Spatial Distribution and Contamination Level Assessment of Marine Sediment of the Safi Bay (Moroccan Atlantic Coast)

Abstract

This study assesses the spatial distribution and contamination level of heavy metals in Safi Bay surface sediments. In this order, 28 surface sediment samples were retrieved from the study area and analyzed using the x-fluorescence method. To assess the contamination of the examined sediment, we used geo-ecological indices such as contamination factor (CF), degree of contamination (DC), geo accumulation index, and pollution load index (PLI). The results show that only Pb and Cd present moderate and considerable contamination in some sampling sites, while other elements (Cr, Cu, Zn, and Ni) indicate no contamination and low contamination by these elements. The inhomogeneous distribution of metal concentrations along the bay suggests different heavy metal sources. Given the ecological and socioeconomic importance of the study area, there is a need for a further analysis of both sediments and biological samples for a better understanding of the contamination levels and origin of metals, in addition to the sustainability of Safi Bay.

1. Introduction

Heavy metals are common environmental pollutants in marine and coastal ecosystems because of their toxicity, non-biodegradability in sediments, and their bio-accumulative nature [1,2,3,4,5,6,7,8]. Once these pollutants reach aquatic environments from both natural processes and/or anthropogenic activities, they may damage marine organisms or can be accumulated in sediments via chemical adsorption and or physical precipitation [9,10,11,12], causing biodiversity loss [13,14]. In aquatic ecosystems, heavy metals do not remain for long in the water column but are precipitated and deposited in sediments as a final receptor [15]. Sediments represent an essential ecological component and play an important role in pollutant storage and distribution, which reflects actual system quality [7,16,17,18,19]. Accordingly, marine sediments can be used as an indicator of pollutants [20]. The growth of human activities around coastal cities, mainly industrial activities in response to the development of socioeconomic sectors, has resulted in human overpopulation and pollution level increase, affecting water resources, sediment, and marine organisms [8,11,21,22]. Indeed, coastal sediments have been found to be polluted by wastewater effluent issued from domestic and industrial activities [17,22,23,24], where several studies indicated that coastal sediment is an important tool for analyzing pollution levels by heavy metals [11,17,22,25,26,27,28,29,30,31,32,33,34]. According to statistical analysis, about 85% of heavy metals are accumulated in superficial sediments [11,22,35,36]. In this order, the study of the pollution level in a coastal environment, which provides various ecosystem services of environmental, socioeconomic, cultural, and recreational value [37], imposes analyzing sediment as an essential ecological component of the coastal environment.

The Bay of Safi is located on the Moroccan Atlantic coast, where multiple human activities are concentrated, including industrial activities, agriculture, and fishing, among others. Thus, the Bay of Safi is subjected to pollutants released from the growth of industrial activities along this littoral zone. Indeed, Kouali et al. and Rafiq et al. [38,39] have identified the intertidal area in Safi as a hotspot of metal contamination. However, few studies have been carried out to analyze the pollution level in this coastal zone despite its socioeconomic and ecological interests. Thus, this ongoing study is the first investigation of the degree of heavy metal pollution in the marine sediment of Safi Bay.

The main aims of this study are to:

• Analyze and quantify the pollution level by heavy metals in Safi Bay sediment using various environmental indices, including contamination factor (CF), degree of contamination (Cd), index of geo accumulation (Igeo), and pollution load index (PLI).
• Calculate the potential ecological risk of metals detected in the Safi Bay sediment.
• Establish the spatial distribution of heavy metals in Safi Bay.
• Attempt to define the possible origin of the heavy metals in this coastal environment to allow for the adequate and efficient management of Safi Bay for sustainable socioeconomic and environmental development.

2. Materials and Methods

2.1. Study Area

The Safi Bay is located on the Moroccan Atlantic coast (32°18′ N–9°15′ W) along a coastal line that extends about 5 km from the tip of the cliff of Sidi Bouzid in the north to Jorf Ammouni in the south (Figure 1). The study region includes the city beach with an NW-SE orientation and the sharp cliff south of the port with an N-S direction [40]. Safi Bay is a triangular bay which has experienced strong population growth and economic development in the last decade. It is characterized by chemical (phosphates) and para-chemical industries (cement, brickworks, plateries) and the agro-industry, especially the fish canneries related to the fishing sector.

At the bottom of this bay, a port with industrial and mineral vocations has been established and is one of the main commercial ports in Morocco. This port has a general traffic of about 5 million tons, a major part of which is destined for mining exports. It is composed of three units (fishing port, commercial port, and ore carrier port). The commercial port has traffic of cereals, gypsum, barite, potash, manganese, fertilizers, and preserves, and the mineral port has traffic of phosphates, sulfur, and phosphoric acid; these industrial, urban, and port activities can constitute sources of heavy metals in this bay.

In Safi Bay, the slope of the continental shelf varies according to the depth, where it reaches 4% between the zero line and the isobath −10 m. The bottoms from −10 m to −25 m have only a slope between 2.5% and 1%. A vast plateau develops from −25 m to −30 m and gradually flares until it reaches a width of 2.5 km. The wave direction is dominant from NW to NNW [40], with the most frequent waves reaching 0.5 to 1.5 m [41]. The distribution of sediments at the bay is controlled by this swell, and an estimated transit of 250,000 m³/year is generated [42].

2.2. Sampling

The superficial sediments of the bay are composed of mostly bioclastic material, with significant biogenic sedimentation favored by the development of bedrock on which fixed organisms are abundant. In contrast, terrigenous detrital inputs are of little importance, while quartz grains and lutites are present only in sheltered coastal areas [43,44]. The main sedimentary inputs in the Bay of Safi come from the erosion of the north coast (cliffs) and are then transited by a north–south littoral drift [40,41,42]. This sediment distribution is controlled by natural (waves, currents) and anthropogenic (geomorphological modification by port developments) factors.

Twenty-eight sediment samples were retrieved in August 2019 on radials perpendicular to the coastline at different depths, with the water depth ranging from 3.5 m to 31.8 m (Figure 1 and

Table 1. Sampling stations, depth (m), sand (%), mud (%), carbonate content, and textural class of each sample.

Stations	Latitude	Longitude	Depth (m)	Sand (%)	Mud (%)	%CaCO3	Textural Class
S1	32°19′48.30″ N	9°17′17.10″ W	18.4	97.39	2.61	72.34	Sand
S2	32°19′21.05″ N	9°16′7.33″ W	6.5	98.79	1.21	82.13	Sand
S3	32°19′22.04″ N	9°16′45.43″ W	23.2	82.16	17.84	62.98	Slightly muddy sand
S4	32°19′21.54″ N	9°17′17.67″ W	30.08	97.16	2.84	78.30	Sand
S5	32°18′45.88″ N	9°17′10.03″ W	29.3	95.15	4.85	72.77	Sand
S6	32°18′49.35″ N	9°16′37.21″ W	25.5	92.02	7.98	71.06	Slightly muddy sand
S7	32°18′50.34″ N	9°16′11.42″ W	21.9	84.64	15.36	74.47	Slightly muddy sand
S8	32°18′50.83″ N	9°15′42.71″ W	17.05	96.86	3.14	79.57	Sand
S9	32°18′52.32″ N	9°15′23.37″ W	15.2	98.55	1.45	82.13	Sand
S10	32°18′53.31″ N	9°15′4.03″ W	3.5	98.86	1.14	82.55	Sand
S12	32°18′17.65″ N	9°15′28.64″ W	13.76	98.41	1.59	79.57	Sand
S13	32°18′18.64″ N	9°16′6.73″ W	23.5	95.88	4.12	79.57	Sand
S15	32°17′43.48″ N	9°16′12.58″ W	26.5	94.25	5.75	77.45	Sand
S16	32°17′42.49″ N	9°15′41.53″ W	25.8	95.41	4.59	77.87	Sand
S17	32°17′42.99″ N	9°15′14.00″ W	21.4	96.98	3.02	76.17	Sand
S18	32°17′43.97″ N	9°14′51.73″ W	12.5	96.94	3.06	69.36	Sand
S19	32°17′43.97″ N	9°16′40.12″ W	28.2	96.46	3.54	82.55	Sand
S20	32°17′42.48″ N	9°17′2.39″ W	29.74	93.72	6.28	65.53	Slightly muddy sand
S21	32°17′6.83″ N	9°16′45.97″ W	30.6	96.26	3.74	79.57	Sand
S22	32°17′7.33″ N	9°16′13.75″ W	28.4	93.85	6.15	73.62	Slightly muddy sand
S23	32°17′6.84″ N	9°15′46.21″ W	26.8	67.57	32.43	52.34	Muddy sand
S28	32°16′30.19″ N	9°15′48.56″ W	24.8	98.30	1.70	77.45	Sand
S29	32°16′30.68″ N	9°16′13.74″ W	26.5	87.41	12.59	37.02	Slightly muddy sand
S30	32°16′31.67″ N	9°16′43.62″ W	29.2	90.79	9.21	41.28	Slightly muddy sand
S32	32°15′49.57″ N	9°16′31.31″ W	26.3	97.35	2.65	80.00	Sand
S33	32°15′48.59″ N	9°16′2.03″ W	22.5	99.02	0.98	77.45	Sand
S34	32°15′18.87″ N	9°15′59.69″ W	11.22	96.96	3.04	72.34	Sand
S38	32°15′19.34″ N	9°17′15.84″ W	31.8	97.82	2.18	77.02	Sand

). All samples were collected with a Van Veen grab, preserved in sealed polyethylene bags, and marked for particle size distribution determination, while only the fine fraction of the samples (sediment <63 µm) was considered for chemical composition analysis. These samples were dried at 50° in an oven and then sieved through 63 μm mesh size, crushed using the grinder, and placed in a new polyethylene bag.

2.3. Heavy Metals Determination

Samples were prepared and analyzed at the Marine Geosciences and Soil Science Laboratory (LGMSS) to determine sediment texture and carbonate content using Bernard calcimetry (Table 1). The grain distribution of each sample was measured using a dry setting on a series of AFNOR standard sieves, and the granulometric parameters were calculated after classification according to [45].

For chemical analysis, only the fine fraction of samples <63 µm was analyzed, where 1 g of each sample was weighed, placed in a bag, and sent for analysis to the ICP-AES laboratory of the Centre National de Recherche Scientifique et Technique de Rabat (CNRST).

The first step of metals analysis consists of removing all organic matter from sediment, so approximately 1 g of dried samples and 10 mL of concentrated HNO₃ were placed together in a plastic digestion tube using a microwave digestion system. Then, a mixture of HNO₃-HFHCl was added to the sediment sample and heated to a temperature of 100–110 °C to obtain a transparent solution [46]. A total of 50 mL of demineralized water was added to the resulting solution and stored at room temperature for the subsequent analysis of heavy metals. The elements Cu, Zn, Cr, Ni, Pb, and Cd were determined, in the Division of Technical Support Units for Scientific Research (UATRS) in the National Center for Scientific and Technical Research of Rabat (CNRST), using Jobin Yvon’s ICP AES model Ultima 2 unit and controlled with 7.4 ICP-Expert Sequential software.

2.4. Statistical Analyses

ArcGis 10.8 software (Esri Co., Ltd., Redlands, CA, USA) was used to draw distribution maps of metal concentrations in surface sediments. All statistical analyses of the data (mean, minimum, maximum, Pearson correlation matrix, and contamination indices) were determined using XLSTAT statistical software 2019. Metal sources were analyzed using primary component analysis (PCA) and Pearson correlation analysis. The PCA was employed to examine both natural and man-made sources of potential pollution [47].

2.5. Assessment of the Environmental Pollution Degree

The environmental indices employed in this study have been widely used in studies related to pollution level assessment and quantification in coastal sediments [18,34,48,49,50]. Some authors have adopted many calculation methods [51,52,53,54,55], whose proposed pollution impact ranges to convert the measured concentrations of heavy metals in soil and sediment into a comprehensive description of pollution levels based on the intensity increase. Thus, in the present study, we used heavy metals pollution indices such as CF, DC, PLI, Igeo, and the potential ecological risk index ($E_r^i$ and RI) to assess the pollution degree of Safi Bay sediments.

2.5.1. Contamination Factor (CF)

The contamination factor is an environmental indicator used to monitor and track the pollution level by heavy metals, where it allows for the assessment of the contamination degree by each metal in each sediment sample. CF values were obtained by dividing the concentration of each metal in the sediment by the baseline or background value (Equation (1)) [52].

$$\mathrm{CF}=\frac{{\mathrm{C}}_{\mathrm{sample}}}{{\mathrm{C}}_{\mathrm{background}}}$$

(1)

where C_sample is the concentration of metal measured in the studied samples, and C_background designates the metal concentration of the reference material or the background value. The authors in [52] defined four categories for sediment quality based on the CF calculated value ranging from low contamination (CF < 1), moderate contamination (1 ≤ CF < 3), considerable contamination (3 ≤ CF < 6), to very high contamination (CF ≥ 6).

2.5.2. Degree of Contamination (DC)

The degree of contamination (DC) is an index that can be derived from CF values and defined as the sum of all individual metal contamination factors [52]. It is calculated as follows (Equation (2)):

$$\mathrm{DC}=\sum _{i=1}^{9}C\mathrm{i}\hspace{0.17em}f$$

(2)

As the utilized components for this index are not always possible to analyze, Abrahim et al. (2008) [56] proposed an alternative method. The modified equation proposed to calculate the degree of contamination is given below (Equation (3)):

$$\mathrm{mCd}=\sum _{i=1}^{9}C\mathrm{i}\hspace{0.17em}f$$

(3)

Regarding the classification and description of the modified contamination degree of sediments, the following terminology was adopted (

Table 2. Description of the modified contamination degree classification.

Classification	Description
0 < mCd < 1.5	Nil–very low degree of contamination
1.5 < mCd < 2	Low degree of contamination
2 < mCd < 4	Moderate degree of contamination
4 < mCd < 8	High degree of contamination
8 < mCd < 16	Very high degree of contamination
16 < mCd < 32	Extremely high degree of contamination
mCd ≥ 32	Ultra-high degree of contamination

):

2.5.3. Pollution Load Index (PLI)

The PLI is used as an indicator of contamination level by heavy metals for each sampling point [57,58]. The PLI is calculated through the following equation:

PLI = (CF₁ × CF₂ × CF₃ ×…× CF_n)^1/n

(4)

where “n” is the number of determined metals, and CF designates the contamination factor. The contamination can be estimated as follows:

• PLI < 1, no metal pollution;
• PLI > 1, polluted condition.

2.5.4. Geo-Accumulation Index (Igeo)

The Igeo was used to assess the metal pollution in the sediment of Safi Bay. The following equation is used to calculate the Igeo for each metal in each sample [51]:

$$\mathrm{I}\mathrm{g}\mathrm{e}\mathrm{o}=\mathrm{l}\mathrm{o}\mathrm{g}2\left(\frac{\mathrm{C}\mathrm{n}}{1.5\hspace{0.17em}\mathrm{B}\mathrm{n}}\right)$$

(5)

where Cn is the measured concentration of the heavy metal (n) in the investigated sediments, and Bn is the background value; here, we used the average abundance value of the upper continental crust (UCC) of a given metal. Also, 1.5 is the background matrix correction factor due to lithogenic effects [59,60,61,62,63]. The classification of sediment pollution level depends on the value of the Igeo, where 7 classes have been defined in

Table 3. Geo-accumulation index classes and designation.

Igeo Value	Igeo Class	Designation of Sediment Quality
>5	6	Extremely contaminated
4–5	5	Strongly to extremely contaminated
3–4	4	Strongly contaminated
2–3	3	Moderately to strongly contaminated
1–2	2	Moderately contaminated
0–1	1	Uncontaminated to moderately contaminated
<0	0	Uncontaminated

.

2.5.5. Potential Ecological Risk Index ($E_r^i$ and RI)

The potential ecological risk factor $E_r^i$ and the potential ecological risk index (RI) were proposed by [52]. Those indices were widely used to evaluate the potential ecological risk associated with heavy metals in aquatic sediments [6,64,65,66,67,68].

$E_r^i$ is calculated using the following equation [52]:

$$C_f^i=C^i/C_n^i$$

(6)

$$E_r^i=T_r^i\times C_f^i$$

(7)

$$RI={\sum }_{i=1}^n{E}_r^i$$

(8)

where $E_r^i$ is the potential ecological risk factor of each heavy metal, and $T_r^i$ is the toxic response factor for heavy metal i. The toxic response factor for Cu, Zn, Cr, Ni, Pb, Cd, and V is 5, 1, 2, 5,5, 30, and 2, respectively [52,69,70], $C_f^i$ is the contamination factor of heavy metal i, and $C^i$ is the measured concentration of heavy metal i in the sediment. The $E_r^i$ and RI values were deduced as follows [7,10,22,71,72]:

2.5.6. Sediment Quality Guidelines (SQGs)

Several authors [11,12,13,33,34] have assessed the impact of metals on the toxicity of aquatic organisms using sediment quality guidelines (SQGs). The threshold effect level (TEL) and probable effect level (PEL) were used in this study to assess the potential biotic influence of metals contained in sediment samples.

3. Results and Discussions

3.1. Spatial Distribution of Sediment Grain Size and CaCO₃ Content

The spatial distribution of sediment grain size and CaCO₃ content are shown in Figure 2. The collected samples are almost sandy except for S23, S7, and S3, which show a relatively important fine fraction of 32.42%. The sand fraction oscillates between 99% and 67.85%. The CaCO₃ content ranged from 37 to 82.5%, while its spatial distribution shows a similar trend as sand fraction, reflecting a significant correlation between sand and CaCO₃ content. The lowest values of CaCO₃ were recorded in the stations with a significant portion of mud, mainly S29, S30, and S23.

3.2. Assessment of the Surface Sediment Contamination by Heavy Metals

Twenty-eight sediment samples retrieved from Safi Bay have been analyzed for Cu, Zn, Cr, Ni, Pb, and Cd concentration determination. The concentrations fluctuate from one sampling point to another, probably reflecting different origins. The metals concentrations varied over the following ranges: Cd (0.305–0.801 mg/kg); Cr (0.305–120.983 mg/kg); Cu (1.740–12.715 mg/kg); Ni (1.573–81.319 mg/kg); Pb (16.575–63.381 mg/kg); and Zn (14.266–127.719 mg/kg). The highest concentrations were recorded in the following stations: S15 (Ni), S17 (Zn), S23 (Cr et Pb), and S29 (Cd et Pb). Industrial and domestic discharges into the ocean are the possible origin of the highest values detected in these sediment samples as they are collected near the city. In addition, these domestic and industrial discharges flow directly into the ocean as the treatment plant is still an ongoing project. The lowest values were registered in the samples retrieved from the north part of the bay, distant from the city and related anthropogenic discharges. Noting also that natural factors such as the granulometric composition of the sediment, seawater dilution levels, and the hydrodynamic conditions that characterize the sampling sites can also affect the distribution of heavy metals in Safi Bay [73]. Noting that stations S23 and S29 indicate significant content fine fractions compared to other sites, explaining the highest recorded concentrations. It is well known that fine fractions accumulate pollutants more than coarser fractions because of their high specific surface area, whereas the presence of important pollutant concentrations in coarser fractions can be explained most likely by the coating phenomena. Organic matter coating on mineral particles may enhance the capacity of dissolved pollutants adsorption [74,75]. Moderate concentrations were found in the following stations, S5, S6, S7, S8, S9, and S10, located near the entrance of loading and unloading vessels for chemical and mining products in Safi port. Figure 3 displays the spatial distribution of heavy metals in Safi Bay, suggesting that the highest concentrations of heavy metals are associated mainly with human activities and port activities, which is in good accordance with the findings of [67], as the lowest concentrations were recorded in the north part far from the Safi port and anthropogenic discharges.

The average concentrations of heavy metals of all sampling stations for each metal Zn = 36.546 mg/kg, Pb = 33.972 mg/kg, Cr = 11.343 mg/kg, Ni = 10.395 mg/kg, Cu = 3.850 mg/kg, Cd = 0.395 mg/kg were compared to the average concentrations found in sediments from similar ecosystems in the world and to upper continental crust (UCC) values

Table 4. The $E_r^i$ and RI values classification.

${\mathit{E}}_{\mathit{r}}^{\mathit{i}}$ Value	Risk Intensity	RI Value	Risk Intensity
<40	Low ecological risk	<150	Low ecological risk
40 < $E_r^i$ ≤ 80	Moderate ecological risk	150 ≤ RI < 300	Moderate ecological risk
80 < $E_r^i$ ≤ 160	Appreciable ecological risk	300 ≤ RI < 600	Considerable ecological risk
160 < $E_r^i$ ≤ 320	High ecological risk	RI > 600	Very high ecological risk
$E_r^i$ > 320	Serious ecological risk

. The heavy metal concentrations of this study were almost less high than those reported in Dakhla Bay, except for Ni and Zn [76]. Cu, Zn, and Pb show low concentrations compared to almost all the coastal ecosystems listed in

Table 5. Comparison table of the heavy metal concentrations measured in Safi Bay surface sediment and other similar marine ecosystems. (ND: not determined).

Locations	Metal Concentrations (mg/kg)						References
	Cd	Cr	Cu	Ni	Pb	Zn
Safi Bay, Morocco	0.395	11.343	3.850	10.395	33.972	36.546	Present study
Dakhla Bay, Morocco	0.4	108	17.3	5.8	71.3	20.8	[76]
Bohai Bay, China	0.04–0.84	ND	7.20–44.0	ND	5.90–97.0	56.3–309	[78]
Bay of Bengal, India	19.8	109.45	76.45	27.984	49.629	78.76	[8]
Zhelin Bay, China	0.063	23.07	7.95	7.5	35.69	74.95	[79]
Laizhou Bay, China	0.19	32.69	10.99	17.38	13.37	50.63	[11]
Tahaddart Estuary, Morocco	0.16	91.83	57.1	34.92	25.55	73.73	[66]
Oualidia Lagoon, Morocco	0.66	102.4	17.7	15.73	10.1	75.8	[18]
Nador Lagoon, Morocco	1.6	71.6	150.8	45.2	135	554.9	[10]
OumEr Bia estuary, Morocco	0.36	9.5	19.6	ND	28	138	[80]
The fishing port of Safi, Morocco	1.2–2.4	ND	45–90	ND	ND	276–552	[67]
Bay of Biscay, Spain	0.08–0.11	2.13–6.16	11.8–21.76	4.17–15.12	6.88–26.23	28.8–66.79	[81]
Upper Continental Crust	0.09	35	25	20	20	71	[82]
The suspended sediment of World Rivers	1.55	133	75.9	74.5	61.1	208	[83]
TEL	0.6	37.3	35.7	18	35	123	[84]
TET	3	100	86	61	170	540	[84]

. The heavy metal concentrations were indeed compared to the sediment quality guideline values, including the threshold effect level (TEL) used to show the concentrations below, where no effect of metal content was detected in sediment on aquatic organisms and the toxic effect threshold (TET) utilized to indicate the heavy metals concentrations, above which substantial effects are likely to occur [77]. Heavy metal concentrations in Safi Bay sediments are less significant than the TELs values in Table 4; therefore, they do/did not present a toxicity risk to marine organisms living in these sediments.

3.3. Correlation among Metals

The Pearson correlation among the heavy metals results is shown in Table 5. The results indicate no significant correlation among heavy metals measured in Safi Bay sediment, suggesting a different origin of these metals in the bay in good accordance with their inhomogeneous distribution along the bay. Only Cu shows a highly significant correlation with Pb (p < 0.01), while Cu, Cr, and Zn indicate significant correlations (p < 0.05), which is in good accordance with Kouali et al.’s (2022) [38] findings. These significant correlations among Cu, Cr, and Zn may signify similar chemical properties, a similar degree of contamination, or derived from the same sources [85,86].

As shown in

Table 6. Pearson correlation matrix of studied heavy metals, sand, mud, and CaCO₃ in Safi Bay.

Variables	Cd (mg/kg)	Cr (mg/kg)	Cu (mg/kg)	Ni (mg/kg)	Pb (mg/kg)	Zn (mg/kg)	Sand (%)	Mud (%)	%CaCO3
Cd (mg/kg)	1.00
Cr (mg/kg)	−0.07	1.00
Cu (mg/kg)	0.27	0.62 *	1.00
Ni (mg/kg)	0.05	−0.02	0.12	1.00
Pb (mg/kg)	0.44	0.32	0.83 **	0.08	1.00
Zn (mg/kg)	0.34	0.45	0.68 **	0.25	0.53 *	1.00
Sand (%)	−0.18	−0.71 **	−0.82 **	−0.09	−0.70 **	−0.50	1.00
Mud (%)	0.18	0.71 **	0.82 **	0.09	0.70 **	0.50	−1.00	1.00
%CaCO3	−0.35	−0.26	−0.78 **	−0.05	−0.81 **	−0.48	0.63 *	−0.63 *	1.00

Significant correlation marked (** p < 0.01) and (* p < 0.05).

, a positive and significant correlation between Cr, Cu, and Pb with mud reveals the affinity of these metals to fine elements. The correlation matrix shows a negative and significant correlation observed for Cr, Cu, Pb, and Zn with CaCO₃ and sand, except for Cr and CaCO₃ (non-significant negative value), indicating that these metals are not associated with CaCO₃.

The Dendrogamme (Figure 4) based on Ward’s method [87] shows three different clusters: Cluster 1 (sand and CaCO₃), Cluster 2 (Pb and Zn), and Cluster 3 (Cr, Ni, Cd, Cu, and mud).

3.4. Assessment of Heavy Metal Contamination

The results of the calculated indices CF, DC, mCd, and PLI for the sediment collected from Safi Bay are shown in Table 6. Except for S17 and S29, which show considerable contamination by Cd, almost all the stations display low to moderate contamination by Cd CF > 3. The contamination factor for Pb indicates considerable contamination in stations S3, S7, S8, S18, S23, S29, S30, and S38, suggesting an anthropogenic origin, while moderate contamination was recorded in the other sampling sites. Other investigated heavy metals show low contamination, suggesting that Cd and Pb mainly contaminate the study area, which is in good accordance with [38], where the Cd exhibited moderate contamination of coastal sediment from Jorf Lihoudi in Safi. Both cadmium and lead indicated a strong positive correlation and considerable contamination, reflecting similar sources into the sediment bay. In addition, the inhomogeneous distribution of contamination levels along the bay reflects different origins of heavy metals, such as domestic, industrial, and ship effluent. Industrial- and port-activities-related waste are reported as the main activities having heavy impacts on the bay environment [88]. The management of this ecosystem is a major concern as 70% of the released waste is thrown into the bay without pre-treatment [88]. In addition, the navigation activities may have potential impacts on this ecosystem environment by causing physical modifications of seabed substrate and habitats [89]. Ships were first identified as a major source of metal pollution in the 1970’s, particularly copper [90].

A considerable degree of contamination was recorded in S23 and S29, while the other stations indicate low and moderate contamination in good accordance with the CF values.

The PLI values calculated for each station are shown in

Table 7. Metal contamination factors (CFs), degree of contamination (DC), modified degree of contamination (mCd), and pollution load indices (PLIs) for sediments of all sites studied in Safi Bay.

Sites	Contamination Factor (Cf)						Degree of Contamination (DC)	Modified Degree of Contamination (mCd)	PLI
	Cd	Cr	Cu	Ni	Pb	Zn
S1	2.53	0.00	0.05	0.14	2.70	0.29	5.72	0.95	0.19
S2	1.78	0.00	0.04	0.09	1.33	0.24	3.49	0.58	0.14
S3	1.62	0.21	0.09	0.08	3.73	0.51	6.23	1.04	0.41
S4	1.68	0.00	0.05	0.06	2.25	0.25	4.29	0.72	0.15
S5	2.49	0.27	0.07	0.22	2.26	0.36	5.66	0.94	0.45
S6	1.69	0.19	0.07	0.06	2.52	0.48	5.01	0.84	0.35
S7	2.90	0.00	0.07	0.16	3.32	0.51	6.97	1.16	0.25
S8	2.81	0.00	0.07	0.16	3.42	0.34	6.81	1.13	0.23
S9	1.97	0.09	0.04	0.02	2.83	0.29	5.24	0.87	0.22
S10	1.74	0.00	0.03	0.04	1.91	0.20	3.93	0.65	0.12
S12	1.86	0.00	0.05	0.04	2.30	0.30	4.56	0.76	0.15
S13	1.55	0.61	0.05	0.13	1.81	0.39	4.54	0.76	0.40
S15	1.67	0.00	0.06	1.08	2.39	0.75	5.95	0.99	0.30
S16	1.54	0.09	0.05	0.12	1.78	0.56	4.13	0.69	0.30
S17	3.04	0.16	0.07	0.15	2.58	1.82	7.83	1.30	0.54
S18	1.63	0.00	0.14	0.19	3.74	0.93	6.62	1.10	0.28
S19	1.76	0.04	0.04	0.05	1.60	0.26	3.75	0.63	0.20
S20	1.61	0.00	0.07	0.09	2.73	0.44	4.94	0.82	0.18
S21	1.61	0.00	0.06	0.05	1.74	0.33	3.79	0.63	0.14
S22	1.64	0.24	0.07	0.07	2.08	0.53	4.62	0.77	0.36
S23	1.93	1.21	0.23	0.15	5.07	1.43	10.01	1.67	0.92
S28	1.98	0.00	0.04	0.03	2.57	0.33	4.95	0.83	0.14
S29	4.01	0.01	0.15	0.17	4.89	0.85	10.08	1.68	0.36
S30	1.65	0.00	0.11	0.16	4.28	0.86	7.07	1.18	0.27
S32	1.87	0.00	0.04	0.12	2.88	0.40	5.31	0.88	0.19
S33	1.59	0.00	0.04	0.07	1.89	0.31	3.91	0.65	0.14
S34	1.53	0.00	0.05	0.07	2.42	0.35	4.42	0.74	0.15
S38	1.70	0.00	0.05	0.08	3.08	0.29	5.20	0.87	0.16
Mean	1.97	0.11	0.07	0.14	2.72	0.52	5.54	0.92	0.27
Min	1.53	0.00	0.03	0.02	1.33	0.20	3.49	0.58	0.12
Max	4.01	1.21	0.23	1.08	5.07	1.82	10.08	1.68	0.92

Bold values represent significant contamination.

and Figure 5. Almost all studied stations indicate no pollution by heavy metals, where the PLI values are inferior to 1. These results may be explained by the strong dilution and dispersion of heavy metal concentrations in seawater because of the strong agitation. The authors in [67] reported high PLI values for sediment retrieved inside the Safi harbor where the sediment grain size is finer, allowing for the accumulation of heavy metals. In contrast, almost all investigated samples were sandy with a high CaCO₃ content, suggesting that those factors are not controlling the distribution and accumulation of the heavy metals in Safi Bay sediments. Thus, further investigation of sediments mainly from the harbor area is needed to provide a clearer picture of the pollution levels and sources.

The geo-accumulation index (Igeo)-calculated values for the investigated sediment are shown in

Table 8. Geo-accumulation index (Igeo) for metals in Safi Bay.

Sites	Geo-Accumulation Index (Igeo)
	Cd	Cr	Cu	Ni	Pb	Zn
S1	0.75	−8.80	−4.85	−3.40	0.85	−2.37
S2	0.25	−8.72	−5.27	−4.02	−0.18	−2.62
S3	0.11	−2.86	−4.04	−4.23	1.31	−1.56
S4	0.16	−8.81	−4.94	−4.64	0.59	−2.56
S5	0.73	−2.50	−4.50	−2.76	0.59	−2.05
S6	0.17	−2.95	−4.35	−4.68	0.75	−1.65
S7	0.95	−8.60	−4.42	−3.19	1.15	−1.55
S8	0.90	−8.65	−4.39	−3.21	1.19	−2.12
S9	0.39	−4.08	−5.25	−6.16	0.92	−2.36
S10	0.21	−8.75	−5.57	−5.25	0.35	−2.88
S12	0.31	−8.66	−4.89	−5.08	0.61	−2.30
S13	0.04	−1.29	−4.89	−3.53	0.27	−1.95
S15	0.15	−8.82	−4.56	−0.47	0.67	−1.00
S16	0.04	−4.12	−4.90	−3.66	0.25	−1.43
S17	1.02	−3.19	−4.38	−3.32	0.78	0.28
S18	0.12	−8.85	−3.46	−2.96	1.32	−0.69
S19	0.23	−5.09	−5.29	−4.80	0.09	−2.52
S20	0.10	−8.86	−4.36	−4.13	0.86	−1.77
S21	0.10	−8.86	−4.75	−5.05	0.22	−2.17
S22	0.12	−2.64	−4.45	−4.43	0.47	−1.51
S23	0.36	−0.31	−2.70	−3.31	1.76	−0.07
S28	0.40	−8.57	−5.24	−5.57	0.77	−2.18
S29	1.42	−8.13	−3.32	−3.10	1.71	−0.82
S30	0.13	−8.83	−3.76	−3.19	1.51	−0.80
S32	0.31	−8.65	−5.09	−3.62	0.94	−1.92
S33	0.08	−8.88	−5.11	−4.38	0.34	−2.29
S34	0.02	−8.94	−4.83	−4.48	0.69	−2.12
S38	0.18	−8.79	−5.02	−4.20	1.04	−2.37
Mean	0.35	−6.65	−4.59	−3.96	0.78	−1.76
Max	1.42	−0.31	−2.70	−0.47	1.76	0.28
Min	0.02	−8.94	−5.57	−6.16	−0.18	−2.88

Bold values represent significant contamination.

. Almost all sampling sites show no pollution by Cr, Cu, Ni, and Zn. Only Cd and Pb show values that fluctuate between 0 and 2, indicating weak and moderate pollution, which is in good accordance with other calculated indices.

The ecological risk index $E_r^i$ was used to assess the risk associated with heavy metal pollution in Safi Bay. The results of $E_r^i$ calculation are presented in

Table 9. Potential ecological risk factors ($E_r^i$) and potential ecological risk index (RI) for studied metals in Safi Bay.

Sites	Ecological Risk Factor (${\mathit{E}}_{\mathit{r}}^{\mathit{i}}$)						RI	RI Grade
	Cd	Cr	Cu	Ni	Pb	Zn
S1	50.60	0.01	0.32	0.78	8.44	0.21	60.36	Low
S2	35.60	0.01	0.24	0.51	4.14	0.18	40.68	Low
S3	32.30	0.46	0.56	0.44	11.64	0.38	45.77	Low
S4	33.50	0.01	0.30	0.33	7.04	0.19	41.36	Low
S5	49.80	0.59	0.41	1.22	7.05	0.27	59.33	Low
S6	33.70	0.43	0.45	0.32	7.88	0.35	43.14	Low
S7	57.90	0.01	0.43	0.91	10.38	0.38	70.00	Low
S8	56.10	0.01	0.44	0.89	10.70	0.25	68.39	Low
S9	39.30	0.20	0.24	0.12	8.85	0.22	48.92	Low
S10	34.80	0.01	0.19	0.22	5.96	0.15	41.33	Low
S12	37.10	0.01	0.31	0.25	7.18	0.22	45.07	Low
S13	30.90	1.36	0.31	0.71	5.67	0.29	39.24	Low
S15	33.30	0.01	0.39	5.98	7.46	0.55	47.69	Low
S16	30.80	0.19	0.31	0.66	5.57	0.41	37.94	Low
S17	60.80	0.36	0.44	0.83	8.06	1.34	71.83	Low
S18	32.50	0.01	0.83	1.06	11.67	0.68	46.76	Low
S19	35.10	0.10	0.23	0.30	5.00	0.19	40.93	Low
S20	32.20	0.01	0.45	0.47	8.52	0.32	41.97	Low
S21	32.20	0.01	0.34	0.25	5.44	0.25	38.48	Low
S22	32.70	0.53	0.42	0.39	6.50	0.39	40.93	Low
S23	38.50	2.69	1.41	0.84	15.85	1.05	60.33	Low
S28	39.60	0.01	0.24	0.17	8.02	0.24	48.29	Low
S29	80.10	0.01	0.92	0.96	15.29	0.62	97.91	Low
S30	32.90	0.01	0.68	0.91	13.38	0.64	48.51	Low
S32	37.30	0.01	0.27	0.67	9.00	0.29	47.54	Low
S33	31.80	0.01	0.26	0.40	5.92	0.23	38.61	Low
S34	30.50	0.01	0.32	0.37	7.57	0.25	39.03	Low
S38	33.90	0.01	0.28	0.45	9.63	0.21	44.48	Low
Mean	39.49	0.25	0.43	0.76	8.49	0.38	49.81	Low
$E_r^i$ grade	Low	Low	Low	Low	Low	Low	Low

. The values of $E_r^i$ ranged from 30.50 to 80.10 for Cd, with an average of 39.49; from 0.01 to 2.69 for Cr, with an average of 0.25; from 0.19 to 1.41 for Cu, with an average of 0.43; from 0.12 to 5.98 for Ni, with an average of 0.76; from 4.14 to 15.85 for Pb, with an average of 8.49; and from 0.18 to 1.34 for Zn, with an average of 0.38. The ecological risk index $E_r^i$ of the investigated heavy metals was less than 40, reflecting a low ecological risk.

4. Conclusions

This study analyzed the spatial distribution of Cr, Zn, Cu, Ni, and Pb in Safi Bay sediments. The results showed an inhomogenous distribution of heavy metals along the bay, suggesting different sources of these metals. However, the concentrations of heavy metals were more elevated in the sampling sites located near the city and the Safi Port, while lower concentrations were recorded in the northern part of Safi City where human activities are less intense.

The use of environmental indices, including CF, DC, mCd, PLI, and $E_r^i$, allowed for the gathering of an understanding of the pollution levels of the bay sediments. The results revealed that the Safi Bay sediment is mainly contaminated by Cd and Pb according to the CF and DC factors. The PLI values were almost >1, suggesting that Safi Bay is an unpolluted area. However, the obtained results imply that there should be a further investigation of the bay sediments, mainly the sediment cores, which would allow for a better understanding of the pollution history in the study area to be obtained.

Factors such as the hydrodynamic conditions, currents, waves, and resuspension/deposition characterizing the study area need to be analyzed to obtain a better understanding of the pollutant spatial distribution and their concentration fluctuations sources.

This study is the first investigation of the contamination of Safi Bay sediments by heavy metals. Thus, the present work provides a database for future investigations of the bay’s environmental quality, mainly its ecological and socioeconomic interests, contributing towards developing conservation and protection projects for the sustainable use of its related ecosystem services.