The Consequences of a Lack of Basic Sanitation in the Municipality of Maricá (Rio de Janeiro, Brazil) Resulting in Low Concentrations of Metals but Dissemination of Endocrine Disruptors Through Local Environments: Subsidies for Local Environmental Management

Abstract

Endocrine-disrupting compounds (EDCs) are emerging pollutants that can potentially accumulate in aquatic ecosystems at significant levels, with the potential to impact the health of both animals and humans. Many scientists have correlated human exposure to high concentrations of EDCs with critical physiological impacts, including infertility, thyroid imbalance, early sexual development, endometriosis, diabetes, and obesity. Several substances, such as heavy metals, belong to this family, ranging from natural to synthetic compounds, including pesticides, pharmaceuticals, and plastic-derived compounds. Domestic sewage represents a significant source of EDCs in the surrounding aquatic ecosystems. To this day, most rural and urban domestic wastewater in the municipality of Maricá is directly discharged into local aquatic environments without any treatment. The present study aimed to assess the potential contamination of the riverine and lagoonal environment in the municipality of Maricá. Water and sediment samples were collected seasonally at 18 sites along the Maricá watershed and the main lagoon, into which most of the watershed’s contributors flow. Water physico-chemical parameters (pH, reduction–oxidation potential—Eh, dissolved oxygen levels, salinity, turbidity, temperature, and fecal coliforms) were analyzed to characterize the urban influence on the aquatic environment. Sediment samples were also analyzed for grain size, total organic carbon percentage, potential bioavailable fraction of trace metals (Cd, Pb, Cu, Cr, Hg, Ni, Zn), and metalloid As. Finally, the sediment toxicity was assessed using yeast estrogen screen (YES) assays. The results obtained already demonstrate the presence of estrogenic effects and raise concerns about water quality. The current study indicates that, despite the absence of agricultural and industrial activities in the city of Maricá, EDCs are already present and have the potential to impact the local ecosystem, posing potential risks to human health.

1. Introduction

Human activities have introduced several emerging pollutants into global ecosystems. Among these pollutants, endocrine-disrupting compounds (EDCs) are a significant group of compounds widely found in aquatic environments. EDCs belong to various chemical groups, including xenobiotic chemicals also present in industrialized products such as children’s toys, everyday utensils, plastic containers or bottles, polyvinyl chloride pipes, cleaning agents, and cosmetics [1,2]. As EDCs degrade and their constituent chemicals and by-products diffuse through the environment, they can influence the hormonal balance of living organisms by neutralizing or counteracting natural hormones [3,4]. Consequently, these pollutants can interact with the endocrine receptors in the bodies of living species, generating “false” hormonal signals that can potentially stimulate or inhibit endocrine system function [5,6]. The presence of these contaminants in freshwater environments is a significant concern, as organisms are chronically exposed to them. Well-documented examples of harmful impacts resulting from EDC exposure include sexual effects and the feminization of male fish [7], inhibition of the molting process in crustaceans [8], and alterations in fish behavior [9]. Human exposure to EDCs can occur through ingestion, inhalation, and dermal absorption [10], and may lead to various negative health impacts, such as the development of type 2 diabetes, obesity, cardiovascular abnormalities, and certain types of cancer [11]. Therefore, comprehensive knowledge of the fate of these pollutants in all of the environmental compartments involved is crucial for assessing the potential risks associated with the discharge of domestic wastewater effluents.

Typically, heavy metals in water are hard to break down due to their complicated ability to build up in living organisms. Mercury, lead, zinc, cadmium, iron, cobalt, manganese, and chromium are quietly researched and documented in the drinking water sources around the world. When people come into contact with heavy metals above safe levels, health issues may arise. Heavy metals are very harmful and are mostly cancer-causing because they can build up in sight and sensing organs. They also have the potential to damage body tissue and other organs, leading to various diseases including cancer. For example, a recent review [12] indicates that arsenic can lead to several health problems including heart, blood, nerve, lung, and stomach issues, birth defects, skin conditions, and cancer when exposed [13].

The world’s water circulation represents a dynamic system that plays a vital role in promoting biogeochemical cycles [14]. Rainfall runoff, which is dominated by rain events [15], washes pollutants from building walls, roofs, streets, land surfaces, and improperly disposed wastes, carrying them into local rivers and other aquatic bodies [16,17]. In the case of water receptor pools, such as lagoonal systems, these environments are sensitive ecosystems situated at the interface between terrestrial and marine coastal environments [18]. Globally, lagoonal environments make up 13% of the Earth’s coastline [19], each having unique features and sensitivities, making them essential natural habitats for the Earth’s biodiversity. Lagoonal systems are also significant for human activities, serving as protected sites for aquaculture, tourism, and recreational purposes. However, uncontrolled exploitation of these coastal environments can lead to negative ecological impacts and disrupt the local ecosystem. Lagoons typically have limited water circulation, making them susceptible to contaminant accumulation [20,21]. Therefore, assessing water quality in the contributing watershed and lagoonal ecosystem is crucial for ecological management, as it depends on the interaction of physical, chemical, and biological mechanisms.

In recent years, the revenue of the Maricá municipality has been rapidly increasing due to the policy of distributing royalties from oil production in the Santos basin [22]. Consequently, there is expected to be accelerated investment in the development and industrialization of the municipality. However, according to Nogueira and Barbosa (2018) [23], the municipality exhibits a low rate of basic sanitation infrastructure installation, with incomplete water supply and sewage networks.

Considering that urban sustainability is more effective when environmental policies are implemented while cities are still relatively small in size [24,25], the main objective of this article is to support the management of local urbanization and industrialization. Therefore, the present study aims to evaluate the potential presence of EDCs in Maricá’s riverine and adjacent lagoonal complexes, assess their potential toxicity, and diagnose current environmental toxicity. This assessment will help in projecting potential environmental impacts associated with expected industrial development.

2. Study Site

The city of Maricá is located in the metropolitan area of the city of Rio de Janeiro, situated between the geographic coordinates of 22°53′ and 22°58′ S and 42°40′ and 43°00′ W. The municipality has a population of over 150,000 and is growing daily [23].

The local predominant climate is classified as tropical hot and super humid [26]. In recent decades, the average annual temperature fluctuates between 27 °C and 30 °C, with annual precipitation ranging from 1015 mm to 1635 mm [27]. The spring and summer seasons experience the highest levels of annual precipitation, with relative air humidity typically ranging between 80% and 90% due to marine influence [28].

The Maricá municipality is situated within a series of coastal plains that extend to the Jurubatiba National Park, which is located in the municipalities of Macaé, Carapebus, and Quissamã [29]. This coastal plain is characterized by the presence of double coastal ridges and associated lagoons, forming the Maricá-Guarapina Lagoon System. This system is connected to the Atlantic Ocean by a channel at the eastern end of this coast [30].

The Araçatiba Lagoon (also known as the Maricá Lagoon) (Figure 1) has a total area of 18.2 km². Its associated drainage basin mainly receives water from the Ubatiba river basin, which is formed by small watercourses originating in the municipality. These watercourses flow into the lagoon system, including the Mumbuca river, the Camburi, Imbassaí, Itapeba, and Burriche streams that flow into the Araçatiba Lagoon, as well as the Padre Guedes, Caju, and Rangel streams, which have their mouth in the Barra Lagoon. Additionally, the rivers Doce, Bananal, Engenho, Nilo Peçanha, and Paracatu, along with their tributaries Manuel Ribeiro, Caranguejo, and Padeco, flow into the Guarapina Lagoon.

The Araçatiba Lagoon was chosen for this study because previous research identified it as one of the most degraded in the system [31,32]. Furthermore, studies such as the one by Knoppers et al. (1991) [33] have already characterized the lagoon as eutrophic, with urban development and population growth in the municipality leading to deforestation, the presence of clandestine landfills, and the release of untreated effluents [33,34].

3. Methodology

Five sub-basins within the Maricá watershed were selected as the study area, along with the Araçatiba Lagoon (Figure 1). The choice of sampling stations was influenced by the adjacent occupation scenario, which has been a result of the recent, uncontrolled growth in the municipality’s population, potentially impacting water quality. Surface water samples were collected at 18 sampling stations during both the dry season (21 August) and the wet season (22 February). A Van Dorn water sampler (5 L) was used to collect water.

A stainless steel spatula and a Van Veen grab sampler were used to collect surface sediment samples. After collection, the samples designated for the yeast estrogen screen (YES assay) were transferred to 200 mL amber glass bottles. For the analysis of metal concentrations and physicochemical characteristics (grain size and organic matter content), sediment samples were stored in polyethylene plastic bags.

The surface water samples collected for the analysis of E. coli were stored in 200 mL plastic bottles. Additionally, a pre-calibrated multiparameter probe (Horiba-U50, Kyoto, Japan) was employed to assess water column physicochemical parameters, including temperature, pH, redox potential, turbidity, dissolved oxygen (DO), and salinity.

After collection, the samples were stored in ice and subsequently transported to the laboratory. Surface sediment samples intended for the yeast estrogen screen (YES) assay were subjected to solid-phase extraction (SPE) and ultrasonic treatment to extract and isolate the target compounds within 48 h of collection. Water samples for the determination of Escherichia coli were also processed within the same timeframe using the most probable number (MPN) method to estimate bacterial concentrations.

In order to avoid interference with the final analysis results, all instruments and glassware used for sample collection and preparation in the laboratory were pre-cleaned through sequential washing with neutral detergent (Extran^®, Merck, Darmstadt, Germany), followed by acetone, hexane, and ultrapure water to ensure thorough decontamination.

3.1. Water Column Parameters

The presence and concentration of Escherichia coli in water samples were determined using the most probable number (MPN) method, following the guidelines outlined in the Standard Methods for the Examination of Water and Wastewater [35]. Briefly, 100 mL of each water sample was filtered through a membrane filter with a 0.45 μm pore size. The filter was then transferred to a selective culture medium specific for E. coli and incubated at 35–37 °C. After 24 h of incubation, the development of E. coli colonies was assessed to confirm their presence.

3.2. Sediment Parameters

The characterization of sediment quality was carried out through the analysis of total organic carbon (TOC%) and grain size, trace metals (Cd, Pb, Cu, Cr, Hg, Ni, and Zn), and metalloid As. The TOC% and grain size analysis were carried out according to the Embrapa Manual (1997) [36]. Trace metal samples were maintained in pre-acidified plastic bowls and transported to the laboratory for analysis. For grain size determination, organic matter was first removed with hydrogen peroxide (30%). Then a Microtrac S3500 (Microtrac, Haan, Germany) grain size analyzer was used. The results were categorized into sand, silt, and clay classes. The fine class content (below 0.063 mm) was used for trace metal evaluation. The approach for the heavy metal and As determination in sediments was carried out using the method described by the Environmental Protection Agency (EPA), method 3050b [37]. According to the referenced methodology, 15.0 mL of 65% concentrated nitric acid (HNO₃) was added with 0.50 g of fine sediment in the pipes of the digestor block. Still, according to the cited method, after 12 h, it was heated until 160 °C, remaining at this temperature for 4 h. Then, 8.0 mL of hydrogen peroxide 30% (v/v) was added and the solution was maintained at 160 °C for an additional 30 min. Finally, the samples were transferred to a volumetric balloon of 100.0 mL and filtrated. Sample blanks and a reference sediment WQB-1 from the National Laboratory for Environmental Testing, Burlington, Canada was also used at regular intervals to monitor quality control. After centrifugation and further dilution, As, Cd, Pb, Cu, Cr, Ni, Hg, and Zn were read by inductively coupled plasma-atomic emission spectrometry (ICP-AES). The detection limits are as follows: Pb, 1.3 mg·kg⁻¹; Cu, 1.3 mg·kg⁻¹; Ni, 0.8 mg·kg⁻¹; Zn, 1.5 mg·kg⁻¹; Cd, 1.0 mg·kg⁻¹; As, 1.2 mg·kg⁻¹, and Cr, 1.5 mg·kg⁻¹. The recovery rates for the trace metals varied between 87.8 and 102.5%. All utensils, tools, and equipment were acid-washed with 10% nitric acid (HNO₃) and rinsed with distilled water to avoid potential procedure contamination. Certified standard material was used to assure the accuracy of the analytical procedures (SPEX-QC-21-16-85 AS-traceable to NIST). The maximum value for precision data was 5%.

The mercury approach was performed according to the USEPA-7471 method, through cold vapor atomic adsorption (USEPA 1997 [38]). This method involves mixing 0.2 g of the sample mass with 5 mL of reagent water and 5 mL of aqua regia, then heating the solution for 2 min in a 95 °C water bath, then adding 50 mL of double deionized water and 15 mL of 10% KMnO₄ solution. After 30 min the samples were transferred from the bath, and once cooled, 6 mL of a solution of 10% sodium chloride–hydroxylamine sulphate was incorporated to reduce the residual KMnO₄. The detection limit for Hg reached 0.0148 mg·kg⁻¹.

Chlorophyll a was determined spectrophotometrically following extraction with 90% acetone. Water samples were filtered through glass fiber filters (e.g., GF/F), which were then placed in 90% acetone and stored in the dark at 4 °C for 12–24 h to allow pigment extraction. The extract was centrifuged to remove particulate matter, and absorbance was measured at specific wavelengths (typically 665 nm and 750 nm) using a spectrophotometer. The chlorophyll a concentration was calculated using standard equations corrected for pheophytin interference.

3.3. Estrogenic Activity (YES Assay)

The methodology used to prepare the sediment sample was solid phase extraction (EFS), based on Routledge and Sumpter (1996) [39] with modifications, according to Gomes et al. (2023) [40]. The sediment samples collected for the YES assay were placed in an oven at 60 °C for 24 h, macerated, and 10 g was placed in a beaker for extraction by sonication with methanol (10 mL/5 min). Subsequently, the samples were centrifuged (2500 g/5 min) (NT 812—Nova Técnica^®, São Paulo, Brazil) and the supernatant was collected and transferred to a 200 mL volumetric flask. This procedure was repeated three times, with the supernatants combined in the same volumetric flask, which was finally added to the volume with ultrapure water until 200 mL and HCL (3 mol·L⁻¹) was added to adjust the pH to 2.

Samples were purified using two EFS columns, Strata-X and Strata-SAX (Torrance, CA, USA^®). Both were previously conditioned, the first with a sequence of 2 × 3 mL of hexane, 2 mL of acetone, 2 × 3 mL of methanol, followed by 10 mL of ultrapure water (pH 3), and the second with 2 × 5 mL of methanol and 2 × 5 mL of ultrapure water. The Strata-SAX cartridge was attached to the top of the Strata-X cartridge and 200 mL of the sample was then percolated through both cartridges in a manifold system with a flow rate of 3 mL s⁻¹. In the end, the cartridges were uncoupled and the EFS procedure continued with just the Strata-X cartridge. The cartridges were cleaned up with a methanol–water solution (1:9 v/v) and followed by complete drying through vacuum aspiration for 10 min. Finally, the analytes of interest retained in the cartridge were eluted in a vial with 2 × 2 mL of acetone. The extracts were evaporated under vacuum, reconstituted with 2 mL of ethanol, covered, homogenized in a vortex (2 min/30 rpm), and subjected to the YES assay.

The in vitro assay uses the yeast Saccharomyces cerevisiae, which has a human estrogen receptor DNA sequence in its genome. In the presence of an estrogenic compound, it interacts with this receptor, causing the expression of a gene and, consequently, the production of the enzyme β-galactosidase. This enzyme is secreted into the medium and produces a colorimetric response, with the degradation of the chromogenic substrate chlorophenol red-β-d-ga-lactopyranoside (CPRG), which is yellow, into chlorophenol red (CPR), a pinkish product [41].

In a laminar flow hood, the assay was performed in sterile 96-well microplates with 12 serial dilutions of the samples in ethanol (HPLC grade). 17β-estradiol (E2) was used as a positive control and ethanol (HPLC grade) was used as a negative control. The dose–response curves of E2 (2724 to 1.33 ng·L⁻¹) were prepared by serial dilutions of E2 and ethanol from a stock solution at 54.48 μg·L⁻¹. A 10 μL aliquot of each sample dilution was transferred to microplates, in duplicate, and evaporated at room temperature. Next, 200 μL of analysis medium (growth medium, yeast, and CPRG) were added to the wells. The microplates were sealed, shaken vigorously in a plate shaker (IKA MS3^®, Artisan Technology Group, Champaign, IL, USA), and incubated for 72 h at 30 °C in an incubator (Nova Ética, 410^®, Nova Ética, São Paulo, Brazil). After incubation, colorimetry and turbidity were measured at 575 nm and 620 nm, respectively, on a spectrophotometric plate reader (Spectramax M3, Molecular Devices^®, San Jose, CA, USA). The absorbance values read on the assay plate were corrected (Equation (1)).

$${\mathrm{Abs}}_{\mathrm{corrected}}={\mathrm{Abs}}_{575 \mathrm{sample}}-\left({\displaystyle \frac{{\mathrm{Abs}}_{620 \mathrm{sample}}}{{\mathrm{Abs}}_{620 \mathrm{blank}}}}\right)$$

(1)

The estrogenic activity of each sample was calculated based on the maximum induction of β-galactosidase in each sample extract. This was done in 17β-estradiol equivalent (EQ-E2) by interpolating the sample curve data with that of the control curve, positive E2 (in ng·L⁻¹). To obtain the real EQ-E2 value of the sediment sample, it was necessary to divide the EQ-E2 value by the concentration factor used in the EFS.

Another calculation procedure carried out was cytotoxicity; that is, the inhibition of the growth of the yeast Saccharomyces cerevisiae due to toxic compounds present in the sample, which translates into the absence of turbidity at the end of the test. To quantify this effect, absorbance control was performed at 620 nm in each well (Equation (2)), as described by Frische et al. (2009) [42].

$$\mathrm{Cytotoxicity}=1-\left({\displaystyle \frac{{\mathrm{Abs}}_{620 \mathrm{sample}}}{{\mathrm{Abs}}_{620 \mathrm{blank}}}}\right)$$

(2)

3.4. Statistical Analyzes

Spearman correlations (r) were calculated between the variables to evaluate the possible relationship between chlorophyll-a, E. coli, and the physicochemical parameters analyzed in the water and, for surface sediments, the possible relationship between EQ-E2 and physicochemical parameters. Correlation strengths were considered according to Dancey and Reidy (2006) [43], where values of r < 0.4 show a weak correlation, 0.4 ≤ r < 0.7 moderate, and r ≥ 0.7 strong. Correlations above 0.7 (p < 0.05/n = 18) were considered significant. Principal component analysis (PCA) was also performed to explore the relationships between all variables.

4. Results and Discussion

4.1. Water

Throughout the research, salinity data exhibited distinct patterns among the various compartments studied, particularly between the sampling stations located within the water contributors and those within the lagoon. Sampling sites in the river basin generally displayed lower salinity values, indicating the presence of freshwater, except for sampling stations C05 and C06, where there appears to have been a potential momentary failure of the multiparametric probe used (Figure 2). As the stations approached the lagoon, salinity levels increased, indicating saline intrusion beginning at the mouths of rivers and canals. Seasonal fluctuations were evident, with the lowest values observed during the rainy season due to dilution from rainfall. However, the salinity values in the Araçatiba Lagoon suggested the influence of marine waters, despite the lagoon’s isolated nature within the lagoon system. Furthermore, the absence of local tidal patterns consistent with the adjacent sea level implies a source of seawater intrusion other than surface intrusion.

Moore (1999) [44] defined the subsurface soil zone where meteoric groundwater mixes with saltwater as a subterranean estuary. In the specific case of Maricá, this term is not limited to groundwater. The overexploitation of groundwater, likely caused by a lack of sufficient fresh water for the local population’s supply, has allowed the percolation of saltwater and subsequent salinization of surface water compartments. According to Mastrocicco and Colombani (2021) [45], one of the major concerns in coastal regions is the progressive salinization of freshwater compartments, which is driven by increasing demand for freshwater, climate change, and land use modifications. Consequently, freshwater salinization has garnered significant attention from the scientific community in recent years [46,47,48,49].

Regarding temperature, this parameter remained relatively stable, with winter temperatures ranging from 21.3 °C to 27.1 °C and summer temperatures from 26.7 °C to 34.47 °C (Figure 3). In contrast, pH values varied between 6.1 and 9.0 throughout the research. In terms of environmental quality, the pH values in the study area indicate relatively healthy environmental conditions since the water column’s acidity is not significantly accentuated (Figure 4). Two main characteristics of the system likely contribute to this: the lagoon’s shallow nature, allowing for effective atmospheric oxygen diffusion, especially during windy weather, and the presence of a relatively narrow sandy ridge separating the lagoon from the sea, which may buffer the lagoon’s waters due to underground percolation of saltwater [50]. This is further supported by the moderate correlation between pH and salinity observed during statistical analysis (R: 0.63212).

Furthermore, the Eh (redox potential) did not exhibit extreme reduction characteristics during the winter, with the exception of points C03, C04, and C08 (Figure 5). In contrast, during the summer, particularly during the vacation season, the increased potential for waste disposal and the influence of rainfall may contribute to enhanced reducing conditions in the contributing channels. Once again, the most compromised conditions were observed in the more confined areas, which are potential locations for domestic sewage disposal. Dissolved oxygen data followed this trend, with levels ranging from 0.3 mg/L to 10.1 mg/L. Oxygen levels in the contributing channels were significantly lower than those in the lagoon, underscoring the importance of atmospheric oxygen diffusion and the distance from sewage sources in maintaining water quality (Figure 6). Turbidity, on the other hand, exhibited a random pattern with no clear trends in terms of seasonal or spatial variations (Figure 7).

Finally, concerning water quality, the coliform concentrations corroborate the domestic origin of the pollution within the watershed of the city of Maricá (Figure 8). Based on this data, with the exception of the collection points within the lagoon, all other points exhibited the presence of sewage waste discharge. Particular consideration should be given to point L1 inside the lagoon, especially during the summer, where coliform levels already indicate the influence of contributors into the lagoon.

4.2. Sediment

Based on the results of the sediment physicochemical analysis, there is a significant difference in the predominant grain size concentrations between the watershed contributors and the lagoonal sampling stations (Figure 9). Along the contributor channels, coarse particles predominate, while in the lagoon, fine sediment particles are prevalent. This pattern can be attributed to the stronger water flow along the rivers and other channels that flow into the lagoon compartment. As water salinity increases, ions dispersed in the water column tend to group together and settle, a phenomenon known as flocculation. This leads to the accumulation of fine particles at the estuary mouths [51].

Similarly, the percentage of total organic carbon (TOC%) was found to be higher in the lagoonal sampling stations (Figure 10). The increased fluxes in the contributing channels appear to prevent the accumulation of TOC in these channels, even in conditions of lower oxygen levels that would typically conserve organic matter loads. Another possible explanation could be the higher presence of TOC in the soluble phase, although this parameter was not analyzed in the current study.

Regarding heavy metal concentrations, all the studied elements generally exhibited low concentrations, when compared to the existing literature (

Table 1. Concentration of heavy metals in sediments available in the scientific literature.

	Heavy Metal	Cu	Zn	Pb	Cd	Ni	As	Cr	Hg	Reference
Reference
Maricá’s watershed and lagoon		n.d.–47.9	5–232	1.07–34.41	n.d.–2.89	n.d.–22.9	n.d.–9.62	0.42–77.42	n.d.	Present Study
Barra de Navidad and Colima Lagoon (Mexico)				42.7–123.9	0.02–0.42		10.7–25.4		n.d.	[52]
Global average shale		45	95	20	0.30	68	4.70	90	0.18	[53]
Red Sea		92	227	64	-	51	-	60		[54]
Shantou Bay (China)		19.0–48.0	44.4–962.6	21.9–102.9	0.2–3.6	8.2–48.0	-	23.7–80.0	-	[55]
ERL		34	150	47	1.2		8.2	81	0.15	[56]
ERM		270	410	218	9.6		70	370	0.71
Non-polluted		<25	<90	<40	-	-	<3	<25	≤1.0	[57]
Moderately polluted		25–50	90–200	40–60	-	-	3–8	25–75	-
Heavely polluted		>50	>200	>60	>6	-	>8	>75	>1.0

). However, some isolated results already indicate potential threats to the ecosystem and living organisms. Nevertheless, the assessment of metal concentrations carried out in the present study confirmed the domestic source of pollution already present in Maricá’s water bodies. It also revealed that despite climatic variations, these variations do not significantly affect the diffusion of metals, as no significant concentration variations were observed (Figure 11, Figure 12, Figure 13, Figure 14, Figure 15, Figure 16 and Figure 17).

4.3. Estrogenic Activity by the YES Assay

For the study’s objectives, the results were deemed satisfactory. The estradiol dose–response curves (positive control) exhibited the anticipated sigmoidal shape, and no contamination was detected in the negative control (white). The average EC50 value for the estradiol dose–response curve for the sediment samples was 38 ± 10 ng·L⁻¹, and the LD (limit of detection) was 0.02 ± 0.01 ng·L⁻¹. The results of the estrogenic activity of the surface sediment samples obtained using the YES assay are depicted in Figure 18 and Figure 19.

Concentrations ranged from below the limit of detection (<LD) to 8.03 ng·g⁻¹. Among the eighteen collection points, only four exhibited cytotoxicity (C02, C06, CL2, and CL3), preventing the assessment of estrogenic activity. In other words, the presence of other pollutants rendered the bioindicator strain unable to reproduce. Conversely, all sampling stations located in the channels and the areas where they connect with the lagoon demonstrated estrogenic activity, with particular emphasis on CL1, which had an EQ-E2 of 8.03 ng·g⁻¹. Among the points within the lagoon, five did not exhibit estrogenic activity, while among the six that did, the one with the highest concentration was L04, situated in the middle of the lagoon, with an EQ-E2 value of 0.16 ng·g⁻¹.

Pusceddu et al. (2019) [58] investigated the presence of estrogens in surface sediments of one of the most industrialized and urbanized estuary systems in Latin America, the Santos and São Vicente estuarine system in the state of São Paulo. They found significant levels of E3, E2, and EE2 in nearly all samples. The authors linked the presence of estrogens to proximity to domestic sewage outfalls, but they also detected contaminants in other areas originating from diffuse sources, such as irregular domestic sewage disposal from regions not covered by sewage services, underscoring the need for studies of these contaminants to not focus solely on point sources.

Lima et al. (2019) [59], in a study aiming to characterize anthropogenic and natural impacts in a coastal zone (Rio Pacoti—CE) involving emerging and traditional organic markers, found that the type of contamination is directly related to the source closest to the sampled points. Estrogens and steroids were quantified in greater quantities in areas near sewage discharges, while n-alkanes were associated with terrigenous sources and hydrocarbons with natural sources, particularly pyrogenic.

Pimentel et al. (2016) [60] examined the morphofunctional parameters of the tropical fish Sphoeroides testudineus (Baiacu Mirim) in an area (Rio Pacoti—Ceará) potentially contaminated by estrogens. Sediment analyses at the fish collection point indicated high contamination by natural (276 ng·g⁻¹) and synthetic (523.97 ng·g⁻¹) estrogens. Vitellogenin (VTG) expression was detected in mature males and undifferentiated fish, indicating endocrine dysregulation, and suggesting contamination with estrogens in the region.

Morais et al. (2020) [61] conducted an environmental diagnostic study to support the development of coastal environmental management policies in a coastal lagoon on the coast of the state of Ceará, with multiple anthropogenic sources related to urban and rural activities involving sterols and estrogens. Sediment analysis results indicated high contamination by synthetic estrogens (EE2 and DES), widely used in contraceptives and various female hormonal treatments, as well as in livestock production to improve productivity. These compounds have a higher octanol–water partition constant (Kow) compared to natural estrogens, contributing to their adsorption to sediment. Among natural estrogens, a higher concentration of E1 was found, possibly related to the oxidation of E2 to E1 in the environment. The environmental diagnostic study revealed moderate to high contamination by sewage.

The presence of estrogenic activity in sediments observed in this study is directly associated with points located near sewage disposal sources, corroborating findings from other studies [62,63,64]. Sediments from water bodies located along the lagoon’s banks exhibited higher EQ-E2 values. This can be explained by the fact that they receive contributions from the basins before flowing into the lagoon, thus receiving a greater influx of domestic wastewater containing high concentrations of estrogenic compounds.

4.4. Statistical Analysis

As for the results of the YES assays, they showed a moderate inverse relationship with pH (

Table 2. Spearman correlation test applied in the present study.

	Temp (°C)	pH	ORP	Turbidity	DO (mg·L−1)	Salinity	E. coli	COT (%)	Fine Sediment	EEQ-E2	As	Cd	Pb	Cu	Cr	Hg	Ni	Zn
Temp (°C)		0.78168	0.071271	0.014823	0.00824	2.85 × 10−6	3.65 × 10−2	0.11622	0.49648	0.99101	0.37143	0.49311	0.3296	0.82113	0.491	0.056701	0.52227	0.83226
pH	−0.07028		0.93997	0.98377	0.59932	0.63212	0.11802	0.060061	0.12407	0.021983	0.81756	0.28844	0.098122	0.19539	0.12498	0.16024	0.18078	0.46851
ORP	0.43492	0.019121		0.23589	0.000122	0.007643	1.42 × 10−4	0.095315	0.003466	0.29345	0.63756	0.39162	0.004436	0.18149	0.005251	0.1141	0.011922	0.32828
turbidity	−0.56376	−0.00517	−0.29427		0.29905	0.009718	0.37673	0.52023	0.86121	6.56 × 10−1	0.93767	0.40091	0.75073	0.50951	0.7322	0.44772	0.65609	0.44745
DO (mg·L−1)	0.60176	0.13282	0.78306	−0.25916		0.004925	0.000179	0.002411	0.001648	0.19935	0.92036	0.48976	0.002533	0.083402	4.44 × 10−3	0.046943	0.009357	0.23711
Salinity	0.86912	−0.12112	0.60631	−0.59152	0.63166		0.039879	0.024156	0.093291	0.57995	0.27499	0.059901	0.080153	0.3862	0.13494	0.18203	0.11204	0.56472
E. coli	−0.51007	−0.3936	−0.79392	0.22896	−0.78672	−0.50235		0.056077	0.031332	0.087656	0.51824	0.79498	1.97 × 10−2	0.71656	0.045332	4.19 × 10−5	0.08778	0.65954
COT (%)	0.38346	0.4514	0.40517	−0.16219	0.66873	0.52847	−0.47146		0.001425	0.007105	0.35801	0.010139	0.002489	1.23 × 10−2	0.006094	0.32052	0.006157	0.053431
Fine Sediment	0.1714	0.37603	0.65049	0.044376	0.68663	0.40745	−0.52272	0.69318		0.012163	0.81098	0.017428	1.17 × 10−7	0.00038	6.44 × 10−9	0.36719	3.99 × 10−9	0.000923
EEQ-E2	−0.00332	−0.60466	−0.30233	0.13053	−0.36505	−0.16204	0.49202	−0.68293	−0.64824		0.27026	0.001132	0.012233	0.011342	0.015243	0.56386	0.03375	0.042629
As	0.22406	−0.05853	−0.1192	0.019857	0.025386	0.27194	0.16839	0.23025	0.060674	−0.31649		0.090331	0.40869	0.10441	0.57003	0.11507	0.64648	0.13202
Cd	0.17848	0.27334	0.22208	−0.21786	0.17984	0.46517	0.07061	0.60462	0.56779	−0.77495	0.42344		0.020883	0.000953	0.028166	0.40923	0.007972	0.000633
Pb	0.2438	0.40207	0.6374	0.080537	0.66632	0.42318	−0.55872	0.66718	0.91378	−0.64785	0.2075	0.55452		4.20 × 10−5	3.33 × 10−12	0.085608	7.35 × 10−10	0.000689
Cu	0.057364	0.32006	0.32972	0.16632	0.41912	0.21739	−0.0951	0.57653	0.74587	−0.653	0.39534	0.72663	0.8124		4.20 × 10−5	0.7787	1.38 × 10−5	2.18 × 10−9
Cr	0.17355	0.37519	0.6281	0.086732	0.6374	0.36627	−0.49104	0.61964	0.94063	−0.63235	0.14349	0.53136	0.97727	0.8124		0.23742	5.69 × 10−12	0.000142
Hg	0.48532	0.36846	0.41066	−0.20437	0.50318	0.35138	−0.85851	0.26539	0.24167	−0.18547	0.40966	−0.23016	0.44312	0.076344	0.31327		0.53911	0.59322
Ni	0.16141	0.33023	0.57838	0.11272	0.5939	0.38756	−0.4265	0.61905	0.94416	−0.56889	0.11607	0.61969	0.95499	0.83851	0.97569	0.16593		3.68 × 10−5
Zn	−0.05375	0.18252	0.24444	0.19112	0.29354	0.14545	0.11527	0.46225	0.71178	−0.54768	0.36884	0.74299	0.72351	0.94829	0.77829	−0.14457	0.81574

). This inverse relationship is consistent with findings in other coastal and lagoon environments, where increased salinity tends to lower pH due to the buffering capacity of seawater and ion exchange processes. The high salinity can also influence the availability of protons in the water, contributing to a decrease in pH levels [65]. Given that the environmental conditions in the lagoon are better than those of its contributors, and that its salinity naturally tends to be higher due to the influence of the adjacent sea, an inverse relationship between both parameters is expected. The same can be said between the concentrations of dissolved O₂ and fecal coliforms. In many aquatic systems, the direct disposal of sewage leads to increased organic matter, which is metabolized by microorganisms, consuming oxygen and resulting in hypoxic conditions. The presence of higher fecal coliform levels in polluted water systems further supports this relationship [66].

In the lagoon, on the other hand, the maintenance of oxygen concentrations is mainly due to the diffusion of this gas through the air–water interface, allowing for an abundance of oxygen for the degradation of the sludge deposited on the lagoon floor. The physical mixing of the water column, driven by tidal and wind action, enhances the oxygen transfer, which helps in the aerobic degradation of organic materials [67,68]. The rise in pH is also influenced by this trend, in addition to being stimulated by the buffering effect of carbonates present in seawater.

The application of the PCA test confirms most of the results already obtained by Spearman (Figure 20). The proximity between the turbidity axes and E. coli confirms the characteristics of high values of both parameters in the channels. The results of the YES assays are also found in the same quadrant. This test reflects the toxic effects of endocrine disruptors (EDs). Most of these compounds are not refractory in the environment and, therefore, must be continually released into the environment to maintain their negative effects on microorganisms. As a result, their concentrations are expected to be higher in the vicinity of the sources, confirming that in Maricá, the primary sources of EDs are domestic sewage flows.

The affinity between metals and fine sediments is also reflected in the PCA presented in this article. Finally, the physicochemical parameters of the water (dissolved oxygen, Eh, salinity, and temperature) all appeared to be in agreement and varying in parallel between the different compartments studied in the Maricá environment.

5. Conclusions and Future Perspectives

Throughout Brazil’s history, the oil production sector has consistently played a crucial role in the national economy. Current legislation mandates that municipalities adjacent to oil production areas receive compensation fees to address potential impacts generated by this activity. Maricá is one such municipality currently experiencing rapid development with a focus on industrialization and growth in other sectors. However, this intensive growth has not been accompanied by the necessary infrastructure to mitigate issues related to the exponential increase in its population. This study has examined the environmental conditions in the hydrographic basin of the Municipality of Maricá, as well as the Araçatiba Lagoon, which is the primary lagoon in the local lagoon system. The results clearly reflect the deficiencies in the municipality’s basic sanitation infrastructure.

The streams and tributaries that flow into the Araçatiba Lagoon were found to have high concentrations of coliforms and heavy metals, which ultimately end up in the lagoon system. These conditions have already demonstrated adverse effects on the local natural ecosystem, potentially leading to hormonal imbalances in the species inhabiting this ecosystem. According to the YES assays, the channels exhibit greater toxicity related to endocrine disruptors. Furthermore, the potential contamination of groundwater, which also serves as a source of drinking water, is a concerning issue. Sinkholes, commonly used as a sanitation method in Maricá, may be contributing to groundwater contamination. Future studies should thoroughly investigate the contamination of groundwater by endocrine-disrupting compounds (EDCs).

This study revealed that while heavy metal concentrations in Maricá’s water bodies were generally low compared to the literature, isolated cases indicated potential ecological threats. The findings confirmed a domestic pollution source, with metal diffusion remaining stable despite climatic variations. Estrogenic activity assessments using the YES assay demonstrated notable impacts in specific regions, particularly in areas connecting channels to the lagoon. However, cytotoxicity observed at certain points hindered estrogenic evaluation, suggesting interference from other pollutants. These results highlight the interplay between pollution sources and their hormone-disrupting potential, emphasizing localized risks to ecosystems and the importance of mitigation strategies.

Considering that Maricá currently lacks significant industrialization or agriculture, the situation is likely to worsen with the establishment of the industrial park, as part of the local government’s plans. This study underscores the importance of implementing an adequate sanitation infrastructure to support the city’s planned industrial development and its overall growth.