<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">GEP</journal-id><journal-title-group><journal-title>Journal of Geoscience and Environment Protection</journal-title></journal-title-group><issn pub-type="epub">2327-4336</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/gep.2019.76001</article-id><article-id pub-id-type="publisher-id">GEP-92933</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth&amp;Environmental Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  Application of Multivariate Statistic of U, Th and Pb Concentrations and Pb Isotopic Signatures in the Assessment of Geogenic and Anthropogenic Sources in a U-Mineralized Area
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Adriana</surname><given-names>Monica Dalla Vecchia</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jorge</surname><given-names>Carvalho de Lena</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ana</surname><given-names>Claudia Queiroz Ladeira</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Department of Geology, Federal University of Ouro Preto, Ouro Preto, Brazil</addr-line></aff><aff id="aff1"><addr-line>Center for Development of Nuclear Technology, Belo Horizonte, Brazil</addr-line></aff><pub-date pub-type="epub"><day>06</day><month>06</month><year>2019</year></pub-date><volume>07</volume><issue>06</issue><fpage>1</fpage><lpage>12</lpage><history><date date-type="received"><day>12,</day>	<month>February</month>	<year>2019</year></date><date date-type="rev-recd"><day>7,</day>	<month>June</month>	<year>2019</year>	</date><date date-type="accepted"><day>10,</day>	<month>June</month>	<year>2019</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
   
   This work presents a Principal Component Analysis (PCA) study using
    
   Pbisotope signatures and U, Th and Pb concentrations from groundwater, sediments and rocks (granites and orthogneisses) of the Complex of Lagoa Real (Bahia
   , 
   Brazil). This area is naturally enriched in U and Th, with the occurrence of Pb derived from the radioactive decay of the elements (<sup>238</sup>U, <sup>235</sup>U and <sup>232</sup>Th) in the form of their stable isotopes <sup>206</sup>Pb, <sup>207</sup>Pb and <sup>208</sup>Pb in addition to the natural isotope <sup>204</sup>Pb. Sampling was carried out in the rainy season (December to January) and the points were select
   ed
    according to regional hydrology and geology. Thirty samples were analyzed
   : 
   12 of groundwater (AP) and 18 of sediments (S). The results show that the use of isotopic ratios allows discrimination between geogenic and anthropogenic samples. This information is not obtained using only the analysis of concentration data. Statistically, the isotopic data of Pb stand out as an efficient tool in the characterization of sources in the scenario investigated, allowing an effective environmental monitoring and a better management of the mining activities. 
  
 
</p></abstract><kwd-group><kwd>Environmental Monitoring</kwd><kwd> Statistical Analysis</kwd><kwd> Lead Stable Isotopes</kwd><kwd> Anthropogenic Sources</kwd><kwd> Geogenic Sources</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>The Uraniferous Province of Lagoa Real (Bahia, Brazil) is an area naturally enriched in U and Th, with the occurrence of Pb derived from the radioactive decay of U (<sup>238</sup>U e <sup>235</sup>U) and Th (<sup>232</sup>Th), in the form of their stable isotopes <sup>206</sup>Pb, <sup>207</sup>Pb and <sup>208</sup>Pb respectively, in addition to the presence of the natural isotope <sup>204</sup>Pb. These mineralizations in uranium are the basis of the mining activity of this element, largely responsible for the economic development of the region. In these areas, the groundwater represents the main source of water for the population, since water scarcity is significant.</p><p>According to  Licht (2001) , most of the natural or anthropic processes occurring on the Earth’s surface are characterized by associations of chemical elements (characteristic of the generating process) and geographically associated to their area of occurrence. However, these geochemical signatures may be masked by the superposition of other ones from different sources. Thus, the identifiable geochemical signal, e.g. in waters and sediments, would represent a sum of contributions originated from the natural environmental processes and human action. According to this author, when a complex geochemical signal is interpreted using a multidisciplinary approach, it is possible to decompose it, and, hence, natural or anthropogenic processes can be identified and isolated.</p><p>In order to investigate the correlation between a given element and the source that originated it (natural or anthropogenic), works from the 1960s onwards showed the applicability of the methodology of Pb isotope ratios in environmental studies  (Nriagu, 1989) . Considering that physical or chemical processes do not affect the isotopic composition of Pb in the environment  (Doe, 1970;   Bollh&#246;fer et al., 1999) , the Pb signature tends to be identical to the source that originated it. Therefore, the isotopic signatures of Pb of anthropogenic provenance are distinct from the isotopic signature of natural origin, and can be used as a tracer of the possible sources of Pb in the environment  (Bollh&#246;fer et al., 1999;   Bollh&#246;fer and Rosman, 2000;   Bollh&#246;fer and Rosman, 2001;   Chen et al., 2005;   Gioia et al., 2006;   Gulson et al., 2007;   Kom&#225;rek et al., 2008;   Gioia et al., 2010;   Vecchia, 2015;   Vecchia et al., 2015;   Vecchia et al., 2017a and 2017b) .</p><p>In the area of the Gneissic-Granitic Complex,  Cordani et al. (1992)  obtained data on isotopic composition of Pb in granite rocks of the S&#227;o Tim&#243;teo type (non-deformed granites) and in orthogneisses (deformed granites and associated with uraniferous mineralization). Subsequently,  Iyer et al. (1999)  demonstrated the applicability of Pb isotopes in the quantitative determination of U and Th mobility in different geological formations present in the S&#227;o Francisco Craton. These authors studied several geological environments belonging to the S&#227;o Francisco Craton, among which is the Lagoa Real Gneissic-Granitic Complex, using the isotopic data of Pb published by  Cordani et al. (1992) .</p><p>According to  Vecchia (2015) ,  Vecchia et al. (2015)  and  Vecchia et al. (2017a and 2017b) , the use of the Pb isotopic tool to study environmentally impacted areas requires knowledge of the Pb isotopic signatures of geographic samples as a determinant factor in the investigative process of environmental matrices. Therefore, this study uses the Pb isotopic data of geographic samples of the study area obtained by  Cordani et al. (1992)  along with the U, Th and Pb concentration data from  Iyer et al., 1999 . The isotopic data of Pb produced by  Cordani et al. (1992) , containing information on the preserved geological environment, were compared to the isotopic data of Pb from  Vecchia et al. (2017b) , in order to diagnose influences of geogenic and/or anthropogenic sources in this area.</p><p>Statistical analyses allow the specification of the variables that best characterize the geogenic influences coming from the geological context and/or the anthropic activities in the environment. The multivariate statistical methods allow the extraction of useful information capable of reducing the dimensional representation of the data, organizing them in a structure that facilitates the visualization of the whole data set. Principal Component Analysis (PCA) is among the most widely used with this purpose. It compacts the data into a smaller number of variables (principal components) whose variance (and importance) is given by their eigenvalues. These components are mathematical functions that generate scores that have embedded the contributions (and importance) of each variable with its weight (loadings)  (Manly, 2005;   Mingoti, 2007;   Zhao et al., 2011,   Cavalcante et al., 2013;   Sun et al., 2013;   Siepak and Sojka, 2017) . It is important to emphasize that the results obtained with these techniques should, whenever possible, be confronted with information related to the research context, seeking an association on the possible processes in the study region  (Vecchia, 2015;   Vecchia et al., 2015;   Vecchia et al., 2017a and 2017b) .</p><p>This work presents a statistical study based on the PCA, using Pb isotopic ratios, and U, Th and Pb concentrations from groundwater and sediments in the Lagoa Real Uranium Complex (Brazil). The main objective is to refine the information from the investigations carried out by  Vecchia et al. (2017b)  by analyzing the contributions of each variable in the diagnosis of possibly impacted areas in the Uraniferous Province area. This work aims to diagnose not only the water quality and sediments in the study area, but also to identify the areas possibly affected by the mining activity.</p></sec><sec id="s2"><title>2. Study Area</title><p>The study area, Southeastern Brazil, is located in the semi-arid region characterized by a marked water deficit. It is considered the main active site of uranium in Brazil and South America. Pb isotopic signature of samples was determined in an area of 1200 km<sup>2</sup> at Lagoa Real Uranium Complex, Bahia State, Brazil (<xref ref-type="fig" rid="fig1">Figure 1</xref>). This complex is geologically identified as a Gneissic-Granitic Complex with ages between of 1.72 and 1.77 Ga  (Cordani et al. 1992) . Granite type S&#227;o Tim&#243;teo (undeformed granites), orthogneiss (deformed granites and associated U-mineralization) and U-albitites (main hosts of the uranium mineralization) are the principal lithologies of the region and represents the geogenic sources  (Vecchia et al., 2017b) .</p><p>The average annual rainfall is around 700 mm, with high variability in the spatial and temporal distribution (annual seasonality)  (Vecchia, 2015) . According to  Lamego Sim&#245;es et al. (2003) , the climatological and hydrological characteristics,</p><p>associated to the conformation of the regional relief with flows to Atlantic slope, give rise to a hydrographic network in which intermittent drainage is common (<xref ref-type="fig" rid="fig1">Figure 1</xref>). Complementary hydrological data and geology of the study area can be found in  Vecchia (2015) .</p></sec><sec id="s3"><title>3. Experimental Methods</title><sec id="s3_1"><title>3.1. Sampling</title><p>Sampling was carried out according to  Vecchia et al. (2017b) . Groundwater and sediment sampling points were selected according to regional hydrology and geology, including points at the mining area and points located upstream and downstream thef U anomalies (contents higher than 1500 ppm). The deficit of surface water led to the choice of groundwater and sediment as study matrices. Sampling was carried out in the rainy season (December to January) because of the discontinuous flow of the rivers and the low precipitation level in the region (around 700 mm). The location of sampling was devised aiming to achieve a reliable geographical representation and to ensure a good spatial distribution of the data. Thirty samples were analyzed; 12 of groundwater (AP) and 18 of sediments (S) as shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>. The sampling points were georeferenced, using GPS (Global Positioning System).</p><p>The sampling and preservation of water samples were carried out according to the Environmental Agency of the State of S&#227;o Paulo directions—  CETESB (2011)  and  Veridiana et al. (2008) . More details in  Vecchia et al. (2017b) .</p><p>Approximately 1 kg of sediments samples, representative of the regional lithologies (<xref ref-type="fig" rid="fig1">Figure 1</xref>), were collected in depth from 50 cm to 80 cm, using a cylindrical collector. This material was transferred to low-density polyethylene (LDPE; Nalgon<sup>&#210;</sup>) containers. Subsequently, these samples were dried, disaggregated, homogenized and sieved. Fractions &lt; 250 Mesh Tyler were sent to isotopic Pb and chemical analysis.</p></sec><sec id="s3_2"><title>3.2. Pb Isotopic Geochemical Analytical Procedure</title><p>Pb isotopic ratios of groundwater and sediments were determined through Thermal Ionization Mass Spectrometry (TIMS), using a multi-collector Finnigan MAT 262 at the Geochronological Research Center of USP (University of S&#227;o Paulo) according to the  Vecchia et al. (2017b) .</p></sec><sec id="s3_3"><title>3.3. Pb, U and Th Geochemistry Analytical Procedure</title><p>U, Th and Pb were analyzed in water and sediments samples by Inductively Couple Plasma Mass Spectrometry, ICP-MS (PerkinElmer - ELAN DRC-e) at the Center for Development of Nuclear Technology (CDTN), according to the  Vecchia et al. (2017b)  and procedures recommended by the U.S. EPA 2008.</p></sec><sec id="s3_4"><title>3.4. Multivariate Analysis</title><p>Data were submitted to a Principal Component Analysis aiming to establish relations between U, Th and Pb contents and Pb isotopic ratios (<sup>206</sup>Pb/<sup>204</sup>Pb, <sup>207</sup>Pb/<sup>204</sup>Pb, <sup>208</sup>Pb/<sup>204</sup>Pb, <sup>206</sup>Pb/<sup>207</sup>Pb, <sup>208</sup>Pb/<sup>207</sup>Pbe <sup>208</sup>Pb/<sup>206</sup>Pb) to the environment and their origin (geogenic or anthropogenic). The whole dataset (Tables 1-3 in Annex) consists of 12 sediment samples, 12 water samples (11 groundwater samples and 1 surface water sample) and 15 samples of  Cordani et al. (1992)  (07 S&#227;o Tim&#243;teo Granite samples and 08 orthogneiss samples). Minitab<sup>&#210;</sup> software, version 16.1.1.0, was used for statistical analysis.</p></sec></sec><sec id="s4"><title>4. Results and Discussion</title>Multivariate Analysis<p>Data (Tables 1-3 in Annex) were submitted to a Principal Component Analysis. This study was conducted in three steps. In the first one U, Th and Pb concentrations and Pb isotopic ratios of orthogneisses samples were analyzed together with data of groundwater and sediment samples. In the second step, only data of isotopic ratios from the same samples were used. In the third step, data of Pb isotopic ratios of S&#227;o Tim&#243;teo granite were used together with data of groundwater and sediment samples. It is important to point out that these two types of rocks are characteristic of the geological formation of the study area and involve the genesis of uranium mineralization. Thus, they are important references of the geographic sources of Pb in the region. The use of these data aims to determine the type of rock that most influences the Pb isotopic signatures of groundwater and sediments and, therefore, which one better discriminates the environmental matrices investigated.</p><p>1) PCA using Pb isotopic ratios and U, Th and Pbconcentrations in sediments, groundwater and orthogneiss samples</p><p><xref ref-type="table" rid="table1">Table 1</xref> presents the loading values of each variable in each of the components as well as their respective eigenvalues. These data can be interpreted in terms of two main components, PC1 and PC2, which account for 81.2% of the data variability. The first component (PC1) with an eigenvalue of 4.6145 accounts for 51.3% of the data variance. It is mainly dominated by isotopic ratios<sup>206</sup>Pb/<sup>204</sup>Pb, <sup>207</sup>Pb/<sup>204</sup>Pb, <sup>206</sup>Pb/<sup>207</sup>Pb, <sup>208</sup>Pb/<sup>206</sup>Pb and by U. This component can be interpreted as representing the contribution of this element and its decay to the geochemistry of sediments and water. The second component (PC2) with an eigenvalue of 2.6974 accounting for 30.0% of the data variance is dominated by the isotopic ratios <sup>208</sup>Pb/<sup>204</sup>Pb, <sup>208</sup>Pb/<sup>207</sup>Pb and by Th and Pb. This component can be understood as representing the contribution of Th and its decay in the general characterization of sediments and waters.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Loading values of each variable in each of the principal components for samples of water, sediment and orthogneisses of the uraniferous province of Lagoa Real BA, for PCA carried out with all variables</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variable</th><th align="center" valign="middle" >PC1</th><th align="center" valign="middle" >PC2</th></tr></thead><tr><td align="center" valign="middle" ><sup>206</sup>Pb/<sup>204</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.440</td><td align="center" valign="middle" >−0.152</td></tr><tr><td align="center" valign="middle" ><sup>207</sup>Pb/<sup>204</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.445</td><td align="center" valign="middle" >−0.104</td></tr><tr><td align="center" valign="middle" ><sup>208</sup>Pb/<sup>204</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.212</td><td align="center" valign="middle" >0.480</td></tr><tr><td align="center" valign="middle" ><sup>206</sup>Pb/<sup>207</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.441</td><td align="center" valign="middle" >−0.141</td></tr><tr><td align="center" valign="middle" ><sup>208</sup>Pb/<sup>206</sup>Pb<sup> </sup></td><td align="center" valign="middle" >−0.416</td><td align="center" valign="middle" >0.230</td></tr><tr><td align="center" valign="middle" ><sup>208</sup>Pb/<sup>207</sup>Pb<sup> </sup></td><td align="center" valign="middle" >−0.002</td><td align="center" valign="middle" >0.567</td></tr><tr><td align="center" valign="middle" >U</td><td align="center" valign="middle" >0.274</td><td align="center" valign="middle" >−0.104</td></tr><tr><td align="center" valign="middle" >Th</td><td align="center" valign="middle" >0.243</td><td align="center" valign="middle" >0.413</td></tr><tr><td align="center" valign="middle" >Pb</td><td align="center" valign="middle" >0.247</td><td align="center" valign="middle" >0.401</td></tr><tr><td align="center" valign="middle" >Eigenvalue</td><td align="center" valign="middle" >4.6145</td><td align="center" valign="middle" >2.6974</td></tr><tr><td align="center" valign="middle" >Proportion</td><td align="center" valign="middle" >0.513</td><td align="center" valign="middle" >0.300</td></tr><tr><td align="center" valign="middle" >Cumulative</td><td align="center" valign="middle" >0.513</td><td align="center" valign="middle" >0.812</td></tr></tbody></table></table-wrap><p><xref ref-type="fig" rid="fig2">Figure 2</xref> shows the score plot of the first two components (PC1 and PC2) for water, sediment and orthogneiss samples. The score of a sample represents the contribution of each variable measured and its respective weights to the characteristics of the sample. Sediment and rock samples are grouped around the origin of the diagram, showing little difference from each other, which shows the geogenic character of the sediments, since in the process of weathering they did not undergo enrichment, i.e., anthropic influence. Sample P19S stands out from this group. Its high score values of PC1 and PC2 suggests enrichment of U and Th whose increase in concentration leads to an increase in the score value for the score of the samples in each component. Also noteworthy is the sample P35S with positive score value of PC1 and negative score value of PC2. In this case, the sample is enriched in U rather than Th, being the U enrichment due to anthropic influence. The water samples stand out from the group with negative score values for both PC1 and PC2. This means that, in general, the values of the variables for this matrix are low, which is a reflex of the low solubility of U, Th and Pb species (and their isotopes) in water. Samples P22AP is enriched in these species while P18A is enriched in Th. Samples P22AP and P18AP stand out from the rest of the groundwater samples, resembling the sediment and orthogneiss group of samples, probably because their isotopic signatures are under the geogenic influence of the orthogneiss.</p><p>2) PCA using Pb isotopic ratios in sediments, groundwater and orthogneiss samples</p><p>The same procedure was applied to the same samples, removing U, Th and Pb concentrations, i.e., working only with the Pb isotopic ratios as variables. <xref ref-type="table" rid="table2">Table 2</xref> shows the loading values for both components. Concerning the isotopic ratios there is no difference between the results obtained with the two approaches, i.e., calculations with and without U, Th and Pb concentrations. <xref ref-type="fig" rid="fig3">Figure 3</xref> and <xref ref-type="fig" rid="fig4">Figure 4</xref> reflect this result. The distributions of samples in both diagrams are the same.</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Loading values of each variable in each of the principal components for samples of water, sediment and orthogneisses of the uraniferous province of Lagoa Real (BA), for PCA carried without U, Th and Pb concentrations</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variable</th><th align="center" valign="middle" >PC1</th><th align="center" valign="middle" >PC2</th></tr></thead><tr><td align="center" valign="middle" ><sup>206</sup>Pb/<sup>204</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.499</td><td align="center" valign="middle" >0.003</td></tr><tr><td align="center" valign="middle" ><sup>207</sup>Pb/<sup>204</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.485</td><td align="center" valign="middle" >0.000</td></tr><tr><td align="center" valign="middle" ><sup>208</sup>Pb/<sup>204</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.150</td><td align="center" valign="middle" >0.693</td></tr><tr><td align="center" valign="middle" ><sup>206</sup>Pb/<sup>207</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.499</td><td align="center" valign="middle" >0.019</td></tr><tr><td align="center" valign="middle" ><sup>208</sup>Pb/<sup>206</sup>Pb<sup> </sup></td><td align="center" valign="middle" >−0.485</td><td align="center" valign="middle" >0.099</td></tr><tr><td align="center" valign="middle" ><sup>208</sup>Pb/<sup>207</sup>Pb<sup> </sup></td><td align="center" valign="middle" >−0.094</td><td align="center" valign="middle" >0.714</td></tr><tr><td align="center" valign="middle" >Eigenvalue</td><td align="center" valign="middle" >3.9889</td><td align="center" valign="middle" >1.8926</td></tr><tr><td align="center" valign="middle" >Proportion</td><td align="center" valign="middle" >0.665</td><td align="center" valign="middle" >0.315</td></tr><tr><td align="center" valign="middle" >Cumulative</td><td align="center" valign="middle" >0.665</td><td align="center" valign="middle" >0.980</td></tr></tbody></table></table-wrap><p>Exception is sample P19S for which the concentrations of these three elements are especially higher. This suggests that the isotopic ratios are sufficient to assess the characteristics of samples. An additional observation due to the absence of the concentration variable in this step is the increase in the percentage of explanation of the variability of the data of the principal components PC1 and PC2, evidencing the importance and efficacy of the isotopic ratios in the study of environmental samples.</p><p>3) PCA using Pb isotopic ratios data for sediments, groundwater and S&#227;o Tim&#243;teo Granite samples.</p><p>For this matrix, only data of Pb isotopic ratios were used. They refer to the samples of S&#227;o Tim&#243;teo type granite, groundwater and sediments. <xref ref-type="table" rid="table3">Table 3</xref> shows the loading values of each variable in each of the main components.</p><p>These data can be interpreted in terms of two principal components, PC1 and PC2, which account for 97.8% of the data variability. The first component (PC1) with an eigenvalue of 3.9180 accounts for 65.3% of the data variance. It is mainly dominated by isotopic ratios<sup>206</sup>Pb/<sup>204</sup>Pb, <sup>207</sup>Pb/<sup>204</sup>Pb, <sup>206</sup>Pb/<sup>207</sup>Pb, <sup>208</sup>Pb/<sup>206</sup>Pb the latter with negative loading value. This component can be interpreted as representing the contribution of U represented by its decay isotopes to the geochemistry of sediments. The second component (PC2) with an eigenvalue of 1.9517 accounting for 32.5% of the data variance is dominated by the isotopic ratios <sup>208</sup>Pb/<sup>204</sup>Pb, <sup>208</sup>Pb/<sup>207</sup>Pb, which are the decay products of Th. It represents the contribution of Th in the general characterization of sediments.</p><p><xref ref-type="fig" rid="fig4">Figure 4</xref> shows the score plot of the first two components (PC1 and PC2) for water, sediment and granite samples. In general, the same observations made with the previous PCA study (<xref ref-type="fig" rid="fig3">Figure 3</xref>) can be summarized here: no separation of sediment and rock samples leading to their geogenic character, separation of water samples, separation of samples P22AP, and P18AP, P19S and one sample (P35S) due to anthropogenic enrichment.</p><p>According to  Vecchia et al. (2017b)  there is a great variation of Pb isotopic</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Loading values of each variable in each of the principal components for samples of water, sediment and granite of the uraniferous province of Lagoa Real BA</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variable</th><th align="center" valign="middle" >PC1</th><th align="center" valign="middle" >PC2</th></tr></thead><tr><td align="center" valign="middle" ><sup>206</sup>Pb/<sup>204</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.503</td><td align="center" valign="middle" >−0.016</td></tr><tr><td align="center" valign="middle" ><sup>207</sup>Pb/<sup>204</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.488</td><td align="center" valign="middle" >0.026</td></tr><tr><td align="center" valign="middle" ><sup>208</sup>Pb/<sup>204</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.161</td><td align="center" valign="middle" >0.678</td></tr><tr><td align="center" valign="middle" ><sup>206</sup>Pb/<sup>207</sup>Pb<sup> </sup></td><td align="center" valign="middle" >0.504</td><td align="center" valign="middle" >−0.003</td></tr><tr><td align="center" valign="middle" ><sup>208</sup>Pb/<sup>206</sup>Pb<sup> </sup></td><td align="center" valign="middle" >−0.477</td><td align="center" valign="middle" >0.176</td></tr><tr><td align="center" valign="middle" ><sup>208</sup>Pb/<sup>207</sup>Pb<sup> </sup></td><td align="center" valign="middle" >−0.040</td><td align="center" valign="middle" >0.713</td></tr><tr><td align="center" valign="middle" >Eigenvalue</td><td align="center" valign="middle" >3.9180</td><td align="center" valign="middle" >1.9517</td></tr><tr><td align="center" valign="middle" >Proportion</td><td align="center" valign="middle" >0.653</td><td align="center" valign="middle" >0.325</td></tr><tr><td align="center" valign="middle" >Cumulative</td><td align="center" valign="middle" >0.653</td><td align="center" valign="middle" >0.978</td></tr></tbody></table></table-wrap><p>signatures for both sediment and groundwater samples related to the geogenic sources (representative of the regional lithologies). However, the variation for the sediments is significantly higher. Moreover, among the geogenic sources it was observed that the Pb isotopic signatures for sediments and groundwater, from the same geographical coordinate, indicated a natural enrichment in U and Th. The values of the majority of the Pb isotopic signatures for groundwater are considered low, in spite of being in accordance with the geogenic sources of the region, which are under the influence of granites. One sediment sample (P35S), collected in the U mining area, presented isotopic Pb signature typical of U anthropogenic sources (high <sup>206</sup>Pb/<sup>204</sup>Pb ratio compared to <sup>208</sup>Pb/<sup>204</sup>Pb ratio), which means U contamination. However, the PCA analysis proved that this was not the behavior evidenced by the P19S sample, which presented isotopic Pb signature in accordance with the geogenic sources of the region.</p></sec><sec id="s5"><title>5. Conclusion</title><p>One of the major vulnerabilities of the nuclear area and/or mining activities to public opinion refers to frequent suspicions that nuclear and/or mining industry always generate(s) large environmental impacts, especially contamination of groundwater. These kinds of worries can find legal resonance even without the necessary pre-operational background data, and most of the decisions consider the analytical results of radionuclide concentrations from the operational phase as the main incriminating technical argument. The present study showed that the determination of the concentration of the contaminants is not enough to characterize environmental contamination. It also shows that the most effective analytical method to elucidate the role of anthropogenic interferences in the environment is the determination of isotopic ratios. It can even be used in environments with high concentrations of radionuclides.</p><p>This tool becomes even more relevant in regions where pre-operational data are scarce and incomplete, if not inexistent, or even in regions, such as Caetit&#233; (Bahia), where water sampling is very difficult due to low water availability. In addition, it has been proved that the Pb isotopic tool, besides being used in any type of environmental matrices, is still promising in the investigation of industrial environmental impacts from mining as well as from physical, chemical and thermal processes where the generation of NORM (Natural Occurring Radioactive Material) wastes is related.</p></sec><sec id="s6"><title>Acknowledgements</title><p>Authors are thankful to CNEN for Doctoral scholarship; to CNPq and to FAPEMIG for financial support.</p></sec><sec id="s7"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s8"><title>Cite this paper</title><p>Vecchia, A. M. D., de Lena, J. C., &amp; Ladeira, A. C. Q. (2019). Application of Multivariate Statistic of U, Th and Pb Concentrations and Pb Isotopic Signatures in the Assessment of Geogenic and Anthropogenic Sources in a U-Mineralized Area. Journal of Geoscience and Environment Protection, 7, 1-12. https://doi.org/10.4236/gep.2019.76001</p></sec></body><back><ref-list><title>References</title><ref id="scirp.92933-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Bollh&amp;#246;fer, A., &amp; Rosman, K. J. R. (2000). Isotopic Source Signatures for Atmospheric Lead: The Southern Hemisphere. Geochimica et Cosmochimica Acta, 64, 3251-3262. https://doi.org/10.1016/S0016-7037(00)00436-1</mixed-citation></ref><ref id="scirp.92933-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Bollh&amp;#246;fer, A., &amp; Rosman, K. J. R. (2001). Isotopic Source Signatures for Atmospheric Lead: The Northern Hemisphere. Geochimica et Cosmochimica Acta, 65, 1727-1740. https://doi.org/10.1016/S0016-7037(00)00630-X</mixed-citation></ref><ref id="scirp.92933-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Bollh&amp;#246;fer, A., Chisholm, W., &amp; Rosman, K. J. R. (1999). Sampling Aerosols for Lead Isotopes on a Global Scale. Analytica Chimica Acta, 390, 227-235.https://doi.org/10.1016/S0003-2670(99)00182-8</mixed-citation></ref><ref id="scirp.92933-ref4"><label>4</label><mixed-citation publication-type="other" xlink:type="simple">Cavalcante, Y. L., Hauser-Davis, R. A., Saraiva, A. C. F., Brand&amp;#227;o, I. L. S., Oliveira, T. F., &amp; Silveira, A. M. (2013). Metal and Physico-Chemical Variations at a Hydroelectric Reservoir Analyzed by Multivariate Analyses and Artificial Neural Networks: Environmental Management and Policy/Decision-Making Tools. Science of the Total Environment, 442, 509-514. https://doi.org/10.1016/j.scitotenv.2012.10.059</mixed-citation></ref><ref id="scirp.92933-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">CETESB. Companhia de Tecnologia de Saneamento Ambiental. (2011). Guia nacional de coleta e preserva&amp;#231;&amp;#227;o de amostras: água, sedimento, comunidades aquáticas e efluentes líquidos. 2. ed. S&amp;#227;o Paulo: CETESB; Brasília-DF: Agência Nacional de águas, ANA, Ministério do Meio Ambiente, 325 p.</mixed-citation></ref><ref id="scirp.92933-ref6"><label>6</label><mixed-citation publication-type="other" xlink:type="simple">Chen, J., Tan, M., Li, Y.-L., Zhang, Y., Lu, W., Tong, Y., Li, Y., &amp; Zhang, G. (2005). A Lead Isotopic Record of Shangai Atmospheric Led Emissions in Total Suspended Particles during the Period of Phasing out of Leaded Gasoline. Atmospheric Environment, 39, 1245-1253. https://doi.org/10.1016/j.atmosenv.2004.10.041</mixed-citation></ref><ref id="scirp.92933-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Cordani, U. G., Iyer, S. S., Taylor, P. N., Kawashita, K., Sato, K., &amp; Mcreath, I. (1992). Pb-Pb, Rb-Sr, and K-Ar Systematic of the Lagoa Real Uranium Province (South-Central Bahia, Brazil) and the Espinha&amp;#231;o Cycle (ca. 1.5-1.0 Ga). Journal of South American Earth Sciences, 5, 33-46. https://doi.org/10.1016/0895-9811(92)90058-7</mixed-citation></ref><ref id="scirp.92933-ref8"><label>8</label><mixed-citation publication-type="other" xlink:type="simple">Doe, B. R. (1970). Lead Isotopes. Berlin: Springer-Verlag.https://doi.org/10.1007/978-3-642-87280-8</mixed-citation></ref><ref id="scirp.92933-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Gioia, S. M. C. L., Babinski, M., Weiss, D. J., &amp; Kerr, A. A. F. S. (2010). Insights into the Dynamics and Sources of Atmospheric Lead and Particulate Matter in S&amp;#227;o Paulo, Brazil, from High Temporal Resolution Sampling. Atmospheric Research, 98, 478-485. https://doi.org/10.1016/j.atmosres.2010.08.016</mixed-citation></ref><ref id="scirp.92933-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Gioia, S. M. C. L., Pimentel, M. M., Tessler, M., Dantas, E. L., Campos, J. E. G., Guimar&amp;#227;es, E. M., Maruoka, M. T. S., &amp; Nascimento, E. L. C. (2006). Sources of Anthropogenic Lead in Sediments from an Artificial Lake in Brasília, Central Brazil. Science of the Total Environment, 356, 125-142. https://doi.org/10.1016/j.scitotenv.2005.02.041</mixed-citation></ref><ref id="scirp.92933-ref11"><label>11</label><mixed-citation publication-type="other" xlink:type="simple">Gulson, B. L., Korsch, M. J., Dickson, B., Cohen, D., Mizon, K. J., &amp; Davis, M. J. (2007). Comparison of Lead Isotopes with Source Apportionment Models, Including SOM, for Air Particulates. Science of the Total Environment, 381, 169-179. https://doi.org/10.1016/j.scitotenv.2007.03.018</mixed-citation></ref><ref id="scirp.92933-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">Iyer, S. S., Babinski, M., Marinho, M. M., Barbosa, J. S. F., Sato, I. M., &amp; Salvador, V. L. (1999). Lead Isotope Evidence for Recent Uranium Mobility in Geological Formations of Brazil: Implications for Radioactive Waste Disposal. Applied Geochemistry, 14, 197-221. https://doi.org/10.1016/S0883-2927(98)00040-7</mixed-citation></ref><ref id="scirp.92933-ref13"><label>13</label><mixed-citation publication-type="other" xlink:type="simple">Komárek, M., Ettler, V., Chrastny, V., &amp; Mihaljevic, M. (2008). Lead Isotopes in Environmental Sciences: A Review. Environment International, 34, 562-577.https://doi.org/10.1016/j.envint.2007.10.005</mixed-citation></ref><ref id="scirp.92933-ref14"><label>14</label><mixed-citation publication-type="other" xlink:type="simple">Lamego Sim&amp;#245;es, F. F. F., Fernandes, H. R. S. M., Franklin, M. R., Flexor, J. M., Fontes, S. L., Pereira, F. S. R., &amp; Nascimento, F. M. F. (2003). Impactos de Minera&amp;#231;&amp;#227;o e Sustentabilidade no Semi-árido.Estudo de caso: Unidade de Concentra&amp;#231;&amp;#227;o de Uranio—URA (Caetité, BA). Centro de Tecnologia Mineral—CETEM—Ministério da Ciência e Tecnologia. In: Simpósio Brasileiro de Recursos Hídricos, 15, 2003, Curitiba. Comunica&amp;#231;&amp;#227;otécnica. Porto Alegre, ABRH, 18 p.</mixed-citation></ref><ref id="scirp.92933-ref15"><label>15</label><mixed-citation publication-type="other" xlink:type="simple">Licht, O. A. B. (2001). Geoquímica Multielementar na Gest&amp;#227;o Ambiental. Identifica&amp;#231;&amp;#227;o e Caracteriza&amp;#231;&amp;#227;o de Províncias Geoquímicas Naturais, Altera&amp;#231;&amp;#245;es Antrópicas das Paisagens, áreas Favoráveis à Prospec&amp;#231;&amp;#227;o Mineral e Regi&amp;#245;es de Risco no Estado do Paraná, Brasil. Tese de Doutorado. Curitiba: Universidade Federal do Paraná, 209 p.</mixed-citation></ref><ref id="scirp.92933-ref16"><label>16</label><mixed-citation publication-type="other" xlink:type="simple">Manly, B. J. J. (2005). Multivariate Statistical Methods. A Primer. 3rd Edition, Chapman &amp; Hall/CRC Press Company, Boca Raton, 214 p.</mixed-citation></ref><ref id="scirp.92933-ref17"><label>17</label><mixed-citation publication-type="book" xlink:type="simple">Mingoti, S. A. (2007). Análise de Dados Através de Métodos de Estatística Multivariada. Uma Abordagem Aplicada. Ed. UFMG Belo Horizonte. 293 p.</mixed-citation></ref><ref id="scirp.92933-ref18"><label>18</label><mixed-citation publication-type="other" xlink:type="simple">Nriagu, J. O. (1989). A Global Assessment of Natural Sources of Atmospheric Trace Metal. Nature, 338, 47-49. https://doi.org/10.1038/338047a0</mixed-citation></ref><ref id="scirp.92933-ref19"><label>19</label><mixed-citation publication-type="other" xlink:type="simple">Siepak, M. &amp; Sojka, M. (2017). Application of Multivariate Statistical Approach to Identify Trace Elements Sources in Surface Waters: A Case Study of Kowalskie and Stare Miasto Reservoirs, Poland. Environmental Monitoring and Assessment, 189, 364. https://doi.org/10.1007/s10661-017-6089-x</mixed-citation></ref><ref id="scirp.92933-ref20"><label>20</label><mixed-citation publication-type="other" xlink:type="simple">Sun, C., Liu, J., Wang, Y., Sun, L., &amp; Yu, H.-W. (2013). Multivariate and Geostatistical Analyses of the Spatial Distribution and Sources of Heavy Metals in Agricultural Soil in Dehui, Northeast China. Chemosphere, 92, 517-523.https://doi.org/10.1016/j.chemosphere.2013.02.063</mixed-citation></ref><ref id="scirp.92933-ref21"><label>21</label><mixed-citation publication-type="other" xlink:type="simple">Vecchia, A. M. D. (2015). Investiga&amp;#231;&amp;#245;es Isotópicas de Pb em águas Subterraneas e Sedimentos—Província Uranífera de Lagoa Real (Bahia). Tese de Doutorado. Centro de Desenvolvimento da Tecnologia Nuclear. Comiss&amp;#227;o Nacional de Energia Nuclear. Belo Horizonte, 222 p.</mixed-citation></ref><ref id="scirp.92933-ref22"><label>22</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Vecchia</surname><given-names> A. M. D.</given-names></name>,<name name-style="western"><surname> Rodrigues</surname><given-names> P. C. H.</given-names></name>,<name name-style="western"><surname> &amp; Ladeira</surname><given-names> A. C. Q. </given-names></name>,<etal>et al</etal>. (<year>2017a</year>)<article-title>. Assinaturas isotópicas de Pb na avalia&amp;#231;&amp;#227;o do impacto ambiental causado pelo lan&amp;#231;amento do efluente tratado pelo complexo mínero industrial do planalto de Po&amp;#231;os de Caldas na represa de águas Claras e Ribeir&amp;#227;o das Antas</article-title><source> Geonomos</source><volume> 25</volume>,<fpage> 14</fpage>-<lpage>23</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.92933-ref23"><label>23</label><mixed-citation publication-type="other" xlink:type="simple">Vecchia, A. M. D., Rodrigues, P. C. H., Ladeira, A. C. Q., &amp; Rios, F. J. (2015). Interpreta&amp;#231;&amp;#227;o de dados isotópicos de Pb em diferentes ambientes investigativos visando o diagnóstico de fontes geogênicas e/ou antrópicas. Geonomos, 22, 77-90. https://doi.org/10.18285/geonomos.v22i2.320</mixed-citation></ref><ref id="scirp.92933-ref24"><label>24</label><mixed-citation publication-type="other" xlink:type="simple">Vecchia, A. M. D., Rodrigues, P. C. H., Rios, F. J., &amp; Ladeira, A. C. Q. (2017b). Investigations into Pb Isotope Signatures in Groundwater and Sediments in a Uranium-Mineralized Area. Brazilian Journal of Geology, 47, 147-158.https://doi.org/10.1590/2317-4889201720160100</mixed-citation></ref><ref id="scirp.92933-ref25"><label>25</label><mixed-citation publication-type="other" xlink:type="simple">Veridiana, M., Babinski, M., Ruiz, I., Sato, K., Souza, S., &amp; Hirata, R. (2008). Analytical Procedures for Determining Pb and Sr Isotopic Compositions in Water by ID-TIMS. Química Nova, 31, 1836-1842. https://doi.org/10.1590/S0100-40422008000700040</mixed-citation></ref><ref id="scirp.92933-ref26"><label>26</label><mixed-citation publication-type="other" xlink:type="simple">Zhao, J., Fu, G., Lei, K., &amp; Li, Y.-W. (2011). Multivariate Analysis of Surface Water Quality in the Three Gorges Area of China and Implications for Water Management. Journal of Environmental Sciences, 23, 1460-1471.https://doi.org/10.1016/S1001-0742(10)60599-2</mixed-citation></ref></ref-list></back></article>