s10661 023 11080 5

(1)

Environmental risk assessment of potentially toxic

elements in Doce River watershed after mining sludge dam breakdown in Mariana, MG, Brazil

Leticia A. Bertoldo · Angelita Ribeiro · Cecília E. S. Reis · Emilli Frachini · Barbara L. Kroetz · Taufik Abrão · Maria Josefa Santos

Received: 25 August 2022 / Accepted: 2 March 2023 / Published online: 5 April 2023

Abstract Faced with a potential risk of a colossal amount of sludge released into the Doce River basin in the most shocking Brazilian mining disaster, we proposed to assess the environmental risk from a new perspective: Understanding the mobilization of potentially toxic elements (PTE) with the geochemical fractions. Soil and sediment samples were taken in nine sites throughout the basin and characterized. The environmental risk was assessed from the PTE sequential extraction in three fractions: soluble, reducible, and oxidizable, in addition to the pseudo- total concentration. The potential mobile fraction (PMF) showed a considerable PTE mobilization from the soil and sediment samples. Principal component statistical analysis indicated the sludge as the single source of PTE. The risk assessment depended on

the fractional distribution and the PTE enrichment degree in the affected samples. The fractional distribution contributed mainly to Mn, Sb, and Pb mobility, with PMF of 96%, 81%, and 100%, respectively.

The mobilization of Cd, Co, Ag, Ni, Pb, Zn, and Cu was predominantly related to the degree of enrichment. The risk assessment from the geochemical fractions pointed to the magnitude of the disaster and the dispersion of PTE with severe effects on the affected populations. Therefore, more strongly enforced regu- lations in the basin are needed, in addition to the urgent use of more secure containment dams. It is also essential to emphasize the transferability of the design of this study to other environmental units in mining disaster conditions.

Keywords Risk assessment · Metal mobilization · Mining waste · Sequential extraction · Geochemical fractions

Angelita Ribeiro, Cecília E S Reis, Emilli Frachini, Barbara L Kroetz, Taufik Abrão and Maria Josefa Santos contributed equally to this work.

L. A. Bertoldo · A. Ribeiro · C. E. S. Reis · E. Frachini · B. L. Kroetz · M. J. Santos (*)

Chemistry Department, Londrina State University, Celso Garcia Cid Highway, Londrina 86057-970, Paraná, Brazil e-mail: [email protected]

L. A. Bertoldo

e-mail: [email protected] A. Ribeiro

e-mail: [email protected] C. E. S. Reis

e-mail: [email protected]

E. Frachini

e-mail: [email protected] B. L. Kroetz

e-mail: [email protected] T. Abrão

Electrical Engineering Department, Londrina State University, Celso Garcia Cid Highway, Londrina 86057-970, Paraná, Brazil e-mail: [email protected]

(2)

Introduction

On November 5th, 2015, the biggest disaster occurred in Brazilian mining: The Fundão mining waste dam collapsed, releasing approximately 50 million tons of sludge, destroying Bento Rodrigues, a sub-district of Mariana in Minas Gerais state, Brazil (Lopes, 2016; Lima et al., 2020). The breakdown caused the death of 19 people and more than 250 injured (Lima et al., 2020). The mining sludge contaminated and destroyed the whole watershed. The main basin rivers, Gualaxo do Norte, Do Carmo, and Doce, were hugely affected, in addition to a vast extent of the Atlantic Ocean coastline (Cionek et al., 2019). The advance of the sludge waterproofed the ground. After 6 years of the catastrophe, little has been done to restore the basin. It is possible to find mining waste in water, plants, fishes, and other living beings, affecting human life (Matos et al., 2022; Foesch et al., 2020;

Tuncak, 2017). The Bento Rodrigues area is now under water. However, the sludge continues to release potentially toxic elements (PTE) into the water column.

The sludge environmental risk has been demonstrated in literature due to the amount of PTE after the Fundão’s disaster. Elements of the ATSDR (2021) Pri- ority List: Ag, As, Cd, Co, Cu, Cr, Hg, Mn, Pb, Sb, Sn, V, Zn, lanthanides, and actinides had their concentration increased by up to 26 times after sludge release and are above the maximum values of the Brazilian regulation for soil and water (Guerra et al., 2017; Gomes et al., 2017; Yamamoto et al., 2022).

Human diseases such as genetic mutation and cancer have been linked to environmental and social risks generated by mining waste (Hemond & Fechner-Levy, 2000; He et al., 2021). PTE has also been pointed out as interferent in plant and fish development (Gomes et al., 2017; Said et al., 2019).

To the best of our knowledge, there are no studies relating environmental risk to PTE mobility, geochemical environment, and effects along the Doce River Basin. Environmental risk assessment is related to mobility. Thus, short- and long-term impacts must be evaluated considering the soil and sediment properties that affect the mobility such as temperature, pH, and redox potential (Sahuquillo et al., 2003; Said et al., 2019; Shaheen et al., 2020). Geochemical fractions are valuable for understanding PTE’s chemical behavior and bioavailability because the total

concentration is insufficient to predict environmental impacts (Gabaròn et al., 2019; Fernandez-Ondono et al., 2017; Khadhar et al., 2020). The modified European Community Bureau of Reference (BCR) offers information about distribution, availability, and toxicity of elements in soil and sediment, including three distinct fractions: acid-soluble, reducible, and oxidizable (Ure et al., 1993; Ates et al., 2020; Oral, 2019). The residual fraction has also been considered in different circumstances (Kovacs et al., 2018; Tong et al., 2020). Usually, elements associated with soluble and reducible fractions are thought more harmful to the environment, followed by the oxidizable, due to the availability (Tessier et al., 1979; Rinklebe &

Shaheen, 2014; Baran & Tarnawski, 2015). Although the residual fraction is less available, environmental conditions such as pH, Eh, and plant root action can increase PTE release to the environment (Queiroz et al., 2018).

Some risk assessment indices have been proposed to understand and better dimension the environmental impact, relating total concentration and geochemical fractions. The Risk Assessment Code (RAC ) describes water contamination based on the acid-soluble fraction, rating risk codes 1 to 5 (Perin et al., 1985). The contamination degree ( C_d ) and the contamination factor ( C_f ) are related to a background concentration ( C_b ) from a reference local. C_d is the sum of C_f indices and helps assess local contamination (Hakanson, 1980). The potential ecological risk factor ( E_R ) and the Global Risk Index (GRI) include mobility by the toxic response factor. E_R is calculated from total concentration, and GRI from concentration in the geochemical fractions (Ikem et al., 2003; Zhao et al., 2012).

Although regional surveys have been developed, the basin has not been considered a whole, and therefore the results cannot be applied to a global understanding. Supposing a lasting environmental impact, with the mobilization of PTE throughout the basin and over the years (Frachini et al., 2021), we seek to assess the environmental risk in the Doce River Basin post-dam breakdown, based on geochemical fractions by applying several indices related to PTE’s mobility. For that, soil and sediment were sampled at nine points of the Doce River Basin as an environmental unit and submitted to BCR sequential extraction procedures. Knowledge about the mobility of ions in the basin and its consequences for the environment,

(3)

agriculture, quality of life, and the economy will broaden the understanding of the disaster and assist in environmental regulation.

Material and methods Study area

The Doce River watershed is located in Southeast- ern Brazil, passing through the states of Minas Ger- ais (MG) and Espírito Santo (ES), Brazil. The basin extends for approximately 850 km, from Espinhaço mountain range in MG to Linhares city in ES, flow- ing into the Atlantic Ocean. About 3.5 million people live around and are dependent on the basin for water and food supplies (Reis et al., 2017). Part of the Iron Quadrangle (IQ) is located in the Doce River Basin and is one of Brazil’s most important ore sources. Mariana (MG) is included in IQ dominion (IBAMA, 2015; Guerra et al., 2017). Large compa- nies are settled in the region. The Fundão Dam breakdown affected the entire watershed, including a vast coastline of the Atlantic Ocean, and potentially toxic

elements have been found in water, soil, and sediment (IBAMA, 2015; Segura et al., 2016; Gomes et al., 2017; Guerra et al., 2017).

Soil and sediment sampling

Nine points were sampled for soil (SL) and sediment (SD) in two campaigns (March and August 2016) throughout Doce River (Fig. 1). Unaffected riverbank soil and sludge-affected river channel sediment were sampled to take the basin as an environmental unit. A preserved reference point (P0) was chosen in Water- fall Swallows Park in Espinhaço Mountain Range.

The sampling points (P) were selected to keep a distance of approximately 80 to 100 km. P0 is in an unaffected area in the Municipal Natural Park Waterfall of the Swallows. The local biomes are Atlantic Forest and Cerrado, with low anthropogenic activity. P1 is in the Gualaxo do Norte River, a Doce River affluent. There was an important hydro- electric power station, which was turned off due to the sludge spill. P2 is located in Bento Rodrigues district, destroyed by a massive sludge amount.

Nowadays, the rubble of a large region of Bento

P0

P2 P1 P3

P5

P4

P6

P8 Sampling sites P7

Doce River Mouth Sampling path Doce River

Fig. 1 Doce River Hydrographic Basin. Font: Google Maps, 2015

(4)

Rodrigues is covered by water from a dam built after the disaster. P3 is in the Doce River, about 200 km from P2. P4, P5, P6, and P7 are near Ipatinga, Gov- ernador Valadares, Conselheiro Pena, and Colatina towns, respectively. These sampling points receive extensive interference from human activity. P8 is an estuarine environment in Linhares town, Espirito Santo State, where the Doce River flows into the Atlantic Ocean. The distance of 80 to 100 km was adjusted so that the sampling location corresponded to the previous analysis sites of government agen- cies and accessibility for collection.

Geographic coordinates (Table SM1) are in Sup- plementary Material (SM). The riverbank soil was sampled with an auger at 20-cm depth. The sludge was sampled superficially in the Bento Rodrigues district. Sediment was sampled in 7.5-cm-diameter PVC tubes covered with decontaminated polyethylene film. The samples were sliced from 0 to 5 cm and 5 to 10 cm in depth, homogenized, dried in an air-circle oven at 50^◦ C for 72 h, sieved through 2.0 mm, and stocked in polyethylene flasks. All samples were collected in triplicate.

Characterization of the samples

Soil and sediment samples were characterized for pHH₂O , pHKCl , cation exchange capacity (CEC), texture, electrical conductivity (EC) (Pavan et al., 1992;

Claessen et al., 1997), organic carbon (OC) content by TOC-V- CSH/CSN, major elements by Energy Dispersive X-Ray Fluorescence (Shimadzu, EDXRF- 720), Rh anode X-ray tube and Si(Li) detector, Ti-U and Na-Sc channels at 50 kV, 30 𝜇 A, 100 s of exci- tation time in air atmosphere and 5-mm collima- tion incident beam. The redox potential (Eh; mV) for 10:1 water-saturated soil and sediment samples was determined by the sum of direct measure (Edir ) and reference (Eref ) potentials. E dir was measured in suspension from Pt and Ag/AgCl combined electrode and E ref from Ag/AgCl KCl saturated reference electrode at a given temperature (Rabenhorst et al., 2007). The samples were submitted to microwave digestion (Milestone High-Performance Microwave Digestion-Ethos One) to quantify pseudo-total element by Inductively Coupled Plasma Mass Spectrom- etry (ICP-MS, Varian 820-MS, USA). Instrumental parameters for microwave digestion and ICP-MS are shown in Tables SM2 and SM3.

Sequential extraction

In order to evaluate the environmental mobility, PTE were sequentially extracted from the soil and sediment samples based on the modified BCR procedure, obtaining three geochemical fractions: acid-soluble (F1), reducible (F2), and oxidizable (F3) (Ure et al., 1993). The extracts were analyzed by ICP-MS using the Expert Software v2.0 b87. The ratio [F1+F2+F3]/

total concentration is called the Potential Mobile Fraction (PMF) and represents the amount mobilized in response to environmental changes. In addition, a fourth residual fraction (F4) was obtained by the difference between PMF and the pseudo-total concentration (Rinklebe & Shaheen, 2014). A three- concentration recovery test was performed for each geochemical fraction to determine the precision and accuracy and to assess the potential mobility of Al, Ag, As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sb, and Zn in the studied samples.

Statistical analysis

Statistical analysis was carried out by Principal Com- ponent Analysis (PCA) and Pearsons’ correlation coefficient to quantify relationships between the physical and chemical properties of the samples and the geochemical fractions. The data set was processed in the MatLab^Ⓡ 7.10.0 mathematical simulator (Bertoldo et al., 2022).¹

Risk assessment index

The PTE risk assessment is most successfully stated by comparing several indices from the literature (Hakanson, 1980; Ikem et al., 2003; Zhao et al., 2012;

Rinklebe & Shaheen, 2014). Each index provides a different rating on the environment, disaster, region, or population affected by the PTE. In addition, a set of indices allows for a better and more realistic understanding of environmental risk.

1 The main numerical results in this section can be generated from the MatLab script available at https:// data. mende ley. com/

datas ets/ bb6st kvw3j/1, Mendeley Data, V1, https:// doi. org/ 10.

17632/ bb6st kvw3j.1.

(5)

The Risk Assessment Code (RAC ) is calculated using the mobile fraction F1 and indicates water contamination, as shown in Eq. (1) (Perin et al., 1985):

The Contamination Factor ( C_f ) and the Contamina- tion Degree ( C_d ) use the total PTE concentration ( C_n ) and a background concentration ( C_b ) from a reference local as shown in Eqs. (3) and (2). Herein we consider the pseudo-total PTE concentration in SL0 as the background. C_d is the sum of the C_f values (Hakanson, 1980).

where

Equation (4) describes the Potential Ecological Risk Factor ( E_R ) including the environmental risk C_f and the toxic response factor ( t_r ) as impact on living beings (Hakanson, 1980):

where t_r values were determined in literature for As (10), Cd (30), Cr (2), Cu (5), Pb (5), and Zn (1) (Hakanson, 1980), Ni (5) (Remeikaitè-Nikienè et al., 2018), Mn (1) and Co (5) (Zheng-Qi et al., 2008), and Sb (10) (Zhao et al., 2012), and calculated in this study for Ag (6) and Al (1), according to Hakanson (1980).

The Global Risk Index (GRI) allows us a local multi- elementary analysis, including t_r as a time-retention assessment, shown in Eq. (5) (Zhao et al., 2012):

Results and discussion Sample characterization

The soil and sediment samples are characterized in Tables SM4 to SM8. Texture in Table SM4, evaluated as suggested by Marshall (2003) for soil particle-size (1) RAC= F1

F_total100%

(2) C_d =

n

∑

i=1

C⁽ⁱ⁾_f ,

(3) C_f = C_n

C_b

(4) E_R⁽ⁱ⁾ =t_r⋅C⁽ⁱ⁾_f ,

(5) GRI=

n

∑

i=1

t⁽ⁱ⁾_r

(F1 + F2 + F3 F4

)⁽ⁱ⁾

distribution, varies from sandy to sandy clay loam for the SL samples. The sludge (SG) is sandy loam. Com- paring soil and sediment samples in Tables SM4 and SM5, SD had lower OC than the SL samples, probably due to direct SG interference, except in P7 and P8, which receive anthropogenic waste deposition. SD and SG showed similar OC (0.041%) as a response to the sludge release in the basin, especially in the disaster vicinity, with effects on infertility or even the soil death (Arenas-Lago et al., 2014; Santolin et al., 2015). Urbanization caused the highest amount of OC (2.80%) in SL5. Although the literature has indicated a decrease in OC amount comparing results pre- and post-dam disaster (Silva et al., 2016), OC and clay tended to stabilize and increase over the Doce River Basin. That condition also was observed by Dick et al.

(2009). Notably, the high CEC value (118 meq kg⁻¹ ) in SL5 can be attributed to the higher OC content.

The direction of a redox reaction and its impact on the environment can be evaluated by the Eh (Nordstrom

& Wilde, 2005; Fiedler et al., 2007; Husson, 2013).

The Eh results ranged from 227 to 662 mV, indicating high oxidation potential for all samples, affecting the fractions.

The pHH₂O of soil and sediment is related to PTE mobility and environmental risk (Sintorini et al., 2021). Herein, the soil pH varied with the characteristics of the sampling areas (Table SM4). The soil samples were classified according to the Brazilian system of soil classification (Santos et al., 2006). SL0, SL2, and SL4 are acidic, confirming high weathering and oxisol classification characteristics. Despite being classified as entisol, poorly weathered and more alkaline, SL8 was more acidic, indicating external interference. The oxisols SL1 and SL7 were less acidic than expected. The SL1 has possibly received the sludge, and the SL7 is located on a farm. The oxisols SL3, SL5, and SL6 were neutral and consistent with their class (EMBRAPA, 2006, 2022). The sediment, in Table SM5, showed a neutral to alkaline character, except for the samples SD0, SD7, and SD8. SD0, the reference, is acidic and is in an unaffected region of the basin. Although SD7 and SD8 received a large amount of sludge, they are 600 km from the origin of the disaster and may have preserved local characteristics. SG is alkaline because of the NaOH used in the mining process (Jordao et al., 1997; Dick et al., 2009;

Silva et al., 2016). Another significant parameter is the pHKCl , which expresses the surface susceptibility

(6)

to sorb negative or positive species (Sposito, 1981;

Noh & Schwartz, 1989; Ramos et al., 2018). The soil and sediment samples presented negative surface charge, with pHH₂O > pHKCl , favoring the retention of cations. This result agrees with that found for the region (Santos et al., 2006; Santolin et al., 2015). The electrical conductivity measures the concentration of ions in the soil’s solution once the salts dissolved in soil water carry electrical charges (USDA, 2011;

Corwin, 2003). For Doce River soil samples, the EC ranged from 0.08 to 1.10 dS m ⁻¹ , indicating the non- saline class of the soils.

The results of EDXRF in Table SM6 show Fe, Al, and Mn as the major elements found in the samples and agree with the literature on mining tailing (Silva et al., 2014; Kiptarus et al., 2015). The pseudo-total concentration determined by ICP-MS in Table SM7 was lower for Cr, Cu, Cd, Pb, Ni, Zn, As, Ag, and Co in SL than in SG samples. The SG pseudo-total concentration extrapolated the Brazilian regulation pre- vention value (PV), a limit concentration of a given substance in the soil that allows the performance of its primary functions (CONAMA, 2009), in 265, 161, and 14 times for Ag, Cd, and As ions, respectively.

Mn and Al are in higher concentrations because they are biogenic for the Doce River Basin. It is material to note in Table SM8 similar pseudo-total concentrations in the SD and SG samples since the sludge from the dam directly affected the river bottom and

the banks. The sludge reached 15 m on the riverbank, covering vegetation, villages, and large tracts of land.

Sequential extraction

The distribution of Cr, Ni, Cu, Zn, Cd, Pb, Mn, Al, As, Ag, Co, and Sb in the geochemical fractions F1, F2, F3, and F4 of the SG sample is shown in Fig. 2.

The other samples’ distribution is in Figs SM1 to SM12. In addition, the potential mobile fraction (PMF) is shown in Fig. 3. Attention must be paid to Mn, Pb, Sb, and Al, which present the higher PMF:

95, 81, 100, and 17%, respectively, increasing the related environmental risk. Mn suffered the most significant effect in terms of mobilization in the basin.

The samples affected by the disaster mobilized 95 times more Mn than the reference (P0). Besides the high mobilization, such PMF values indicate release in different geochemical conditions. The prevalence of the residual fraction indicates strong interaction with soil matrix, biogenic origin, or rapid incorporation in the matrix by interlamellar substitution or precipitation (Coutris et al., 2012a, b). Even though F4 is higher, it must be considered that the sequential extraction represents a geochemical distribution at one moment, and the environmental conditions may favor the gradual release of elements over the years.

Furthermore, the wide range of elements and the sum of mobility in each fraction can harm man and nature.

Fig. 2 Geochemical fractions in the sludge sample

(7)

For better understanding, the results were separated by the prevalence of the PTE in the fraction.

F1 — Acid‑soluble fraction

F1 includes elements precipitated with carbonates or weakly bound to the matrix: the most exchange- able, highly toxic, and bioavailable (Matong et al., 2016). As the environment’s acidity is responsible for the mobilization, F1 becomes more critical as the pH decreases. The most acidic points, P0, P7, and P8, favor the release of Ni, Zn, Cu, Cd, and Ag ions and deserve attention regarding the risk imposed by F1. The high Cu-F1 proportion in SG makes Cu ions highly available to the environment.

The PTE distribution in the soil and sediment samples indicates that Cu and Cd (Figs SM3 and SM5) were mainly associated with F1, especially for the affected areas. Although the predominance of Cu in F1 is not well established in the literature, the soil OC may have favored the Cu-F1 association (Baran

& Tarnawski, 2015). In turn, Cd-F1, well established in the literature, predominated (Rinklebe & Shaheen, 2014; Baran & Tarnawski, 2015; Bo et al., 2015;

Gabarón et al., 2017; Kovacs et al., 2018). Since the results showed Cd-F3 absent, soluble OC complexes may be being counted for F1 (Sungur et al., 2014).

Higher temperatures in the extraction method may

have masked the Cd-F3 results. The nearly filled 3d Cd orbitals in the most probable oxidation state for the pH and Eh sample conditions, Cd²⁺ (Pourbaix diagram) (Takeno, 2005), can make it difficult complexation with OM ligands (Huheey et al., 1993).

Therefore, F1 is the most critical fraction for cadmium mobility assessment in the Doce River Basin.

The silver in Fig SM10 is considerable in F1, and there may be rapid incorporation into the matrix by the K ⁺ vs Ag⁺ interlamellar exchange or precipitation with OM, according to Coutris et al. (2012a, b). In addition, the bulk of the PMF in F1 point to the inser- tion of Mn in the food chain.

F2 — Reducible fraction

Reducible fraction covers the elements linked to iron and manganese oxides, whose release is regulated by the reduction processes (Matong et al., 2016). Pb, Mn, and Co ions are dominant, and the proportion of Al was considerable in F2. As reported in the literature, Pb significantly interacts with Fe-Mn oxides (Rinklebe &

Shaheen, 2014; Sungur et al., 2014; Baran & Tarnawski, 2015; Sungur et al., 2015; Bo et al., 2015; Gabarón et al., 2017), and its immediate and gradual release over the years will possibly be controlled by reduction processes in the Doce River Basin. These results may be explained by Pearson’s hard and soft acids and bases theory. O ²⁻ as

Fig. 3 Potential mobile fraction (PMF) determined by geochemical fractions

(8)

a hard base interacts strongly with Mn²⁺ , a hard acid, followed by so-called intermediary acids, such as Pb²⁺ and Co²⁺ (Miessler et al., 2014). Due to the matrix structure and lower reduction potential, prior studies have demonstrated the importance of F2 in manganese mobilization.

Several reports have shown that manganese is the most mobile and bioavailable element, easily inserted into the food chain (Arenas-Lago et al., 2014; Sungur et al., 2014;

Kumar & Ramanathan, 2018; Frachini et al., 2021).

Although Mn proved highly mobile (Fig SM7), the lower Mn-PMF for SG is explained by the higher sample pH caused by the mining process (Grygo-Szymanko et al., 2016). The fact that Al and Mn are part of the matrix (Frachini et al., 2021) can be related to a significant impact in the mobilization of other elements. Therefore, understanding the behavior of the matrix is crucial for establishing the risks in the Doce River Basin.

As observed in Fig SM11, samples from SD1 to SD8 showed a higher residual fraction for pH above 4.0. According to Yousefi et al. (2015), such pH conditions make pyritization a limiting process in cobalt release. SG was an exception, with a similar distribution of Co in F1, F2, and F3, as the increase in pH promotes its incorporation into aluminosili- cates (Bario-Parra et al., 2018). Other authors have reported the association of cobalt with residual or reducible fractions (Coutris et al., 2012b; Andreas

& Zhang, 2016; Gao et al., 2017; Budakoglu et al., 2018), describing Fe-Mn oxides as fundamental for the mobilization of cobalt in soil and sediment.

F3 — Oxidizable fraction

Oxidation processes play an essential role in mobilization, as observed for Cr, Al, As, Ag, and Sb ions in Figs SM1, SM8, SM9, SM10, and SM12, respectively. The Eh positive makes F3 essential for understanding PTE mobility across the basin and assessing environmental risk. Arsenopyrite in the soil and sediment samples contributes to the PTE-F3 increase. Although Cr ion is considered a hard acid, a strong Cr-F3 association has been described by other authors, even when Fe-Mn oxides content is high (Sungur et al., 2014; Baran & Tarnawski, 2015;

Sungur et al., 2015; Kovacs et al., 2018). Thus, it can be inferred that the energy of the Cr LUMO orbitals is low enough for the formed Cr-OM complexes to prevail in the geochemical distribution (Miessler

et al., 2014). Indeed, a strong interaction Cr-OM can be observed in Fig SM1. Despite the abundant Fe-Mn oxides in the sludge, the low Cr-F2 ratio contrasts with the high Cr-OM. F3 is, therefore, the most critical fraction to understanding chromium mobility in the basin. Lower Mn LUMO energy also indicates a stronger association with F3. However, the minor contribution of the oxidation processes for Mn mobility in Fig SM7 is probably due to the instability of Mn-OM complexes or the low OM content (Arenas- Lago et al., 2014; Moreira et al., 2016).

Even though the literature indicates a more significant association of Al with the reducible fraction, the influence of OC on PMF distribution has been reported (Soliman et al., 2018). F3>F2>F1 observed in Fig SM8 shows the importance of OC in Al distribution on the fractions. The oxidizable fraction (Al- F3) may be related to the formation of insoluble complexes at pH above 5.5 and the release of OM from the soil particles, inhibiting the interaction Al-oxides (Yvanes-Giuliani et al., 2014; Palleiro et al., 2016;

Palleiro et al., 2018). Aluminum 3d orbitals, available for Al-OM complexation, potentiate Al-F3 (Miessler et al., 2014). Thus, oxidation processes can be critical for Al mobilization in the basin.

As and Sb, in Figs SM9 and SM12, are primarily associated with the oxidizable fraction, with influence from the pyritization processes due to their similarity (Kim et al., 2014; Shaheen et al., 2017; Kumar

& Ramanathan, 2018). Our results are consistent with the role attributed to Fe-Mn oxides in the arsenic and antimony mobilization (Ma et al., 2015; Xu et al., 2017), associating F2 and F3. The SG, alkaline and crystalline matrix, can promote the incorporation and immobilization of As and Sb by complexation.

Oxidation of OM and sulfides appears as the most critical Ag mobilization process in Fig SM10. Pear- son’s theory can explain the predominance of Ag-F3:

soft acid and base, Ag⁺ and S ²⁻ , potentiate the interaction with F3 (Borovec, 1996; Miessler et al., 2014).

In turn, the oxidizable fraction was the most important for copper mobility in P1 and P2. OM may have influenced the high Cu solubility and carbonate affin- ity. Pb-OM and Co-OM interactions observed in Figs SM6 and SM11, resulting in mobilization effects, have also been observed by other authors (Sherene, 2010;

Nenati et al., 2011; Beesley et al., 2014; Arenas-Lago et al., 2014).

(9)

General distribution in the geochemical fractions To the best of our knowledge, all fractions are relevant to understanding the mobilization and assessment of environmental risk in the Doce River Basin.

However, some potentially toxic elements do not have a defined predominance in a geochemical fraction, as shown for Ni and Zn in Figs SM2 and SM4. No direct relationship was observed between the content of Fe-Mn and F2 oxides, nor of F3 and OC. The interaction with a moiety depends on the competition for binding sites and matrix composition. Although LUMO orbitals for Ni and Zn are available, the complexation likely is limited by competition with other elements of lower LUMO energy, such as Cr. In addition, studies have reported Ni-F1 and Zn-F1 interaction when the OM content is low (Sungur et al., 2014, 2015; Baran & Tarnawski, 2015; Gabarón et al., 2017).

The sequential extraction showed more significant mobilization potential for Mn, Pb, and Sb and less for other PTE. It is worth noting that these results do not consider extreme conditions of acidity, reduction or oxidation, anthropogenic incorporation of OM, and

the occurrence of geochemical processes over the years, which would impact the environmental risk.

The mobilization of PTE from the sludge is low when analyzed punctually. However, a global view of the geochemical fractions along the basin indicates an increase in mobilization, as exemplified for Mn in Fig SM7. As geochemical fractions favor metal mobilization, the risk depends not only on sludge release but on exposure to basin conditions.

Statistical analysis

The relationships between soil and sediment samples’ physical and chemical properties and geochemical fractions were explored by principal component analysis. The first three principal components (PC) explain 64.23% of the variance (27.80% PC1, 23.12%

PC2, and 13.31% PC3) and highlight the anthropogenic factor. The distribution of PTE geochemical fractions, pseudo-total concentration, OC, Eh, and pH, and loadings for the first two PC is shown in Fig. 4. According to the proximity of the samples in PC1 vs PC2, six relevant groups were considered: (i) G1: SD0.1, SD0.2, SL0; (ii) G2: SL1, SL2, SL6, SL7,

-0.3 -0.2 -0.1 0 0.1 0.2 0.3

PC1 (27.8016%) -0.25

-0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.25

PC2 (23.1155%) ^Sb-PT

Ni-F2

Mn-F2 Mn-PT

Co-F2 pH

Pb-F2 Cd-F2

Mn-F3

Pb-F3

Ag-F3 Al-F2

Co-F1 Zn-F2

Zn-F3 Ag-PT

Mn-F1

Al-F3 Zn-F1

Cd-PT Co-PT Pb-PT

Ni-PT Cr-PT Cu-PT

Al-F1

OC

Co-F3 Cu-F2

Ni-F3 Ag-F2

Ni-F1

Cu-F3 Zn-PT

Cd-F1

Cr-F2 Cu-F1

Ag-F1

Pb-F1

Al-PT Eh

As-F3

As-PT

Cr-F3

Cr-F1 Sb-F1Sb-F2

Sb-F3 As-F1

As-F2 SL8

SD2.1

SL2 SL1 SL6

SD1.1 SD1.2

SG SD2.2

SL3

SD8.1 SD8.2 SD4.2

SD7.2 SD7.1 SD6.2

G1

SD6.1 SD5.2 SD4.1

SL5 SL0

SD0.2 SL7

SD0.1

G2

G3

SD5.1 G4

G5

SL4G6 SD3.1

SD3.2

Fig. 4 Principal component analysis for PTE and fractions, pH, and OC. Triangle marker is for G1: ▴ , diamond for G2: ⧫ , square for G3: ▪ , circle for G4: ∙ , pentagram for G5:★ , and asterisk for G6: ∗

(10)

SL8; (iii) G3: SD1.1, SD1.2, SD2.1, SD2.2, SD3.1, SD3.2, SG; (iv) G4: SD3.2, SD4.1, SD5.1, SD5.2, SD6.1, SD6.2; (v) G5: SD4.2, SD7.1, SD7.2, SD8.1, SD8.2; (vi) G6: SL3, SL4, SL5. Samples from areas closer to the disaster are separate from those further away, highlighting the great impact caused by mining sludge on the Doce River Basin sediment. The groups present sedimentary contamination similar to mining sludge (SG) in both the superficial and deeper layers, besides the similarity in the sediment- SG composition. In addition, impacts have been geo- graphically expanded with increasing contamination over the years due to PTE-SG leaching. SD1 and SG are in G2, but SL1 does not appear to have been contaminated by the 2015 Fundão dam breakdown, and the similarity may be a consequence of prior mining sludge contamination.

It is worth noting the distribution of samples from upstream to downstream through PC1 in Fig. 4. The Upper Basin sampling points, closest to the disaster, are at the opposing end of PC1 and are followed by the Middle Basin points to the Lower Basin points on the positive side of PC1. Samples in the PCA lower quadrants apparently do not receive interference from the mining sludge. Considering that the dataset was obtained from sampling 5 months after the disaster, it is possible to note an evolution of the PTE geochemical fractions (F1, F2, and F3) throughout the basin, with higher concentrations in the Middle-Doce River, reaching maximum values at the end of the Basin (P7 and P8).

G1 and G2, constituted by the reference samples (P0) and mainly the soil samples, probably were not affected by the 2015 disaster. These samples are Eh- dependent and include a more significant effect of the three geochemical fractions associated with As and Sb. Geochemical fractions of weakly chelating elements as As, Sb, and Pb are relevant to outer- sphere cation bridging (Kleber et al., 2015). Cati- onic bridges are formed by coordinating an anionic functional group of organic matter in the sorption of polyvalent cations on the mineral surface. The mechanism involves H-bonds, inner- and outer- sphere complexes, the aromatic system 𝜋 electron of the organic ligand, and the cation-𝜋-interactions. Cd did not contribute to such interactions because Cd-F3 was not quantifiable. The two first Pb fractions also are significant for G2.

G3 and G4 samples show the influence of pH and pseudo-total PTE concentration. The distribution of the samples clearly shows the discrepancy between the pseudo-total PTE concentration and the geochemical fractions. Mn-F2, as a sludge structural part, and Ag-F1 cluster the samples collected closer to the dam breakdown (G3) (Frachini et al., 2021). Emphasis should be given to the increase in PTE concentration in urban areas related to the G4 sediment samples.

The OC significantly influences the Middle-Doce River sediment (G6) and the Lower-Doce River soil (G5), probably due to the increasing urban activity. Additionally, the OC is important for 2+ and 3+

cations in F2 and F3. Regarding the OC and mineral Fe-Mn oxides in the soil, the probable formation of polyvalent cation bridging by inner-sphere complexation can explain the eased interaction of Al, Cu, Cr, Pb, Zn, Ni, and Mn with F2 and F3. SL3, SL4, and SL5 samples have F3 predominance in geochemical distribution overlapping OC. Cation bridging also is relevant in these samples.

Pearson’s correlation analysis was carried out to investigate which soil/sediment property is the most important for each element mobilization. Signifi- cant positive correlations among various elements in the studied area are shown in Tables SM8 to SM12.

According to Pearson’s coefficients, the pseudo-total concentration of Cr, Ni, Cu, Zn, Cd, Pb, Co, As, and Ag is significantly correlated (r>0.7) with each other, indicating the same origin. Although Al and Sb did not correlate with the other elements, correlations with the fractions were observed: Al-PT with Cr-F2, Cr-F3, Ni-F1, Zn-F1, Zn-F3, Mn-F1, and Al-F3; Sb-PT with Pb-F2. Mn-PT showed a strong correlation with Mn-F2 and Mn-F3 since Mn is part of the structure of oxides and sulfides. The physical and chemical characteristics of the samples (pH, Eh, and OC) were not determinants for the geochemical fractions, as expected. Due to the possibility of coexistence of species, Eh presented a correlation with As-F3, Sb-F2, and Sb-F3. OC correlated with Cu-F3, Zn-F3, Zn-F2, and Al-F2. Cu, Zn, and Al may be associated with the OC-mineral metal bridges. No significant contribution of pH for geochemical fractions in the Doce River Basin was observed. The results show that potentially toxic elements can influence each other’s mobility, establishing competition in surface reactions.

(11)

Environmental risk assessment

Figures 5 and 3 exhibit the global indices. The individual indices risk assessment code (RAC ), contamination factor ( C_f ), and potential ecological risk factor ( E_R ) are presented in SM (Figs SM15 to SM17). RAC is an individual index related to water bodies contamination. From the RAC , Mn is the most harmful element, presenting medium to very high risk, reaching 73% Mn-F1 in SD7 and 31% Mn-F1 in SL6. Other authors also found the same Mn behavior (Sungur et al., 2014). Additionally, the risk for Mn increased from the breakdown, P1 and P2 (1%) to P8 (54%).

The lower risk for zinc in unaffected soil, compared to SG and sediment, is a consequence of SG alkaline properties (Kahkha et al., 2017). The interference of OC in RAC may depend on the formed complexes’

solubility, as for Pb and Ni, whose RAC is lower in affected than unaffected samples, because of the decrease in OC content (Liang et al., 2017).

Analysis of C_f , an individual concentration index, exhibited enrichment for all sampling points when compared to the respective soil sampling point. The general C_f order was: Cd>Co>Ni≈Ag>Pb>Zn≈ Cu (very high) and Cr>Mn>Al>As (moderate). Atten- tion is given to cadmium, because of the greater contamination degree ( C_d ) for samples affected by the breakdown, with an increase of up to 27 times.

As mentioned in the literature, a decrease in the background concentration increases C_d value for Cd and the environmental risk (Remeikaitè-Nikienè et al., 2018; Rizo et al., 2015). Associated to C_f , the C_d index in Fig. 5 increases due to SG leaching in Doce River Basin sediments. The affected samples and SL1 were characterized by a very high contamination degree, while unaffected soil and sediment presented moderate to low degrees. The unexpected result for SL1 is a consequence of the similarity with SG in the PCA analysis, indicating previous contamination of SL1 point by mining tailing.

The risk evaluation by E_R includes individual toxicity and follows the order: Cd>Co>Ag>

Ni>Pb>Cu>As>Cr>Zn≈Sb≈Al≈Mn. Although several reports have found a standard between E_R and toxic response factor ( t_r ) (Guo et al., 2010; Zhao et al., 2012), the Doce River Basin did not follow a standard. Higher risks were expected for As and Sb, pointing out the biogenic origin in sampling points and the importance of the pseudo-total concentration in the E_R evaluation.

Toxicity from geochemical fractions is evaluated by the global risk index GRI for a set of elements (Figure SM18). Although low to very high risk lev- els are not entirely validated by Zhao et al. (2012), a global environmental risk assessment is possible from the toxic response factor. For GRI, the affected

Fig. 5 C_d determined by pseudo-total concentrations

(12)

sampling points exhibited a lower risk than unaffected due to the use of many PTE with low potential mobile fractions. In addition, elements such as Mn, with high PMF, have low t_r , generating a low GRI. The risk assessment mainly depended on fractional distribution, enrichment degree, and the toxic response factor of the PTE. The fractional distribution contributes mainly to the Mn, Sb, and Pb mobility, while the enrichment degree contributes to Cd mobility, followed by Co, Ag, Ni, Pb, Zn, and Cu, and the toxic response factor mainly to Cd, Co, and Ag mobility.

Conclusions

The dam failure caused a significant PTE enrichment in the Doce River Basin. Although no extreme conditions were observed, the research pointed to the primary mobilization of Mn, Pb, and Sb regarding the effects of geochemical fractions. The impact of the sludge was evident by the PCA separation of sediment and soil along the basin since the characteristics of the sludge overlap with those of the river sediment. The basin favors the PTE mobilization and reinforces the idea that the environmental risk evaluation depends on two main parameters: the enrichment factor, given by the highest C_f and C_d in the sediment, and the geochemical distribution. Thus, analyses of PTE concentration associated with organic content, Eh, and pH are preponder- ant to assess the environmental risk of mobilization and contamination over the basin. The environmental risk can be used to develop interventions for managing solid waste, such as the sludge spilled into the basin.

While Brazilian mining is fundamental on the world stage, the fall in commodity prices puts pressure on the mineral production sector, reducing investments in the most sensitive part, the containment and tailings treatment. Sequential dykes, the least reliable, are the most common in sludge containment dams. Thus, the construction and inspection of dams must be improved to avoid irreparable environmental destruction caused by ruptures and the consequent mobilization of PTE by tailings released into the basin. From our findings, several fronts to repair the damages can minimally be considered: allocation of financial resources for treatment and adequate containment of urban and industrial waste to avoid PTE mobilization, environmental actions to recompose plant and animal life in the basin, in

addition to restitution of financial losses to the affected population. The scope and importance of this study are demonstrated when its conception can, ideally, be trans- ferred to other environmental units impacted by the tailings of the ruptured mining dams.

Acknowledgements The authors would like to thank Prof.

Dr. Cimélio Bayer from Soil Science Department, Federal Uni- versity of Rio Grande do Sul, Brazil, for the TOC analysis, and the Physics and Chemistry Laboratory of Soils, from Agron- omy Department, State University of Londrina, Brazil.

Author contribution Bertoldo, L.: conceptualization, methodology, investigation, mathematical modeling, writing — reviewing and editing. Ribeiro. A.: conceptualization, methodology. Reis, C.E.S.: conceptualization, methodology, investigation. Frachini, E.: investigation. Kroetz, B.L.: investigation.

Abrão, T.: software, mathematical modeling, data curation.

Santos, M.J.: conceptualization, methodology, mathematical modeling, writing — reviewing and editing, supervision, pro- ject administration.

Funding This study had no financial support, except for a fellowship from the Brazilian Coordination for higher Educa- tion Staff Development (Capes).

Availability of data Numerical results are available at https://

data.mendeley.com/datasets/bb6stkvw3j/1, Mendeley Data, V1, doi: 10.17632/bb6stkvw3j.1.

Code availability Not applicable

Declarations

Ethics approval Not applicable Consent to participate Not applicable Consent for publication Not applicable

Competing interests The authors declare no competing interests.

References

Andreas, R., & Zhang, J. (2016). Fractionation and environmental risk of trace metal in surface sediment of the east China sea by modified BCR sequential extraction method.

Molekul, 11, 42–52. https:// doi. org/ 10. 20884/1. jm. 2016.

11.1. 193

Arenas-Lago, D., Andrade, M. M., Lago-Vila, M., Rodrígues- Seijo, A., & Vega, F. A. (2014). Sequential extraction of heavy metals in soils from a copper mine: Distribution in geochemical fractions. Geoderma, 230–231, 108–118.

https:// doi. org/ 10. 1016/j. geode rma. 2014. 04. 011

(13)

Ates, A., Demirel, H., & Mergul, N. (2020). Risk Assessment and Chemical Fractionation of Heavy Metals by BCR Sequential Extraction in Soil of the Sapanca Lake Basin, Turkey. Polish Journal of Environmental Studies, 29, 1523–1533. https:// doi. org/ 10. 15244/ pjoes/ 101609 ATSDR. (2021). Toxicological Profiles. techreport Agency for

Toxic Substances and Disease Registry. Retrieved from https:// www. atsdr. cdc. gov/ toxpr ofile docs/ index. html Baran, A., & Tarnawski, M. (2015). Assessment of heavy metals

mobility and toxicity in contaminated sediments by sequential extraction and a battery of bioassays. Ecotoxicology, 24, 1279–1293. https:// doi. org/ 10. 1007/ s10646- 015- 1499-4 Bario-Parra, F., Elío, J., de Miguel, E., Garcia-González, J.

E., Izquierdo, E. D. M. M., & Álvarez, R. (2018). Envi- ronmental risk assessment of cobalt and manganese from industrial sources in an estuarine system. Environmental Geochemistry and Health, 40, 737–748. https:// doi. org/

10. 1007/ s10653- 017- 0020-9

Beesley, L., Inneh, O. S., Norton, G. J., Moreno-Jimenez, E., Pardo, T., Clemente, R., & Dawson, J. J. C. (2014).

Assessing the influence of compost and biochar amend- ments on the mobility and toxicity of metals and arsenic in a naturally contaminated mine soil. Environ Pol, 186, 195–202. https:// doi. org/ 10. 1016/j. envpol. 2013. 11. 026 Bertoldo, L., Ribeiro, A., Reis, C., Frachini, E., Kroetz, B.,

Abráo, T., & Santos, M. (2022). Environmental risk assessment of potentially toxic elements in Doce River watershed post-mining dam breakdown in Mariana MG- Brazil. Retrieved from https:// data. mende ley. com/ datas ets/

bb6st kvw3j/1, https:// doi. org/ 10. 17632/ bb6st kvw3j.1 Bo, L., Wang, D., Zhang, G., & Wang, C. (2015). Heavy metal

speciation in sediments and the associated Ecological Risks in rural rivers in Southern Jiangsu Province, China.

Soil and Sediment Contamination, 24, 90–102. https:// doi.

org/ 10. 1080/ 15320 383. 2014. 914465

Borovec, Z. (1996). Evaluation of the concentration of the trace elements in stream sediments by factor and cluster analysis and the sequential extraction procedure. Science of the Total Environment, 177, 237–250. https:// doi. org/ 10. 1016/

0048- 9697(95) 04901-0

Budakoglu, M., Karaman, M., Kumral, M., Zeytuncu, B., Doner, Z., Yildrim, D. K., Tasdelen, S., Bűlbűl, A., &

Gumus, L. (2018). Risk assessment of trace metals in an extreme environment sediment: shallow, hypersaline, alkaline, and industrial Lake Aciol, Denizi, Turkey. Envi‑

ron Monit Assessm, 190, 2–27. https:// doi. org/ 10. 1007/

s10661- 018- 6495-8

Cionek, V. M., Alves, G. H. Z., Rodrigues-Filho, J. L., &

Dias, R. M. (2019). Brazil in the mud again: lessons not learned from Mariana dam collapse. Biodiversity and Conservation, 28, 1935–1938. https:// doi. org/ 10. 1007/

s10531- 019- 01762-3

Claessen, M. E. C., Barreto, W. O., Paula, J. L., & Duarte, M.

N. (1997). Soil Analysis Methods. The Brazilian Agricul- tural Research Corporation - EMBRAPA Rio de Janeiro - Brazil.

CONAMA. (2009). National Council of the Environment, Reso‑

lution 420/2009. Technical Report 1 Environment Minis- try-Brazil. Retrieved from https:// chemr eg. net/ regul ations/

Envir onmen tal/ Gener al/ Brazil/ 17- 45% 20GMS DS. pdf/ view

Corwin, D. L. (2003). Soil salinity measurement. In Encyclo‑

pedia of water science (pp. 852–857). Marcel Dekker, Inc.

Coutris, C., Aas, T. H., Lapied, E., Joner, E. J., & Oughton, D.

H. (2012a). Bioavailability of cobalt and silver nanoparti- cles to the earthworm Eisenia fetida. Nanotoxicology, 6, 186–195. https:// doi. org/ 10. 3109/ 17435 390. 2011. 569094 Coutris, C., Joner, E. J., & Oughton, D. H. (2012b). Aging and

soil organic matter content affect the fate of silver nanopar- ticles in soil. The Science of the Total Environment, 420, 327–333. https:// doi. org/ 10. 1016/j. scito tenv. 2012. 01. 027 Dick, D. P., Novotny, E. H., Dieckow, J., & Bayer, C. (2009).

Chemistry of soil organic matter. In Chemistry and min‑

eralogy of soil Part II Aplications (Química e mineralo‑

gia do solo Parte II ‑ Aplicações) chapterXI. (pp. 1–67).

Brazilian Soc Soil Sci. Retrieved from https:// www.

scirp. org/ (S(lz5mq p453e dsnp5 5rrgj ct55.))/ refer ence/

refer ences papers. aspx? refer enceid= 22016 72

EMBRAPA. (2006). Brazilian System of soil classification.

(2nd ed.). Rua Jardim Botânico, 1024, Rio de Janeiro, Brazil: The Brazilian Agricultural Research Corporation.

ISBN:85-85864-19-2.

EMBRAPA. (2022). Correspondence between SIBCS, WRB FAO, and soil taxonomy classes.

Fernandez-Ondono, E., Bacceta, G., Lallena, A. M., Navarro, F.

B., Ortiz, J., & Jimenez, M. N. (2017). Use of BCR procedure in metal transfer predictions in contaminated mine tailings in Sardinia. Journal of Geochemical Exploration, 172, 133–141. https:// doi. org/ 10. 1016/j. gexplo. 2016. 09. 013 Fiedler, S., Vepraskas, M. J., & Richardson, J. (2007). Soil

redox potential: Importance, field measurements, and observations. In D.L. Sparks (Ed.), Advances Agron (pp.

1–54). Academic Press volume94. https:// doi. org/ 10. 1016/

S0065- 2113(06) 94001-2

Foesch, M. D. S., Francelino, M. R., Rocha, P. A., & Gomes, A. R. L. (2020). River Water Contamination Resulting from the Mariana Disaster. Brazil. Floresta Ambient., 27, 1–10. https:// doi. org/ 10. 1590/ 2179- 8087. 013218

Frachini, E., Ferreira, C. R., Kroetz, B. L., Urbano, A., Abráo, T.,

& Santos, M. (2021). Modeling the kinetics of potentially toxic elements desorption in sediment affected by a dam breakdown disaster in Doce River - Brazil. Chemosphere, 283, 131–157. https:// doi. org/ 10. 1016/j. chemo sphere. 2021.

131157

Gabaròn, M., Zornoza, R., Martínez-Martínez, S., Muñoz, V.

A., Faz, A., & Costa, J. A. (2019). Effect of land use and soil properties in the feasibility of two sequential extraction procedures for metals fractionation. Chemosphere, 218, 266–272. https:// doi. org/ 10. 1016/j. chemo sphere.

2018. 11. 114

Gabarón, M., Faz, A., Martínez, S. M., Zornoza, R., &

Acosta, J. A. (2017). Assessment of metals behavior in industrial soil using sequential extraction, multivariable analysis and a geostatistical approach. Journal of Geo‑

chemical Exploration, 172, 174–183. https:// doi. org/ 10.

1016/j. gexplo. 2016. 10. 015

Gao, L., Gao, B., Zhou, Y., Xu, D., & Sun, K. (2017). Pre- dicting remobilization characteristics of cobalt in ripar- ian soils in the Miyn Reservoir prior to water retention.

Ecological Indicators, 80, 196–203. https:// doi. org/ 10.

1016/j. ecoli nd. 2017. 05. 024

(14)

Gomes, L. E. O., Correa, L. B., Sá, F., Neto, R. R., & Bernardinho, A. F. (2017). The impacts of the Samarco Mine tailing spill on the Doce River Estuary, Eastern, Brazil. Marine Pollution Bulletin, 120, 28–36. https:// doi. org/ 10. 1016/j. marpo lbul.

2017. 04. 056

Grygo-Szymanko, E., Tobiasz, A., & Walas, S. (2016).

Speciation analysis and fractionation of manganese: A review. Trends in Analytical Chemistry, 80, 112–124.

https:// doi. org/ 10. 1016/j. trac. 2015. 09. 010

Guerra, M. B. B., Teaney, B. T., Mount, B. J., Assunskis, D.

J., Jordan, B. T., Barker, R. T., Santos, E. E., & Shaefer, C. E. G. R. (2017). Post-catastrophe analysis of the Fundão tailings dam failure in the Doce River system, Southeast Brazil: Potencially toxic elements in affected soils. Water, Air, and Soil Pollution, 228, 1–12. https://

doi. org/ 10. 1007/ s11270- 017- 3430-5

Guo, W., Liu, X., Liu, Z., & Li, G. (2010). Pollution and potential ecological risk evaluation of heavy metals in the sediments around Dongjiang Harbor, Tianjin. Proce‑

dia Environmental Sciences, 2, 729–736. https:// doi. org/

10. 1016/j. proenv. 2010. 10. 084

Hakanson, L. (1980). An ecological risk index for aquatic pollution control, A sedimentological approach. Water Research, 14, 975–1001. https:// doi. org/ 10. 1016/ 0043- 1354(80) 90143-8

He, X., Yuan, T., Jiang, X., & Zheng, C. L. (2021). Effects of contaminated surfacewater and groundwater froma rare earth mining area on the biology and the physiol- ogy of Sprague-Dawley rats. Science of the Total Envi‑

ronment, 761, 1–12. https:// doi. org/ 10. 1016/j. scito tenv.

2020. 144123

Hemond, H. F., & Fechner-Levy, E. J. (2000). Chemical fate and transport in environment (2nd ed.). San Diego, Cal- ifornia, USA: American Press. https:// doi. org/ 10. 1016/

C2009-1- 03794-0

Huheey, J. A., Keiter, E. A., & Keiter, R. L. (1993). Inorganic Chemistry principles of structure and Reactivity. (4th ed.).

Harper Collins College Publishers. ISBN:8177581309, 9788177581300.

Husson, O. (2013). Redox potential (Eh) and pH as drivers of soil/plant/microorganism systems: a transdisciplinary overview pointing to integrative opportunities for agronomy. Plant and Soil, 362, 389–417. https:// doi. org/ 10.

1007/ s11104- 012- 1429-7

IBAMA. (2015). Preliminary technical report of Environ- mental impacts resulting from the disaster involving the collapse of the Fundão dam, in Mariana, Minas Gerais.

Techreport Brazilian Institute of Environment and Natu- ral Resources - IBAMA.

Ikem, A., Egiebor, N. O., & Nyavor, K. (2003). Trace elements in water, fish and sediment from Tuskegee Lake, south- eastern USA. Water, Air, and Soil Pollution, 149, 51–75.

https:// doi. org/ 10. 1023/A: 10256 94315 763

Jordao, C., Pereira, J., & Jham, G. (1997). Chromium contamination in sediment, vegetation and fish caused by tanner- ies in the State of Minas Gerais, Brazil. The Science of the Total Environment, 207, 1–11. https:// doi. org/ 10. 1016/

S0048- 9697(97) 00232-5

Kahkha, M. R. R., Bagheri, S., Noori, R., Piri, J., & Javan, S. (2017). Examining total concentration and sequential extraction of heavy metals in agricultural soil and wheat.

Polish Journal of Environmental Studies, 26, 2021–2028.

https:// doi. org/ 10. 15244/ pjoes/ 67658

Khadhar, S., Sdiri, A., Chekirben, A., Azouzi, R., & Charef, A. (2020). Integration of sequential extraction, chemical analysis and statistical tools for the availability risk assessment of heavy metals in sludge amended soils.

Environmental Pollution, 263, 1–9. https:// doi. org/ 10.

1016/j. envpol. 2020. 114543

Kim, E. J., Yoo, J. C., & Baek, K. (2014). Arsenic speciation and bioacessibility in arsenic-contaminated soils: Sequen- tial extraction and mineralogical investigation. Environ‑

mental Pollution, 186, 29–35. https:// doi. org/ 10. 1016/j.

envpol. 2013. 11. 032

Kiptarus, J. J., Muumbo, A. M., Makokha, A. B., & Kimutai, S. K. (2015). Characterization of selected mineral ores in the eastern zone of Kenya: Case study of Mwingi north constituency in Kitui county. International Journal of Mineral Processing, 4, 8–17. ID:131165208.

Kleber, M., Eusterhues, K., Mikutta, C., Mijutta, R., & Nico, P. S. (2015). Mineral-Organic Associations: Formation, Properties, and Relevance in soil environments. Advances in Agronomy, 130, 1–140. https:// doi. org/ 10. 1016/ bs.

agron. 2014. 10. 005

Kovacs, K., Halás, G., Takacs, A., Heltoi, G., Széles, E., Gyori, Z., & Horváth, M. (2018). Study of ultrasound-assisted sequential extraction procedure for potentially toxic element content of soils and sediments. Microchemical Journal, 136, 80–84. https:// doi. org/ 10. 1016/j. microc. 2016. 10. 006 Kumar, M., & Ramanathan, A. (2018). Vertical Geochemical

variations and speciation studies of As, Fe, Mn, Zn and Cu in the sediments of the central Gangetic Basin: Sequential extraction and statistical approach. International Journal of Environmental Research and Public Health, 15, 183–

205. https:// doi. org/ 10. 3390/ ijerp h1502 0183

Liang, G., Zhangc, B., Lin, M., Wu, S., Hou, H., Zhang, J., Qian, G., Huang, X., & Zhou, J. (2017). Evaluation of heavy metal mobilization in creek sediment: Influence of RAC values and ambient environmental factors. The Sci‑

ence of the Total Environment, 607, 1339–1347. https://

doi. org/ 10. 1016/j. scito tenv. 2017. 06. 238

Lima, A. T., Bastos, F. A., Jr, F. J. T., Neto, R. R., Cooper, A.,

& Barroso, G. F. (2020). Strengths and Weaknesses of a Hybrid Post-disaster Management Approach: the Doce River (Brazil) Mine-Tailing Dam Burst. Environmen‑

tal Management, 65, 711–724. https:// doi. org/ 10. 1007/

s00267- 020- 01279-4

Lopes, L. M. N. (2016). The collapse of the Mariana dam and its social and environmental impacts (O colapso da Represa de Mariana e seus impactos sociais e ambientais).

Sinapse Múltipla, 5, 1–14.

Ma, J., Lei, H. G. M., Zhou, X., Li, F., Yu, T., Wei, R., Zhang, H., Zhang, X., & Wu, Y. (2015). Arsenic adsorption and its fractions on aquifer sediment: Effect of pH, arsenic species, and iron/manganese minerals. Water, Air, and Soil Pollution, 226, 1–15. https:// doi. org/ 10. 1007/

s11270- 015- 2524-1

Marshall, T. (2003). Particle-size distribution of soil and the perception of texture. Australian Journal of Soil Research, 41, 245–249. https:// doi. org/ 10. 1071/ SR020 70

Matong, J. M., Nyaba, L., & Nomngongo, P. N. (2016). Frac- tionation of trace elements in agricultural soils using