Asare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Beni-Suef University Journal of https://doi.org/10.1186/s43088-022-00199-y Basic and Applied Sciences RESEARCH Open Access Eco-toxic risk assessment and source distribution of trace metals in surface sediments of the coastal and in four rivers estuary of Sarawak Ebenezer Aquisman Asare1,2* , Zaini Assim1, Rafeah Wahi1 and Joseph Richmond Fianko2 Abstract Background: Trace metals pollution in the coastal and estuarine sediment could harm water quality and aquatic organisms, leading to potential long-term health risks on the environment and humans. Thus, the purpose of this study was to conduct an assessment of selected trace metals in surface sediments of the coastal and in four rivers estuary in the Sarawak State of Malaysia to investigate their distribution, environmental risk, and potential source distribution. Results: Average concentrations of trace metals in sediment increased in the following order: Cd ˂ As ˂ Co ˂ Cu ˂ Ni ˂ Cr ˂ Zn ˂ Mn ˂ Mg ˂ Fe. The enrichment, contamination, and geo-accumulation index results showed that surface sediments were polluted with Zn and Mg. In contrast, the other metals (i.e., As, Fe, Mn, Ni, Cr, Cu, Co, and Cd) indicated background concentration to minor contamination. Generally, the pollution load index values showed that almost all the sampling sites were unpolluted with the selected trace metals. Sediment quality guidelines (SQGs) and risk indexes were employed to assess the ecotoxicological risk of trace metal contamination in the sediments. The results proved that studied trace metals are not likely to have a deleterious impact on bottom-dwelling organisms. Still, a fur- ther accumulation of trace metals such as Zn, Ni, and Cr with time may adversely affect bottom-dwelling organisms. The risk index results showed a low ecological risk to the study sites. The correlation analysis and principal compo- nent analysis indicated that nine studied trace metals have strong interrelationships, suggesting common pollution sources or similar geochemical characteristics. Conclusions: The study highlights the need to make tremendous efforts to monitor and control trace metal pollu- tion in the coastal and estuarine areas. Keywords: Trace metals, Eco-toxic risk, Surface sediments, Pollutants, Bottom-dwelling organisms 1 Background estuaries and coastal [7, 8], wetlands [9], and lakes [10], Trace metals are a pressing concern regarding pollu- receive trace metals in inadequately treated or untreated tion in aquatic ecosystems because of their persistence, wastewater from agricultural, domestic, and industrial bioaccumulation, environmental toxicity, etc. [1–3]. sources. As an essential constituent in riverine and estua- Aquatic bodies, for example, reservoirs [4], rivers [5, 6], rine environments, sediments are a source and a sink of trace metals [11, 12]. Trace metals entering rivers and estuaries rapidly deposit into the sediment and are much *Correspondence: aquisman1989@gmail.com 1 Department of Chemistry, Faculty of Resource Science and Technology, more concentrated than in the water body of riverine, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia estuarine, or coastal systems [13, 14]. When there is an Full list of author information is available at the end of the article alteration of the hydrological or the physicochemical © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://c reati veco mmons. org/l icen ses/ by/4. 0/. Asare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 2 of 17 conditions, trace metals in the sediment may resuspend Malaysia. The study area has a tropical rainforest cli- or desorb to result in secondary pollution in the water mate, moderately hot yet very humid once in a while, and body [15, 16]. Trace metals accumulation in the sedi- receives considerable rainfall. The mean annual precipi- ment directly influences benthic organisms. Trace met- tation is approximately 4200 mm. The study area receives als in sediment also affect many other organisms via the an average of 247 rainy days per year with an average food chain and threaten the comfort of the aquatic envi- of 6  h of sunshine and a mean of 3.7  h per day during ronment. Thus, it is necessary to evaluate and appreci- January. North-East Monsoon months of November to ate the accumulation and distribution of trace metals in February is the wettest time whiles June to August is con- sediment. sidered the driest months. The temperature of the study Rambungan, Sibu, Salak, and Santubong Rivers are area range between 19 to 36 °C with a mean temperature key rivers in the Sarawak state of Malaysia. They flow of roughly 23  °C in the early hours of the morning and through the Kuching city and support many less densely rises to approximately 33  °C in the course of mid-after- populated towns, offering services to both agriculture noon and can reach 42  °C in the dry season. Figure  1 and industry. Over the past few decades, there have been shows the sampling locations of the coastal and four riv- trace metals pollution in riverine, estuarine, and coastal ers estuary. sediment of the Sarawak state of Malaysia because of the wastewater discharge from agricultural, metallurgical, 2.2 Sediment sampling and treatment and mining industries carrying trace metals. Even though The field studies and sample collection were conducted many researchers have studied trace metals pollution in according to the procedure outlined by Gao [26] from the Rambungan, Sibu, Salak, and Santubong Rivers and September to October 2020. The coordinates for each their associate estuary [17, 18]; a systematic study is still sampling site were determined using a portable Global lacking to correlate the sediment with trace metals dis- Positioning System (GPS), Garmin etrex (Table  1). Six- tribution, characteristics, risk assessment, likely sources, teen surface sediments were collected from sampling and their effect on the aquatic environment. sites. Samples were collected at each sampling site at Geochemical indices used for ecological risk assess- approximately 5.0 cm depth using a Wildco grab sampler. ment of trace elements in surface sediments comprised To minimize contamination, the grab sampler was dis- of computation of enrichment factor (EF), contamination infected using biodegradable detergent and rinsed with factor (CF), geo-accumulation index (Igeo), pollution load deionized water before and after each use. Sediments index (PLI) [19–21], potential ecological risk indices [22], were placed in cleaned polyethylene containers and kept and excess regression analysis [20, 23]. Analyses of trace in the cooler box at a temperature of 5  °C during trans- metals in river sediments have been used considerably portation. In the laboratory, samples were air-dried in a for the essence of pollution monitoring [19, 24, 25]. A well-ventilated area for a week. The bulky materials such handful of these studies focused on the paths of impart- as stones and unwanted materials were removed from ing trace metals content in sediments without evaluating the sediments using stainless-steel forceps and homog- their ecotoxicological risks [17, 18]. Therefore, this study enized. The dried sediment samples were pulverized aimed to determine ten trace metals (i.e., Zn, As, Fe, Mg, into fine particles using a mortar and a pestle. Pulver- Mn, Ni, Cr, Cu, Co, and Cd) in surface sediments of the ized sediments were then sieved using a 55 μm mesh size coastal and in four rivers estuary of the Kuching Division sieve to obtain powdered sediments which then placed in of Sarawak. Also, using the geochemical indices to evalu- cleaned polyethylene containers. The samples were kept ate the contribution of anthropogenic activities carrying in a refrigerator for further analysis [27]. trace metals into estuary and coastal sediment. Deter- mining potential risks linked with trace metal toxicity 2.3 Sediment extraction and analysis using sediment quality guidelines and ecotoxicological The procedure used to analyze sediment absolute trace risk index. Finally, ascertaining the source distribution of metal contents is acid digestion adapted by Hossner trace metals using statistical tools such as Pearson’s coef- [28]. A powdered sample of 0.5 g was placed in a cruci- ficient correlation and principal component analysis. ble. About 3 mL of H 2SO4 (95%) and 4 mL of HCl (96%) were added to the crucible contents. The contents of the 2 Methods crucibles were then placed in an oven Memmert model 2.1 D escription of the study area 30 – 70 (UN 30) at 115  °C for 20  h to break down all The field studies and sampling were conducted in the organic materials and the weight was recorded. The sedi- coastal and in four rivers (i.e., Santubong, Salak, Sibu, ment samples were reheated at 500 °C for 3 h 30 min in and Rambungan) estuary in the Kuching Division of a muffle furnace (Model Ney Vulcan D – 550 series) and Sarawak in the North-Western portion of Borneo Island, the weights were recorded. 2.0 mL of distilled water and A sare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 3 of 17 km N 0 100 200 LEGEND East Malaysia 6 10 3 5 Border of Sarawak 8 2 9 4 7 Border of the study area 1 Kuching Division National park and wetlands Sampling sites 110°E Fig. 1 Map of study area showing 10 sampling sites; adapted from Asare et al. [7]. Note: On the map, the sampling site codes were labelled numerically for easy identification of sampling position but the actual naming of each sampling site is attached with CZ for example sample site 1 denotes CZ1 Asare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 4 of 17 Table 1 Coordinates of sampling locations Sample site code Locality Coordinates CZ1(1),(2) Rambungan River Estuary N01°41′37.7″ E110°08′24.5” CZ2(1),(2) Offshore of Batang Rambungan opposite small Satang Island N01°44′46.8″ E110°08′45.4” CZ3(1),(2) Offshore of Batang Rambungan adjacent big Satang Island N01°46′22.6″ E110°08′37.8” CZ4(1),(2) Sibu River Estuary N01°44′46.8″ E110°08′45.4” CZ5 Offshore of Telaga Air opposite to small Satang Island N01°45′50.4″ E110°11′30.2” CZ6 Offshore of Telaga Air adjacent big Satang Island N01°47′23.5″ E110°10′39.7” CZ7(1),(2) Salak River Estuary N01°40′41.1″ E110°16′59.2” CZ8 Santubong Bay N01°42′45.7″ E110°27′63.1” CZ9(1),(2) Offshore of Santubong Resort N01°44′49.6″ E110°29′72.3” CZ10 Santubong River Estuary N01°42′32.6″ E110°19′02.3” 2.0 mL concentrated HNO3 were added to cool the sam- Table 2 Characteristics performance of ICP-OES calibration ples and further heated to dryness on a hot plate (Model equation Favorit HS070V2 Serial 5434). 10 mL distilled water and Trace metal Parameters 1.0  mL concentrated HCl were added to each crucible’s 2 content and stirred for 3 min for uniformity. The mixture R Slope Intercept LODs (mg/ LOQs (mg/kg) kg) was then filtered through Whatman No. 42 filter paper, and the content (filtrate) was top up with distilled water Zn 0.9880 0.0114 0.0012 0.0404 0.1224 to 100  mL. Trace metals concentrations were analyzed As 0.9910 0.0136 0.0014 0.0379 0.1149 using an inductively coupled plasma optical emission Fe 0.9720 0.0371 0.0206 0.0106 0.0321 spectrophotometer (ICP-OES). Mg 0.9830 0.0131 0.0017 0.0143 0.0143 Mn 0.9870 0.0211 0.0043 0.0348 0.1055 Ni 0.9910 0.0117 0.0013 0.0330 0.1000 2.4 Q uality assurance and control (QA/QC) Cr 0.9690 0.0431 0.0073 0.0429 0.1300 To ensure the quality and efficiency of the instrumen- Cu 0.9950 0.0201 0.0134 0.0541 0.1639 tal outcomes; QA and QC techniques were established. Co 0.9990 0.0114 0.0036 0.0101 0.0306 It includes cleaning laboratory materials and apparatus Cd 0.9670 0.0633 0.0073 0.0132 0.0400 using 15% H 2SO4, applying standard operating methods, LOD limit of detection, LOQ limit of quantification, R2 variance analyzing blanks, and standard calibration and recovery of actual additions. Instrumental validation is a crucial analytical precondition of the multi-elemental analysis The method efficiency for the study was determined process. The procedure lays out a system for describing using recovery tests. Analyte for individual trace metal the efficiency of the instrument. In addition, it proves was used to spike the digestion sample solution. The the performance abilities of the procedure being exam- spiked samples were analyzed, and the average concen- ined by ensuring that it is coherent with the used method tration of trace metal after spiking was compared with [6]. The limit of detection (LOD) and limit of quantifica- the concentration of analyte trace metal before spiking. tion (LOQ) were calculated for the ten trace metals after The recoveries were calculated as follows [6]: establishing the calibration curves and equation of ICP- ( ) OES. The LOD and LOQ values were computed using the Recovery(%) = Average Conc.spiked/Analyte Conc. × 100% formulae adapted by [29]: (3) The amount of trace metals concentrations was ( ) LOD = 3.3× S.dblank/y (1) assessed according to the formula: ( ) Final Conc. mg/L = Conc. ( ) sediment × DF × NV (mL) LOQ = 10× S.dblank/y (2) (4) where S.d refers to mean standard deviation of blanks, where, Conc.sediment represents trace metal concentration and y represents the sensitivity of the calibration curve in sediment samples, DF denotes dilution factor, and NV [29]. Table  2 shows the properties’ performance of the is nominal volume. ICP-OES calibration equation. A sare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 5 of 17 The percentage recoveries of the spiked samples ana- CF = (Cm)sample/(Cm)background (6) lyzed varied from 89 – 104% (Table 3). The analyte level of approximately 1  mg/kg has been reported, and the Cmsample denotes the concentration of a given trace metal acceptable recovery range is 90.0–110% [6, 30, 31]. The in sediment, and (Cm)background is the values of refer- obtained values in this current study were found to be ence metal, which are the average shale values of each within the acceptable recovery range. Hence, the analyti- study metal for sedimentary rock [35]. The CF values are cal instrument is suitable to for analysis of selected trace grouped into four groups as listed in Table 4. metals. 2.5.3 G eo‑accumulation index (Igeo) Igeo makes it possible to determine pollution by compar- 2.5 E nvironmental assessment of trace metals ing the present and pre-industrial concentrations of trace contamination metals in the earth’s crust [32]. The geo-accumulation 2.5.1 Enrichment factor (EF) index (Igeo) can be calculated using Eq. 7 [32]: EF deals with estimating the anthropogenic impacts on the media, such as soil, sediments, and others. Iron (Fe) is Igeo = Log2(Cn/1.5 ∗ Bn) (7) used as a normalization metal because the collected sedi- where, Cn refers to the measured concentration of the ments from the study area were abundant in Fe. The EF trace elements in the sediment samples and Bn repre- can be calculated by Eq. 5 proposed by Muller [32]. sents the geochemical background value in the earth’s ( ) ( ) Xn Xn crust. The factor of 1.5 is introduced to reduce the impact EF = ÷ (5) Fe Fe of possible variations in the background values due to sample crust lithogenic variations (i.e., alteration during early chemi- where, (Xn/Fe)sample represents ratios of arithmetic aver- cal reactions within freshly deposited sediment) [36]. The age concentrations (mg/kg, dry wt) of the target heavy interpretation of the Igeo values is summarised in Table 4. metals; (Xn/Fe)crust denotes Fe in the investigated sedi- ments and continental earth crust according to Mul- 2.5.4 T he pollution load index (PLI) ler [32]. The classifications of trace metals enrichment PLI for each sampling site is derived as the nth root of n and their environmental risk grades in soil/sediment are number multiplied together by the values of the CF sug- shown in Table 4. gested by Tomilson et al., as shown by Eq. 8 [37]. PLI = (CF ∗ CF ∗ CF ∗ . . . . . . CF )1/n1 2 3 n (8) 2.5.2 Contamination factor (CF) where, n represents the number of heavy metals. PLI CF is applied to assess pollution in an aquatic ecosystem index is ranked into several classes, as shown in Table 4. by a given toxic substance. Thus, it serves as a vital indi- cator of sediment contamination [33]. The CF was com- puted using Eq. 6 formulated by Hakanson [34] as: 2.6 Ecological risk assessment 2.6.1 S ediment quality guidelines Sediment-quality guidelines (SQGs) were developed in Table 3 Method efficiency data for analysis of ten trace metals Australia and New Zealand in 2000 to predict the adverse in spiked surface sediment samples biological impacts caused by contaminated sediments [38]. The technique has been employed to determine the Trace metal Analyte Conc. Mean Conc. of a % Recovery potential risk to aquatic organisms due to trace metal (mg/kg) spiked sample (mg/ kg) pollution in aquatic bodies [39]. The assessment is estab- lished by comparing the measured trace metal contents Zn 1.00 0.98 98 in sediment samples with the consensus-based threshold As 3.00 2.75 92 effect concentration (TEC), probable effect concentration Fe 2.00 2.08 104 (PEC) values, and midway values between the TEC and Mg 1.00 1.01 101 PEC (i.e., MEC) [40]. Mn 2.00 1.95 98 Ni 2.00 1.78 89 2.6.2 T hreshold effect concentration (TEC) Cr 2.00 1.98 99 TEC is a sediment contamination concentration at which Cu 1.00 0.97 97 a toxic response has begun to be observed in benthic Co 2.00 1.94 97 organisms. Florida Department of Environmental Pro- Cd 2.00 1.96 98 tection developed Eq. 9 to determine TEC based on the Asare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 6 of 17 Table 4 Enriched factor (EF), contamination factor (CF), geo-accumulation index (Igeo) and pollution load index (PLI) range values and their environmental risk grades Index type Value Environmental risk grade References Single Indices EF [32] 0 – 1 Background concentration or no enrichment 1 – 3 Minor enrichment 3 – 5 Moderate enrichment 5 – 10 Moderately severe enrichment 10 – 25 Severe enrichment 25 – 50 Very severe enrichment > 50 Extremely serve enrichment CF [34] ˂ 1 Minimum contamination 1 to 3 Moderate contamination 3 to 6 Considerable contamination > 6 Very high contamination Igeo [32] 0 Uncontaminated or background concentration 0–1 Uncontaminated 1–2 Moderately contaminated to uncontaminated 2–3 Moderately contaminated 3–4 Moderately to highly contaminated 4–5 Highly contaminated > 5 Very highly contaminated Integrated Index PLI [37] 0 Perfection 1 Baseline > 1 Increasing contamination concentrations at which benthic organisms from aquatic 2.6.4 M edian effect concentration (MEC) ecosystems exhibited toxic responses in the laboratory It is assumed that sediment contamination concentra- [41]. tions below TEC are acceptable and concentrations √ above the PEC are unacceptable. The region in between TEC = (EDS− L*NEDS−M) (9) the TEC and PEC is called median effect concentra- EDS-L represents the concentration at which 15% of tion (MEC). The MEC values require further study and benthos showed effects, and NEDS-L denotes concentra- judgment to ascertain the likelihood of environmental tion at which 50% of benthos showed no impact. consequences. 2.6.5 P otential ecological risk index (RI) 2.6.3 Probable effect concentration (PEC) RI can be calculated using Eqs.  11–13 developed by PEC is the concentration at which a large percentage of Hakanson [34]. RI is widely used in evaluating the eco- the benthic population shows a toxic response. PEC can logical risk of trace metals contamination in sediments be calculated using Eq.  10 as proposed by the Florida [42]. Thus, RI is calculated using the formula: Department of Environmental Protection [41]. ∑ √ RI = Ei (11) PEC = (EDS−M*NEDS−H) (10) EDS-M denotes concentration at which 50% of benthos Ei = TiFi (12) showed effects, and NEDS-H indicates concentration at which 85% of benthos showed no impact. A sare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 7 of 17 Fi = Ci/Cb (13) The detected arsenic (As) concentration in the samples detected ranged from 3.02 to 6.88  mg/kg with a mean where, RI is the sum of all risk factors in the sediment value of 5.13 mg/kg (Table 6). Arsenic primarily exists in samples; Ei is the monomial potential ecological risk fac- the ecosystem because of natural processes (i.e., volcanic tor for individual factors; Ti is the metal toxic response processes and weathering of rocks, etc.) and anthropo- factor and Fi is the metal contamination factor, Ci is the genic activities such as mining, industrial pollution, fer- calculated concentration of trace metal in the sediment tilizer, pesticides, and insecticides [27, 49]. The elevated sample, and Cb refers to the value of the reference ele- concentration of As in the study area could be attributed ment [35]. Metal contamination factor (Fi), risk index to the excessive use of inorganic fertilizer and domestic classification, and their environmental risk intensity are sewage discharges [50]. highlighted in Table  5. The metal contamination factor The iron (Fe) concentrations in the analysed sam- data of eight out of the ten detected trace metals in the ples ranged from 10,142.25 to 18,483.22  mg/kg, with a samples were available in literature [34]. Therefore, the mean value of 16,415.17  mg/kg. In the current study, it potential ecological risk assessment of 8 trace metals was was observed that Fe concentrations detected in all sam- evaluated in this work. ples were higher compared to other trace metals. Apart from erosion, weathering, and some natural sources; the 2.7 Statistical analysis dominance of Fe in the surface sediments can be caused SPSS 24.0 software (IBM Corp., Armonk, NY, USA) was by large-scale anthropogenic processes including agri- used for basic descriptive statistical analysis of the sam- cultural activities, solid waste, and urban-industrial dis- ple data [43]. This provided the mean and standard devia- charges [51]. tion for the sampled trace metal concentrations. Bivariate The occurrence of magnesium (Mg) in sediments is analysis such as Pearson’s correlation method was used either a solute in pore-fluids or an essential constituent to assess the correlations between trace metals and mul- in the formation of late-stage diagenetic chlorite and tivariate analysis such as principal component analysis dolomite [52]. Mg concentration ranged from 7183.17 to (PCA) was applied to study the source distribution of the 9561.75  mg/kg with an average value of 8597.46  mg/kg selected trace metals. (Table 6). Mg is the second highest concentration follow- ing Fe in the collected surface sediments from the study 3 R esults area. The relatively high content of Mg may be attributed 3.1 D istribution of trace metals in surface sediments to C aCO3 sweating out from the sedimentary column or Trace metal concentrations in surface sediments sampled human activities such as industrial pollution, waste dis- from the coastal and in four rivers estuary are shown in charges, excessive pesticides, and fertilizer application Table  6. The concentration of detected zinc (Zn) in the [53]. surface sediments varied from 57.02 to 155.05  mg/kg Manganese (Mn) concentration varied from 98.93 to with an average concentration of 133.45  mg/kg. It has 194.90 mg/kg with an average of 142.92 mg/kg (Table 6). been reported that Zn has high mobility, and dissolved The behavior of Mn in sediment is different compared to Zn can potentially increase its biological availability in other trace metals and can be influenced by the existence an aquatic ecosystem [19, 44–46]. Osullivan et  al. sug- of MnO2 in oxic surface sediments [19, 54]. Loska and gested that Zn can readily adsorb and be scavenged by Wienchula suggested that Mn pollution results from dep- the hydroxides and oxides [47]. The high level of Zn con- osition in the atmosphere and organic material emissions centration in the surface sediments could be attributed to [55]. The nickel (Ni) concentration in the surface sedi- the fuel station, vehicle emissions, and commercial dis- ments ranged from 10.54 to 27.28  mg/kg with an aver- charges [19, 48]. age value of 20.18 mg/kg (Table 6). Loska and Wienchula Table 5 Metal contamination factor (Fi) of the selected trace metals, classification and environmental risk intensity Trace metal Co Cu Ni Cr Zn Mn Cd As Metal contamination 5.0 5.0 5.0 2.0 1.0 1.0 30.0 10.0 factor Risk Index Value Environmental Risk Categories 1 ˂ 150 Low ecological risk 2 ≥ 150 ˂ 300 Moderate ecological risk 3 ≥ 300 ˂ 600 Considerable ecological risk 4 ≥ 600 Very high ecological risk Asare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 8 of 17 Table 6 Trace metals concentrations (mg/kg) in surface sediments from the coastal and in four rivers estuary of Sarawak Sample site code Zn As Fe Mg Mn Ni Cr Cu Co Cd CZ1(1) 57.02 ± 0.09 3.02 ± 0.08 13,572.17 ± 5.21 7261.00 ± 2.02 102.61 ± 0.94 18.63 ± 0.71 21.64 ± 1.13 11.02 ± 1.05 5.08 ± 0.31 0.01 ± 0.003 CZ1(2) 101.34 ± 0.21 3.73 ± 0.11 14,356.00 ± 8.61 7183.17 ± 5.06 116.43 ± 1.52 11.30 ± 1.01 34.56 ± 1.10 10.82 ± 0.84 3.98 ± 0.16 0.01 ± 0.001 CZ2(1) 104.09 ± 0.17 2.98 ± 0.04 14,895.02 ± 9.87 7929.05 ± 2.71 99.42 ± 0.83 16.42 ± 0.81 33.81 ± 2.21 10.13 ± 0.95 4.33 ± 0.41 0.02 ± 0.003 CZ2(2) 107.14 ± 0.26 5.41 ± 0.10 10,142.25 ± 6.41 8018.33 ± 1.81 98.93 ± 0.74 19.95 ± 1.21 33.53 ± 1.41 10.01 ± 0.46 2.99 ± 0.11 0.03 ± 0.001 CZ3(1) 134.03 ± 0.11 4.19 ± 0.07 15,524.00 ± 9.01 8099.57 ± 2.68 108.67 ± 2.11 20.06 ± 0.09 34.66 ± 0.89 9.69 ± 0.89 4.73 ± 0.31 0.01 ± 0.001 CZ3(2) 137.11 ± 0.42 4.88 ± 0.13 15,872.31 ± 5.81 8131.08 ± 1.41 117.59 ± 2.48 24.01 ± 0.16 36.61 ± 2.22 9.89 ± 0.41 5.93 ± 0.24 - CZ4(1) 141.26 ± 0.39 5.43 ± 0.09 16,324.19 ± 6.91 9561.75 ± 0.96 142.07 ± 1.79 24.98 ± 0.71 38.11 ± 1.51 10.98 ± 1.21 5.98 ± 0.31 0.06 ± 0.001 CZ4(2) 144.09 ± 0.41 6.29 ± 0.10 18,483.22 ± 10.73 8938.60 ± 2.31 149.62 ± 1.69 22.00 ± 0.11 40.21 ± 2.61 12.06 ± 1.13 6.07 ± 0.43 0.02 ± 0.002 CZ5 147.03 ± 0.72 6.67 ± 0.09 17,327.71 ± 9.19 9183.01 ± 4.86 152.88 ± 2.51 25.57 ± 0.94 41.85 ± 1.31 12.77 ± 0.91 7.01 ± 0.68 - CZ6 148.17 ± 0.18 5.99 ± 0.13 17,114.81 ± 12.61 9172.66 ± 3.14 183.36 ± 3.10 26.11 ± 0.69 41.28 ± 1.88 13.61 ± 1.01 6.99 ± 0.77 0.01 ± 0.003 CZ7(1) 150.06 ± 0.21 6.88 ± 0.23 17,210.64 ± 6.43 9317.09 ± 2.51 183.94 ± 1.42 26.91 ± 0.76 44.69 ± 2.10 14.93 ± 1.66 7.61 ± 0.39 0.03 ± 0.005 CZ7(2) 154.19 ± 0.66 5.96 ± 0.11 18,221.73 ± 12.11 8989.73 ± 5.19 194.90 ± 3.51 27.28 ± 0.82 43.74 ± 1.21 14.96 ± 1.44 7.92 ± 0.94 - CZ8 151.14 ± 0.28 4.85 ± 0.27 17,982.43 ± 7.17 9077.48 ± 2.38 164.27 ± 2.62 20.32 ± 0.91 47.99 ± 0.99 15.05 ± 0.89 6.28 ± 0.61 0.03 ± 0.002 CZ9(1) 155.05 ± 0.53 5.12 ± 0.11 14,942.99 ± 6.46 9141.12 ± 4.92 154.99 ± 1.11 17.32 ± 0.94 38.28 ± 1.03 14.91 ± 0.64 6.81 ± 0.95 0.04 ± 0.001 CZ9(2) 150.18 ± 0.81 5.11 ± 0.15 15,337.01 ± 8.04 8552.71 ± 3.41 158.26 ± 2.75 10.54 ± 0.61 36.18 ± 1.71 10.64 ± 0.48 5.01 ± 0.91 - CZ10 153.22 ± 0.95 5.59 ± 0.21 15,194.05 ± 8.71 9002.93 ± 3.21 158.84 ± 1.46 11.45 ± 0.94 33.60 ± 2.04 10.71 ± 0.71 5.13 ± 0.17 - Mean 133.45 ± 0.01 5.13 ± 0.021 16,415.17 ± 6.36 8597.46 ± 2.49 142.92 ± 1.25 20.18 ± 0.72 37.55 ± 0.61 12.01 ± 0.89 5.74 ± 0.01 0.02 ± 0.001 Average shale 95.00 13.00 47,200.00 15,000 850.00 68.00 90.00 45.00 19.00 0.300 Details of sample site codes are mentioned in the materials and methods section World average shale values (ASV) for trace metals as reported by Turekian and Wedepohl, 1961 were used as background values for calculating the geochemical indices because there were no geochemical background concentrations for the selected trace metals for the study area A sare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 9 of 17 suggested that Ni is primarily available in the organically This may be due to the new deposition of sediments in bound form in the soil, which under certain pH (acidic the estuarine sediments. Average concentrations of ten or neutral) conditions accelerate its movement and bio- trace metals were compared to the average shale value logical availability [55]. According to Anderson et al., the for sedimentary rock [35]. It was observed that only Zn primary anthropogenic sources of Ni pollution are fuel contents in all sampled sites exceeded the average shale combustion and agricultural wastes [56]. concentration for sedimentary rock. The other trace met- The concentration level of chromium (Cr) varied from als concentrations in all sampled sites were below the 21.64 to 47.99  mg/kg with an average concentration average shale values for sedimentary rock. Thus, it can of 37.55  mg/kg (Table  6). Cr is regarded as low mobil- be concluded that the fundamental source of trace met- ity trace metal, usually under moderately oxidizing and als at the studied sites is due to natural activities and little reducing conditions and nearly neutral pH. Zarei et  al. influence of anthropogenic activities (Table 7). reported that Cr and its associate compounds are used in synthesizing steel and some alloys, pigment produc- 3.2 Assessment of trace metals contamination tion, and chrome plating [57]. Thus, it can be deduced The average shale concentrations for sedimentary rock that the steel and iron industry and chrome plating are were used as background concentrations for trace met- the primary sources of Cr in the study area. Copper (Cu) als in evaluating EF [35]. Zn is more enriched in sampled concentration levels detected in all sampling sites varied sites CZ2 (i.e., offshore of Rambungan River opposite from 9.69 to 15.05 mg/kg with a mean concentration of to small Satang Island), CZ9 (i.e., offshore of Santubong 12.01 mg/kg (Table 6). Cu as a mineral is of great impor- resort), and CZ10 (i.e., Santubong River estuary). The tance for the proper growth and development of plants other sampled sites showed moderate enrichments of Zn due to its constituent of different enzymes and proteins (Table 8). [40, 55]. Cu is extensively applied in roofing, electrical High enrichment of Zn was detected in a sample col- wiring, and manufacturing pigments, piping, alloys, and lected from the offshore of Batang Rambungan opposite cooking utensils [49]. Therefore, manufacturing indus- small Satang Island i.e., CZ2(2), which could be attrib- tries of electrical appliances, alloys, roofing materials, uted to industrial discharges and domestic sewage. The etc., near the study area are the primary source of Cu. It EF values for As in collected samples at sampled sites has been reported that the pollution of the aquatic sys- CZ1 (i.e., Rambungan River estuary), CZ2 (i.e., Batang tem with Cu is linked with agrochemicals [19, 58]. Cobalt Rambungan opposite small Satang Island), and CZ3(1) (Co) concentration levels in the surface sediment var- (i.e., offshore of Batang Rambungan adjacent big Satang ied from 2.99 to 7.92 mg/kg with an average concentra- Island) were below 1, indicating no enrichment. The EF tion of 5.74 mg/kg (Table 6). The concentration levels of values for As for other sampled sites were between 1 and the detected cadmium (Cd) in the samples ranged from 3, showing minor enrichments. The highest EF value for nil (zero) to 0.06  mg/kg with a mean concentration of Mg is observed in a sample collected from Rambungan 0.02  mg/kg (Table  6). It was noticed that the estuarine River estuary, CZ2(1), with a value of 2.49, indicating sediments exhibited the highest concentration of Zn, minor enrichment (Table 8). Except for CZ1(1), the other Fe, Mg, and Mn compared to the coastal sediments. sampled sites have EF values for Mg between 1 and 3, Table 7 Detected trace metal concentrations in surface sediments in the study sites and in some selected world rivers Location Unit Zn As Fe Mg Mn Ni Cr Cu Co Cd References Coastal and selected estuaries, Malaysia mg/kg 133.45 5.13 16,415.17 8597.46 142.92 20.18 37.55 12.01 5.74 0.02 This study Langat River, Malaysia µg/g – – 28,300.00 – – 7.84 21.03 – – – [33] River Subin, Ghana mg/kg 49.70 4.82 – – – – 55.80 6.66 – 1.16 [59] River Ganga, India µg/g 67.76 – 31,988.60 – 372.04 26.70 69.94 29.75 – – [51] River Tigris, Turkey mg/kg 509.84 – – – – 284.00 135.81 1257.76 – – [60] River Jialu, China mg/kg 107.58 – – – – 42.44 60.80 39.22 – – [61] Mangonbangon River, Philippines mg/kg 213.45 – 22,006.14 – 261.97 61.14 89.45 116.36 15.31 – [40] Shur River, Iran Ppm 522.00 – – – – – – 9174.00 – – [62] Korotoa River, Bangladesh mg/kg – – – – – 95.00 109.00 76.00 – – [63] River Gomti, India mg/kg 76.34 – – – – 23.92 16.19 23.23 – – [64] River Huaihe, China mg/kg – – 28,300.00 – – 7.84 21.03 – – – [39] Asare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 10 of 17 Table 8 Enrichment of detected trace metals in surface sediments of the selected study sites Sample site code Zn As Mg Mn Ni Cr Cu Co Cd CZ1(1) 2.09 0.81 0.17 0.42 0.95 0.84 0.85 0.93 0.12 CZ1(2) 3.51 0.94 1.58 0.45 0.55 1.26 0.79 0.67 0.11 CZ2(1) 3.47 0.73 2.49 0.37 0.77 1.19 0.71 0.72 0.21 CZ2(2) 5.25 1.94 1.64 0.39 1.37 1.73 1.04 0.73 0.47 CZ3(1) 4.29 0.98 1.61 0.75 0.90 1.17 0.66 0.76 0.10 CZ3(2) 4.29 1.12 1.61 0.80 1.05 1.21 0.65 0.93 – CZ4(1) 4.30 1.21 1.84 0.83 1.06 1.22 0.71 0.91 0.58 CZ4(2) 3.87 1.24 1.52 0.93 0.83 1.14 0.68 0.82 0.17 CZ5 4.22 1.40 1.67 0.92 1.02 1.27 0.77 1.00 – CZ6 4.30 1.27 1.69 1.11 1.06 1.27 0.83 1.02 0.09 CZ7(1) 4.33 1.45 1.70 1.10 1.09 1.36 0.91 1.10 0.27 CZ7(2) 4.20 1.19 1.55 1.20 1.04 1.26 0.86 1.08 – CZ8 4.18 1.00 1.59 1.00 0.78 1.40 0.88 0.87 0.26 CZ9(1) 5.15 1.24 1.93 0.94 0.80 1.34 1.05 1.13 0.42 CZ9(2) 4.88 1.21 1.76 1.03 0.48 1.24 0.73 0.81 – CZ10 5.01 1.34 1.86 0.98 0.52 1.16 0.74 0.84 – Mean 4.21 1.19 1.64 0.83 0.89 1.25 0.80 0.90 0.18 Details of sample site codes are mentioned in the materials and methods section suggesting minor enrichment. Most of the EF values for for Ni, −2.64 to −1.49 for Cr, −2.80 to −2.18 for Cu, Ni and Cr in the samples were between 1 and 3, indicat- −3.25 to −1.85 for Cd, and −5.49 to −2.91 for Co. The ing minor enrichment while, most of the estimated EFs Igeo values for As, Fe, Mg, Mn, Ni, Cr, Cu, Cd, and Co for Co and Cd were below 1, suggesting background con- in the sediments from the study area were below class 0, centration. The high EF values obtained for some trace indicating unpolluted site. The high Igeo value for Zn was metals in some sampled sites may be ascribed to anthro- recorded in surface sediment collected from the offshore pogenic sources such as urbanization, industrial wastes of Santubong resort i.e., CZ9(1), suggesting unpolluted deposition, etc. Trace metals bioavailability and toxicity to moderately polluted. The positive Igeo values for Zn at in sediments are determined by their concentrations and the sampled sites from CZ4(2) to CZ10 may be attributed chemical form [19, 65]. Thus, trace metals in sediments to sewages discharges and/or effluents. with high EF values associated with labile fractions have The PLI values for trace metals of the studied site were the potential for mobility and bioavailability in aquatic summarised in Table 10. The PLI values varied from 0.22 environments [63]. to 0.52 and with a mean value of 0.31. This indicates that The list of CFs of ten trace metals in surface sediments there has been no occurrence of contamination in the is highlighted in Table  9. The highest CF value for Zn studied site. High PLI value was found in sediment from (i.e., CF = 1.63) was recorded in a sample collected from the offshore of Telaga Air opposite to small Satang Island. the offshore of Santubong Resort i.e., CZ9(1), suggest- In contrast, low PLI value was observed in sediment ing moderately contamination. This may be attributed from the Rambungan River estuary and the offshore of to commercial activities and vehicular effluence. Also, Batang Rambungan opposite small Satang Island. Based the CFs values obtained for As, Fe, Mg, Mn, Ni, Cr, Cu, on the PLI values, no significant disturbances of the Co, and Cd were below 1, which could be ascribed to aquatic environment due to heavy metals pollution were lithogenic influences. Anthropogenic activities such as observed. residential discharges, chemical control of surrounding weeds, etc., may also play a minor role. The Igeo values for trace metals in surface sediments 3.3 Ecotoxicological risk assessment from the coastal area and in four rivers estuary of Kuch- To determine the risks associated with trace metals tox- ing Division were shown in Table 10. The Igeo values for icity on organisms living at or near the bottom of the each trace metals are as follows: −0.49 to 0.11 for Zn, aquatic bodies (i.e., bodies of water forming a physiologi- −2.74 to −1.50 for As, −2.81 to −1.94 for Fe, −1.62 to cal feature for example a river, sea, etc.,); trace metals −1.22 for Mg, −3.69 to −2.71 for Mn, −3.28 to −1.91 concentrations were compared with consensus-based A sare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 11 of 17 Table 9 Contamination levels of detected trace metals in surface sediments of the selected study sites Sample site code Zn As Fe Mg Mn Ni Cr Cu Co Cd CZ1(1) 0.60 0.23 0.29 0.48 0.12 0.27 0.24 0.25 0.27 0.03 CZ1(2) 1.07 0.29 0.30 0.48 0.14 0.17 0.38 0.24 0.21 0.03 CZ2(1) 1.10 0.23 0.32 0.53 0.12 0.24 0.38 0.22 0.23 0.07 CZ2(2) 1.13 0.42 0.22 0.54 0.12 0.29 0.37 0.22 0.25 0.10 CZ3(1) 1.41 0.32 0.33 0.54 0.13 0.30 0.39 0.22 0.31 0.03 CZ3(2) 1.44 0.38 0.34 0.54 0.14 0.35 0.41 0.22 0.32 – CZ4(1) 1.47 0.42 0.35 0.64 0.17 0.37 0.42 0.24 0.32 0.07 CZ4(2) 1.52 0.48 0.39 0.60 0.18 0.32 0.45 0.27 0.37 0.07 CZ5 1.55 0.51 0.37 0.61 0.18 0.38 0.47 0.28 0.37 – CZ6 1.56 0.46 0.36 0.61 0.22 0.38 0.46 0.30 0.40 0.03 CZ7(1) 1.58 0.53 0.37 0.62 0.22 0.38 0.50 0.33 0.42 0.10 CZ7(2) 1.62 0.46 0.37 0.60 0.23 0.40 0.47 0.33 0.33 – CZ8(1) 1.59 0.37 0.38 0.61 0.19 0.30 0.53 0.33 0.36 0.10 CZ9(1) 1.63 0.39 0.32 0.61 0.18 0.25 0.43 0.33 0.26 0.13 CZ9(2) 1.58 0.39 0.33 0.57 0.19 0.16 0.40 0.24 0.26 – CZ10 1.61 0.43 0.32 0.60 0.19 0.17 0.37 0.24 0.26 – Mean 1.40 0.33 0.34 0.57 0.17 0.30 0.42 0.27 0.31 0.05 Details of sample site codes are mentioned in the materials and methods section Table 10 Geo-accumulation indices (Igeo) and pollution load indices (PLI) values of detected trace metals in surface sediments of the selected study sites Sample site code Zn As Fe Mg Mn Ni Cr Cu Co Cd PLI CZ1(1) −1.32 −2.69 −2.38 −1.62 −3.64 −2.45 −2.64 −2.62 −2.49 −5.49 0.22 CZ1(2) −0.49 −2.38 −2.30 −1.58 −3.46 −3.17 −1.97 −2.64 −2.84 −5.49 0.24 CZ2(1) −0.45 −2.74 −2.25 −1.49 −3.68 −2.64 −2.00 −2.74 −2.72 −4.49 0.22 CZ2(2) −0.41 −1.85 −2.81 −1.47 −3.69 −2.35 −2.01 −2.76 −3.25 −3.91 0.29 CZ3(1) −0.09 −2.22 −2.19 −1.46 −3.56 −2.35 −1.96 −2.80 −2.59 −5.91 0.28 CZ3(2) −0.06 −2.00 −2.16 −1.45 −3.44 −2.09 −1.88 −2.77 −2.27 – 0.34 CZ4(1) −0.01 −1.84 −2.12 −1.22 −3.17 −2.03 −1.82 −2.62 −2.25 −2.91 0.34 CZ4(2) 0.02 −1.63 −1.94 −1.32 −3.10 −2.21 −1.75 −2.48 −2.23 −4.49 0.35 CZ5 0.05 −1.55 −2.03 −1.28 −3.06 −2.00 −1.69 -2.40 −2.02 – 0.52 CZ6 0.06 −1.70 −2.05 −1.28 −2.80 −1.97 −1.71 −2.31 −1.91 −5.49 0.34 CZ7(1) 0.08 −1.50 −2.04 −1.26 −2.79 −1.92 −1.60 −2.18 −1.85 −3.91 0.40 CZ7(2) 0.11 −1.71 −1.96 −1.31 −2.71 −1.91 −1.63 −2.18 −1.85 – 0.49 CZ8 0.08 −2.01 −1.98 −1.29 −2.96 −2.33 −1.49 −2.19 −2.18 −3.91 0.37 CZ9(1) 0.12 −1.93 −2.45 −1.28 −3.04 −2.56 −1.82 −2.18 −2.06 −3.49 0.35 CZ9(2) 0.08 −1.93 −2.21 −1.38 −3.01 −3.28 −1.90 −2.65 −2.45 – 0.35 CZ10 0.11 −1.80 −2.22 −1.31 −3.69 −3.16 −1.79 −2.64 −2.47 – 0.36 Mean −0.11 −1.97 −1.62 −1.38 −3.24 −2.40 −1.85 −2.07 −2.34 −3.09 0.31 Details of sample site codes are mentioned in the materials and methods section threshold effect concentration (TEC), probable effect were available in the sediments quality guidelines devel- concentration (PEC), and the midway concentration oped by ANZECC/ARMCANZ, 2000. Thus, risks asso- between TEC and PEC (i.e., MEC) values fetched from ciated with 8 trace metals toxicity on bottom-dwelling the sediments quality guidelines developed by ANZECC/ organisms in the study area were appraised. The com- ARMCANZ, 2000 [38]. The TEC, MEC, and PEC data of parisons of consensus-based sediment-quality guidelines eight out of the ten detected trace metals in the samples (SQGs) with detected trace metals levels in the surface Asare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 12 of 17 sediments of the selected study sites were presented in equal or less than MEC, whereas 37.50 % of the samples Table  11. Twenty-five percent of the samples contained had Ni concentrations surpassing TEC but equal or less Zn concentrations less than the TEC value for Zn, while than MEC. Furthermore, 18.75 % of the sampled sites 62.50 % of the sampled sites contained Ni concentrations contained Cr concentrations above TEC but equal or less lower than the TEC value for Ni (Table 11). In addition, than MEC. 81.25 % of the samples had Cr concentrations below the The monomial potential ecological risks (Ei) for each TEC value for Cr. All the sampled sites contained As, Fe, trace metal and possible environmental risk index (RI) Mn, Cu, and Cd concentrations below TEC values for As, in all collected samples from the coastal and in four riv- Fe, Mn, Cu, and Cd, respectively. None of the samples ers estuary were detailed in Table  12. The RI index was contained trace metals exceeding the PEC values. Trace computed based on the eight heavy metals (i.e., Zn, As, metals concentrations in surface sediments below TEC Ni, Cr, Cu, Co, and Cd). The mean potential ecological values were unlikely to negatively impact bottom-dwell- risk for studied tace metals follow the order of Mn ˂ Cr ing organisms [60]. Seventy-five percent of the sampled ˂ Ni ˂ Cu ˂ Zn ˂ Cd ˂ Co ˂ As. Among the analysed trace sites contained Zn concentrations exceeding TEC but metals; Mn, Cr, and Ni had relatively lower RI values due Table 11 Comparisons of consensus-based sediment-quality guidelines (SQGs) with detected trace metals levels in the surface sediments of the selected study sites Zn As Fe Mn Ni Cr Cu Cd SQGs TEC 120 9.8 20,000 460 23 43 32 0.99 MEC 290 21.4 30,000 780 36 76.5 91 3.00 PEC 460 33 40,000 1100 49 110 150 5.00 % sample sites of detected trace metal less than TEC 25.00 100.00 100.00 100.00 62.50 81.25 100.00 100.00 % sample sites of detected trace metal greater than TEC but 75.00 0 0 0 37.50 18.75 0 0 equal or less than MEC % sample sites of detected trace metal greater than PEC 0 0 0 0 0 0 0 0 Details of detected trace metals value in each sample site are mentioned in Table 6 in the results section Table 12 The potential ecological risk index values (RI) of detected trace elements in surface sediments of the selected study sites Sample site code Ei RI Zn As Mn Ni Cr Cu Co Cd CZ1(1) 0.60 2.30 0.12 1.35 0.48 1.25 1.35 0.90 8.05 CZ1(2) 1.07 2.90 0.14 0.85 0.76 1.20 1.05 0.90 8.87 CZ2(1) 1.10 2.30 0.12 1.20 0.76 1.10 1.15 2.10 9.83 CZ2(2) 1.13 4.20 0.12 1.45 0.74 1.10 1.25 3.00 12.99 CZ3(1) 1.41 3.20 0.13 1.50 0.78 1.10 1.55 0.90 10.57 CZ3(2) 1.44 3.80 0.14 1.75 0.82 1.10 1.60 – 10.65 CZ4(1) 1.47 4.20 0.17 1.85 0.84 1.20 1.60 2.10 13.43 CZ4(2) 1.52 4.80 0.18 1.60 0.90 1.35 1.85 2.10 14.30 CZ5 1.55 5.10 0.18 1.90 0.94 1.40 1.85 – 12.92 CZ6 1.56 4.60 0.22 1.90 0.92 1.50 2.00 0.90 13.60 CZ7(1) 1.58 5.30 0.22 1.90 1.00 1.65 2.10 3.00 16.75 CZ7(2) 1.62 4.60 0.23 2.00 0.94 1.65 1.65 – 12.69 CZ8 1.59 3.70 0.19 1.50 1.06 1.65 1.80 3.00 14.49 CZ9(1) 1.63 3.90 0.18 1.25 0.86 1.65 1.30 3.90 14.67 CZ9(2) 1.58 3.90 0.19 0.80 0.80 1.20 1.30 – 9.77 CZ10 1.61 4.30 0.19 0.85 0.74 1.20 1.30 – 10.19 Mean 1.40 3.30 0.17 0.85 0.84 1.35 1.55 1.50 10.96 Details of sample site codes are mentioned in the materials and methods section A sare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 13 of 17 to their low toxicity response factors. Furthermore, RI In this current study, PCA was conducted based on results in the surface sediment varied from 8.05 (CZ1) to the evaluated concentrations of trace metals with vari- 16.75 (CZ7). The obtained RI values for all sampled sites max rotation. The Kaiser–Meyer–Olkin (KMO) test were lower than 150, indicating that the sediments in gives 0.49, and the Barlett test gives 99.82 (df = 45), the studied site posed a minimum risk. The most signifi- showing strong interrelationships among variables cant Ei values were recorded for As, because, based on and substantiating that PCA can be used to reduce Hakanson’s approach, the toxic response of this metal is the dimensionality of variables. Based on PCA results the highest. Although, it does not show a high ecologi- (Fig. 2 and Additional file 1: Table S1), PCA1 accounts cal risk in the coastal and in four rivers estuary sediment, for 67.33% of the variation, and its representative con- owing to the fact that the quantified As values are posi- geners include Mn, Mg, Zn, Co, Cr, As, Cu, Fe, and Ni, tioned below the acceptable limit. The other metals that suggesting a common source that is probably exog- made an important contribution to the final result of the enous discharge [68, 69]. PCA2 accounts for 11.80% of RI index include Cu, Ni and Co. the variation, and its representative congeners are Cd and Mg, implying a similar source that may be attrib- 3.4 Trace metal pollution source uted to industrial and domestic discharge. The weak Evaluating the sources of trace metals can help com- correlation between Cd and other trace metals is an prehend their distribution. Thus, Pearson’s correlation indication of different external sources. analysis and principal component analysis (PCA) were employed to analyze the relationship and source of the trace metals [66, 67]. The correlation coefficient matrix recording the Pear- son’s product-moment coefficients were shown in Table  13. Positive correlations were recorded between (Zn and As), (Zn and Fe), (Zn and Mg), (Zn and Mn), (Zn and Cr), (As and Mg), (As and Cr), (As and Co), (Fe and Mg), (Fe and Mn), (Fe and Cr), (Fe and Co), (Mg and Mn), (Mg and Cr), (Mg and Co), (Mn and Cr), (Mn and Cu), (Mn and Co), (Ni and Co), (Cr and Cu), (Cr and Co), and (Cu and Co) at 0.01 significant level. Positive correlations were also noticed between (Zn and Cu), (Zn and Co), (As and Ni), (As and Cu), (Fe and Cu), (Mg and Cu), (Mg and Cd), (Mn and Cu), and (Mn and Cd) at 0.05 significant level. The high positive interrelationships between stud- ied trace metals are indication of a common source. Fig. 2 Principal component profile of the ten trace metals collected from the sediments of the selected sampling sites Table 13 Correlation coefficients between different detected trace metals in surface sediments of the selected study sites Zn As Fe Mg Mn Ni Cr Cu Co Cd Zn 1 As 0.747** 1 Fe 0.630** 0.48 1 Mg 0.849** 0.801** 0.625** 1 Mn 0.768** 0.741** 0.715** 0.790** 1 Ni 0.268 0.543* 0.477 0.4790 0.375 1 Cr 0.807** 0.686** 0.711** 0.739** 0.740** 0.496 1 Cu 0.499* 0.511* 0.581* 0.612* 0.799* 0.452 0.707** 1 Co 0.619* 0.630** 0.808** 0.726** 0.832** 0.667** 0.667** 0.812** 1 Cd 0.435 0.377 0.065 0.649* 0.252 0.331 0.342 0.241 0.267 1 **Correlation is significant at the 0.01 level (2-tailed) *Correlation is significant at the 0.05 level (2-tailed) Computed values were for all the selected study sites Asare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 14 of 17 4 Discussion sampled sites followed the order: Cd ˂ Cu ˂ Mn ˂ Ni ˂ Co The coastal and four rivers estuary (i.e., Santubong, ˂ As ˂ Mg ˂ Cr ˂ Zn (Table  8). Generally, the evaluation Salak, Sibu, and Rambungan) is a vital agricultural and showed minor enrichments of almost all the trace metals transportation water resources for the Kuching Division in all sampled sites. The enrichments of trace metals may of Sarawak. Therefore, it is necessary to evaluate the pol- be attributed to both natural processes and anthropogenic lution status, ecotoxicological risks, and likely sources of sources, including industrial wastes deposition, sewage trace metals in the surface sediments of the coastal and discharges, and urbanization. The trend of obtained CFs four selected rivers estuary. In aquatic ecosystems, sedi- values for trace metals in all samples followed the order: ment is both a source and a sink of trace metals. Thus, Cd ˂ Mn ˂ Cu ˂ Ni ˂ Co ˂ As ˂ Fe ˂ Cr ˂ Mg ˂ Zn. Almost this study investigated ten trace metals in surface sedi- all the trace metals CF values were below 1 in all sampled ments from the coastal and four rivers estuary. sites, suggesting minimum contamination conditions In sediment samples, all ten trace metals were detected, except for Zn, which showed moderate contamination in and their average concentration followed the order of Cd some sample sites (Table 10). All the trace metals except ˂ As ˂ Co ˂ Cu ˂ Ni ˂ Cr ˂ Zn ˂ Mn ˂ Mg ˂ Fe. The assess- Zn have Igeo values lower than 0, indicating background ment showed moderate As, Mg, Cr, and Ni pollution. The concentration. Generally, the Igeo values obtained for Zn average concentrations of trace metals in surface sedi- indicate a minor role played by anthropogenic activities. ment were compared with other studies of trace metals From the PLI results; there is no significant disturbance in rivers in the world (Table  7). The Zn concentrations of the aquatic environment due to trace metals pollution. detected in all sampled sites were lower than Zn con- The PLI values can be used as baseline contamination lev- tent in Tigris River sediment, Mangobangon River sedi- els in the future for pollution monitoring in a selected site. ment [40], and shur River sediment [62]. Furthermore, The ecological risk index has been demonstrated as a the average concentrations of Cu in the studied area highly productive tool to evaluate the total pollution of were below Cu contents reported values from surface sediments of an aquatic ecosystem [54]. Protano et  al. sediments from Tigris River [60], Mangonbangon River narrated that the inadequacy of updated reference metal sediment [40], Jialu River sediment [61], Krotoa River values for a specified ecological site or geographical zone sediment [63], and Gomti River sediment [64] (Table 7). can lead to underestimating or overestimating the actual The mean concentrations of Ni in all sediment samples pollution load in sediments and the environmental risk were lower than values reported in surface sediments index [70]. Decena et al. reported that to get an accurate from Tigris River [60], Jialu River [61], Mangonbangon estimation of the ecological risk of metals, regular updates River [40], Korotoa River [63], and Gomti River [64]. The of reference concentrations after a certain period are average concentration of Cr in this current study was required, especially in geological zones with sensitive eco- below the detected level of Cr in surface sediment’s from logical environments [40]. Average concentrations of trace the Subin River [59], Tigris River [60], Mangonbangon metals were compared with sediment-quality guidelines River [40], and Korotoa River [63]. The Mn in the sedi- (SQGs). It was observed that almost all the trace metals ments of Mangonbangon River [40] exceeded the val- in all sampled sites were below TEC values for respective ues of Mn concentration in this study. Furthermore, the trace metals except Zn, Ni, and Cr, in which their concen- detected level of Cd was higher than Cd levels detected trations exceeded TEC values for Zn i.e., from sampled in surface sediments from the Subin River [59]. In con- site CZ3(1) to CZ10; Ni i.e., from sampled site CZ3(2) to trast, the average concentrations of detected Fe in this CZ7(2); and Cr i.e., from sampled site CZ7(1) to CZ8. It study were below the concentrations of detected Fe in can be deduced that trace metals concentrations in sam- surface sediments from Mangonbangon River [40] and pled sites above TEC but equal or less than MEC may Huaihe River [39]. probably affect bottom-dwelling organisms. According to Although the single factor pollution indices (i.e., EF, CF, the IR results, a low potential ecological risk from all the and Igeo) method has been widely used, it is functional trace metals in all sampled sites was noticed. to a single pollutant. Thus, it does not consider a mixture Since the studied trace metals in sediments have a mod- of trace metals primarily available in the pollution con- erate adverse health impact on the biome, it is necessary ditions. However, it has helped to ascertain how much to assess and control the pollution source. Trace elements the available metal in sampled sites has elevated relative in sediments often show complex interrelationships. Many to average natural abundance due to human activity [7]. factors influence their relative abundance, for instance, Nevertheless, an integrated pollution index (i.e., PLI) was parent materials and rocks, anthropogenic activities, employed to help considering the mixture of trace met- and soil formation processes [42, 71]. Pearson’s correla- als present in the contamination conditions. Based on tion analysis was used to assess the relationship between EF results, the trend of trace metal enrichments in all the trace metals. Principal component analysis (PCA) A sare et al. Beni-Suef Univ J Basic Appl Sci (2022) 11:18 Page 15 of 17 was performed to evaluate the most common pollution Acknowledgements sources. Correlation analysis and PCA results showed The authors acknowledge the contribution of colleagues from the Analytical Chemistry Laboratory, Faculty of Resource Science and Technology (FRST), strong positive interrelationships between trace metals, Universiti Malaysia Sarawak. suggesting a common source or similar geochemical char- acteristics except for Cd, which showed a weak correlation Authors’ contributions EAA, ZA, and RW conceived of the study and carried out the design of the with other trace metals except for Mg (Fig.  2 and Addi- experiment. EAA carried out the sample preparation and analysis, EAA, ZA, tional file 1: Table S1). The inverse relationships between and JRF assessed the data, and EAA, ZA, and RW helped to draft and edited Cd and other trace metals are indication of different exter- the manuscript. All authors read and approved the final manuscript. nal sources. Funding Despite a low level of absolute content, the As, Cd, The consumables and field trip cost of the entire research were financially and Ni in sediment already render a moderate mono- supported by Universiti Malaysia Sarawak, Postgraduate Research Grant, with Grant Code: F07/PGRG/1896/2019. mial ecological risk and therefore calls urgent attention. The primary source of trace metals in sediment is natu- Availability of data and materials ral processes and sediment properties. Anthropogenic All data generated or analyzed during this study are included in this paper. activities may also influence trace metals distribution of the studied area. Declarations Ethical approval and consent to participate 5 C onclusions Not applicable. The concentrations of ten trace metals in surface sedi- Consent for publication ments collected from the coastal and in four rivers estu- Not applicable. ary in Sarawak, Malaysia, were examined. All ten trace Competing interests metals were detected at all sampled sites, with a concen- The authors declare that they have no competing interests. tration lower than the average shale value for sedimen- tary rock except Zn. Pollution appeared more severe in Author details1 Department of Chemistry, Faculty of Resource Science and Technology, the coastal of the studied area, probably due to point Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia. source contamination nearby. Among the trace met- 2 Department of Nuclear Science and Applications, Graduate School of Nuclear als of interest, Zn, Ni, and Cr concentrations surpassed and Allied Sciences, University of Ghana, AE1, Kwabenya-Accra, Ghana. the TEC values and should be carefully monitored and Received: 9 November 2020 Accepted: 17 January 2022 remediated because they may cause unfavorable impacts on bottom-dwelling organisms. 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