The Distribution of Dissolved Copper and Natural Organic Ligands in Tropical Coastal Waters Under Seasonal Variation

Abstract

The bioavailability of dissolved copper (Cu) in seawater is influenced by the presence of natural organic matter. Changes in physicochemical conditions, such as pH, temperature, and salinity, can significantly affect the solubility and speciation of copper, thereby impacting the complexation of Cu(II)-binding organic ligands. The concentration of dissolved Cu in the coastal water of Mersing, Malaysia, was detected by anodic stripping voltammetry (ASV). The natural organic copper(II)-binding ligands (CuL) and their conditional stability constants (log K′) were determined by using the competitive ligand exchange–adsorptive cathodic stripping voltammetry method (CLE–AdCSV) in our samples. The in situ parameters, such as pH, temperature, salinity, and dissolved oxygen (DO), were found to be significantly different between sampling periods and indicated the different physical chemical conditions between the sampling periods. However, we found a consistent concentration of dissolved Cu throughout the water column between sampling periods. This suggests that the presence of a strong class of natural organic ligands (L₁) in Mersing’s coastal water maintains the dissolved Cu(II) ions in the water column and prevents the scavenging and precipitation processes under the seasonal variations.

1. Introduction

In coastal areas, the direct runoff and point discharge of anthropogenic activities have resulted in high concentrations of heavy-metal inputs [1,2]. A high input of metals such as copper (Cu) may affect the growth of the natural phytoplankton community. It could be toxic to marine organisms when present in high concentrations, as it produces dangerous reactive oxygen species and disrupts protein function by displacing other metal cofactors [3,4]. However, the existence of organic ligands could maintain the stability of Cu(II) ions in coastal areas. In seawater, dissolved trace metals are predominantly bound to ligands [5,6,7,8,9], which can increase their potential to become bioavailable [10]. The presence of organic ligands buffers the toxicity of free metal ions through complexation.

More than 99.9% of dissolved Cu [7,11,12,13,14] is associated with organic complexing ligands in seawater. Organic complexation is important in stabilizing trace metal ions in the dissolved phase. The bioavailability of trace metals to phytoplankton generally depends on the concentration of free metal ions rather than the total metal concentration [15,16]. Metals must be in a bioavailable state to enter an organic body and interact within the cell [17].

For electrochemical analysis, competitive ligand exchange–adsorptive cathodic stripping voltammetry (CLE-AdCSV) was introduced to measure the binding strength of organic ligands [18]. CLE-AdCSV provides information on the total concentration and conditional binding strength of dissolved organic ligands. Conditional stability constants (Log K′) refer to the measurement of the tightness of the ligand coordinates of a metal ion. It is measured based on the competition against well-characterized artificial ligands with known stability constants during the titrating method. With a lack of known ligand structural characterization, conditional stability constants are the only method used to distinguish between metal–ligand complexes and their origin in seawater [19]. Types of ligands (L) are classified based on the value of Log K′. In general, ligands can be classified into different classes, where L₁ (log K′ > 12) is considered a strong ligand and L₂ (log K′ < 12) is a weak ligand. To date, both strong and weak ligands have been found in coastal areas, with values of log K′ between 11 and 16 [12,13,20,21]. Studies have suggested that thiol, humic compounds, and protein-based phytoplankton exudates make up the majority of organic Cu-binding ligands [22].

In Southeast Asia, wind flow from the Pacific Ocean passes through the South China Sea towards the southwest between November and February, which is known as a northeast (NE) monsoon. On the east coast of Peninsular Malaysia, the occurrence of NE monsoons brings heavy rains, turbulent wind, and high waves of energy in the region [23,24,25]. Between May and September, southwest (SW) monsoons occur, where the wind flows from the Indian Sea through the South China Sea. Generally, the wind flow is dry and produces hot weather [26]. The transition period between NE and SW monsoons is known as the inter-monsoon season, which is characterized by inconsistent winds and lightning accompanied with heavy rains [26]. Season change, e.g., monsoons, can have physical, chemical, and biological effects on the marine environment’s condition, changing the physicochemical parameters in the coastal area [27], which can possibly affect the biogeochemistry cycle of dissolved trace metals [28].

According to previous studies, southwest (SW) monsoons induce upwelling along the east coast of Peninsular Malaysia, which results in sufficient nutrients and high productivity in the water system [29]. The upwelling process brings enough nutrients from the water for the growth of phytoplankton during the monsoon event [30]. Monsoon events influence the distribution of chlorophyll a (Chl-a), and rainfall leads to the nutrient being flushed from the river to the coastal area [31]. The nutrient input generates a higher growth of phytoplankton in coastal areas during the monsoon event. In addition to this, there are changes in physical parameters, such as salinity and temperature, during monsoons due to the influence of rainfall on the phytoplankton biomass [32]. Phytoplankton were reported as the main source of organic ligands in seawater [33]. The presence of organic ligands can reduce metal ions and their toxicity in seawater through complexation [34]. In seawater, 99% of dissolved Cu(II) and Fe(III) was found via complexation with organic ligands [35,36].

Experimental results found that changes in physicochemical parameters such as pH, temperature, and salinity could affect solubility and metal speciation. Gledhill et al. (2015) suggested that the complexation of Cu(II) by natural ligands is likely influenced by changes in pH [37]. Their results suggested that at least a portion of the ligand pool is unable to compete with complexation by the added ligands as pH decreases. This is likely because the complexation of Cu(II) by these natural ligands is more strongly influenced by pH, indicating a changing availability for biological uptake. However, this study was an initial report on the effect of pH on metal-binding ligands based on modeling and laboratory simulation [35]. Therefore, understanding the effect of physicochemical changes on the distribution of dissolved trace metals is crucial to understanding how these changes could affect the biogeochemistry cycle of Cu(II) in coastal areas. According to a recent study by Mohamed et al. (2021), changes in the pH and salinity of seawater do not affect organic Fe (III)-ligand binding strength or the ligand saturation state [38].

However, very little is known about the levels and distribution of dissolved Cu in this area, specifically in the coastal waters, which has limited our knowledge of this matter [39,40]. Most of the studies related to dissolved metals found in Malaysia are related to river pollution [41,42,43] and estuarine water quality [44,45]. Fe and Cu are both essential for biological production and are required by photosynthetic organisms. Several research studies discuss the importance of ligands in binding dissolved Fe. However, there is limited literature on Cu-binding ligands. In this study, Cu was selected as the core metal because of the established method and available resources [12,28]. To the best of our knowledge, there is a lack of prior data regarding ligands that bind to copper within this sampling area. Hence, it is important to study the interaction between dissolved Cu and organic ligands in this seawater. This study aims to examine the distribution of dissolved Cu(II) and natural organic ligands during different sampling seasons.

2. Materials and Methods

2.1. Sampling Area and Activities

The district of Mersing is an area with high biodiversity, and it was selected by the National Geopark Committee to be developed into a geopark [46]. The Mersing coastal area is located on the east coast of Peninsular Malaysia in Johor. It is geographically located opposite the South China Sea, with several islands in this area, such as Pulau Aur, Pulau Tinggi, Pulau Pemanggil, and Pulau Tioman (located in the Pahang state). These islands experience northeast monsoon (NEM) and southwest monsoon (SWM) events. The NEM dominates the region from November to March, bringing strong northeasterly monsoon winds, while the SWM brings southwesterly winds between May and October.

In this study, four series of water samplings were carried out during August 2020 (season 1), March 2021 (season 2), April 2022 (season 3), and October 2022 (season 4). A total of six stations were selected in every sampling depending on the site conditions. The exact coordinates of the sampling locations were measured by a Garmin GPSMAP 64 s and plotted as in Figure 1. The sampling points encompass the Mersing coastal area which faces the South China Sea. A depth finder was used to determine the depth of the sampling points. The depth of the sampling stations in the Mersing coastal area ranged from 30 to 50 m. A total of five to six vertical depth profiles were divided according to the total depth of the sampling locations, depending on the depth of each station. Any point less than 2 m from the seafloor was avoided to prevent the mixing of seawater with the sediments.

The seawater samples were collected using a 5 L Niskin water sampler (KC Denmark A/S, Silkeborg, Denmark) at each sampling station (Figure 1). A total of 1 L of each water sample from each sampling point was stored in a cleaned low-density polyethylene (LDPE) bottle. The water samples were well labeled, with the sampling point and depth indicated on the LDPE bottles.

All the glassware and LDPE bottles used in this research were cleaned with detergent. All LDPE bottles were soaked in Decon 90 (2% v/v) for 24 h to remove any residual organic material before being rinsed three times with reverse osmosis (Milli-RO; Millipore Systems) water. The bottles were then soaked in hydrochloric acid (HCl) for a week before being rinsed three times with Milli-Q (MQ) water (MilliQ, Merck, Molsheim, France). Following this pre-treatment, the LDPE bottles were submerged in a nitric acid (HNO₃) bath for another week. After that, they were rinsed three times with MQ water before being filled with MQ water. Finally, the bottles were acidified to a pH of ~2 with HCl (9 M) [47].

The in situ parameters were measured immediately using a YSI Professional Plus Multi-Parameter Meter (603190 Pro Plus multi-probe, YSI Incorporated, Yellow Springs, OH, USA) at the sampling sites. This measurement procedure was repeated three times to ensure the data accuracy. Temperature, dissolved oxygen (DO), pH, salinity, and conductivity were obtained through this measurement.

The seawater samples were then filtered through 0.45 μm and 0.20 μm cellulose nitrate membrane filters (Whatman, Maidstone, UK). The 0.45 μm filtered samples were used for determining the dissolved copper, while the 0.20 μm filtered samples were used for copper speciation analysis. After filtration, the seawater samples were transferred into 250 mL low-density polyethylene (LDPE) bottles (Nalgene, Rochester, NY, USA). The bottles were tightly capped, bagged, and stored in double-sealed plastic bags in a freezer until further speciation analysis. For the total dissolved copper analysis, the 250 mL samples were acidified at pH 2.0.

2.2. Chemical Preparation

The standard addition method was applied in the quantification of metal concentrations in the samples during the voltammetric analysis [48]. Copper standards for ICP (1000 mg/L, brand Fluka, Seelze, Switzerland) were prepared and diluted in 0.01 M HCl (Romil UpA grade, Cambridge, UK) for use in standard addition during the analysis. Standard addition helps to overcome the matrix effect that interferes with analyte measurement signals by the calibration of standards with the same samples [49,50,51].

Ammonium acetate (NH₄CH₃COOH) was used as a buffer solution and ligand to determine multiple elements simultaneously through the differential pulse anodic stripping voltammetry (DPASV) method. Dilute acetate acid (2 M final concentration, Avantor Performance Materials, Bangkok, Thailand) and ammonium solution (1 M final concentration, Merck, Darmstadt, Germany) were used to prepare the buffer solution at pH 4.6. Lasumin et al. (2019) reported that the optimized measurement of trace metal concentrations by using voltammetry was obtained at pH 4.6 [52].

A borate buffer (1.0 M; pH 8.05) solution was prepared with boric acid (H₃BO₃, Fisher Scientific, Waltham, MA, USA) in 0.3 M ammonia (Suprapur, Merck, Darmstadt, Germany) [12,13,53]. A study suggested that the working pH for Cu and SA is within the range of 8.0 to 8.5, at which maximum sensitivity is obtained. A pH of 8.05 was found to be optimal for Cu-SA complex measurement in Malaysia coastal waters [12,13]. The borate buffer solution was added with 0.02 M of 2-(2-Thiazolylazo)-p-cresol (TAC) (C₁₀H₉N₃OS, Aldrich, United States) and left overnight to remove the interference in the stock solution. The buffer solution was then cleaned by using a C18 SepPak column (Whatman) to remove Fe contamination, which might have competed with Cu to form a complex with SA [53,54].

An aqueous solution of 0.01 M salicylaldoxime (SA) was prepared in 0.1 M HCl, and it functioned as an added ligand to compete with natural ligands so that the amount of Cu(II) bound by the added ligand was similar to the complex stability of natural ligands in the sample. As a result, the concentration could be calculated. The SA solution was stable for at least 8 weeks at 4 °C [12,55] and was replaced every three months. SA was used as it forms a stronger complex with Cu, and has greater sensitivity than other ligands such as oxine, catechol, or tropolone for determining Cu in seawater by cathodic stripping voltammetry (CSV) [55].

2.3. Determination of Dissolved Cu(II) by Anodic Stripping Voltammetry

The concentration of dissolved Cu(II) was measured by using ASV combined with a Trace Metal Analyzer (797 VA Computrace, Metrohm AG, Herisau, Switzerland) in this study. The water samples were first acidified to pH 2.0 for sample digestion by UV irradiation to destroy the organic matter that complexed with metals [56,57,58,59]. Samples were then left to cool to room temperature after UV irradiation. After cooling, the samples were then adjusted to the natural pH of seawater (~8.05). A 10 mL sample was added with 1 mL of ammonium acetate buffer (pH 4.6) before being poured into the voltammetric vial. The samples were purged with high-purity nitrogen (99.999%, Alpha Gas Solution Sdn. Bhd., Shah Alam, Malaysia) to remove the dissolved oxygen.

The ASV analysis was started with the accumulation step (deposition time: 300 s), where the deposition potential was kept negative to accumulate and reduce the metal ions onto the working electrode (hanging mercury drop electrode, HMDE) surface. The samples were left for an equilibration time of 10 s, and then differential pulse voltammetry (DPV) was performed from −1.15 to 0.02 V with a sweep rate of 59.5 mV/s. The determination of the samples was repeated with standard addition (4 additions, 1 ppm) to calibrate sensitivity.

2.4. Determination of Total Dissolved Cu(II) Concentration by Cathodic Stripping Voltammetry

UV irradiation was applied to the acidified sample for 4.5 min for total dissolved copper(II) determination [13]. After cooling to room temperature, 10 mL of seawater sample was buffered to pH 8.05 using a borate buffer (final concentration 0.01 M) followed by SA (final concentration 25 μM). The buffered sample was transferred into the voltammetric vials for cathodic stripping voltammetry (CSV) analysis [13,55]. A 100 μL amount of Cu standard solution (10⁻⁶ M) (SpectrosoL grade, Merck, Darmstadt, Germany) was added three times during the standard addition step. Dissolved oxygen was eliminated from the samples by deaeration for 300 s with dry nitrogen gas. Subsequently, a fresh mercury drop was used to adsorb total dissolved Cu onto the sample (hanging mercury drop electrode, HMDE) at an applied potential of −0.1 V for 120 s while the sample was stirred. Upon completion, the stirrer was then stopped, and, using the differential pulse mode from −1.5 V to −0.1 V at 0.04 s pulse time, the potential was scanned, and the stripping current from the adsorbed Cu(II) was swept. The limit of detection for Cu(II) by CSV has been reported in the nM range [12,13].

2.5. Determination of Natural Organic Ligands (CuL)

The concentration of natural organic ligands (CuL) and their conditional stability constants (log K′) were determined using competitive ligand exchange–adsorptive cathodic stripping voltammetry (CLE-AdCSV). The complex of natural organic Cu(II) ligands was analyzed to determine the concentration of Cu(II) ions that bind to the natural organic ligand at a 1:1 ratio. Therefore, the concentration of Cu(II) determined represents the concentration of natural organic ligands forming the complex. The log K′ value represents the binding strength between Cu(II) and CuL in the sample. Analysis of Cu(II) speciation was conducted to determine [CuL] and log K′ considering the stability of Cu()II) ions in seawater [60,61].

The voltammetry consisted of a static mercury drop electrode (Metrohm VA797, Herisau, Switzerland), a double-junction Ag/saturated AgCl reference electrode with a salt bridge containing 3 M KCl, and a counter electrode of glassy carbon. MQ water (MilliQ, Merck, Molsheim, France) was used to prepare aqueous solutions. Labile copper concentrations in seawater samples were determined by CLE-AdCSV with SA as a competing ligand [55]. The added ligand SA bound Cu(II) in the seawater samples before it could be detected by AdCSV. Ligand competition using SA (final concentration 25 µM) was the optimized approach used in this study to investigate the Cu(II) complexation in seawater at pH 8.05 and salinities between 1 and 35 psu [12,13,55].

Approximately 120 mL of seawater sample was added to 0.8 mL of 1.0 M borate buffer and left to equilibrate for an hour before the addition of 0.3 mL of 25 μM SA. Then, 11 subsamples were prepared by pipetting 10 mL of seawater into 11 fluorinated ethylene propylene (FEP) bottles before adding the Cu standards in increasing concentrations (0–0.08 μM) (Figure 2). To ensure the accuracy, 11 subsamples (titration points) were measured for each sample. Organic ligands in seawater bind Cu(II) in a non-linear manner, and an insufficient number of titration points may fail to capture the transition from ligand undersaturation to saturation. The subsamples were left to equilibrate overnight to ensure all reactions had taken place between Cu and the added SA in the sample [12,13,28]. The titrations determined the concentration of natural metal-complexing ligands (CuL) and their conditional stability constants (K′) by utilizing a ligand competition approach.

The labile Cu concentrations which had reacted with the added SA were determined the next day. The subsample was poured into the voltammetric vials and determined according to the order. The dissolved oxygen in the sample was first removed by using nitrogen gas for 300 s followed by 60 s of deposition with sample stirring. The electroactive Cu(SA)_x complexes were adsorbed onto the mercury drop during deposition at an applied potential of −0.15 V. Upon completion, the stirrer was stopped and an equilibrating time of 30 s was allowed before the potential was scanned. The samples were scanned with a potential starting at −0.15 V and ending at −0.65 V using the differential pulse mode. The stripping reduction current from the adsorbed Cu(SA)_x complex and the peak height were recorded. The voltammetric vials were rinsed with MQ water between titrations without changing the order of the subsamples, to condition the vials with copper and to eliminate adsorption onto the cell walls. The limit of detection for Cu(II) by AdCSV was 0.27 nM [55].

The organic Cu(II)-binding ligand concentrations and the conditional stability constant were calculated using Van den Berg linearization [12,55]. If the measurement of log K′ > 12, it was denoted as a stronger ligand, and a measurement of log K′ < 12 was denoted as a weaker ligand. The values calculated from this linearization are generally more sensitive to analytical uncertainties because the values for log K′ and ligand concentration are inversely related to the slope and intercept of the plot during analysis.

The obtained raw data on in situ parameters during water sampling and electrochemistry analysis were recorded and tabulated in Excel files. All the primary data (in situ parameters and concentration of dissolved trace metals) were first analyzed using a normality test. A proper parametric and non-parametric statistical test was applied to the related data based on their normality.

2.6. Data Analysis

The data obtained from the study site and laboratory for the entire study group were analyzed using statistical analysis. The Friedman test, Wilcoxon signed-rank test, one-way repeated-measures ANOVA, and correlation were employed by using IBM SPSS version 28.0 to achieve the research objectives. The voltammetric parameters (peak current, concentration of dissolved Cu(II)) obtained were tabulated into Excel files, and speciation parameters (ligand concentration and log K′) were determined by the Van den Berg linearization method. A similar statistical analysis was used to determine the difference among the sampling seasons.

3. Results and Discussion

3.1. Physicochemical Parameters of Seawater Samples

During season 1, the temperature ranged from 26.70 °C (St 4 40 m) to 29.50 °C (St 1 3 m), with an average of 28.53 °C (n = 30) (

Table 1. In situ parameters recorded in sampling season of season 1 (August 2020) in Mersing coastal area.

Station	Depth (m)	pH	Temp. (°C)	Cond. (μS/cm)	Salinity (ppt)	DO (mg/L)
St 1	3	8.07	29.50	55,129	33.14	5.74
	10	8.09	29.08	54,869	33.24	5.86
	20	8.10	29.08	54,874	33.28	5.79
	30	8.11	28.68	53,921	32.92	5.52
	35	8.10	27.50	54,450	34.14	4.79
St 2	3	8.14	29.20	54,824	33.18	5.64
	10	8.15	29.10	54,703	33.17	5.62
	20	8.15	29.00	54,726	33.24	5.60
	30	8.15	28.50	54,910	33.72	5.22
	35	8.14	27.00	54,309	34.38	4.61
St 3	3	8.17	29.20	54,848	33.21	5.62
	10	8.19	29.10	54,737	33.17	5.77
	20	8.18	29.10	55,430	33.67	5.93
	30	8.18	28.30	54,615	33.62	5.31
	40	8.17	26.80	54,218	34.47	4.61
St 4	3	8.20	29.20	54,518	33.14	5.69
	10	8.20	29.10	54,533	33.05	5.76
	20	8.20	29.00	54,891	33.36	5.78
	30	8.20	28.50	54,966	33.77	5.51
	40	8.19	26.70	54,085	34.44	4.70
St 5	3	8.21	29.08	54,816	33.20	5.82
	10	8.21	29.10	54,940	33.30	5.71
	20	8.21	29.10	54,952	33.34	6.16
	30	8.20	27.80	54,701	34.06	5.24
	40	8.19	26.73	54,206	34.50	4.57
St 6	3	8.22	29.20	54,983	33.25	5.92
	10	8.22	29.13	54,720	33.16	5.73
	20	8.22	29.10	54,858	33.29	5.67
	30	8.22	28.15	54,627	34.06	4.93
	40	8.21	26.85	54,192	34.44	4.44

). The pH values varied between a minimum of 8.07 (St 1 3 m) and a maximum of 8.22, observed at Station 6 (3 m, 10 m, 20 m, and 30 m depths), with an overall average of 8.17 (n = 30). The range of salinity was from 32.92 ppt (St 1 30 m) to 34.50 ppt (St 5 40 m), with an average of 33.56 ppt (n = 30). Conductivity was observed to range from 53,921μS/cm (St 1 30 m) to 55,430 μS/cm (St 3 20 m), with an average of 54,685 μS/cm (n = 30). The mean DO concentration was 5.44 ± 0.48 mg/L with the minimum value 4.44 mg/L (St 6 40 m) and maximum value 6.16 mg/L (St 4 20 m).

During season 2, the temperature ranged from 27.90 °C (St 3 40 m) to 29.60 °C (St 1 3 m), with an average of 28.86 °C (n = 28). The range of salinity was from 28.60 ppt (St 1 3 m) to 29.58 ppt (St 3 40 m) in season 2. Conductivity was found to be in the range of 47,803 μS/cm (St 5 30 m) to 48,821 μS/cm (St 1 10 m), with an average of 48,524 μS/cm (n = 28). pH ranged from 7.20 (St 1 3 m) to 8.21 (St 5 30 m, 45 m and St 6 3 m, 10 m, 15 m, 30 m) with an average of 8.07 (n = 28). The average level of DO in season 2 was 6.63 ±2.58 mg/L with a range of 5.28 mg/L (St 6 10 m) to 17.98 mg/L (St 3 3 m).

During season 3, temperature was in the range of 28.00 °C (St 4 40 m, St 5 40 m) to 29.80 °C (St 4 3 m) with an average of 28.86 °C (n = 27). The range of salinity was from 26.76 ppt (St 3 10 m) to 33.36 ppt (St 4 20 m), with an average of 28.73 ppt (n = 27). The conductivity ranged from 44,945 μS/cm (St 2 30 m) to 55,291 μS/cm (St 4 20 m), with an average of 47,941 μS/cm (n = 27). The pH ranged from 8.16 (St 1 15 m) to 8.21 (St 2 20 m, St 4 30 m, 40 m, St 5 30 m, 40 m) with an average of 8.19 (n = 27), whereas DO ranged from 4.27 mg/L (St 6 10 m) to 9.79 mg/L (St 5 3 m), with a mean of 5.52 mg/L (n = 27).

During season 4, the temperature recorded was in the range of 29.10 °C (St 6 20 m) to 29.40 °C (St 1, 2, 4 3 m) with an average of 29.21 °C (n = 23). The minimum value of salinity was 25.79 ppt (St 6 3 m), while the maximum salinity was 31.55 ppt (St 4 15 m). The conductivity was found to be in the range of 43,564 μS/cm (St 6 3 m) to 54,935 μS/cm (St 3 3 m) with an average of 50,302 μS/cm 01 (n = 23). pH ranged from 8.72 (St 1 3 m, 10 m, 25 m) to 8.75 (St 6 3 m) with an average of 8.74 (n = 23). DO ranged from 4.49 mg/L (St 3 20 m) to 8.77 mg/L (St 1 3 m), with a mean value of 5.30 mg/L during season 4.

Table 1,

Table 2. In situ parameters recorded in sampling season of season 2 (April 2021) in Mersing coastal area.

Station	Depth (m)	pH	Temp. (°C)	Cond. (μS/cm)	Salinity (ppt)	DO (mg/L)
St 1	3	7.20	29.60	48,342	28.60	7.18
	10	7.35	29.40	48,821	29.02	6.43
	15	7.54	29.10	48,550	29.01	5.74
	30	7.66	28.50	48,177	29.15	5.97
St 2	3	8.10	29.20	48,811	29.13	9.53
	10	8.12	29.10	48,690	29.12	6.47
	15	8.12	29.00	48,655	29.11	5.85
	30	8.13	29.00	48,764	29.19	5.62
	40	8.13	29.10	48,359	29.13	5.64
St 3	3	8.13	29.10	48,789	29.16	17.98
	10	8.16	28.90	48,612	29.13	6.37
	15	8.16	28.90	48,610	29.19	5.84
	30	8.17	28.30	48,408	29.37	5.77
	40	8.17	27.90	48,341	29.58	5.58
St 4	3	8.18	29.10	48,749	29.13	5.68
	10	8.18	28.90	48,617	29.17	6.15
	15	8.18	28.70	48,545	29.22	5.84
	30	8.18	28.60	48,487	29.29	5.62
	45	8.19	28.50	48,504	29.32	5.80
St 5	3	8.19	29.10	48,727	29.12	11.38
	10	8.20	29.00	48,628	29.13	6.87
	15	8.20	28.90	48,577	29.16	5.89
	30	8.21	28.30	47,803	29.31	5.34
	45	8.21	28.20	48,281	29.40	5.28
St 6	3	8.21	29.30	48,774	29.03	5.34
	10	8.21	29.10	48,445	28.95	5.28
	15	8.21	29.00	48,432	28.97	5.50
	30	8.21	28.30	48,189	29.26	5.62

,

Table 3. In situ parameters recorded in sampling season of season 3 (March 2022) in Mersing coastal area.

Station	Depth (m)	pH	Temp. (°C)	Cond. (μS/cm)	Salinity (ppt)	DO (mg/L)
St 1	3	8.17	29.80	47,776	28.00	9.57
	10	8.17	29.77	46,076	27.00	8.07
	15	8.16	28.80	47,110	28.23	7.28
St 2	3	8.20	29.80	48,331	28.46	4.44
	10	8.20	29.50	48,305	28.59	4.48
	20	8.21	28.40	47,704	28.86	4.94
	30	8.19	28.13	44,945	27.20	4.95
	40	8.20	28.03	47,043	28.42	4.92
St 3	3	8.19	29.67	47,767	28.15	4.70
	10	8.19	29.47	45,436	26.76	4.76
	20	8.20	28.60	48,055	28.98	4.77
	30	8.19	28.33	46,984	28.43	4.99
	40	8.20	28.03	45,014	27.28	4.95
St 4	3	8.19	29.80	48,833	28.76	4.92
	10	8.20	29.33	48,544	28.86	4.85
	20	8.20	29.00	55,291	33.36	5.78
	30	8.21	28.03	48,486	29.61	5.23
	40	8.21	28.00	48,447	29.61	5.25
St 5	3	8.19	29.73	48,504	28.60	9.79
	10	8.20	28.90	48,618	29.19	4.99
	20	8.20	28.50	48,730	29.51	5.46
	30	8.21	28.10	48,540	29.58	5.32
	40	8.21	28.00	48,405	29.54	5.33
St 6	3	8.19	29.67	47,465	27.96	4.97
	10	8.19	29.43	47,970	28.41	4.27
	20	8.20	28.20	48,204	29.34	5.16
	30	8.20	28.10	47,837	29.11	5.00

and

Table 4. In situ parameters recorded in sampling season of season 4 (October 2022) in Mersing coastal area.

Station	Depth (m)	pH	Temp. (°C)	Cond. (μS/cm)	Salinity (ppt)	DO (mg/L)
St 1	3	8.72	29.40	51,086	30.53	8.77
	10	8.72	29.30	52,284	31.38	6.70
	25	8.72	29.30	52,263	31.52	5.65
St 2	3	8.74	29.40	46,038	30.04	5.38
	10	8.73	29.30	52,229	31.38	4.71
	15	8.73	29.30	52,226	31.36	4.72
St 3	3	8.74	29.30	54,935	30.91	4.93
	15	8.73	29.30	51,649	31.12	4.75
	20	8.73	29.30	52,156	31.30	4.49
St 4	3	8.74	29.40	52,313	31.34	4.75
	15	8.73	29.30	52,619	31.55	4.65
	30	8.73	29.20	48,816	29.17	4.62
St 5	3	8.73	29.20	51,777	31.10	7.57
	10	8.73	29.13	43,603	25.84	6.93
St 6	3	8.75	29.13	43,564	25.79	5.15
	10	8.74	29.37	52,013	31.16	4.74
	20	8.74	29.10	50,437	31.21	5.02

show the in situ parameters measured in the Mersing coastal area during different sampling seasons. The Friedman test showed that there was a significant difference in pH, temperature, DO, salinity, and conductivity between different sampling seasons (p < 0.05). Generally, these parameters exhibit significant changes due to climate changes such as ocean acidification and a higher rate of rainfall. The significant changes in physicochemical parameters observed in this study area might also be due to the seasonal monsoonal variations at the sampling location during different sampling seasons [27,62].

According to Wilcoxon signed-rank tests, pH differed significantly between all the sampling seasons (p < 0.05) (

Table 5. Wilcoxon signed-rank tests show the difference in in situ parameters between different sampling seasons in the Mersing coastal area.

Parameter	Season	p-Value	Significantly Different?
pH	season 1–season 2	<0.001	Yes
	season 1–season 3	0.002	Yes
	season 1–season 4	<0.001	Yes
	season 2–season 3	<0.001	Yes
	season 2–season 4	<0.001	Yes
	season 3–season 4	<0.001	Yes
Temperature	season 1–season 2	0.929	No
	season 1–season 3	0.28	No
	season 1–season 4	0.001	Yes
	season 2–season 3	0.478	No
	season 2–season 4	<0.001	Yes
	season 3–season 4	0.022	Yes
Salinity	season 1–season 2	<0.001	Yes
	season 1–season 3	<0.001	Yes
	season 1–season 4	<0.001	Yes
	season 2–season 3	0.008	Yes
	season 2–season 4	0.031	Yes
	season 3–season 4	0.021	Yes
DO	season 1–season 2	0.003	Yes
	season 1–season 3	0.068	No
	season 1–season 4	0.128	No
	season 2–season 3	0.016	Yes
	season 2–season 4	0.008	Yes
	season 3–season 4	0.068	No
Conductivity	season 1–season 2	<0.001	Yes
	season 1–season 3	<0.001	Yes
	season 1–season 4	<0.001	Yes
	season 2–season 3	0.003	Yes
	season 2–season 4	0.033	Yes
	season 3–season 4	0.033	Yes

). The highest average pH was found in sampling season 4 (pH 8.74), followed by season 3 (pH 8.19), season 1 (pH 8.17), and season 2 (pH 8.07), which had the lowest (Figure 1). The low mean pH found in season 2 (pH = 8.07) compared to the rest of the sampling seasons (Figure 3a) might be due to the mixing of freshwater [63]. Freshwater influx to the coastal area consists of terrestrial organic matter which undergoes decomposition, which could raise the carbon dioxide concentration [64,65]. In addition, another possible cause of the pH changes in the coastal waters is the upwelling process [66], as a previous study had proof that upwelling occurs during the southwest monsoon dynamic in our study area [29]. The lowest pH was found in season 2, which might be due to the upwelling process. During an upwelling process, the more acidic water at the bottom is brought up to the ocean surface [67,68].

Seasonal temperature fluctuations may be attributed to wind force, freshwater input, and atmospheric temperature. In our study area, sampling during season 4 was in an inter-monsoon period, marking the transition of the SWM (dry season) to the NEM (wet season) in Mersing coastal waters. The high temperature (29.21 °C) in season 4 suggested that this area experienced less precipitation without cloudy weather, and direct sunlight exposure [69]. The consistent temperature during the earlier seasons (seasons 1, 2, and 3) might have been influenced by its bottom layer of temperature (Figure 3b). Generally, lower temperatures can be found in deeper water samples. However, the lower temperature in seasons 2 and 3 could be linked to significant monsoonal rainfall [70,71].

Salinity was found to be highest in season 1 (33.56 ppt) compared to the other seasons, followed by season 4 (30.17 ppt) and season 2 (29.15 ppt), with the lowest salinity being observed in season 3 (28.73 ppt) (Figure 3c). These fluctuations suggest seasonal variations in salinity within the coastal waters of Mersing. According to the Wilcoxon signed-rank test results, salinity exhibited a significant difference across all sampling seasons (p < 0.05) (Table 5). These results confirm that the salinity levels in this study area are of high variability and are significantly impacted by seasonal changes. The highest salinity in season 1 could be linked to the SWM (dry season). The dry season caused less dilution of seawater from precipitation and a huge amount of freshwater influx from the land. As a result, the highest salinity was found in season 1 compared to the rest of the sampling seasons in this study. In contrast, the lower salinity recorded in season 2 and season 3 was likely due to the river discharge and precipitation, which dilute the salinity of the seawater during monsoonal events [72]. Monsoonal changes can affect the salinity of coastal areas. Salinity in coastal areas is mostly influenced by the influx and transport of freshwater into the seawater. Therefore, these findings highlight the role of freshwater flux into our coastal area under the influence of monsoons during season 2 and season 3. The moderate salinity observed in October 2022 may represent a transition between dry and wet periods.

A higher level of DO was found in season 2, with a mean concentration of 6.63 mg/L (Figure 3). The Wilcoxon signed-rank test results reveal significant differences between season 2 and season 1 (p = 0.003), season 3 (p = 0.016), and season 4 (p = 0.008) (Table 5). The rest of the seasons did not show significance differences among themselves (p > 0.05). These findings highlight that, while DO levels remained within a relatively narrow range overall (5.30 to 6.63 mg/L), the differences between these specific seasons were statistically significant, particularly between season 2 and the other seasons. The higher DO levels found in season 2 might be due to the lower temperatures compared to season 4 (which had the lowest DO level). Warmer water is saturated with oxygen and holds less dissolved oxygen compared to colder water [73]. Additionally, the high mean DO concentration during season 2 might be due to the upwelling or water-mixing process. A previous study suggested that water mixing due to high turbulence could transport nutrients from the bottom layer to the surface layer. The upwelling of water with high nutrient levels, especially phosphates, can enhance phytoplankton blooms, which increase primary productivity through photosynthesis [74]. These phytoplankton blooms enhance photosynthesis and produce more oxygen as a waste product [75]. Over time, this increased photosynthesis can raise DO levels, particularly in surface waters.

The conductivity levels ranged from a high of 54,685 µS/cm in season 1 to a low of 47,941 µS/cm in season 3 (Figure 3e). Wilcoxon signed-rank test results indicated significant differences between all seasons, with p-values less than 0.05. The significant difference between season 1 and the other seasons (p < 0.001) indicates a sharp contrast in conductivity levels between the dry season and the wet seasons. This pattern closely aligns with salinity variations. Conductivity is commonly used to indicate salinity level. The conductivity has a highly positive correlation with the concentration of dissolved salts [76]. In this study, salinity and conductivity exhibited a similar trend, where the highest values were found in season 1. Elevated conductivity can likely be attributed to the pre-NEM (dry season), which had reduced freshwater input [77]. The lower conductivity in seasons 2 and 3 was due to increased dilution or the mixing of freshwater from rivers.

The statistical analysis demonstrated significant changes in pH, temperature, salinity, conductivity, and dissolved oxygen between the seasons. Season 1 experienced a dry season, with the proof of high salinity (33.56 ppt), while seasons 2 and 3 had lower salinity due to freshwater influx compared to the four sampling seasons in the Mersing coastal waters (Figure 1). The significant changes of in situ parameters are probably due to the seasonal changes such as monsoons, which bring rainfall and freshwater influx into the coastal waters [78,79]. During season 2, the salinity (29.15 ppt) was lower than that of the other seasons (except season 3 (28.73 ppt)), indicating freshwater input rather than an upwelling process. However, upwelling is possible if there is enough freshwater input from rivers, which would lower surface salinity while mixing with the upwelled waters. The combination of lower salinity, lower pH, and higher DO suggests that season 2 may have experienced some degree of upwelling or mixing of deeper water into the surface layer.

3.2. Dissolved Cu(II) in Mersing Coastal Area

Table 6. Descriptive table of dissolved Cu across different sampling seasons in Mersing coastal water.

Sampling	Sample Size	Min.	Max.	Mean	Std. Dev.
	(n)	(µg/L)
August 2020	30	0.014	0.577	0.163	0.146
April 2021	28	0.003	0.023	0.010	0.006
March 2022	27	0.010	0.230	0.085	0.126
October 2022	23	0.006	0.209	0.052	0.055

summarizes the descriptive statistics of dissolved Cu(II) concentrations, including the minimum, maximum, and average values across the sampling seasons.

Figure 4 visualizes the mean concentration of dissolved Cu(II) for different sampling seasons. The concentration order of dissolved Cu was as follows: season 1 > season 3 > season 4 > season 2. The graph shows that the mean concentration of dissolved Cu(II) was found to be highest during season 1 and the lowest was found in season 2. However, the Friedman test revealed that the concentrations of dissolved Cu in this study area did not show a significant difference during different sampling seasons (χ² (3) = 5.80, p = 0.122).

The constant concentration of dissolved Cu(II) in this coastal water region suggests the possible role of dissolved organic matter in the water column, which regulates the concentration of dissolved metals and alters metal speciation [80,81]. This suggests that the concentration of Cu(II) may be more strongly regulated by the presence of natural organic ligands in seawater. Previous studies have shown that Cu(II) tends to form more stable complexes with organic ligands compared to other divalent metals [81,82]. This affinity for organic matter likely explains the stability of dissolved Cu(II) levels across different environmental conditions, highlighting the key role that natural organic ligands play in controlling the speciation and behavior of trace metals in coastal waters. Hence, further copper speciation analysis was conducted to identify the complexation of organic ligands under the changes of in situ parameters in the coastal area.

3.3. Distribution of Cu(II) Speciation

Speciation parameters such as the copper(II)-complexing ligands (CuL), conditional stability constant (Log K′), excess ligand concentration (L′), ratio of copper-complexing ligands and total dissolved copper, percentage of Cu that is organically complexed, free cupric ions (Cu²⁺), and free cupric ion activities (pCu) were obtained.

Table 7. Statistical results for dissolved-copper-binding ligand parameters. Minimum, maximum, and mean with standard deviation during different sampling seasons. The number of samples (n) varied by sampling period: 30 (August 2020), 28 (April 2021), 27 (March 2022), and 23 (October 2022).

Seasons		dCu (nM)	CuL (nM)	log K′ (mol−1)	L′ (nM)	CuL (%)	CuL/dCu	Cu2+ (M)	pCu
1	min	6.18	6.19	14.13	0.00	99.97	1.00	9.78 × 10−25	21.62
	max	8.36	8.90	15.22	0.64	100.00	1.09	2.38 × 10−22	24.01
	mean	7.43	7.68	14.75	0.25	99.99	1.03	3.68 × 10−23	22.93
	std. dev.	0.53	0.61	0.28	0.22	0.01	0.03	6.59 × 10−23	0.66
2	min	10.22	10.22	14.50	0.01	99.98	1.00	1.42 × 10−24	21.79
	max	13.63	13.64	15.61	0.43	100.00	1.04	1.64× 10−22	23.85
	mean	11.61	11.74	15.24	0.14	100.00	1.01	2.51 × 10−23	23.07
	std. dev.	0.97	0.95	0.27	0.13	0.00	0.01	4.07 × 10−23	0.65
3	min	7.18	7.20	14.62	0.00	99.98	0.86	1.08 × 10−24	21.74
	max	11.98	12.26	15.83	0.35	100.00	1.11	1.83 × 10−22	23.97
	mean	9.24	9.34	15.07	0.11	100.00	1.01	2.89 × 10−23	22.87
	std. dev.	1.18	1.22	0.30	0.11	0.00	0.04	4.00 × 10−23	0.59
4	min	7.02	7.02	14.65	0.00	99.95	1.00	8.29 × 10−25	21.49
	max	8.87	9.73	15.39	0.86	100.00	1.10	3.23 × 10−22	24.08
	mean	7.74	7.92	15.05	0.17	99.99	1.02	4.58 × 10−23	22.92
	std. dev.	0.51	0.65	0.24	0.23	0.01	0.03	8.62 × 10−23	0.73

min = minimum; max = maximum; std. dev. = standard deviation; dCu = dissolved copper concentration; CuL = copper-complexing ligands; log K′ = conditional stability constant; L′ = excess ligand concentration (L′ = CuL − dCu); CuL (%) = percentage of the Cu organically complexed; Cu²⁺ = free cupric ions; pCu = free cupric ion activities.

shows the summary of the statistical results (minimum, maximum, and average) for the Cu speciation parameters.

The ligand concentrations were found to exceed or roughly equal the total dissolved Cu(II) concentrations in all measured samples (Table 7). The concentrations of dCu and CuL were linearly correlated (Figure 5) throughout the depth and location. The R² values of 0.88 (season 1), 0.98 (season 2), 0.99 (season 3), and 0.91 (season 4) indicate a strong correlation between dCu and CuL during each sampling season (Figure 5).

The observed correlation between dCu and CuL shows that, as the concentration of dissolved copper increases, there is a corresponding increase in ligand concentration. This indicates that the production of CuL is highly influenced by the changing of organic ligands, which is consistent with findings in other coastal areas [83,84]. This pattern is not only observed in the surface water, but extends throughout the entire water column during the sampling seasons. A steeper slope in season 4 (1.22) suggests a stronger influence of dCu on CuL concentration during the sampling seasons. This represents a feedback mechanism where a higher concentration of dCu will induce the ligand production to reduce the Cu toxicity [84,85,86]. These ligands bind to the free copper ions, thereby reducing the concentration of free copper ions that could otherwise be toxic. This difference in slope may reflect seasonal changes affecting ligand availability and copper binding, leading to increased sensitivity to copper levels in season 4.

The efficiency of the complexation of Cu(II) with natural organic ligands is essential in regulating the bioavailability of copper and preventing its transition into precipitated forms [87]. In this study, the ratio of CuL/dCu was constant, with a mean value ranging from 1.01 to 1.03 (Table 7). This ratio provides insight into the saturation state between dCu and CuL, which reflects the role of organic ligands in stabilizing the dCu in seawater. According to [88,89], a ratio near 1 indicates the saturation state of the natural ligand towards Cu values close to 1, which designates that most of the ligands are bound with the metal. Hence, this suggested that the dCu present in this study area was primarily bound to ligands. When the ratio of CuL/dCu is less than 1, there are fewer ligands available to bind and complex the dissolved metal ions. This results in transitions of non-organically bound metals into the particulate phase through processes such as scavenging, biological uptake, or precipitation [90]. This creates the risk of an elevated concentration of free Cu²⁺ ions, which are mostly bioavailable and toxic in the water column.

However, previous studies reported that a low CuL/dCu ratio between 1.1 and 2.7 is favorable for Cu precipitation as the available ligand sites are nearly saturated with metal ions [60,89]. A higher ratio is normally found in deeper water samples >450 m from surface. According to Thuróczy et al. (2011), a smaller ratio (closer to 1) indicates a lower concentration of excess ligands at the sampling sites, suggesting conditions that are more favorable for ligand saturation [89]. The highest ratio observed in this study was 1.11, which revealed a balance between ligand availability and copper, potentially indicating that the ligands are close to saturation but not yet fully saturated. In our study area, the lowest CuL/dCu ratio recorded was 0.86, which was observed during season 3.

This interpretation is further supported by the observed low excess ligands (L′) in this study. Excess ligand concentrations (L′) represent the number of available free Cu-binding sites. Excess ligands were identified at all stations, with mean concentrations of L′ 0.25 nM (season 1), 0.14 nM (season 2), 0.11 nM (season 3), and 0.17 nM (season 4), which suggested a near saturation of the ligands (Table 6). These excess ligands were free and uncomplexed ligands, which could be readily complexed with any addition of Cu²⁺. However, any external inputs of Cu in this study area may risk increasing the free Cu²⁺ ions in the water column due to the limitation of ligand pool complexation [53]. Hence, higher levels of excess ligands are important to reduce and buffer the toxicity [91]. When ligands are fully saturated with an increase in dCu, the extra Cu is unable to complex with the organic ligands, which might cause high levels of free metal ions and the precipitation process to occur. This result is similar to the CuL/dCu ratio in Pulau Pangkor, on the west coast of Peninsular Malaysia (1.03 to 2.77), and Pulau Perhentian, on the east coast of Peninsular Malaysia (1.00 to 2.31) [12,13]. Based on these previous studies, a good complexation process reduces the concentration of Cu²⁺ and L′, making dCu function with bioavailability.

The mean concentrations of free Cu²⁺, as low as 10⁻²³ M (Figure 6), in this study area across the sampling seasons were found to be relatively low when triggering toxicity in seawater. A free copper ion level above a certain level (1.1 × 10⁻¹¹ M) can be toxic to marine phytoplankton [92] and suppress the growth of cyanobacteria, phytoplankton, and zooplankton [93]. Growth of cyanobacteria such as Synechococcus can be inhibited with a Cu²⁺ concentration exceeding 10⁻¹² M, and other species such as T. oceanica and T. pseudonana at above 10^−9.5 M [16,94], while eukaryotic algae exhibit maximum toleration of reproduction rates at 10⁻¹¹ M [16,94,95,96]. Conversely, phytoplankton can develop defense mechanisms against toxic Cu²⁺ through the complexation of Cu²⁺ with organic ligands, reducing its bioavailability [97].

Previous studies have suggested that low Cu²⁺ concentrations <10⁻¹⁴ M may limit the growth of phytoplankton [98]. Certain research has also reported that Cu concentrations above 10^−15.1–10^−14.4 M could inhibit the growth of diatoms in seawater [95,99]. In this study area, the lowest concentration of 10⁻²⁵ M was detected in both season 1 and season 4. However, certain studies have suggested that organically complexed Cu becomes bioavailable to marine phytoplankton to relieve Cu limitation in seawater [100,101].

The low concentration of Cu²⁺ is highly related to the high copper ion activity, in terms of pCu, where pCu = –log[Cu²⁺], at this sampling point, which suggests that copper is mostly bound to ligands, reducing its bioavailability and toxicity. Copper ion activity (pCu) indicates the mobility and reactivity of copper within the aquatic ecosystem, as well as provides insight into its bioavailability and toxicity [102]. A lower pCu value indicates a high concentration of free Cu²⁺ ions, meaning copper is more bioavailable and potentially more toxic. In this study, the pCu values varied from 21.62 to 24.01 (season 1); 21.79 to 23.85 (season 2); 21.74 to 23.97 (season 3); and 21.49 to 23.08 (season 4) (Table 7). These results show a vast difference compared to those previously reported in coastal areas: 10.59–12.35 [13]; 10.44–12.39 [12]; 12.40–13.10 [83]. This might be due to the presence of a single class of strong ligands in this study area. These values suggest that the bioavailability and potential toxicity of copper in Mersing coastal waters are within the expected range for coastal waters, where complexation with strong ligands helps control the free copper ion concentrations. This shows that the dCu was fully saturated with the organic ligands in the water column, which reduced the concentration of free metals ions.

Apart from ligand saturation, the binding strength of the Cu–ligand complex is also important in regulating the free Cu²⁺. The conditional stability constant (log K′) serves as an indicator of the binding strength between Cu and the complexing ligand, and was revealed by the presence of only strong ligands (L₁) (log K′ > 12) throughout this study area (Figure 7a) [8,11]. The mean log K′ value in these studies was found to be in the range of 14.77 (season 1) to 15.30 (season 2) (Figure 7a), with a mean L₁ concentration in the range from 7.66 nM (season 1) to 11.74 nM (season 2) (Figure 7b). Weak ligands have lower conditional stability constants (generally log K′ < 12) and form less stable complexes, making metals more readily available for biological uptake or transformation [103]. It influences the bioavailability and reactivity of the metal, where a strong complexation could reduce the activity and inhibit the presence of free Cu²⁺ ions in the water column. Figure 6 demonstrates that the lowest concentration of Cu²⁺ was found in season 2, which had the highest ligand concentration and binding strength (Figure 7).

Other research has similarly reported the occurrence of one strong ligand class in coastal regions, such as the Bohai Sea, China (log K′ = 12.70 to 13.60) [83], Pulau Perhentian, Malaysia (log K′ = 12.04 to 12.96) [12], Venice lagoon, Italy (log K = 12.50 to 14.20) [104], and the East China Sea, China (log K′ 13.1 to 15.1) [84]. These strong ligands, characterized by high conditional stability constants, effectively bind dissolved metal ions, forming stable complexes that significantly reduce the levels of free, bioavailable metal ions [100,105]. This process is critical for mitigating the toxicity associated with free metal ions in seawater, as strong ligands can complex more than 99% of dissolved metals, thereby minimizing the concentration of toxic free ions. In this study area, the findings (Table 7) indicate that more than 99.95% of dissolved Cu(II) was bound to strong ligands, underscoring the ligands’ critical role in controlling metal bioavailability and toxicity in coastal waters. Thereby, the concentration of free Cu²⁺ ions in Mersing coastal water remained low and stable across sampling seasons.

Spearman correlation reported a negative strong correlation between CuL and pH (r = −0.482), salinity (r = −0.688), and conductivity (r = −0.575) (

Table 8. Correlation of CuL and log K′ and physicochemical parameters.

		pH	Temp	Cond.	Salinity	DO
CuL	r	−0.482	−0.034	−0.575	−0.688	0.245
	Sig.	<0.001	0.766	<0.001	<0.001	0.029
	N	80	80	80	80	80
log K′	r	−0.154	0.167	−0.299	−0.379	0.138
	Sig.	0.173	0.138	0.007	<0.001	0.221
	N	80	80	80	80	80

). It indicated that the changes in CuL concentration between seasons are highly related to pH, salinity, and conductivity.

This result suggests that 36% and 28.1% of the variation of CuL was influenced by the salinity and pH. The DO had the least effect on the variation of CuL (Figure 8). Season 1 and season 4 exhibited a constant lower concentration of CuL due to a higher salinity (33.56 ppt and 30.17 ppt, Figure 3c) in the water column. In contrast, CuL concentration was found to be the highest in season 2, which was observed to have a lower salinity in the water column (Figure 7b). The negative correlation of salinity and ligand concentration is in line with previous studies [60,83]. This suggests that the sources of ligands could be freshwater influx or river discharge during the NEM in Mersing coastal areas.

The highest log K′ value was observed in season 2 (15.30), while the lowest (14.77) was in season 1. The lower log K′ (14.77) values in season 1 suggest weaker ligands than the other seasons. This might be due to the higher salinity during season 1. The higher the salinity in the water column, the weaker the binding strength, leading to a lower log K′ value in season 1 (Figure 9). Spearman correlation analysis showed a moderate negative correlation between log K′ and salinity (p < 0.001, r = −0.379) (Table 8). In contrast, the higher log K′ values observed during season 2 indicate the presence of strong ligands that form stable complexes with copper under a lower-salinity condition. This result was supported by the study of Hollister et al. (2021), who reported that high salinity results in a significant electrostatic effect, which reduces the attraction between metal ions and the natural organic ligands [61]. In this study, log K′, as an indicator for the binding strength of natural organic ligands, does not have any significance correlation with pH, temperature, or DO (p > 0.05) (Table 8). The seasonal changing of pH, temperature, and DO does not influence its binding strength.

According to previous studies, acidic conditions could reduce the binding strength in the water column, which is in contrast with the findings of our study [5]. In this study, concentrations of CuL and Log K′ values were found to be the highest during season 2, which had the most acidic conditions (pH 8.07) compared to the other four sampling seasons. In this case, the lower pH (Figure 3a) did not weaken the binding strength of ligands when comparing among the four sampling seasons (Figure 7a). As discussed earlier, there was possibly an occurrence of upwelling or a vertical mixing process during season 2. Hence, it is suggested that the sources of strong ligands in this study might be released from the sediments during the upwelling/vertical mixing process during season 2.

In this study, only strong ligands were found to have the same detection windows as in previous studies in this study area [12,13]. However, this observation was different to those in previous studies for coastal areas, where both weak and strong ligands were detected at Pulau Pangkor, Malaysia. Godon et al. (2018) revealed that pH influences the binding strength of ligands, with acidic conditions (pH ~6) leading to the presence of two distinct classes of ligands [12]. This might be due to the seasonal effect of physicochemical parameters such as pH and salinity on the binding strength [37,106,107]. A decrease in pH (8.3 to 6.8) reduces the conditional stability constants of metal–ligand complexes, which indicates that fewer metals are bound to organic ligands, while more are present in their free ionic form [37]. Natural ligands may become less effective in metal binding due to competition from increased hydrogen ion concentrations under acidic conditions. At a lower pH, the dissociation of organic ligands can reduce binding strength, leading to increased bioavailability and potential toxicity of free Cu. Our study area had a smaller variation in pH, 8.07 (season 2) to 8.74 (season 4), as the monsoon event could not have much impact on the binding strength of organic ligands. Drastic changes in pH are often caused by anthropogenic activities that lead to increased levels of CO₂, such as deforestation and hydropower dams [61]. Therefore, only strong ligands were detected in this study area, playing a crucial role in regulating the bioavailability and toxicity of dissolved Cu(II). Although the CuL was in the range of 7.66–11.74 nM, the strong Cu organic ligands lowered the Cu²⁺ concentration, ensuring that the Cu was bioavailable for biological processes rather than toxic.

4. Conclusions

In conclusion, this study identified that seasonal variations in pH, salinity, temperature, DO, and conductivity, under the influence of NEM events, do not significantly influence the dissolved Cu(II) concentration. Our findings highlight the presence of strong ligands (L₁) in the Mersing coastal area which regulate the distribution of dissolved Cu(II) under the seasonal variation. The excess ligands and pCu remained consistent throughout the sampling seasons in this study, which proves the role of organic ligands. The presence of strong ligands in this coastal region suggested their influence on the distribution of Cu(II) speciation, which regulated the complexation of dissolved Cu(II) with natural organic ligands. Future research should prioritize the speciation of Zn(II), Pb(II), and Cd(II) and reveal how the organic ligands regulate the bioavailability of dissolved metals under varying in situ parameters.