-10.7, <0.005-10.7, 1.1-48.2, 7.8-770.8, 611-48330, 1.2-979.1, <0.001-196.3, 6.54- 50660 and 1.4-611.5 mg kg⁻¹, respectively.

The average concentration ranked in a descending order , where Al (36534.67 mg kg⁻¹)> Cd (34397.26mg kg⁻¹)> Zn (32049.83mg kg⁻¹)> Ni (936.083mg kg⁻¹)> Cu (537.513 mg kg⁻¹)> Co (373.06mg kg⁻¹) > Cr (95.2166mg kg⁻¹) >Mn (29.03 mg kg⁻¹) > Pb (6.91 mg kg⁻¹)> Fe (6.1mg kg⁻¹). However, heavy metals concentrations of ten heavy metals along El-Khadrawia drain were higher than background values of study area.

Table (5): Concentration of heavy metals (mg kg⁻¹) in the sediment of El-Khadrawia drain and El-Rayah El-Menoufy

Toxicity characteristics for heavy metals

Sediment Contamination Index (SCI) evaluate sediments pollution according to toxicity characteristics for six heavy metals that are Cr, Zn, Cu, Ni, Pb and Cd (Banu et al., 2013 and Pejman et al., 2015) of El-Khadrawia drain. The index revealed El-Khadrawia drain sediments as a dangerous polluted at all sites of drain (5Km on beside of outlet Mubark industrial zone) and naturally at El-Rayah El-Menoufy. Figure 5A destructive the SCI percentages for investigated sites in order ES₁ (25%)> ES₄ (23%)>ES₂ (21%)> ES₃ (16%)> ES₅ (15%) and for El-Rayah El-Menoufy. The spatial distribution of heavy metals was site-specific; demonstration a extremely high level in the sampling locations with intense of agricultural activities (El-Khadrawia drain) and industrial activities (outlet Mubark and Quesna industrial zones) that agree with Fang Shen et al., 2019 for identification and assessment of heavy metals source.

                              (A)                                                   (B)

Fig. (5 A-B) Distribution of toxicity characteristics using SCI and PERI for heavy metals along El-Khadrawia drain

Potential Ecological Risk Index (PERI) for aquatic pollution control is an analytical tool to sort out which site-specific should be given special attention. The results showed the potential ecological risk factor of single metal (Eⁱ_r ) for heavy metals risks ranking in the following order Cd (248760)> Pb (23839.91)> Cu (147.844)> Zn (319.5)> Cr (34.62) as listed in Table (6) and Fig.(5B).

Table (6):   Broad potential ecological risk index (PERI)

According to the grading standards of the PERI index indicated that there were high potential risks (PERI) for each single metals at all sites ES₁ (360409)> ES₄ (325791.6)> ES₂ (296053.6)> ES₃ (217937.7)> ES₅ (ES₅) in each sediment sample along El-Khadrawia drain as demonstrated in Fig.(5B) and Fig.(6).

3.4 Sediment Quality Guideline (SQGs)

Council of Ministers of the Environment Quality Standard for Sediment (CSQGs - mg/Kg dry weight) standards contain three effects value, namely, effect range low (ERL) which determine values indicative of concentrations below which adverse biological effects such as toxicity to biota rarely occur, effect range medium (ERM) which determine values representive of concentrations above which adverse biological effects frequently occur and severe effect level (SEL) which indicates alevel of contamination to the majority of sediment-dwelling organisms (CCME, 2001).

Criteria Designed of Internationally Traditional Canadian Council - Ministers of the Environment quality standards for Sediment (SQGs - mg/kg dry weight) is selected to assess sediment quality and the ecological risks (Ali et al., 2016; Zarezadeh et al., 2017 and Birch et al., 2018) associated with heavy metals: Cd, Cr, Co, Zn, Ni, Cu, Fe and Mn as presented in Table (7).

Table (7)  Descriptive study of sediment quality (CCME, 2001)

 Table (7) showed the possible toxicological significance of chemical concentrations in sediments to rank and prioritize sites chemical concern. Samples, in which ERL concentrations are exceeded but no ERM are exceeded, might be given intermediate ranks. Samples in which the ERM values are exceed by a large degree may be considered as more contaminated than those in which none of the SQGs values are exceeded. Samples in which the ERM values are exceed which is the level of contaminate concentration in sediment that could potentially eliminate most of the benthic organisms and hazard water quality or human health.

Comparison of measured concentrations (mg/kg - dry weight) of various contaminants within the sediments with these guideline values provides a basic indication of the degree of contamination on ecology. Table (7) clarified the concentration of Cr, Cu, Fe, Ni, Pb, Zn, Cd and Mn in the present study that did not exceed the ERL values for El-Rayah El-Menoufy which had 0-% incidence of adverse biological effect.

Figure (7 A-H) clarified the occurrence (%) of adverse biological effects in concentration ranges that defined by ERL, EML and ESL values of sediment quality guidelines (CSQGs) for heavy metals that have been investigated. Four heavy metals: Zn (11-27%) (Fig. 7 F), Cu (15-70%) (Fig. 7 B), Ni (6-34%) (Fig. 7 D) and Pb (13-24%) (Fig. 7 E), concentrations had exceeded the ERM values that represented as incidence of adverse biological affects and pose special threats on organisms in the area.

Fig. (7): Heavy metals concentrations percentage of CSQGs standards along El-Khadrawia drain and El Rayah El Menoufy

Cadmium concentrations had various adverse biological effects along El-Khadrawia drain which ES₂ (21%), ES₃ (16%), ES₄ (23%) and ES₅ (14%) had exceeded ERM values while ES₁ (26%) exceeded ESL values. Also, manganese recorded variables adverse biological effects along El-Khadrawia drain which ES₁ (17%), ES₂ (12%) and ES₃ (12%) did not exceeded ESL values while ES₄ (33%) ES₅ (24%) exceeded ESL values indicating that this metal may cause an adverse effect on the biota community.

Finally, iron recorded very high concentrations exceeded ERS values (ERS: 4000 mg/Kg) for all studied samples along El-Khadrawia drain that represented 13-26% incidence of adverse biological effects: ES₁ (26%), ES₂ (17%), ES₃ (13%), ES₄ (23%) and ES₅ (21%) had exceeded ERM values.

4.       CONCLUSION

It is found clearly that the heavy metals pollution in sediments along El-Khadrawia drain and El-Rayah El-Menoufy were found by utilizing SCI and PERI indices. It is more provide significant data for making choices will protect and enhance the biological community. The concentration of ten heavy metals that were Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn ranged in 411-53490, <0.001-10.7, <0.005-10.7, 1.1-48.2, 7.8-770.8, 611-48330, 1.2-979.1, <0.001-196.3, 6.54- 50660 and 1.4-611.5 mg kg⁻¹, respectively.

CSQG guidelines clarified occurrence (%) of adverse biological effects in concentration ranges defined by ERL, ERM and ESL values of sediment quality guidelines (CSQGs) for heavy metals that have been investigated. The fixation from the data, Fe surpassed ERL worth for all studied samples and others were variables which four heavy metals: Zn (11-27%), Cu (15-70%), Ni (6-34%) and Pb (13-24%) concentrations had exceeding the ERM values that represented incidence of adverse biological affects and pose special threats on organisms in the area. Cadmium and manganese concentrations had various adverse biological effects along El-Khadrawia drain that may cause an adverse effect on the biota community. Furthermore, the study showed that, sediment samples were highly polluted to danger related to different anthropogenic sources activities and human wastes.

5.       ACKNOWLEDGEMENTS

Authors are grateful to Central Laboratory for Environmental Quality Monitoring (CLEQM), National Water Research Center (NWRC) for carrying out this research work to avail the laboratory and other facilities with instrumental support under cooperation scheme.

6.       REFERENCES

Ali, M.M. ; M.L. Ali ; M.S. Islam and M.Z. Rahman (2016). Preliminary assessment of heavy metals in water and sediment of Karnaphuli River, Bangladesh. Environmental Nanotechnology Monitoring Management, 5: 27–35.

APHA, (2017). American Public Health Association for Standard Methods for the Examination of Water and Wastewater 23^th ed. APHA, Inc. Washington, DC.

Bandyopadhyay, K.K. ; P. Aggarwal ; D. Chakraborty ; S. Pradhan ; R.N. Garg and R. Singh (2012). Practical Manual on Measurement of Soil Physical Properties. Division of AgriculturalPhysics, Indian Agricultural Research Institute, New Delhi- 110 012, India: 62.

Banu, Z. ; M.D.S. ; A. Chowdhury ; M.D.D. Hossain and K. Nakagam (2013). Contamination and ecological risk assessment of heavy metal in the sediment of Turag River, Bangladesh: An Index Analysis Approach. J. of Water Resource and Protection, 5: 239-248.

Birch, G.F. (2018). A review of chemical-based sediment quality assessment methodologies for the marine environment. Marine Pollution Bulletin, 133: 218–232.

Bureau of Habitat, (2014). Screening and Assessment of Contaminated Sediment. New York State Department of Environmental Conservation Division of Fish, Wildlife, and Marine Resources

Canadian Soil Quality Guidelines (CSQG), (2001). Canadian soil quality guidelines (CSQG) for the protection of environmental and human health: Summary tables. Updated September, 2001. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg by Canadian Council of Ministers of the Environment (CCME).

Carver, R.E. (1971). Procedures in Sedimentary Petrology. John Wiley and Sons. Canada, Limited, New York, 653 p.

Clive, N.T. ; K.J. Rodgers ; I.S. McLellan and A.S. Hursthouse (2019). Geochemistry Inorganic, Editor (s): Paul Worsfold, Colin Poole, Alan Townshend, Manuel Miró, Encyclopedia of Analytical Science (Third Edition), Academic Press, Pp: 271-282,

EPA, (1996). Guidance on Use of Modeled Results to Demonstrate Attainment of the Ozone NAAQS, EPA-454/B-95–007

Fang, S. ; L. Mao ; R. Sun ; J. Du ; Z. Tan and M. Ding (2019). I Contamination evaluation and source identification of heavy metals in the sediments from the Lishui River Watershed. Southern China. Int. J. Environ. Res. and Public Health,  16:1-14.

Fathy, I.H.; A. El-Belasy ; Y.E. Helal and M.F. Sobeih (2013). Effect of Main barrages failure on the Nile Valley. Nile Basin Water Sci. and Eng. J., 6(2): 76-87.

Fleming, B.W. (2000). A revised textural classification of gravel-free muddy sediments on the basis of ternary diagrams. Continental Shelf Res., 20(10-11):1125-1137.

Folk, R.L.(1954). The distinction between grain size and mineral composition in sedimentary-rock nomenclature. J. of Geol., 62(4):344–359

Folk, R.L. (1980). Petrology of Sedimentary Rocks. Hemphills PublCo, Austin, Texas, p. 170.

Ghannam, H.E.; E.S.E. El Haddad and A.S. Talab (2015). Bio-accumulation of heavy metals in tilapia fish organs. Journal of Biol. and Environ. Sci., 7(2): 88-99.

Griffiths, J.C. (1951). Size versus sorting in Caribbean sediments. J. Geol. 59: 211–243.

Gulten, G. (2021). The change of metal pollution in the water and sediment of the Bartın River in rainy and dry seasons. Environmental Engineering Research., Environ. Eng. Res. Article. https://doi.org/10.4491/eer.2020.701.

Hakanson, L. (1980). The ecological risk index for aquatic pollution control sediment logical approaches. Water Res.; 14: 975–1001.

Hazrat, A.; E. Khan and I. Ilahi (2019). Environmental Chemistry and Ecotoxicology of Hazardous Heavy Metals: Environmental Persistence, Toxicity, and Bioaccumulation. Hindawi J. of Chemistry, Article ID 6730305, 14 pages.

Legin, A. (2020). Real-Time water quality monitoring with chemical sensors. Sensors, 2020.  20: 1-20, 3432. [Cross Ref]

Li, R.Z. ; C.R. Pan ; J.J. Xu ; G.Z. Ding and Y. Zou (2012). Application of Potential Ecological Risk Assessment Model Based on Monte Carlo Simulation. Res. Environ. Sci., 25:1336–1343.

Liu, D. ; J. Wang ; H. Yu ; H. Gao and W. Xu (2021). Evaluating ecological risks and tracking potential factors influencing heavy metals in sediments in an urban river. Environ. Sci.Europe, 33(42):1-13.

Long, E.R. ; C. Ingersoll and D.D. MacDonald (2006). Calculation and uses of mean sediment quality guideline quotients. A critical review. Environ. Sci. Technol., 40:1726–1736.

Javed, T.; N. Ahmad and A. Mashiatullah (2018). Heavy metals contamination and ecological risk assessment in surface sediments of Namal Lake, Pakistan. Pollution . J. Environ. Stud., 27: 675–688.

MacDonald, D.D. ; C.G. Ingersoll and T.A. Berger (2000). Development and evaluation of consensus-based sediment quality guidelines for fresh water ecosystems. Archives of Environ. Contamination and Toxicol., 39: 20-31.

Pejman, A. ; G.N. Bidhendi ; M. Ardestani ; M. Saeedi and A. Baghvand (2015). A new index for assessing heavy metals contamination in sediments: A case study, Ecological Indicators, 58: 365-373.

Pejrup, M. (1988). The triangular diagram used for classification of estuarine sediments: A new approach. In: de Boer PL, Van Gelder A, Nio SD (eds) Tide-influenced Sedimentary Environments and Facies. Reidel, Dordrecht, pp 289–300.

Persuad, D. ; R. Jaagumagi and A. Hayton (1993). Guidelines for the protection and management of aquatic sediment quality. Ontario ministry of environment and energy report,30, Canada

Peyravi, M. ; M. Jahanshahi and H. Tourani (2020). Chapter 6: Analytical methods of water pollutants detection. In Inorganic Pollutants in Water; Devi, P., Singh, P., Kansal, S.K., Eds.; Elsevier: Amsterdam, The Netherlands, pp: 97–113.

Shafaqat, A. ; Z. Abbas ; M. Rizwan ; I.E. Zaheer ; I. Yava ; A. Ünay ; M.M. Abdel-Daim ; M. Bin-Jumah ; M. Hasanuzzaman  ; D. Kalderis (2020). Application of Floating Aquatic Plants in Phytoremediation of Heavy Metals Polluted Water: A review. Sustainability, 2020, 12, 1927; DOI: 10.3390/su12051927

Sambito, M. and G. Freni (2021). Strategies for improving optimal positioning of quality sensors in urban drainage systems for non-conservative contaminants. Water, 13:1-20, 934. [Cross Ref]

Singh, M. ; G.Müller and I.B. Singh ( 2002). Heavy metals in freshly deposited stream sediments of rivers associated with urbanization of the Ganga Plain, India. Water Air Soil Pollution, 141: 35–54.

State, of Queensland (Department of Transport and Main Roads), (2021). Materials Testing Manual Ed.5, Transport and Main Roads, Amendment 6 June 2021,

Sun, M.X.; T. Wang ; X.B. Xu ; L.X. Zhang ; J. Li and Y.J. Shi (2020). Ecological risk assessment of soil cadmium in China’s coastal economic development zone: A meta-analysis. Ecosystem Health and Sustainability, 6: 1-20

UN-Water (2015): Compendium of Water Quality Regulatory Frameworks: Which Water for Which Use?

UN-Water (2016): Towards a Worldwide Assessment of Freshwater Quality.

UN-Water (2021): Summary Progress Update 2021: SDG 6 — water and sanitation for all.

Usha, N. and R.S.B. Ranga (2011). Vertical profile of heavy metal concentration in core sediments of Buckingham canal, Ennore. Indian J. of Geo-Marine Sci., 40(1):83-97.

Uzairu, A. ; G.F.S. Harrison; M.L. Balarabe and J.C.Nnaji (2009). Concentration levels of trace metals in fish and sediment from Kubanni River, Northern Nigeria. Bulletin of the Chemical Society of Ethiopia J., 23 (1): 9–17.

Yang, Q. ; Z. Li ; X. Lu ; Q. Duan ; L. Huang and J. Bi (2018). A review of soil heavy metal pollution from industrial and agricultural regions in China: Pollution and Risk Assessment. Sci. of the Total Environ., 642: 690–700.

Yao, Z. and P. Gao (2007). Heavy metal research in lacustrine sediment: A review. Chinese J. of Oceanology and Limnol., 25 (4):444-454.

Yaroshenko, I. ; D. Kirsanov ; M. Marjanovic ; P.A. Lieberzeit ; O. Korostynska ; A. Mason ; I. Frau ; R. Zarezadeh ; P. Rezaee ; R. Lak ; M. Masoodi and M. Ghorbani (2017). Distribution and accumulation of heavy metals in sediments of the northern part of Mangrove in Hara Biosphere Reserve, Qeshm Island (Persian Gulf). Soil Water Res., 12(2): 86–95.

Zhao, Q. ; L. Zhou ; X. Zheng ; Y. Wang and J. Lu (2014). Study on enzymatic activities and behaviors of heavy metal in sediment–plant at muddy tidal flat in Yangtze Estuary. Environ. Earth Sci., DOI 10.1007/s12665-014-3614-x

Zhang, L.L. and J.L. Liu (2014). In situ relationships between spatial-temporal variations in potential ecological risk indexes for metals and the short-term effects on periphyton in a macrophyte-dominated lake: a comparison of structural and functional metrics. Eco-toxicology, 23(4):553–566

Zhu, X. ; H. Ji ; Y. Chen ; M. Qiao and L. Tang (2013). Assessment and sources of heavy metals in surface sediments of Miyun Reservoir, Beijing. Environ. Monitoring Assessment, 185: 6049–6062.

Zhou, X. ; K. Zhou ; R. Liu ; S. Sun ; X. Guo ; Y. Yang ; L. Chen ; K. Zou and W. Lei (2021). Significant Decrease in Heavy Metals in Surface Sediment after Ten-Year Sustainable Development in Huaxi Reservoir Located in Guiyang, Southwestern China. Int. J. Environ. Res. Public Health, 18:1-22.

تقييم نسبة التلوث ومخاطر السميةالبيئية للمعادن الثقيلة في الرسوبيات على طولمصرف الخضراوية

صفاء ابراهيم محمد راضى ، شيرين شعيب يوسف

المرکز القومى لبحوث المياه

يتعرض مصرف الخضراوية لعدد من الأنشطة البشرية مثل صيد الأسماک والري وصرف المنطقة الصناعية بقويسنا وکذلک مدينة مبارک الصناعية مما يشکل خطرا کبيرا علي طبيعة الرسوبيات على طول المصرف وذلک لوجود ترکيزات عاليه من المعادن الثقيلة في صرف تلک المناطق الصناعيه مما يؤثر سلبا علي البيئه الاقتصاديه.

يهدف هذا البحث الي  إجراء التحليل الميداني والمعملي لتقييم مستوى التلوث والمخاطر البيئية المحتملة على طبيعة الرسوبيات على طول مصرف الخضراوية.

 وعلى ذلک فقد تم جمع ستة عينات من الرسوبيات في ثلاث طبقات من الرواسب على طول  مصرف الخضراويه وتم عمل توصيف للخصائص الکيميائية للرسوبيات وکذلک تم عمل التحليل الجيوکيميائي للسموم البيئية باستخدام دليل جودة الرواسب (SQGs) ، ومؤشر تلوث الرواسب (SCI) ومؤشر المخاطر البيئية المحتملة (PERI) لتحديد نسبة ترکيز العناصر الثقيله مثل الألمنيوم: (Al) ، النيکل (Ni) ، الحديد (Fe) ، المنغنيز (Mn) ، الکوبالت (Co) ، الکادميوم (Cd) ، الکروم (Cr) ، الزنک (Zn) ، النحاس (Cu) و کذلک الرصاص (Pb) في عينات الرسوبيات على طول مصرف الخضراوية وکذلک الرياح المنوفي  لتقييم وتوقع المخاطر البيئيه المحتمله.

وقد اظهرت نتائج البحث أن نسبة ترکيز جميع المعادن الثقيله (ماعدا الکروم ) في جميع عينات الرسوبيات التى تم جمعها قد تعدت الحدود المسموح بها وذلک وفقا للحدود القياسيه الکنديه لنوعية الرسوبيات  (SQGs) وقد کان لها تأثير منخفض على الحياه البيولوجيه للکائنات الحية.

وقد أفاد مؤشر تلوث الرواسب (SCI) ومؤشر المخاطر البيئية المحتملة (PERI) أن جميع عينات الرسوبيات التى تم جمعها تحتوى علي نسبه عاليه من التلوث بالعناصر الثقيله.