The Fundão dam failure: Iron ore tailing impact on marine benthic macrofauna.

The Fundão dam failure, the worst environmental disaster in Brazilian history, launched 50 million m3 of iron ore tailings mud through the Doce River, reaching the Atlantic Ocean. Generally, mine tailings increase the sediment inflow, leading to mud burial of epibenthic macrofauna, and the raise of metal(oid)s concentration causing macrofauna long-term changes. After almost four years, tailings mud was still spreading on the Doce River Shelf, while impacts on marine macrofauna were still unknown. Herein, the IMS index (a tracer of Fundão dam tailings mud), sediment variables, organic pollutants, and metal(oid)s were integrated to uncover the drives of macrofauna structure from Costas da Algas to Abrolhos bank MPAs. Tailings mud was present only in Doce River Mouth and Degredo, organic pollutants and metal(oid)s above safety levels were concentrated in those same areas. Tailings mud (IMS index) drastically reduced species richness and diversity, favoring the abundance of opportunistic species. Mud, IMS index and Al, Ba, and V, metal(oid)s linked to dam failure, structured macrofauna composition in this impacted area, dominated by resistant groups as Nuculidae, Spionidae, and Magelonidae. Conversely, an opposite pattern was found for further and deeper sites with high CaCO3 content and total nitrogen that also showed large grain size, in areas known to harbour biogenic structures, sustaining a macrofauna composition distinct from the impacted areas, dominated by Syllidae and Crassatellidae, sensitives to impacts. Macrofauna composition was most structured by sediment variables, followed by the intersection between metal(oid)s-IMS and Mud, both gradients acting almost entirely on a broad spatial scale. Benthic macrofauna at the Doce River Shelf is still impacted by Fundão dam tailings mud, even after almost four years of the disaster, and may continue to, since the influx of tailings does not stop, and sediment resuspension is a recurrent source for those impacts.

Physicochemical characterization of monazite sand and its associated bacterial species from the beaches of southeastern Brazil.

Beaches with monazitic sands show high natural radiation, and the knowledge of this radiation is fundamental to simulate the effects of natural terrestrial radiation on biological systems. Monazite-rich sand from a beach in the southeastern Brazil were collected and analyzed by X-ray fluorescence, X-ray diffraction, and magnetic susceptibility. The natural terrestrial radiation of the beach sand showed a positive correlation with the Th and Y elements, which are closely associated with Ce, Nd, Ca, and P, suggesting that this grouping is mainly associated with local natural radiation. Based on the sand characterization, a physical simulator of natural gamma radiation was built with parameters similar to those of the monazite beach sand, considering areas with high natural radiation levels. The simulation revealed that the natural radiation of the monazite sands has a significant effect on reducing the growth of the bacteria strains of E. coli and S. aureus present in the beach sand, with a reduction of 23.8% and 18.4%, respectively.

A review of the main strategies used in the interpretation of similar chemical profiles yielded by receptor models in the source apportionment of particulate matter.

Receptor models have been widely used for the source apportionment of airborne particulate matter. However, in the last 10 years, the use of factor analysis-based models, such as PMF and UNMIX, has increased significantly. The results yielded by these models must be interpreted by users who must know all variables influencing the modeling, and without this knowledge, the probability of incorrect interpretation of the source profiles may increase, especially when two or more sources have similar chemical profiles. Concerning the quality of data, this work shows that a broad characterization of PM composition, including inorganic, organic, and mineralogical species can improve this process, avoiding misinterpretation and the attribution of mixed or unidentified sources. This work aims to provide readers with some answers for a question often risen during source apportionment studies: Which source markers should be used for better separation and interpretation of source profiles? This review shows there is no right answer for this because different strategies can be used for this purpose. Therefore, this review aims to compile and highlight qualitatively the key strategies already used by several experienced receptor models users, combining the use of inorganic, organic, and mineralogical markers of PM for better separation and interpretation of the profiles yielded by receptor models. Also, this work presents a compilation in tables of the main chemical species reported in the literature as markers for interpreting the source profiles.

Evaluation of induced biological effects in rats by continuous and natural gamma radiation using a physical simulator.

PURPOSE: The effects of radioactivity on human health have been debated for many years but there are still important gaps that need to be addressed especially related to the effects of high natural background radiation on the local population. The beach of Meaípe, in the city of Guarapari (Brazil), emits natural gamma radiation due to the presence of monazite sands. We aimed to investigate the effects of gamma radiation doses on the biological system of wistar rats using a physical simulator of gamma radiation designed using Meaípe monazite sands. METHODS: Female Wistar rats were divided into three groups, submitted to no radiation (control group) and to continuous radiation levels, one of very high level (20 µSv h-1) and another of high level (3.6 µSv h-1). The three group of animals were monitored weekly for 3 months and at the end of the study the animals were sacrificed, and the organs were extracted and weighed for anthropometric, oxidative stress and histological evaluations. RESULTS: Exposure to radiation released by the monazite sands did not cause anthropometric alterations or blood pressure change in the animals. Similarly, there was no change in the quantification of ovarian follicles between the radiation groups and the control group. There was no difference in the oxidative stress quantification by the thiobarbituric acid reactive substance and advanced oxidation protein product methods in the ovaries. There were no evidenced damages in the structure of the renal tissue. It was observed the presence of granulomas in the hepatic tissue and alterations in the nuclei of the hepatocytes. CONCLUSIONS: Our results suggest that the continuous exposure of females rats to 3.6 and 20 µSv h-1 doses of gamma radiation slightly affected the hepatic tissue, but did not alter the histological parameters in the kidneys and ovaries and oxidative stress.

Tracing iron ore tailings in the marine environment: An investigation of the Fundão dam failure.

This work aims to characterize, in mineral and chemical terms, the ore tailings related to the Mariana disaster (MG, Brazil), occurred on 5 November 2015, and assess its correlation with sediments found in the continental shelf adjacent to the Doce River mouth (ES, Brazil). This study uses samples of tailings and seabed sediments collected at the mouth of the Doce River from 2012 to 2019. Elemental compositions of all samples were determined by X-ray fluorescence measurements; however, Synchrotron Resonant X-Ray Diffraction proved to be a remarkable technique to characterize the crystallographic phases of iron present in sediments. Studies and analyzes of the sediment samples showed that the tailings have a notable feature of the iron-crystallographic phases, mainly observed in the period after the Fundão dam failure, as compared with sediments collected in the period before. This set of iron-containing mineral phases, here called the Iron Mineralogical Set (IMS), consists of the main phases of hematite and magnetite and the minority phases of goethite and greenalite and it is used as a marker of tailings. Mass ac magnetic susceptibility measures supported the concept of the IMS as a marker. It is suggested a relationship between the content of the IMS in the sediment samples as a function of the measures of mass magnetic susceptibility. The IMS had shown the influence of tailings on the sea bed sediment indicating that there is no possibility, at the current stage, of predicting how many years this material will still be at the seabed.

Uncommon chemical species in PM2.5 and PM10 and its potential use as industrial and vehicular markers for source apportionment studies.

Chemical characterization of PM2.5 and PM10 is important to identify potential compounds that induce biological responses that translate into cardio-respiratory health problems. This study shows the reliability of the use of crystalline phases, identified in samples from receptor sites, as source markers, helping researchers to infer the main sources of air pollution, even without the use of receptor models. PM2.5 and PM10 samples were collected at two sites in an urban industrialized region located at southeast of Brazil and analyzed by Synchrotron X-ray Diffraction to identify crystalline compounds. Results show 5 PM10 and PM2.5 species not previously reported in the literature. We propose reaction mechanisms for these species and identify specific sources for each crystalline phase found: BaTiO3 was found in PM10 receptor samples and proved to be a vehicular marker formed during brake action; maghemite (γ-Fe2O3), pyracmonite [(NH4)3Fe(SO4)3], ammonium perchlorate (NH3OHClO4) and potassium ferrate (K2Fe2O4) were found in PM2.5 proved to be markers of industrial activities. The crystalline phases found in PM samples from receptor sites and the mechanisms of reactions showed the reliability of the use of crystalline phases as source markers in the identification of potential sources of air pollution without misinterpretation of the likely source.

Use of inorganic and organic markers associated with their directionality for the apportionment of highly correlated sources of particulate matter.

Particulate matter source identification using receptor models is one of the tools applied in air quality management. These models have limitations such as the collinearity effects, hindering their application and interpretation. Positive Matrix Factorization (PMF) models use chemical markers for the definition of likely sources, leaving to users the factors interpretation. This can lead to biased interpretations, as chemical species can be markers for several sources, particularly when there is source similarity. The Region of Greater Vitória, located southeast of Brazil, is a complex site in which similar industrial activities are installed, such as a pelletizing plant and a steel plant, that produce iron pellets and sinter, both iron-agglomerates with similar chemical profiles. To minimize the effects of collinearity between those sources, a new PMF approach is proposed by using inorganic and organic chemical species and the directionality of pollutant using wind roses. The proposed methodology determines the following consolidated markers: elemental carbon (EC) and organic carbon (OC) for vehicular sources; chloride (Cl) and sodium (Na) for sea salt; iron (Fe) for industrial sources. This association was possible by identifying the directionality of the chemical species. Cl a typical sea salt marker also attributed to industrial sintering activities. Some PMF factors showed high OC loadings, a typical marker for both vehicular exhaust and coal burning. The definition of the most appropriate sources for those factors was only possible due to the assessment of the pollutant roses. Pollutant roses generally showed that higher concentrations of potassium (K), a marker of biomass burning, was predominantly associated with winds from an industrial park, and are most likely associated with sintering emissions. Results showed that combining both organic and inorganic markers with the pollutant roses for identification of the directionality of predominant sources improved the interpretation of PMF factor numbers in source apportionment studies.