Assessment of Heavy Metal Contamination and Ecological Risk in Mangrove Marine Sediments Inside and Outside Zhanjiang Bay: Implications for Conservation

Abstract

Mangrove ecosystems effectively sequester heavy metals, making their sediment distribution and ecological risk assessment vital for coastal protection. This study focuses on the mangrove forests on both sides of the Donghai Island embankment in Huguang Town, Zhanjiang Bay, analyzing the content, spatial distribution, and potential ecological risks of heavy metals (Cu, Zn, Cd, Pb, Cr, As, Hg) in surface and vertical sediment profiles through systematic sampling. The results show higher, more uniform heavy metal concentrations inside the bay, with Cd, Cr, and As showing significant accumulation, while outside, levels are lower but with Pb and As at sites like DW-Z-1 and DW-Z-4 nearing Class I Marine Sediment Quality Guideline limits. Vertically, concentrations inside the bay increase with depth due to long-term pollution, geoaccumulation and potential ecological risk indices, Cd emerges as the primary pollutant, posing a high risk (Er Class 3) inside the bay (RI Class 2) and a low to moderate risk outside. Pollution sources inside stem from industrial, urban, and aquaculture inputs, while tidal dynamics and mangroves pose purification mitigate risks outside. This study underscores Cd control needs and supports the ecological conservation of Zhanjiang Bay.

1. Introduction

Heavy metal contamination, induced by the presence of heavy metal elements or their compounds, represents a pervasive environmental challenge that has garnered global attention due to its persistence, bioaccumulative nature, and potential toxicological impacts within natural ecosystems [1,2,3,4,5,6]. Within estuarine and nearshore environments, heavy metals are ubiquitously distributed across water bodies, sediments, and biota, posing a significant threat to ecosystem integrity through intricate biogeochemical cycling processes [7]. Mangrove forests, emblematic of wetland ecosystems thriving in the low-energy tidal zones of tropical and subtropical coastlines, assume a pivotal role in global coastal conservation, owing to their distinctive woody plant community structures and multifaceted ecological functions [8]. Heavy metals originate from tidal flows, riverine inputs, atmospheric deposition, and anthropogenic activities through mechanisms such as root uptake, sediment particle adsorption, and organic matter complexation. Mangrove sediments are typically rich in organic matter, which forms complexes with metals such as copper (Cu), zinc (Zn), and cadmium (Cd), significantly affecting their bioavailability and mobility within the sedimentary environment [9,10,11,12]. This association underscores the need to consider organic matter dynamics when assessing heavy metal contamination in mangrove ecosystems. Consequently, variations in heavy metal concentrations within mangrove sediments not only mirror the dynamic evolution of regional environmental quality but also provide an indispensable foundation for ecological risk assessment and the formulation of conservation strategies.

Established in 1997, the Zhanjiang National Mangrove Nature Reserve in Guangdong Province stands as a cornerstone of mangrove conservation in southern China, with the extensive mangrove forests within Zhanjiang Bay forming its principal constituent [13]. The mangroves of Huguang Town in Zhanjiang rely on coastal silty sediments for their development, sustaining a rich floristic assemblage and a diverse array of fauna, thereby contributing significantly to regional biodiversity preservation and the provision of ecological services [14,15,16]. However, in recent years, escalating anthropogenic pressures—most notably the rapid expansion of oyster aquaculture and the burgeoning growth of high-pollution industries such as steel, chemical, and petrochemical production along the coast—have subjected Zhanjiang Bay to intensifying heavy metal contamination [17,18,19,20,21]. These pollutants are introduced into the bay via multiple pathways, including wastewater discharges, maritime activities, and agricultural runoff, exacerbating tidal zone erosion, diminishing intertidal areas, and precipitating a marked decline in mangrove coverage, thus severely undermining ecosystem stability [22,23,24,25]. Against this backdrop, the restoration of mangrove ecosystems has emerged as an urgent environmental imperative.

While global studies have addressed heavy metal pollution in mangroves, few integrate spatial and vertical profiles to assess ecological risks in semi-enclosed bays like Zhanjiang Bay [26,27,28,29]. Previous research has often focused on individual pollutants or surface sediments, lacking a comprehensive evaluation of heavy metal pollution in mangroves of Zhanjiang Bay, particularly regarding spatial disparities, vertical distributions, and ecological risks. To address these gaps, this study targets the mangrove forests along the Donghai Island embankment in Huguang Town, Zhanjiang Bay. We quantify heavy metal concentrations and apply the geoaccumulation index (I_geo) and potential ecological risk index (RI) to analyze their spatial distribution, sources, and ecological impacts. This work aims to clarify the links between pollution characteristics and environmental consequences, providing new insights to bridge research gaps and a scientific foundation for the conservation and sustainable management of mangrove ecosystems of Zhanjiang Bay.

2. Samples and Experimental Methods

2.1. Study Area

The Huguang Mangrove Nature Reserve, located in the easternmost part of the Zhanjiang National Mangrove Nature Reserve in Guangdong Province, lies between 110°6′35″ E–110°30′19″ E and 20°48′5″ N–21°7′53″ N. Established in 1997, it covers approximately 1200 hectares. The reserve experiences a typical maritime monsoon climate, with an annual average temperature of 22.4 °C, annual precipitation of 1816 mm (80% occurring from May to September), and an average relative humidity of 81.8%. It supports a diverse mangrove ecosystem dominated by species such as Kandelia obovata, Sonneratia apetala, Excoecaria agallocha, and Lumnitzera racemosa, providing critical habitats for migratory birds and marine species [30,31,32,33]. However, the reserve faces significant anthropogenic pressures, including wastewater from surrounding aquaculture ponds, urban domestic sewage, industrial effluents from steel and petrochemical industries, maritime pollution, and agricultural runoff [34,35,36,37,38,39]. These pollution sources contribute to heavy metal accumulation and ongoing degradation of mangrove habitats.

2.2. Sample Collection

Sediment samples were collected in December 2022 from mangrove areas along both sides of the Donghai Island embankment, with nine sampling stations established (see Figure 1). Sediment cores were collected using PVC tubes, with core lengths ranging from 10 to 30 cm depending on the sediment depth and compaction at each station. Specifically, cores from stations DHD-Z-1 to DHD-Z-4 (inside the bay) reached depths of 25 cm, while cores from stations DW-Z-1 to DW-Z-5 (outside the bay) ranged from 10 to 30 cm due to differences in sediment accumulation and tidal influence. Each core was sectioned at 5 cm intervals for analysis, yielding a total of 42 samples (Supplementary Table S1) [40]. The samples were then placed in polyethylene sealed bags and stored under frozen conditions to ensure analytical integrity.

2.3. Sample Preparation and Analysis

Sediment samples were lyophilized in a vacuum freeze-dryer, pulverized using an agate mortar, and sieved through a 200-mesh nylon sieve. For the digestion process, 0.1000 g of sediment sample was accurately weighed and placed into a polytetrafluoroethylene (PTFE) digestion vessel. Then, 6 mL of aqua regia (HNO₃:HCl = 3:1) and 2 mL of hydrofluoric acid (HF) were added. The samples were digested using a microwave digestion system at 180 °C for 30 min, followed by acid evaporation on a hot plate at 140 °C. The digested samples were then diluted to a final volume of 50 mL with 2% HNO₃ and filtered through a 0.22 μm membrane prior to analysis. Concentrations of Cu, Zn, Pb, Cr, Cd, and As were quantified using an inductively coupled plasma mass spectrometer (ICP-MS, Agilent 7500Cx, Agilent Technologies, Santa Clara, CA, USA), with a detection limit of 0.015 mg·kg⁻¹. Total Hg was determined following the national standard GB/T 22105.1-2008 [40], digesting 0.1 g (weighed to 0.0001 g) of sieved sediment in aqua regia and analyzing it with an atomic fluorescence spectrometer (SK-Ruixi, Beijing Jinsuokun Technology Development Co., Ltd., Beijing, China), with a detection limit of 0.002 mg·kg⁻¹. Quality control was ensured using GBW 07314 reference material, achieving recovery rates of 80.6–122% and uncertainties of 0.012–4.0%. A total of 42 sediment samples (Supplementary Table S1) were analyzed, with all parameters validated to meet regulatory standards [41].

From the 42 sediment samples selected (Supplementary Table S1), the full procedural analysis of each certified reference material confirmed that all parameter measurements resided within the uncertainty bounds of recommended values, adhering to established standards. The experiment utilized the certified reference material GBW 07314 for offshore marine sediments (

Table 1. Certified reference material table for offshore marine sediment composition analysis.

Certified Reference Material GBW07314	Element	Cu	Zn	Cd	Pb	Cr	As	Hg
		(mg·kg−1)
	Measured Value 1	31.30	88.20	0.206	24.40	69.40	10.10	0.059
	Measured Value 2	28.30	82.20	0.214	23.60	77.40	10.90	0.055
	Certified Value	31.00	87.00	0.200	25.00	86.00	10.30	0.048
	Uncertainty	4.00	2.00	0.040	4.00	4.00	1.40	0.012
	Recovery 1	101.00%	101.00%	103.00%	97.60%	80.60%	98.50%	122.00%
	Recovery 2	91.40%	94.50%	107.00%	94.50%	90.00%	106.00%	115.00%

).

2.4. Research Methods

2.4.1. Geoaccumulation Index Method

This investigation employs the geoaccumulation index (I_geo), as proposed by the German scholar Muller [42], to assess heavy metal pollution within the sediments of the study area. The computational formula is articulated as follows:

$$I_{geo}={\log }_2[C_n/(1.5\times B_n)]$$

where:

$I_{geo}$ denotes the geoaccumulation index;

$C_n$ represents the measured concentration of heavy metal n in the sediment;

$B_n$ denotes the background value of heavy metals, here represented by the concentrations recorded in the coastal sediments of western Guangdong Province in 1982 (

Table 2. Reference values for heavy metal concentrations in marine sediments.

Reference Standard	Cu	Zn	Cd	Pb	Cr	As	Hg
	(mg·kg−1)
Class I Marine Sediment Quality Guideline [43]	35	150	0.50	60	80	20	0.200
Heavy metals in sediments from the coastal area of western Guangdong Province in 1982 [44]	13	52	0.08	33	103	10	0.109

). At that time, Zhanjiang had undergone minimal industrial development; therefore, its heavy metal levels are considered suitable as baseline values.

The geoaccumulation index is stratified into seven distinct levels to characterize the extent of sediment contamination, with detailed classification criteria delineated in

Table 3. Classification of sediment pollution levels using the geoaccumulation index (I_geo).

Pollution Level	Sediment Igeo Range	Igeo Class
Unpolluted	Igeo < 0	0
Unpolluted to Moderately polluted	0 ≤ Igeo < 1	1
Moderately polluted	1 ≤ Igeo < 2	2
Moderately to Strongly polluted	2 ≤ Igeo < 3	3
Strongly polluted	3 ≤ Igeo < 4	4
Strongly to Extremely polluted	4 ≤ Igeo < 5	5
Extremely polluted	Igeo ≥ 5	6

.

2.4.2. Potential Ecological Risk Index Method

This investigation adopts the potential ecological risk index method, developed by Swedish scholar Hakanson [45], to assess the ecological risks posed by heavy metals in surface sediments of the study area. The pertinent equations are as follows:

$$\begin{array}{c}{C}_{\mathrm{d}}={\displaystyle \frac{c^i}{c_n^i}}\hfill \\ C_{\mathrm{d}}={\displaystyle \sum _i^m{C}_f^i}\hfill \\ E_r^i=T_r^i\cdot C_f^i\hfill \\ E_{RI}={\displaystyle \sum _i^m{E}_r^i}={\displaystyle \sum _i^m{T}_r^i}\cdot C_f^i={\displaystyle \sum _i^m{T}_r^i}\cdot {\displaystyle \frac{c^i}{c_n^i}}\hfill \end{array}$$

where the variables are defined as follows:

$C_f^i$ represents the contamination factor of heavy metal i in the sediment;

$C^i$ indicates the measured concentration of heavy metal i in the sediment;

$C_n^i$ denotes the reference value for heavy metal i, herein employing the heavy metal concentrations from coastal sediments of western Guangdong Province in 1982 [44];

$E_f^i$ signifies the potential ecological risk factor for heavy metal i;

$T_f^i$ refers to the toxicity response coefficient of heavy metals, with values assigned as 40 for Hg, 30 for Cd, 10 for As, 5 for Cu, 5 for Pb, 2 for Cr, and 1 for Zn;

$E_{RI}$ represents the comprehensive potential ecological risk index for multiple heavy metals in the sediment.

The potential ecological risk index (RI) is classified into levels to delineate pollution severity, with specific grading standards provided in

Table 4. Hierarchical classification of ecological risk levels based on potential ecological risk factors (Er) and index (RI) for heavy metals in sediments.

Potential Ecological Risk Factor (Er)	Risk Class	Potential Ecological Risk Index (RI)	Risk Class
Er < 40	Low	RI < 150	Low
40 ≤ Er < 80	Moderate	150 ≤ RI < 300	Moderate
80 ≤ Er < 160	High	300 ≤ RI < 600	High
160 ≤ Er < 320	Very High	600 ≤ RI < 1200	Very High
320 ≤ Er	Extremely High	1200 ≤ RI	Extremely High

.

This study integrates the geoaccumulation index (I_geo) and potential ecological risk index (RI) methods to comprehensively evaluate heavy metal pollution in the surface sediments of the mangrove study area. The RI method holistically assesses the toxicity response coefficients of heavy metals and their potential ecological hazards, encompassing physical, chemical, and biological environmental factors. The synergy of these two approaches enables a more thorough and objective depiction of the heavy metal pollution status and associated ecological risks in the study region. Given that the predominant zonal soil in the study area is lateritic red soil, the heavy metal concentrations from the 1982 coastal sediments of western Guangdong Province were selected as the reference values for this investigation.

2.5. Data Processing

This study utilized SPSS 27.0 and Origin 2021 software for data processing and statistical analysis. Initially, the mass fractions of heavy metals were subjected to a normality test. Subsequently, the correlations among heavy metals were examined using Pearson correlation analysis. To further elucidate the distribution characteristics of heavy metal elements, principal component analysis (PCA) was employed for an in-depth investigation. Additionally, graphical representations were generated using CorelDraw 2022 (v24.5) and ArcGIS 10.8 software.

3. Results

3.1. Characteristics of Heavy Metal Concentrations in Surface Sediments of Mangrove Forests Adjacent to the Donghai Island Embankment, Huguang Town, Zhanjiang

Based on the data in

Table 5. Spatial distribution and statistical parameters of heavy metals in Zhanjiang Bay mangrove surface sediments (0–5 cm).

Sample	Cu	Zn	Cd	Pb	Cr	As	Hg
Within Zhanjiang Bay
DHD-Z-1-1	23.10	93.06	0.287	22.82	86.34	18.20	0.140
DHD-Z-2-1	24.13	99.76	0.303	14.71	89.00	18.36	0.133
DHD-Z-3-1	21.36	91.74	0.288	17.87	84.27	17.69	0.130
DHD-Z-4-1	23.61	100.74	0.275	12.79	96.77	19.65	0.135
Statistical Summary (Within Bay)
Minimum	21.36	91.74	0.28	12.79	84.27	17.69	0.130
Maximum	24.13	100.74	0.30	22.82	96.77	19.65	0.140
Mean	23.05	96.33	0.29	17.05	89.10	18.47	0.134
Std. Dev.	1.21	4.58	0.01	4.38	5.47	0.83	0.004
Coeff. Var. (%)	5.23	4.81	3.99	27.76	6.35	4.43	3.480
Outside Zhanjiang Bay
DW-Z-1-1	22.34	85.78	0.180	23.45	94.74	22.32	0.238
DW-Z-2-1	18.96	79.61	0.183	28.01	83.09	13.91	0.081
DW-Z-3-1	20.43	81.33	0.172	21.78	91.11	21.00	0.081
DW-Z-4-1	22.96	93.71	0.227	29.49	97.49	19.94	0.081
DW-Z-5-1	15.12	62.81	0.130	24.16	72.18	16.29	0.067
Statistical Summary (Outside Bay)
Minimum	15.12	62.81	0.13	21.78	72.18	13.91	0.067
Maximum	22.96	93.71	0.23	29.49	97.49	22.32	0.238
Mean	19.96	80.65	0.18	25.38	87.72	18.69	0.110
Std. Dev.	3.13	13.77	0.03	3.24	10.23	3.49	0.072
Coeff. Var. (%)	16.27	14.16	20.50	13.48	11.98	18.17	61.90
Method Detection Limit	0.008	0.160	0.015	0.070	0.070	0.180	0.002

Note: Concentrations in mg·kg⁻¹. Full dataset available in Supplementary Table S1.

and spatial illustrations in Figure 2, the distribution characteristics of heavy metal concentrations across sampling stations within and outside Zhanjiang Bay are as follows:

(1)

Copper (Cu) distribution patterns: Within the bay, surface sediment samples exhibit Cu concentrations ranging from 21.36 to 24.13 mg·kg⁻¹, with low variability (coefficient of variation: 5.23%). Outside the bay, Cu concentrations range from 15.12 to 22.96 mg·kg⁻¹, with the lowest value at station DW-Z-5.

(2)

Zinc (Zn) distribution patterns: Inside the bay, Zn concentrations range from 91.74 to 100.74 mg·kg⁻¹. Outside, Zn levels vary from 62.81 to 93.71 mg·kg⁻¹, with the lowest at station DW-Z-5.

(3)

Cadmium (Cd) distribution patterns: Inside the bay, Cd concentrations range from 0.275 to 0.303 mg·kg⁻¹. Outside, Cd levels range from 0.130 to 0.227 mg·kg⁻¹, with the minimum at station DW-Z-5.

(4)

Lead (Pb) distribution patterns: Inside the bay, Pb concentrations range from 12.79 to 22.82 mg·kg⁻¹. Outside, Pb levels range from 21.78 to 29.49 mg·kg⁻¹, with the highest at station DW-Z-4.

(5)

Chromium (Cr) distribution patterns: Inside the bay, Cr concentrations range from 84.27 to 96.77 mg·kg⁻¹. Outside, Cr levels range from 72.18 to 97.49 mg·kg⁻¹, with the lowest at station DW-Z-5.

(6)

Arsenic (As) distribution patterns: Inside the bay, As concentrations range from 17.69 to 19.65 mg·kg⁻¹. Outside, As levels vary from 13.91 to 22.32 mg·kg⁻¹, with the peak at station DW-Z-1.

(7)

Mercury (Hg) distribution patterns: Inside the bay, Hg concentrations range from 0.130 to 0.140 mg·kg⁻¹. Outside, Hg levels range from 0.067 to 0.238 mg·kg⁻¹, with the highest at station DW-Z-1.

Heavy metal concentrations in surface sediments within Zhanjiang Bay are generally higher and more uniform, with mean concentrations of Cu at 23.05 mg·kg⁻¹, Zn at 96.33 mg·kg⁻¹, Cd at 0.29 mg·kg⁻¹, Pb at 17.05 mg·kg⁻¹, Cr at 89.10 mg·kg⁻¹, As at 18.47 mg·kg⁻¹, and Hg at 0.134 mg·kg⁻¹. Outside the bay, concentrations show greater variability, with averages of Cu at 19.96 mg·kg⁻¹, Zn at 80.65 mg·kg⁻¹, Cd at 0.18 mg·kg⁻¹, Pb at 25.38 mg·kg⁻¹, Cr at 87.72 mg·kg⁻¹, As at 18.69 mg·kg⁻¹, and Hg at 0.110 mg·kg⁻¹. Hg exhibits a high coefficient of variation (61.90%) outside the bay.

3.2. Ecological Risk Assessment of Heavy Metals

3.2.1. Geoaccumulation Index Analysis of Heavy Metal Pollution in Zhanjiang Bay Mangrove Surface Sediments

The analysis of the geoaccumulation index (I_geo) for heavy metals in surface sediments of mangrove forests inside and outside Zhanjiang Bay (

Table 6. Geoaccumulation index (I_geo) values for heavy metals in surface sediments of mangrove ecosystems within and outside Zhanjiang Bay, South China.

Study Area	Site	Cu	Zn	Cd	Pb	Cr	As	Hg
Within the bay	DHD-Z-1	0.24	0.25	1.26	−1.12	−0.84	0.28	−0.22
	DHD-Z-2	0.31	0.36	1.34	−1.75	−0.80	0.29	−0.30
	DHD-Z-3	0.13	0.23	1.27	−1.47	−0.87	0.24	−0.34
	DHD-Z-4	0.28	0.37	1.20	−1.95	−0.67	0.39	−0.28
Outside the bay	DW-Z-1	0.20	0.14	0.59	−1.08	−0.71	0.57	0.54
	DW-Z-2	−0.04	0.03	0.61	−0.82	−0.89	−0.11	−1.01
	DW-Z-3	0.07	0.06	0.52	−1.18	−0.76	0.49	−1.01
	DW-Z-4	0.24	0.26	0.92	−0.75	−0.66	0.41	−1.02
	DW-Z-5	−0.37	−0.31	0.11	−1.03	−1.10	0.12	−1.28

) reveals pronounced disparities in pollution levels between the two regions. According to the classification standards outlined in Table 3, within the bay, Cd exhibits I_geo values ranging from 1.20 to 1.34, corresponding to moderate pollution (I_geo Class 2), which underscores a significant accumulation effect for this element. Cu and Zn display I_geo values ranging from 0.13 to 0.37 and 0.23 to 0.37, respectively, indicative of mild pollution (I_geo Class 1), suggesting a relatively minor contamination extent. In contrast, Pb, Cr, and Hg yield negative I_geo values, denoting negligible pollution levels that fall below thresholds of notable concern. As exhibits I_geo values between 0.24 and 0.39.

Outside the bay, Cd I_geo values range from 0.11 to 0.92, spanning mild to moderate pollution levels, with station DW-Z-1 registering an I_geo value of 0.59, indicative of mild pollution. Cu and Zn present I_geo values ranging from −0.37 to 0.24 and −0.31 to 0.26, respectively, reflecting a low degree of contamination. Pb, Cr, and Hg consistently exhibit negative I_geo values, signifying minimal pollution impact. As demonstrates I_geo values fluctuating between −0.11 and 0.57, with considerable variability.

3.2.2. Potential Ecological Risk Factor and Potential Ecological Risk Index Method

The analysis of the potential ecological risk factor (Er) and potential ecological risk index (RI) for heavy metals in surface sediments of mangrove forests inside and outside Zhanjiang Bay (

Table 7. Assessment of potential ecological risk factors (Er) and risk index (RI) for heavy metals in surface sediments of mangrove ecosystems within and outside Zhanjiang Bay, South China.

Study Area	Sample	Potential Ecological Risk Factor (Er)							Potential Ecological Risk Index (RI)	Risk Class
		Cu	Zn	Cd	Pd	Cr	As	Hg
Within the bay	DHD-Z-1	8.88	1.79	107.47	3.46	1.68	18.20	51.56	193.04	Moderate
	DHD-Z-2	9.28	1.92	113.62	2.23	1.73	18.36	48.77	195.91	Moderate
	DHD-Z-3	8.21	1.76	108.18	2.71	1.64	17.69	47.54	187.72	Moderate
	DHD-Z-4	9.08	1.94	103.09	1.94	1.88	19.65	49.39	186.96	Moderate
Outside the bay	DW-Z-1	8.59	1.65	67.57	3.55	1.84	22.32	87.38	192.91	Moderate
	DW-Z-2	7.29	1.53	68.64	4.24	1.61	13.91	29.89	127.13	Low
	DW-Z-3	7.86	1.56	64.61	3.30	1.77	21.00	29.76	129.83	Low
	DW-Z-4	8.83	1.80	85.30	4.47	1.89	19.94	29.69	151.92	Moderate
	DW-Z-5	5.82	1.21	48.59	3.66	1.40	16.29	24.64	101.60	Low

) reveals distinct differences in ecological risk levels between the two regions. According to the pollution classification standards delineated in Table 4, the RI values within the bay range from 186.960 to 195.914 (RI Class 2). Notably, Cd exhibits Er values ranging from 103.09 to 113.62, classifying it as a high-risk element (Er Class 3). Conversely, the Er values for other heavy metals—Cu, Zn, Pb, Cr, As, and Hg—remain below 40.

In contrast, outside the bay, RI values span from 101.603 to 192.907 (RI Class 1), but DW-Z-1 and DW-Z-4 show 192.907 and 151.923 (RI Class 2). Cd Er values outside the bay range from 48.59 to 85.30, with the highest value of 85.30 at DW-Z-1. The Er values for the remaining heavy metals consistently fall below 40.

4. Discussion

4.1. Spatial Distribution of Heavy Metal Concentrations in Surface Sediments

The higher and more uniform heavy metal concentrations inside Zhanjiang Bay compared to outside are likely due to restricted tidal flushing and greater anthropogenic inputs, such as industrial effluents and urban sewage. The heterogeneity outside the bay, with a high coefficient of variation for Hg (61.90%), may result from external factors like tidal dynamics and localized pollution sources. Although concentrations outside the bay are generally lower, Pb and As levels at stations DW-Z-1 and DW-Z-4 approach or exceed the Class I Marine Sediment Quality Guideline (Table 2), indicating localized contamination risks. Inside the bay, Cr and As levels are also near or exceeding this standard, suggesting a higher pollution risk.

4.2. Vertical Distribution Characteristics of Heavy Metal Concentrations in Mangrove Sediments Inside and Outside Zhanjiang Bay

The analysis of the vertical distribution patterns of heavy metal concentrations in mangrove sediments on both sides of Zhanjiang Bay (Figure 3 and Supplementary Table S1) reveals marked disparities between the sediment cores inside and outside the bay. The data points depicted in the figure represent the mean concentrations of samples from identical depths within and beyond the bay. Overall, concentrations of Cu, Zn, Cd, As, and Hg in sediment cores within the bay significantly exceed those outside, whereas differences in Pb and Cr concentrations between the two regions are less pronounced. This distributional disparity is primarily attributable to the multiplicity of anthropogenic pollution sources affecting the bay interior, encompassing industrial effluents, urban domestic sewage, maritime emissions, aquaculture discharges, and agricultural non-point source pollution, which collectively contribute to elevated heavy metal inputs. In contrast, the exterior region, shielded by the Donghai Island embankment, experiences more constrained heavy metal sources, predominantly influenced by aquaculture effluents and tidal dynamics, resulting in comparatively lower total heavy metal loads.

Figure 3 and Supplementary Table S1 reveal a pronounced pollution accumulation effect in sediment cores from mangroves inside Zhanjiang Bay, with the middle to deep layers (10–25 cm) identified as key enrichment zones. Zn, Cd, and As exhibit a consistent increasing trend (Zn by 19.7%, As by 103%), likely due to long-term industrial wastewater inputs and sulfide fixation under anoxic conditions. Pb concentrations remain relatively stable, consistently low, and below background values. Hg peaks at 15–20 cm (0.23 mg/kg), corresponding to the global peak in atmospheric mercury deposition. In contrast, Cu and Cr display minimal fluctuations (<15%), suggesting dominance by natural sources. Sediment cores outside Zhanjiang Bay exhibit strong tidal regulation, with most elements (Cu, Cr, Hg) showing decreasing concentrations with depth (e.g., Cu: 19.96 to 14.26 mg/kg; Hg: 0.11 to 0.08 mg/kg), reflecting the export of fine-grained pollutants. Conversely, As and Cd display slight increases (As: 18.69 to 20.48 mg/kg; Cd: 0.18 to 0.21 mg/kg), yet their levels are only 50–70% of those inside the bay, indicating residual pollution inputs. Lead (Pb) exhibits surface enrichment (25.38 mg/kg at 2.5 cm) followed by a gradual decline, suggesting limited terrestrial sources.

Mangrove sediments in Zhanjiang Bay are predominantly composed of silt and clay, with minor fractions of sand and gravel, as determined by grain size analysis [21]. Silt and clay fractions, due to their high surface area and organic matter content, are effective in adsorbing heavy metals such as Cd and Pb, while sand fractions, though less dominant, can also trap pollutants through physical retention [41].

The observed vertical distribution patterns may also be influenced by biological factors, particularly the bioaccumulation capacity of dominant mangrove species in the region. For instance, Sonneratia apetala exhibits a remarkable capacity to bioaccumulate elements across its organs, with a notably high enrichment of Cu, Zn, and Cr in fine roots [46]. Similarly, Excoecaria agallocha has been identified as a potential bioindicator of heavy metal pollution, particularly for Cu and Hg [47]. This bioaccumulation likely contributes to the observed decrease in Cu, Cr, and Hg concentrations with depth outside the bay, complementing the effect of tidal export.

4.3. Source Analysis of Heavy Metals

It is generally posited that the mass fractions of heavy metal elements and their interrelationships within sediments of a given region exhibit relatively stable characteristics. When sediment origins are analogous or identical, the correlation coefficients among heavy metal elements approach unity, signifying a strong correlation; higher coefficients indicate greater similarity in the sources of these elements [48,49,50,51].

Pearson correlation analyses conducted on seven heavy metals within and outside the study area (

Table 8. Correlation matrix of heavy metal concentrations in mangrove sediments within and outside Zhanjiang Bay, South China, based on statistical analysis.

Study Area	Heavy Metal	Cu	Zn	Cd	Pb	Cr	As	Hg
Within the bay	Cu	1.000
	Zn	0.833	1.000
	Cd	0.191	−0.024	1.000
	Pb	−0.381	−0.822	0.086	1.000
	Cr	0.619	0.860	−0.531	−0.728	1.000
	As	0.618	0.812	−0.590	−0.636	0.992 **	1.000
	Hg	0.424	−0.031	−0.225	0.562	0.109	0.222	1.000
Outside the bay	Cu	1.000
	Zn	0.976 **	1.000
	Cd	0.871	0.955 *	1.000
	Pb	0.230	0.410	0.647	1.000
	Cr	0.993 **	0.963 **	0.847	0.160	1.000
	As	0.683	0.532	0.306	−0.438	0.735	1.000
	Hg	0.487	0.321	0.094	−0.306	0.446	0.598	1.000

Note: ** p < 0.01 (highly statistically significant correlation), * p < 0.05 (statistically significant correlation) based on two-tailed Pearson/Spearman test.

) reveal substantial differences in their interrelationships. Within the bay, sediments demonstrate a robust positive correlation between Cu and Zn (r = 0.833), while Zn exhibits strong positive correlations with Cr and As (r = 0.86 and r = 0.812, respectively). The strong Cr-As correlation (r = 0.992, p < 0.01) within the bay suggests a common origin, potentially linked to steel industry effluents prevalent in the region.

In contrast, Cd displays weaker correlations with other heavy metals and a slight negative correlation with Zn (r = −0.024). Outside the bay, sediments exhibit more pronounced correlations, particularly between Cu and Zn, Cd, and Cr, with Cu and Cr showing an exceptionally strong association (r = 0.993, p < 0.01) and Zn and Cd also highly correlated (r = 0.955, p < 0.05). Furthermore, Cr demonstrates significant positive correlations with both Cu and Zn (r = 0.993 and r = 0.963, p < 0.01, respectively). These findings suggest divergent sources and migration–transformation processes for heavy metals inside and outside the bay. The stronger correlations observed outside the bay may reflect more consistent external inputs, whereas the bay interior appears subject to greater interference from localized pollution sources.

4.4. Ecological Risk Assessment and Implications

The higher ecological risk inside the bay (RI Class 2) compared to outside (mostly RI Class 1) is driven by Cd (Er Class 3), likely due to concentrated anthropogenic inputs. Cd high Er values (103.09–113.62) inside suggest potential toxicity to benthic organisms, warranting further bioassay studies. Outside, moderate risks at DW-Z-1 and DW-Z-4 are linked to localized Pb and As accumulation. The lower risk outside is attributed to mangrove purification through plant uptake and organic matter complexation, which reduce metal bioavailability. These findings highlight the need for targeted Cd control inside the bay.

The cadmium (Cd) potential ecological risk index (Er values ranging from 103.09 to 113.62) in mangrove sediments within Zhanjiang Bay exhibits distinct regional characteristics: it is approximately 10 times higher than those reported for mangroves along the Red Sea coast of Egypt (Er = 11.61) [52], while comparable to pollution levels observed in Yanbu industrial zone mangroves along the Red Sea coast of Saudi Arabia (Er = 7–181) [53]. This spatial distribution pattern likely correlates with anthropogenic factors, including industrial emission intensity and coastal discharge conditions in the region, warranting further pollution source apportionment studies integrated with local industrial distribution analyses.

5. Conclusions

This study systematically analyzed the concentrations, distribution characteristics, and ecological risks of heavy metals (Cu, Zn, Cd, Pb, Cr, As, Hg) in surface sediments of mangrove forests flanking the Donghai Island embankment in Huguang Town, Zhanjiang Bay, elucidating the spatial disparities in heavy metal pollution and its potential environmental implications within this region. The findings are summarized as follows:

(1)

Heavy metal concentrations inside Zhanjiang Bay are higher and more uniform than outside, with Cd, Cr, and As showing significant accumulation. Outside the bay, levels are lower, but Pb and As at stations DW-Z-1 and DW-Z-4 approach Class I Marine Sediment Quality Guideline limits, indicating localized risks. Vertically, concentrations inside the bay increase with depth due to historical pollution, while outside, mangrove bioaccumulation and external inputs regulate levels.

(2)

Geoaccumulation index (I_geo) and potential ecological risk index (RI) assessments identify Cd as the primary pollutant, with a high risk (Er Class 3) inside the bay (RI Class 2) and low to moderate risk outside. Pollution inside stems from industrial, urban, and aquaculture inputs, while tidal dynamics and mangrove purification mitigate risks outside.

(3)

Mangroves of Zhanjiang Bay face pollution pressure, with Cd control prioritized inside the bay. We recommend regulating industrial wastewater, enhancing mangrove replanting, and long-term monitoring to reduce Cd accumulation. These measures aim to mitigate heavy metal pollution threats, supporting the sustainable conservation of the ecosystem.