Assessment of Bioaccumulation of Heavy Metals and Their Ecological Risk in Sea Lettuce (Ulva spp.) along the Coast Alexandria, Egypt: Implications for Sustainable Management

Abstract

The pollution of aquatic ecosystems is an issue facing many countries all over the world and may result in issues such as eutrophication in coastal zones. Managing this eutrophication is a real challenge. The current study focuses on the investigation and identification of aquatic environmental characteristics, including the sediments, waters, and seaweed, of seven eutrophicated locations along the Mediterranean coast of Alexandria (Egypt). Different ecological risk assessment and bioaccumulation factors were calculated in order to identify the probable pollution source and the degree of the problem, in addition to the accumulation of heavy metals in the seaweed. The characteristics of the seaweed, sediments, and waters were chemically analyzed and heavy metals were measured. The genetically and biochemically identified seaweed species were Ulva compressa, Ulva fasciata, Ulva lactuca and Ulva linzea. The sediments of the El-Tabia location contained the highest concentrations of Cd, Co, Ni, and Pb, because this location receives these elements from the El-Amia drain. The Abu Qir location was found to contain the highest concentrations of the same heavy metals in the studied water samples because it was located much closer to the Abu Qir harbor. Ecological risk assessment indices indicated moderate to high contamination for most of the studied elements and locations. The results of the bioaccumulation factor analysis indicated that the studied seaweed species are accumulators of trace elements. These seaweed species should be further investigated concerning ecotoxicology if they are to be used in the human diet and for other benefits. This study opens many windows of research to be investigated in the future regarding the sustainable management of polluted coastal zones.

1. Introduction

The pollution of coastal zones is a significant concern worldwide, including the coasts of the Mediterranean basin [1,2]. The coastal zones of the city of Alexandria, Egypt, which is at a latitude of 31°13′ to 31°19′ N and a longitude of 29°55′ to 30°04′ E, lie in the southeastern Mediterranean Sea and have more than 35 beaches with a length of 24 km [3]. The coastal zone of this city suffers from many sources of pollution, as reported by several researchers; these include organic pollutants [1], radionuclides [4], heavy metals [5] and municipal wastewater sludge [6]. Marine sediments serve as a source and sink of trace elements, influencing their concentrations and distribution patterns in the water column; this is based on local bottom conditions, sediment re-suspension activity, and local biogeochemical cycling regimes in the sediment [7]. Generally, the initial concentrations of trace elements in water sources do not represent a hazard to aquatic creatures. However, the concentration of trace elements in marine waterways is rising as a result of effluents discharged by human industrial and agricultural production operations [8]. Monitoring trace elements in the environment is crucial due to their potential harm to human health [9,10]. Thus, several indices may be employed as indicators to monitor the natural variation in soil and sediment composition, the possibility of human-source pollution, and the toxicological health concerns that are related to soil and sediment pollution [11]. Contaminated seawater can pose health concerns to humans through skin absorption during recreation or the ingestion of contaminated seafood, which might expose individuals to metal contamination, among other issues [12]. As a result, addressing the health hazards posed by metals in saltwater is critical [13].

Eutrophication, particularly due to nitrogen and phosphorus, is a common phenomenon in several coastal zones in many countries such as China [14,15], Brazil [16], Fuji [17], Italy [18], Japan [19], Côte d’Ivoire [20], Vietnam [21], and Egypt [22]. This phenomenon occurs in Alexandria (Egypt) because of pollution that enhances phytoplanktonic biomass, especially marine algal blooms, which are good indicators of eutrophication [23]. The eutrophication of aquatic ecosystems causes anoxia [14,24]. Macroalgal blooms are linked to coastal eutrophication and are becoming increasingly common across the globe [25].

These green tides are a specific marine environmental issue, and often involve sea lettuce (Ulva spp.). Common Ulva species include Ulva lactuca, U. armoricana, U. rigida, U. prolifera, U. pertusa, U. fasciata and U. rotundata [26]. Green tides occur seasonally because of anthropogenic eutrophication and are thought to have increased since the 1970s [27]. Many strategies have been investigated to manage eutrophication, such as reducing phosphorus input [28], estimating nutrient thresholds [29], monitoring water temperature [30], and reducing the abundance of Cyanophyta [31].

Macroalgae or seaweeds include green algae (Chlorophyta), brown algae (Phaeophyta) and red algae (Rhodophyta). These kinds of seaweed produce several bioactive compounds, which are mainly used as biofertilizers, animal feed, and human foods [32]. Macroalgae are also considered biomonitoring agents due to their limited mobility, significant biomass, simple identification, long life, availability, and their capacity to collect metals [33]. Green macroalgae or green seaweeds are an important source of food for millions of people [33]. They are rich in bioactive compounds such as proteins (9.13–25.1%), carbohydrates (31.97–56.07%), lipids (3.1–10.1%), ashes (53%), amino acids, phytohormones such as auxins, gibberellins, cytokinins and abscisic acid, and antimicrobial compounds and minerals such as nitrogen, phosphorus, and potassium [34]. Seaweeds and seaweed-based products can be raised in aquaculture [35] for food and feed [36], biofuels [37,38], cosmetics, dyes, and therapeutic applications [39]. Biofertilizers derived from seaweeds have been used in agriculture to improve soil management, water efficiency, nutritional strategies, and drought tolerance [40,41]. Thus, the key characteristics of seaweed, such as metal biosorption and bioaccumulation, have drawn the attention of international authorities such as the European Food Safety Authority (EFSA) and the United States Environmental Protection Agency (USEPA) [33].

Therefore, this study focuses on the assessment of the bioaccumulation of heavy metals in sea lettuce (Ulva spp.) along the coast of Alexandria, Egypt. Ecological risk assessment was also evaluated for such metals in the coastal zone. The ultimate goal was to provide information that is important to the sustainable management of this vital area.

2. Materials and Methods

2.1. Selected Sites and Sampling

The Alexandria shoreline stretches for about 35 km along Egypt’s Mediterranean coast. The shoreline is characterized by natural rock outcroppings that stretch along the coastline, inland, and into the water, separated by long sandy beaches. Sea lettuce (Ulva spp.) was collected along with seawater and sediments from seven sites on the Alexandria coast that had a large amount of sea lettuce and were separated by approximately 5 km each (Figure 1): El-Tabia (L1), Abu Qir (L2), El-Mandara (L3), Sidi Bishr (L4), Roshdy (L5), El-Raml Station (L6) and Qaitbay Castle (L7) (Table 1 and Figure 2). A graphical summary of this study, including all measurements and analyses, is presented in Figure 3.

In total, 63 samples of each seaweed (Ulva spp.), seawater, and sediment (7 locations × 3 samples × 3 replicates) were randomly collected during October 2020. All samples were collected in one day under similar weather and environmental conditions: smooth sea, sunny with no wind, and no recent rain. Benthic sediment samples were collected from each location at a depth of around 50 cm from the water or seaweed surface. Seaweed was collected from an area of 10–20 m² from each location. All seaweed thalli were carefully washed to remove rock debris, sand, and epiphytes using seawater. Seaweed, sediment, and seawater samples were sorted and transported separately in plastic bags on ice to the laboratory. Using a plastic grab device, surficial sediment samples were collected from the upper 0–20 cm, removing non-sediment objects and stones by hand. They were then placed into polyethylene bags. The collected sediment samples were dried and homogenized at room temperature and then stored at −20 °C until analysis. About 2 L of water sample was collected from each location in triplicate. The water samples were taken from the top of the water surface down to 50 cm in plastic bottles. The seaweed collected from each location was sun dried, cut into 1–3 mm particles using a knife, washed with distilled water, filtered, and dried overnight at 60 °C to prepare the samples for analyses.

2.2. Seaweed Analyses

Dried seaweed was crushed into a powder and digested using a mixture of sulfuric, nitric, and perchloric acids (2:2:1) [42]. The digested material was brought to a volume of 50 mL with distilled water. A blank sample was made using the mixture of acids only without seaweed, in order to offer a chemical background. Atomic Absorption (Perkin Elmer pin AAcle 500, Waltham, MA, USA) was used to determine the types and amounts of trace elements in the extract.

Total phosphorus was determined using a modified version of the John method [43]. First, 0.1 mL of clear digestate was diluted with 9 mL of distilled water. Two drops of a 0.1% solution of the indicator (2,4 dinitrophenol) were added, followed by the addition of 5 M NaOH drop by drop until the solution turned yellow. Next, 2 M HCl was added drop by drop until the solution became colorless. Then, 1 mL of the combined reagents was added, and the solution was gently shaken. The absorbance was measured at 710 nm after 30 min. The mixed reagent was prepared by mixing antimony molybdate acid and recently prepared 2.5% ascorbic acid in a 4:1 ratio. The mixture was stabilized for 1 day. The antimony molybdate acid was prepared by dissolving 0.75 g of (NH₄)₆Mo₇O₂₄·4H₂O and 0.014 g of antimony potassium tartrate in 50 mL of distilled water. Then, 8.8 mL of concentrated H₂SO₄ was added, and the solution was cooled. The volume was adjusted to 100 mL with distilled water, and the solution was stored in a dark-colored glass bottle.

The phosphorus concentrations were estimated considering a standard curve in the 0–5 µg range of phosphorus. Dried samples were used to determine the total nitrogen using the Kjeldahl technique. The samples were weighed and transported to Kjeldahl digestion flasks that contained 7.00–10.0 g of a catalyst made from a mixture of K₂SO₄ (9 g), in addition to CuSO₄.5H₂O (1 g) and 25 mL of concentrated H₂SO₄. Following the digestion, the distillation occurred in the Kjeldahl distillation unit by adding more baser, followed by the boiling and condensation of the NH₃ gas in a receiving solution of 5% H₃BO₃ that contained methyl red and methylene blue indicators. It was then titrated with 0.1 N HCl. The nitrogen (%) was calculated on a dry matter basis [44].

2.3. Water Analyses

Seawater samples were filtered and the pH of the untreated samples was measured using a pH meter (JENWAY 3510, Staffordshire, UK) in the laboratory. Then, 1 L of seawater was acidified using 2% HNO₃ at 60 °C, and it was then concentrated to 50 mL to measure the elemental contents by Graphite Furnace Atomic Absorption Spectrometry (GBC Avanta E, Victoria, Australia) according to APHA [45]. Levels of N, P, K, Mg, Ca, Cu, Co, Cd, Fe, Ni, Mg, Pb, and Zn were determined in the clear extract using Atomic Absorption (Perkin Elmer pin AAcle 500, USA).

2.4. Sediment Analyses

Dried sediment samples were digested in a mixture of nitric, sulfuric, and perchloric acid (2:2:1) [42]. After digestion, the samples were cooled and the extract was brought to a volume of 50 mL with distilled water. A blank sample was made using the mixture of acids with no sediment digestion to provide a chemical background. The levels of Mg, Ca and trace elements were determined in the clear extract using Atomic Absorption (Perkin Elmer pin AAcle 500, USA). The N content of the sediments was measured using the Kjeldahl method [46], and a spectrophotometer (Double beam UV/Visible Spectrophotometer Libra S80PC, Cambridge, England) was used to measure P [47].

2.5. Calculation of Pollution Indices

Two pollution indices were calculated to evaluate sediment contamination at the study sites, the geo-accumulation index (Igeo) and the enrichment factor (EF). To compare the level of elements in the studied sediments with the mean background contents (MBC) (mg kg⁻¹), the ecological risk was assessed, as suggested by Kabata-Pendias [48]. A comparison of the common pollution indices and what they measure is given in Brevik et al. [49]. It is important to use pollution indices as the absolute value of trace elements does not necessarily indicate the human health threat posed by them [9].

2.5.1. The Geo-Accumulation Index

The geo-accumulation index is utilized to assess the contamination level in soil or sediment [50]. It compares present and predicted pre-industrial concentrations using Equation (1):

Igeo = log₂ [C/1.5B](1)

where C is the concentration of trace elements n in the sediment, B is the content of trace elements in the geochemical background, and 1.5 is a constant that allows the analysis of fluctuations in the trace element content due to natural processes. The outcomes are divided into 7 classes (0, 1, 2, 3, 4, 5, and 6) as follows:

• Class 0 = Igeo ≤ 0 is uncontaminated;

• Class 1 = 0 < Igeo ≤ 1 is uncontaminated to moderately contaminated;

• Class 2 = 1 < Igeo ≤ 2 is moderately contaminated;

• Class 3 = 2 < Igeo ≤ 3 is moderately to heavily contaminated;

• Class 4 = 3 < Igeo ≤ 4 is heavily contaminated;

• Class 5 = 4 < Igeo ≤ 5 is heavily to extremely contaminated; and

• Class 6 = Igeo > 5 is extremely contaminated [11,51].

2.5.2. Contamination Factor

The contamination factor is a one-element index that defines the degree of pollution of a given toxic material in the ecosystem [52] using Equation (2):

CF = C_sample/C_background(2)

where C_sample is the current trace elements content in the sediment and C_background is background concentration. The contamination factor is categorized into the following: CF < 1 indicates a small amount of contamination; 1 ≤ CF< 3 refers to medium contamination; 3 ≤ CF < 6 is significant contamination; and CF ≥ 6 is very high contamination.

2.6. Bioaccumulation Factor (BAF)

The BAF was evaluated to show how effective the seaweed or algae was at accumulating trace elements from the sediment or seawater using Equation (3) [53]:

BAF = C_algae/C_sediment or C_algae/C_seawater(3)

where C_algae= trace element concentrations in algae or seaweed tissues (mg kg⁻¹) and C_sediment and C_seawater are trace element concentrations in sediment and seawater, respectively (mg L⁻¹).

2.7. DNA Extraction

To extract algal DNA from the samples that were frozen at −20 °C, a 150 mg sample was ground in liquid nitrogen using a mortar and pestle. The DNA was isolated using the Cetyl-trimethyl ammonium bromide method [54], and the concentrations were determined using a Nanodrop spectrophotometer (Implen, Westlake Village, CA, USA).

2.8. PCR and Gel Electrophoresis

A polymerase chain reaction (PCR) was performed with six decamer random amplified polymorphic DNA (RAPD) primers. PCRs were performed in the presence of 1X Taq DNA polymerase buffer (i.e., 10 mM Tris-HCl at pH 8.3, 50 mM KCl and 1.5 mM MgCl₂), 100 μM dNTPs, 10 picomole of a random primer, 25 ng DNA template, and a half unit of Taq DNA polymerase in a whole volume of 25 μL. PCR was carried out in an automated thermal cycler (MJ-Mini, Bio-Rad, Hercules, CA, USA). The first step was performed at 95 °C for 4 min, then 35 cycles were performed at 94 °C for 1 min., at 36 °C for 30 s and at 72 °C for 3 min for denaturation, annealing, and polymerization, respectively, followed by a final expansion step at 72 °C for 7 min. The products of amplification were separated on 1.5% agarose gel in a 0.5 × TBE buffer versus molecular size standard 1 Kbp ladder. Gels were visualized under UV light and depicted by the gel documentation system (UVITEC, Cambridge, UK).

2.9. Quantification of Antioxidant Enzymatic Activities

The activities of antioxidant enzymes, including catalase, peroxides, and polyphenol oxidase were measured in the algal samples. Catalase (CAT; EC 1.11.1.6) activity was determined using H₂O₂ at 240 nm [55]. The reaction combination (1 mL overall) included 20 mg total protein, 50 mM sodium phosphate buffer (pH 7.0) and 10 mM H₂O₂. For each measure, the blank paralleled the absorbance of the combination at time zero, and the real reading paralleled the absorbance that was measured after 1 min. One unit of CAT activity was described as a 0.01 decrease in absorbance at 240 nm/mg of protein/min. Peroxidase (POX; EC 1.11.1.7) activity was determined based on the procedure described by Hammerschmidt et al. [56], and polyphenol oxidase (PPO; EC 1.10.3.1) activity was determined according to Malik and Singh [57].

2.10. Quality Control and Quality Assurance

All blanks, measurements, triplicate trace element measurements in extracts, and certified reference materials for each studied element were included for quality control, and uncertainty was calculated. All the equipment was calibrated according to the manufacturer’s specifications. Internal and external quality assurance systems were applied according to the requirements of ISO/IEC 17025-2017 [58]. Certified reference materials obtained from Phenova Certified Reference Materials (Torrance, CA, USA; WS0718; September 2018) were used for quality control to calculate the analyses’ efficiencies. The recovery was between 92% and 103% depending on the studied element, whereas the average relative standard deviation (RSD) was less than 5%. The standard deviation (SD) of the measurements was above 5% in a few cases. These values were not included in the statistical analyses. The detection limits obtained for Cd, Co, Cu, Fe, Ni, Pb and Zn were 0.02, 0.05, 0.04, 0.06, 0.04, 0.05, and 0.04 mg L⁻¹, respectively.

2.11. Statistical Analyses

The means and analysis of variance were calculated using Costat Version 6.311 statistical software [59]. The means were separated by least significant difference (LSD) and Duncan’s multiple range tests, and significance was determined at p ≤ 0.01.

Amplification profiles were generated using the RAPD primers and recorded as 1 or 0 for the presence or absence, respectively, of a band of a specific molecular size, in order to produce a binary matrix that was subjected to cluster analysis. The similarity matrix was assessed by Jaccard’s genetic similarity index [60]. A dendrogram was produced by cluster analysis using the arithmetic averages (UPGMA) by the un-weighed pair group technique. The PAST statistics software version 2.17 package was utilized to analyze the data [61].

3. Results

3.1. Ulva and Pollution

3.1.1. Chemical Analyses of Ulva spp.

All seaweed samples varied in their content (in mg kg⁻¹) of K (7670–20,820), Mg (14,000–17,820), P (2960–5810), N (860–3360), Ca (400–33,330), Cu (7.7–26.7), Fe (533–4437), and Zn (14.2–19.5) in all locations (Table 2). The Mg content was the highest element tested in all the algal samples from all locations. When comparing locations, the algal samples from L1 had the highest P and Fe contents, whereas the samples from L3 contained the highest N and Mg. The highest K content was recorded at L7. The trace elements concentrations varied significantly among the locations. Pb and Ni showed the highest trace elements concentrations (28.6–35.8 and 23.9–33.8 mg kg⁻¹, respectively) in the samples from all locations compared to the other trace elements. The highest significant mean concentrations of Co, Ni and Pb were 20.9, 33.8, and 35.8 mg kg⁻¹, respectively, at L3. The highest significant mean concentrations of Fe, Cu and Zn were 4437, 26.7, and 19.5 mg kg⁻¹, respectively, at L1. The highest mean concentration of Cd was 12.8 mg kg⁻¹ at L5.

3.1.2. Antioxidant Enzymes Activity of Ulva spp.

The activities of some antioxidant enzymes were measured for the seaweed samples at each location (Figure 4). These antioxidants were catalase (CAT), peroxidase (POX) and polyphenol oxidase (PPO). The samples from L4 had the highest activities of all antioxidant enzymes studied, followed by the samples from L1, and the algal samples from L3 had the lowest values of CAT and POX. The CAT and POX enzyme activity decreased in samples from L4 toward the L7 location. The activities of the antioxidant enzymes studied reflected the degree of pollution at these sites. These findings indicate that L4 was associated with the highest level of human activity near Alexandria. Based on the values of antioxidant activities, the sites were ordered as follows: L4 ˃ L1 ˃ L5 ˃ L7 ˃ L2 ˃ L6 ˃ L3.

3.1.3. Genetic Diversity of Ulva spp.

Six RAPD primers were used for four populations of Ulva spp. from the studied costal locations (Table 3). The RAPD primers effectively created scoreable and instructive bands. The RAPD profiles of the magnified products are presented in Figure 5. Various banding shapes were formed from various primers. The level of polymorphism was 100% with all the investigated primers except OPF08, which had 90% polymorphism through all examined Ulva populations. Primer OPD12 yielded the most bands (12) while primers OPC04, OPF08, and OPV02 amplified the fewest (9). The highest similarity value (0.43) was recorded for the L1 and L2 populations, while the lowest value (0.06) was recorded for L7 populations. Similarity coefficient matrices were utilized to make a dendrogram of the four Ulva spp. studied, according to UPGMA analysis (Figure 6).

3.2. Chemical Characterization of Seawater

The seawater samples significantly varied in their characteristics among the different locations (Table 4). In general, Sidi Bishr (L4) had the highest concentrations of both K (1031 mg L⁻¹) and Mg (384 mg L⁻¹), whereas Abu Qir had the highest concentrations of trace elements such as Pb (4.11 mg L⁻¹), Ni (3.81 mg L⁻¹), Co (2.38 mg L⁻¹), and Cd (0.507 mg L⁻¹). The chemical analysis of seawater showed that all locations had high concentrations of trace elements compared to the normal level of these elements in seawater. The concentrations of trace elements in aquatic compartments such as sediments reflect either anthropogenic impacts or the chemical composition of the bedrock. The pH values were 7.18, 7.88, 7.93, 7.92, 7.74, 7.68, and 7.84 in the studied locations, respectively.

3.3. Chemical Properties of Sediments

The chemical composition of sediment samples varied significantly among the locations (Table 5). The sediment samples ranged (in mg kg⁻¹) from 5660–7250, 338–1585, 4223–11,546, 80–1280, 1.2–13.5, 1000–9656, and 78.1–149.5 for N, P, Mg, Ca, Cu, Fe, and Zn, respectively. The differences between the concentrations of the various metals were highly significant (p ≤ 0.01).

3.4. Ecological Risk Assessment

Two selected pollution indices (CF and Igeo) were calculated to evaluate sediment contamination as part of the ecological risk assessment (Table 6). All sites had low Cu, Fe, and Zn contamination based on the CF values (i.e., CF = 1 ≤ CF < 3), while they were very highly contaminated by the other metals studied (i.e., CF ≥ 6). The values of the bioaccumulation factor (BAF) were calculated using both sediments and seawater, and are shown in Table 7. The BAF values were higher than 1 at all sites for all metals, except Cu at L6 and Fe at 4 locations. This indicated that the algae accumulated these metals in their tissues at most of the study sites and were classified as metal accumulators. Geo-accumulation (Igeo) index values were extremely high and showed polluted conditions for Cd at all locations, whereas Fe and Zn values for this index indicated uncontaminated to moderately contaminated conditions. All locations had Igeo index values that ranged between 1 and 2 for Pb, whereas the values were between 2 and 3 for Co.

3.5. Principal Component Analysis (PCA) and Correlation

The PCA showed two principal components (Figure 7), PCA1 and PCA2, which accounted for 74.81 and 12.51% of the whole variance in the data matrix, respectively. The estimated Kaiser–Meyer–Olkin Measure (KMO) value was 0.70 and the Bartlett’s level of significance was <0.01, indicating the general suitability of the data for PCA. This suggested that all elements were included in PCA1 except N, which was included in PCA2. PCA1 was heavy with the positive loading of Zn, Co, Pb and Ni, which indicates that these metals have similar sources. This result is supported by the results of the strong relationships among these metals, demonstrated by the correlation analysis (Table 8). PCA2 included only N, indicating that N in this area has a different source to the other elements studied. The correlation between the studied heavy metals was significantly higher than 96% (R²) for Co, Pb, Ni, Mg, and Zn.

4. Discussion

Several coastal zones all over the world suffer from the effects of intensive human activities, which lead to the pollution of these aquatic environments. In the current study, the coastal zone along Alexandria, Egypt, was selected as a case study of a eutrophicated area due to human activities. To evaluate the environmental effects of human activity, samples of seawater, seaweed from the genus Ulva, and sediments were collected from seven locations along the Alexandria coastal zone.

4.1. Seaweed and Eutrophication in Selected Locations

The chemical properties of seaweed showed that all locations had high concentrations of trace elements compared to the typical values reported in the literature. This finding means that the seaweed species is a hyperaccumulator of the studied heavy metals and, therefore, of important bioindicators for eutrophicated locations. The reason for the high heavy metal values may be due to the intensive human activities in these coastal zones, which provide many sources of pollution; this includes untreated sewage, oil spillage, oil transport, and industrial wastewater [62]. The populations were separated into two marked clusters by the unweighted pair group method. The first was comprised of the L1 and L2 populations, while the second cluster consisted of the L4 and L7 populations. According to their morphological characteristics, the four Ulva populations collected from L1, L2, L4 and L7 were U. lactuca, U. compressa, U. fasciata and U. linzea, respectively. These results clearly indicate that U. lactuca was phylogenetically close to the species U. compressa. The phylogenetic relationship indicated by the dendrogram in Figure 7 agreed with the results obtained by Guidone et al. [63] and Ismail and Mohamed [64]. The distribution of green macroalgae, such as the Ulva spp., in coastal zones worldwide is presented in Table 9. The green tides composed of green macroalgae have been observed at multiple locations worldwide. These green tides are considered bioindicators of pollution, and different mitigation strategies have been applied to overcome this global problem. Eutrophication mitigation strategies should include controlling nutrient loads and organic matter, as well as the restoration of ecosystems so that they can function in a sustainable way [65]. These strategies should be investigated for absolute environmental sustainability assessments [66].

4.2. Seawater Eutrophication in Selected Locations

Nutrients (i.e., N, P, Fe, Mg, etc.) are commonly abundant in the coastal zone. These nutrients and their concentrations depend on the source and level of input. Human activities may also introduce pollutants, including heavy metals and nutrient overloads, into coastal waters and sediments. In the current study, all metals were found in high concentrations in seaweed, seawater, and sediment according to the expected background concentrations reported by Kabata-Pendias and Mukherjee [81] and Kabata-Pendias [48]. These findings reflect the presence of pollution in this area, which emphasizes the impact of human activities, such as the release of industrial wastes from sewage sludge and factories. The locations studied were eutrophicated, and the pollution indices for trace elements in the seawater from these sites confirmed the presence of pollution. There are many reasons for this, including the adsorption of these elements into organic compounds and their deposition in sediments [48]. These findings are in an agreement with the results of Alprol et al. [3], who reported that the pollution levels in the Alexandria coastal zone had increased over time. Trace elements that are soluble in seawater may be linked to water pollution in the studied locations [82]. Seaweed is a sink of trace elements that efficiently sequesters these elements in its tissues; elemental levels in the tissues correlate to the elemental levels in both the water and sediment [34]. Seawater intrusion may decrease the toxicity of heavy metals in coastal zones, but might increase the ecological risk for coastal groundwater, as reported in India [83].

4.3. Sediments under Eutrophication in Selected Locations

Coastal zones are under anthropogenic pressures that vary from one area to another depending on the type and intensity of human activity. Therefore, suitable indicators of negative effects from this pressure are critical in order to evaluate coastal ecological quality, which is temporally and spatially variable [17]. Sediments are an important component of the aquatic environment and are a significant indicator of pollution levels. The concentrations of trace elements in the studied locations were higher than their background concentrations in many other parts of the world, as determined from the literature. The distribution of green macroalgae, such as Ulva spp., in coastal zones worldwide is presented in Table 10. This implies that the coastline of Alexandria was more polluted than other coastal zones in many locations around the world. This may be due to environmental pollutants that originate on land (discharge of urban domestic sewage, agricultural and industrial wastewater, disturbance of soil during agricultural and construction activities, etc.) and reach the sea via riverine inputs or aerial depositions, alongside the high level of human ocean-based activity in this area, including shipping and port services, fishing, and aquaculture.

All the metal concentrations in the sediment were higher than the sediment quality guidelines for the protection of aquatic life (marine) [90]. Water pollutants, depending on their physicochemical properties, may stay in the water column or bind to particles that are subsequently deposited on the seabed [91]. If there are a considerable amount of these elements adsorbed in the sediments, the elements may become a hazard to aquatic life when released, due to changes in the physicochemical properties of the seawater. Mining, manufacturing, and municipal wastewaters are all anthropogenic activities that have a strong link with trace elements in waters and sediments [48]. The concentrations of trace elements in the sediments were higher than the maximum allowable concentrations of these elements in agricultural soils. The concentration of many studied elements in the recent study were high, as reported by El Zokm et al. [92].

4.4. Ecological Risk Assessment of Selected Locations

There is an urgent need to use potential ecological risk assessments to determine the effects of pollutants or nutrients and their role in the eutrophication phenomenon. Assessment of sediment pollution is considered crucial for evaluating the health of ecosystems; however, the determination of metals concentrations alone is not enough to assess possible anthropogenic and environmental health impacts [49]. Thus, several quantitative indices have been developed to assess the level of pollution and ecological risk posed by metals in the environment [49,93]. Bibak et al. [94] stated that ecological risk assessment indicated that elemental sediment pollution has occurred as a result of anthropogenic activities.

The suggested indices of risk assessment are important tools for identification of environmental health risk in coastal zones and should be integrated into eutrophication evaluations [95]. The seven studied locations are along the coastline of Alexandria, which includes major harbors, is considered one of the most industrialized zones in Egypt, and receives considerable amounts of petroleum product inputs [96]. These sources of pollution have generated eutrophication due to green tides along the coastal zones of Alexandria. The pollution of these coastal zones has been described by several authors focusing on pollutants such as polycyclic aromatic hydrocarbons [97], heavy metals [92,98], and urban dust, rich in HMs [99]. Furthermore, Alexandria possesses approximately 40% of Egypt’s industry and is the main summer resort in Egypt [3].

There are many indices for monitoring the pollution of aquatic environments that have been used in the evaluation of the eutrophication phenomenon. The degree of metal contamination ranged between zero (or low) to moderate contamination for Cd in approximately half of the studied sites, and was significant in the remaining sites. Cu contamination was low to moderate at all the studied sites. Zn contamination was very high, and Co, Ni, and Pb contamination was high at all sites. According to the Igeo values, all sites were uncontaminated or moderately contaminated by Cu, Fe, and Zn, while all sites were moderately contaminated by Ni and Pb. All sites were extremely contaminated by Cd. The Pb and Cd concentrations in seawater in the current study were many times higher than those in natural seawater and drinking water. These findings indicate the presence of pollution in this area, which reflects the impact of human activities, such as the release of industrial wastes from sewage sludge and factories [48].

Algae are used in the assessment of marine ecosystems due to their high capacity for HMs bioaccumulation; they are considered good bioindicators. Some algae species can survive in polluted environments because of the genetic mutations they undergo. We calculated BAF values related to both sediments and seawater. The BAF examines the degree to which elements are mobilized from the environment and travel into plants, by determining the efficiency with which plants accumulate elements that are in the environment [93]. When the BAF > 1, the given element is more likely to accumulate in the plant’s tissues [100,101]. According to Alvarez-Mateos et al. [102] and Elbehiry et al. [100], plants are classified as hyperaccumulators (>5 mg kg⁻¹), accumulators <5 mg kg⁻¹ and (>1 mg kg⁻¹), and excluders (<1 mg kg⁻¹), based on their BAF values. Correlation analysis was applied to explain the relationships among the examined elements and factors that may affect their interactions [103]. The highest strong positive correlation was observed between Ni and Pb; Co and Ni; Pb, Zn, and Mn; and Cd and Co. These results confirm that the sources of these elements are similar, as are the results of the ecological risk assessment. PCA is also an effective tool in order to confirm the main potential pollution source in the environment and to condense a huge number of indicators into a more manageable set [11,100]. The PCA analysis also indicated that all the elements studied, except for N, have a similar source.

The values of the bioaccumulation factors show that these algae are good accumulators for all metals except Fe (BAF_sediment > 1) (as depicted in Table 10). Copper and Zn are essential microelements for algae, but in higher concentrations, they become toxic. Cd and Pb translocated into plant tissues due to an interference with essential elements, which become toxic when they accumulate in high enough concentrations [104]. The BAF_sediment was higher than 1 at all sites for all metals except Cu at L6 and Fe at all locations [101]. Ulva spp. BAF_seawater values were higher than for BCF_sediment. The maximum BAF_seawater value recorded for algae was higher than 1 for all metals, which means that bioaccumulation was confirmed. The BAF_seawater comparison between the metals was Zn > Cu > Fe > Cd > Co > Pb > Ni (Table 10). Other studies showed that the concentrations of heavy metals vary from species to species [105].

4.5. Suggested Sustainable Management of Eutrophication

Several pollutants may result from human activities, including heavy metals and organic chemicals from sources such as fertilizers, pesticides, medical activities, waste disposal, and industrial activities [106]. The concentrations of these pollutants can become elevated in aquatic ecosystems, leading to toxicity for aquatic biota [107]. Eutrophication (mainly from N and P) can lead to harmful algal blooms (mainly Cyanophyta), as presented in Figure 8. Therefore, there is an urgent need to identify sustainable approaches for the management of coastal zones in order to prevent eutrophication, such as applying Bacillariophyta and Chlorophyta to inhibit harmful Cyanophyta blooms [32]. Additional strategies include reducing phosphorus input [29], estimating nutrient thresholds [30], monitoring water temperature [31], reducing the abundance of Cyanophyta [32], the integrated risk assessment approach [95], marine green economics [108], and the use of biological nanomaterials for the nanoremediation of polluted water [109]. It is possible that the blooms that cause this eutrophication could be harvested to provide organic fertilizer for agricultural production or be used directly as a human food source. However, doing so requires an understanding of the potential for contaminates to bioaccumulate in ocean plants such as seaweed. Several approaches are needed for the sustainable management of eutrophication. Preventing the problem and using bioindicators such as seaweed to monitor pollution is the best solution [110].

5. Conclusions

Alexandria has several eutrophicated coastal zones that result from the growth of extensive green tides of macroalgae. Seven coastal zone sites were selected to evaluate these green tides and the environmental conditions in which they exist. The results confirmed that Ulva spp. was a biomarker and accumulator for contamination in this area, especially for trace element contamination. The ecological risk assessment results confirmed the different degrees of pollution by a variety of elements at the studied locations. Owing to the very high nutrient content, particularly N, P, Ca, K, and Mg in the Ulva species, this seaweed could act as an effective biofertilizer or human food source. However, these species should be further investigated regarding ecotoxicology if they are to be used in human nutrition or biofertilizers. The trace element contamination seen in this study is a concern and must be addressed before the seaweed can be applied to these other uses. Therefore, while this seaweed has promise in terms of helping to meet food security goals, the trace element contamination levels seen in this study represent a concern. Further research should focus on the use of algal extracts, which are effective in organic farming, and are an eco-friendly approach to sustainable agriculture. It is imperative to develop a comprehensive program for the management and restoration of the coastline of Alexandria through monitoring of the water quanlity. Municipal, industrial, fish farm, and other wastes must be controlled and/or treated before being discharged into the sea.

Author Contributions

Conceptualization and visualization, M.E.E.-M.; methodology, A.E.-B., F.S.M. and Y.M.H.; software, Q.M.; validation, Y.H.D., E.C.B. and H.E.-R.; formal analysis, M.E.E.-M.; investigation, F.E. and Y.M.H.; resources, H.E.-R.; data curation, M.E.E.-M.; writing—original draft preparation, H.E.-R., Y.H.D., F.E. and E.C.B.; writing—review and editing, all authors; visualization, H.E.-R.; supervision, M.E.E.-M.; project administration, H.E.-R. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data sets presented in this study are available upon reasonable request from Mohammed El-Mahrouk.

Acknowledgments

The authors thank the staff members of the Physiology and Breeding of Horticultural Crops Laboratory, Department of Horticulture, Faculty of Agriculture, Kafrelsheikh University for their technical support.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. A general view of sea lettuce (Ulva spp.) and the locations that were selected for the sampling of seaweed, water and sediments: (A) Ulva spp, (B) EL-Tabia (L1), (C) Abu Qir (L2), (D) El-Mandra (L3), (E) Sidi Bishr (L4), (F) Roshdy (L5), (G) El-Raml Station (L6) and (H) Qaitbay Castle (L7).

Figure 2. A map showing the locations selected for sampling and study near Alexandria, Egypt.

Figure 3. An overview of the current study, including the sampling of seaweed, seawater, and sediment, the measurements made, and calculated indices for each type of sample.

Figure 4. Antioxidant enzyme activities of Ulva spp., including (A) catalase (CAT), (B) peroxidase (POX) and (C) polyphenol oxidase (PPO) for the study locations. All location (L1 to L7) details can be found in Table 1.

Figure 5. Agarose gel electrophoresis of RAPD profiles for the Ulva spp. seaweed. (M): 100 bp DNA ladder, 1–4 represents Ulva spp. collected from Qaitbay Castle, El Tabia, Sidi Bishr and Abu Qir coastal regions, respectively. V02, F08, C04, D12, C08, and C10 refer to primer numbers.

Figure 6. Randomly amplified polymorphic DNA-based phylogenetic tree and clustering analysis among four Ulva spp. collected from selected coastal locations using the unweighted pair group method.

Figure 7. The principal component analysis loading plot for the studied elements.

Figure 8. Eutrophication and its definition, the common places this phenomenon occurs, the main causes and problems, and suggested management approaches.

Table 1

Descriptions of the selected sampling locations.

Location	Code	Description of Location
El-Tabia	L1	The main drain for this station is the El-Amia, where industrial wastes from El-Tabia Pumping Station (average 1.5–2.0 million m3 day−1) are discharged to Abu-Qir Bay, which is a semi-circular basin.
Abu Qir	L2	This location is a beach at the north of the town and near the Abu Qir port. There are no wastes flowing to the beach.
El-Mandara	L3	This location is a private beach with no wastes flowing to it.
Sidi Bishr	L4	This location is a very crowded beach with no wastes flowing to it. An attempt to protect the beach using cement blocks can be seen in Figure 1.
Roshdy	L5	This location is a rocky shoreline with no wastes flowing to it.
El-Raml Station	L6	This location is a rocky shoreline with no wastes flowing to it.
Qaitbay Castle	L7	This location is a rocky shoreline with no wastes flowing to it.

Table 2

The mean concentrations of major elements and heavy metals (mg kg⁻¹) in seaweed (Ulva spp.) samples collected near Alexandria, Egypt.

Site	N	P	K	Mg	Ca	Fe	Cu	Cd	Co	Ni	Pb	Zn
L1	1090 e	5810 a	7670 h	15,440 c	6670 c	4437 a	26.7 a	4.6 d	20.9 a	24.6 d	31.3 b	19.5 a
L2	890 g	3100 e	7702 g	14,000 e	8000 b	1563 c	10.2 b	5.8 cd	18.4 c	23.9 e	30.7 c	14.3 g
L3	3360 a	4610 c	13,130 c	17,820 a	5330 d	1004 d	10.8 b	5.3 b	20.4 a	33.8 a	35.8 a	16.3 b
L4	1940 d	2960 g	10,260 d	15,660 c	12,000 a	533 h	9.6 c	5.2 cd	17.5 d	29.9 b	28.6 e	14.2 h
L5	2740 c	4210 d	13,280 b	15,680 c	5330 d	739 g	13.3 b	12.8 a	19.3 b	29 b	30.5 bc	15.1 d
L6	860 g	4570 c	8130 e	14,800 d	400 e	3940 b	11 b	5.8 c	19.3 b	27.2 c	30.1 c	15.3 c
L7	3230 b	5220 b	20,820 a	16,180 b	33,330 f	966 e	7.7 d	5.5 c	18.4 c	26.8 c	29.7 d	14.8 e

Different letters in the same column show significant differences among each group of treatments according to Duncan’s test at p ≤ 0.01. All location (L1 to L7) details can be found in Table 1.

Table 3

The sequence of the RAPD primers used in this study.

Primer Name	Nucleotide Sequence	Total Bands	Monomorphic Bands	Polymorphic Bands	Polymorphism (%)
OPC-04	CCGCATCTAC	9	0	9	100
OPC-08	TGGACCGGTG	11	0	11	100
OPC-10	TGTCTGGGTG	10	0	10	100
OPD-12	CACCGTATCC	12	0	12	100
OPF-08	GGGATATCGG	10	1	9	90
OPV-02	AGTCACTCCC	9	0	9	100

Table 4

Concentration of elements in seawater (mg L⁻¹) collected from different locations near Alexandria, Egypt.

Site	N	P	K	Mg	Ca	Fe	Cu	Cd	Co	Ni	Pb	Zn
L1	0.182 e	0.227 a	455 e	371 d	176 g	9.86 c	0.263 b	0.433 c	2.20 b	3.30 c	3.69 b	1.46 d
L2	0.226 d	0.000 c	870 bc	372 cd	310 d	3.88 e	0.227 b	0.507 a	2.38 a	3.81 a	4.11 a	1.42 e
L3	3.361 a	0.000 c	856 d	375 bc	192 f	5.57 d	0.227 b	0.480 b	1.63 d	3.75 a	4.11 a	1.68 b
L4	0.241 c	0.000 c	1031 a	384 a	860 b	12.78 b	0.250 b	0.497 ab	1.85 c	3.71 a	4.29 a	1.69 b
L5	0.388 b	0.013 b	891 b	373 bcd	900 a	23.67 a	0.260 b	0.463 bc	1.75 cd	3.37 bc	3.87 b	1.52 c
L6	0.211 d	0.013 b	885 bc	376 b	664 c	3.46 g	0.220 b	0.443 c	1.62 d	3.23 c	3.79 b	1.35 f
L7	0.246 c	0.000 c	870 c	376 b	216 e	3.70 f	0.503 a	0.507 a	1.45 e	3.44 b	3.85 b	2.25 a

Different letters in same column show significant differences among each group of treatments according to Duncan’s test at p ≤ 0.01. All location (L1 to L7) details can be found in Table 1.

Table 5

The content of studied elements in sediments (mg kg⁻¹) from locations near Alexandria, Egypt.

Site	N	P	Mg	Ca	Fe	Cu	Cd	Co	Ni	Pb	Zn
L1	5950 b	1585 b	8402 e	180 c	1578 d	9.2 b	4.0 a	14.6 a	23.9 a	27.2 a	117.7 c
L2	6700 ab	755 f	4223 g	080 e	9656 h	1.7 d	3.4 d	13 b	19.5 d	20.2 e	78.1 e
L3	5900 b	1204 c	8880 d	200 b	1360 e	1.2 d	3.8 c	13.6 b	20.7 c	21.3 c	100.2 d
L4	7050 a	338 g	9148 c	180 c	1000 g	6.3 c	2.2 g	9.5 d	16.4 e	15.0 h	94.1 d
L5	5780 c	1951 a	10,844 b	120 d	1698 c	6.3 c	3.7 e	12.4 bc	19.4 cd	20.9 d	121.2 b
L6	7250 a	847 e	11,546 a	200 b	2045 a	13.5 a	4.8 b	14.6 a	22.5 b	25.0 b	149.5 a
L7	5660 c	994 d	8814 d	1280 a	1799 b	5.4 c	3.9 cd	12.1 c	19.0 d	16.3 g	120.5 b

Different letters in same column show significant differences among each group of treatments according to Duncan’s test at p ≤ 0.01. All location (L1 to L7) details can be found in Table 1.

Table 6

Contamination factor (CF) and geo-accumulation index (Igeo) of the studied trace elements.

Site	Cu	Cd	Co	Fe	Ni	Pb	Zn
	Contamination Factor (CF)
L1	0.37 b ± 0.01	9.21 a ± 0.1	1.50 a ± 0.04	0.05 c ± 0.001	0.87 a ± 0.02	0.93 a ± 0.02	1.68 c ± 0.01
L2	0.07 d ± 0.1	7.29 d ± 0.1	1.30 b ± 0.03	0.03 d ± 0.001	0.73 d ± 0.01	0.70 d ± 0.01	1.12 f ± 0.01
L3	0.05 d ± 0.1	7.55 c ± 0.1	1.34 b ± 0.03	0.05 c ± 0.001	0.75 c ± 0.01	0.76 c ± 0.01	1.43 d ± 0.02
L4	0.25 c ± 0.03	4.84 e ± 0.1	1.00 d ± 0.01	0.03 d ± 0.001	0.61 e ± 0.03	0.52 f ± 0.01	1.34 e ± 0.01
L5	0.25 c ± 0.04	6.93 e ± 0.2	1.29 b ± 0.1	0.06 b ± 0.001	0.73 d ± 0.01	0.71 d ± 0.02	1.73 b ± 0.01
L6	0.54 a ± 0.03	8.36 b ± 0.1	1.46 a ± 0.01	0.07 a ± 0.002	0.83 b ± 0.01	0.87 b ± 0.03	2.14 a ± 0.02
L7	0.22 c ± 0.03	7.39 d ± 0.1	1.25 c ± 0.02	0.06 b ± 0.001	0.72 d ± 0.01	0.56 e ± 0.02	1.72 b ± 0.01
Geo-accumulation index (Igeo)
L1	0.34 b ± 0.01	8.66 a ± 0.08	1.40 a ± 0.04	0.05 b ± 0.001	0.82 a ± 0.02	0.88 a ± 0.01	1.58 c ± 0.01
L2	0.06 d ± 0.02	6.85 d ± 0.1	1.22 bc ± 0.03	0.03 d ± 0.001	0.68 d ± 0.01	0.65 d ± 0.01	1.05 f ± 0.01
L3	0.04 d ± 0.01	7.10 c ± 0.1	1.26 b ± 0.02	0.04 c ± 0.001	0.71 d ± 0.01	0.71 c ± 0.02	1.34 d ± 0.02
L4	0.24 c ± 0.03	4.55 f ± 0.1	0.94 e ± 0.01	0.03 d ± 0.001	0.57 e ± 0.1	0.49 f ± 0.02	1.26 e ± 0.01
L5	0.24 c ± 0.04	6.52 e ± 0.1	1.22 c ± 0.1	0.05 b ± 0.001	0.69 d ± 0.01	0.67 d ± 0.02	1.63 b ± 0.01
L6	0.51 a ± 0.02	7.86 b ± 0.1	1.37 a ± 0.1	0.06 a ± 0.001	0.78 b ± 0.01	0.82 b ± 0.03	2.01 a ± 0.02
L7	0.20 c ± 0.03	6.94 d ± 0.1	1.18 d ± 0.03	0.06 a ± 0.001	0.68 d ± 0.02	0.53 e ± 0.02	1.62 b ± 0.01

Different letters in same column show significant differences among each group of treatments according to Duncan’s test at p ≤ 0.01. All location (L1 to L7) details can be found in Table 1.

Table 7

Bioaccumulation factor (BAF) based on seawater or sediment for the studied trace elements by location.

Sites	Cu	Cd	Co	Fe	Ni	Pb	Zn
	Bioaccumulation factor (BAF)seawater
L1	105 a ± 20.4	11.4 bc ± 0.5	9.16 c ± 0.5	44.99 b ± 0.5	7.45 d ± 0.3	8.46 a ± 0.3	133 a ± 1.5
L2	46.17 b ± 9.5	10.05 d ± 0.4	7.72 d ± 0.2	40.33 c ± 0.2	6.11 e ± 0.4	7.41 c ± 0.2	100 c ± 2.2
L3	47.67 b ± 1.5	12.36 b ± 0.2	12.53 b ± 1.1	18.03 e ± 0.2	8.97 a ± 0.4	8.59 a ± 0.1	97.1 d ± 0.5
L4	38.74 b ± 2.6	10.11 d ± 0.1	9.47 c ± 0.5	4.18 f ± 0.1	7.85 c ± 0.2	6.75 d ± 0.5	84.5 e ± 0.7
L5	51.10 b ± 2.7	26.10 a ± 1.1	11.07 b ± 0.4	3.12 e ± 0.1	8.7 ab ± 0.2	7.94 b ± 0.1	99.5 c ± 0.8
L6	50.14 b ± 6.2	11.71 b ± 0.7	11.94 ab ± 0.6	113.9 a ± 3.5	8.4 b ± 0.1	8.03 b ± 0.2	113 b ± 0.5
L7	15.26 c ± 1.0	10.57 cd ± 0.5	12.68 b ± 0.5	26.15 d ± 0.2	7.64 cd ± 0.3	7.65 bd ± 0.1	66.1 f ± 0.2
Bioaccumulation factor (BAF)sediment
L1	2.92 b ± 0.1	1.08 f ± 0.1	1.35 d ± 0.03	0.28 a ± 0.001	1.04 f ± 0.03	1.16 e ± 0.05	1.66 b ± 0.01
L2	6.20 ab ± 1.6	1.40 d ± 0.05	1.42 c ± 0.06	0.16 a ± 0.001	1.19 e ± 0.08	1.51 d ± 0.02	1.84 a ± 0.02
L3	14.86 a ± 4.5	1.57 c ± 0.01	1.53 b ± 0.05	0.07 a ± 0.001	1.66 b ± 0.03	1.61 c ± 0.03	1.63 c ± 0.02
L4	1.55 b ± 0.2	2.07 b ± 0.01	1.76 a ± 0.02	0.05 a ± 0.001	1.76 a ± 0.02	1.91 a ± 0.04	1.52 d ± 0.01
L5	2.14 b ± 0.4	3.49 a ± 0.06	1.49 b ± 0.01	0.04 a ± 0.001	1.48 c ± 0.03	1.49 d ± 0.03	1.25 e ± 0.01
L6	0.81 b ± 0.1	1.24 e ± 0.02	1.33 d ± 0.02	0.19 a ± 0.001	1.22 e ± 0.02	1.20 e ± 0.05	1.03 f ± 0.01
L7	1.44 b ± 0.3	1.45 d ± 0.01	1.48 bc ± 0.03	0.05 a ± 0.001	1.36 d ± 0.02	1.80 b ± 0.06	1.23 e ± 0.03

Different letters in same column show significant differences among each group of treatments according to Duncan’s test at p ≤ 0.01. All location (L1 to L7) details can be found in Table 1.

Table 8

Pearson’s correlation coefficients for the studied metals and elements.

	Cu	Cd	Co	Fe	Ni	Pb	Zn	Mg	Ca	N	P
Cu	1
Cd	0.68 **	1
Co	0.78 **	0.88 **	1
Fe	0.79 **	0.46 **	0.70 **	1
Ni	0.72 **	0.88 **	0.99 **	0.62 **	1
Pb	0.78 **	0.87 **	0.99 **	0.67 **	0.99 **	1
Zn	0.85 **	0.84 **	0.98 **	0.76 **	0.96 **	0.97 **	1
Mg	0.80 **	0.85 **	0.96 **	0.63 **	0.96 **	0.96 **	0.97 **	1
Ca	0.59 **	0.56 **	0.61 **	0.27 *	0.59 **	0.61 **	0.59 **	0.69 **	1
N	0.19	0.38 **	0.47 **	0.28 *	0.54 **	0.47 **	0.49 **	0.37 **	−0.22	1
P	0.80 **	0.77 **	0.85 **	0.65 **	0.81 **	0.85 **	0.84 **	0.89 **	0.70 **	0.032	1

**—Correlation is significant at the 0.01 level (2-tailed). *—Correlation is significant at the 0.05 level (2-tailed).

Table 9

Distribution of green macroalgae of the genus Ulva at eutrophicated coasts worldwide.

Country	The Coastal Region(Sea or Ocean)	Brief Description of Study	Dominant Species of Ulva	Reference
Egypt	Alexandria (Mediterranean Sea)	Evaluation of pollution in an area affected by green tides	U. lactuca, U. compressa, U. fasciata, U. linzea	Current study
China	Yellow Sea	Monitoring distribution of U. prolifera during 2020–2022 using remote sensing	Ulva prolifera	Wang et al. [67]
China	Yellow Sea	Largest U. prolifera bloom coverage in this sea was observed during June/July 2021	Ulva prolifera	Nukapothula et al. [68]
China	South Yellow Sea	Green tide reached its largest scale in history during 2021	Ulva prolifera	Zheng et al. [69]
China	Jiangsu Province (Yellow Sea)	Mitigation of green tides	Ulva prolifera	Liu et al. [70]
Brazil	Itanhaém, Sao Paulo (South Atlantic Ocean)	U. lactuca exposed to laboratory coastal oceanic acidification	Ulva lactuca	Sousa et al. [71]
China	Yantai City (Yellow Sea)	Pollution due to phenolic endocrine-disrupting compounds, EDCs	Ulva pertusa, U. prolifera	Zhang et al. [72]
China	Subei Shoal (Jiangsu Province, Yellow Sea)	Pollution due to nutrient-rich submarine groundwater discharge	Ulva prolifera	Zhao et al. [73]
Japan	Tosa Bay, Kochi(Pacific Ocean)	Mitigation of green tides	Ulva ohnoi, U. reticulata	Hiraoka et al. [74]
China	Subei Shoal (Yellow Sea)	Mitigation of green tides	Ulva prolifera	Sun et al. [75]
China	Qingdao (Yellow Sea)	Pollution by nitric oxide (NO)	Ulva prolifera	Wang et al. [76]
USA	Elkhorn Slough, Monterey bay, California	Mitigation of green tides	U. intestinalis, U. lactuca	Duplá [77]
India	Gujarat and others	Mitigation of green tides	Ulva rigida	Balar et al. [78]
South Korea	Jeju coast (Bangdu Bay)	Polluted with high nitrate concentration (NO3−) due to sewage discharge	Ulva spp.	Samanta et al. [79]
China	Rushan city (Yellow Sea)	Polluted with bisphenol A (BPA)	Ulva prolifera	Zhang et al. [80]

Table 10

A comparison of heavy metal concentrations for surface seawater (compared to their concentrations in drinking water (mg L⁻¹) and sediment in different locations worldwide. Kabata-Pendias [48] indicates background levels for seawater.

	Kabata-Pendias [48]	Wang et al. [84]	Arikibe and Prasad [85]	Nour and El-Sorogy [86]	Liu et al. [87]	Current Study
Seawater
Cd	0.0001	0.17–1.55	0.15–0.25	0.013–0.13	0.08–0.73	0.433–0.507
Co	0.00001	-	-	-	-	1.45–2.38
Cu	0.0002	0.04–31.0	0.88–10.29	0.43–0.62	0.83–5.38	0.227–0.503
Fe	0.001	-	-	1.97–2.45	-	3.70–23.67
Ni	0.0005	-	0.23–0.80	0.003–0.008	-	3.30–3.81
Pb	0.00003	0.42–7.25	0.88–1.76	0.08–1.80	0.52–3.60	3.69–4.11
Zn	0.00003	1.97–42.2	0.08–1.45	0.22–0.25	2.22–40.7	1.42–2.25
Sediments
	Arikibe and Prasad [85]	Nour and El-Sorogy [86]	Liu et al. [87]	Nour et al. [88]	Soliman et al. [89]	Current study
Cd	5.49–9.16	0.55	0.08–0.23	0.53	0.04–0.47	2.2–4.8
Co	-	-	-	-	0.43–26.39	9.5–14.6
Cu	78.43–490.18	5.10	13.5–26.0	9.43	0.46–26.26	17–13.5
Fe	-	2384	-	8451	243–38,045	1000–2045
Ni	17.24–28.74	2.87	-	17.5	1.65–60.25	16–23
Pb	116.96–233.92	17.3	11.0–20.8	11.4	3.34–53.67	15–27
Zn	16.00–68.78	22.4	17.6–34.1	44.2	2.05–62.21	78–149

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