Open AccessArticle

Comprehensive Assessment of the Relationship between Metal Contamination Distribution and Human Health Risk: Case Study of Groundwater in Marituba Landfill, Pará, Brazil

Roberta C. de O. Soares

Ricardo Jorge A. de Deus

Monia M. C. Silva

³,

Kleber Raimundo F. Faial

³,

Adaelson C. Medeiros

and

Rosivaldo de A. Mendes

^1,3,*

Postgraduate Program in Epidemiology and Health Surveillance, Evandro Chagas Institute, Ananindeua 67030-000, PA, Brazil

Faculty of Biotechnology, Federal University of Pará, Belém 66075-110, PA, Brazil

Environment Section, Evandro Chagas Institute, Ananindeua 67030-000, PA, Brazil

Author to whom correspondence should be addressed.

Water 2024, 16(15), 2146; https://doi.org/10.3390/w16152146

Submission received: 29 May 2024 / Revised: 5 July 2024 / Accepted: 8 July 2024 / Published: 29 July 2024

(This article belongs to the Special Issue Groundwater Quality and Human Health Risk)

Download

Browse Figures

Versions Notes

Abstract

Effective management of urban solid waste in the Metropolitan Region of Belém, State of Pará, Brazil is essential for conserving ecosystems and public health in eight cities, emphasizing the municipality of Marituba. Considering the vulnerability of underground water resources in Marituba to pollution due to the possible impact of leachate percolation from the landfill, this study evaluates the quality of groundwater captured in tubular wells from different adjacent locations potentially used for human consumption. For this purpose, the systematic methodologies of the groundwater quality index and human health risk assessment analysis: non-carcinogenic and carcinogenic risk to human health were used based on chronic daily intake of heavy metals by consumption and dermal adsorption of groundwater, measured through risk quotients, risk index, and incremental lifetime cancer risk. To evaluate the interrelationships of pollutants, analysis of variance, hierarchical cluster analysis, and principal component analysis were used based on the spatio-temporal quantification of pH, temperature, electrical conductivity, As, Al, Ba, Co, Cd, Cu, Cr, Fe, Hg, Ni, Pb, Sb, Se, U, and Zn. Residents of the study area are not at potential risk, as the results demonstrate that groundwater is within the potability standards of Brazilian legislation, except for aluminum concentrations, which ranged from 53.12 to 378.01 μg L⁻¹ and 3.82 to 339.5 μg L⁻¹ in the dry and rainy seasons, respectively, exceeding the established limit of 200.0 μg L⁻¹. The quality index for groundwater and the heavy metal pollution index demonstrated that groundwater has good drinking quality with low metal contamination. The risk was considered low at all sampling sites in the non-carcinogenic risk assessment. Principal component analysis indicated that the sources of metal pollution are natural origins and anthropogeny. In this sense, they become worried because aluminum is a recognized neurotoxicant that can interfere with the central nervous system’s critical physiological and biochemical processes. Furthermore, despite complying with potability standards, trace concentrations of highly toxic metals such as As, Pb, Cd, and Ni may indicate initial contamination by landfill leachate.

Keywords:

landfill; heavy metals; water quality; Marituba; health risk index

1. Introduction

Heavy metals in water are present due to natural processes, but anthropogenic activities increase concentration levels. Pollution of soil and aquatic systems by heavy metals above acceptable levels affects the quality of the environment and constitutes an imminent risk of poisoning for humans [1]. Heavy metals exist naturally in the ecosystem, but their presence in groundwater is undesirable because many have toxic effects, even in low concentrations.

Groundwater contamination can be caused by industrial and domestic sewage [2] and landfill contamination. Trace metal contamination of surface and groundwater damages water quality, human health, and aquatic ecosystem [3]. The primary anthropogenic sources of residual metals are the combustion of fossil fuels, leachate from landfills, mining effluents, industrial effluents deposited in the environment, automotive service centers, surface runoff, and industrial chemicals. They may be responsible for the high metal concentrations in the environment [4,5].

The impact of landfills has been considered an essential source of contamination of soil, groundwater, and surface water due to the infiltration of leachate favored by hydrogeological factors such as rain, mineral weathering, topography of the dumping area, and biological processes [6]. Leachate pollutants are classified into four categories: (1) dissolved organic matter; (2) xenobiotic organic compounds; (3) inorganic macrocomponents, such as NH⁴⁺, Ca²⁺, Na²⁺, and Cl⁻ (4); and heavy metals, including mainly Cd, Zn, and Ni [7,8]. However, among these categories, the evaluation of heavy metals becomes a high priority, as low pH values in the leachate in the acid degradation phase generate high production of volatile fatty acids in the landfill mass [8,9]. This contributes to greater solubilization of metal ions, consequently increasing the contamination of surface and underground waters due to the dissipation of leachate through the soil [9,10,11]. Although some heavy metals are vital for human health [12], abundant intake of these metals and other toxic elements can create prejudicial health effects, such as cancer, hypertension, lung disease, gastrointestinal bleeding, kidney disease, neurological and reproductive effects, and carcinogenic and potentially genotoxic effects [13]. The risk classification of the most common heavy metals in leachate is in the following order based on their toxicity: Cd > Pb > Ni > Cr > Zn > Cu. The leaching of toxic species from waste depends on the processes that fix the pollutants in the soil and transport contaminants to groundwater [14]. Systematic health risk assessment methodologies and the groundwater quality index become essential tools to evaluate prejudicial health effects from exposure to water contaminated by metals and other contaminants [3,15] since accessibility to high-quality drinking water is necessary for environmental and human well-being [7] did not find potential health risks from metals in groundwater from a river in China exposed to industrial activities. In another study [16], groundwater consumption showed the possibility of non-carcinogenic and carcinogenic risks.

The vulnerability of groundwater quality around landfills is generally understood by assessing the impact of leachate pollution by comparing or classifying municipal landfills [17]; based on pollution potential, temporal and seasonal variation, the quality of leachate due to the level of irrigation, the leachate treatment system, the interrelationship between water quality parameters, and sources of pollution.

In this context, the Urban Waste Processing and Treatment Center (CPTR) was installed in the municipality of Marituba, Pará, Brazil—which is a private enterprise essentially consisting of a sanitary landfill, sorting unit, composting shed, and treatment of effluents by reverse osmosis in an area of 1,110,000 m²—to receive and provide final disposal for approximately 40.5 thousand tons/month of Class II urban solid waste from the cities of Belém, Ananindeua, and Marituba (equivalent to 85% of the metropolitan region of Belém, Pará), by Brazilian legislation NBR 10004/2004 [18,19]; According to the Public Ministry of the State of Pará, several negative physical–chemical–biological impacts on the environment and public health were generated in the municipality of Marituba by the implementation of the sanitary landfill due to part of the leachate generated at the landfill being discarded directly into nature. This is associated with the demographic, hydrographic, and climatic conditions of the region in addition to its proximity to the urban area. The municipality of Marituba contains 66,555 households with a water supply; approximately 77% of families are supplied by groundwater and can be impacted by landfill activity [18,19]. Therefore, analyzing the primary sources of groundwater pollution in the Marituba area is essential to establishing relationships between shallow groundwater quality and its potential polluting sources. This relevance is even more significant because it is a densely populated urban area with necessary socioeconomic conditions and sanitation deficiencies. Integrating this subject with hydrochemical aspects can significantly assist in defining the existing water potential in the area and its conditions of occurrence and rational exploitation.

This study contributes to the knowledge of pollution that affects groundwater supplied and used for consumption by communities living around the Marituba landfill (ML), and it is essential to investigate the spatial distribution of heavy metals in landfill groundwater and determine concentrations of toxic metals to assess the quality of water consumed and levels of health risk. Therefore, the objective of the present study will be to evaluate water quality by determining the concentration of heavy metals in groundwater intended for human consumption in the surroundings of the ML as well as by calculating the health risk factors due to exposure to these heavy metals. The results can help policymakers promote treatment and control measures to protect groundwater and human health.

2. Materials and Methods

2.1. Study Area

The Marituba landfill has operated since 2015 (Figure 1). It is the final destination of urban solid waste (MSW) from the Metropolitan Region of Belém, State of Pará, Northern Region of Brazil, with geographic coordinates of latitude 1°23′53.47″ S and longitude 48°20′25″ W, approximately 4 km from the center of the municipality of Marituba. It occupies an area of 111 ha, with 780,000 m² allocated to processing/treatment units and support infrastructure and 320,000 m² allocated as an environmental preservation area. The landfill receives around 40.5 thousand tons of waste per month from the RMB [19], which comprises the cities of Ananindeua, Belém, and Marituba and has a combined total population estimated at almost 2 million inhabitants.

The municipality of Marituba, where the landfill is located, has an estimated population of 133,685 people and a territorial extension of 103,214 km² [20]. Near the study area, the geology presents a sedimentary cover from the Quaternary Period, whose lithostratigraphic profiles show that the confined aquifers are protected by a layer of clayey material with red, gray, and variegated clays as well as good-to-medium sand and ferruginous levels [20]. The primary sanitation data are worrying. Only 18.8% of sanitary sewage and a small percentage (0.4%) of of households have adequate urbanization (presence of curbs, drains, sidewalks, and paving). The HDI (human development index) is 0.676, ranking 2524th out of 5565 Brazilian municipalities [21].

Data from the Department of Health Surveillance indicate a general number of households with a water supply 66,555. Among these residences, SISÁGUA (water quality surveillance information system for human consumption) recorded a total of 4384 houses that are supplied by IAS (individual alternative solution)—that is, they have an artesian well or Amazon well, and 47,106 homes have water are provided by CAS (collective alternative solution)—that is, they are served by a tubular well managed by City Hall. Therefore, approximately 77% of homes are supplied by groundwater.

Figure 1. Municipal network, hydrography, road system, and polygonal representation of the landfill and the wildlife refuge in the municipality of Marituba [22,23,24].

2.2. Collection and Analysis of Groundwater Samples

In total, 32 samples were distributed across 16 collection sites in May (rainy period) and October (dry period) 2022 (Figure 2). According to the following pre-established criteria: (a) water sample for exclusively residential consumption; (b) water source by underground abstraction; (c) sites located close to the Marituba Landfill.

Figure 2. Map of collection sites [25,26].

The distances from the area comprising the landfill to the collection sites used vary from 1160 m to 3300 m (Figure 2).

Water samples were collected from sampling sites in high-density polyethylene bottles pre-washed with a 10% nitric acid (HNO³) solution. Aliquots of water samples were filtered through 0.45 µm non-pyrogenic syringe filters and stored in 50 mL polypropylene bottles, then acidifying the sample with 65% HNO³ to pH ≤ 2. Then, the samples were placed in thermal boxes and transferred to the Environmental Chemistry and Health Laboratory at the Evandro Chagas Institute, Pará, Brazil.

The metals aluminum (Al), barium (Ba), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), zinc (Zn), mercury (Hg), antimony (Sb), and arsenic (As) were analyzed using the inductively coupled plasma mass spectrometry (ICP MS) technique, Agilent Model 7900. The method follows the protocol adapted from the Standard Methods for the Examination of Water and Wastewater [27].

Analytical quality control was performed by analyzing the reagent blank, sample blank, and certified reference standard (SRM 1640a: Gaithersburg, MD, USA). Triplicate analyses were performed for all samples to determine the method’s reproducibility. Calibration standards were diluted from metal stock solutions. Quantification limits ranged from 0.01 to 5.50 µg L⁻¹. The analytical recovery of metals in SEM ranged from 91–103% and was fortified blank between 92–108%.

2.3. Groundwater Quality Index (GWQI)

To calculate the polluting potential of leachate from landfills, the WQI equation (Equations (1) and (2)) was used for the rainy and dry periods [28] established by [29] in the USA, and today, this approach is widely benefited by water quality examiners [28].

G W Q I = \sum [W_{i} . (\frac{C_{i}}{S_{i}}) \times 100]

(1)

W_{i} = w_{i} / Σ w_{i}

(2)

W_{i}

refers to the relative weight for the it pollutant variable. Considering the parameters’ comparatively critical impacts on public health, the values are designated by minimum and maximum magnitudes of 1 and 5, respectively. Based on the Brazilian regulation on water quality for human consumption (Ordinance GM/Brazilian Ministry of Health No. 888 of 4 May 2021) and the WHO Guideline for Drinking Water (2017).

C_{i}

represents the element level for the ith variable quantified in water, and

S_{i}

expresses the values for the ith reference variable reported by the WHO regarding drinking water. About WQI, water quality is evaluated in five categories: GWQI ≥ 300, non-potable; 200 ≤ GWQI < 300, very poor; 100 ≤ GWQI < 200, poor; 50 ≤ GWQI < 100, good; GWQI < 50, excellent [29]. The assigned weight (

w_{i}

) and relative weight (

W_{i}

) are presented in Table 1.

2.4. Heavy Metal Pollution Index (HPI)

Calculating the HPI is necessary because it is an assessment approach that considers the combined impact of each heavy metal on total water quality. Most scientists have used it to broadly assess water quality in general. Its calculation is based on Equations (3) and (4), proposed as follows [31]:

H P I = \sum_{i = 1}^{n} w_{i} p_{i} / \sum_{i = 1}^{n} w_{i}

(3)

p_{i} = (\sum_{i = 1}^{n} C_{i} / S_{i}) \times 100

(4)

In Equations (3) and (4),

w_{i}

expresses the unit weight of the ith factor, and

p_{i}

refers to the subindex of the metals analyzed.

S_{i}

indicates the reference values of the factor,

C_{i}

represents the tracked values of toxic metals, and n represents the number of factors considered. HPI < 100 therefore represents a low level of heavy metal pollution that is possibly not responsible for serious health effects [31], and HPI > 100 represents high levels of contamination with direct effects on public health.

2.5. Heavy Metals Assessment Index (HEI)

Similar to the HPI, the HEI sets the general trend in examining water quality with regards to heavy metal pollution in water. In this manner, it can simply be employed to interpret the degree of water pollution [32]. In this study, the HEI was calculated based on Equation (5).

H E I = \sum_{i = 1}^{n} H_{C} / H_{M A C}

(5)

where

H_{C}

refers to the value detected for each factor and

H_{M A C}

expresses the magnitude of the maximum permissible concentration (MAC) for all WHO variables. Concerning MAC, high metal levels lead to even more unpleasant water quality [28,31,32,33]. As a general rule, water is not advisable for consumption when any individual metal exceeds the MAC value (HEI > 10). Water quality can decrease due to other causes when metal levels do not exceed but are close to MAC values. Therefore, the HEI is verified by three classifications: HEI > 20 means high contamination, 10 < HEI < 20 means medium contamination, and HEI < 10 means low contamination [31,34].

2.6. Risk Assessment to Human Health

A human health risk assessment calculation is necessary to evaluate toxicity in humans. According to the United States Environmental Protection Agency [30], the calculations of the risk quotient (RQ) and the risk index (RI) were measured based the target group, adult inhabitants of the Municipality of Marituba who live around the landfill. Initially, the chronic daily intake (CDI) of heavy metals by ingestion and dermal adsorption of water for population was calculated using Equations (6) and (7), respectively. The parameters and values used in the equations are presented in Table 2.

{C D I}_{o r a l} (m g {k g}^{- 1} {d a y}^{- 1}) = \frac{C_{h m} \times D I \times A B S \times E F \times E D}{B W \times A T}

(6)

{C D I}_{d e r m a l} (m g {k g}^{- 1} {d a y}^{- 1}) = \frac{C_{h m} \times S A \times K_{p} \times A B S \times E T \times E F \times E D \times C F}{B W \times A T}

(7)

Equations (8) and (9) calculated the HQ of heavy metals through ingestion and dermal absorption of water for population in the area.

{R Q}_{o r a l} = \frac{{C D I}_{o r a l}}{R_{f} D_{o r a l}}

(8)

{R Q}_{d e r m a l} = \frac{{C D I}_{d e r m a l}}{R_{f} D_{d e r m a l}}

(9)

HI is the total non-carcinogenic health risks caused by different heavy metals in water. It was calculated using Equations (10) and (11) according to the USEPA guidelines for water ingestion and dermal adsorption for people in the study area.

R I = {R I}_{o r a l} + {R I}_{d e r m a l}

(10)

{R I}_{t o t a l} = \sum_{i = 1}^{n} {R I}_{m e t a l s}

(11)

To estimate potential non-carcinogenic health risks caused by heavy metals present in water, the limit value was determined at 1.0. The RQ value < 1.0 means that exposed populations suffer prejudicial health impacts. On the other hand, the RQ value > 1.0 means that non-cancer health risks may occur for the local population of the study area [35]. On the other hand, they report that the RI (hazard index) is evaluated in 5 categories: total RI > 4 means extreme risk, 3 < total RI < 4 means high risk, 2 < total RI < 3 means medium risk, 1 < Total RI < 2 means low risk, and total RI < 1 means no risk [36].

Carcinogenic risk to human health is assessed after the incremental lifetime cancer risk (ILCR) is calculated due to exposure to a potential carcinogen (in this study: As, Co, Cd, Cu, Cr, Ni, and Pb). The possibilities of an individual’s carcinogenic potential risk of developing cancer over a lifetime of exposure are calculated by multiplying the CDI and the cancer slope factor (CSF) together [30,37]. Equation (12) was used to calculate the ILCR for each carcinogen.

I L C R = C D I \times C S F

(12)

In the present study, CSF values for the carcinogens mentioned above were introduced by the California Office of Environmental Health Assessment [38] (Table 1). When calculating the total ILCR (ΣILCR) for groundwater, the CDI of oral and dermal exposure to the aforementioned carcinogens was considered. According to the USEPA, the acceptable range for ΣILCR is 1 × 10⁻⁶ to 1 × 10⁻⁴ for single-element or multielement carcinogens [30,35,39].

Table 2. Input assumptions are used to calculate the non-carcinogenic risk to human health due to exposure to heavy metals through ingestion and skin absorption of water.

Parameter	Unit	Values		Reference
Parameter	Unit	Ingestion	Dermal Adsorption	Reference
$Heavy metal concentration (C_{h m})$	$m g L^{- 1}$	-	-	[35]
$Daily average intake (D I)$	$L {d a y}^{- 1}$	2.0	-	[35]
$Skin surface area (S A$ )	${c m}^{2}$	-	18,000	[40]
$Permeability coefficient (K_{p}$ )	$c m h^{- 1}$		As, Hg, Cd, Fe, Cu, Se, Sb, U = 0.001; Co = 0.0004; Cr = 0.002 Pb = 0.0001; Ni = 0.0002 and Al, Ba, Zn = 0.0006	[40]
$Exposure time (E T$ )	$h {e v e n t}^{- 1}$	-	0.58	[40]
$Exposure frequency (E F$ )	$D a y s {y e a r}^{- 1}$	365	365	[40]
$Exposure duration (E D$ )	$y e a r$	8	8	[35]
$Conversion factor (C F$ )	$L {c m}^{- 3}$	-	0.001	[40]
$Average body weight (B W$ )	$k g$	65	65	[41]
$Absorption Fator (A B S$ )	-	0.001	0.001	[40]
$Average time (A T$ )	$D a y$	2737	2737	[42]

2.7. Interrelationship between Water Quality Parameters and Pollution Source Identification

For assessment of the interrelationship between water quality parameters, MINITAB version 17 software was used, aiming to promote analysis of variance (ANOVA) to measure significant differences reported when p < 0.05 and the identification of the origin was based on hierarchical cluster analysis (HCA) and principal component analysis (PCA) to classify groups of water quality variables and resource sampling locations of similar contamination. PCA was conducted to determine the contributing source. Furthermore, Spearman’s correlation coefficient matrix was used for all selected elements to determine correlations between several options.

3. Results and Discussion

3.1. Heavy Metals in Groundwater

Supplementary Table S1 shows the values of groundwater quality parameters in locations around the Marituba Landfill in the rainy and dry seasons according to the standards [30,40,43,44].

The results show that water in dry and rainy seasons is acidic, with pH values below the WHO recommended standards of 6.50–8.50. However, it was observed that the pH of water in the rainy season is slightly more acidic than water in the dry season. These values indicate that there was not much difference in pH and that there is no significant pH variability due to seasonal contamination. Almost all of the water analyzed has an average temperature of 28 °C. Average conductivities were higher in the rainy season, indicating that the water contains large amounts of ions responsible for such conductivities [45,46].

Average levels of trace metals generally did not show significant differences between groundwater during the dry and rainy seasons. In the rainy season, the average concentration of heavy metals was presented in descending order as follows: Al > Fe > Ba > Zn > Cu > Ni > Pb > Co > Se > U > Hg > Cr > Cd > Sb. In the dry season, the average concentration was as follows: Al > Fe > Ba > Cu > Co > Ni > Pb > U > Cd, Cr, Hg, Sb, Se, and Zn. Almost all of them presented concentrations below the limits established by the standards of regulatory agencies, except aluminum, whose limit established by national and international bodies is 200 μg L⁻¹ [11,32,42,45]. Aluminum concentrations ranged from <LD to 378.01 μg L⁻¹ and 3.82 to 339.5 μg L⁻¹ in the dry and rainy seasons, respectively. The highest values were found at sites P01, P06, and P15 (dry season) and sites P01, P02, P03, P04, P06, P15, and P16 (dry season), exceeding the limit required for drinking water established by CONAMA. These variations can be explained by concentrations of dissolved aluminum in waters with almost neutral pH values, which generally range from 10 to 50 μg L⁻¹ but increase to 500 to 1000 μg L⁻¹ in more acidic or carbon-rich waters. These high concentrations of Aluminum may be related to natural and/or anthropogenic occurrences.

Cu was found in low concentrations ranging from <LD to 4.74 μg L⁻¹ in most samples during the rainy season. Cu, due to its low solubility, is generally present in groundwater at concentrations <1 μg L⁻¹ [41]. Cr, Hg, Se, and Zn presented levels ranging from <LD−0.09 μg L⁻¹, <LD−0.24 μg L⁻¹, <LD−0.35 μg L⁻¹, <LD−17.25 μg L⁻¹, respectively, while Sb was <LD in all samples analyzed. Arsenic was detected only in the dry period with values varying between <LD−0.22 μg L⁻¹ with an average of 0.10 μg L⁻¹. Hg was found in three samples during the rainy season at sites P04 (0.24 μg L⁻¹), P07 (0.12 μg L⁻¹), and P12 (0.27 μg L⁻¹). Toxic metals such as Cd, Pb, and Ni were found in values ranging from <LD to 0.22 μg L⁻¹, <LD to 1.44 μg L⁻¹ and <LD to 3.93 μg L⁻¹, respectively, with more significant influence from the less rainy period. U presented values of <LD at 0.15 μg L⁻¹, with no marked difference between the months studied.

In our paper, Al, Ba, Ni, and Pb were observed at all 16 sites during the rainy season in the heavy metal analysis. In the dry period, the most abundant metals were Ba and Al in 16 and 15 sites, respectively. Only Al presented values above 200 μg L⁻¹, the value permitted by Brazilian legislation—in 3 sites (P01, P06, and P15) in the rainy period and in 7 sites in the dry period (P01, P02, P03, P04, P06, P15, and P16) above. These high concentrations of Al may be due to geological formation, as it is a naturally available metal in the environment, as well as anthropogenic interference. The study area’s geological formation has clay as its main lithostratigraphic profile. Clay reacts with waters with acidic pH values and releases aluminum into the groundwater. Even so, several epidemiological studies have reported associations between chronic aluminum exposure and neurological disorders, including Alzheimer’s disease. However, little evidence links aluminum exposure and neurological diseases [47]. Many factors, including water pH and organic matter content, greatly influence aluminum toxicity. As the pH decreases, its toxicity increases. Aluminum is considered very harmful to nerve, bone, and hemopoietic cells [48].

Cu, Au, and Zn are essential elements, and the main concerns regarding their presence in drinking water are their effects on taste, odor, color, and stains on clothing and plumbing. Within the established limits, the levels of these metals typically found in drinking water do not cause adverse health effects [47]. Chronic copper toxicity is generally observed in patients with Wilson’s disease, the rare inherent disease characterized by excessive accumulation of copper in various tissues of the body [49].

Ba, Ni, and Pb are present in groundwater in trace concentrations, and as toxic pollutants, they can be harmful to health even at low concentrations. The Cd was present in 3 samples, and the other 15 metals analyzed were present at specific collection sites. The exception is for Sb and As, which presented values below the limit of quantification (LQ).

During the rainy season, there is more significant surface runoff due to the increased rainfall in the Amazon. In the dry period, there was a more remarkable absence of metals in trace concentrations—Sb, Se, Zn, Cd, Cr, and Hg were below the LQ. However, during this period, all samples presented trace values for As, which was absent during the intense rain. Toxic metals are even present in trace concentrations, such as As, Pb, Cd, Hg, Co, and Zn, which can accumulate in soft tissues. They can access the human body, including through contaminated water. As they are not biodegradable, they generate several adverse environmental effects that are also harmful to human health in the long term [49,50].

Pb in the rainy season presented concentrations in all samples collected. Even low levels of Pb in children’s blood can result in learning problems, hyperactivity, slow growth, and anemia. In adult women, this metal accumulates in the bones over time and, during pregnancy, is released to the fetus through maternal calcium. It is a metal that crosses the placental barrier [35].

As and Pb are considered among the most toxic water pollutants and a significant threat to quality drinking water. According to WHO, the maximum allowable concentration of this metal must be very restricted. The USEPA allows As concentrations in waters of up to 10 μg L⁻¹. Long-term exposure to this metal is related to an increase in skin, lung, bladder, and kidney cancer, as it bioaccumulates in the human body. Arsenic was found in all samples from the dry period, with an average concentration of 0.1 μg L⁻¹ and a maximum value of 0.22 μg L⁻¹. The International Agency for Research on Cancer (IARC) already classifies inorganic arsenic as carcinogenic to humans [51].

Ni is easily found in wastewater and waste processing plants. It appears in soil due to anthropogenic interference from the decomposition of batteries and metallic finishes, which are generally present in waste dumped in landfills. Ni is released when the potentially polluting source is a landfill. Studies carried out in Canada at three landfills in operation for at least 30 years have already identified more intense concentrations of Ni in the leachate. It is one of the metals most present in groundwater near landfills [52]. Its health effects when the route of exposure is non-occupational are related to kidney and respiratory problems. IARC does not yet have confirmation that Ni metal is carcinogenic, and it is classified as a possibly carcinogenic substance (Group 2B). In the samples collected, the average concentration of Ni in the rainy season is 0.685 μg L⁻¹ and 0.47 μg L⁻¹ in the dry season, which is considered low for potability standards; however, adequate, and robust monitoring is necessary, as according to research by ATSDR, more than half of the nickel used in the production of batteries will be discarded in landfills. Future generations may suffer from higher concentrations of Ni and other metals, which would have negative consequences for the health and well-being of the population surrounding the landfill, as previously mentioned.

In the study proposed by Essien et al. [53], the levels of heavy metals in surface waters in dumps and landfills in Uyo, Nigeria were slightly higher than those found here. Wang et al. [53], in a study carried out in a landfill in a low-permeability area in Zyiang, China, found metal values lower than those found in ML, mainly Zn, PB, and Cu. In Poland, a landfill was studied for seven years, and an increase in the Cd value was detected, causing a deterioration in groundwater quality [52]. Communities living closer to landfills are exposed to more significant diverse health risks than those living further away from landfills [51]. In this study, the sites studied were approximately 1160 m to 3300 m from the ML. Regarding the distribution of metal levels in this study, the highest concentrations of Al, Cd, Ni, Cr, and PB were found closer to the ML (1160 m to 1189 m). In a study in Laos, two groundwater samples were collected and analyzed from wells located within the landfill and 70 m from the landfill; the metal results were lower than in our study [54]. In Bulawayo, Zimbabwe, communities were located within a radius of 800–2135 m from the landfill slope area, with Cd and Pb levels higher than the levels found in our study [55]. In a previous study, Queiroz et al. [56,57] analyzed four metals in groundwater around the ML. Concentration levels of metals (As, Cu, Pb, and Mn) were low—similar to what was found in our study—but presented an RQ > 1, indicating exposure to non-carcinogenic risks for water for human consumption.

The mobilization and distribution of heavy metals in groundwater near landfills are frequent, so special attention must be paid to groundwater quality since residents near landfills consume this water.

3.2. Groundwater Quality Index

Based on the application of Equations (1) and (2) in the function of the assigned weight (w_i) and the relative weight (W_I) for each parameter, Table 1 and the values of the parameters pH, temperature, electrical conductivity, As, Al, Ba, Co, Cd, Cu, Cr, Fe, Hg, Ni, Pb, Sb, Se, U, and Zn in the rainy and dry periods, presented in Supplementary Table S1, the WQI results for groundwater samples from around the landfill of municipality of Marituba in the rainy and dry seasons are presented in Table 3. The WQI values for the rainy and dry seasons were 13.729 and 14.766, respectively, presenting excellent water quality for consumption, even though the sampling site were approximately 1 km from the LM [53].

3.3. Heavy Metal Pollution Index

The HPI values for the rainy and dry periods were 6.180 and 7.176 (Table 3), respectively, to calculate the heavy metal pollution index. This represents a low level of heavy metal pollution that may not be responsible for severe effects on the health of Marituba’s population [32].

Based on the heavy metals assessment index, the HEI values for the rainy and dry periods were 0.876 and 1.036 (Table 3), respectively. These values represent low contamination by heavy metals compared to the concentration of heavy metals and maximum permissible concentration for all metals involved in this study [32].

The results of the IQA and HMPI models for the parameters studied in this work are presented in Table 3. However, the statistical variability of the IQA and HMPI models between the monitored points was insignificant, which allowed us to choose to use average values of the studied parameters in the calculations of the weighted arithmetic method.

3.4. Risk Assessment to Human Health

Regarding heavy metals, non-carcinogenic risk for adults was computed using risk quotient (RQ) and risk index (RI) based on oral ingestion and dermal absorption of groundwater in the Municipality of Marituba. This calculation was based on input assumptions (Table 2) collected in the field, where

{C D I}_{o r a l} (m g {k g}^{- 1} {d a y}^{- 1})

indicates average daily dose per intake and

{C D I}_{d e r m a l} (m g {k g}^{- 1} {d a y}^{- 1})

expresses average daily dose per intake in μg kg⁻¹dia⁻¹;

C_{h m}

refers to the concentration of metals in surface waters in μg L⁻¹;

D I

is the intake rate, which in our work is 2.0 L day⁻¹ for adults;

A B S

refers to the unitless gastrointestinal absorption factor, being 0.001 for oral ingestion and dermal absorption from groundwater;

E F

is the frequency of exposure, defined as 365 days/year for oral ingestion and dermal absorption of groundwater, depending on being an inhabitant of Marituba;

E D

represents the average defined exposure time—8 years for adults—according to the period of installation of the landfill;

B W

presents an average body weight of 65 kg for adults;

A T

is the average time in days and is set at 2737 for adults;

S A

is the area of exposed skin in cm², 18,000 for adults;

K_{p}

is the coefficient of dermal permeability in water in cm h⁻¹,

E T

represents exposure time during bathing, which is 0.58 h/day; and

C F

is the unit conversion factor, which is 0.001

L {c m}^{- 3}

[42]. The values of toxicological parameters used to assess health risk are illustrated in Table 1, reference oral dose (

R_{f} D_{o r a l}

), and reference dermal doses (

R_{f} D_{d e r m a l}

) (Table 1). For values below the detection limit, the detection limit value for the referred metal was considered for calculation purposes, and its results are illustrated in Supplementary Table S2. The calculated cancer risks posed by these toxic metals through ingestion and dermal exposure to residents of the study area are presented in Supplementary Table S2.

Cd is the only element analyzed in the risk assessment that is considered carcinogenic by IARC. In our study, it was present in four samples (P01, P07, P13, and P16) in trace concentrations with an average of 0.016 μg L⁻¹ in the rainy season and at lower limits than are quantifiable in the dry season. Cd has a long half-life in the body; even at low concentrations, it has long-term consequences, especially for children and fetal health. Kidney, lung, and bone cancers are those most related to Cd exposure [48].

Humans are exposed to metal residues through direct ingestion, inhalation through the mouth and nose, and dermal absorption through the skin. The health risk associated with drinking water depends on the volume of water consumed and the individual’s weight. The results indicate that the calculated oral and dermal RQ values for the metals—except aluminum—were below 1.0, indicating that the metals were within an acceptable level of non-carcinogenic health hazard risk in all locations. Oral values of aluminum RQ found in groundwater in the municipality of Marituba become worrying because aluminum is a recognized neurotoxicant that can interfere with critical physiological and biochemical processes in the central nervous system, such as synaptic transmission, synthesis of neurotransmitters, synthesis and degradation of proteins, gene expression, and inflammatory responses, resulting in neurodegenerative changes [58]. Consequently, the total RI value calculated to determine the total potential for non-carcinogenic impacts on human health created by all heavy metals studied in association resulted in values of 1.09 × 10¹ in the rainy season and 1.43 × 10¹ in the dry period, showing that due to the high aluminum values, the adult population of the municipality of Marituba can suffer extreme non-carcinogenic impacts in both the rainy and dry period, as shown in Figure 3.

The results show that for the calculated mean values of ILCR for each toxic metal considered in both rainy and dry periods, the cancer risks are considered so small as to be insignificant. Furthermore, the ΣILCR values were 1.76 × 10⁻⁴ and 6.17 × 10⁻⁶ for ILCR (total oral) and ILCR (total dermal), respectively, in the rainy period; for the dry period, the values were 3.07 × 10⁻⁹ and 2.05 × 10⁻⁵ for ILCR (total oral) and ILCR (total dermal), respectively. This demonstrates that according to USEPA, the values are within the acceptable range for ΣILCR for multi-element carcinogens [30,35,39].

3.5. Interrelationship between Water Quality Parameters and Pollution Source Identification

Contamination source identification to classify clusters of water quality variables and sampling locations of similar contamination characteristics was based on hierarchical cluster analysis (HCA) and principal component analysis (PCA) [59,60]. PCA was used to find possible sources of toxic metals in groundwater. Figure 4a,b show the load graph and the correlation between the metals studied in the dry and rainy seasons. Three main factors were found to represent 77.1% of the total variation (Figure 4a). PC1 represented 35.6% of the total variation and was dominated by Fe, Cd, Pb, and Zn. Natural and anthropogenic sources influence this component (Figure 4a). PC2 and PC3 accounted for 24.4% and 12.1% of the total variation and were dominated by Fe and Hg (PC2) and Al, Ba, Se, Co, Ni, and U (PC3). PC2 was influenced by natural sources, and natural and anthropogenic sources influenced PC3. For the dry season samples (Figure 4b), the first principal component (PC1) represented 44.7% of the total variance, and the second component (PC2) represented 26.4%, a combined 71.1% of the total variance. PC1 was dominated by Fe, Al, Ba, Pb, and Cu, while PC2 was dominated by As, U, Ni, and Co. Both PC1 and PC2 were influenced by natural and anthropogenic sources.

According to the Spearman correlation matrix, there are strong correlations between aluminum and barium (Figure 5), temperature, and pH. In the rainiest period, there was a similarity between metal values in the following sampling locations: (A) P02, P03, P04, P05, P06, and P07; (B) P09, P10, P11, and P14; and (C) P08 and P12. In the driest period, there was a different profile with the similarity between values of the physical–chemical parameters as follows: five sampling locations (P02, P03, P04, P05, and P07), another group with two sampling locations (P09 and P15), and yet another group with two more similar sampling locations (P10 and P11). These 3 groups had a statistically significant difference between these locations (p < 0.05).

4. Conclusions

This study demonstrated the presence of heavy metals in groundwater around the Marituba Landfill in Brazil. Heavy metals, such as Ni, Pb, Al, Hg, and Cd, were found in low concentrations within the limit established by Brazilian legislation, except aluminum, which presented levels outside the limit in three sampling points in the rainy season and seven points in the rainy season. After chemical analysis, it was found that the groundwater was suitable for consumption. The GWQI values were 13.279 and 14.766 in the dry and rainy seasons, respectively, which are considered excellent for human consumption. HEI and HPI levels indicated low levels of contamination. Although the risk assessment does not present data harmful to human health according to the studies and calculations carried out, the results of heavy metal concentrations are considered a warning: the presence of toxic metals, even in trace concentrations, demonstrates contamination of these pollutants by human activity, as they are not found naturally in the environment. This confirms that the source of pollution is the landfill, as there is no other industrial activity nearby. Although the landfill is installed upstream of nearby neighborhoods, these low concentrations indicate pollution by leachate from the free aquifer.

More robust monitoring is needed to mitigate impacts, preserve these sources, and control pollutants so that in the future, the waters remain suitable for consumption, as they are today, and that the population does not suffer from diseases resulting from the action of these pollutants.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w16152146/s1. Table S1: The measured concentration of water quality parameters complies with the standards of Ordinance GM/Brazilian Ministry of Health (MS888/2021), World Health Organization (WHO), European Union (EU), and U.S. Environmental Protection Agency (US EPA); Table S2: Risk quotient (RQ) and risk index (RI), based on oral ingestion and dermal absorption of groundwater in the Municipality of Marituba in the rainy and dry periods; Table S3: Coordinates of the sites and depth of the underground wells; Figures S1 and S2: Metal concentration graph in the dry season; Figures S3 and S4: Metal concentration graph in the rainy season; Figure S5: aluminum concentration graph in the dry and rainy season.

Author Contributions

Conceptualization, R.C.d.O.S., R.J.A.d.D. and R.d.A.M.; methodology, R.d.A.M., M.M.C.S., A.C.M., K.R.F.F. and R.J.A.d.D.; validation, R.C.d.O.S., R.J.A.d.D. and R.d.A.M.; writing—original draft preparation, R.d.A.M., R.J.A.d.D. and R.C.d.O.S.; writing—review and editing, R.C.d.O.S. and R.d.A.M.; supervision, R.d.A.M. All authors have read and agreed to the published version of the manuscript.

Funding

The Evandro Chagas Institute, an organization belonging to the Health and Environment Surveillance Secretariat of the Brazilian Ministry of Health, financed this project.

Data Availability Statement

The authors authorize the availability of data explained in this research. The relevant data can be found in this article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

Han, Z.; Ma, H.; Shi, G.; He, L.; Wei, L.; Shi, Q. A review of groundwater contamination near municipal solid waste landfill sites of China. Sci. Total Environ. 2016, 569–570, 1255–1264. [Google Scholar] [CrossRef] [PubMed]
Publio, M.C.M.; Delgado, J.F.; Pierri, B.S.; Lima, L.d.S.; Gaylarde, C.C.; Neto, J.A.B.; Neves, C.V.; Fonseca, E.M. Assessment of groundwater contamination in the Southeastern coast of Brazil: A potential threat to human health in Marica Municipality. Eng 2023, 4, 2640–2655. [Google Scholar] [CrossRef]
Asare-donkor, N.K.; Boadu, T.A.; Adimado, A.A. Evaluation of grounwater and surface water quality and human risk assessment for trace metals in human settlements around the Bosomtwe Crater Lake in Ghana. SpringerPlus 2016, 5, 1812. [Google Scholar] [CrossRef] [PubMed]
Brindha, K.; Paul, R.; Walter, J.; Tan, M.L.; Singh, M.K. Trace metals contamination in groundwater and implications on human health: Comprehensive assessment using hydrogeochemical and geostatistical methods. Environ. Geochem. Health 2020, 42, 3819–3839. [Google Scholar] [CrossRef]
Bakyayita, G.K.; Norrström, A.C.; Kulabako, R.N. Assessment of Levels, speciation, and Toxicity of Trace Metal Contaminants in Selected Shallow Groundwater Sources, Surface Runoff, Wastewater, and Surface Water from Designated Streams in Lake Victoria Basin, Uganda. J. Environ. Public Health 2019, 2019, 6734017. [Google Scholar] [CrossRef]
Triassi, M.; Cerino, P.; Montuori, P.; Pizzolante, A.; Trama, U.; Nicodemo, F.; D’auria, J.L.; De Vita, S.; De Rosa, E.; Limone, A. Heavy Metals in Groundwater of Southern Italy: Occurrence and Potential Adverse Effects on the Environment and Human Health. Int. J. Environ. Res. Public Health 2023, 20, 1693. [Google Scholar] [CrossRef] [PubMed]
Liu, F.; Qiu, Z.; Zhang, J.; Liu, W.; Liu, C.; Zeng, G. Investigation, Pollution Mapping and Simulative Leakage Health Risk Assessment for Heavy Metals and Metalloids in Groundwater from a Typical Brownfield, Middle China. Int. J. Environ. Res. Public Health 2017, 14, 768. [Google Scholar] [CrossRef] [PubMed]
Castilhos, A.B., Jr.; Medeiros, P.A.; Firta, I.N.; Lupatini, G.; da Silva, J.D. Principais Processos de Degradação de Resíduos Sólidos Urbanos; ABES: Rio de Janeiro, Brazil, 2003. [Google Scholar]
Kjeldsen, P.; Barlaz, M.A.; Rooker, A.P.; Baun, A.; Ledin, A.; Christensen, T.H. Present and Long-Term Composition of MSW Landfill Leachate: A Review. Crit. Rev. Environ. Sci. Technol. 2002, 32, 297–336. [Google Scholar] [CrossRef]
Băbău, A.M.C.; Micle, V.; Damian, G.E.; Sur, I.M. Sustainable Ecological Restoration of Sterile Dumps Using Robinia pseudoacacia. Sustainability 2021, 13, 14021. [Google Scholar] [CrossRef]
World Organization of Health—WHO. Guidelines for Drinking Water Quality, 2nd ed.; WHO: Geneva, Switzerland, 1996. [Google Scholar]
Crossgrove, J.; Zheng, W. Manganese Toxicity upon overexposure. NMR Biomed. 2004, 17, 544–553. [Google Scholar] [CrossRef]
Pejman, A.; Bidhendi, G.N.; Ardestani, M.; Saeedi, M.; Baghvand, A. Fractionation of heavy metals in sediments and assessment of their availability risk: A case study in the northwestern of Persian Gulf. Mar. Pollut. Bull. 2017, 114, 881–887. [Google Scholar] [CrossRef]
Hussain, S.; Habib-Ur-Rehman, M.; Khanam, T.; Sheer, A.; Kebin, Z.; Jianjun, Y. Health Risk Assessment of Different Heavy Metals Dissolved in Drinking Water. Int. J. Environ. Res. Public Health 2019, 16, 1737. [Google Scholar] [CrossRef] [PubMed]
El-Naqa, A. Environmental impact assessment using rapid impact assessment matrix (RIAM) for Russeifa landfill, Jordan. Environ. Geol. 2004, 47, 632–639. [Google Scholar] [CrossRef]
Mutileni, N.; Mudau, M.; Edokpay, J.N. Water quality, geochemistry and human health risk of grounwater in the Vyeboom region, Limpopo province, South Africa. Sci. Rep. 2023, 13, 19071. [Google Scholar] [CrossRef] [PubMed]
Sun, F.; Chen, J.; Tong, Q.; Zeng, S. Integrated risk assessment and screening analysis of drinking water safety of a conventional water supply system. Water Sci. Technol. 2007, 56, 47–56. [Google Scholar] [CrossRef]
Instituto Água e Saneamento. Available online: https://www.aguaesaneamento.org.br/municipios-e-saneamento/pa/marituba#:~:text=32%2C13%25%20da%20popla%C3%A7%C3%A3o%20%C3%A9,n%C3%A3o%20t%C3%AAm%20acesso%20%C3%A0%20%C3%A1gua (accessed on 21 March 2021).
Instituto Brasileiro de Geografia e Estatística (IBGE). Cidades: Marituba. Rio de Janeiro. Available online: https://www.cidades.ibge.gov.br (accessed on 4 March 2021).
Matta, M.A.S. Fundamentos Hidrogeológicos para a Gestão Integrada de Recursos Hídricos da Região Metropolitana de Belém/Ananindeua—Pará, Brasil. Ph.D. Thesis, Federal University of Pará, Belém, Brazil, 2002. [Google Scholar]
Instituto Brasileiro de Geografia e Estatística (IBGE). Censo, 2010. Available online: https://www.censo2010.ibge.gov.br (accessed on 21 March 2021).
Instituto Brasileiro de Geografia e Estatística (IBGE). Malha Municipal 2018; IBGE: Rio de Janeiro, Brazil, 2018. Available online: https://www.ibge.gov.br/geociencias/todos-os-produtos-geociencias/15774-malhas.html?=&t=o-que-e (accessed on 23 July 2022).
ANA—Agência nacional de águas. Sistema Nacional de Informações em Recursos Hídricos (SNIRH); ANA-MMA: Brasília, Brazil, 2012. Available online: https://www.snirh.gov.br/hidroweb/apresentacao (accessed on 24 July 2020).
Guama Tratamento de Residuos. Aterros Sanitarios. 2018. Available online: https://www.guamaambiental.com.br/aterros (accessed on 10 May 2021).
Collection Sites of Water and Landfill. Department of Carthographic. SAAMB. Evandro Chagas Institute. 2022.
Instituto Brasileiro de Geografia e Estatística (IBGE). Administrative Politicals, Limits and Divisions. 2021. Available online: https://brasilemsintese.ibge.gov.br/territorio/divisao-politica.html (accessed on 5 June 2022).
Baird, R.; Bridgewater, L. Standard Methods for the Examination of Water and Wastewater, 23rd ed.; American Public Health Association: Washington, DC, USA, 2017. [Google Scholar]
Mohan, S.V.; Nithila, P.; Reddy, S.J. Estimation of heavy metals in drinking water and development of heavy metal pollution index. J. Environ. Sci. Health Part A Environ. Sci. Eng. Toxicol. 1996, 31, 283–289. [Google Scholar] [CrossRef]
Horton, R.K. An Index Number System for Rating Water Quality. J. Water Pollut. Control Fed. 1965, 37, 300–306. [Google Scholar]
Environmental Protection Agency U.S. Available online: https://www.epa.gov/ (accessed on 10 October 2022).
Xiao, J.; Wang, L.; Deng, L.; Jin, Z. Characteristics, sources, water quality and health risk assessment of trace elements in river water and well water in the Chinese Loess Plateau. Sci. Total Environ. 2018, 650, 2004–2012. [Google Scholar] [CrossRef]
Saleh, H. Heavy Metals; IntechOpen: Rijeka, Croatia, 2018. [Google Scholar]
Edet, A.; Offiong, O. Evaluation of Water Quality Pollution Indices for Heavy Metal Contamination Monitoring. A Study Case from Akpabuyo-Odukpani Area, Lower Cross River Basin (Southeastern Nigeria). GeoJournal 2002, 57, 295–304. [Google Scholar] [CrossRef]
Goher, M.; Hassan, A.; Abdel-Moniem, I.; Fahmy, A. El-Sayed S Evaluation of surface water quality and heavy metal indices of Ismailia Canal, Nile River, Egypt. Egypt. J. Aquat. Res. 2014, 40, 225–233. [Google Scholar] [CrossRef]
Mohammadi, A.A.; Zarei, A.; Majidi, S.; Ghaderpoury, A.; Hashempour, Y.; Saghi, M.H.; Alinejad, A.; Yousefi, M.; Hosseingholizadeh, N.; Ghaderpoori, M. Carcinogenic and non-carcinogenic health risk assessment of heavy metals in drinking water of Khorramabad, Iran. MethodsX 2019, 6, 1642–1651. [Google Scholar] [CrossRef] [PubMed]
Wu, J.; Sun, Z. Evaluation of Shallow Groundwater Contamination and Associated Human Health Risk in an Alluvial Plain Impacted by Agricultural and Industrial Activities, Mid-west China. Expo. Health 2016, 8, 311–329. [Google Scholar] [CrossRef]
Wei, X.; Gao, B.; Wang, P.; Zhou, H.; Lu, J. Pollution characteristics and health risk assessment of heavy metals in street dusts from different functional areas in Beijing, China. Ecotoxicol. Environ. Saf. 2015, 112, 186–192. [Google Scholar] [CrossRef] [PubMed]
CalEPA, Office of Environmental Health Hazard Assessment (OEHHA) Acute, 8-hour and Chronic Reference Exposure Level (REL). Summary as of November. 2019. Available online: https://oehha.ca.gov/media/CPFs042909.pdf (accessed on 15 July 2023).
Hadzi, G.Y.; Essumang, D.K.; Adjei, J.K. Distribution and Risk Assessment of Heavy Metals in Surface Water from Pristine Environments and Major Mining Areas in Ghana. J. Health Pollut. 2015, 5, 86–99. [Google Scholar] [CrossRef]
USEPA. Risk Assessment Guidance for Superfund. Volume 1: Human Health Evaluation Manual (Part, E; Supplemental Guidance for Dermal Risk Assessment); EPA/540/R/99/Office of Superfund Remediation and Technology Innovation: Washington, DC, USA, 2004. [Google Scholar]
BBS (Bangladesh Bureau of Statistics). Health and Morbidity Status Survey; Bangladesh Bureau of Statistics, Statistics and Informatics Division, Ministry of Planning; Government of the People’s Republic of Bangladesh: Dhaka, Bangladesh, 2015. Available online: www.bbs.gov.bd (accessed on 10 June 2024).
Zakir, H.; Sharmin, S.; Akter, A.; Rahman, S. Assessment of health risk of heavy metals and water quality indices for irrigation and drinking suitability of waters: A case study of Jamalpur Sadar area, Bangladesh. Environ. Adv. 2020, 2, 100005. [Google Scholar] [CrossRef]
Brazil. Ministry of Health. Minister’s Office GM/MS n. 88. Available online: https://bvsms.saude.gov.br/bvs/saudelegis/gm/2021/prt0888_07_05_2021.htmlhtml (accessed on 10 June 2021).
European Comission (UE). Directive (UE) 2020/2184. Available online: https://eur-lex.europa.eu/PT/legal-content/summary/good-quality-water-in-europe-eu-water-directive.html (accessed on 15 June 2021).
American Public Health Association—APHA. Standard Methods for the Examination of Water and Wastewater, 23rd ed.; Estados Unidos: Washington, DC, USA, 2017. [Google Scholar]
Jain, C.K.; Singhal, D.C.; Sharma, M.K. Metal Pollution Assessment of Sediment and Water in the River Hindon, India. Environ. Monit. Assess. 2005, 105, 193–207. [Google Scholar] [CrossRef]
Rondeau, V.; Commenges, D.; Dartigues, J.F.; Gadda, H.J. Relation between aluminum concentrations in drinking water and Alzheimer’s disease: An 8-year follow-up study. Am. J. Epidemiol. 2000, 152, 59–66. [Google Scholar] [CrossRef]
Barabasz, W.; Albinska, D.; Jaskowska, M.; Lipiec, J. Ecotoxicology of Aluminium. Pol. J. Environ. Stud. 2002, 11, 199–203. [Google Scholar]
Kumar, V.; Pandita, S.; Sidhu, G.P.S.; Sharma, A.; Khanna, K.; Kaur, P.; Bali, A.S.; Setia, R. Copper bioavailability, uptake, toxicity and tolerance in plants: A comprehensive review. Chemosphere 2020, 262, 127810. [Google Scholar] [CrossRef]
Ejaz, H.; Copper, W.M.; Lang, W.W. Toxicity Links to Pathogenesis of Alzheimer’s Disease and Therapeutics Approaches. Int. J. Mol. Sci. 2021, 7660, 20. [Google Scholar]
Agency for Toxic Substances and Disease Registry—ATSDR. Toxicological Profile of Heavy Metals; Agency for Toxic Substances and Disease Registry—ATSDR: Atlanta, GA, USA, 2023. [Google Scholar]
Essien, J.P.; Ikpe, D.I.; Inam, E.D.; Okon, A.O.; Ebong, G.A.; Benson, N.U. Occurrence and spatial distribution of heavy metals in landfill leachates and impacted freshwater ecosystem: An environmental and human health threat. PLoS ONE 2022, 17, e0263279. [Google Scholar] [CrossRef] [PubMed]
Wang, F.; Song, K.; He, X.; Peng, Y.; Liu, D.; Liu, J. Identification of Groundwater Pollution Characteristics and Health Risk Assessment of a Landfill in a Low Permeability Area. Int. J. Environ. Res. Public Health 2021, 18, 7690. [Google Scholar] [CrossRef] [PubMed]
Przydatek, G.; Kanownik, W. Impact os small municipal solid waste landfill on groundwater quality. Environ. Monit. Assess. 2019, 191, 169. [Google Scholar] [CrossRef] [PubMed]
Njoku, P.O.; Edokpayi, J.N.; Odiyo, J.O. Health and environmental risks of residents living close to a landfill: A case study of Thohoyandou Landfill, Limpopo Province, South Africa. Int. J. Environ. Res. Public Health 2019, 16, 2125. [Google Scholar] [CrossRef] [PubMed]
de Queiroz, T.K.L.; Câmara, V.d.M.; Naka, K.S.; Mendes, L.d.C.d.S.; Chagas, B.R.; de Jesus, I.M.; Meyer, A.; Lima, M.d.O. Human Health Risk Assessment Is Associated with the Consumption of Metal-Contaminated Groundwater around the Marituba Landfill, Amazonia, Brazil. Int. J. Environ. Res. Public Health 2022, 19, 13865. [Google Scholar] [CrossRef] [PubMed]
Tchounwou, P.B.; Yedjou, C.G.; Patlolla, A.K.; Sutton, D.J. Heavy metal toxicity and the environment. Mol. Clin. Environ. Toxicol. 2012, 101, 133–164. [Google Scholar] [CrossRef]
Maya, S.; Prakash, T.; Madhu, K.D.; Goli, D. Multifaceted effects of aluminium in neurodegenerative diseases: A review. Biomed. Pharmacother. 2016, 83, 746–754. [Google Scholar] [CrossRef] [PubMed]
Srivastava, K.K.; Singh, S.R.; Ahmad, N.; Das, B.; Sharma, O.C.; Rathe, J.Á.; Bhat, S.K. Genetic divergence analysis of pear using qualitative traits as per DUS guidelines. Indian J. Hortic. 2012, 69, 432–434. [Google Scholar]
Mishra, S.; Kumar, A.; Yadav, S.; Singhal, M.K. Assessment of heavy metal contamination in water of Kali River using principle component and cluster analysis, India. Sustain. Water Resour. Manag. 2018, 4, 573. [Google Scholar] [CrossRef]

Figure 3. Graphic of risk index (HI) based on non-carcinogen results.

Figure 4. (a) Correlation of metals in the rainiest period; (b) correlation of metals in dry period.

Figure 5. Scatter matrix with the correlation of Al and Ba.

Table 1. The assigned weight and relative weight of each parameter used to determine the GWQI.

Parameters	Assigned Weight ( $w_{i}$ )	Weight Relative ( $W_{i}$ )	( $R_{f} D_{o r a l}$ ) [30]	( $R_{f} D_{d e r m a l}$ ) [30]	Cancer Slope Factor (CSF) Oral	Cancer Slope Factor (CSF) Dermal
pH	3	0.045	-	-	-	-
Temperature	3	0.045	-	-	-	-
Electric conductivity	3	0.045	-	-	-	-
As	5	0.075	3.0 × 10⁻⁴	1.2 × 10⁻⁴	1.5 × 10	3.6 × 10
Al	4	0.059	4.0 × 10⁻⁴	7.0 × 10⁻⁴	NE	NE
Ba	2	0.030	4.6 × 10⁻²	4.8 × 10⁻³	NE	NE
Co	2	0.030	2.0 × 10⁻²	1.6 × 10⁻²	9.8 × 10	9.8 × 10
Cd	5	0.075	1.0 × 10⁻³	1.0 × 10⁻⁵	5.0 × 10⁻¹	2.0 × 10¹
Cu	2	0.030	4.0 × 10⁻²	1.2 × 10⁻²	1.7 × 10⁻²	4.2 × 10¹
Cr	4	0.059	3.0 × 10⁻³	6.0 × 10⁻⁵	4.2 × 10⁻¹	20.0 × 10
Fe	4	0.059	8.4 × 10	7.0 × 10⁻²	NE	NE
Hg	5	0.075	3.0 × 10⁻⁴	2.1 × 10⁻⁵	NE	NE
Ni	5	0.075	2.0 × 10⁻²	5.4 × 10⁻³	9.1 × 10⁻¹	9.8 × 10
Pb	5	0.075	3.5 × 10⁻³	5.2 × 10⁻⁴	8.5 × 10⁻³	8.5 × 10⁻³
Sb	4	0.059	5.0 × 10⁻³	4.9 × 10⁻³	NE	NE
Se	4	0.059	5.0 × 10⁻³	2.0 × 10⁻²	NE	NE
U	5	0.075	5.4 × 10⁻³	7.0 × 10⁻⁵	NE	NE
Zn	2	0.030	3.0 × 10⁻³	6.0 × 10⁻²	NE	NE
	$\sum w_{i} = 67$	$\sum W_{i} = 1$

Note: NE: not established.

Table 3. GWQI results.

Index	Value in Period		Classification
Index	Rainfall	Drought	Classification
GWQI	13.729	14.766	GWQI ≥ 300 (Not drinkable) 200 ≤ GWQI < 300 (Too bad) 100 ≤ GWQI < 200 (Bad) 50 ≤ GWQI < 100 (Good) GWQI < 50 (Great)
HPI	6.180	7.176	HPI < 100 (Low level of contamination) HPI > 100 (High levels of contamination)
HEI	0.876	1.036	HEI > 20 (High contamination) 10 < HEI < 20 (Medium contamination) HEI < 10 (Low contamination)

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Share and Cite

MDPI and ACS Style

Soares, R.C.d.O.; de Deus, R.J.A.; Silva, M.M.C.; Faial, K.R.F.; Medeiros, A.C.; Mendes, R.d.A. Comprehensive Assessment of the Relationship between Metal Contamination Distribution and Human Health Risk: Case Study of Groundwater in Marituba Landfill, Pará, Brazil. Water 2024, 16, 2146. https://doi.org/10.3390/w16152146

AMA Style

Soares RCdO, de Deus RJA, Silva MMC, Faial KRF, Medeiros AC, Mendes RdA. Comprehensive Assessment of the Relationship between Metal Contamination Distribution and Human Health Risk: Case Study of Groundwater in Marituba Landfill, Pará, Brazil. Water. 2024; 16(15):2146. https://doi.org/10.3390/w16152146

Chicago/Turabian Style

Soares, Roberta C. de O., Ricardo Jorge A. de Deus, Monia M. C. Silva, Kleber Raimundo F. Faial, Adaelson C. Medeiros, and Rosivaldo de A. Mendes. 2024. "Comprehensive Assessment of the Relationship between Metal Contamination Distribution and Human Health Risk: Case Study of Groundwater in Marituba Landfill, Pará, Brazil" Water 16, no. 15: 2146. https://doi.org/10.3390/w16152146

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Menu