Assessment of Heavy Metal Pollution and Human Health Risks Associated with Etroplus suratensis (Green Chromide) in Koggala Lagoon, Sri Lanka

Assessment of Heavy Metal Pollution and Human Health Risks Associated with Etroplus suratensis (Green Chromide) in Koggala Lagoon, Sri Lanka | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessment of Heavy Metal Pollution and Human Health Risks Associated with Etroplus suratensis (Green Chromide) in Koggala Lagoon, Sri Lanka APSW Abeysooriya, EGKYC Bandara, HLK Sanjaya, Mok Wen Jye, PPSK Patabandi, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4587800/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Fish have long been identified as good indicators for scientific studies particularly to examine heavy metal pollution in aquatic environments and its associated human health risks. This study assesses the accumulation of heavy metals in different tissues of the food fish Etroplus suratensis (Green Chromide) collected from Koggala lagoon, Sri Lanka. We quantified the concentrations of the four heavy metal ions; Cu2+, Cd3+, Pb2+, and Cr3+ across distinct tissues including skin, liver, gill, and flesh in fish in varying sizes using Atomic Absorption Spectrophotometer (AAS). Samples comprised thirty-six (n=36) fish from three different locations in the lagoon; the area near the KEPZ (L1), the middle of the lagoon (L2), and the area near the cultivation site (L3). The highest concentrations of heavy metals were found in the flesh and skin, while the lowest were observed in the gills. The range of heavy metal concentrations (g/g) in the body tissue varied by fish size; for small-sized fish, Cu (0.0443-0.6210), Cd (0.0110-0.0214), Pb (below detection level-0.46), and Cr (below detection level-39.633); for medium-sized fish, Cu (0.0713-0.6210), Cd (0.0134-0.0170), Pb (below detection level-40.906), and Cr (0.0014-0.0500) and for larger-sized fish, Cu (0.0553-0.345), Cd (0.0110-0.0256), Pb (0.0204-0.2103) and Cr (0.0194-0.0773). The levels of Cd, Cr, and Pb in the flesh tissues of E. suratensis flesh tissues were below the FAO’s recommended standards, however, the nontoxic heavy metal Cu exceeded these limits. Given the bioaccumulation and biomagnification of the studied heavy metals and the consumption of E. suratensis in the Koggala lagoon, regular monitoring is essential to ensure consumer safety. Green chromide fish heavy metals pollution assessment Koggala Lagoon Sri Lanka Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Lagoons are among the most sensitive and vulnerable aquatic ecosystems to heavy metal pollution. These natural environments provide multiple ecosystem services to humans, hence they are exploited extensively where many human activities such as aquaculture, fishing, coastal tourism, and agriculture are practiced in and around lagoon systems [1-6]. The unsustainable exploitation of lagoons' ecosystems threatens their viability and endangers human health. In lagoons, contaminants continuously accumulated through food chains can potentially affect humans and other living organisms at different trophic levels. The bioaccumulation depends on the concentration of heavy metals in plants, water, and sediments [7-9]. Industrialized urban areas enhance the entry of pollutants to coastal areas, such as lagoons, posing a threat of ecosystem degradation. The heavy metals assimilated by fish will accumulate at various concentrations in various tissues or organs [10-12]. As fish have become the staple food of coastal communities, the heavy metal bioaccumulation in fish has become an alarming threat, especially to poor coastal communities [13-14]. The uptake of heavy metals by fish will depend on both biotic and abiotic factors though there are various mechanisms to excrete some of the assimilated metals [15]. However, the species, location, and seasons may determine the bioavailability of heavy metals in fish; therefore, scientific studies in these areas are vital. The Koggala lagoon covers a hydro catchment area of approximately 55 km 2 and features various land use activities, primarily paddy farming and small-scale fisheries [16]. Fishing in Koggala lagoon is a partially modernized income-generating activity, mainly carried out through small-scale subsistence operations. The fish production in this coastal lagoon supports the livelihood of local (poor) farmers living around Koggala lagoon while providing a source of affordable, high–quality protein supplements. Koggala lagoon hosts a variety of finfish and shellfish species, including E. suratensis , Oreochromis niloticus, Oreochromis mossambicus, Ctenopharyngodon Idella, Hypophthalmichthys molitrix, Cyprinus carpio, Mugil cephalus, Penaeus indicus, Penaeus monodon, Scylla serrata, and Portunus pelagicus, among others [17]. The lagoon is also known as one of the main tourist spots on the southern coast of Sri Lanka, boasting rich biodiversity and ecosystems [16]. Consequently, there are several tourist hotels, resorts, and boat safari businesses located around the lagoon area. Due to various land use practices and development activities, the lagoons are threatened by both point and non-point source pollution. The nearest area of Koggala lagoon consists of non-paddy crops, paddy crops, tourist hotels (resorts), and the Koggala Export Processing Zone (KEPZ). Agrochemicals used in the nearby rice and tea plantations have direct access to the lagoon. Currently, 12 factories are operating in the KEPZ, with the majority of them in the apparel industry. However, none of these industries are involved in the dyeing and washing processes that could significantly contribute to producing toxic wastewater. Additionally, other industries, such as plastics and rubber toys are also in production, with most of them using organic solvents that release toxic chemicals into the environment [18]. Up to this point, the KEPZ has neglected wastewater and sewage treatment, while industrial wastes such as plastics, fabric scraps, and food are dumped onto marshy land bordering the lagoon which augmented the problem, particularly during the rainy seasons with frequent rainfall [16]. E. suratensis is one of the most commonly (popular) consumed fish species by communities residing near the Koggala lagoon, especially among low-income families. Compared to other brackish water fish species, E. suratensis exhibits rapid growth and attains maturity in just a few months. Since many villagers consume fish in at least one meal per day, this study aimed to evaluate the concentration of Cd, Cu, Pb, and Cr in the tissues of the E. suratensis fish, including gills, flesh, skin, and liver, all collected from the Koggala lagoon, Sri Lanka. Subsequently, the results were compared across different body sizes (small, medium, and large) and against the permissible limits established by the European Commission (EC), the United States Food and Drug Administration (USFDA), Food and Agriculture Organization (FAO), and the World Health Organization (WHO) to determine heavy metal contamination. Furthermore, the transfer factor of heavy metal also was used to evaluate the lagoon environment. Materials and Methods Site selection We selected the Koggala lagoon as a case study to assess the heavy metals' bioavailability. The lagoon is located in the Galle District of Southern Sri Lanka and comprises eight small islands with diverse ecosystems surrounding it. The Koggala lagoon is 4.8 km long, 2 km wide, and has a surface area of approximately 7.27 km 2 . Water depths within the lagoon range from 1 m to 3.7 m [16]. Koggala lagoon primarily relies on rainwater for its freshwater supply, with several small streams connected to it, though its main source is the Koggala Oya. Three sampling sites were selected in Koggala lagoon based on the basic information from villagers, fishermen, and field observations. They were a location near the Koggala Export Processing Zone (KEPZ), the middle of the lagoon, and a area near the cultivation area. Table 1 GPS location of sampling stations at Koggala lagoon Site Location Area near the KEPZ (L1) 5° 59' 39.4836'' N and 80° 19' 45.5808'' E Middle of the lagoon (L2) 6° 0' 19.3032'' N and 80° 19' 35.0148'' E Area near the cultivation site (L3) 5° 59' 51.774'' N and 80° 20' 21.3576'' E Samples collection (water, sediment, and fish) Water, sediment, and fish samples were collected from the sampling sites. The sediment samples were collected in triplicate at each sampling site using Kajak core sampler. These samples were then transferred to polythene bags, that had been thoroughly rinsed with Dil. HNO 3 acid and deionized water. As for the water samples, triplicate samples were collected from three layers of the water column at each sampling site including the surface, middle layer, and bottom layers. One liter (1 L) of water sample was collected from each of these layers at all three locations using the Ruttner sampler. All water samples were collected in polypropylene bottles that had been thoroughly rinsed with deionized water and Dil. (HNO 3 ) to avoid any potential contaminants. Prior to sampling, the sampling bottles were also rinsed with lagoon water. A total of thirty- six fish were collected from the lagoon's fresh catch by fishermen early in the morning. These thirty-six fish were grouped based on their body size; small (SF):10.1 cm - 11.6 cm, medium (MF):14.1 cm -16.6 cm, and large (LF) fish: 19.6 cm – 23.2 cm. From each selected site, 12 fish were collected for the analysis ensuring representation across the available size ranges. Each fish was washed with distilled water before being packed in pre-clean polythene bags. The fish were then carefully preserved with ice in a box to minimize tissue degradation and maintain moisture content during transportation [19]. Finally, fish were transported to the general laboratory, Department of Fisheries and Aquaculture Faculty of Fisheries and Marine Sciences and Technology at the University of Ruhuna, Matara, Sri Lanka. Analysis of water quality Water temperature ( o C), dissolved oxygen (mg/L), salinity (ppt), pH, conductivity (mS/cm), and total dissolved solid (mg/L) were measured by using a multi-probe (YSI 556 MPS, Japan). Chlorophyll -a in water was measured in accordance with ESS method 150.1 [20]. The total suspended solid (TSS) in water was measured according to the Standard Methods, 2540D and EPA (1983) Method 160.2 (Residue, non-filterable). A well-mixed, measured volume of a water sample is filtered through a pre-weighed glass fiber filter. The filter is heated to constant mass at 104 ± 1ºC and then weighed. The mass increase divided by the water volume filtered is equal to the TSS in mg/L. Table 2 (Mean ± SD) of Total length, Standard length, Head length, Total weight and their range (minimum and maximum) and percentage of maturity stage of E. suratensis captured from three different locations of Koggala lagoon on 09 th May 2022. Location of the lagoon Fish size range Total length (cm) Head length (cm) Standard length (cm) Total weight (g) Percentage of maturity stage DM DF DM* DF* SM SF L1 SF 9.8 ± 0.4 9.2 – 10.3 3.2 ± 0.2 2.8 - 3.5 8.4 ± 0.5 7.6 – 9.2 20.0 ± 1.8 16.5 - 22.1 41.66% 58.34% MF 14.1 ± 1.2 12.3- 16.0 4.7 ± 0.3 4.0 - 5.0 12.0 ± 1.4 10.1 - 14.3 79.2 ± 8.1 68.6 - 90.0 33.34% 66.66% LF 20.5 ± 1.4 18.6 – 22.3 6.1 ± 0.3 5.6 - 6.8 18.3 ± 1.6 16.2 - 20.4 148.4 ± 15.3 130.0 - 168.6 50% 50% L2 SF 10.8 ± 0.5 10.1 - 11.6 3.5 ± 0.2 3.2 - 3.9 9.4 ± 0.5 8.6 - 10.1 21.7 ± 2.7 16.5 - 25.0 41.66% 58.34% MF 15.6 ± 0. 8 14.1 - 16.6 4.7 ± 0.4 4.0 - 5.3 13.5 ± 0.9 12.0 - 14.5 85.7 ± 7.8 70.2 - 96.5 50% 50% LF 21.7 ± 1.3 19.6 - 23.2 6.2 ± 0.4 5.6 - 6.8 18.6 ± 1.2 16.8 - 19.8 154.6 ± 13.3 133.5 - 168.6 66.66% 33.34% L3 SF 9.9 ± 0.4 9.2 – 10.6 3.4 ± 0.2 3.2 - 3.7 9.2 ± 0.4 8.6 - 10.0 20.8 ± 2.4 16.5 - 25.0 75% 25% MF 15.4 ± 0. 6 14.6 - 16.6 4.7 ± 0.3 4.0 - 5.0 13.4 ± 0.8 12.0 - 14.4 84.7 ± 6.8 70.2 - 91.1 33.34% 66.66% LF 22.1 ± 1.9 19.6 - 25.5 6.3 ± 0.4 5.6 - 6.8 18.6 ± 1.1 16.8 - 19.8 152.8 ± 13.8 130.0 - 170.0 58.33% 41.67% NB: number of fish (n) = 12, DM - Developing Male, DF - Developing Female, DM* - Developed Male, DF* - Developed Female, SM - Spawning Male and SF - Spawning Female Sample preparation and acid digestion of samples (sediment, water, and fish) Once in the laboratory, all collected samples, sediments, water, and fish have undergone physical preparation and acid digestion according to Shumo et al. [21], Kwaansa-Ansahet al. [22], and Mendil et al. [23] respectively. The sample preparation and acid digestion of different samples is detailed in the schematic presentation below (Fig. 2). Analysis using atomic absorption spectrophotometer Digested fish samples, sediments, and filtered water samples were prepared for atomic absorption spectroscopy (Varian 220) to analyze four heavy metals; Lead (Pb), chromium (Cr), Cadmium (Cd), and copper (Cu). Standard solution of Pb, Cd, Cu, and Cr at 1000 ppm was prepared to create a series of ionic samples at nine concentrations; 0.05, 0.1, 0.2, 0.4, 0.8, 1.6, 3, 5 and 10 ppm. A standard curve was drawn using the absorbance levels of these known concentrations and calculated the heavy metal concentration of each sample. Readings were taken for all the triplicate samples [24]. Transfer factor The transfer factor of fish tissues in the aquatic ecosystem was determined using the methodology described by Rashed et al. [25]. This method was used to calculate the levels of heavy metals in fish tissue in relation to sediment and water Statistical data analysis Statistical analysis was performed using IBM SPPS software package. Initially, the data of all heavy metal concentrations of relevant body sizes were checked for normality. A one-sample t-test was used to determine whether there were significant differences in metal concentrations among fish tissues, water, and sediment samples. Additionally, these samples were compared with the standard recommended heavy metal limits. To compare the differences in heavy metal concentrations in water, sediment, and different body parts of fish at each sampling site, a one-way ANOVA (at a 95% confidence level) with a post-hoc test (Turkey’s test) was conducted. Metal concentration in gills, liver, muscle, skin, water, and sediment samples were compared using Turkey’s multiple comparisons of means. The SPPS software was also used to compute descriptive statistics for the data. Results Water quality parameters The water samples were collected from three locations in the lagoon, namely, an area near the KEPZ (L1), the middle of the lagoon (L2), and the area close to the cultivation site (L3). These samples were analyzed for water-selected quality parameters, including temperature (°C), DO (mg/L), salinity (ppt), pH, conductivity (mS/cm), Total suspended solids - TSS (ppm), Total dissolved solid - TDS (mg/L) and Chlorophyll-a (mg/L) ( Table 3). The general water quality parameters, such as temperature and pH at all the locations were not significantly different and remained within the range of 28-29 °C and 5.5-6.0 respectively. However, the dissolved oxygen level (DO) at the target locations showed significant differences. The highest value (7.21 mg/L) was recorded at L1 while the lowest value (2.80 mg/L) was detected at L3. In terms of salinity, both L1 and L3 exhibited no significant difference, with values ranging approximately from 6.7 to 6.8. In contrast, the salinity level at L2 was significantly lower (3.02 ppt) compared to those at the other two sites. The conductivity values followed a similar pattern, as L1 and L3 showed no significant difference (12.09 mS/cm and 12.82 mS/cm, respectively) while the lowest significant value (6.14 mS/cm) was recorded at L2. The highest amount of total suspended solid was detected at L2 (400.31 ppm), whereas the lowest (288.54 ppm) was found at L1, and these TSS values were significantly different from each other. Regarding the total dissolved solids (TDS), the values at L1 (77.92 mg/L) and L3 (76.70 mg/L) locations were not significantly different from each other. However, the lowest TDS value was recorded at L2 (37.03 mg/L). Finally, the Chlorophyll-a content was also measured, and the results indicated significant differences among all locations. The highest Chlorophyll-a content was recorded at L3 (0.15 mg/L) whereas the lowest was recorded at L2 (0.10 mg/L). Table 3 Water quality parameters (Mean ± SD) and the range (minimum-maximum) from Koggala lagoon on 09 th May 2022 Site of the Koggala lagoon Water Quality Parameters Temperature ( ° C) DO (mg/L) DO % Salinity (ppt) pH Conductivity (mS/cm) TSS (ppm) TDS (mg/L) Chlorophyll - a (mg/L) L1 29.01 ± 0.00 a 29.00 - 29.01 7.21 ± 0.04 a 7.23 - 7.30 95.62 ± 0.005 a 95.22 - 96.24 6.80 ± 0.03 a 6.71 - 6.82 5.53 ± 0.02 a 5.51 - 5.50 12.09 ± 0.03 a 12.88 - 12.93 288.54 ± 1.00 c 287.51 - 289.50 77.92 ± 0.02 a 77.70 - 78.12 0.13 ± 0.02 b 0.11 - 0.15 L2 28.92 ± 0.00 a 28.91 - 28.92 4.84 ± 0.06 b 4.78 - 4.90 64.23 ± 0.01 b 63.42 - 64.81 3.02 ± 0.05 b 2.94 - 3.07 5.95 ± 0.06 a 5.88 - 6.00 6.14 ± 0.03 b 6.11 - 6.16 400.31 ± 2.55 a 397.48 - 402.50 37.03± 0.12 b 36.89 - 37.11 0.10 ± 0.10 c 0.09 - 0.11 L3 29.31 ± 0.00 a 29.30 - 29.31 2.80 ± 0.02 c 2.80 - 2.81 37.09 ± 0.002 c 36.83 - 37.32 6.70 ± 0.01 a 6.64 -6.70 5.60 ± 0.01 a 5.59 - 5.61 12.82 ± 0.01 a 12.77 - 12.79 352.50 ± 28.93 b 319.50 - 373.50 76.70 ± 0.02 a 76.69 - 76.72 0.15 ± 0.03 a 0.12 - 0.18 NB: Number of samples (n) = 3, TDS: Total Dissolved Solid, TSS: Total Suspended Solid, DO: Dissolved Oxygen, mean values within the same column with different superscripts are significantly different at P < 0.05 Heavy metal levels in water Heavy metal concentrations, namely Cu, Cd, Pb, and Cr, were assessed across three distinct water layers; surface, middle, and bottom, at three designated locations (L1, L2, and L3) using an Absorption Spectrophotometer (AAS). The results of these measurements are presented in Table 4. According to the result shown Table 4, all the measured heavy metal concentrations in the same water layer at each location did not show any significant difference. Nevertheless, within the same location, significant variations were evident in the heavy metal concentrations across the three water layers for all the assessed heavy metals. The heavy metal concentrations distribution in the three layers are in the following order Bottom layers>Middle layers> Surface layers. Among the tested heavy metals Cr exhibited the highest concentration across all the locations and the water layers. However, the surface layer at L3 (in proximity to the cultivation site) did not show any detectable concentrations of Cr. Additionally, the bottom layer exhibited the highest detectable level for each heavy metal where the concentrations of Cu and Cd at the L3 bottom layer were 0.7051 mg/L and 0.6020 mg/L respectively while at L2 and L1 bottom layers Pb and Cr displayed the following concentrations: 1.8213 mg/L and 25.7660 mg/L respectively. Conversely, the surface layers indicated the lowest concentrations mainly at the L2 surface layers. Cu, Cd, and Pb showed the flowing concentrations, 0.0413 mg/L, - 0.0510 mg/L, and 1.8213 mg/L respectively. At L3 surface layers, Cr level was found below the detectable limit.Moreover, the detected levels of Cu and Cd were significantly lower compared to Pb and Cr. Thus, the results show variations of notable significance emerged in the heavy metal concentrations within the same water layers across different locations, except in a few instances where the same water layer displayed insignificant detections in at least two sites (e.g., Cd levels in the safe layer, Cr levels in the bottom layer). Table 4 Metal concentration (mg/L) (Mean ± SD) and their range (minimum-maximum) measured using an Atomic Absorption Spectrophotometer (AAS) in water (surface, middle, and bottom layer) collected from Koggala lagoon on 09th May 2022 compared with three water layers Site of the lagoon Heavy Metal Level (mg/L) Cu Cd Pb Cr L1 Surface Layer 0.0752 ± 0.0015 c 0.0740 - 0.0770 0.0961 ± 0.0005 c 0.0950 - 0.0960 0.3833 ± 0.0115 c 0.3700 - 0.3900 3.8513 ± 0.0012 c 3.8500 - 3.8520 Middle Layer 0.1173 ± 0.0025 b 0.1150 - 0.1200 0.1304 ± 0.0005 b 0.1300 - 0.1310 0.6474 ± 0.0115 b 0.6400 - 0.6600 6.2673 ± 0.0011 b 6.2660 - 6.2680 Bottom Layer 0.1764 ± 0.0015 a 0.1750 - 0.1780 0.2803 ± 0.0005 a 0.2800 - 0.2810 1.6572 ± 0.0057 a 1.6500 - 1.6600 25.7660 ± 0.0020 a 25.7640 - 25.7680 L2 Surface Layer 0.0413 ± 0.0011 c 0.0400 - 0.0420 0.0510 ± 0.0010 c 0.0500 - 0.5200 0.0994 ± 0.0011 c 0.0980 - 0.1000 1.1440 ± 0.0010 c 1.1430 - 1.1450 Middle Layer 0.2030 ± 0.0030 b 0.2000 - 0.2060 0.1683 ± 0.0011 b 0.1670 - 0.1690 0.9871 ± 0.0057 b 0.9800 - 0.9900 12.3650 ± 0.1861 b 12.2570 - 12.5800 Bottom Layer 0.4040 ±0.0059 a 0.4000 - 0.4100 0.3053 ± 0.0011 a 0.3040 - 0.3060 1.8213 ± 0.0011 a 1.8200 - 1.8220 21.9261 ± 0.0011 a 21.9250 - 21.9270 L3 Surface Layer 0.0763 ± 0.0011 c 0.0963 ± 0.0011 c 0.3494 ± 0.0005 c BDL 0.0750 - 0.0770 0.0950 -0.09770 0.3490 - 0.3500 - Middle Layer 0.1754 ± 0.0015 b 0.3213 ± 0.0005 b 0.9600 ± 0.0010 b 5.0742 ± 0.0011 b 0.1740 - 0.1770 0.3210 - 0.3220 0.9590 - 0.9610 5.0733 - 5.0750 Bottom Layer 0.7051 ± 0.0055 a 0.6020 ± 0.0015 a 1.7511 ± 0.0011 a 8.4363 ± 0.0015 a 0.7010 - 0.7110 0.6000 - 0.6030 1.7500 - 1.7520 8.4350 - 8.4380 NB: Number of samples(n) = 3, BDL: Below Detection Level, mean values within the same column with different superscripts (a.b.c) are significantly different at P < 0.05 Table 5 Metal concentration (mg/L) (Mean ± SD) and their range (minimum-maximum) measured using AAS in three water layers (surface, middle, and bottom layer) collected from Koggala lagoon on 09 th May 2022 compared with three sampling sites. Site of the lagoon Heavy Metal Level (mg/L) Cu Cd Pb Cr Surface Layer 0.0764 ± 0.0015 a 0.0740 - 0.0770 0.0964 ± 0.0005 a 0.0950 - 0.0960 0.3833 ± 0.0115 a 0.3700 - 0.3900 3.8513 ± 0.0012 a 3.850 - 3.852 L1 0.0413 ± 0.0011 b 0.0400 - 0.0420 0.0510 ± 0.0010 b 0.0500 - 0.5200 0.0994 ± 0.0011 c 0.0980 - 0.1000 1.1440 ± 0.0010 b 1.1430 - 1.1450 L2 0.0763 ± 0.0011 c 0.0763 ± 0.0011 0.0953 ± 0.0011 a 0.0950 -0.09770 0.3500 ± 0.0005 b 0.3490 - 0.3500 BDL L3 Middle Layer 0.1173 ± 0.0025 c 0.1150 - 0.1200 0.1304 ± 0.0005 c 0.1300 - 0.1310 0.6472 ± 0.0115 c 0.6400 - 0.6600 6.2673 ± 0.0011 b 6.2660 - 6.2680 L1 0.2030 ± 0.0030 a 0.2000 - 0.2060 0.1683 ± 0.0011 b 0.1670 - 0.1690 0.9866 ± 0.0057 a 0.9800 - 0.9900 12.3650 ± 0.1861 a 12.2570 - 12.5800 L2 0.1764 ± 0.0015 b 0.3213 ± 0.0005 a 0.9600 ± 0.0010 b 5.0736 ± 0.0011 c L3 0.1740 - 0.1770 0.3210 - 0.3220 0.9590 - 0.9610 5.0733 - 5.0750 Bottom Layer 0.1766 ± 0.0015 c 0.1750 - 0.1780 0.2803 ± 0.0005 c 0.2800 - 0.2810 1.6600 ± 0.0057 c 1.6500 - 1.6600 25.7660 ± 0.0020 a 25.7640 - 25.7680 L1 0.4040 ±0.0059 b 0.4000 - 0.4100 0.3053 ± 0.0011 b 0.3040 - 0.3060 1.8214 ± 0.0011 a 1.8200 - 1.8220 21.9256 ± 0.0011 b 21.9250 - 21.9270 L2 0.7051 ± 0.0055 a 0.7010 - 0.7110 0.6024 ± 0.0015 a 0.6000 - 0.6030 1.7506 ± 0.0011 b 1.7500 - 1.7520 8.4363 ± 0.0015 b 8.4350 - 8.4380 L3 NB: Number of samples (n) = 3, BDL: Below Detection Level, mean values within the same column with different superscripts are significantly different at P < 0.05 Heavy metal levels in sediments The concentrations of heavy metals measured in sediment samples retrieved from three sampling sites are presented in Fig. 3. The Cu and Cd were detected at the respective ranges of 0.06 -0.085, and 0.025-0.041 (mg/gdry weight), while Pb and Cr were below the detection level. The heavy metals concentrations in sediment were found lower than those reported in water samples (Tables 4 and 6). The highest concentration of Cu (0.0796 ± 0.0083 mg/g dry weight) was detected in the L3 site less than the established standard level by FAO /WHO (100 mg/kg dry weight; FAO/WHO, 2001[54]. The highest Cd concentration (0.0413 ± 0.0006 mg/g dry weight) was measured at the L1 site and did not exceed the standard level. The obtained values were less than those reported in similar ecosystems around the world (e.g., Oualidia lagoon in Morocco [27] Segara Anakan lagoon, Indonesia [28], Sidi Moussa lagoon in Morocco [2], Songkhla lagoon in Thailand [29] and Kalametiya lagoon in Sri Lanka [30] Table 6 Metal concentration (g/g dry weight), (Mean ± SD) and their range (minimum-maximum) measured using AAS in sediment collected from Koggala lagoon on 09th May 2022 Site of the lagoon Heavy Metal Level (mg/g dry weight) Cu Cd Pb Cr Area near to the KEPZ 0.0684 ± 0.0006 c 0.0670 - 0.0680 0.0413 ± 0.0006 a 0.0410 -0.0420 BDL BDL Middle of the lagoon 0.0693 ± 0.0101 b 0.0600 - 0.0800 0.0370 ± 0.0057 b 0.0360 - 0.0370 BDL BDL Area near the Cultivation 0.0800 ± 0.0083 a 0.0700 - 0.0850 0.0263 ± 0.0011 c 0.0250 - 0.0270 BDL BDL NB: Number of samples (n) = 3, Mean values within the same column with different superscripts are significantly different at p < 0.05. Heavy metal levels in fish Four heavy metals were (Cu, Cd, Cr, and Pb) measured in the liver, skin, gill tissues, and flesh of E. suratensis living in three selected locations within the Koggala lagoon, Sri Lanka namely L1 (area near the KEPZ), L2 (middle of the lagoon) and L3 (area near to the cultivation site). In addition to the locations from which the fish samples were collected, the size of the fish (Small: 10.1 cm - 11.6 cm, medium: 14.1 cm -16.6 cm, and large fish: 19.6 cm – 23.2 cm) was also considered when measuring the heavy metal concentrations. The results of all the combinations are illustrated in Fig. 4, 5, and 6. Heavy metal concentrations of the selected tissues and organs of fish collected near the KEPZ (L1) Fig. 4 shows the heavy metal concentrations measured in selected tissues and organs of fish collected near the KEPZ (L1). As shown in the figure, the heavy metal concentrations in liver samples vary according to the metal type, and also according to the fish size, where we notice that medium-sized fish contained the highest significant Cu concentration (0.117 mg/g DW), and the lowest concentration (0.052 mg/g DW) is found in larger-sized fish. Cd content in liver samples was significantly higher in smaller-sized fish (0.107 mg/g DW) compared to the other samples. Interestingly Pb was only detected (0.197 mg/g DW) in larger-sized fish while Cr was found in detectable levels in medium-sized (0.031 mg/g DW) and larger (0.019 mg/g DW) fish. The Cu and Cd content in skin samples of smaller-sized fish were notably higher (0.244 mg/g DW and 0.021 mg/g DW respectively) when compared to the fish of other sizes. Moreover, medium-sized fish exhibited relatively higher Cu and Cd contents compared to the larger-sized ones. Cr and Pb concentrations occurrence were similar to the liver samples while both of them were no detectable in small fishes. Pb in the four tissue/organs of L1 fish samples was only detected in larger-sized fish. Similar distribution of Pb was found in gill and flesh samples as well as for Cr which was only detected in medium and larger-sized fish. The highest concentration of Cu was noticed in medium-sized fish (0.078 mg/g DW), while the lowest concentration was recorded in larger-sized fish (0.040 mg/g DW). Cd content was about 55 times higher in the smaller-sized fish (0.11 mg/g DW) compared to the lowest concentration, registered in medium-sized fish (0.02 mg/g DW). Regarding flesh samples, heavy metal concentrations mainly Cu were found significant in small-sized fish (0.821 mg/g DW). Larger-sized fish contained the highest level of Cd (0.041 mg /g DW). Among the different tissues/organs under investigation, flesh indicates a high concentration of Cu detected in small-sized fish compared to the liver, skin, and gill. Cd Value was more important in gill and liver of small sized fish as well. Pb concentrations were only shown for larger-sized fish where significant concentrations were found in skin and liver samples. Heavy metal concentrations of the selected tissues/organs of fish collected middle of the lagoon (L2) Samples collected from the middle of the Koggala lagoon (denoted L2) show almost similar values as L1. According to Fig. 5, Pb is detected also in small sized and large-sized fish while it is still not detected in medium-sized fish. Similarly to L1 findings, Cr is only measured in medium and large-sized fish samples. Metals concentrations vary according to the type of samples (tissue or organ) and fish sample size where Cu concentrations were found high in both liver (0.087 µg/g DW) and gill (0.071 mg/g DW) of medium-sized but also higher in skin (0.178 mg/g DW) and flesh (0.621 mg/g) DW small sized fish samples. The Cd content was consistently lower in all fish tissues including the flesh. Heavy metal concentrations of the selected tissues/organs of fish collected in the area near to cultivation site (L3) The concentrations of heavy metals measured in the fish samples collected from the vicinity of the cultivation site (L3) are shown in Fig. 6. The distribution of examined heavy metals is almost similar to L2 where in both L2 and L3, Pb is present in larger and smaller sized fish samples. The higher concentrations are recorded in flesh samples similar to the two other sampling stations. Cu was found high in the gill and liver of medium-sized samples (0.065 mg/g DW and 0.053 mg/g DW, respectively) and important as well in the skin and flesh (0.514 mg/g DW), of smaller-sized fish. Additionally, Cr was not detected in all tissues of small-sized fish, but a significantly higher level (0.02 mg/g DW) of Cr was found in the liver samples, flesh samples (0.080 mg/g DW) of larger-sized fish, and skin samples of medium-sized fish (0.051 mg/g DW). As for Cd levels, all the skins and flesh of different-sized fish showed lower concentrations, but the smaller-sized fish had the highest significant amount (0.019 mg/g DW, 0.021 mg/g DW respectively) compared to the other fish groups. Concerning the Cd levels in gill tissues' the larger-sized fish had the highest concentration (0.03 mg/g DW), while the smaller-sized fish had the lowest (0.02 mg/g DW). Accordingly, the distribution and accumulation mode of these metals is different according to the fish size and the organs and tissue type. Bioaccumulation transfer factor Bioaccumulation transfer factor (TF) measures the transportation of a substance between various environmental compartments, often involving the passage from soil or water to plants (animals) or from plants to animals [31,32]. TF was used in the field measurement of environmental science and toxicology, enabling the comprehension of the movement of pollutants or chemicals across distinct segments of ecosystems. Table 7 presents the bioaccumulation transfer factor calculated for various organs and tissues of three different sizes of fish samples from water and sediments retrieved from the same sampling sites. Although the exact source of metals in various body parts was unknown, the bioaccumulation transfer factor was calculated by assuming that particular metals had been accumulated solely from water and sediment. When the TF exceeds 1, this means that the heavy metal accumulation in fish tissues is (P < 0.05) greater than in water and sediment, thus, it means bioaccumulation. The TF of Cu from water is more significant in flesh of small sized fish where it indicates a value of 15.525 compared to TF from sediment value (8.598). Similarly for skin samples of medium-sized fish, Cu indicates important TF values, 9.900 and 5.500 from water and sediment respectively. Also, in flesh samples of medium-sized samples, the TF values of Cu from water and sediment were 6.750 and 3.738 respectively. Therefore, Cu shows more important TF from both water and sediment in the 4 types of organs and tissues of three sizes of fish except for Gill / Sediment in three investigated sizes, and for Liver / Sediment in small-sized fish samples. This finding highlights that the TF of Cu from water and sediment to the skin and flesh of small and medium-sized fish is more significant than the other metals while it is found also significant in the liver of large-sized fish samples. Accordingly, the fish samples experience bioaccumulation of Cu, first from water and then from the sediment of the lagoon. The calculation of bioaccumulation transfer factors from other compartments (water and sediment) of the studied area to the fish samples indicates that the TF of metals is more important from water to organs and tissues of fish samples than sediments. This result is consistent with Rashed [25] and Kalfakakour and Akrida-Demertzi [33] findings. For Pb, the transfer factor values exceed 1 only in Skin/Water (1.031) and (Liver/Water (2.143) samples. Other elements, Cd, Pb, and Cr show weak transfer factor values <1 from both water and sediment. These findings shed light on the possible health risks associated with the consumption of this lagoon fish mainly villagers rely on fish flesh for their daily consumption. Consequently, heavy metals can be ingested through the flesh. Table 7 Transfer factor (TF) of heavy metals in different tissues of E. suratensis collected from Koggala lagoon on 09th May 2022 Fish Tissue parts Transfer Factor Etroplus suratensis size category Small size (S) Medium size (M) Large size (L) Cu Cd Pb Cr Cu Cd Pb Cr Cu Cd Pb Cr Skin Skin / Water 3.956 0.400 NA NA 9.900 0.340 NA 0.017 1.800 0.220 1.031 0.045 Skin /Sediment 2.472 0.571 NA NA 5.500 0.486 NA AS 1.000 0.314 AS AS Gill Gill / Water 1.275 0.220 NA NA 1.775 0.260 NA 0.001<< 1.375 0.520 0.214 0.018 Gill / Sediment 0.708 0.314 NA NA 0.986 0.371 NA AS 0.764 0.743 AS AS Liver Liver / Water 1.100 0.220 NA NA 2.175 0.260 NA 0.001<< 8.500 0.380 2.143 0.017 Liver / Sediment 0.611 0.314 NA NA 1.205 0.371 NA AS 4.708 0.543 AS AS Flesh Flesh / Water 15.525 0.360 NA NA 6.750 0.320 NA 0.024 3.200 0.380 0.531 0.067 Flesh / Sediment 8.598 0.514 NA NA 3.738 0.457 NA AS 1.772 0.543 AS AS NB: AS = Accumulated from another Source, NA = Not Accumulate Discussion Bioaccumulation of heavy metals concentration in fish tissues In the current study, the bioavailable metal pollution in the lagoon is reflected by the accumulated levels of Pb, Cd, Cr, and Cu in several tissues of E. suratensis , a food fish in the Koggala lagoon. Fig. 4, 5, and 6 depict the copper (Cu) concentration levels in most of the analyzed tissues, which exceeded the maximum recommended level (0.1 µg/g DW) set by the FAO for Cu in three different size classes of fish at each sampling site. Additionally, the concentrations of cadmium (Cd), chromium (Cr), and lead (Pb) in the flesh tissues were found to be below the standard recommended limits of 1.0 µg/g DW for Cd, 2.0 µg/g DW for Cr, and 2.0 µg/g DW for Pb, as specified by the FAO. Therefore, E. suratensis exhibits high Cu levels, although Cu is not considered a toxic heavy metal. In this study, the overall accumulation of heavy metals in fish tissues was observed to be lower than the recommended values. The accumulation of heavy metals in fish tissue is primarily influenced by metal concentrations in the surrounding water; however, other environmental factors such as salinity, pH, hardness, and temperature have also been found to play a significant role in metal accumulation. Few studies have quantitatively analyzed patterns of metal bioaccumulation and trophic transfers in aquatic ecosystems, in contrast to many studies that have focused on the levels of heavy metals in fish [34,35]. Despite the significance of such studies in predicting the effects of metal pollution on aquatic organisms and the subsequent risk to human health, factors such as animals' body size (i.e., length and weight [36], feeding preferences, habitat preferences [37], ability to adapt to metals load and the physical and chemical characteristics of the aquatic environment [38] all impact the bioaccumulation of metals. The ecological needs and size of aquatic animals have also been found to influence their proclivity for metal accumulation. Therefore, it's vital to understand how the animal size and metal concentrations-both essential and non-essential- relate to each other. In related studies, elevated levels of certain heavy metals have been detected in Green chromide ( E. suratensis ) populations inhabiting Bolgoda Lake, Negambo lagoon, and the Chilaw lagoon area [39,40]. The total metal levels in muscle tissue (in ug/g wet weight) of the fish obtained from Bolgoda Lake exhibited a wide variation: lead, 0.02- 20.1, cadmium, 0.01 - 0.3, chromium, 0.01-0.2, copper, 0.1 - 10.1, and zinc, 2.5-10.4 (n=60) of the different metal levels detected in the edible muscle of the fish. Bolgoda Ganga exceeds the maximum limits of food for human consumption set by the European Union. A comparison of metal levels in the fish's muscles, gills, and liver tissues revealed that the liver tissue accumulated the most metals. The findings suggest that excessive intake of E. suratensis from Bolgoda lake may pose a health risk to consumers [39]. As well as, 12 sampling sites of the Negambo estuary presented a wide range of metal concentrations: Pb, not detected-5.7; Cu, not detected-2.5; Cd, not detected -2.1; Mn, not detected-0.9; Ni, not detected -7.4; Cr, 0.9-1.2; Hg, below the detection limit; and Zn, 40.4-180.4. (Koggala lagoon add). The concentration ranges of all eight elements (in mg/kg) in sediments were: Pb, 4.8-20.1; Cu, 5.3-24.2; Cd, 0.03-0.22; Mn, 121.9-792.5; Ni, 9.2-34.7; Cr, 19.2-73.5; Hg, 0.3-2.2; and Zn, 119.5-207.4. The ranges of the concentrations of metals in the edible muscle tissues were: Pb 0.01-0.08; Cu 0.02 -0.37; Cd 0.002-0.048; Mn 0.05-0.51; Ni 0.01-0.31; Cr 0.02 -0.28; Hg 0.03-0.33 and Zn 0.03 - 3.02 in E. suratensis (Indrajith et al ., 2010). The wide ranges of specific metal levels observed in fish collected from three locations in the lagoon may indicate that these fish were exposed to a variety of metals with different bioavailabilities within the lagoon through water and food sources. The analyzed fish were in various stages of development, including developing, developed, and spawning stages, and therefore the accumulated heavy metal concentrations varied depending on the fish's body size. This variation occurred because fish of different had varying organ sizes responsible for absorbing heavy metals. Specifically, fingerlings (small-sized fish) have organs that are still in the development stage [41]. In comparison to the developed and spawning stages of fish that have been studied, fingerling’s ability to absorb certain metals may differ. Their immature organs may not be able to accumulate toxic heavy metals like Cr and Pb, but they may accumulate higher levels of Cu and Cd in polluted areas compared to adult fish. Consequently, some references have indicated a positive relationship between heavy metal concentrations and fish body size. Since, in most species, smaller (younger) individuals grow faster than the older ones, the dilution of metal concentrations due to tissue growth should have a more significant effect on smaller individuals than on larger ones, leading to a positive slope in the metal concentration-body size relationship. Also, the accumulation of the metals may occur throughout the life of the organisms, and that higher concentrations in the larger (older) individuals reflect longer-term exposures [42,43]. Fish organs might exhibit diverse distributions of heavy metals due to their differing capacities to absorb and metabolize each element [44]. Most heavy metals do not accumulate in muscle tissue. The gills and skin are two organs that are immediately exposed to water. The quantities of trace elements in fish gills and skin are most likely proportional to the amounts of trace elements in lagoon water. The liver is fish's major metabolic organ, capable of effectively accumulating heavy metals and metalloids from the aquatic environment and through ingestion. The bulk of trace elements are concentrated in fish liver. Toxic metals were discovered mostly in the liver and gills [45]. Environment factors toward heavy metals concentration The tissues of fish from three different size classes collected from three different locations within the lagoon displayed variations of heavy metal accumulation levels. This can be related to two factors: firstly, human activities; and secondly, the variations occurring in the aquatic environment, such as the fish growth rate, metabolism, feeding pattern, and ecological requirements of a given fish species, upon which the accumulation of heavy metals in fish depends [46]. Due to rapid urbanization, population growth, and industrialization, emerging countries are currently facing several serious environmental problems such as air and water pollution and solid waste management. Early research has found an increase in the pollution of specific heavy metals in freshwater systems around the world, particularly in rivers. Pollution has primarily been created by industrial operations and industrial waste, most notably chemicals derived from textiles, oils, and rubber [47]. The heavy metals concentrations distribution among the three stations indicated that station L1 located near to Koggala Export Processing Zone (KEPZ) recorded significant concentrations compared to L2 and L3. Koggala lagoon is surrounded by a large area of agricultural cultivation and the highly industrialized Koggala Export Processing Zone (KEPZ). During heavy rains, the cultivation areas are prone to flooding, leading to the washout of all the agrochemicals and pesticides into the lagoon through the surrounding streams. Also, KEPZ discharges a significant quantity of wastewater, industrial chemicals, and dyes into the lagoon [16] which explain the significant concentration reported in L1 station located near to KEPZ. In addition, 12 factories are currently operating in the KEPZ, with most of them engaged in the apparel industry none of these industries are involved in the dyeing and washing processes, which are significant contributors to toxic wastewater. Furthermore, light industries such as plastics and rubber toys are also in production, and the majority of them use organic solvents that release toxic chemicals into the environment. It is also noted that up to date, the KEPZ has not implemented wastewater and sewage treatment, which means more chemicals can silt reach the water body contaminate different compartments of the lagoon, and pose a risk to aquatic life. In the meantime, industrial wastes such as plastics, pieces of fabric, and food are dumped onto marshy land bordering the lagoon and they have direct access to the lagoon, impaired by the region's frequent rainfall (Amarasekara et al. , 2016). This shed light on the urgent need for establishing strategies that aim at protecting the lagoon and conserving its natural resources while taking into consideration the other socio-economic factors mainly industries and agricultural activities surrounding the lagoon which must take part in the development of these strategies. Also, the tourism industry can be a source of pollution in the aquatic system [48] where in the Koggala lagoon, tourism activity has been involved in the variation of heavy metal levels in different locations of the lagoon. The L3 station showed values of heavy metals higher than those found in L2. L3 station is located in an area close to a cultivation site and surrounded by both paddy and non-paddy crops where the agrochemicals used in the nearby rice and tea plantations have direct access to the lagoon leading to a potential impact on marine organisms including crustaceans due to pesticide exposure. The used pesticides in Koggala were reported by Readmen et al. [49] to be belonging to some of the most known as toxic groups which have adverse impacts on the sensitive tropical aquatic ecosystems. Chemical analysis conducted elsewhere has indicated that pesticides used in Koggala have adverse impacts on the sensitive tropical marine ecosystem. Evidence of fish deaths in the lagoon and sighting of malformed fish indicate that these agrochemicals may be affecting certain organisms. These fish deaths have occurred during periods of increased agricultural activity [16]. When considering the L3, higher metal concentrations can be noted compared to the middle area of the lagoon. Specifically, chromium (Cr) concentration is notably higher at L3 than at the other locations. The measured levels of metals in the water samples collected from different locations in Koggala lagoon indicate relatively high concentrations of Pb, Cd, Cu, and Cr, exceeding maximum permissible limits set by the WHO (Cu: 1 mg / L, Cd: 0.05 mg / L, Pb: 0.05 mg / L and Cr: 0.05 mg / L) for water quality [50]. Chromium (Cr) concentration is particularly elevated at three locations within the Koggala lagoon (Table 5). Water quality toward heavy metals concentration The concentration of heavy metals is influenced by various water quality parameters including temperature, pH, DO, and salinity. In general, high temperatures induce the accumulation of heavy metals in sediment. Increased DO concentrations facilitate the dissolution of heavy metals in water while lower DO values tend to elevate heavy metal levels in sediment. A lower pH value reduces the solubility of heavy metals in water, leading to higher concentrations near the bottom [51]. Elevated water salinity can lead to the formation of organic matter clumps, expediting the deposition of heavy metals and reducing their concentration in the water (Li et al., 2013). Temperature and total suspended solids (TSS) exhibit a stronger association with and influence on heavy metal concentrations. During the observations, the water temperature measured was 30.1 0 C. Collecting data at sufficiently high water temperatures can result in lower heavy metal concentrations in the water [51]. This is due to the creation of heavy metal ions at high temperatures, which causes heavy metals to settle and enter the sediment. The concentration of heavy metals in the water can be affected by the pH of the water. The pH value obtained during observation ranged from 5.00 to 7.66, indicating that the lagoon water tends to be acidic. A low pH reduces the solubility of heavy metals in water, increasing heavy metal levels at the bottom of the water [52]. The concentration of heavy metals may vary depending on the sampling location in the same water body. Therefore, water and sediments samples collected from the three different locations in the lagoon can be contaminated by different volume of heavy metal levels originated from various activities practiced around and in the study, area including industrial, agricultural, fishing and tourism activities. Yan et al . [53] indicated that heavy metal concentrations tend to be higher in the soil and water of industrial and residential areas than in the soil and water of agricultural areas, which is in good accordance with our finding where the L1 samples retrieved near Koggala Export Processing Zone (KEPZ) recorded significant concentrations compared to L2 and L3. Conclusion Based on the results of the present study, it can be concluded that the measured concentrations of heavy metals in the three water layers are higher than those in the sediment. Concentrations of Cr, Pd, Cu, and Cd in the water from three sampling sites exceeded the maximum permissible limits set by globally recognized organizations for heavy metals. Additionally, the heavy metal concentration increases from the surface layer to the bottom layer of the water column. Cu was found to be the most abundant heavy metal in the sediment at all sampling sites in the Koggala lagoon. These findings suggest that the water in Koggala lagoon is contaminated and not suitable for human use in daily life. Significant differences in heavy metal concentrations were observed in the body tissues of fish across small, medium, and large size categories. Small fish accumulated only Cu and Cd, medium fish accumulated Cu, Cd, and Cr, while large size fish accumulated all the analyzed heavy metals. This study indicates that different body sizes of fish accumulate metals at varying concentrations in their tissues. However, the concentrations of Cd, Cr, and Pb in the flesh tissues were within the standard recommended limits for heavy metal levels as referred to by the FAO. On the other hand, Cu concentration in the flesh tissues exceeded the standard limits, although Cu is not considered a toxic heavy metal. Overall, the heavy metal levels in the fish are lower than the recommended values. However, it is important to note that in the future, considering the nature of bioaccumulation and biomagnification, the consumption of E. suratensis may pose human health hazards. More studies should be conducted in collaboration with medical researchers to determine any connection between heavy metal accumulations and an increase in the number of patients suffering from chronic kidney disease and cancer. Also, reducing the toxicity of wastewater as much as possible and releasing it under maximum permissible limits. Declarations Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author contributions The study conception and design were performed by Rajapakshage Dilani Nuwandhika Wijesinghe and Arukattu Patabadige Sajini Wathma Abeysooriya; Material preparation, data collection and analysis were performed by Arukattu Patabadige Sajini Wathma Abeysooriya, Rajapakshage Dilani Nuwandhika Wijesinghe, and Henegama Liyanage Kelum Sanjaya . The first draft of the manuscript was written by Arukattu Patabadige Sajini Wathma Abeysooriya and all authors commented on previous versions of the manuscript. Supervision was done by Rajapakshage Dilani Nuwandhika Wijesinghe, Epitawatthe Gedara Kiribandalage Yogya Chathurani Bandara and Henegama Liyanage Kelum Sanjaya . Review, interpretation of data, validation, and editing were performed by Rajapakshage Dilani Nuwandhika Wijesinghe, Prathibha Patabandige Sarath Kumara Patabandi, Mok Wen Jye and Nezha Mejjad and Yeong Yik Sung . All authors read and approved the final manuscript. Data availability All data generated or analyzed during this study are included in this published article. The researchers confirm that the study was carried out without any commercial or financial associations that could be interpreted as a possible conflict of interest. Ethics Approval Not applicable ( as already collected the dead fish from the fisherman's fresh catch). Consent to Participate Not applicable. Consent for Publication Not applicable. Competing Interests The authors have no relevant financial or non-financial interests to disclose. References Mejjad, N., Laissaoui, A., Fekri, A., Benmhammed, A., El Hammoumi, O., & Cherif, E. K. (2020, March). Does human activities growth lead to biodiversity loss in the Moroccan coastal lagoons? A diagnostic comparison study. 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B. (2022). The coastal tourism industry in the Mediterranean: A critical review of the socio-economic and environmental pressures & impacts. Tourism Management Perspectives , 44 , 101007. https://doi.org/10.1016/j.tmp.2022.101007 Readman, J. W., Kwong, L. L. W., Mee, L. D., Bartocci, J., Nilvé, G., Rodriguez-Solano, J. A., & Gonzalez-Farias, F. (1992). Persistent organophosphorus pesticides in tropical marine environments. Marine Pollution Bulletin , 24 (8), 398-402. https://doi.org/10.1016/0025-326X(92)90500-6 Mahmud, H. N. M. E., Huq, A. O., & binti Yahya, R. (2016). The removal of heavy metal ions from wastewater/aqueous solution using polypyrrole-based adsorbents: a review. Rsc Advances , 6 (18), 14778-14791. https://doi.org/10.1039/C5RA24358K Li, H., Shi, A., Li, M., & Zhang, X. (2013). Effect of pH, temperature, dissolved oxygen, and flow rate of overlying water on heavy metals release from storm sewer sediments. 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L2, and L3) sites in Koggala lagoon, Sri Lanka on 09\u003csup\u003eth\u003c/sup\u003e\u0026nbsp; May 2022. Error bars represent the standard error of three replicates; * indicates significant differences (P \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4587800/v1/55be9997b5442791ddb99924.png"},{"id":59548032,"identity":"cf80c4a6-e36a-4387-919e-813bd5d219c5","added_by":"auto","created_at":"2024-07-03 05:38:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":354246,"visible":true,"origin":"","legend":"\u003cp\u003eMetal concentration (g / g DW) in liver tissue of three size classes of \u003cem\u003eE. suratensis \u003c/em\u003ecaptured from L1 in Koggala lagoon on 09\u003csup\u003eth\u003c/sup\u003e of May 2022. Error bars represent the standard error of three replicates; different alphabetic indicate significant differences (P\u0026lt;0.05)\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4587800/v1/2eecf3cc62647dc2f18d0a1f.png"},{"id":59548034,"identity":"fcf4333d-f59c-46e9-bc2e-877f3576577a","added_by":"auto","created_at":"2024-07-03 05:38:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":375093,"visible":true,"origin":"","legend":"\u003cp\u003eMetal concentration (g/g dry weight) in liver tissue of three size classes of \u003cem\u003eE. suratensis \u003c/em\u003ecaptured from L2 in Koggala lagoon on 09th May 2022 Error bars represent the standard error of three replicates; different alphabetic indicate significant differences (P\u0026lt;0.05)\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4587800/v1/d205a40ccc3ba6f8eeae65c2.png"},{"id":59548035,"identity":"6506f567-f7bb-41a8-8794-9a07fd7a349a","added_by":"auto","created_at":"2024-07-03 05:38:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":348894,"visible":true,"origin":"","legend":"\u003cp\u003eMetal concentration (g/g dry weight) in liver tissue of three size classes of \u003cem\u003eE. suratensis \u003c/em\u003ecaptured from L3 in Koggala lagoon on 09th May 2022 Error bars represent the standard error of three replicates; different alphabetic indicate significant differences (P\u0026lt;0.05)\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4587800/v1/2fed4173909d6113a5ecc5c2.png"},{"id":60158766,"identity":"7baee958-57e6-4908-9702-8cf5834c76ab","added_by":"auto","created_at":"2024-07-12 12:38:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2794287,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4587800/v1/a33bb186-c73a-4b26-b014-983b87ea1d39.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of Heavy Metal Pollution and Human Health Risks Associated with Etroplus suratensis (Green Chromide) in Koggala Lagoon, Sri Lanka","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLagoons are among the most sensitive and vulnerable aquatic ecosystems to heavy metal pollution. These natural environments provide multiple ecosystem services to humans, hence they are exploited extensively where many human activities such as aquaculture, fishing, coastal tourism, and agriculture are practiced in and around lagoon systems [1-6]. The unsustainable exploitation of lagoons\u0026apos; ecosystems threatens their viability and endangers human health. In lagoons, contaminants continuously accumulated through food chains can potentially affect humans and other living organisms at different trophic levels. The bioaccumulation depends on the concentration of heavy metals in plants, water, and sediments [7-9]. Industrialized urban areas enhance the entry of pollutants to coastal areas, such as lagoons, posing a threat of ecosystem degradation. The heavy metals assimilated by fish will accumulate at various concentrations in various tissues or organs [10-12]. As fish have become the staple food of coastal communities, the heavy metal bioaccumulation in fish has become an alarming threat, especially to poor coastal communities [13-14]. The uptake of heavy metals by fish will depend on both biotic and abiotic factors though there are various mechanisms to excrete some of the assimilated metals [15]. However, the species, location, and seasons may determine the bioavailability of heavy metals in fish; therefore, scientific studies in these areas are vital. The Koggala lagoon covers a hydro catchment area of approximately 55 km\u003csup\u003e2\u003c/sup\u003e and features various land use activities, primarily paddy farming and small-scale fisheries [16]. Fishing in Koggala lagoon is a partially modernized income-generating activity, mainly carried out through small-scale subsistence operations. The fish production in this coastal lagoon supports the livelihood of local (poor) farmers living around Koggala lagoon while providing a source of affordable, high\u0026ndash;quality protein supplements. Koggala lagoon hosts a variety of finfish and shellfish species, including \u003cem\u003eE. suratensis\u003c/em\u003e, \u003cem\u003eOreochromis niloticus, Oreochromis mossambicus, Ctenopharyngodon Idella, Hypophthalmichthys molitrix, Cyprinus carpio, Mugil cephalus, Penaeus indicus, Penaeus monodon, Scylla serrata,\u003c/em\u003e and \u003cem\u003ePortunus pelagicus, \u003c/em\u003eamong others [17].\u003c/p\u003e\n\n\u003cp\u003eThe lagoon is also known as one of the main tourist spots on the southern coast of Sri Lanka, boasting rich biodiversity and ecosystems [16]. Consequently, there are several tourist hotels, resorts, and boat safari businesses located around the lagoon area. Due to various land use practices and development activities, the lagoons are threatened by both point and non-point source pollution. The nearest area of Koggala lagoon consists of non-paddy crops, paddy crops, tourist hotels (resorts), and the Koggala Export Processing Zone (KEPZ). Agrochemicals used in the nearby rice and tea plantations have direct access to the lagoon. Currently, 12 factories are operating in the KEPZ, with the majority of them in the apparel industry. However, none of these industries are involved in the dyeing and washing processes that could significantly contribute to producing toxic wastewater. Additionally, other industries, such as plastics and rubber toys are also in production, with most of them using organic solvents that release toxic chemicals into the environment [18]. Up to this point, the KEPZ has neglected wastewater and sewage treatment, while industrial wastes such as plastics, fabric scraps, and food are dumped onto marshy land bordering the lagoon which augmented the problem, particularly during the rainy seasons with frequent rainfall [16].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eE. suratensis\u003c/em\u003e is one of the most commonly (popular) consumed fish species by communities residing near the Koggala lagoon, especially among low-income families. Compared to other brackish water fish species, \u003cem\u003eE. suratensis\u003c/em\u003e exhibits rapid growth and attains maturity in just a few months. Since many villagers consume fish in at least one meal per day, this study aimed to evaluate the concentration of Cd, Cu, Pb, and Cr in the tissues of the \u003cem\u003eE. suratensis\u003c/em\u003e fish, including gills, flesh, skin, and liver, all collected from the Koggala lagoon, Sri Lanka. Subsequently, the results were compared across different body sizes (small, medium, and large) and against the permissible limits established by the European Commission (EC), the United States Food and Drug Administration (USFDA), Food and Agriculture Organization (FAO), and the World Health Organization (WHO) to determine heavy metal contamination. Furthermore, the transfer factor of heavy metal also was used to evaluate the lagoon environment. \u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eSite selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe selected the Koggala lagoon as a case study to assess the heavy metals\u0026apos; bioavailability. The lagoon is located in the Galle District of Southern Sri Lanka and comprises eight small islands with diverse ecosystems surrounding it. The Koggala lagoon is 4.8 km long, 2 km wide, and has a surface area of approximately 7.27 km\u003csup\u003e2\u003c/sup\u003e. Water depths within the lagoon range from 1 m to 3.7 m [16]. Koggala lagoon primarily relies on rainwater for its freshwater supply, with several small streams connected to it, though its main source is the Koggala Oya. Three sampling sites were selected in Koggala lagoon based on the basic information from villagers, fishermen, and field observations. They were a location near the Koggala Export Processing Zone (KEPZ), the middle of the lagoon, and a area near the cultivation area.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;1\u003c/strong\u003e GPS location of sampling stations at Koggala lagoon\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"545\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Location\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003eArea near the KEPZ\u0026nbsp;(L1) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;5\u0026deg; 59\u0026apos; 39.4836\u0026apos;\u0026apos; N and 80\u0026deg; 19\u0026apos; 45.5808\u0026apos;\u0026apos; E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003eMiddle of the lagoon (L2) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 6\u0026deg; 0\u0026apos; 19.3032\u0026apos;\u0026apos; N and 80\u0026deg; 19\u0026apos; 35.0148\u0026apos;\u0026apos; E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\"\u003e\n \u003cp\u003eArea near the cultivation site (L3) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;5\u0026deg; 59\u0026apos; 51.774\u0026apos;\u0026apos; N and 80\u0026deg; 20\u0026apos; 21.3576\u0026apos;\u0026apos; E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSamples collection (water, sediment, and fish)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWater, sediment, and fish samples were collected from the sampling sites. The sediment samples were collected in triplicate at each sampling site using Kajak core sampler. These samples were then transferred to polythene bags, that had been thoroughly rinsed with Dil. HNO\u003csub\u003e3\u003c/sub\u003e acid and deionized water. As for the water samples, triplicate samples were collected from three layers of the water column at each sampling site including the surface, middle layer, and bottom layers. One liter (1 L) of water sample was collected from each of these layers at all three locations using the Ruttner sampler. All water samples were collected in polypropylene bottles that had been thoroughly rinsed with deionized water and Dil. (HNO\u003csub\u003e3\u003c/sub\u003e) to avoid any potential contaminants. Prior to sampling, the sampling bottles were also rinsed with lagoon water. A total of thirty- six fish were collected from the lagoon\u0026apos;s fresh catch by fishermen early in the morning. These thirty-six fish were grouped based on their body size; small (SF):10.1 cm - 11.6 cm, medium (MF):14.1 cm -16.6 cm, and large (LF) fish: 19.6 cm \u0026ndash; 23.2 cm. From each selected site, 12 fish were collected for the analysis ensuring representation across the available size ranges. Each fish was washed with distilled water before being packed in pre-clean polythene bags. The fish were then carefully preserved with ice in a box to minimize tissue degradation and maintain moisture content during transportation [19]. Finally, fish were transported to the general laboratory, Department of Fisheries and Aquaculture Faculty of Fisheries and Marine Sciences and Technology at the University of Ruhuna, Matara, Sri Lanka.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAnalysis of water quality\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eWater temperature (\u003csup\u003eo\u003c/sup\u003eC), dissolved oxygen (mg/L), salinity (ppt), pH, conductivity (mS/cm), and total dissolved solid (mg/L) were measured by using a multi-probe (YSI 556 MPS, Japan). Chlorophyll -a in water was measured in accordance with ESS method 150.1 [20]. The total suspended solid (TSS) in water was measured according to the Standard Methods, 2540D and EPA (1983) Method 160.2 (Residue, non-filterable). A well-mixed, measured volume of a water sample is filtered through a pre-weighed glass fiber filter. The filter is heated to constant mass at 104 \u0026plusmn; 1\u0026ordm;C and then weighed. The mass increase divided by the water volume filtered is equal to the TSS in mg/L.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e (Mean \u0026plusmn; SD) of Total length, Standard length, Head length, Total weight and their range (minimum and maximum) and percentage of maturity stage of \u003cem\u003eE. suratensis\u0026nbsp;\u003c/em\u003ecaptured from three different locations of Koggala lagoon on 09\u003csup\u003eth\u003c/sup\u003e May 2022.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"976\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.55327868852459%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation of\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ethe lagoon\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.528688524590164%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eFish size range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.118852459016393%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal length (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.889344262295082%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eHead length (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.938524590163935%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard length\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.348360655737705%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal weight\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.622950819672134%\" colspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage of maturity stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.028846153846153%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.990384615384617%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDM*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.58653846153846%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDF*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.182692307692308%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.55327868852459%\" rowspan=\"6\"\u003e\n \u003cp\u003eL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.528688524590164%\" rowspan=\"2\"\u003e\n \u003cp\u003eSF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.118852459016393%\" rowspan=\"2\"\u003e\n \u003cp\u003e9.8 \u0026plusmn; 0.4\u003c/p\u003e\n \u003cp\u003e9.2 \u0026ndash; 10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.889344262295082%\" rowspan=\"2\"\u003e\n \u003cp\u003e3.2 \u0026plusmn; 0.2\u003c/p\u003e\n \u003cp\u003e2.8 - 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.938524590163935%\" rowspan=\"2\"\u003e\n \u003cp\u003e8.4 \u0026plusmn; 0.5\u003c/p\u003e\n \u003cp\u003e7.6 \u0026ndash; 9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.348360655737705%\" rowspan=\"2\"\u003e\n \u003cp\u003e20.0 \u0026plusmn; 1.8\u003c/p\u003e\n \u003cp\u003e16.5 - 22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.684426229508197%\" valign=\"bottom\"\u003e\n \u003cp\u003e41.66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.094262295081966%\" valign=\"top\"\u003e\n \u003cp\u003e58.34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.991803278688525%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.069672131147541%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.045081967213115%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.737704918032787%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.028846153846153%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.990384615384617%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.58653846153846%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.182692307692308%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.652920962199312%\" rowspan=\"2\"\u003e\n \u003cp\u003eMF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.194730813287514%\" rowspan=\"2\"\u003e\n \u003cp\u003e14.1 \u0026plusmn; 1.2\u003c/p\u003e\n \u003cp\u003e12.3- 16.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.82016036655212%\" rowspan=\"2\"\u003e\n \u003cp\u003e4.7 \u0026plusmn; 0.3\u003c/p\u003e\n \u003cp\u003e4.0 - 5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" rowspan=\"2\"\u003e\n \u003cp\u003e12.0 \u0026plusmn; 1.4\u003c/p\u003e\n \u003cp\u003e10.1 - 14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.56930126002291%\" rowspan=\"2\"\u003e\n \u003cp\u003e79.2 \u0026plusmn; 8.1\u003c/p\u003e\n \u003cp\u003e68.6 - 90.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.59106529209622%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.049255441008018%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.934707903780069%\" valign=\"bottom\"\u003e\n \u003cp\u003e33.34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.903780068728523%\" valign=\"bottom\"\u003e\n \u003cp\u003e66.66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.758304696449026%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.414662084765178%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.028846153846153%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.990384615384617%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.58653846153846%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.182692307692308%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.652920962199312%\" rowspan=\"2\"\u003e\n \u003cp\u003eLF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.194730813287514%\" rowspan=\"2\"\u003e\n \u003cp\u003e20.5 \u0026plusmn; 1.4\u003c/p\u003e\n \u003cp\u003e18.6 \u0026ndash; 22.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.82016036655212%\" rowspan=\"2\"\u003e\n \u003cp\u003e6.1 \u0026plusmn; 0.3\u003c/p\u003e\n \u003cp\u003e5.6 - 6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" rowspan=\"2\"\u003e\n \u003cp\u003e18.3 \u0026plusmn; 1.6\u003c/p\u003e\n \u003cp\u003e16.2 - 20.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.56930126002291%\" rowspan=\"2\"\u003e\n \u003cp\u003e148.4 \u0026plusmn; 15.3\u003c/p\u003e\n \u003cp\u003e130.0 - 168.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.59106529209622%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.049255441008018%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.934707903780069%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.903780068728523%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.758304696449026%\" valign=\"top\"\u003e\n \u003cp\u003e50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.414662084765178%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e50%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.028846153846153%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.990384615384617%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.58653846153846%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.182692307692308%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.55327868852459%\" rowspan=\"6\"\u003e\n \u003cp\u003eL2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.528688524590164%\" rowspan=\"2\"\u003e\n \u003cp\u003eSF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.118852459016393%\" rowspan=\"2\"\u003e\n \u003cp\u003e10.8 \u0026plusmn; 0.5\u003c/p\u003e\n \u003cp\u003e10.1 - 11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.889344262295082%\" rowspan=\"2\"\u003e\n \u003cp\u003e3.5 \u0026plusmn; 0.2\u003c/p\u003e\n \u003cp\u003e3.2 - 3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.938524590163935%\" rowspan=\"2\"\u003e\n \u003cp\u003e9.4 \u0026plusmn; 0.5\u003c/p\u003e\n \u003cp\u003e8.6 - 10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.348360655737705%\" rowspan=\"2\"\u003e\n \u003cp\u003e21.7 \u0026plusmn; 2.7\u003c/p\u003e\n \u003cp\u003e16.5 - 25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.684426229508197%\" valign=\"bottom\"\u003e\n \u003cp\u003e41.66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.094262295081966%\" valign=\"top\"\u003e\n \u003cp\u003e58.34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.991803278688525%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.069672131147541%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.045081967213115%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.737704918032787%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.028846153846153%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.990384615384617%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.58653846153846%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.182692307692308%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.652920962199312%\" rowspan=\"2\"\u003e\n \u003cp\u003eMF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.194730813287514%\" rowspan=\"2\"\u003e\n \u003cp\u003e15.6 \u0026plusmn; 0. 8\u003c/p\u003e\n \u003cp\u003e14.1 - 16.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.82016036655212%\" rowspan=\"2\"\u003e\n \u003cp\u003e4.7 \u0026plusmn; 0.4\u003c/p\u003e\n \u003cp\u003e4.0 - 5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" rowspan=\"2\"\u003e\n \u003cp\u003e13.5 \u0026plusmn; 0.9\u003c/p\u003e\n \u003cp\u003e12.0 - 14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.56930126002291%\" rowspan=\"2\"\u003e\n \u003cp\u003e85.7 \u0026plusmn; 7.8\u003c/p\u003e\n \u003cp\u003e70.2 - 96.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.59106529209622%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.049255441008018%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.934707903780069%\" valign=\"top\"\u003e\n \u003cp\u003e50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.903780068728523%\" valign=\"bottom\"\u003e\n \u003cp\u003e50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.758304696449026%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.414662084765178%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.028846153846153%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.990384615384617%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.58653846153846%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.182692307692308%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.652920962199312%\" rowspan=\"2\"\u003e\n \u003cp\u003eLF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.194730813287514%\" rowspan=\"2\"\u003e\n \u003cp\u003e21.7 \u0026plusmn; 1.3\u003c/p\u003e\n \u003cp\u003e19.6 - 23.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.82016036655212%\" rowspan=\"2\"\u003e\n \u003cp\u003e6.2 \u0026plusmn; 0.4\u003c/p\u003e\n \u003cp\u003e5.6 - 6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" rowspan=\"2\"\u003e\n \u003cp\u003e18.6 \u0026plusmn; 1.2\u003c/p\u003e\n \u003cp\u003e16.8 - 19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.56930126002291%\" rowspan=\"2\"\u003e\n \u003cp\u003e154.6 \u0026plusmn; 13.3\u003c/p\u003e\n \u003cp\u003e133.5 - 168.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.59106529209622%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.049255441008018%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.934707903780069%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.903780068728523%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.758304696449026%\" valign=\"top\"\u003e\n \u003cp\u003e66.66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.414662084765178%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e33.34%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.028846153846153%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.990384615384617%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.58653846153846%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.182692307692308%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.55327868852459%\" rowspan=\"6\"\u003e\n \u003cp\u003eL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.528688524590164%\" rowspan=\"2\"\u003e\n \u003cp\u003eSF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.118852459016393%\" rowspan=\"2\"\u003e\n \u003cp\u003e9.9 \u0026plusmn; 0.4\u003c/p\u003e\n \u003cp\u003e9.2 \u0026ndash; 10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.889344262295082%\" rowspan=\"2\"\u003e\n \u003cp\u003e3.4 \u0026plusmn; 0.2\u003c/p\u003e\n \u003cp\u003e3.2 - 3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.938524590163935%\" rowspan=\"2\"\u003e\n \u003cp\u003e9.2 \u0026plusmn; 0.4\u003c/p\u003e\n \u003cp\u003e8.6 - 10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.348360655737705%\" rowspan=\"2\"\u003e\n \u003cp\u003e20.8 \u0026plusmn; 2.4\u003c/p\u003e\n \u003cp\u003e16.5 - 25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.684426229508197%\" valign=\"bottom\"\u003e\n \u003cp\u003e75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.094262295081966%\" valign=\"top\"\u003e\n \u003cp\u003e25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.991803278688525%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.069672131147541%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.045081967213115%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.737704918032787%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.028846153846153%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.990384615384617%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.58653846153846%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.182692307692308%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.652920962199312%\" rowspan=\"2\"\u003e\n \u003cp\u003eMF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.194730813287514%\" rowspan=\"2\"\u003e\n \u003cp\u003e15.4 \u0026plusmn; 0. 6\u003c/p\u003e\n \u003cp\u003e14.6 - 16.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.82016036655212%\" rowspan=\"2\"\u003e\n \u003cp\u003e4.7 \u0026plusmn; 0.3\u003c/p\u003e\n \u003cp\u003e4.0 - 5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" rowspan=\"2\"\u003e\n \u003cp\u003e13.4 \u0026plusmn; 0.8\u003c/p\u003e\n \u003cp\u003e12.0 - 14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.56930126002291%\" rowspan=\"2\"\u003e\n \u003cp\u003e84.7 \u0026plusmn; 6.8\u003c/p\u003e\n \u003cp\u003e70.2 - 91.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.59106529209622%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.049255441008018%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.934707903780069%\" valign=\"top\"\u003e\n \u003cp\u003e33.34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.903780068728523%\" valign=\"bottom\"\u003e\n \u003cp\u003e66.66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.758304696449026%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.414662084765178%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.028846153846153%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.990384615384617%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.58653846153846%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.182692307692308%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.652920962199312%\" rowspan=\"2\"\u003e\n \u003cp\u003eLF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.194730813287514%\" rowspan=\"2\"\u003e\n \u003cp\u003e22.1 \u0026plusmn; 1.9\u003c/p\u003e\n \u003cp\u003e19.6 - 25.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.82016036655212%\" rowspan=\"2\"\u003e\n \u003cp\u003e6.3 \u0026plusmn; 0.4\u003c/p\u003e\n \u003cp\u003e5.6 - 6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" rowspan=\"2\"\u003e\n \u003cp\u003e18.6 \u0026plusmn; 1.1\u003c/p\u003e\n \u003cp\u003e16.8 - 19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.56930126002291%\" rowspan=\"2\"\u003e\n \u003cp\u003e152.8 \u0026plusmn; 13.8\u003c/p\u003e\n \u003cp\u003e130.0 - 170.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.59106529209622%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.049255441008018%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.934707903780069%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.903780068728523%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.758304696449026%\" valign=\"top\"\u003e\n \u003cp\u003e58.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.414662084765178%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e41.67%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.028846153846153%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.990384615384617%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.58653846153846%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.182692307692308%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" colspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNB: number of fish (n) = 12, DM - Developing Male, DF - Developing Female, DM* - Developed Male, DF* - Developed Female, SM - Spawning Male and SF - Spawning Female\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eSample preparation and acid digestion of samples (sediment, water, and fish)\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eOnce in the laboratory, all collected samples, sediments, water, and fish have undergone physical preparation and acid digestion according to Shumo et al. [21], Kwaansa-Ansahet al. [22], and Mendil et al. [23] respectively. The sample preparation and acid digestion of different samples is detailed in the schematic presentation below (Fig. 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis using atomic absorption spectrophotometer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDigested fish samples, sediments, and filtered water samples were prepared for atomic absorption spectroscopy (Varian 220) to analyze four heavy metals; Lead (Pb), chromium (Cr), Cadmium (Cd), and copper (Cu). Standard solution of Pb, Cd, Cu, and Cr at 1000 ppm was prepared to create a series of ionic samples at nine concentrations; 0.05, 0.1, 0.2, 0.4, 0.8, 1.6, 3, 5 and 10 ppm. A standard curve was drawn using the absorbance levels of these known concentrations and calculated the heavy metal concentration of each sample. Readings were taken for all the triplicate samples [24].\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTransfer factor\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe transfer factor of fish tissues in the aquatic ecosystem was determined using the methodology described by Rashed et al. [25]. This method was used to calculate the levels of heavy metals in fish tissue in relation to sediment and water\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"560\" height=\"76\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using IBM SPPS software package. Initially, the data of all heavy metal concentrations of relevant body sizes were checked for normality. A one-sample t-test was used to determine whether there were significant differences in metal concentrations among fish tissues, water, and sediment samples. Additionally, these samples were compared with the standard recommended heavy metal limits. To compare the differences in heavy metal concentrations in water, sediment, and different body parts of fish at each sampling site, a one-way ANOVA (at a 95% confidence level) with a post-hoc test (Turkey\u0026rsquo;s test) was conducted. Metal concentration in gills, liver, muscle, skin, water, and sediment samples were compared using Turkey\u0026rsquo;s multiple comparisons of means. The SPPS software was also used to compute descriptive statistics for the data.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e\u003cstrong\u003eWater quality parameters\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe water samples were collected from three locations in the lagoon, namely, an area near the KEPZ (L1), the middle of the lagoon (L2), and the area close to the cultivation site (L3). These samples were analyzed for water-selected quality parameters, including temperature (\u0026deg;C), DO (mg/L), salinity (ppt), pH, conductivity (mS/cm), Total suspended solids - TSS (ppm), Total dissolved solid - TDS (mg/L) and Chlorophyll-a (mg/L) ( Table 3). The general water quality parameters, such as temperature and pH at all the locations were not significantly different and remained within the range of 28-29 \u0026deg;C and 5.5-6.0 respectively. However, the dissolved oxygen level (DO) at the target locations showed significant differences. The highest value (7.21 mg/L) was recorded at L1 while the lowest value (2.80 mg/L) was detected at L3. In terms of salinity, both L1 and L3 exhibited no significant difference, with values ranging approximately from 6.7 to 6.8. In contrast, the salinity level at L2 was significantly lower (3.02 ppt) compared to those at the other two sites. The conductivity values followed a similar pattern, as L1 and L3 showed no significant difference (12.09 mS/cm and 12.82 mS/cm, respectively) while the lowest significant value (6.14 mS/cm) was recorded at L2. The highest amount of total suspended solid was detected at L2 (400.31 ppm), whereas the lowest (288.54 ppm) was found at L1, and these TSS values were significantly different from each other. Regarding the total dissolved solids (TDS), the values at L1 (77.92 mg/L) and L3 (76.70 mg/L) locations were not significantly different from each other. However, the lowest TDS value was recorded at L2 (37.03 mg/L). Finally, the Chlorophyll-a content was also measured, and the results indicated significant differences among all locations. The highest Chlorophyll-a content was recorded at L3 (0.15 mg/L) whereas the lowest was recorded at L2 (0.10 mg/L).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Water quality parameters (Mean \u0026plusmn; SD) and the range (minimum-maximum) from Koggala lagoon on 09\u003csup\u003eth\u003c/sup\u003e May 2022\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"973\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.221993833504625%\" colspan=\"\" rowspan=\"2\" style=\"width: 2.3086%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite of the Koggala lagoon\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"91.26413155190133%\" colspan=\"16\" style=\"width: 25.0158%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWater Quality Parameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.771300448430493%\" colspan=\"2\" style=\"width: 3.17%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTemperature\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003csup\u003e\u0026deg;\u003c/sup\u003eC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.31390134529148%\" colspan=\"2\" style=\"width: 2.4809%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDO\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mg/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.547085201793722%\" colspan=\"2\" style=\"width: 2.791%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDO %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.09865470852018%\" style=\"width: 2.8255%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSalinity (ppt)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.538116591928251%\" colspan=\"\" style=\"width: 2.5154%;\"\u003e\n \u003cp\u003e\u003cstrong\u003epH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.547085201793722%\" colspan=\"2\" style=\"width: 3.1011%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConductivity (mS/cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.089686098654708%\" colspan=\"3\" style=\"width: 2.5498%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTSS\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(ppm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.32286995515695%\" colspan=\"2\" style=\"width: 2.6876%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTDS\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mg/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.210762331838565%\" colspan=\"2\" style=\"width: 2.8599%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChlorophyll - a (mg/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.776180698151951%\" style=\"width: 1.8262%;\"\u003e\n \u003cp\u003eL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.780287474332649%\" colspan=\"2\" style=\"width: 3.1011%;\"\u003e\n \u003cp\u003e29.01 \u0026plusmn; 0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e29.00 - 29.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.164271047227926%\" colspan=\"2\" style=\"width: 2.7566%;\"\u003e\n \u003cp\u003e7.21 \u0026plusmn; 0.04\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e7.23 - 7.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.08829568788501%\" colspan=\"2\" style=\"width: 3.1011%;\"\u003e\n \u003cp\u003e95.62 \u0026plusmn; 0.005\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e95.22 - 96.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.164271047227926%\" style=\"width: 2.8255%;\"\u003e\n \u003cp\u003e6.80 \u0026plusmn; 0.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e6.71 - 6.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.240246406570842%\" style=\"width: 2.2742%;\"\u003e\n \u003cp\u003e5.53 \u0026plusmn; 0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e5.51 - 5.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.856262833675565%\" colspan=\"2\" style=\"width: 2.9288%;\"\u003e\n \u003cp\u003e12.09 \u0026plusmn; 0.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e12.88 - 12.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.293634496919918%\" colspan=\"3\" style=\"width: 3.2734%;\"\u003e\n \u003cp\u003e288.54 \u0026plusmn; 1.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e287.51 - 289.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.369609856262834%\" colspan=\"2\" style=\"width: 2.791%;\"\u003e\n \u003cp\u003e77.92 \u0026plusmn; 0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e77.70 - 78.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.26694045174538%\" style=\"width: 2.6876%;\"\u003e\n \u003cp\u003e0.13 \u0026plusmn; 0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.11 - 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.776180698151951%\" style=\"width: 1.8262%;\"\u003e\n \u003cp\u003eL2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.780287474332649%\" colspan=\"2\" style=\"width: 3.1011%;\"\u003e\n \u003cp\u003e28.92 \u0026plusmn; 0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e28.91 - 28.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.164271047227926%\" colspan=\"2\" style=\"width: 2.7566%;\"\u003e\n \u003cp\u003e4.84 \u0026plusmn; 0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e4.78 - 4.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.08829568788501%\" colspan=\"2\" style=\"width: 3.1011%;\"\u003e\n \u003cp\u003e64.23 \u0026plusmn; 0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e63.42 - 64.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.164271047227926%\" style=\"width: 2.8255%;\"\u003e\n \u003cp\u003e3.02 \u0026plusmn; 0.05\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e2.94 - 3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.240246406570842%\" style=\"width: 2.2742%;\"\u003e\n \u003cp\u003e5.95 \u0026plusmn; 0.06\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e5.88 - 6.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.856262833675565%\" colspan=\"2\" style=\"width: 2.9288%;\"\u003e\n \u003cp\u003e6.14 \u0026plusmn; 0.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e6.11 - 6.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.293634496919918%\" colspan=\"3\" style=\"width: 3.2734%;\"\u003e\n \u003cp\u003e400.31 \u0026plusmn; 2.55\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e397.48 - 402.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.369609856262834%\" colspan=\"2\" style=\"width: 2.791%;\"\u003e\n \u003cp\u003e37.03\u0026plusmn; 0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e36.89 - 37.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.26694045174538%\" style=\"width: 2.6876%;\"\u003e\n \u003cp\u003e0.10 \u0026plusmn; 0.10\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.09 - 0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.776180698151951%\" style=\"width: 1.8262%;\"\u003e\n \u003cp\u003eL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.780287474332649%\" colspan=\"2\" style=\"width: 3.1011%;\"\u003e\n \u003cp\u003e29.31 \u0026plusmn; 0.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e29.30 - 29.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.164271047227926%\" colspan=\"2\" style=\"width: 2.7566%;\"\u003e\n \u003cp\u003e2.80 \u0026plusmn; 0.02\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e2.80 - 2.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.08829568788501%\" colspan=\"2\" style=\"width: 3.1011%;\"\u003e\n \u003cp\u003e37.09 \u0026plusmn; 0.002\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e36.83 - 37.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.164271047227926%\" style=\"width: 2.8255%;\"\u003e\n \u003cp\u003e6.70 \u0026plusmn; 0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e6.64 -6.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.240246406570842%\" style=\"width: 2.2742%;\"\u003e\n \u003cp\u003e5.60 \u0026plusmn; 0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e5.59 - 5.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.856262833675565%\" colspan=\"2\" style=\"width: 2.9288%;\"\u003e\n \u003cp\u003e12.82 \u0026plusmn; 0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e12.77 - 12.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.293634496919918%\" colspan=\"3\" style=\"width: 3.2734%;\"\u003e\n \u003cp\u003e352.50 \u0026plusmn; 28.93\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e319.50 - 373.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.369609856262834%\" colspan=\"2\" style=\"width: 2.791%;\"\u003e\n \u003cp\u003e76.70 \u0026plusmn; 0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e76.69 - 76.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.26694045174538%\" style=\"width: 2.6876%;\"\u003e\n \u003cp\u003e0.15 \u0026plusmn; 0.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.12 - 0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNB: Number of samples (n) = 3, TDS: Total Dissolved Solid, TSS: Total Suspended Solid, DO: Dissolved Oxygen, mean values within the same column with different superscripts are significantly different at P \u0026lt; 0.05\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eHeavy metal levels in water\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eHeavy metal concentrations, namely Cu, Cd, Pb, and Cr, were assessed across three distinct water layers; surface, middle, and bottom, at three designated locations (L1, L2, and L3) using an Absorption Spectrophotometer (AAS). The results of these measurements are presented in Table 4. According to the result shown Table 4, all the measured heavy metal concentrations in the same water layer at each location did not show any significant difference. Nevertheless, within the same location, significant variations were evident in the heavy metal concentrations across the three water layers for all the assessed heavy metals. The heavy metal concentrations distribution in the three layers are in the following order Bottom layers\u0026gt;Middle layers\u0026gt; Surface layers. Among the tested heavy metals Cr exhibited the highest concentration across all the locations and the water layers. However, the surface layer at L3 (in proximity to the cultivation site) did not show any detectable concentrations of Cr. Additionally, the bottom layer exhibited the highest detectable level for each heavy metal where the concentrations of Cu and Cd at the L3 bottom layer were 0.7051 mg/L and 0.6020 mg/L respectively while at L2 and L1 bottom layers Pb and Cr displayed the following concentrations: 1.8213 mg/L and 25.7660 mg/L respectively. Conversely, the surface layers indicated the lowest concentrations mainly at the L2 surface layers. Cu, Cd, and Pb showed the flowing concentrations, 0.0413 mg/L, - 0.0510 mg/L, and 1.8213 mg/L respectively. At L3 surface layers, Cr level was found below the detectable limit.Moreover, the detected levels of Cu and Cd were significantly lower compared to Pb and Cr. Thus, the results show variations of notable significance emerged in the heavy metal concentrations within the same water layers across different locations, except in a few instances where the same water layer displayed insignificant detections in at least two sites (e.g., Cd levels in the safe layer, Cr levels in the bottom layer).\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e Metal concentration (mg/L) (Mean \u0026plusmn; SD) and their range (minimum-maximum) measured using an Atomic Absorption Spectrophotometer (AAS) in water (surface, middle, and bottom layer) collected from Koggala lagoon on 09th May 2022 compared with three water layers\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"939\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.82089552238806%\" colspan=\"2\" rowspan=\"2\" style=\"width: 10.3118%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Site of the lagoon\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.513859275053306%\" colspan=\"4\" style=\"width: 25.9792%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeavy Metal Level (mg/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.674418604651166%\" colspan=\"\" style=\"width: 14.3885%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.674418604651166%\" colspan=\"\" style=\"width: 14.3885%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.083056478405314%\" colspan=\"\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089700996677742%\" colspan=\"\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCr\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.586353944562898%\" colspan=\"\" rowspan=\"6\" style=\"width: 6.5548%;\"\u003e\n \u003cp\u003eL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.300639658848613%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\n \u003cp\u003eSurface Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.0752 \u0026plusmn; 0.0015\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0740 - 0.0770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.417910447761194%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.0961 \u0026plusmn; 0.0005\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0950 - 0.0960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.098081023454156%\" colspan=\"\" rowspan=\"2\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e0.3833 \u0026plusmn; 0.0115\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.3700 - 0.3900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.818763326226012%\" rowspan=\"2\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e3.8513 \u0026plusmn; 0.0012\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e3.8500 - 3.8520\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"87.60330578512396%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.18624641833811%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\n \u003cp\u003eMiddle Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.054441260744987%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.1173 \u0026plusmn; 0.0025\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.1150 - 0.1200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063037249283667%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.1304 \u0026plusmn; 0.0005\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.1300 - 0.1310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.63323782234957%\" colspan=\"\" rowspan=\"2\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e0.6474 \u0026plusmn; 0.0115\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.6400 - 0.6600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.91404011461318%\" rowspan=\"2\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e6.2673 \u0026plusmn; 0.0011\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e6.2660 - 6.2680\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"87.60330578512396%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.18624641833811%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\n \u003cp\u003eBottom Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.054441260744987%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.1764 \u0026plusmn; 0.0015\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.1750 - 0.1780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063037249283667%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.2803 \u0026plusmn; 0.0005\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.2800 - 0.2810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.63323782234957%\" colspan=\"\" rowspan=\"2\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e1.6572 \u0026plusmn; 0.0057\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1.6500 - 1.6600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.91404011461318%\" rowspan=\"2\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e25.7660 \u0026plusmn; 0.0020\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e25.7640 - 25.7680\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"87.60330578512396%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.586353944562898%\" colspan=\"\" rowspan=\"6\" style=\"width: 6.5548%;\"\u003e\n \u003cp\u003eL2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.300639658848613%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\n \u003cp\u003eSurface Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.0413 \u0026plusmn; 0.0011\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0400 - 0.0420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.417910447761194%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.0510 \u0026plusmn; 0.0010\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0500 - 0.5200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.098081023454156%\" colspan=\"\" rowspan=\"2\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e0.0994 \u0026plusmn; 0.0011\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0980 - 0.1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.818763326226012%\" rowspan=\"2\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e1.1440 \u0026plusmn; 0.0010\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1.1430 - 1.1450\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"87.60330578512396%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.18624641833811%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\n \u003cp\u003eMiddle Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.054441260744987%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.2030 \u0026plusmn; 0.0030\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.2000 - 0.2060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063037249283667%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.1683 \u0026plusmn; 0.0011\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.1670 - 0.1690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.63323782234957%\" colspan=\"\" rowspan=\"2\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e0.9871 \u0026plusmn; 0.0057\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.9800 - 0.9900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.91404011461318%\" rowspan=\"2\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e12.3650 \u0026plusmn; 0.1861\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e12.2570 - 12.5800\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"87.60330578512396%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.18624641833811%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\n \u003cp\u003eBottom Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.054441260744987%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.4040 \u0026plusmn;0.0059\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.4000 - 0.4100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063037249283667%\" colspan=\"\" rowspan=\"2\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.3053 \u0026plusmn; 0.0011\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.3040 - 0.3060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.63323782234957%\" colspan=\"\" rowspan=\"2\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e1.8213 \u0026plusmn; 0.0011\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1.8200 - 1.8220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.91404011461318%\" rowspan=\"2\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e21.9261 \u0026plusmn; 0.0011\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e21.9250 - 21.9270\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"87.60330578512396%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.586353944562898%\" colspan=\"\" rowspan=\"5\" style=\"width: 6.5548%;\"\u003e\n \u003cp\u003eL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.300639658848613%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\n \u003cp\u003eSurface Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\" colspan=\"\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.0763 \u0026plusmn; 0.0011\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.417910447761194%\" colspan=\"\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.0963 \u0026plusmn; 0.0011\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.098081023454156%\" colspan=\"\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e0.3494 \u0026plusmn; 0.0005\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.818763326226012%\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003eBDL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.18624641833811%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.054441260744987%\" colspan=\"\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.0750 - 0.0770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063037249283667%\" colspan=\"\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.0950 -0.09770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.63323782234957%\" colspan=\"\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e0.3490 - 0.3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.91404011461318%\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.18624641833811%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\n \u003cp\u003eMiddle Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.054441260744987%\" colspan=\"\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.1754 \u0026plusmn; 0.0015\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063037249283667%\" colspan=\"\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.3213 \u0026plusmn; 0.0005\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.63323782234957%\" colspan=\"\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e0.9600 \u0026plusmn; 0.0010\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.91404011461318%\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e5.0742 \u0026plusmn; 0.0011\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.18624641833811%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.054441260744987%\" colspan=\"\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.1740 - 0.1770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063037249283667%\" colspan=\"\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.3210 - 0.3220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.63323782234957%\" colspan=\"\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e0.9590 - 0.9610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.91404011461318%\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e5.0733 - 5.0750\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.18624641833811%\" colspan=\"\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\n \u003cp\u003eBottom Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.054441260744987%\" colspan=\"\" valign=\"bottom\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.7051 \u0026plusmn; 0.0055\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.063037249283667%\" colspan=\"\" valign=\"bottom\" style=\"width: 6.7946%;\"\u003e\n \u003cp\u003e0.6020 \u0026plusmn; 0.0015\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.63323782234957%\" colspan=\"\" valign=\"bottom\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e1.7511 \u0026plusmn; 0.0011\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.91404011461318%\" valign=\"bottom\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e8.4363 \u0026plusmn; 0.0015\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.520255863539447%\" valign=\"bottom\" style=\"width: 5.9153%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.300639658848613%\" colspan=\"\" valign=\"bottom\" style=\"width: 4.4764%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.17910447761194%\" colspan=\"\" valign=\"bottom\" style=\"width: 7.514%;\"\u003e\n \u003cp\u003e0.7010 - 0.7110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.417910447761194%\" colspan=\"\" valign=\"bottom\" style=\"width: 6.8745%;\"\u003e\n \u003cp\u003e0.6000 - 0.6030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.098081023454156%\" colspan=\"\" valign=\"bottom\" style=\"width: 20.3125%;\"\u003e\n \u003cp\u003e1.7500 - 1.7520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.818763326226012%\" colspan=\"\" valign=\"bottom\" style=\"width: 27.4375%;\"\u003e\n \u003cp\u003e8.4350 - 8.4380\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNB: Number of samples(n) = 3, BDL: Below Detection Level, mean values within the same column with different superscripts (a.b.c) are significantly different at P \u0026lt; 0.05\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e Metal concentration (mg/L) (Mean \u0026plusmn; SD) and their range (minimum-maximum) measured using AAS in three water layers (surface, middle, and bottom layer) collected from Koggala lagoon on 09\u003csup\u003eth\u0026nbsp;\u003c/sup\u003eMay 2022 compared with three sampling sites.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"924\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.16883116883117%\" colspan=\"2\" rowspan=\"2\" style=\"width: 38.9512%;\"\u003e\n \u003cp\u003eSite of the lagoon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"68.83116883116882%\" colspan=\"4\" style=\"width: 60.9238%;\"\u003e\n \u003cp\u003eHeavy Metal Level (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.471698113207548%\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.528301886792452%\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.233766233766232%\" rowspan=\"6\" style=\"width: 22.4375%;\"\u003e\n \u003cp\u003eSurface Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.935064935064934%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.532467532467532%\" rowspan=\"2\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003e0.0764 \u0026plusmn; 0.0015\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0740 - 0.0770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.207792207792206%\" rowspan=\"2\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003e0.0964 \u0026plusmn; 0.0005\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0950 - 0.0960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.883116883116884%\" rowspan=\"2\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003e0.3833 \u0026plusmn; 0.0115\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.3700 - 0.3900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.207792207792206%\" rowspan=\"2\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003e3.8513 \u0026plusmn; 0.0012\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e3.850 - 3.852\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\n \u003cp\u003eL1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.829457364341085%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.930232558139537%\" rowspan=\"2\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003e0.0413 \u0026plusmn; 0.0011\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0400 - 0.0420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" rowspan=\"2\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003e0.0510 \u0026plusmn; 0.0010\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0500 - 0.5200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.155038759689923%\" rowspan=\"2\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003e0.0994 \u0026plusmn; 0.0011\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0980 - 0.1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" rowspan=\"2\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003e1.1440 \u0026plusmn; 0.0010\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1.1430 - 1.1450\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\n \u003cp\u003eL2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.829457364341085%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.930232558139537%\" rowspan=\"2\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003e0.0763 \u0026plusmn; 0.0011\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0763 \u0026plusmn; 0.0011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" rowspan=\"2\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003e0.0953 \u0026plusmn; 0.0011\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0950 -0.09770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.155038759689923%\" rowspan=\"2\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003e0.3500 \u0026plusmn; 0.0005\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.3490 - 0.3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" rowspan=\"2\" valign=\"top\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003eBDL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\n \u003cp\u003eL3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.233766233766232%\" rowspan=\"6\" style=\"width: 22.4375%;\"\u003e\n \u003cp\u003eMiddle Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.935064935064934%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.532467532467532%\" rowspan=\"2\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003e0.1173 \u0026plusmn; 0.0025\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.1150 - 0.1200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.207792207792206%\" rowspan=\"2\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003e0.1304 \u0026plusmn; 0.0005\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.1300 - 0.1310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.883116883116884%\" rowspan=\"2\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003e0.6472 \u0026plusmn; 0.0115\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.6400 - 0.6600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.207792207792206%\" rowspan=\"2\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003e6.2673 \u0026plusmn; 0.0011\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e6.2660 - 6.2680\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\n \u003cp\u003eL1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.829457364341085%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.930232558139537%\" rowspan=\"2\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003e0.2030 \u0026plusmn; 0.0030\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.2000 - 0.2060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" rowspan=\"2\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003e0.1683 \u0026plusmn; 0.0011\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.1670 - 0.1690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.155038759689923%\" rowspan=\"2\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003e0.9866 \u0026plusmn; 0.0057\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.9800 - 0.9900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" rowspan=\"2\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003e12.3650 \u0026plusmn; 0.1861\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e12.2570 - 12.5800\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\n \u003cp\u003eL2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.829457364341085%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.930232558139537%\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003e0.1764 \u0026plusmn; 0.0015\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003e0.3213 \u0026plusmn; 0.0005\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.155038759689923%\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003e0.9600 \u0026plusmn; 0.0010\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003e5.0736 \u0026plusmn; 0.0011\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.829457364341085%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\n \u003cp\u003eL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.930232558139537%\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003e0.1740 - 0.1770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003e0.3210 - 0.3220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.155038759689923%\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003e0.9590 - 0.9610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003e5.0733 - 5.0750\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.233766233766232%\" rowspan=\"5\" style=\"width: 22.4375%;\"\u003e\n \u003cp\u003eBottom Layer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.935064935064934%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.532467532467532%\" rowspan=\"2\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003e0.1766 \u0026plusmn; 0.0015\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.1750 - 0.1780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.207792207792206%\" rowspan=\"2\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003e0.2803 \u0026plusmn; 0.0005\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.2800 - 0.2810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.883116883116884%\" rowspan=\"2\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003e1.6600 \u0026plusmn; 0.0057\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1.6500 - 1.6600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.207792207792206%\" rowspan=\"2\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003e25.7660 \u0026plusmn; 0.0020\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e25.7640 - 25.7680\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\n \u003cp\u003eL1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.829457364341085%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.930232558139537%\" rowspan=\"2\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003e0.4040 \u0026plusmn;0.0059\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.4000 - 0.4100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" rowspan=\"2\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003e0.3053 \u0026plusmn; 0.0011\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.3040 - 0.3060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.155038759689923%\" rowspan=\"2\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003e1.8214 \u0026plusmn; 0.0011\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1.8200 - 1.8220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" rowspan=\"2\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003e21.9256 \u0026plusmn; 0.0011\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e21.9250 - 21.9270\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\n \u003cp\u003eL2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.829457364341085%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.930232558139537%\" rowspan=\"2\" style=\"width: 16.3691%;\"\u003e\n \u003cp\u003e0.7051 \u0026plusmn; 0.0055\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.7010 - 0.7110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" rowspan=\"2\" style=\"width: 16.2285%;\"\u003e\n \u003cp\u003e0.6024 \u0026plusmn; 0.0015\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.6000 - 0.6030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.155038759689923%\" rowspan=\"2\" style=\"width: 15.7871%;\"\u003e\n \u003cp\u003e1.7506 \u0026plusmn; 0.0011\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1.7500 - 1.7520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54263565891473%\" rowspan=\"2\" style=\"width: 13.9629%;\"\u003e\n \u003cp\u003e8.4363 \u0026plusmn; 0.0015\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e8.4350 - 8.4380\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.083333333333336%\" valign=\"bottom\" style=\"width: 22.4375%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"47.916666666666664%\" valign=\"bottom\" style=\"width: 18.0762%;\"\u003e\n \u003cp\u003eL3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNB: Number of samples (n) = 3, BDL: Below Detection Level, mean values within the same column with different superscripts are significantly different at P \u0026lt; 0.05\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eHeavy metal levels in sediments\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe concentrations of heavy metals measured in sediment samples retrieved from three sampling sites are presented in Fig. 3. The Cu and Cd were detected at the respective ranges of 0.06 -0.085, and 0.025-0.041 (mg/gdry weight), while Pb and Cr were below the detection level. The heavy metals concentrations in sediment were found lower than those reported in water samples (Tables 4 and 6). The highest concentration of Cu (0.0796 \u0026plusmn; 0.0083 mg/g dry weight) was detected in the L3 site less than the established standard level by FAO /WHO (100 mg/kg dry weight; FAO/WHO, 2001[54]. The highest Cd concentration (0.0413 \u0026plusmn; 0.0006 mg/g dry weight) was measured at the L1 site and did not exceed the standard level. The obtained values were less than those reported in similar ecosystems around the world (e.g., Oualidia lagoon in Morocco [27] Segara Anakan lagoon, Indonesia [28], Sidi Moussa lagoon in Morocco [2], Songkhla lagoon in Thailand [29] and Kalametiya lagoon in Sri Lanka [30]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u0026nbsp;\u003c/strong\u003e Metal concentration (g/g dry weight), (Mean \u0026plusmn; SD) and their range (minimum-maximum) measured using AAS in sediment collected from Koggala lagoon on 09th May 2022\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"667\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.689655172413794%\" rowspan=\"2\" style=\"width: 16.676%;\"\u003e\n \u003cp\u003eSite of the lagoon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"71.06446776611695%\" colspan=\"4\" style=\"width: 62.4088%;\"\u003e\n \u003cp\u003eHeavy Metal Level (mg/g dry weight)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.35538752362949%\" style=\"width: 22.74%;\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.22117202268431%\" style=\"width: 21.8557%;\"\u003e\n \u003cp\u003eCd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.476370510396976%\" style=\"width: 10.1067%;\"\u003e\n \u003cp\u003ePb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.550094517958414%\" style=\"width: 7.8327%;\"\u003e\n \u003cp\u003eCr\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.689655172413794%\" style=\"width: 16.676%;\"\u003e\n \u003cp\u003eArea near to the\u003c/p\u003e\n \u003cp\u003eKEPZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.488755622188904%\" style=\"width: 22.74%;\"\u003e\n \u003cp\u003e0.0684 \u0026plusmn; 0.0006\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0670 - 0.0680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.58920539730135%\" style=\"width: 21.8557%;\"\u003e\n \u003cp\u003e0.0413 \u0026plusmn; 0.0006\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0410 -0.0420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89505247376312%\" style=\"width: 10.1067%;\"\u003e\n \u003cp\u003eBDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.09145427286357%\" style=\"width: 7.8327%;\"\u003e\n \u003cp\u003eBDL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.689655172413794%\" style=\"width: 16.676%;\"\u003e\n \u003cp\u003eMiddle of the lagoon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.488755622188904%\" style=\"width: 22.74%;\"\u003e\n \u003cp\u003e0.0693 \u0026plusmn; 0.0101\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0600 - 0.0800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.58920539730135%\" style=\"width: 21.8557%;\"\u003e\n \u003cp\u003e0.0370 \u0026plusmn; 0.0057\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0360 - 0.0370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89505247376312%\" style=\"width: 10.1067%;\"\u003e\n \u003cp\u003eBDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.09145427286357%\" style=\"width: 7.8327%;\"\u003e\n \u003cp\u003eBDL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.689655172413794%\" rowspan=\"2\" style=\"width: 16.676%;\"\u003e\n \u003cp\u003eArea near the Cultivation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.488755622188904%\" rowspan=\"2\" style=\"width: 22.74%;\"\u003e\n \u003cp\u003e0.0800 \u0026plusmn; 0.0083\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0700 - 0.0850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.58920539730135%\" rowspan=\"2\" style=\"width: 21.8557%;\"\u003e\n \u003cp\u003e0.0263 \u0026plusmn; 0.0011\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.0250 - 0.0270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.89505247376312%\" rowspan=\"2\" style=\"width: 10.1067%;\"\u003e\n \u003cp\u003eBDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.09145427286357%\" rowspan=\"2\" style=\"width: 7.8327%;\"\u003e\n \u003cp\u003eBDL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNB: Number of samples (n) = 3, Mean values within the same column with different superscripts are significantly different at p \u0026lt; 0.05.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eHeavy metal levels in fish\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eFour heavy metals were (Cu, Cd, Cr, and Pb) measured in the liver, skin, gill tissues, and flesh of \u003cem\u003eE. suratensis\u003c/em\u003e living in three selected locations within the Koggala lagoon, Sri Lanka namely L1 (area near the KEPZ), L2 (middle of the lagoon) and L3 (area near to the cultivation site). In addition to the locations from which the fish samples were collected, the size of the fish (Small: 10.1 cm - 11.6 cm, medium: 14.1 cm -16.6 cm, and large fish: 19.6 cm \u0026ndash; 23.2 cm) was also considered when measuring the heavy metal concentrations. The results of all the combinations are illustrated in Fig. 4, 5, and 6.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHeavy metal concentrations of the selected tissues and organs of fish collected near the KEPZ (L1)\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFig. 4 shows the heavy metal concentrations measured in selected tissues and organs of fish collected near the KEPZ (L1). As shown in the figure, the heavy metal concentrations in liver samples vary according to the metal type, and also according to the fish size, where we notice that medium-sized fish contained the highest significant Cu concentration (0.117 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW), and the lowest concentration (0.052 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW) is found in larger-sized fish. Cd content in liver samples was significantly higher in smaller-sized fish (0.107 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW) compared to the other samples. Interestingly Pb was only detected (0.197 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW) in larger-sized fish while Cr was found in detectable levels in medium-sized (0.031 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW) and larger (0.019 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW) fish. The Cu and Cd content in skin samples of smaller-sized fish were notably higher (0.244 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW and 0.021 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW respectively) when compared to the fish of other sizes. Moreover, medium-sized fish exhibited relatively higher Cu and Cd contents compared to the larger-sized ones. Cr and Pb concentrations occurrence were similar to the liver samples while both of them were no detectable in small fishes. Pb in the four tissue/organs of L1 fish samples was only detected in larger-sized fish. Similar distribution of Pb was found in gill and flesh samples as well as for Cr which was only detected in medium and larger-sized fish. The highest concentration of Cu was noticed in medium-sized fish (0.078 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW), while the lowest concentration was recorded in larger-sized fish (0.040 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW). Cd content was about 55 times higher in the smaller-sized fish (0.11 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW) compared to the lowest concentration, registered in medium-sized fish (0.02 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW). Regarding flesh samples, heavy metal concentrations mainly Cu were found significant in small-sized fish (0.821 mg/g\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDW). Larger-sized fish contained the highest level of Cd (0.041 mg /g DW).\u003c/p\u003e\n\u003cp\u003eAmong the different tissues/organs under investigation, flesh indicates a high concentration of Cu detected in small-sized fish compared to the liver, skin, and gill. Cd Value was more important in gill and liver of small sized fish as well. Pb concentrations were only shown for larger-sized fish where significant concentrations were found in skin and liver samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHeavy metal concentrations of the selected tissues/organs of fish collected middle of the lagoon (L2)\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSamples collected from the middle of the Koggala lagoon (denoted L2) show almost similar values as L1. According to Fig. 5, Pb is detected also in small sized and large-sized fish while it is still not detected in medium-sized fish. Similarly to L1 findings, Cr is only measured in medium and large-sized fish samples. Metals concentrations vary according to the type of samples (tissue or organ) and fish sample size where Cu concentrations were found high in both liver (0.087 \u0026micro;g/g DW) and gill (0.071 mg/g DW) of medium-sized but also higher in skin (0.178 mg/g DW) and flesh (0.621 mg/g) DW small sized fish samples. The Cd content was consistently lower in all fish tissues including the flesh.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHeavy metal concentrations of the selected tissues/organs of fish collected in the area near to cultivation site (L3)\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe concentrations of heavy metals measured in the fish samples collected from the vicinity of the cultivation site (L3) are shown in Fig. 6. The distribution of examined heavy metals is almost similar to L2 where in both L2 and L3, Pb is present in larger and smaller sized fish samples. The higher concentrations are recorded in flesh samples similar to the two other sampling stations. Cu was found high in the gill and liver of medium-sized samples (0.065 mg/g DW and 0.053 mg/g DW, respectively) and important as well in the skin and flesh (0.514 mg/g DW), of smaller-sized fish. Additionally, Cr was not detected in all tissues of small-sized fish, but a significantly higher level (0.02 mg/g DW) of Cr was found in the liver samples, flesh samples (0.080 mg/g DW) of larger-sized fish, and skin samples of medium-sized fish (0.051 mg/g DW). As for Cd levels, all the skins and flesh of different-sized fish showed lower concentrations, but the smaller-sized fish had the highest significant amount (0.019 mg/g DW, 0.021 mg/g DW respectively) compared to the other fish groups. Concerning the Cd levels in gill tissues\u0026apos; the larger-sized fish had the highest concentration (0.03 mg/g DW), while the smaller-sized fish had the lowest (0.02 mg/g DW). Accordingly, the distribution and accumulation mode of these metals is different according to the fish size and the organs and tissue type.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eBioaccumulation transfer factor\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eBioaccumulation transfer factor (TF) measures the transportation of a substance between various environmental compartments, often involving the passage from soil or water to plants (animals) or from plants to animals [31,32]. TF was used in the field measurement of environmental science and toxicology, enabling the comprehension of the movement of pollutants or chemicals across distinct segments of ecosystems. Table 7 presents the bioaccumulation transfer factor calculated for various organs and tissues of three different sizes of fish samples from water and sediments retrieved from the same sampling sites. Although the exact source of metals in various body parts was unknown, the bioaccumulation transfer factor was calculated by assuming that particular metals had been accumulated solely from water and sediment. When the TF exceeds 1, this means that the heavy metal accumulation in fish tissues is (P \u0026lt; 0.05) greater than in water and sediment, thus, it means bioaccumulation. The TF of Cu from water is more significant in flesh of small sized fish where it indicates a value of 15.525 compared to TF from sediment value (8.598). Similarly for skin samples of medium-sized fish, Cu indicates important TF values, 9.900 and 5.500 from water and sediment respectively. Also, in flesh samples of medium-sized samples, the TF values of Cu from water and sediment were 6.750 and 3.738 respectively. Therefore, Cu shows more important TF from both water and sediment in the 4 types of organs and tissues of three sizes of fish except for Gill / Sediment in three investigated sizes, and for Liver / Sediment in small-sized fish samples. This finding highlights that the TF of Cu from water and sediment to the skin and flesh of small and medium-sized fish is more significant than the other metals while it is found also significant in the liver of large-sized fish samples. Accordingly, the fish samples experience bioaccumulation of Cu, first from water and then from the sediment of the lagoon. The calculation of bioaccumulation transfer factors from other compartments (water and sediment) of the studied area to the fish samples indicates that the TF of metals is more important from water to organs and tissues of fish samples than sediments. This result is consistent with Rashed [25] and Kalfakakour and Akrida-Demertzi [33] findings. For Pb, the transfer factor values exceed 1 only in Skin/Water (1.031) and (Liver/Water (2.143) samples. Other elements, Cd, Pb, and Cr show weak transfer factor values \u0026lt;1 from both water and sediment. These findings shed light on the possible health risks associated with the consumption of this lagoon fish mainly villagers rely on fish flesh for their daily consumption. Consequently, heavy metals can be ingested through the flesh.\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7\u003c/strong\u003e Transfer factor (TF) of heavy metals in different tissues of \u003cem\u003eE. suratensis\u003c/em\u003e collected from Koggala lagoon on 09th May 2022\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"965\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.453416149068323%\" rowspan=\"3\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFish Tissue parts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.939958592132506%\" rowspan=\"3\" style=\"width: 6.2729%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransfer Factor\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"79.60662525879917%\" colspan=\"12\" style=\"width: 36.9544%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eEtroplus suratensis\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;size category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.598958333333332%\" colspan=\"4\" style=\"width: 12.9185%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmall size (S)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.244791666666664%\" colspan=\"4\" style=\"width: 15.2165%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedium size (M)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.505208333333336%\" colspan=\"4\" style=\"width: 11.3658%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLarge size (L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.311688311688311%\" valign=\"bottom\" style=\"width: 3.7886%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.532467532467533%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.8441558441558445%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96103896103896%\" valign=\"bottom\" style=\"width: 3.1675%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCr\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.792207792207792%\" valign=\"bottom\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.532467532467533%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.8441558441558445%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.116883116883116%\" valign=\"bottom\" style=\"width: 5.7761%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCr\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.96103896103896%\" valign=\"bottom\" style=\"width: 3.9128%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.753246753246753%\" valign=\"bottom\" style=\"width: 2.857%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7012987012987%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCr\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.445708376421924%\" rowspan=\"2\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003eSkin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.926577042399172%\" valign=\"bottom\" style=\"width: 6.2729%;\"\u003e\n \u003cp\u003eSkin / Water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618407445708376%\" valign=\"bottom\" style=\"width: 3.7886%;\"\u003e\n \u003cp\u003e3.956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.997931747673216%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.653567735263702%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.135470527404343%\" valign=\"bottom\" style=\"width: 3.1675%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.204756980351603%\" valign=\"bottom\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003e9.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.997931747673216%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.653567735263702%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.444674250258531%\" valign=\"bottom\" style=\"width: 5.7761%;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.135470527404343%\" valign=\"bottom\" style=\"width: 3.9128%;\"\u003e\n \u003cp\u003e1.800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.377456049638056%\" valign=\"bottom\" style=\"width: 2.857%;\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.96277145811789%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003e1.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.928645294725957%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.966480446927374%\" valign=\"bottom\" style=\"width: 6.2729%;\"\u003e\n \u003cp\u003eSkin /Sediment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150837988826815%\" valign=\"bottom\" style=\"width: 3.7886%;\"\u003e\n \u003cp\u003e2.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.4804469273743015%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.027932960893855%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.709497206703911%\" valign=\"bottom\" style=\"width: 3.1675%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.70391061452514%\" valign=\"bottom\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003e5.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.4804469273743015%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.027932960893855%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.28491620111732%\" valign=\"bottom\" style=\"width: 5.7761%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.709497206703911%\" valign=\"bottom\" style=\"width: 3.9128%;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.810055865921788%\" valign=\"bottom\" style=\"width: 2.857%;\"\u003e\n \u003cp\u003e0.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.603351955307263%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.4860335195530725%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.445708376421924%\" rowspan=\"2\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003eGill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.926577042399172%\" valign=\"bottom\" style=\"width: 6.2729%;\"\u003e\n \u003cp\u003eGill / Water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618407445708376%\" valign=\"bottom\" style=\"width: 3.7886%;\"\u003e\n \u003cp\u003e1.275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.997931747673216%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.653567735263702%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.135470527404343%\" valign=\"bottom\" style=\"width: 3.1675%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.204756980351603%\" valign=\"bottom\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003e1.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.997931747673216%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.653567735263702%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.444674250258531%\" valign=\"bottom\" style=\"width: 5.7761%;\"\u003e\n \u003cp\u003e0.001\u0026lt;\u0026lt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.135470527404343%\" valign=\"bottom\" style=\"width: 3.9128%;\"\u003e\n \u003cp\u003e1.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.377456049638056%\" valign=\"bottom\" style=\"width: 2.857%;\"\u003e\n \u003cp\u003e0.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.96277145811789%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.928645294725957%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.966480446927374%\" valign=\"bottom\" style=\"width: 6.2729%;\"\u003e\n \u003cp\u003eGill / Sediment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150837988826815%\" valign=\"bottom\" style=\"width: 3.7886%;\"\u003e\n \u003cp\u003e0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.4804469273743015%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.027932960893855%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.709497206703911%\" valign=\"bottom\" style=\"width: 3.1675%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.70391061452514%\" valign=\"bottom\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003e0.986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.4804469273743015%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.027932960893855%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.28491620111732%\" valign=\"bottom\" style=\"width: 5.7761%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.709497206703911%\" valign=\"bottom\" style=\"width: 3.9128%;\"\u003e\n \u003cp\u003e0.764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.810055865921788%\" valign=\"bottom\" style=\"width: 2.857%;\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.603351955307263%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.4860335195530725%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.445708376421924%\" rowspan=\"2\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.926577042399172%\" valign=\"bottom\" style=\"width: 6.2729%;\"\u003e\n \u003cp\u003eLiver / Water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618407445708376%\" valign=\"bottom\" style=\"width: 3.7886%;\"\u003e\n \u003cp\u003e1.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.997931747673216%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.653567735263702%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.135470527404343%\" valign=\"bottom\" style=\"width: 3.1675%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.204756980351603%\" valign=\"bottom\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003e2.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.997931747673216%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.653567735263702%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.444674250258531%\" valign=\"bottom\" style=\"width: 5.7761%;\"\u003e\n \u003cp\u003e0.001\u0026lt;\u0026lt;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.135470527404343%\" valign=\"bottom\" style=\"width: 3.9128%;\"\u003e\n \u003cp\u003e8.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.377456049638056%\" valign=\"bottom\" style=\"width: 2.857%;\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.96277145811789%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003e2.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.928645294725957%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.966480446927374%\" valign=\"bottom\" style=\"width: 6.2729%;\"\u003e\n \u003cp\u003eLiver / Sediment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150837988826815%\" valign=\"bottom\" style=\"width: 3.7886%;\"\u003e\n \u003cp\u003e0.611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.4804469273743015%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.027932960893855%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.709497206703911%\" valign=\"bottom\" style=\"width: 3.1675%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.70391061452514%\" valign=\"bottom\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003e1.205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.4804469273743015%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.027932960893855%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.28491620111732%\" valign=\"bottom\" style=\"width: 5.7761%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.709497206703911%\" valign=\"bottom\" style=\"width: 3.9128%;\"\u003e\n \u003cp\u003e4.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.810055865921788%\" valign=\"bottom\" style=\"width: 2.857%;\"\u003e\n \u003cp\u003e0.543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.603351955307263%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.4860335195530725%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.445708376421924%\" rowspan=\"2\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003eFlesh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.926577042399172%\" valign=\"bottom\" style=\"width: 6.2729%;\"\u003e\n \u003cp\u003eFlesh / Water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618407445708376%\" valign=\"bottom\" style=\"width: 3.7886%;\"\u003e\n \u003cp\u003e15.525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.997931747673216%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.653567735263702%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.135470527404343%\" valign=\"bottom\" style=\"width: 3.1675%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.204756980351603%\" valign=\"bottom\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003e6.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.997931747673216%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.653567735263702%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.444674250258531%\" valign=\"bottom\" style=\"width: 5.7761%;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.135470527404343%\" valign=\"bottom\" style=\"width: 3.9128%;\"\u003e\n \u003cp\u003e3.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.377456049638056%\" valign=\"bottom\" style=\"width: 2.857%;\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.96277145811789%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.928645294725957%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.966480446927374%\" valign=\"bottom\" style=\"width: 6.2729%;\"\u003e\n \u003cp\u003eFlesh / Sediment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150837988826815%\" valign=\"bottom\" style=\"width: 3.7886%;\"\u003e\n \u003cp\u003e8.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.4804469273743015%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.027932960893855%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.709497206703911%\" valign=\"bottom\" style=\"width: 3.1675%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.70391061452514%\" valign=\"bottom\" style=\"width: 3.4781%;\"\u003e\n \u003cp\u003e3.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.4804469273743015%\" valign=\"bottom\" style=\"width: 3.416%;\"\u003e\n \u003cp\u003e0.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.027932960893855%\" valign=\"bottom\" style=\"width: 2.5464%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.28491620111732%\" valign=\"bottom\" style=\"width: 5.7761%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.709497206703911%\" valign=\"bottom\" style=\"width: 3.9128%;\"\u003e\n \u003cp\u003e1.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.810055865921788%\" valign=\"bottom\" style=\"width: 2.857%;\"\u003e\n \u003cp\u003e0.543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.603351955307263%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.4860335195530725%\" valign=\"bottom\" style=\"width: 2.298%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNB: AS = Accumulated from another Source, NA = Not Accumulate\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003eBioaccumulation of heavy metals concentration in fish tissues\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the current study, the bioavailable metal pollution in the lagoon is reflected by the accumulated levels of Pb, Cd, Cr, and Cu in several tissues of \u003cem\u003eE. suratensis\u003c/em\u003e, a food fish in the Koggala lagoon. Fig. 4, 5, and 6 depict the copper (Cu) concentration levels in most of the analyzed tissues, which exceeded the maximum recommended level (0.1 \u0026micro;g/g DW) set by the FAO for Cu in three different size classes of fish at each sampling site. Additionally, the concentrations of cadmium (Cd), chromium (Cr), and lead (Pb) in the flesh tissues were found to be below the standard recommended limits of 1.0 \u0026micro;g/g DW for Cd, 2.0 \u0026micro;g/g DW for Cr, and 2.0 \u0026micro;g/g DW for Pb, as specified by the FAO. Therefore, \u003cem\u003eE. suratensis \u003c/em\u003eexhibits high Cu levels, although Cu is not considered a toxic heavy metal. In this study, the overall accumulation of heavy metals in fish tissues was observed to be lower than the recommended values.\u003c/p\u003e\n\u003cp\u003eThe accumulation of heavy metals in fish tissue is primarily influenced by metal concentrations in the surrounding water; however, other environmental factors such as salinity, pH, hardness, and temperature have also been found to play a significant role in metal accumulation. Few studies have quantitatively analyzed patterns of metal bioaccumulation and trophic transfers in aquatic ecosystems, in contrast to many studies that have focused on the levels of heavy metals in fish [34,35]. Despite the significance of such studies in predicting the effects of metal pollution on aquatic organisms and the subsequent risk to human health, factors such as animals\u0026apos; body size (i.e., length and weight [36], feeding preferences, habitat preferences [37], ability to adapt to metals load and the physical and chemical characteristics of the aquatic environment [38] all impact the bioaccumulation of metals. The ecological needs and size of aquatic animals have also been found to influence their proclivity for metal accumulation. Therefore, it\u0026apos;s vital to understand how the animal size and metal concentrations-both essential and non-essential- relate to each other.\u003c/p\u003e\n\u003cp\u003eIn related studies, elevated levels of certain heavy metals have been detected in Green chromide (\u003cem\u003eE. suratensis\u003c/em\u003e) populations inhabiting Bolgoda Lake, Negambo lagoon, and the Chilaw lagoon area [39,40]. The total metal levels in muscle tissue (in ug/g wet weight) of the fish obtained from Bolgoda Lake exhibited a wide variation: lead, 0.02- 20.1, cadmium, 0.01 - 0.3, chromium, 0.01-0.2, copper, 0.1 - 10.1, and zinc, 2.5-10.4 (n=60) of the different metal levels detected in the edible muscle of the fish. Bolgoda Ganga exceeds the maximum limits of food for human consumption set by the European Union. A comparison of metal levels in the fish\u0026apos;s muscles, gills, and liver tissues revealed that the liver tissue accumulated the most metals. The findings suggest that excessive intake of E. suratensis from Bolgoda lake may pose a health risk to consumers [39].\u003c/p\u003e\n\u003cp\u003eAs well as, 12 sampling sites of the Negambo estuary presented a wide range of metal concentrations: Pb, not detected-5.7; Cu, not detected-2.5; Cd, not detected -2.1; Mn, not detected-0.9; Ni, not detected -7.4; Cr, 0.9-1.2; Hg, below the detection limit; and Zn, 40.4-180.4. (Koggala lagoon add). The concentration ranges of all eight elements (in mg/kg) in sediments were: Pb, 4.8-20.1; Cu, 5.3-24.2; Cd, 0.03-0.22; Mn, 121.9-792.5; Ni, 9.2-34.7; Cr, 19.2-73.5; Hg, 0.3-2.2; and Zn, 119.5-207.4. The ranges of the concentrations of metals in the edible muscle tissues were: Pb 0.01-0.08; Cu 0.02 -0.37; Cd 0.002-0.048; Mn 0.05-0.51; Ni 0.01-0.31; Cr 0.02 -0.28; Hg 0.03-0.33 and Zn 0.03 - 3.02 in \u003cem\u003eE. suratensis\u003c/em\u003e (Indrajith \u003cem\u003eet al\u003c/em\u003e., 2010).\u003c/p\u003e\n\u003cp\u003eThe wide ranges of specific metal levels observed in fish collected from three locations in the lagoon may indicate that these fish were exposed to a variety of metals with different bioavailabilities within the lagoon through water and food sources. The analyzed fish were in various stages of development, including developing, developed, and spawning stages, and therefore the accumulated heavy metal concentrations varied depending on the fish\u0026apos;s body size. This variation occurred because fish of different had varying organ sizes responsible for absorbing heavy metals. Specifically, fingerlings (small-sized fish) have organs that are still in the development stage [41]. In comparison to the developed and spawning stages of fish that have been studied, fingerling\u0026rsquo;s ability to absorb certain metals may differ. Their immature organs may not be able to accumulate toxic heavy metals like Cr and Pb, but they may accumulate higher levels of Cu and Cd in polluted areas compared to adult fish. Consequently, some references have indicated a positive relationship between heavy metal concentrations and fish body size. Since, in most species, smaller (younger) individuals grow faster than the older ones, the dilution of metal concentrations due to tissue growth should have a more significant effect on smaller individuals than on larger ones, leading to a positive slope in the metal concentration-body size relationship. Also, the accumulation of the metals may occur throughout the life of the organisms, and that higher concentrations in the larger (older) individuals reflect longer-term exposures [42,43]. Fish organs might exhibit diverse distributions of heavy metals due to their differing capacities to absorb and metabolize each element [44]. Most heavy metals do not accumulate in muscle tissue. The gills and skin are two organs that are immediately exposed to water. The quantities of trace elements in fish gills and skin are most likely proportional to the amounts of trace elements in lagoon water. The liver is fish\u0026apos;s major metabolic organ, capable of effectively accumulating heavy metals and metalloids from the aquatic environment and through ingestion. The bulk of trace elements are concentrated in fish liver. Toxic metals were discovered mostly in the liver and gills [45].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnvironment factors toward heavy metals concentration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe tissues of fish from three different size classes collected from three different locations within the lagoon displayed variations of heavy metal accumulation levels. This can be related to two factors: firstly, human activities; and secondly, the variations occurring in the aquatic environment, such as the fish growth rate, metabolism, feeding pattern, and ecological requirements of a given fish species, upon which the accumulation of heavy metals in fish depends [46]. Due to rapid urbanization, population growth, and industrialization, emerging countries are currently facing several serious environmental problems such as air and water pollution and solid waste management. Early research has found an increase in the pollution of specific heavy metals in freshwater systems around the world, particularly in rivers. Pollution has primarily been created by industrial operations and industrial waste, most notably chemicals derived from textiles, oils, and rubber [47]. \u003c/p\u003e\n\u003cp\u003eThe heavy metals concentrations distribution among the three stations indicated that station L1 located near to Koggala Export Processing Zone (KEPZ) recorded significant concentrations compared to L2 and L3. Koggala lagoon is surrounded by a large area of agricultural cultivation and the highly industrialized Koggala Export Processing Zone (KEPZ). During heavy rains, the cultivation areas are prone to flooding, leading to the washout of all the agrochemicals and pesticides into the lagoon through the surrounding streams. Also, KEPZ discharges a significant quantity of wastewater, industrial chemicals, and dyes into the lagoon [16] which explain the significant concentration reported in L1 station located near to KEPZ. In addition, 12 factories are currently operating in the KEPZ, with most of them engaged in the apparel industry none of these industries are involved in the dyeing and washing processes, which are significant contributors to toxic wastewater. Furthermore, light industries such as plastics and rubber toys are also in production, and the majority of them use organic solvents that release toxic chemicals into the environment. It is also noted that up to date, the KEPZ has not implemented wastewater and sewage treatment, which means more chemicals can silt reach the water body contaminate different compartments of the lagoon, and pose a risk to aquatic life. In the meantime, industrial wastes such as plastics, pieces of fabric, and food are dumped onto marshy land bordering the lagoon and they have direct access to the lagoon, impaired by the region\u0026apos;s frequent rainfall (Amarasekara \u003cem\u003eet al.\u003c/em\u003e, 2016). This shed light on the urgent need for establishing strategies that aim at protecting the lagoon and conserving its natural resources while taking into consideration the other socio-economic factors mainly industries and agricultural activities surrounding the lagoon which must take part in the development of these strategies. Also, the tourism industry can be a source of pollution in the aquatic system [48] where in the Koggala lagoon, tourism activity has been involved in the variation of heavy metal levels in different locations of the lagoon.\u003c/p\u003e\n\u003cp\u003eThe L3 station showed values of heavy metals higher than those found in L2. L3 station is located in an area close to a cultivation site and surrounded by both paddy and non-paddy crops where the agrochemicals used in the nearby rice and tea plantations have direct access to the lagoon leading to a potential impact on marine organisms including crustaceans due to pesticide exposure. The used pesticides in Koggala were reported by Readmen et al. [49] to be belonging to some of the most known as toxic groups which have adverse impacts on the sensitive tropical aquatic ecosystems. Chemical analysis conducted elsewhere has indicated that pesticides used in Koggala have adverse impacts on the sensitive tropical marine ecosystem. Evidence of fish deaths in the lagoon and sighting of malformed fish indicate that these agrochemicals may be affecting certain organisms. These fish deaths have occurred during periods of increased agricultural activity [16]. When considering the L3, higher metal concentrations can be noted compared to the middle area of the lagoon. Specifically, chromium (Cr) concentration is notably higher at L3 than at the other locations. The measured levels of metals in the water samples collected from different locations in Koggala lagoon indicate relatively high concentrations of Pb, Cd, Cu, and Cr, exceeding maximum permissible limits set by the WHO (Cu: 1 mg / L, Cd: 0.05 mg / L, Pb: 0.05 mg / L and Cr: 0.05 mg / L) for water quality [50]. Chromium (Cr) concentration is particularly elevated at three locations within the Koggala lagoon (Table 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWater quality toward heavy metals concentration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe concentration of heavy metals is influenced by various water quality parameters including temperature, pH, DO, and salinity. In general, high temperatures induce the accumulation of heavy metals in sediment. Increased DO concentrations facilitate the dissolution of heavy metals in water while lower DO values tend to elevate heavy metal levels in sediment. A lower pH value reduces the solubility of heavy metals in water, leading to higher concentrations near the bottom [51]. Elevated water salinity can lead to the formation of organic matter clumps, expediting the deposition of heavy metals and reducing their concentration in the water (Li et al., 2013). Temperature and total suspended solids (TSS) exhibit a stronger association with and influence on heavy metal concentrations. During the observations, the water temperature measured was 30.1 \u003csup\u003e0\u003c/sup\u003eC. Collecting data at sufficiently high water temperatures can result in lower heavy metal concentrations in the water [51]. This is due to the creation of heavy metal ions at high temperatures, which causes heavy metals to settle and enter the sediment. The concentration of heavy metals in the water can be affected by the pH of the water. The pH value obtained during observation ranged from 5.00 to 7.66, indicating that the lagoon water tends to be acidic. A low pH reduces the solubility of heavy metals in water, increasing heavy metal levels at the bottom of the water [52]. The concentration of heavy metals may vary depending on the sampling location in the same water body. Therefore, water and sediments samples collected from the three different locations in the lagoon can be contaminated by different volume of heavy metal levels originated from various activities practiced around and in the study, area including industrial, agricultural, fishing and tourism activities. Yan et al\u003cem\u003e.\u003c/em\u003e [53] indicated that heavy metal concentrations tend to be higher in the soil and water of industrial and residential areas than in the soil and water of agricultural areas, which is in good accordance with our finding where the L1 samples retrieved near Koggala Export Processing Zone (KEPZ) recorded significant concentrations compared to L2 and L3. \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBased on the results of the present study, it can be concluded that the measured concentrations of heavy metals in the three water layers are higher than those in the sediment. Concentrations of Cr, Pd, Cu, and Cd in the water from three sampling sites exceeded the maximum permissible limits set by globally recognized organizations for heavy metals. Additionally, the heavy metal concentration increases from the surface layer to the bottom layer of the water column. Cu was found to be the most abundant heavy metal in the sediment at all sampling sites in the Koggala lagoon. These findings suggest that the water in Koggala lagoon is contaminated and not suitable for human use in daily life. Significant differences in heavy metal concentrations were observed in the body tissues of fish across small, medium, and large size categories. Small fish accumulated only Cu and Cd, medium fish accumulated Cu, Cd, and Cr, while large size fish accumulated all the analyzed heavy metals. This study indicates that different body sizes of fish accumulate metals at varying concentrations in their tissues. However, the concentrations of Cd, Cr, and Pb in the flesh tissues were within the standard recommended limits for heavy metal levels as referred to by the FAO. On the other hand, Cu concentration in the flesh tissues exceeded the standard limits, although Cu is not considered a toxic heavy metal. Overall, the heavy metal levels in the fish are lower than the recommended values. However, it is important to note that in the future, considering the nature of bioaccumulation and biomagnification, the consumption of \u003cem\u003eE. suratensis\u003c/em\u003e may pose human health hazards. More studies should be conducted in collaboration with medical researchers to determine any connection between heavy metal accumulations and an increase in the number of patients suffering from chronic kidney disease and cancer. Also, reducing the toxicity of wastewater as much as possible and releasing it under maximum permissible limits.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe study conception and design were performed by\u0026nbsp;\u003c/em\u003eRajapakshage Dilani Nuwandhika Wijesinghe and\u0026nbsp;Arukattu Patabadige Sajini Wathma Abeysooriya;\u003cem\u003e\u0026nbsp;\u003cem\u003eMaterial preparation, data collection and analysis were performed by\u0026nbsp;\u003c/em\u003e\u003c/em\u003eArukattu Patabadige Sajini Wathma Abeysooriya, Rajapakshage Dilani Nuwandhika Wijesinghe,\u0026nbsp;and Henegama Liyanage Kelum Sanjaya\u003cem\u003e. \u003cem\u003eThe first draft of the manuscript was written by\u0026nbsp;\u003c/em\u003e\u003c/em\u003eArukattu Patabadige Sajini Wathma Abeysooriya and all \u003cem\u003eauthors commented on previous versions of the manuscript. Supervision was done by\u0026nbsp;\u003c/em\u003eRajapakshage Dilani Nuwandhika Wijesinghe,\u0026nbsp;Epitawatthe Gedara Kiribandalage Yogya Chathurani Bandara and Henegama Liyanage Kelum Sanjaya\u003cem\u003e.\u003cem\u003e\u0026nbsp;Review, interpretation of data, validation, and editing were performed by\u0026nbsp;\u003c/em\u003e\u003c/em\u003eRajapakshage Dilani Nuwandhika Wijesinghe,\u0026nbsp;Prathibha Patabandige Sarath Kumara Patabandi, Mok Wen Jye\u003cem\u003e\u0026nbsp;and\u0026nbsp;\u003c/em\u003eNezha Mejjad\u003cem\u003e\u0026nbsp;and\u0026nbsp;\u003c/em\u003eYeong Yik Sung\u003cem\u003e. All authors read and approved the final manuscript.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAll data generated or analyzed during this study are included in this published article.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe researchers confirm that the study was carried out without any commercial or financial associations that could be interpreted as a possible conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e Not applicable\u003cem\u003e\u0026nbsp;( as already collected the dead fish from the fisherman\u0026apos;s fresh catch).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMejjad, N., Laissaoui, A., Fekri, A., Benmhammed, A., El Hammoumi, O., \u0026amp; Cherif, E. 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Joint FAO/WHO Food Standards Programme, ALINORM 10/12A.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Green chromide, fish, heavy metals, pollution assessment, Koggala Lagoon, Sri Lanka","lastPublishedDoi":"10.21203/rs.3.rs-4587800/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4587800/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Fish have long been identified as good indicators for scientific studies particularly to examine heavy metal pollution in aquatic environments and its associated human health risks. This study assesses the accumulation of heavy metals in different tissues of the food fish Etroplus suratensis (Green Chromide) collected from Koggala lagoon, Sri Lanka. We quantified the concentrations of the four heavy metal ions; Cu2+, Cd3+, Pb2+, and Cr3+ across distinct tissues including skin, liver, gill, and flesh in fish in varying sizes using Atomic Absorption Spectrophotometer (AAS). Samples comprised thirty-six (n=36) fish from three different locations in the lagoon; the area near the KEPZ (L1), the middle of the lagoon (L2), and the area near the cultivation site (L3). The highest concentrations of heavy metals were found in the flesh and skin, while the lowest were observed in the gills. The range of heavy metal concentrations (g/g) in the body tissue varied by fish size; for small-sized fish, Cu (0.0443-0.6210), Cd (0.0110-0.0214), Pb (below detection level-0.46), and Cr (below detection level-39.633); for medium-sized fish, Cu (0.0713-0.6210), Cd (0.0134-0.0170), Pb (below detection level-40.906), and Cr (0.0014-0.0500) and for larger-sized fish, Cu (0.0553-0.345), Cd (0.0110-0.0256), Pb (0.0204-0.2103) and Cr (0.0194-0.0773). The levels of Cd, Cr, and Pb in the flesh tissues of E. suratensis flesh tissues were below the FAO’s recommended standards, however, the nontoxic heavy metal Cu exceeded these limits. Given the bioaccumulation and biomagnification of the studied heavy metals and the consumption of E. suratensis in the Koggala lagoon, regular monitoring is essential to ensure consumer safety.","manuscriptTitle":"Assessment of Heavy Metal Pollution and Human Health Risks Associated with Etroplus suratensis (Green Chromide) in Koggala Lagoon, Sri Lanka","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-03 05:38:09","doi":"10.21203/rs.3.rs-4587800/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"05673b1b-6370-4b18-9593-d0e2adf50043","owner":[],"postedDate":"July 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-12T12:30:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-03 05:38:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4587800","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4587800","identity":"rs-4587800","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}