Arsenic Contamination of Drinking Water: A Study of the Exposure to Residents From the Passagem De Mariana, A Historical Gold Mining Town in the Quadrilátero Ferrifero, Brazil

Arsenic Contamination of Drinking Water: A Study of the Exposure to Residents From the Passagem De Mariana, A Historical Gold Mining Town in the Quadrilátero Ferrifero, Brazil | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Arsenic Contamination of Drinking Water: A Study of the Exposure to Residents From the Passagem De Mariana, A Historical Gold Mining Town in the Quadrilátero Ferrifero, Brazil Louise Aparecida Mendes, Jorge Carvalho de Lena, Adriana Trópia Abreu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4486749/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Human biomonitoring is one of the important tools for assessing exposure to toxic chemicals. A history of arsenic contamination via drinking water from gold mines in the Passagem district of Mariana, Brazil, is a way of incorporating this element into the body. This study aimed to evaluate water quality consumed by residents of Passagem de Mariana and to analyze biological samples, and investigate the magnitude of the exposure to arsenic. The results showed the presence of this trace element in higher concentrations than the maximum value permitted by the law. In two samples, concentrations were above 10 µg L − 1 , regardless of the season, for two years. As for biological samples, arsenic concentrations in hair samples (0.048 to 0.925 µg g − 1 ) were lower than the normal level (< 1µg g − 1 ). Arsenic was quantified in urine, both in individuals in the exposed (9.80 to 211 µg L − 1 ) and in the reference group (8.20 to 55.7 µg L − 1 ), whose content is capable of affecting a degree of medium and high toxicological risk (> 15 µg L − 1 ). This group was affected by other sources contributing to arsenic exposure, making it necessary to study other environmental matrices as well as foods. After confirming the exposure, continued biomonitoring was recommended since the adverse effects caused by arsenic can be manifested in the long term. human biomonitoring gold mining health risk trace element environmental contamination Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction In Latin America, 70% of the countries experience problems related to arsenic contamination (Teixeira et al., 2020 ). According to Bundschuh et al. ( 2012 ), the number of people consuming water, which exceeds the maximum limit of 10 µg L − 1 , is estimated at around 14 million, including Brazilians. Considering the risks associated with human exposure to arsenic, constant monitoring is necessary in areas with an incidence of this metalloid. Arsenic contamination in Brazil is not only due to mining activity, but this segment and metallurgical processes (smelting of non-ferrous metals) and energy production (burning of fossil fuels) are the main anthropogenic sources of air, water and soil contamination by this metalloid (Teixeira et al., 2020 ). The review manuscript by Teixeira et al. ( 2020 ), addresses the topic of arsenic contamination in Brazil, which has been a long-term environmental and health problem covering an extensive area of the country. The mining of gold, precious stones and other minerals contributed to the development and urbanization of a large part of the country (Teixeira et al., 2020 ). One of the most important states in Brazil in terms of mining activity is Minas Gerais, especially the area called Quadrilátero Ferrífero. For three centuries, the region has stood out as one of the most important regions of gold exploitation in Brazil (mining and rudimentary gold exploitation). The mineral assemblages present in these gold deposits are rich in trace elements (Silva et al., 2018 ), the majority of which have high toxic potential. Past and present gold mining activities are considered important sources of trace elements that contaminate drinking water and soils (Borba et al., 2000 ). In this context, the Quadrilátero Ferrífero can be viewed as a classic example of contamination by arsenic (Borba et al., 2000 ; Costa et al., 2006 ). It is worth mentioning that the study area positioned in the periclinal zone of the Mariana anticline (Fig. 1 ), which is a geological structure located in the southeastern portion of the Iron Quadrangle, is considered the area where the highest concentrations of arsenic occur in waters, soils and sediments (Borba et al., 2000 ; Costa et al., 2006 ; Costa et al., 2010 ). In the study area, the occurrence of gold is associated with sulfide minerals, especially arsenopyrite (FeAsS) that occurs in a disseminated form in veins embedded in schists of the Rio das Velhas Supergroup and itabirites of the Minas Supergroup. In the old mines, the sulfide minerals are exposed and subject to oxidation. This process slowly releases trace elements into soil, groundwater, and surface water. A study performed by Borba et al. ( 2004 ) revealed a high concentration of arsenic (2 980 mg L − 1 ) in water samples from the Passagem de Mariana gold mine, which exceeds 300 times the value stipulated by the Ministry of Health Ordinance and the WHO (World Health Organization). The aggravating factor is that the population of the district uses water from abandoned gold mines for domestic consumption without any quality monitoring. Arsenic is a potentially toxic element known to be distributed globally in the hydrosphere (Masuda, 2018 ). For this reason, there is a growing worldwide concern about drinking water quality. Surface and groundwater occurring in sulfide gold mining areas are arsenic sources, and the continuous exposure to this element, even in small concentrations, may seriously affect human organs (Smith et al., 2000 ; Bryan et al., 2007 ), especially when used for irrigation and cooking. For example, in Bangladesh, Rahman et al. ( 2009 ) reported high levels of arsenic in rice grains (maximum 557 µg kg − 1 ) collected from areas irrigated with groundwater contaminated with arsenic. Arsenic stands out as the most hazardous chemical element on the Priority List de Hazardous Substances of the Comprehensive Environmental Response, Compensation and Liability Act (ATSDR, 2022 ), and therefore, it is the subject of great concern about public health issues. Ingestion of inorganic arsenic over a long period of time can cause chronic poisoning, called arsenicosis. The effects that can take years to manifest, depending on the dose of exposure, including illnesses or diseases such as skin lesions, peripheral neuropathy, gastrointestinal symptoms, diabetes, cardiovascular diseases, cancer of the skin and internal organs (WHO, 2019 ; WHO, 2022 ). The initial symptoms of prolonged exposure to considerable levels of inorganic arsenic, mainly through water consumption, are generally observed on the skin (Fatmi et al., 2013 ; WHO, 2022 ), thus leading to changes in pigmentation, such as hyperpigmentation and hyperkeratosis in the palms of the hands and soles of the feet. These symptoms manifest themselves 5 years after minimal exposure and may be precursors to skin cancer (WHO, 2022 ). It is worth noting that arsenic is one of the few substances that have been proven to cause cancer in humans through water consumption (WHO, 2019 ; Baghery et al. 2023 ). Moreover, many studies as mentioned in the articles by Quansah et al. ( 2015 ) and Tolins et al. ( 2014 ) have hypothesized that arsenic is related to negative impacts during pregnancy and child health, affecting the development of children. Quansah et al. ( 2015 ) published a review article on the association of arsenic with adverse effects on pregnancy and infant mortality. Tolins et al. ( 2014 ) in their study came to the conclusion that arsenic is neurotoxic to human development, however, they emphasize that future studies must be carried out to gain a more precise understanding of this relationship between arsenic and cognitive development at the beginning of life. The influence of the environment on human health should be studied with the analysis of biological and geological samples. This practice is becoming an important tool for diagnosing the presence of trace elements in the human body. In general, investigations are performed by analyzing blood and urine samples. However, hair and nail samples can also be used to monitor a population exposed to trace elements by ingesting food or water (Sela et al., 2007 ; Rafiee et al., 2020 ; Agah, 2021 , Khan et al., 2022 ). In this context, this work aimed to evaluate the mine waters and the arsenic exposure degree of the population from Passagem de Mariana, whose occurrence comes from the local rock formations and the historical gold exploitation in the region. Arsenic was quantified in urine and hair samples of Passagem de Mariana residents. This was the first investigation into medical geology in the region and this information is of the utmost importance to take action in order to avoid such exposure. Since current studies highlight the danger of this element for human health, especially in relation to maternal and fetal complications. This study is also among the 17 Sustainable Development Goals (SDGs) established by the United Nations (UN), contributing to Health and Well-Being (goal 3) as well as Drinking Water and Sanitation (goal 6). 2. Experimental part Water sampling and analysis Water samples were collected from abandoned gold mines and water treatment plant (WTP) reservoirs. Table 1 presents the code, Universal Transverse Mercator (UTM) coordinates and the location of water sample collection. Part of the population at Passagem de Mariana, known as Vila São Vicente, receives water from the treatment plant and the other portion is supplied with water from mines that are exempt from treatment and quality monitoring. The WTP waters were sampled in order to compare the results with mine waters, since the samples from the treatment plants come from springs that are on quartzites, which generally have low concentrations of trace elements. The WTP waters are subjected to conventional treatment with the addition of calcium hypochlorite for disinfection during the dry period. During the rainy season, when turbidity increases, the water undergoes complete treatment with the addition of calcium hydroxide and aluminum sulfate to remove impurities. Table 1 Water sample code, UTM coordinates and description of the sampling location Water sample code UTM Coordinates Location description C1 662608/ 7743601 Elevation: 861m Water treatment plant: WTP south: Serrinha wellspring C2 662608/ 7743601 Elevation: 861 m Water treatment plant: WTP south: Belém wellspring CMRC3 661601/ 7744391 Elevation: 932 m Calvário Street, Passagem de Mariana (Note: mine: spring water is 30 km) CMRC4 661478/ 7744349 Elevation: 931 m Calvário Street, Passagem de Mariana (Note: mine: water; spring water) CD5 661240/ 7744353 Elevation: 945 m Water tank, Passagem de Mariana CMRE1 661389/ 7744308 Elevation: 918 m Residence: João Batista Street, Passagem de Mariana (Note: mine water) CMRE2 661377/ 7744283 Elevation: 910 m Residence: João Batista Street, Passagem de Mariana (Note: mine water) CM11 661805/ 7744080 Elevation: 836 m Caminho Novo Street, Passagem de Mariana, southern portion of the investigated area (Note: water from a mine that supplies the community). CM12 661964/ 7744094 Elevation: 841 m Caminho Novo Street, Passagem de Mariana, southern portion of the investigated area (Note: water from the mine that supplies the residence). FG13 662195/ 7744180 Elevation: 847m Fonte da Glória, Praça Nossa Senhora da Glória, Passagem de Mariana. CM15 662148/ 7744203 Elevation: 841m Residence: Praça Nossa Senhora da Glória, Passagem de Mariana (Note: mine water) Four water sample collection campaigns were performed, two of which in the rainy season (November 2010 and January 2011) and two in the dry season (April 2010 and August 2011). In total, 40 samples were collected at 10 sampling points (Fig. 1 ). At the collection site, the samples were filtered using a 0.45 µm cellulose acetate membrane (Millipore®) and ultrapure HNO 3 was added for conservation. The arsenic content in the samples was quantified by inductively coupled plasma mass spectrometry (ICP-MS, Perkin Elmer, ELAN DRC-e and ICP-MS Agilent, 7700x). The pH parameters, Eh, electrical conductivity, temperature, resistivity, total dissolved solids were measured in situ using the multiparameter field meter (Ultrameter Miron L. Company, model 6Psi). Dissolved oxygen was measured using an oximeter (HANNA Instruments, model HI9146). All these parameters were conducted with the aim of evaluating the physical-chemical aspects of the water. Sampling and preparation of urine samples In order to assess the possible exposure of the population at Passagem de Mariana to arsenic, biological materials were sampled in two distinct groups called the reference and the exposed groups. The reference group was made up of people who consume water from the water treatment plant, generally residents of Vila São Vicente. The group exposed was made up of people who lived in the west and southeast portion of Passagem de Mariana, who used water directly from the mines. The sampling was collected systematically, that is, for each set of three houses, only one was selected to be part of the sampling set. A total of 93 individuals from the region were selected and urine was collected in a 50 mL polyethylene bottle, always the first urine of the day. Each individual, in addition to signing the free consent form to participate in the research voluntarily, also filled out a questionnaire with basic information, such as: age, data on nutrition and health, living conditions and history of illnesses. The purpose of applying this questionnaire was to survey diseases that were possibly related to arsenic. The urine samples were subjected to constant agitation for 24 hours. A 2.5 mL aliquot was pipetted into Teflon bottles and 8.0 mL of HNO 3 65% suprapur (Merck), 2.0 mL of H 2 O 2 30% PA ACS ISO (Merck) were added and the digestion in an oven with microwave radiation (Milestone, Stard D). The heating program for digestion consisted of two stages, the first stage lasting 35 minutes until reaching 180 ºC and the second stage lasting at 180 ºC for 15 minutes. After digestion and complete cooling of the samples, dilution was carried out in a 25.00 mL volumetric flask, and finally, the arsenic concentration was analyzed using the ICP-MS technique (Agilent, 7700x). Due to the absence of certified reference material for urine samples, the method was validated by evaluating matrix effect, precision, accuracy, limit of detection (LOD) and limit of quantification (LOQ). Sampling and preparation of hair samples 34 hair samples were collected from residents of the Passagem de Mariana district, from the back of the neck, in the region just above the neck (a strand). This collection site is already standardized since it is less susceptible to external contamination, and also because there is almost always hair on this region in bald individuals (Pozebon et al., 1999 ). After collection, the hair was stored in plastic bags. Hair samples intended for analysis were washed to remove dust particles, sweat and grease using a methodology specified by the International Atomic Energy Agency (IAEA, 1980). The hair sample was wrapped in filter paper to dry at room temperature. Once dried, the sample was cut with porcelain scissors into short segments. Digestion of hair samples was performed on an electric plate. The solubilization of the hair sample was continued by weighing exactly (0.1000 ± 0.0001) g in Teflon bottles, adding 3.0 mL of HNO 3 65% suprapur (Merck) and 1.0 mL of H 2 O 2 30% PA ACS ISO (Merck). It remained in pre-digestion with the bottle closed for one day, and subsequently, the bottles were placed on an electric plate at 100 ºC. After cooling the bottle, ultrapure water was added to obtain a final 100-fold dilution of the hair sample. After the hair sample digestion procedure, the arsenic concentration was determined using the ICP-MS technique (Agilent, 7700x). Statistical analysis The data from each group (reference and exposed) were entered into a Normal Probability Chart - NPC (Chambers et al., 1983 ; Das and Rahmatullah-Imon, 2016 ) to verify the normality of the data and possible identification of outliers. The Kolmogorov-Smirnov normality test (e.g., Romeu, 2003 ; Das and Rahmatullah-Imon, 2016 ) was applied to the data. Then the F test was used to compare the variances of two groups, and finally, the means were compared using the Student test (Sanders and Smidt, 2000 ). For statistical analyses, samples with levels below the quantification limit of the arsenic determination technique were not considered. The aforementioned tests were conducted with a significance value of 0.05. All work was carried out with Minitab version 17. 3. Results and Discussion 3.1 Characterization of water samples The main results obtained for the water samples from the WTP and the mines are shown in Table 2 . The samples called C1 and C2, belonging to the water treatment plant, were collected in the pipelines, before chemical treatment. These samples presented low electrical conductivity and total dissolved solids compared to the other samples, showing that there is probably less solubilization of the rocks present in the wellspring that are on quartzites, where water is collected. As for arsenic concentration, both samples presented values below those stipulated by Consolidation Ordinance No. 5 of the Ministry of Health of 2017, hence showing that the WTP water is safe in relation to the element arsenic, which is the focus of this study. Obviously, this does not exempt the investigation of other parameters to certify the potability of the water samples. In general, the parameters evaluated for these two samples presented lower results than the mine samples, which was expected, given that the rock formation of the two studied locations has different compositions. The water samples from the western portion (CMRC4, CD5, CMRE1 and CMRE2) and the southeastern portion (CM11, CM12, FG13 and CM15) of Passagem de Mariana, are on a mineral deposit containing large amounts of arsenopyrite, either in quartz veins and carbonates or disseminated in banded iron formations, tourmalinite, phyllite and quartzite (Oliveira, 1998 ). The presence of arsenopyrite (FeAsS), arsenolite (As 2 O 3 ) and scorodite (Fe[AsO] 4 .2H 2 O) was proven in studies carried out by Borba (2003). As the samples in this work were collected close to the studied area by Borba (2003), it is believed that these are responsible for the availability of arsenic in the water samples. The electrical conductivity in most of these samples was higher in the rainy season (November 2010 and January 2011), which is probably related to the greater leaching of rocks during this period. A clear difference in the conductivity of the water samples between the western and southeastern portions is also observable (Table 2 ). Samples from the southeastern portion have higher conductivity, thus exhibiting lower pH values. It is known that at pH values below 7.0, metal oxides, hydroxides and salts tend to be solubilized, increasing their concentration and making them available to the environment. On the other hand, at pH values above 7.0, metallic cations tend to be precipitated as oxides, hydroxides, carbonates and sulfides (Bourg 1995 ), resulting in low mobility of the elements. Arsenic was found in water samples from mines in both the eastern and western portions in the concentration range of 0.21 to 44.0 µg L − 1 . Of these water samples, four (CMRC4, CMRE2, CM11 and CM12) showed arsenic concentrations that exceed the maximum permitted value (MPV) of 10.0 µg L − 1 , established by ordinance No. 5 of the Ministry of Health, in at least one of the four campaigns (Fig. 2 ). Two samples (CMRE2 and CM11) showed arsenic levels higher than the MPV in the four campaigns (Fig. 2 ). It is worth mentioning that on the map in Fig. 1 , the four samples that exceeded the MPV are colored red, in order to spatialize the contamination observed and facilitate the understanding of the local community and public authorities. Table 2 : Arsenic concentration and physical-chemical parameters of water samples collected in Passagem de Mariana The CMRC4 water sample, coming from a spring, exceeded the MPV only in the August 2011 sampling, which is a dry period. The arsenic concentration in this sample was 22.4 µg L − 1 . During this period, the sample was unfit for consumption, as a single parameter outside the norm already demonstrated that it does not have safe levels for ingestion. This spring supplies most of the homes on Calvário Street, which is approximately 700 meters long. The CMRE2 sample, also from the western portion, presented an arsenic concentration (23.8–37.9 µg L − 1 ) higher than the MPV in all collection campaigns. The mine from which this sample was taken is located in the backyard of a residence on João Batista Street, where there are old galleries of gold mines mainly supplying the residence in question and some houses in the surrounding area. The sample from the CMRE1 mine, which is also located in this residence, showed an arsenic concentration lower than the MPV. This can be explained by the difference in lithology between the two mines. Samples from the mines in the southeastern portion of Passagem de Mariana, CM11 and CM12, were also collected in an old gold mine gallery in a residence located on Caminho Novo Street. The water from the CM11 mine supplies the surrounding community and the water from the CM12 mine supplies the residence where the collection was made. The two samples presented arsenic concentrations ranging from 14.8 to 44.0 µg L − 1 , which were higher than the MPV in all samplings, except in the campaign carried out in January 2011 for sample CM12, whose concentration was 8.32 µg L − 1 . According to Gonçalves et al. (2011), the release of arsenic into the water is due to the presence of this element in weathered, oxidized covers, in mineralized rocks and enriched with sulfide minerals found on the surface and in the walls of abandoned mine galleries, represented mainly by the minerals arsenopyrite, pyrite and pyrrhotite. Weathering processes promote the oxidation of the sulfides present, depositing secondary arsenic minerals on the roofs (Borba et al., 2000 ). During the dry period, there is an accumulation of these minerals and during the rainy period these minerals are solubilized and leached into the environment, which may explain the presence of arsenic in some water samples evaluated. Among the mine waters evaluated, CMRE2, CM11 and CM12 are the most worrying, due to the arsenic concentration exceeding the value of 10 µg L − 1 , which is the maximum content allowed by Consolidation Ordinance nº 5 of the Ministry of Health. The evaluation of these waters occurred for two consecutive years, showing that the presence of this element is still a reality and that monitoring of the waters in this district must be continued. In these three samples, contamination appeared to be natural and timeless. It should be noted that the repetitive ingestion of water contaminated by arsenic in significant concentrations, as in this case, can cause a series of health problems, due to its cumulative effect on the human body. Therefore, there is a need to further evaluate the compromised health of the population at the Passagem de Mariana, carrying out analyzes of biological samples to try to explain the cause-effect of disease manifestations in the studied location, which is a work of great importance in terms of environmental, geochemical and public health aspects. 3.2 Analysis of biological samples The arsenic concentrations obtained for urine samples from residents of the Passagem de Mariana (called the exposed group) and Vila São Vicente (called the reference group) are presented in Table 3 . Table 3 Arsenic concentration in urine samples Exposed group Sample Arsenic concentration (µg L − 1 ) Sample Arsenic concentration (µg L − 1 ) Sample Arsenic concentration (µg L − 1 ) Sample Arsenic concentration (µg L − 1 ) U2 22,7 U28 < 6,95 U51 < 6,95 U73 < 6,95 U10 31,8 U32 29,8 U52 < 6,95 U74 < 6,95 U11 38,6 U33 33,0 U53 < 6,95 U75 < 6,95 U12 46,7 U35 < 6,95 U54 < 6,95 U76 < 6,95 U13 22,8 U36 < 6,95 U55 < 6,95 U79 < 6,95 U14 < 6,95 U37 15,2 U59 < 6,95 U83 27,3 U15 28,6 U39 22,4 U61 102 U84 < 6,95 U17 27,1 U40 39,3 U62 9,80 U87 10,2 U19 < 6,95 U42 16,6 U63 < 6,95 U91 25,0 U20 < 6,95 U43 < 6,95 U64 < 6,95 U92 27,2 U21 10,5 U45 < 6,95 U65 < 6,95 U93 < 6,95 U22 12,7 U46 < 6,95 U66 11,5 U94 30,8 U23 106 U47 11,3 U68 < 6,95 U95 < 6,95 U24 211 U48 < 6,95 U69 16,3 U97 < 6,95 U25 22,7 U49 23,0 U70 < 6,95 U100 44,3 U26 36,1 U50 10,3 U72 < 6,95 Reference group Sample Arsenic concentration (µg L − 1 ) Sample Arsenic concentration (µg L − 1 ) Sample Arsenic concentration (µg L − 1 ) Sample Arsenic concentration (µg L − 1 ) U5 < 6,95 U71 17,6 U99 17,0 U117 10,0 U6 46,6 U77 < 6,95 U103 < 6,95 U119 26,6 U9 10,0 U78 8,20 U105 < 6,95 U122 < 6,95 U18 12,5 U88 < 6,95 U106 55,7 U124 < 6,95 U34 19,3 U89 < 6,95 U108 36,3 U125 15,9 U44 12,1 U90 < 6,95 U110 11,4 U57 10,7 U98 < 6,95 U114 < 6,95 The concentration of arsenic in urine samples from residents of Passagem de Mariana, related to the exposed group, ranged from 9.80 to 211 µg L − 1 . For the reference group it ranged from 8.20 to 55.7 µg L − 1 . In order to assess the toxicological risks of the groups studied, the classification proposed by Matschullat et al. ( 2000 ) was adopted, as shown in Table 4 . Table 4 Classification proposed by Matschullat et al. ( 2000 ) for arsenic concentration in urine Class Concentration (µg L − 1 ) Risk Action I Less than 15 Low toxicological risk No action. II Between 15 and 40 Medium toxicological risk It is recommended that individuals be evaluated and monitored within this range. III Greater than 40 High toxicological risk It is considered a health risk and requires immediate investigation and monitoring of the contamination in each individual. Based on the results obtained, it was already expected that the reference group would present lower arsenic concentrations in urine than the exposed group. Furthermore, according to the classification proposed by Matschullat et al. ( 2000 ), the expectation was that arsenic concentrations would be lower than 15 µg L − 1 , considering that this group had low or no exposure to arsenic. However, the results show that the reference group also suffers from exposure to arsenic, with the possibility of medium and high toxicological risk. This suggests that water is not the only route of arsenic contamination in the studied region. Figure 3 shows the distribution of urine samples, with their respective arsenic concentrations and the limits suggested by Matschullat et al. ( 2000 ). In seven samples, named U6, U12, U23, U24, U61, 100 and U106, the arsenic concentration exceeded 40.0 µg L − 1 , the maximum value for environmental exposure to arsenic according to Matschullat et al. ( 2000 ). Five of the samples were from the exposed group and two were from the reference group. Samples that present arsenic levels above this base value need to be monitored, as there is a high risk of adverse health effects. In total, 31% of the samples evaluated from the reference group showed arsenic concentrations in the medium and high toxicological risk ranges. Regarding this result, other means of exposure must be investigated, such as: dust, soil, vegetables, eggs and chicken meat, etc. For the exposed group, approximately 40% of the samples presented arsenic concentrations in the medium and high toxicological risk ranges. As already mentioned, of 63 samples, five presented concentrations above 40 µg L − 1 , with three samples from the exposed group standing out for their high concentration of arsenic in relation to the other samples, whose determined levels were 102, 106 and 211 µg L − 1 . These values were 2.6; 2.7; 5.3 times above the base value of the classification proposed by Matschullat et al. ( 2000 ), respectively. In order to better discuss the data, all participants answered a questionnaire about eating habits, living conditions and the occurrence of diseases. This information was used to associate the results found with the incidence of diseases caused by the presence of arsenic in the human body. Although it cannot be inferred that the diseases that are being manifested in the population are caused exclusively by the presence of arsenic in the body, the hypothesis that this element can be a precursor or enhance adverse effects should not be ignored. Table 5 presents the main information obtained for these individuals according to the questionnaire they answered. Table 5 Information obtained from the questionnaire answered by participants classified in Class III (Matschullat et al., 2000 ) Sample Life stage Group type Questionnaire Information U6 Child Reference He had no health problems, according to the questionnaire answered by his guardian. This individual also does not consume chicken products and vegetables grown at home. U12 Adult Exposed He admitted to having hypertension. The questionnaire also states that he consumes eggs and meat from chickens raised at his home. U23 Child Exposed He had no health problems, according to the questionnaire answered by his guardian. They do not consume farmed products and vegetables grown in their homes. U24 Adult Exposed He stated that he had no health problems. They do not consume farmed products and vegetables grown in their homes. U61 Adult Exposed He stated that he had no health problems. They do not consume farmed products and vegetables grown in their homes. U100 Adult Exposed He has no health problems. He eats vegetables grown at home. U106 Adult Reference He declared that he had hypertension. According to the information in the questionnaire, this donor is a smoker and consumes eggs and meat from chickens raised in his backyard. Taking into account those who do not consume livestock products and vegetables in their homes and who are classified in Class III (Matschullat et al., 2000 ), inhalation, ingestion and dermal contact with dust are common routes, through which arsenic can penetrate the human body (Madany et al., 1987 ; Lewis et al., 1999 ; Johnson-Restrepo and Kannan, 2009 ), especially in children, due to hand-to-mouth contact, common behavior of crawling, touching and licking toys (Mercier et al., 2011; Raffy et al., 2018 ; Cao et al., 2020 ; Hejami et al., 2020 ). Some authors (Huang et al., 2007 , Rahman et al., 1999 , Tsai et al., 1999 ) suggest that there is an association between the development of arterial hypertension and heart disease with chronic arsenic intake. It is also known that arsenic accumulates in the skin, therefore causing various lesions such as hyperpigmentation and hyperkeratosis to appear, and yet another disease associated with arsenic is diabetes mellitus, according to Tseng et al. ( 2000 ). Table 6 presents the main diseases declared by the participants. It is clear that it is not possible to say that these illnesses are caused by exposure to arsenic, but the probability that the symptoms were intensified by the ingestion of this trace element cannot be ignored. Table 6 Diseases declared by participants Disease Number of cases Number of individuals classified as medium and high risk Arterial hypertension 15 individuals 5 Skin spots 9 individuals 1 Diabetes Mellitus 6 individuals 2 Urine sampling from the population of Passagem de Mariana and determinations of its total arsenic content allowed the assessment of the extent of contamination of the population of that district. Figure 4 presents the NPCs for both groups (A - reference, B - exposed). They highlight the samples considered outliers for each group. From the reference group (A), samples U6 (46.6 mg L − 1 ), U106 (55.7 mg L − 1 ) and U108 (36.3 mg L − 1 ) were disregarded for further analysis. For the exposed group (B), samples U23 (106.0 mg L − 1 ), U24 (211.0 mg L − 1 ) and U61 (102.0 mg L − 1 ) were disregarded. The normality test with the remaining samples showed that the data did not differ significantly from those of a normal distribution - group A (KS 0.216, p-value 0.122) and group B (KS 0.112, p-value 0.822). For these same groups, the mean and standard deviation were calculated - group A (14.28, 5.2, n = 12) and group B (24.26; 10.7, n = 29). The F test for comparing variances led to a p-value of 0.016 (F = 4.18), which means that the variances (and standard deviations) of the two groups differ significantly. This information was used in the subsequent Student test. Thus, the test comparing the means of the two groups led to t = 4.00, which corresponds to a p-value of 0.000 (or very close to zero). This procedure revealed that the means of the two groups differ significantly, leading us to the conclusion that the levels of the exposed group (average 24.26 mg L − 1 ) are higher than those of the control group (14.28 mg L − 1 ). In comparison with studies obtained in the literature, it is observed that the concentration of arsenic is more prominent in urine samples from the population of Passagem de Mariana in relation to other locations. In the study carried out by Matos et al. ( 2022 ), whose objective was to carry out the study of human biomonitoring in blood, serum and urine samples in individuals residing in regions affected by the environmental disaster of the Fundão dam collapse, the average concentration of arsenic in urine in the control group was of 6.87 µg L − 1 and in the exposed group it was 6.38 µg L − 1 . The difference in average concentration between this research and the aforementioned work can be justified by the fact that the region studied by Matos et al. ( 2022 ) does not have a lithology that shows the presence of mines that contain arsenic, as clearly seen in Passagem de Mariana. Vormitagg et al. (2021) investigated the concentration of potentially toxic chemical elements in urine and blood samples from residents of the district of Barra Longa, Brazil, a place also affected by the Fundão dam collapse disaster in 2015. The concentration of arsenic in urine ranged from 12 .3 to 54.2 µg L − 1 g, whose content is comparable to the present study. This result of arsenic in the samples analyzed by Vormitagg et al. (2021) can be explained by the exposure of the population to suspended dust derived from dried mud and reconstruction works implemented in Barra Longa. The presence of this chemical element in the mud may come from contamination of the Carmo and Gualaxo do Norte rivers (which are located in the aforementioned district), which was already recorded prior to the dam collapse (Eleutério, 1997 ; Costa et al., 2010 ). It is worth mentioning that the study area is located at the headwaters of the Carmo river, being one of the main source areas for elements such as arsenic (Costa et al., 2010 ). Probably, the material deposited at the bottom of the rivers was disturbed and dragged along with the mud. The results of Arsenic content in hair samples are presented in Table 7 . Table 7 Arsenic concentration in hair samples Sample Arsenic concentration (µg g − 1 ) Sample Arsenic concentration (µg g − 1 ) Sample Arsenic concentration (µg g − 1 ) C2 0,330 C16 0,079 C25 0,095 C3 0,368 C17 0,075 C26 0,297 C4 0,206 C19 0,064 C27 0,232 C5 0,513 C18 0,048 C28 0,166 C8 0,209 C21 0,330 C30 0,113 C13 0,137 C22 0,202 C35 0,925 C14 < 0,174 a C23 0,112 C15 0,168 C24 0,080 Sample Arsenic concentration (µg g − 1 ) Sample Arsenic concentration (µg g − 1 ) Sample Arsenic concentration (µg g − 1 ) C1 0,110 C10 0,080 C29 0,067 C6 0,118 C11 0,161 C32 0,328 C7 0,074 C12 0,070 C33 0,118 C9 0,066 C20 0,110 C34 0,062 a Note: Concentrations in µg L − 1 , disregarding the dilution factor In these samples, the arsenic concentration varied from 0.048 to 0.925 µg g − 1 , with the levels in the reference group ranging from 0.066 to 0.328 µg g − 1 and in the exposed group there was a variation from 0.048 to 0.925 µg g − 1 . It is observed that the arsenic concentration range in the exposed group is wider in relation to the reference group. According to the ToxGuideTM for Arsenic (ATSDR, 2007), the concentration of this trace element considered normal in human hair must be less than 1 µg g − 1 . It was observed that the hair samples collected in the district of Passagem de Mariana presented lower concentrations in relation to the content considered acceptable. However, it cannot be guaranteed that the concentration of arsenic found in the hair samples is not causing or will cause toxicological effects in the individuals investigated. Since arsenic can bioaccumulate in the body through long-term exposure to small amounts of this element, first causing skin lesions, such as hyperkeratosis and hyperpigmentation, and later more serious diseases such as skin and lung cancer (inhalation), prostate, bladder, kidney and liver (WHO, 2001 ). Conclusion The data corroborate the hypothesis of this work that historical gold exploration activities in the investigated area contributed to the occurrence of arsenic contamination in water sources. It is evident that the leaching process of sulfide minerals, such as arsenopyrite, made this trace element available to the environmental compartments, thus demonstrating that the hypothesis of resident exposure to arsenic is presumable. The comparison of data from biological samples between the exposed and reference groups studied was important for this work, revealing that there is a difference between the degree of exposure between the two groups studied. However, it was possible to observe that water is not the only route of contact between the chemical element studied with the population, since the reference group also contained arsenic concentrations of the urine in the medium and high toxicological risk ranges. In this case, it is recommended to study other matrices such as dust, soil, vegetables, eggs and chicken meat to evaluate other routes of contamination. Arsenic concentrations in hair samples were lower than the level considered normal by the Agency for Toxic Substances and Disease Registry. It is believed that there was no accumulation of this element in this matrix within a period of 2 to 5 months, which is the time for the concentrations to be detected. However, it cannot yet be said that the arsenic content found in hair samples from residents of this region will not cause harm to health in the long term. With the results obtained in this research, it is recommended that residents of the region be rigorously evaluated and monitored, as arsenic contamination has been confirmed. Declarations Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author Contributions Louise A. Mendes: Experimental part, data processing and writing of the manuscript. Jorge Carvalho de Lena: Statistical analysis and discussion of results. Adriana Trópia de Abreu: Experimental part, method validation and sample analysis. Liliane Catone Soares: Discussion of results and writing of the manuscript. Emanueli do Nascimento da Silva: Discussion of results and writing of the manuscript. Roberta Eliane Santos Froes-Silva: Experimental part and method validation. Helena Eugênia Leonhardt Palmieri: Experimental part and sample analysis. Adivane Terezinha Costa: mentor of the work, discussion of results and data from environmental geochemistry and medical geology. Ethics approval This study was approved by the Ethics Committee of the Universidade Federal de Ouro Preto, by Official CEP No. 111/2010, dated October 15, 2010. (CAAE: 0024.0.238.000-10). 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Environmental Health Criteria 224: arsenic and arsenic compounds . http://www.inchem.org/documents/ehc/ehc/ehc224.htm . Acesso em 09/05/2024. WHO. (2019). Preventing disease through healthy environments exposure to arsenic: A major public health concern . https://www.who.int/publications/i/item/WHO-CED-PHE-EPE-19.4.1 . Acesso em 20/02/2024. WHO. (2022). Arsenic . https://www.who.int/news-room/fact-sheets/detail/arsenic . Acesso em 20/02/2024. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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19:14:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":25630,"visible":true,"origin":"","legend":"\u003cp\u003eArsenic concentration in water samples collected in Passagem de Mariana and the maximum permitted value (MPV) by ordinance No. 5 of the Ministry of Health\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4486749/v1/492a217fdc8eda3aff3a2f4e.png"},{"id":58229178,"identity":"c221c3b5-40c5-47ad-9b64-6f022a09f34e","added_by":"auto","created_at":"2024-06-12 19:14:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":19011,"visible":true,"origin":"","legend":"\u003cp\u003eSamples, arsenic concentrations in urine and limits proposed by Matschullat et al. (2000)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4486749/v1/b6a6d1fa77d844e2a709d346.png"},{"id":58229181,"identity":"e76379c7-a85e-41b8-b8b2-417a8f5d9d00","added_by":"auto","created_at":"2024-06-12 19:14:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":19011,"visible":true,"origin":"","legend":"\u003cp\u003eNPC diagrams for samples from the control group (A) and the exposed group (B). The figure shows the samples considered outliers that were removed from subsequent calculations\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4486749/v1/3429a0b4330b8ea7703e30bf.png"},{"id":58231716,"identity":"9a68e0fd-b0c9-47cc-bd0e-763eff04a708","added_by":"auto","created_at":"2024-06-12 19:30:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1118323,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4486749/v1/03de1b96-f509-4277-b5d7-6872a5e7a9bb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eArsenic Contamination of Drinking Water: A Study of the Exposure to Residents From the Passagem De Mariana, A Historical Gold Mining Town in the Quadrilátero Ferrifero, Brazil\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn Latin America, 70% of the countries experience problems related to arsenic contamination (Teixeira et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to Bundschuh et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), the number of people consuming water, which exceeds the maximum limit of 10 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, is estimated at around 14\u0026nbsp;million, including Brazilians. Considering the risks associated with human exposure to arsenic, constant monitoring is necessary in areas with an incidence of this metalloid.\u003c/p\u003e \u003cp\u003eArsenic contamination in Brazil is not only due to mining activity, but this segment and metallurgical processes (smelting of non-ferrous metals) and energy production (burning of fossil fuels) are the main anthropogenic sources of air, water and soil contamination by this metalloid (Teixeira et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The review manuscript by Teixeira et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), addresses the topic of arsenic contamination in Brazil, which has been a long-term environmental and health problem covering an extensive area of the country.\u003c/p\u003e \u003cp\u003eThe mining of gold, precious stones and other minerals contributed to the development and urbanization of a large part of the country (Teixeira et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). One of the most important states in Brazil in terms of mining activity is Minas Gerais, especially the area called Quadril\u0026aacute;tero Ferr\u0026iacute;fero. For three centuries, the region has stood out as one of the most important regions of gold exploitation in Brazil (mining and rudimentary gold exploitation). The mineral assemblages present in these gold deposits are rich in trace elements (Silva et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), the majority of which have high toxic potential. Past and present gold mining activities are considered important sources of trace elements that contaminate drinking water and soils (Borba et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In this context, the Quadril\u0026aacute;tero Ferr\u0026iacute;fero can be viewed as a classic example of contamination by arsenic (Borba et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Costa et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). It is worth mentioning that the study area positioned in the periclinal zone of the Mariana anticline (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), which is a geological structure located in the southeastern portion of the Iron Quadrangle, is considered the area where the highest concentrations of arsenic occur in waters, soils and sediments (Borba et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Costa et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Costa et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the study area, the occurrence of gold is associated with sulfide minerals, especially arsenopyrite (FeAsS) that occurs in a disseminated form in veins embedded in schists of the Rio das Velhas Supergroup and itabirites of the Minas Supergroup. In the old mines, the sulfide minerals are exposed and subject to oxidation. This process slowly releases trace elements into soil, groundwater, and surface water. A study performed by Borba et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) revealed a high concentration of arsenic (2 980 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) in water samples from the Passagem de Mariana gold mine, which exceeds 300 times the value stipulated by the Ministry of Health Ordinance and the WHO (World Health Organization). The aggravating factor is that the population of the district uses water from abandoned gold mines for domestic consumption without any quality monitoring.\u003c/p\u003e \u003cp\u003eArsenic is a potentially toxic element known to be distributed globally in the hydrosphere (Masuda, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). For this reason, there is a growing worldwide concern about drinking water quality. Surface and groundwater occurring in sulfide gold mining areas are arsenic sources, and the continuous exposure to this element, even in small concentrations, may seriously affect human organs (Smith et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Bryan et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), especially when used for irrigation and cooking. For example, in Bangladesh, Rahman et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) reported high levels of arsenic in rice grains (maximum 557 \u0026micro;g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) collected from areas irrigated with groundwater contaminated with arsenic.\u003c/p\u003e \u003cp\u003eArsenic stands out as the most hazardous chemical element on the Priority List de Hazardous Substances of the Comprehensive Environmental Response, Compensation and Liability Act (ATSDR, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and therefore, it is the subject of great concern about public health issues. Ingestion of inorganic arsenic over a long period of time can cause chronic poisoning, called arsenicosis. The effects that can take years to manifest, depending on the dose of exposure, including illnesses or diseases such as skin lesions, peripheral neuropathy, gastrointestinal symptoms, diabetes, cardiovascular diseases, cancer of the skin and internal organs (WHO, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; WHO, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The initial symptoms of prolonged exposure to considerable levels of inorganic arsenic, mainly through water consumption, are generally observed on the skin (Fatmi et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; WHO, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), thus leading to changes in pigmentation, such as hyperpigmentation and hyperkeratosis in the palms of the hands and soles of the feet. These symptoms manifest themselves 5 years after minimal exposure and may be precursors to skin cancer (WHO, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It is worth noting that arsenic is one of the few substances that have been proven to cause cancer in humans through water consumption (WHO, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Baghery et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMoreover, many studies as mentioned in the articles by Quansah et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and Tolins et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) have hypothesized that arsenic is related to negative impacts during pregnancy and child health, affecting the development of children. Quansah et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) published a review article on the association of arsenic with adverse effects on pregnancy and infant mortality. Tolins et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) in their study came to the conclusion that arsenic is neurotoxic to human development, however, they emphasize that future studies must be carried out to gain a more precise understanding of this relationship between arsenic and cognitive development at the beginning of life.\u003c/p\u003e \u003cp\u003eThe influence of the environment on human health should be studied with the analysis of biological and geological samples. This practice is becoming an important tool for diagnosing the presence of trace elements in the human body. In general, investigations are performed by analyzing blood and urine samples. However, hair and nail samples can also be used to monitor a population exposed to trace elements by ingesting food or water (Sela et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Rafiee et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Agah, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Khan et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this context, this work aimed to evaluate the mine waters and the arsenic exposure degree of the population from Passagem de Mariana, whose occurrence comes from the local rock formations and the historical gold exploitation in the region. Arsenic was quantified in urine and hair samples of Passagem de Mariana residents. This was the first investigation into medical geology in the region and this information is of the utmost importance to take action in order to avoid such exposure. Since current studies highlight the danger of this element for human health, especially in relation to maternal and fetal complications. This study is also among the 17 Sustainable Development Goals (SDGs) established by the United Nations (UN), contributing to Health and Well-Being (goal 3) as well as Drinking Water and Sanitation (goal 6).\u003c/p\u003e"},{"header":"2. Experimental part","content":"\u003cp\u003e \u003cem\u003eWater sampling and analysis\u003c/em\u003e \u003c/p\u003e \u003cp\u003eWater samples were collected from abandoned gold mines and water treatment plant (WTP) reservoirs. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the code, Universal Transverse Mercator (UTM) coordinates and the location of water sample collection. Part of the population at Passagem de Mariana, known as Vila S\u0026atilde;o Vicente, receives water from the treatment plant and the other portion is supplied with water from mines that are exempt from treatment and quality monitoring. The WTP waters were sampled in order to compare the results with mine waters, since the samples from the treatment plants come from springs that are on quartzites, which generally have low concentrations of trace elements. The WTP waters are subjected to conventional treatment with the addition of calcium hypochlorite for disinfection during the dry period. During the rainy season, when turbidity increases, the water undergoes complete treatment with the addition of calcium hydroxide and aluminum sulfate to remove impurities.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWater sample code, UTM coordinates and description of the sampling location\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater sample code\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUTM Coordinates\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLocation description\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e662608/ 7743601 Elevation: 861m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWater treatment plant: WTP south: Serrinha wellspring\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e662608/ 7743601 Elevation: 861 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWater treatment plant: WTP south: Bel\u0026eacute;m wellspring\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMRC3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661601/ 7744391 Elevation: 932 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalv\u0026aacute;rio Street, Passagem de Mariana (Note: mine: spring water is 30 km)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMRC4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661478/ 7744349 Elevation: 931 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalv\u0026aacute;rio Street, Passagem de Mariana (Note: mine: water; spring water)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661240/ 7744353 Elevation: 945 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWater tank, Passagem de Mariana\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMRE1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661389/ 7744308 Elevation: 918 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResidence: Jo\u0026atilde;o Batista Street, Passagem de Mariana (Note: mine water)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMRE2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661377/ 7744283 Elevation: 910 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResidence: Jo\u0026atilde;o Batista Street, Passagem de Mariana (Note: mine water)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCM11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661805/ 7744080 Elevation: 836 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCaminho Novo Street, Passagem de Mariana, southern portion of the investigated area (Note: water from a mine that supplies the community).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCM12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661964/ 7744094 Elevation: 841 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCaminho Novo Street, Passagem de Mariana, southern portion of the investigated area (Note: water from the mine that supplies the residence).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFG13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e662195/ 7744180 Elevation: 847m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFonte da Gl\u0026oacute;ria, Pra\u0026ccedil;a Nossa Senhora da Gl\u0026oacute;ria, Passagem de Mariana.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCM15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e662148/ 7744203 Elevation: 841m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResidence: Pra\u0026ccedil;a Nossa Senhora da Gl\u0026oacute;ria, Passagem de Mariana (Note: mine water)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFour water sample collection campaigns were performed, two of which in the rainy season (November 2010 and January 2011) and two in the dry season (April 2010 and August 2011). In total, 40 samples were collected at 10 sampling points (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). At the collection site, the samples were filtered using a 0.45 \u0026micro;m cellulose acetate membrane (Millipore\u0026reg;) and ultrapure HNO\u003csub\u003e3\u003c/sub\u003e was added for conservation. The arsenic content in the samples was quantified by inductively coupled plasma mass spectrometry (ICP-MS, Perkin Elmer, ELAN DRC-e and ICP-MS Agilent, 7700x).\u003c/p\u003e \u003cp\u003eThe pH parameters, Eh, electrical conductivity, temperature, resistivity, total dissolved solids were measured in situ using the multiparameter field meter (Ultrameter Miron L. Company, model 6Psi). Dissolved oxygen was measured using an oximeter (HANNA Instruments, model HI9146). All these parameters were conducted with the aim of evaluating the physical-chemical aspects of the water.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eSampling and preparation of urine samples\u003c/em\u003e \u003c/p\u003e \u003cp\u003eIn order to assess the possible exposure of the population at Passagem de Mariana to arsenic, biological materials were sampled in two distinct groups called the reference and the exposed groups. The reference group was made up of people who consume water from the water treatment plant, generally residents of Vila S\u0026atilde;o Vicente. The group exposed was made up of people who lived in the west and southeast portion of Passagem de Mariana, who used water directly from the mines.\u003c/p\u003e \u003cp\u003eThe sampling was collected systematically, that is, for each set of three houses, only one was selected to be part of the sampling set. A total of 93 individuals from the region were selected and urine was collected in a 50 mL polyethylene bottle, always the first urine of the day. Each individual, in addition to signing the free consent form to participate in the research voluntarily, also filled out a questionnaire with basic information, such as: age, data on nutrition and health, living conditions and history of illnesses. The purpose of applying this questionnaire was to survey diseases that were possibly related to arsenic.\u003c/p\u003e \u003cp\u003eThe urine samples were subjected to constant agitation for 24 hours. A 2.5 mL aliquot was pipetted into Teflon bottles and 8.0 mL of HNO\u003csub\u003e3\u003c/sub\u003e 65% suprapur (Merck), 2.0 mL of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e 30% PA ACS ISO (Merck) were added and the digestion in an oven with microwave radiation (Milestone, Stard D). The heating program for digestion consisted of two stages, the first stage lasting 35 minutes until reaching 180 \u0026ordm;C and the second stage lasting at 180 \u0026ordm;C for 15 minutes. After digestion and complete cooling of the samples, dilution was carried out in a 25.00 mL volumetric flask, and finally, the arsenic concentration was analyzed using the ICP-MS technique (Agilent, 7700x). Due to the absence of certified reference material for urine samples, the method was validated by evaluating matrix effect, precision, accuracy, limit of detection (LOD) and limit of quantification (LOQ).\u003c/p\u003e \u003cp\u003e \u003cem\u003eSampling and preparation of hair samples\u003c/em\u003e \u003c/p\u003e \u003cp\u003e34 hair samples were collected from residents of the Passagem de Mariana district, from the back of the neck, in the region just above the neck (a strand). This collection site is already standardized since it is less susceptible to external contamination, and also because there is almost always hair on this region in bald individuals (Pozebon et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter collection, the hair was stored in plastic bags. Hair samples intended for analysis were washed to remove dust particles, sweat and grease using a methodology specified by the International Atomic Energy Agency (IAEA, 1980). The hair sample was wrapped in filter paper to dry at room temperature. Once dried, the sample was cut with porcelain scissors into short segments.\u003c/p\u003e \u003cp\u003eDigestion of hair samples was performed on an electric plate. The solubilization of the hair sample was continued by weighing exactly (0.1000\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001) g in Teflon bottles, adding 3.0 mL of HNO\u003csub\u003e3\u003c/sub\u003e 65% suprapur (Merck) and 1.0 mL of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e 30% PA ACS ISO (Merck). It remained in pre-digestion with the bottle closed for one day, and subsequently, the bottles were placed on an electric plate at 100 \u0026ordm;C. After cooling the bottle, ultrapure water was added to obtain a final 100-fold dilution of the hair sample. After the hair sample digestion procedure, the arsenic concentration was determined using the ICP-MS technique (Agilent, 7700x).\u003c/p\u003e \u003cp\u003e \u003cem\u003eStatistical analysis\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe data from each group (reference and exposed) were entered into a Normal Probability Chart - NPC (Chambers et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Das and Rahmatullah-Imon, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) to verify the normality of the data and possible identification of outliers. The Kolmogorov-Smirnov normality test (e.g., Romeu, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Das and Rahmatullah-Imon, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) was applied to the data. Then the F test was used to compare the variances of two groups, and finally, the means were compared using the Student test (Sanders and Smidt, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). For statistical analyses, samples with levels below the quantification limit of the arsenic determination technique were not considered. The aforementioned tests were conducted with a significance value of 0.05. All work was carried out with Minitab version 17.\u003c/p\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 Characterization of water samples\u003c/h2\u003e\n\u003cp\u003eThe main results obtained for the water samples from the WTP and the mines are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The samples called C1 and C2, belonging to the water treatment plant, were collected in the pipelines, before chemical treatment. These samples presented low electrical conductivity and total dissolved solids compared to the other samples, showing that there is probably less solubilization of the rocks present in the wellspring that are on quartzites, where water is collected. As for arsenic concentration, both samples presented values below those stipulated by Consolidation Ordinance No. 5 of the Ministry of Health of 2017, hence showing that the WTP water is safe in relation to the element arsenic, which is the focus of this study. Obviously, this does not exempt the investigation of other parameters to certify the potability of the water samples. In general, the parameters evaluated for these two samples presented lower results than the mine samples, which was expected, given that the rock formation of the two studied locations has different compositions.\u003c/p\u003e\n\u003cp\u003eThe water samples from the western portion (CMRC4, CD5, CMRE1 and CMRE2) and the southeastern portion (CM11, CM12, FG13 and CM15) of Passagem de Mariana, are on a mineral deposit containing large amounts of arsenopyrite, either in quartz veins and carbonates or disseminated in banded iron formations, tourmalinite, phyllite and quartzite (Oliveira, \u003cspan class=\"CitationRef\"\u003e1998\u003c/span\u003e). The presence of arsenopyrite (FeAsS), arsenolite (As\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e) and scorodite (Fe[AsO]\u003csub\u003e4\u003c/sub\u003e.2H\u003csub\u003e2\u003c/sub\u003eO) was proven in studies carried out by Borba (2003). As the samples in this work were collected close to the studied area by Borba (2003), it is believed that these are responsible for the availability of arsenic in the water samples.\u003c/p\u003e\n\u003cp\u003eThe electrical conductivity in most of these samples was higher in the rainy season (November 2010 and January 2011), which is probably related to the greater leaching of rocks during this period. A clear difference in the conductivity of the water samples between the western and southeastern portions is also observable (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Samples from the southeastern portion have higher conductivity, thus exhibiting lower pH values. It is known that at pH values below 7.0, metal oxides, hydroxides and salts tend to be solubilized, increasing their concentration and making them available to the environment. On the other hand, at pH values above 7.0, metallic cations tend to be precipitated as oxides, hydroxides, carbonates and sulfides (Bourg \u003cspan class=\"CitationRef\"\u003e1995\u003c/span\u003e), resulting in low mobility of the elements.\u003c/p\u003e\n\u003cp\u003eArsenic was found in water samples from mines in both the eastern and western portions in the concentration range of 0.21 to 44.0 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Of these water samples, four (CMRC4, CMRE2, CM11 and CM12) showed arsenic concentrations that exceed the maximum permitted value (MPV) of 10.0 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, established by ordinance No. 5 of the Ministry of Health, in at least one of the four campaigns (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Two samples (CMRE2 and CM11) showed arsenic levels higher than the MPV in the four campaigns (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). It is worth mentioning that on the map in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, the four samples that exceeded the MPV are colored red, in order to spatialize the contamination observed and facilitate the understanding of the local community and public authorities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e: Arsenic concentration and physical-chemical parameters of water samples collected in Passagem de Mariana\u003c/p\u003e\n\u003cp\u003e\u003cimg 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alt=\"\" /\u003e\u003c/p\u003e\n\u003cp\u003eThe CMRC4 water sample, coming from a spring, exceeded the MPV only in the August 2011 sampling, which is a dry period. The arsenic concentration in this sample was 22.4 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. During this period, the sample was unfit for consumption, as a single parameter outside the norm already demonstrated that it does not have safe levels for ingestion. This spring supplies most of the homes on Calv\u0026aacute;rio Street, which is approximately 700 meters long.\u003c/p\u003e\n\u003cp\u003eThe CMRE2 sample, also from the western portion, presented an arsenic concentration (23.8\u0026ndash;37.9 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) higher than the MPV in all collection campaigns. The mine from which this sample was taken is located in the backyard of a residence on Jo\u0026atilde;o Batista Street, where there are old galleries of gold mines mainly supplying the residence in question and some houses in the surrounding area. The sample from the CMRE1 mine, which is also located in this residence, showed an arsenic concentration lower than the MPV. This can be explained by the difference in lithology between the two mines.\u003c/p\u003e\n\u003cp\u003eSamples from the mines in the southeastern portion of Passagem de Mariana, CM11 and CM12, were also collected in an old gold mine gallery in a residence located on Caminho Novo Street. The water from the CM11 mine supplies the surrounding community and the water from the CM12 mine supplies the residence where the collection was made. The two samples presented arsenic concentrations ranging from 14.8 to 44.0 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which were higher than the MPV in all samplings, except in the campaign carried out in January 2011 for sample CM12, whose concentration was 8.32 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAccording to Gon\u0026ccedil;alves et al. (2011), the release of arsenic into the water is due to the presence of this element in weathered, oxidized covers, in mineralized rocks and enriched with sulfide minerals found on the surface and in the walls of abandoned mine galleries, represented mainly by the minerals arsenopyrite, pyrite and pyrrhotite. Weathering processes promote the oxidation of the sulfides present, depositing secondary arsenic minerals on the roofs (Borba et al., \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e). During the dry period, there is an accumulation of these minerals and during the rainy period these minerals are solubilized and leached into the environment, which may explain the presence of arsenic in some water samples evaluated.\u003c/p\u003e\n\u003cp\u003eAmong the mine waters evaluated, CMRE2, CM11 and CM12 are the most worrying, due to the arsenic concentration exceeding the value of 10 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which is the maximum content allowed by Consolidation Ordinance n\u0026ordm; 5 of the Ministry of Health. The evaluation of these waters occurred for two consecutive years, showing that the presence of this element is still a reality and that monitoring of the waters in this district must be continued. In these three samples, contamination appeared to be natural and timeless. It should be noted that the repetitive ingestion of water contaminated by arsenic in significant concentrations, as in this case, can cause a series of health problems, due to its cumulative effect on the human body. Therefore, there is a need to further evaluate the compromised health of the population at the Passagem de Mariana, carrying out analyzes of biological samples to try to explain the cause-effect of disease manifestations in the studied location, which is a work of great importance in terms of environmental, geochemical and public health aspects.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 Analysis of biological samples\u003c/h2\u003e\n\u003cp\u003eThe arsenic concentrations obtained for urine samples from residents of the Passagem de Mariana (called the exposed group) and Vila S\u0026atilde;o Vicente (called the reference group) are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eArsenic concentration in urine samples\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\u003ccolgroup\u003e\u003c/colgroup\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth colspan=\"8\" align=\"left\"\u003e\n\u003cp\u003eExposed group\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSample\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration (\u0026micro;g L\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration (\u0026micro;g L\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration (\u0026micro;g L\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration (\u0026micro;g L\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22,7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31,8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29,8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38,6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33,0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e46,7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22,8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15,2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27,3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28,6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22,4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e102\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27,1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e39,3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9,80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10,2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16,6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25,0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27,2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10,5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12,7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU46\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11,5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30,8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e106\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11,3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e211\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16,3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22,7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23,0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44,3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36,1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10,3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\" align=\"left\"\u003e\n\u003cp\u003eReference group\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSample\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration (\u0026micro;g L\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration (\u0026micro;g L\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration (\u0026micro;g L\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration (\u0026micro;g L\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17,6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17,0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU117\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10,0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e46,6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU103\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU119\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26,6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10,0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8,20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU105\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU122\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12,5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU106\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e55,7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU124\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19,3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU108\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36,3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU125\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15,9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12,1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU110\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11,4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10,7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU114\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;6,95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe concentration of arsenic in urine samples from residents of Passagem de Mariana, related to the exposed group, ranged from 9.80 to 211 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. For the reference group it ranged from 8.20 to 55.7 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. In order to assess the toxicological risks of the groups studied, the classification proposed by Matschullat et al. (\u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e) was adopted, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eClassification proposed by Matschullat et al. (\u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e) for arsenic concentration in urine\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\u003ccolgroup\u003e\u003c/colgroup\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eClass\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eConcentration (\u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRisk\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAction\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLess than 15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow toxicological risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo action.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eII\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBetween 15 and 40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMedium toxicological risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIt is recommended that individuals be evaluated and monitored within this range.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIII\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGreater than 40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh toxicological risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIt is considered a health risk and requires immediate investigation and monitoring of the contamination in each individual.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on the results obtained, it was already expected that the reference group would present lower arsenic concentrations in urine than the exposed group. Furthermore, according to the classification proposed by Matschullat et al. (\u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e), the expectation was that arsenic concentrations would be lower than 15 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, considering that this group had low or no exposure to arsenic. However, the results show that the reference group also suffers from exposure to arsenic, with the possibility of medium and high toxicological risk. This suggests that water is not the only route of arsenic contamination in the studied region. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows the distribution of urine samples, with their respective arsenic concentrations and the limits suggested by Matschullat et al. (\u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIn seven samples, named U6, U12, U23, U24, U61, 100 and U106, the arsenic concentration exceeded 40.0 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, the maximum value for environmental exposure to arsenic according to Matschullat et al. (\u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e). Five of the samples were from the exposed group and two were from the reference group. Samples that present arsenic levels above this base value need to be monitored, as there is a high risk of adverse health effects. In total, 31% of the samples evaluated from the reference group showed arsenic concentrations in the medium and high toxicological risk ranges. Regarding this result, other means of exposure must be investigated, such as: dust, soil, vegetables, eggs and chicken meat, etc.\u003c/p\u003e\n\u003cp\u003eFor the exposed group, approximately 40% of the samples presented arsenic concentrations in the medium and high toxicological risk ranges. As already mentioned, of 63 samples, five presented concentrations above 40 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, with three samples from the exposed group standing out for their high concentration of arsenic in relation to the other samples, whose determined levels were 102, 106 and 211 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. These values were 2.6; 2.7; 5.3 times above the base value of the classification proposed by Matschullat et al. (\u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e), respectively.\u003c/p\u003e\n\u003cp\u003eIn order to better discuss the data, all participants answered a questionnaire about eating habits, living conditions and the occurrence of diseases. This information was used to associate the results found with the incidence of diseases caused by the presence of arsenic in the human body. Although it cannot be inferred that the diseases that are being manifested in the population are caused exclusively by the presence of arsenic in the body, the hypothesis that this element can be a precursor or enhance adverse effects should not be ignored. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e presents the main information obtained for these individuals according to the questionnaire they answered.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eInformation obtained from the questionnaire answered by participants classified in Class III (Matschullat et al., \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e)\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\u003ccolgroup\u003e\u003c/colgroup\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSample\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eLife stage\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGroup type\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eQuestionnaire Information\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChild\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHe had no health problems, according to the questionnaire answered by his guardian. This individual also does not consume chicken products and vegetables grown at home.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdult\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eExposed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHe admitted to having hypertension. The questionnaire also states that he consumes eggs and meat from chickens raised at his home.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChild\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eExposed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHe had no health problems, according to the questionnaire answered by his guardian. They do not consume farmed products and vegetables grown in their homes.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdult\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eExposed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHe stated that he had no health problems. They do not consume farmed products and vegetables grown in their homes.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdult\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eExposed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHe stated that he had no health problems. They do not consume farmed products and vegetables grown in their homes.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdult\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eExposed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHe has no health problems. He eats vegetables grown at home.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eU106\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdult\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHe declared that he had hypertension. According to the information in the questionnaire, this donor is a smoker and consumes eggs and meat from chickens raised in his backyard.\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTaking into account those who do not consume livestock products and vegetables in their homes and who are classified in Class III (Matschullat et al., \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e), inhalation, ingestion and dermal contact with dust are common routes, through which arsenic can penetrate the human body (Madany et al., \u003cspan class=\"CitationRef\"\u003e1987\u003c/span\u003e; Lewis et al., \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e; Johnson-Restrepo and Kannan, \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e), especially in children, due to hand-to-mouth contact, common behavior of crawling, touching and licking toys (Mercier et al., 2011; Raffy et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Cao et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hejami et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eSome authors (Huang et al., \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e, Rahman et al., \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e, Tsai et al., \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e) suggest that there is an association between the development of arterial hypertension and heart disease with chronic arsenic intake. It is also known that arsenic accumulates in the skin, therefore causing various lesions such as hyperpigmentation and hyperkeratosis to appear, and yet another disease associated with arsenic is diabetes mellitus, according to Tseng et al. (\u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e). Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e presents the main diseases declared by the participants. It is clear that it is not possible to say that these illnesses are caused by exposure to arsenic, but the probability that the symptoms were intensified by the ingestion of this trace element cannot be ignored.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab6\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eDiseases declared by participants\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\u003ccolgroup\u003e\u003c/colgroup\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eDisease\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNumber of cases\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNumber of individuals classified as medium and high risk\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eArterial hypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15 individuals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSkin spots\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9 individuals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6 individuals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUrine sampling from the population of Passagem de Mariana and determinations of its total arsenic content allowed the assessment of the extent of contamination of the population of that district. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e presents the NPCs for both groups (A - reference, B - exposed). They highlight the samples considered outliers for each group. From the reference group (A), samples U6 (46.6 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), U106 (55.7 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and U108 (36.3 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were disregarded for further analysis. For the exposed group (B), samples U23 (106.0 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), U24 (211.0 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and U61 (102.0 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were disregarded.\u003c/p\u003e\n\u003cp\u003eThe normality test with the remaining samples showed that the data did not differ significantly from those of a normal distribution - group A (KS 0.216, p-value 0.122) and group B (KS 0.112, p-value 0.822). For these same groups, the mean and standard deviation were calculated - group A (14.28, 5.2, n\u0026thinsp;=\u0026thinsp;12) and group B (24.26; 10.7, n\u0026thinsp;=\u0026thinsp;29). The F test for comparing variances led to a p-value of 0.016 (F\u0026thinsp;=\u0026thinsp;4.18), which means that the variances (and standard deviations) of the two groups differ significantly. This information was used in the subsequent Student test. Thus, the test comparing the means of the two groups led to t\u0026thinsp;=\u0026thinsp;4.00, which corresponds to a p-value of 0.000 (or very close to zero). This procedure revealed that the means of the two groups differ significantly, leading us to the conclusion that the levels of the exposed group (average 24.26 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) are higher than those of the control group (14.28 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003eIn comparison with studies obtained in the literature, it is observed that the concentration of arsenic is more prominent in urine samples from the population of Passagem de Mariana in relation to other locations. In the study carried out by Matos et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), whose objective was to carry out the study of human biomonitoring in blood, serum and urine samples in individuals residing in regions affected by the environmental disaster of the Fund\u0026atilde;o dam collapse, the average concentration of arsenic in urine in the control group was of 6.87 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and in the exposed group it was 6.38 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The difference in average concentration between this research and the aforementioned work can be justified by the fact that the region studied by Matos et al. (\u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e) does not have a lithology that shows the presence of mines that contain arsenic, as clearly seen in Passagem de Mariana.\u003c/p\u003e\n\u003cp\u003eVormitagg et al. (2021) investigated the concentration of potentially toxic chemical elements in urine and blood samples from residents of the district of Barra Longa, Brazil, a place also affected by the Fund\u0026atilde;o dam collapse disaster in 2015. The concentration of arsenic in urine ranged from 12 .3 to 54.2 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e g, whose content is comparable to the present study. This result of arsenic in the samples analyzed by Vormitagg et al. (2021) can be explained by the exposure of the population to suspended dust derived from dried mud and reconstruction works implemented in Barra Longa. The presence of this chemical element in the mud may come from contamination of the Carmo and Gualaxo do Norte rivers (which are located in the aforementioned district), which was already recorded prior to the dam collapse (Eleut\u0026eacute;rio, \u003cspan class=\"CitationRef\"\u003e1997\u003c/span\u003e; Costa et al., \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e). It is worth mentioning that the study area is located at the headwaters of the Carmo river, being one of the main source areas for elements such as arsenic (Costa et al., \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e). Probably, the material deposited at the bottom of the rivers was disturbed and dragged along with the mud.\u003c/p\u003e\n\u003cp\u003eThe results of Arsenic content in hair samples are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab7\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eArsenic concentration in hair samples\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\u003ccolgroup\u003e\u003c/colgroup\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSample\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArsenic concentration\u003c/p\u003e\n\u003cp\u003e(\u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSample\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArsenic concentration\u003c/p\u003e\n\u003cp\u003e(\u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSample\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArsenic concentration\u003c/p\u003e\n\u003cp\u003e(\u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,330\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,079\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,095\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,368\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,075\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,297\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,206\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,064\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,232\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,513\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,048\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,166\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,209\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,330\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,113\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,137\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,202\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,925\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0,174\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,112\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,168\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,080\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSample\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration (\u0026micro;g g\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration (\u0026micro;g g\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eArsenic concentration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(\u0026micro;g g\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;1\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,110\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,080\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,067\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,118\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,161\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,328\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,074\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,070\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,118\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,066\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,110\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0,062\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003e\u003csup\u003ea\u003c/sup\u003eNote: Concentrations in \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, disregarding the dilution factor\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIn these samples, the arsenic concentration varied from 0.048 to 0.925 \u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, with the levels in the reference group ranging from 0.066 to 0.328 \u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and in the exposed group there was a variation from 0.048 to 0.925 \u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. It is observed that the arsenic concentration range in the exposed group is wider in relation to the reference group.\u003c/p\u003e\n\u003cp\u003eAccording to the ToxGuideTM for Arsenic (ATSDR, 2007), the concentration of this trace element considered normal in human hair must be less than 1 \u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. It was observed that the hair samples collected in the district of Passagem de Mariana presented lower concentrations in relation to the content considered acceptable. However, it cannot be guaranteed that the concentration of arsenic found in the hair samples is not causing or will cause toxicological effects in the individuals investigated. Since arsenic can bioaccumulate in the body through long-term exposure to small amounts of this element, first causing skin lesions, such as hyperkeratosis and hyperpigmentation, and later more serious diseases such as skin and lung cancer (inhalation), prostate, bladder, kidney and liver (WHO, \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe data corroborate the hypothesis of this work that historical gold exploration activities in the investigated area contributed to the occurrence of arsenic contamination in water sources. It is evident that the leaching process of sulfide minerals, such as arsenopyrite, made this trace element available to the environmental compartments, thus demonstrating that the hypothesis of resident exposure to arsenic is presumable. The comparison of data from biological samples between the exposed and reference groups studied was important for this work, revealing that there is a difference between the degree of exposure between the two groups studied. However, it was possible to observe that water is not the only route of contact between the chemical element studied with the population, since the reference group also contained arsenic concentrations of the urine in the medium and high toxicological risk ranges. In this case, it is recommended to study other matrices such as dust, soil, vegetables, eggs and chicken meat to evaluate other routes of contamination. Arsenic concentrations in hair samples were lower than the level considered normal by the Agency for Toxic Substances and Disease Registry. It is believed that there was no accumulation of this element in this matrix within a period of 2 to 5 months, which is the time for the concentrations to be detected. However, it cannot yet be said that the arsenic content found in hair samples from residents of this region will not cause harm to health in the long term. With the results obtained in this research, it is recommended that residents of the region be rigorously evaluated and monitored, as arsenic contamination has been confirmed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLouise A. Mendes: Experimental part, data processing and writing of the manuscript. Jorge Carvalho de Lena: Statistical analysis and discussion of results. Adriana Tr\u0026oacute;pia de Abreu: Experimental part, method validation and sample analysis. Liliane Catone Soares: Discussion of results and writing of the manuscript. Emanueli do Nascimento da Silva: Discussion of results and writing of the manuscript. Roberta Eliane Santos Froes-Silva: Experimental part and method validation. Helena Eug\u0026ecirc;nia Leonhardt Palmieri: Experimental part and sample analysis. Adivane Terezinha Costa: mentor of the work, discussion of results and data from environmental geochemistry and medical geology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the Universidade Federal de Ouro Preto, by Official CEP No. 111/2010, dated October 15, 2010. (CAAE: 0024.0.238.000-10).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Free Consent Form was signed by all participants and, mainly, by parents when children participated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no images, videos or personal details of the participants are being used in the manuscript. All were kept confidential.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgah, H. (2021). Ecological risk assessment of heavy metals in sediment, fish, and human hair from Chabahar Bay, Makoran, Iran. 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Acesso em 20/02/2024.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"human biomonitoring, gold mining, health risk, trace element, environmental contamination","lastPublishedDoi":"10.21203/rs.3.rs-4486749/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4486749/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHuman biomonitoring is one of the important tools for assessing exposure to toxic chemicals. A history of arsenic contamination via drinking water from gold mines in the Passagem district of Mariana, Brazil, is a way of incorporating this element into the body. This study aimed to evaluate water quality consumed by residents of Passagem de Mariana and to analyze biological samples, and investigate the magnitude of the exposure to arsenic. The results showed the presence of this trace element in higher concentrations than the maximum value permitted by the law. In two samples, concentrations were above 10 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, regardless of the season, for two years. As for biological samples, arsenic concentrations in hair samples (0.048 to 0.925 \u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were lower than the normal level (\u0026lt;\u0026thinsp;1\u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Arsenic was quantified in urine, both in individuals in the exposed (9.80 to 211 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and in the reference group (8.20 to 55.7 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), whose content is capable of affecting a degree of medium and high toxicological risk (\u0026gt;\u0026thinsp;15 \u0026micro;g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). This group was affected by other sources contributing to arsenic exposure, making it necessary to study other environmental matrices as well as foods. After confirming the exposure, continued biomonitoring was recommended since the adverse effects caused by arsenic can be manifested in the long term.\u003c/p\u003e","manuscriptTitle":"Arsenic Contamination of Drinking Water: A Study of the Exposure to Residents From the Passagem De Mariana, A Historical Gold Mining Town in the Quadrilátero Ferrifero, Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-12 19:14:12","doi":"10.21203/rs.3.rs-4486749/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ef72c15f-2451-4001-ba49-ed924cd49000","owner":[],"postedDate":"June 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-12T19:14:14+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-12 19:14:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4486749","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4486749","identity":"rs-4486749","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}