SciELO - Scientific Electronic Library Online

 
vol.49 issue5Using the nematode Panagrolaimus sp. in larval rearing of longfin yellowtail Seriola rivoliana: preliminary resultsCharacterization of rural small-scale rainbow trout (Oncorhynchus mykiss) farms in Mexico author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Latin american journal of aquatic research

On-line version ISSN 0718-560X

Lat. Am. J. Aquat. Res. vol.49 no.5 Valparaíso Nov. 2021

http://dx.doi.org/10.3856/vol49-issue5-fulltext-2628 

Short Communication

Heavy metals in sediment and fish from two coastal lagoons of the Mexican Central Pacific

Eduardo Ramírez-Ayala1  2 
http://orcid.org/0000-0002-1026-3571

Miguel A. Arguello-Pérez1 
http://orcid.org/0000-0002-4668-4669

Adrián Tintos-Gómez1  2 
http://orcid.org/0000-0002-7530-416X

Jorge A. Mendoza Pérez3 
http://orcid.org/0000-0002-8651-3506

Juan A. Díaz-Gómez2 
http://orcid.org/0000-0002-2792-0603

Rebeca Y. Pérez-Rodríguez4 
http://orcid.org/0000-0001-8293-1666

Gabriel Núñez-Nogueira5 
http://orcid.org/0000-0001-9217-6959

César A. Sepúlveda-Quiroz6 
http://orcid.org/0000-0002-7787-5249

Francisco A. Zepeda-González2 
http://orcid.org/0000-0001-7650-2259

Carlos Lezama-Cervantes7 
http://orcid.org/0000-0002-8772-2668

1Doctorate Program in Sciences in Biosystematics, Ecology, and Management of Natural and Agricultural Resources (BEMARENA), Department of Studies for the Development of the Coastal Zone University of Guadalajara, Jalisco, Mexico

2Renewable Energy Research Centre, Technical Secretariat of the Academic Area Manzanillo University of Technology, Manzanillo, Colima, Mexico

3National School of Biological Sciences of National Polytechnic Institute, Mexico City, Mexico

4DCNyE Spectroscopy, Chromatography and Calorimetry Services Laboratory, Department of Chemistry Division of Natural and Exact Sciences, University of Guanajuato, Guanajuato, Mexico

5Hydrobiology and Aquatic Pollution Laboratory, Academic Division of Biological Sciences (DACBiol) Juárez Autonomous University of Tabasco, Villahermosa, Tabasco, Mexico

6Laboratory of Tropical Aquaculture, Academic Division of Biological Sciences (DACBiol) Juárez Autonomous University of Tabasco, Villahermosa, Tabasco, Mexico

7Faculty of Marine Sciences, University of Colima, Colima, Mexico

ABSTRACT

The present work analyzed the concentration of As, Cd, Pb, and Hg in sediment and the Hg concentration in fish muscle from two coastal lagoons in the states of Jalisco (Barra de Navidad Lagoon) and Colima (Cuyutlán Lagoon), Mexico. Both lagoons showed relatively low levels of metal contamination and potential health risk compared to other Mexican areas. A non-carcinogenic hazard quotient (HQ) was determined. As (10.7 ± 1.3 - 25.4 ± 3.1 µg g-1) and Pb (42.7 ± 4.2 - 123.9 ± 14.7 µg g-1) concentrations exceeded the permissible levels, otherwise for Hg and Cd were below the limits. The highest total mercury concentration was found in Haemulopsis sp. and Lutjanus sp. with 0.23 and 0.1 µg g-1 (wet weight) respectively, out of 14 species of fish analyzed that are frequently consumed locally. HQ based on the national daily per capita consumption of fish in Mexico and the consumption of fish associated with fishing communities in Mexico showed an HQs >2, which manifests the vulnerability of these communities to persistent toxic and bioaccumulative contaminants.

Keywords: heavy metals; sediment; non-carcinogenic hazard quotient; fish intake; coastal lagoon; Mexico

Chemical pollution of aquatic ecosystems, particularly caused by heavy metals, is one of the most serious problems facing modern society. Both due to its significant contribution to the general degradation of aquatic ecosystems and the loss of biodiversity, as well as the immediate risk that it presents in terms of public health and food security (Reyes et al. 2016). This pollution presents a growing and multidimensional problem that is expected to worsen with population growth and the rapid increase in industrial areas worldwide, especially in countries with emerging economies (Ramírez-Ayala et al. 2018). Mexico is a prominent member of the mega-diverse countries, which has a considerable extension/surface of aquatic ecosystems of international importance. It is the second country with more wetlands registered in the RAMSAR agreement (RAMSAR Convention 2020). It also holds one of the largest human populations globally, being the 10th most populous country on the planet (UN 2019). Industrial developments include mining, oil, textile, and agricultural industries, cause a complicated balance between economic development and environmental protection. This contradictory scenario represents a significant challenge in the protection and responsible management of national aquatic ecosystems. In recent decades, international conventions and treaties, laws, norms, national policies, and monitoring programs (e.g. National Monitoring Network, CONAGUA 2017) have been established for promoting the protection and conservation of the country's aquatic ecosystems. However, the complex pollution scenarios in which a large part of the country's aquatic ecosystems are found (CONAGUA 2017) require even more efforts from the competent authorities and decision-makers to meliorate the problem (McCulligh 2014).

Mexico has a great wealth of aquatic ecosystems; however, many of these present considerable pollution levels. Although notable efforts have been made to monitor aquatic contamination, much remains to be done, especially in monitoring persistent toxic and bioaccumulative contaminants (PTBCs), as with heavy metals (e.g. mercury, Hg; cadmium, Cd; lead, Pb; or arsenic, As). Monitoring PTBCs such as toxic metals, particularly Hg, is crucial in the various environmental matrices because it estimates the potential health risk for aquatic ecosystems and humans. Heavy metals toxicity is a topic of increasing interest due to the high potential for bioaccumulation and biomagnification, mainly of Hg, considered one of the most dangerous elements, species-wise in its organic form as methyl mercury (MeHg) (Manavi & Mazumder 2018). MeHg appears in aquatic ecosystems mainly through bacterial biotransformation of inorganic Hg principally in the sediments, through methylation (Paranjape & Hall 2017). On the other hand, the main source of human exposure to MeHg is through the consumption of fish (Fuentes-Gandara et al. 2018), given that of the total Hg contained in the fish muscle of 75 to >90%, it is found as MeHg (Ruelas-Insunza et al. 2008, Hong et al. 2012, Ehnert-Russo & Gelsleichter 2020, Le Croizier et al. 2020). MeHg exposure has been shown to have neurotoxic, immunotoxic, or carcinogenic effects and reproductive and embryonic developmental disorders, primarily in the development of the nervous system (Hong et al. 2012, Paranjape & Hall 2017).

Tens of tons of heavy metals are generated in Mexico as waste from various activities and industries. For example, it produces about 1.8 million tons of mining products, being considered one of the main producers of this sector (Franco-Hernández et al. 2010, INECC 2017, SGM 2018). Likewise, thousands of tons of electronic waste are generated (OINCyTU 2018). Other important sources of heavy metals are domestic and industrial wastewater; only 50% of the wastewater generated in the country receives some level of treatment (CONAGUA 2017). This discharge results in the release of huge amounts of toxic metals throughout the Mexican territory.

In Mexico, researchers in recent decades have been monitoring the concentration of heavy metals in various environmental matrices (water, sediment, air, and biota) of aquatic ecosystems. They are generating valuable information that can serve as a basis for decision-making in environmental and public health matters to favor the protection and responsible management of the ecosystems. However, despite the great effort, there are still areas with little information about persistent pollutants in different environmental matrices, such as the central part of the Mexican Pacific coast. Therefore, this work aims to evaluate the possible risk of Hg, Pb, Cd, and Cr concentrations in sediments and Hg in fish from two Mexican coastal lagoons (Barra de Navidad Lagoon-BNL and Cuyutlán Lagoon-CL). These objectives were reached by comparing them against international environmental guidance values for the ecotoxicological risk of trace metals in sediments and maximum metal ingestion allowances for humans.

The BNL is located in the coastal area of the state of Jalisco in the municipality of Cihuatlán (19°11’N, 104°39’W), a municipality that has about 40 thousand inhabitants and whose economic activity is mainly oriented to tourism, agriculture, and coastal fishing (INEGI, 2017a). BNL has a surface area of 334 ha and freshwater inlets from two river sources, the Arroyo Seco River and the Marabasco River, and water exchanges with the sea through a mouth of 100 m wide (Aguilar-Betancourt et al. 2016). On the other hand, the CL is located in the municipality of Manzanillo in the state of Colima (19°03’N, 104°19’W), which has about 184,000 inhabitants, and whose economy is mainly oriented to industry (port, electrical, mining sector), tourism and coastal fishing (INEGI 2017b). This aquatic body, with an area of 38,884 ha, has a distinctive geographical feature: the separation into four reservoirs called “vasos”, delimited by natural and artificial barriers that regulate the exchange of water and the drag of sediments between one compartment and another (Torres & Quintanilla-Montoya 2014). This lagoon receives limited contributions of fresh-water from the Coahuayana River and the Armería River.

The concentrations of metals in sediments were compared against international reference values for adverse biological effects for aquatic biota. Threshold effects level (TEL), low range effect level (ERL), and probable effects level (PEL) guidelines were used, according to the Canadian Council of Minister of the Environment and the National Oceanic and Atmospheric Administration, USA (Table 1). Fish sampling was carried out in March 2018 by local fishermen's assistance, sampling for three days (one per week). The organisms were collected near the sampling points established for sediment collection by traditional fishing gear (cast fishing net and trammel). Once the specimens were collected, they were put on ice and transported to the laboratory, where biometric data (weight and total height) were measured and subsequently individually packed in airtight plastic bags and kept frozen at −20°C until further analysis.

Table 1 Environmental guidelines (µg g-1 dry weight) for metal concentrations in sediment for biological effects. As: arsenic, Cd: cadmium, Hg: mercury, Pb: lead, TEL: threshold effects level, ERL: low range effect level, PEL: probable effects level, CCCME (Canadian Council of Minister of the Environment), NNOAA (2008)

As Cd Hg Pb
TEL 7.24N 0.68N 0.13C 30.2C
ERL 8.20N 1.2N 0.15N 46.7N
PEL 41.20N 4.21N 0.71C 112C

The determination of heavy metals in sediment was performed by mass spectrometry with inductively coupled plasma (ICP-MS, Agilent 7900 ICP-MS). Before determining heavy metals, the sediment samples were dried at room temperature in the shade for seven days. Sediments were crushed/pulverized in an agate mortar and passed through a #20 (840 µm) sieve, the samples were homogenized, and subsequently, three sub-samples of 1 g were taken. The sub-samples were subjected to acid digestion with concentrated HNO3 (JT Beiker) on a hot plate (100°C) as described in Pérez-Rodríguez et al. (2017) with some modifications. Five grams of muscle were digested with HNO3 and H2SO4 to determine Hg in fish muscle, with their respective reagent blanks and standard solutions as control of quality and processed following the NMX-AA-051-SCFI-2016 standard, using an Agilent 240FS AA atomic absorption spectrophotometer coupled to a hydride generator. A reagent blank (2% HNO3) and a multi-elemental NIST standard were routinely measured after every 10 experimental samples to verify the reliability of the analysis. Similarly, the experimental samples, blanks, and reference materials (NIST-RM8704 and NIST-SRM1577 for sediment and fish, respectively) were added with 100 µg mL-1 of Agilent internal calibration standard of Li, Sc, Ge, Y, In, Tb, and Bi (p/n 5183-4681, Agilent, USES). The recoveries for certified reference materials were 95 ± 15% for As, Cd, Pb, and Hg in sediments and 100 ± 9.8% for Hg in tissue. The detection limits were as follow: As (0.1 µg g-1), Cd (0.005 µg g-1), Hg (0.05 µg g-1) and Pb (0.005 µg g-1), respectively.

The potential health risk from Hg ingestion associated with fish consumption was evaluated considering the non-carcinogenic risk ratio by calculating hazard quotient (HQ) as an indicator. The equation: HQ = E / RfD was used as reference dose for oral exposure (Newman & Unger 2002), where RfD is the reference dose (μg kg-1 kg-1 of body weight d-1), E is the level of exposure or consumption of the contaminant and is calculated using the equation E = C × I / W, where C: concentration of the contaminant (μg g-1 wet weight: ww), I: per capita ingestion rate (g d-1), and W: weight consumer average (kg), and RfD of 0.1 µg kg-1, ww was considered for MeHg (USEPA 2010), I of 36 g d-1 (CONAPESCA 2017), and W of 70 kg (Walpole et al. 2012). One-way analysis of variance (ANOVA) was performed to assess significant differences between the data, using the SPSS statistical package (Ver.16) with a P < 0.05. The biota-sediment accumulation factor (BSAF) can be calculated using the expression BSAF = Corg/ Csed (Thomann et al. 1995), where Corg is the metal concentration in the organism and Csed is the concentration of the metal in the sediment. Fish can be classified according to their BSAF value into: macro-concentrators (BSAF >2), micro-concentrator (1 < BSAF <2) and as non-concentrators (BSAF <1) (Ziyaadini et al. 2017).

In the case of Hg, no concentrations were found that exceeded the detection limit (DL <0.05 µg g-1). Although no sediment sample showed mercury above the detection limit, it is known that the concentration in sediments is not sufficient for the prediction of the bioaccumulation process of mercury in aquatic food chains (Lawrence & Mason 2001). Therefore, any presence of mercury below the present study's detection limit might be accumulating at lower levels of the food chain. This process should mainly include benthic invertebrates or animal diets associated with the estuarine cycle of organic matter (Lawrence & Mason 2001). This metal will eventually contribute to the presence of mercury detected in fish.

Cd concentrations (from 0.02 ± 0.01 to 0.42 ± 0.23 µg g-1) were found below the threshold effects level (TEL: 0.68 µg g-1) (Fig. 2). On the other hand, the concentrations of As (from 10.7 ± 1.3 to 25.4 ± 3.1 µg g-1) in both lagoons exceeded the TEL (7.24 µg g-1) and low range effect level (ERM: 8.20 µg g-1), likewise in the case of Pb the probable effects level (PEL: 112 µg g-1) was exceeded (from 42.7 ± 4.2 to 123.9 ± 14.7 µg g-1) (Fig. 2). In general, Barra de Navidad and Cuyutlán coastal lagoons showed similar conditions concerning the pollutants here analyzed. In both lagoons, differences were found between the sampling sites, mainly for Pb, registering the highest concentrations in the areas closest to the mouth of both coastal lagoons (Fig. 2).

Figure 1 Location of the sampling areas. a) Barra de Navidad Lagoon, b) Cuyutlán Lagoon. A, B, C, D and E are sampling points. 

Figure 2 Metal concentrations (mean ± standard deviation, μg g-1 dry weight) in sediment from Barra de Navidad Lagoon (Jalisco: A, B, and C) and Cuyutlán Lagoon (Colima: D, E, and F). As: arsenic (a), Pb: lead (b), Cd: cadmium (c), TEL: threshold effects level, ERL: low range effect level, PEL: probable effects level. a,b,c,dDifferent superscript letters denote significant differences (P < 0.05). 

Concerning total mercury (THg) concentration, 14 species of fish were analyzed. The highest concentration was found in Haemulopsis sp. and Lutjanus sp. with 0.23 and 0.1 µg g-1 ww and BSAF equal to 4.6 and 2.0. On the other hand, it is observed that in each one of the cases, the cogeneration of THg in fish muscle does not exceed the maximum permissible limits of 1 µg g-1 ww proposed by USA (USFDA 2017), the European Community (EU 2006), or Mexico (DOF, 2009) (Table 2). Regarding the non-carcinogenic risk ratio (HQ), the results show that for our study area, the national per capita consumption rate of fish showed that the HQ value was maintained in all cases <1, except in the case of Haemulopsis sp. with an HQ = 1.12 (Table 2). However, in the estimates set on fish consumption rate from some fishing communities in Mexico (400 g d-1), HQ values >3 were observed. Table 3 shows the HQ values associated with the national per capita fish consumption rate and the consumption rate associated with fishing communities, which showed similarities to other cases previously reported in other coastal areas of Mexico.

Table 2 Total mercury (THg) concentration (mean ± standard deviation, µg g-1 wet weight) and sediment-biota accumulation factor (BSAF) in fish muscle from the Barra de Navidad Lagoon and the Cuyutlán Lagoon. LD: detection limits: Hg (0.05 µg g-1). Maximum permissible limits of Hg in fish: USFDA (1 µg g-1 wet weight); European Community (1 µg g-1 wet weight); NOM-242-SSA1-2009 (1 µg g-1 wet weight). Sample size by species N = 6. *A single organism. 

Site Species Common name Size (cm) THg BSAF
Cuyutlán Lagoon Mugil sp. Lisa 25 ± 3 0.08 ± 0.04 1.6
Sciades guatemalensis Bagre 20 ± 4 0.06 ± 0.02 1.2
Polydactylus approximans Bonito 16 ± 1 <LD -
Centropomus sp. Constantino 25 ± 5 <LD -
Caranx caninus Jurel 15 ± 2 0.09 ± 0.04 1.8
Lutjanus sp. Pargo 16 ± 2 0.07 ± 0.05 1.4
Elops affinis Machete 25 ± 2 0.06 ± 0.03 1.2
Barra de Navidad Lagoon Chanos chanos Sábalo 30* 0.05 1
Mugil sp. Lisa 33 ± 9 0.06 ± 0.05 1.2
Acanthurus xanthopterus Navajero 30 ± 4 0.07 ± 0.11 1.4
Diapterus peruvianus Mojarra 17 ± 5 <LD -
Sciades guatemalensis Bagre 34 ± 6 0.06 ± 0.04 1.2
Haemulopsis sp. Ronco 23 ± 8 0.23 ± 0.16 4.6
Selene sp. Tostón 25 ± 3 <LD -
Achirus mazatlanus Lenguado 15 ± 2 0.09 ± 0.06 1
Caranx caninus Jurel 18 ± 1 0.08 ± 0.05 1.6
Peprilus snyderi Gavilán 16 ± 1 0.05 ± 0.03 1
Lutjanus sp. Pargo 21 ± 3 0.10 ± 0.09 2

Table 3 Methyl mercury (MeHg) concentration μg g−1 wet weight (considered as 95% of total mercury concentration), non-carcinogenic risk ratio (hazard quotient, HQ) associated with the most consumed fish in fishing communities in Mexico. RfD = 0.1 μg kg−1 d−1; average adult weight in México 70 kg. HQN: calculated based on the national average fish intake of 36 g d−1. HQP: calculated based on fish consumption reported in some fishing communities in México of 400 g d−1

Species MeHg HQN HQP Location Reference
Mugil sp. 0.06 0.34 3.80 Cuyutlán Lagoon, Colima This study
0.05 0.25 2.70 Barra de Navidad Lagoon, Jalisco This study
<0.01 <0.1 0.3.3 Barra de Navidad Lagoon, Jalisco Aguilar-Betancourt et al. (2016)
0.02 0.10 1.09 Alvarado Lagoon, Veracruz Elliott et al. (2015)
0.08 0.44 4.89 Kino Bay, Sonora García-Hemández et al. (2018)
0.03 0.10 1.34 Estero de Urias, Sinaloa Frias-Espericueta et al. (2016)
0.04 0.20 2.28 Coastal lagoons of the Mexican northeast, Sinaloa Delgado-Alvarez el al. (2017)
0.04 0.20 2.71 Alvarado Lagoon, Veracruz Guentzel el al. (2007)
0.36 1.86 20.63 Altata-Ensenada del Pabellón, Sinaloa Ruelas-Inzunza et al. (2011)
Elops affinis 0.06 0.24 2.44 Cuyutlán Lagoon, Colima This study
0.37 1.90 21.27 Santamar-La Reforma Lagoon, Sinaloa Ruelas-Inzunza et al. (2011)
0.15 0.78 8.69 Topolobampo Bay, Sonora Ruelas-Inzunza et al. (2011)
0.38 1.63 16.29 Topolobampo Bay, Sinaloa Ruelas-Inzunza et al. (2011)
0.17 0.87 90.66 Coastal lagoons of the Mexican northeast, Sinaloa Ruelas-Inzunza et al. (2008)
Lutjanus sp. 0.08 0.39 40.34 Barra de Navidad Lagoon, Jalisco This study
0.06 0.29 30.26 Cuyutlán Lagoon, Colima This study
0.25 1.27 14.11 Altata-Ensenada del Pabellón, Sinaloa Ruelas-Inzunza et al. (2011)
0.17 0.87 90.66 Altata-Ensenada del Pabellón, Sinaloa Ruelas-Inzunza & Páez-Ozuna (2005)
0.10 0.52 50.75 Coastal lagoons of the Mexican northeast, Sinaloa Ruelas-Inzunza & Páez-Ozuna (2005)
Centropomus sp. 0.03 0.15 10.63 Cuyutlán Lagoon, Colima This study
0.29 1.47 16.29 Tecuala, Nayarit Elliott etal. (2015)
0.17 0.88 90.77 Alvarado Lagoon, Veracruz Elliott et al. (2015)
0.42 2.15 23.89 Topolobampo Bay, Sonora Ruelas-Inzunza et al. (2011)
Caranx caninus3 0.08 0.39 40.34 Barra de Navidad Lagoon, Jalisco This study
0.09 0.44 40.89 Cuyutlán Lagoon, Colima This study
0.95 4.89 54.29 Topolobampo Bay, Sonora Ruelas-Inzunza et al. (2011)
0.18 0.93 10.31 Estero de Urias, Sinaloa Martinez-Salcido et al. (2018)
0.18 0.94 10.50 Estero Huizache, Sinaloa Martinez-Salcido et al. (2018)
Acanthurus xcmthopterus 0.07 0.34 30.80 Barra de Navidad Lagoon, Jalisco This study
Sciades guatemalensis 0.06 0.29 30.26 Barra de Navidad Lagoon, Jalisco This study
0.06 0.29 3.26 Cuyutlán Lagoon, Colima This study
0.51 2.64 29.31 Barra de Navidad Lagoon, Jalisco Aguilar-Betancourt et al. (2016)
Haemulopsis sp. 0.21 0.14 1.12 0.73 12.48 8.14 Barra de Navidad Lagoon, Jalisco Guerrero coast, Guerrero This study Spanopoulos-Zarco et al. (2014)

The differences found among the sampling sites (mainly in Pb, which recorded the highest concentrations in the area closest to the mouth of both lagoons, Figs. 1-2) are probably due to its proximity to human settlements. Multiple fishing boats with outboard motors have been related as important sources of Pb in coastal sediments (Soto-Jiménez et al. 2008). In the case of the BNL, the result is also consistent with Marmolejo-Rodríguez et al. (2007), who found maximum values of 18 µg g-1 dry weight (dw) of Pb (Fig. 2) related to a terrigenous origin (labile fraction <1%). It could indicate a possible recent anthropic origin of the high concentrations of Pb (>100 µg g-1 dw) as here founded. Rapid enrichment with Pb has also been observed in other coastal ecosystems of Mexico, mainly in port areas. For example, González-Lozano et al. (2006), reported concentrations of Pb that ranged between 14-43 µg g-1 dw in 1998 and 43-123 µg g-1 dw in 2002 in Salina Cruz, Oaxaca, Mexico. These can be related to the sedimentation processes of suspended particulate materials. For example, Soto-Jiménez et al. (2008) indicate that suspended particulate matter can contribute to >98% of the Pb present, suggesting that this factor could also be involved in the presence of lead in BNL. Other significant Pb sources could be related to air transportation, such as the atmospheric deposition of vehicular emissions and the thermoelectric plant emissions located next to the CL in the municipality of Manzanillo as urban wastewater discharges. These emissions have been increased in recent years in this region, which could explain the high concentrations of Pb found in both lagoons. On the other hand, only previously reported Cd values were found for the BNL. Marmolejo-Rodríguez et al. (2007) reported values of 0.05-0.34 µg g-1 dw in 2005, which are similar to those found in the present study (Fig. 2). There are no previous reports of As and Hg concentrations in sediment from the BNL and the CL. Similarly, it is observed that As and Pb concentrations found, both for the BNL and the CL, significantly exceed the TEL and the ERL levels (Fig. 2). They represent a potential risk for organisms associated with these ecosystems and the local population that consumes them (Enuneku et al. 2018, Ali et al. 2019).

It is unclear why the mean As concentration found in site C (the furthest from the BNL mouth) was higher than the other sites near the urbanized areas (Fig. 2). Further studies are needed to clarify the origin and accumulation of arsenic in that geographical zone, especially considering that this metalloid has already been reported in local fish (Aguilar-Bentacourt et al. 2016). The exposure of aquatic organisms to toxic environmental pollutants, such as STPBs, even in low concentrations, represents a potential risk of toxicity to be considered. It can affect the wildlife ecological balance of affected ecosystems and directly people's health belonging to communities heavily dependent on these resources and the population in general. Very little is known about the pathological outcome of chronic exposure to environmental pollutants in trace amounts in the region. The presence and bioaccumulation of some heavy metals (mainly Hg in its organic form MeHg) in the trophic networks of aquatic ecosystems may constitute a risk to human health (Mendoza-Carranza et al. 2016).

On the other hand, the bioaccumulation processes are influenced by various processes, such as the different routes of exposure and the ecological niche of each monitored species. In general, monitoring the concentration of metals in aquatic organisms can reflect the contamination of these ecosystems. Furthermore, it can help understand the potential risk they present for consumers (Wang et al. 2013). The BSAF describes the bioaccumulation of compounds, such as heavy metals associated with sediments in the tissues of organisms (Burkhard 2009). In other words, it reflects the efficiency of the accumulation of heavy metals in an organism, allowing assessing the potential toxicity of contaminated sediments. In the present study, most organisms analyzed can be considered as micro-concentrators (Table 2). However, this may be because the coastal lagoons act as a hatchery for large predators (Aguilar-Betancourt et al. 2016). Only juvenile organisms of C. caninus could be collected (Lutjanus sp. and A. mazatlanus), explaining the relatively low BSAF values. At the same time, they are considered top predators in their respective ecological niches in their adult stages, so they are one of the final receptors for the Hg available in the trophic web. It is essential to highlight that the highest BSAF observed was in Haemulopsis sp. (Table 2), a commercial species from BNL. Although the mean THg concentration was below the maximum permissible limit of 1 µg g-1 ww, it is crucial to analyze the effects at a subcellular level due to this exposure, inducing antioxidant response changes at the molecular level.

On the other hand, the potential risk to human health due to exposure to Hg associated with the consumption of contaminated fish is a matter of global concern. Various diseases have been related to exposure to low concentrations of this pollutant, such as cancer, neuro-toxicity, cardiovascular diseases, endocrine disruption, and neurological defects in the developing fetus when exposed to MeHg (Dórea 2008, García-Hernández et al. 2018). The HQ is the relationship between the potential exposure to a substance and the level at which no adverse effects are expected. An HQ less than or equal to 1 indicates that adverse effects are not likely to occur. Therefore, it can be considered to have a statistically significant probability of no risk. However, HQs >1 are not statistical probabilities of damage occurring but a simple quantitative statement of whether an exposure concentration exceeds the RfD. In the present work, the concentration of Hg was transformed to MeHg form by a conversion factor of 0.95, considering that more than 90% of THg in fish muscle is present as MeHg (García-Hernández et al. 2018). Likewise, the RfD of 0.1 μg kg-1 d-1 proposed by the EPA was used (USEPA 2010). Consumption of fish of 36 g d-1 was considered, representing the national average (CONAPESCA 2017) and a consumption of 300 g d-1 associated with fishing communities (Zamora-Arellano et al. 2017, Astorga-Rodríguez et al. 2018, García-Hernández et al. 2018). Table 3 shows the different HQs for MeHg associated with the consumption of collected fish.

Based on the national average fish consumption rate, about 13.2 kg y-1 or 36 g d-1 (CONAPESCA 2017), it is possible to consider that the studied area has a relatively low-risk potential with an HQ ?1 in all cases, compared to other national coastal areas showing HQs ?2. However, this situation represents a potential risk for the general population of those regions (Table 2). This risk remains considerably low, compared to vulnerable communities, such as coastal fishing communities, which have a high rate of fish consumption associated with 400 g d-1 (Zamora-Arellano et al. 2017, Astorga-Rodríguez et al. 2018), which puts them in a situation of evident vulnerability especially to children and women in reproductive age. Generally, a considerable increase in HQ's value is associated with fishing communities, based on their high consumption of fishery products, representing some risk for these communities.

In general, the data obtained indicate that both BNL and CL show relatively low levels of metal contamination and potential health risk compared to other Mexican areas. However, the presence of toxic metals like As, Cd, Pb, and Hg are undeniable. As and Pb from BNL and CL significantly exceed the TEL and the ERL levels, representing possible biological effects and risk for local biota. Ronco fish (Haemolupsis sp.) from BNL showed the species with the highest BSAF with 4.6 for THg, suggesting the need to analyze this species for antioxidant response at the subcellular level. In addition, HQ was determined. As (10.7 ±1.3 - 25.4 ± 3.1 µg g-1) and Pb (42.7 ± 4.2 - 123.9 ± 14.7 µg g-1) concentrations exceeded the permissible levels, otherwise for Hg and Cd were below the limits. However, a non-complex risk analysis, such as the calculation of HQs, can give a consistent perspective to dimensional the problem, at least in vulnerable populations or communities.

On the other hand, constant monitoring of pollutant levels present in the different environmental matrices is a fundamental tool in responsibly managing aquatic resources, mainly in Mexico, where aquatic ecosys-tems play an important role both ecologically and for socio-economic development.

REFERENCES

Aguilar-Betancourt, C.M., González-Sansón, G., Kidd, K.A., Munkittrick, K.R., Curry, R.A., Kosonoy-Aceves, D., et al. 2016. Fishes as indicators of untreated sewage contamination in a Mexican coastal lagoon. Marine Pollution Bulletin, 113: 100-109. doi: 10.1016/j.marpolbul.2016.08.073 [ Links ]

Ali, H., Khan, E. & Ilahi, I. 2019. Environmental chemistry and ecotoxicology of hazardous heavy metals: environmental persistence, toxicity, and bioaccumulation. Journal of Chemistry, 2019: 6730305. doi: 10.1155/2019/6730305 [ Links ]

Astorga-Rodríguez, J.E., Martínez-Rodríguez, I.E., García-de la Parra, L.M., Betancourt-Lozano, M., Vanegas-Pérez, R.C., Ponce de León-Hill, C.A. & Ruelas-Inzunza, J. 2018. Lead and cadmium levels in mussels and fishes from three coastal ecosystems of NW Mexico and its potential risk due to fish and seafood consumption. Toxicology and Environmental Health Sciences, 10: 203-211. doi: 10.1007/s13530-018-0365-1 [ Links ]

Burkhard, L. 2009. Estimation of biota sediment accumulation factor (BSAF) from paired observations of chemical concentrations in biota and sediment. US Environmental Protection Agency, Ecological Risk Assessment Support Center EPA/ 600/R-06/047, Cincinnati, 30 pp. [https://cfpub.epa.gov/ncea/risk/era/recordisplay.cfm?deid=205446]. Reviewed: March20, 2020. [ Links ]

Canadian Council of Ministers of the Environment (CCME). 2002. Canadian sediment quality guidelines for the protection of aquatic life: summary tables, updated. In: Canadian environmental quality guidelines, 1999. Canadian Council of Ministers of the Environment, Winnipeg. [ Links ]

Comisión Nacional del Agua (CONAGUA). 2017. Estadísticas del agua en México. Secretaría de Medio Ambiente y Recursos Naturales, Comisión Nacional del Agua, Ciudad de México, pp. 294. [http://sina.conagua.gob.mx/publicaciones/EAM_2017.pdf]. Reviewed: March 20, 2020. [ Links ]

Comisión Nacional de Acuacultura y Pesca (CONAPESCA). 2017. Anuario estadístico de acuacultura y pesca. Comisión Nacional de Acuacultura y Pesca, Mazatlán, 293 pp. [https://www.conapesca.gob.mx/work/sites/cona/dgppe/2017/ANUARIO_ESTADISTICO_2017.pdf]. Reviewed: March 20, 2020. [ Links ]

Delgado-Alvarez, C.G., Frías-Espericueta, M.G., RuelasInzunza, J., Becerra-Álvarez, M.J., Osuna-Martínez, C.C., Aguilar-Juárez, M., Osuna-López, J.I., et al. 2017. Total mercury in muscles and liver of Mugil spp. from three coastal lagoons of NW Mexico: concentrations and risk assessment. Environmental Monitoring and Assessment, 189: 312. doi: 10.1007/s10661-017-6020-5 [ Links ]

Diario Oficial de la Federación (DOF). 2009. Norma Oficial Mexicana NOM-242-SSA1-2009. Productos y servicios. Productos de la pesca frescos, refrigerados, congelados y procesados. Especificaciones sanitarias y métodos de prueba. Secretaría de Gobernación, Ciudad de México. [ Links ]

Dórea, J.G. 2008. Persistent, bioaccumulative and toxic substances in fish: human health considerations. Science of the Total Environment, 400: 93-114. doi: 10.1016/j.scitotenv.2008.06.017 [ Links ]

Ehnert-Russo, S.L. & Gelsleichter, J. 2020. Mercury accumulation and effects in the brain of the Atlantic sharpnose shark (Rhizoprionodon terraenovae). Archives of Environmental Contamination and Toxicology, 78: 267-283. doi: 10.1007/s00244-019-00691-0 [ Links ]

Elliott, J.E., Kirk, D.A., Elliott, K.H., Dorzinsky, J., Lee, S., Ruelas, E., et al. 2015. Mercury in forage fish from Mexico and Central America: implications for fish-eating birds. Archives of Environmental Contamination and Toxicology, 69: 375-389. doi: 10.1007/s00244-015-0188-x [ Links ]

Enuneku, A., Omoruyi, O., Tongo, I., Ogbomida, E., Ogbeide, O. & Ezemonye, L. 2018. Evaluating the potential health risks of heavy metal pollution in sediment and selected benthic fauna of Benin River, Southern Nigeria. Applied Water Science, 8: 224. doi: 10.1007/s13201-018-0873-9 [ Links ]

European Union Commission (EU). 2006. Commission Regulation (EC) No. 1881/2006 of December 19, 2006, setting maximum levels of certain contaminants in foodstuffs. Official Journal of the European Communities, 20/12/2006 L 364/5. [ Links ]

Franco-Hernández, M.O., Vásquez-Murrieta, M.S., Patiño-Siciliano, A. & Dendooven, L. 2010. Heavy metals concentration in plants growing on mine tailings in Central Mexico. Bioresource Technology, 101: 3864-3869. doi: 10.1016/j.biortech.2010.01.013 [ Links ]

Frías-Espericueta, M.G., Vargas-Jiménez, A., RuelasInzunza, J., Osuna-López, J.I., Aguilar-Juárez, M., Bautista-Covarrubias, J.C. & Voltolina, D. 2016. Total mercury in Mugil spp. and Eugerres axillaris of a subtropical lagoon of NW Mexico. Bulletin of Environmental Contamination and Toxicology, 97: 211-215. doi: 10.1007/s00128-016-1811-x [ Links ]

Fuentes-Gandara, F., Herrera-Herrera, C., PinedoHernández, J., Marrugo-Negrete, J. & Diez, S. 2018. Assessment of human health risk associated with methylmercury in the imported fish marketed in the Caribbean. Environmental Research, 165: 324-329. doi: 10.1016/j.envres.2018.05.001 [ Links ]

García-Hernández, J., Ortega-Vélez, M.I., ContrerasPaniagua, A.D., Aguilera-Márquez, D., Leyva-García, G. & Torre, J. 2018. Mercury concentrations in seafood and the associated risk in women with high fish consumption from coastal villages of Sonora, Mexico. Food and Chemical Toxicology, 120: 367-377. doi: 10.1016/j.fct.2018.07.029 [ Links ]

González-Lozano, M.C., Méndez-Rodríguez, L.C., López-Veneroni, D.G. & Vázquez-Botello, A. 2006. Evaluación de la contaminación en sedimentos del área portuaria y zona costera de Salina Cruz, Oaxaca, México. Interciencia, 31: 647-656. [ Links ]

Guentzel, J.L., Portilla, E., Keith, K.M. & Keith, E.O. 2007. Mercury transport and bioaccumulation in riverbank communities of the Alvarado Lagoon System, Veracruz State, Mexico. Science of the Total Environment, 388: 316-324. doi: 10.1016/j.scitotenv.2007.07.060 [ Links ]

Hong, Y.S., Hunter, S., Clayton, L.A., Rifkin, E. & Bouwer, E.J. 2012. Assessment of mercury and selenium concentrations in captive bottlenose dolphin's (Tursiops truncatus) diet fish, blood, and tissue. Science of the Total Environment, 414: 220-226. doi: 10.1016/j.scitotenv.2011.11.021 [ Links ]

Instituto Nacional de Ecología y Cambio Climático (INECC). 2017. Contaminación y salud. Integración del inventario nacional de emisiones y liberaciones de mercurio, 2015. Coordinación General de Contaminación y Salud Ambiental del INECC. SEMARNAT, Ciudad de México. [ Links ]

Instituto Nacional de Estadística y Geografía (INEGI). 2017a. Anuario estadístico y geográfico de Jalisco 2017. México, 854 pp. [https://transparencia.info.jalisco.gob.mx/sites/default/files/Anuario%20Estad%C3%Adstico%20y%20Geogr%C3%A1fico%20de%20Jalisco%202017.pdf]. Reviewed: May 15, 2020. [ Links ]

Instituto Nacional de Estadística y Geografía (INEGI). 2017b. Anuario estadístico y geográfico de Colima 2017. México, 393 pp. [https://www.datatur.sectur.gob.mx/ItxEF_Docs/COL_ANUARIO_PDF.pdf]. Reviewed: March 20, 2020. [ Links ]

Lawrence, A.L. & Mason, R.P. 2001. Factors controlling the bioaccumulation of mercury and methylmercury by the estuarine amphipod Leptocheirus plumulosus. Environmental Pollution, 111: 217-231. doi: 10.1016/S0269-7491(00)00072-5 [ Links ]

Le Croizier, G., Lorrain, A., Schaal, G., Ketchum, J., Hoyos-Padilla, M., Besnard, L., et al. 2020. Trophic resources and mercury exposure of two silvertip shark populations in the Northeast Pacific Ocean. Chemosphere, 253: 126645. doi: 10.1016/j.chemosphere.2020.126645 [ Links ]

Manavi, P.N. & Mazumder, A. 2018. Potential risk of mercury to human health in three species of fish from the southern Caspian Sea. Marine Pollution Bulletin, 130: 1-5. doi: 10.1016/j.marpolbul. 2018.03.004 [ Links ]

Marmolejo-Rodríguez, J.M., Prego, R., Meyer-Willerer, A., Shumilin, E. & Cobelo-García, A. 2007. Total and labile metals in surface sediments of the tropical river-estuary system of Marabasco (Pacific coast of Mexico): influence of an iron mine. Marine Pollution Bulletin, 55: 459-468. doi: 10.1016/j.marpolbul.2007.09.008 [ Links ]

Martínez-Salcido, A.I., Ruelas-Inzunza, J., Gil-Manrique, B., Nateras-Ramírez, O. & Amezcua, F. 2018. Mercury levels in fish for human consumption from the southeast Gulf of California: tissue distribution and health risk assessment. Archives of Environmental Contamination and Toxicology, 74: 273-283. doi: 10.1007/s00244-017-0495-5 [ Links ]

McCulligh, C. 2014. Contaminar para competir. Contaminación industrial del río Santiago en Jalisco. Carta Económica Regional, 26: 114-137. [ Links ]

Mendoza-Carranza, M., Sepúlveda-Lozada, A., Dias-Ferreira, C. & Geissen, V. 2016. Distribution and bioconcentration of heavy metals in a tropical aquatic food web: a case study of a tropical estuarine lagoon in SE Mexico. Environmental Pollution, 210: 155-165. doi: 10.1016/j.envpol.2015.12.014 [ Links ]

Newman, M.C. & Unger, M.A. 2002. Fundamentals of ecotoxicology. Lewis Publishers, Boca Raton. [ Links ]

National Oceanic and Atmospheric Administration (NOAA). 2008. Screening quick reference tables. NOAA, Maryland. [https://repository.library.noaa.gov/view/noaa/9327]. Reviewed: March 20, 2020. [ Links ]

Norma Oficial Mexicana NMX-AA-051-SCFI-2016.2016. Análisis de agua. Medición de metales por absorción atómica en aguas naturales, potables, residuales y residuales tratadas método de prueba. Secretaría de Economía. Ciudad de México, 39 pp. [http://www.economia-nmx.gob.mx/normas/nmx/2010/nmx-aa-051-scfi-2016.pdf]. Reviewed: May 15, 2020. [ Links ]

Oficina de Información Científica y Tecnológica para el Congreso de la Unión (OINCyTU). 2018. Residuos electrónicos. FCCyT, Ciudad de México, 6 pp. [ Links ]

Paranjape, A.R. & Hall, B.D. 2017. Recent advances in the study of mercury methylation in aquatic systems. FACETS, 2: 85-119. doi: 10.1139/facets-2016-0027 [ Links ]

Pérez-Rodríguez, R.Y., Castro-Larragoitia, J., Alfaro-De La Torre, M.C. & Díaz-Barriga, F. 2017. Optimization of an acidic digestion method for the determination of total Pb concentration and its isotope ratios in human blood using ICP-QMS. Journal of Environmental Science and Health - Part A: Toxic/Hazardous Substances & Environmental Engineering, 52: 350-358. doi: 10.1080/10934529.2016.1260889 [ Links ]

Ramírez-Ayala, E., Arguello-Pérez, M.A., IlizaliturriHernández, C.A., Tintos-Gómez, A., Mejía-Saavedra, J. & Borja-Gómez, I. 2018. A brief review of the use of biomarkers in Mexico's aquatic ecosystems pollution assessment: 2001-2017. Latin American Journal of Aquatic Research, 46: 860-879. doi: 10.3856/vol46-issue5-fulltext-1 [ Links ]

RAMSAR Convention. 2020. The list of wetlands of international importance. The Secretariat of the Convention on Wetlands (Ramsar, Iran, 1971), Gland, 55 pp. [https://www.ramsar.org/sites/default/files/docu-ments/library/sitelist.pdf]. Reviewed: April 25, 2020. [ Links ]

Reyes, Y.C., Vergara, I., Torres, O.E., Díaz, M. & González, E. 2016. Heavy metals contamination: implications for health and food safety. Revista Ingeniería, Investigación y Desarrollo, 16: 66-77. [ Links ]

Ruelas-Inzunza, J. & Páez-Osuna, F. 2005. Mercury in fish and shark tissues from two coastal lagoons in the Gulf of California, Mexico. Bulletin of Environmental Contamination and Toxicology, 74: 294-300. doi: 10.1007/s00128-004-0583-x [ Links ]

Ruelas-Inzunza, J., Meza-López, G. & Páez-Osuna, F. 2008. Mercury in fish that are of dietary importance from the coasts of Sinaloa (SE Gulf of California). Journal of Food Composition and Analysis, 21: 211-218. doi: 10.1016/j.jfca.2007.11.004 [ Links ]

Ruelas-Inzunza, J., Páez-Osuna, F., Ruiz-Fernández, A.C. & Zamora-Arellano, N. 2011. Health risk associated to dietary intake of mercury in selected coastal areas of Mexico. Bulletin of Environmental Contamination and Toxicology, 86: 180-188. doi: 10.1007/s00128-011-0189-z [ Links ]

Servicio Geológico Mexicano (SGM). 2018. Anuario estadístico de la minería mexicana. Secretaría de Minería, Ciudad de México. [ Links ]

Soto-Jiménez, M.F., Páez-Osuna. F., Scelfo, G., Hibdon, S., Franks, R., Aggarawl, J. & Russell, A. 2008. Lead pollution in subtropical ecosystems on the SE Gulf of California Coast: a study of concentrations and isotopic composition. Marine Environmental Research, 66: 451-458. doi: 10.1016/j.marenvres.2008.07.009 [ Links ]

Spanopoulos-Zarco, P., Ruelas-Inzunza, J., Meza-Montenegro, M., Osuna-Sánchez, K. & AmezcuaMartínez, F. 2014. Health risk assessment from mercury levels in bycatch fish species from the coasts of Guerrero, Mexico (Eastern Pacific). Bulletin of Environmental Contamination and Toxicology, 93: 334-338. doi: 10.1007/s00128-014-1311-9 [ Links ]

Thomann, R.V., Mahony, J.D. & Mueller, R. 1995. Steady-state model of biota sediment accumulation factor for metals in two marine bivalves. Environmental Toxicology and Chemistry: An International Journal, 14: 1989-1998. [ Links ]

Torres, J. & Quintanilla-Montoya, A.L. 2014. Alteraciones antrópicas: historia de la Laguna de Cuyutlán, Colima. Investigación Ambiental, 6: 29-42. [ Links ]

United Nations (UN). 2019. World population prospects 2019. Volume II: Demographic profiles. UN, New York. [ Links ]

US Environmental Protection Agency (USEPA). 2010. Guidance for implementing the January 2001 methylmercury water quality criterion. EPA 823-R-10-001. US Environmental Protection Agency, Office of Water, Washington, DC. [ Links ]

US Food and Drug Administration (USFDA). 2017. [https://www.fda.gov/ICECI/ComplianceManuals/Com-pliancePolicyGuidanceManual/ucm074510.htm]. Reviewed: October 10, 2020. [ Links ]

Walpole, S.C., Prieto-Merino, D., Edwards, P., Cleland, J., Stevens, G. & Roberts, I. 2012. The weight of nations: an estimation of adult human biomass. BMC Public Health, 12: 439. doi: 10.1186/1471-2458-12-439 [ Links ]

Wang, S.L., Xu, X.R., Sun, Y.X., Liu, J.L. & Li, H.B. 2013. Heavy metal pollution in coastal areas of South China: a review. Marine Pollution Bulletin, 76: 7-15. doi: 10.1016/j.marpolbul.2013.08.025 [ Links ]

Zamora-Arellano, N.Y., Ruelas-Inzunza, J., GarcíaHernández, J., Ilizaliturri-Hernández, C.A. & Betancourt-Lozano, M. 2017. Linking fish consumption patterns and health risk assessment of mercury exposure in a coastal community of NW Mexico. Human and Ecological Risk Assessment: An International Journal, 23: 1505-1521. doi: 10.1080/10807039.2017.1329622 [ Links ]

Ziyaadini, M., Yousefiyanpour, Z., Ghasemzadeh, J. & Zahedi, M.M. 2017. Biota-sediment accumulation factor and concentration of heavy metals (Hg, Cd, As, Ni, Pb, and Cu) in sediments and tissues of Chiton lamyi (Mollusca: Polyplacophora: Chitonidae) in Chabahar Bay, Iran. Iranian Journal of Fisheries Sciences, 16: 1123-1134. [ Links ]

Received: August 11, 2020; Accepted: July 21, 2021

Corresponding author: Adrián Tintos-Gómez (adrian-tintos@utem.edu.mx)

Corresponding editor: Marcel Ramos

Creative Commons License This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.