The main objective of this study was to investigate the 2019 and 2022 oil spill events that occurred off the coast of the State of Ceará, Northeastern Brazil. To further assess these mysterious oil spills, we investigated whether the oils stranded on the beaches of Ceará in 2019 and 2022 had the same origin, whether their compositional differences were due to weathering processes, and whether the materials from both were natural or industrially processed. We collected oil samples in October 2019 and January 2022, soon after their appearance on the beaches. We applied a forensic environmental geochemistry approach using both one-dimensional and two-dimensional gas chromatography to assess chemical composition. The collected material had characteristics of crude oil and not refined oils. In addition, the 2022 oil samples collected over 130 km of the east coast of Ceará had a similar chemical profile and were thus considered to originate from the same source. However, these oils had distinct biomarker profiles compared to those of the 2019 oils, including resistant terpanes and triaromatic steranes, thus excluding the hypothesis that the oil that reached the coast of Ceará in January 2022 is related to the tragedy that occurred in 2019. From a geochemical perspective, the oil released in 2019 is more thermally mature than that released in 2022, with both having source rocks with distinct types of organic matter and depositional environments. As the coast of Ceará has vast ecological diversity and Marine Protected Areas, the possibility of occasional oil spills in the area causing severe environmental pollution should be investigated from multiple perspectives, including forensic environmental geochemistry.

The Aquidauana River is one of the most important rivers in the Pantanal region, Brazil. However, its waters have been contaminated by nearby anthropogenic activities, threatening native fish species. In this study, our objectives were: 1) to determine the concentrations of Al, As, Cd, Cu, Fe, Mn, Ni, Pb, and Zn in water and sediment samples from the Aquidauana River and to assess the risks posed to aquatic biota; 2) to quantify the concentration of these elements in muscle and liver tissue samples from four native fish species; 3) to evaluate the potential bioaccumulation of inorganic elements in the muscles and liver; and 4) to investigate genotoxicity biomarkers and their association with the inorganic element concentrations present in the muscle tissue. Water and fish samples were collected in November 2020. The concentrations of Al, As, Cd, Cu, Fe, and Pb in the water samples were in disagreement with the Brazilian legislation and presented risks to the aquatic biota. In terms of mixtures of inorganic elements, there was a great increase in the risk to biota. The As concentration did not meet the Brazilian standard for sediments in the sample collected at sampling site 6. The concentrations of Cd and Pb in the muscle tissue of Hypostomus regani, Prochilodus lineatus, Brycon hilarii, and Mylossoma duriventre exceeded the Brazilian standards for human consumption. H. regani showed greater genotoxic damage, and the higher the Al and Fe concentrations in the muscle tissue, the higher the frequencies of lobulated nuclei and nuclear invaginations. Together, our results demonstrate the negative impacts on native fish species from the Aquidauana River contamination and indicate risks to Pantanal biodiversity.

Habitat loss and fragmentation together represent the most significant threat to the world's biodiversity. In order to guarantee the survival of this diversity, the monitoring of bioindicators can provide important insights into the health of a natural environment. In this context, we used the comet assay and micronucleus test to evaluate the genotoxic susceptibility of 126 bats of eight species captured in soybean and sugarcane plantation areas, together with a control area (conservation unit) in the Cerrado savanna of central Brazil. No significant differences were found between the specimens captured in the sugarcane and control areas in the frequency of micronuclei and DNA damage (comet assay). However, the omnivore Phyllostomus hastatus had a higher frequency of nuclear abnormalities than the frugivore Carollia perspicillata in the sugarcane area. Insectivorous and frugivorous bats presented a higher frequency of genotoxic damage than the nectarivores in the soybean area. In general, DNA damage and micronuclei were significantly more frequent in agricultural environments than in the control area. While agricultural development is an economic necessity in developing countries, the impacts on the natural landscape may result in genotoxic damage to the local fauna, such as bats. Over the medium to long term, then DNA damage may have an increasingly negative impact on the wellbeing of the local species.

Passive biomonitoring was applied in four Atlantic forest plots in southeast Brazil, affected by different levels of trace metal pollution (OP site located in Minas Gerais State and PEFI, PP and STG located in São Paulo State). Native tree species were selected as biomonitors according to their abundance in each plot and successional classification. Current trace metal concentrations in total suspended particles, leaves of non-pioneer (NPi) and pioneer (Pi) species, topsoil (0–20 cm) and litter and concentration ratios at the plant/soil interface were analyzed to verify the atmosphere-plant-soil interactions, basal concentrations, spatial variations and metal accumulation at the ecosystem level. Redundant analysis helped to identify similar characteristics of metal concentrations in PP and PEFI, which can be influenced by the high concentrations of elements related to anthropogenic inputs. Analysis of variance and multivariate statistics indicated that the trees of OP presented higher concentrations of Cr, Fe, Mn and Ni than those in the other sites. High enrichment of Cd, Fe, Ni in non-pioneer plants indicated that the PP forest (initially considered as the least polluted) has still been affected by metal pollution. Soil collected in STG was enriched by all elements, however these elements were low available for plant uptake. Metal deposited in leaves and litter was an important sink for soil cycling, nevertheless, these metals are not bioavailable in most cases. Non-pioneer tree species revealed to be more appropriate than pioneer species to indicate the current panorama of the contamination and bioavailability levels of trace metals in the tree community-litter-soil interface of the Atlantic forest remnants included in this study.

Litter is an ecological, economic, and social problem that impacts marine environments around the world. To create prevention and mitigation measures to solve this issue, it is necessary to understand the amounts and sources of this type of pollution. Cassino Beach is an extensive sandy beach located in South Brazil (∼220 km in length) that presents multiple uses, such as touristic, portuary and fishery activities. In order to evaluate the spatial and seasonal variation of litter amounts, types and sources at Cassino Beach, litter (>2.5 cm) was collected over 27 months at two urban and two non-urban sites. At each site, the litter present in three 200 m² areas was sampled and evaluated. A total of 19,457 items were collected, mostly composed by plastic (∼88%). Paper, metal, and cloth items were also present, but in low amounts. Fragments and cigarette butts were the major types of plastic litter, with abundances of 28.4% and 17.0%, respectively. Urban sites presented higher amounts of litter, with those related to beach use being more common, emphasizing the contribution of beachgoers to litter input at these sites. During the summer season, when beach use increases, the highest total litter concentration was found. Undefined and/or beach use-related sources were dominant in all sites and seasons. Mapping the predominant materials, types and potential sources of litter creates important baseline data that can contribute not only to beach monitoring, but also to the development of litter reduction strategies.

North-Eastern Brazil saw intensive application of the insecticide pyriproxyfen (PPF) during the microcephaly outbreak caused by the Zika virus (ZIKV). ZIKV requires the neural RNA-binding protein Musashi-1 to replicate. Thyroid hormone (TH) represses MSI1. PPF is a suspected TH disruptor. We hypothesized that co-exposure to the main metabolite of PPF, 4′–OH–PPF, could exacerbate ZIKV effects through increased MSI1 expression. Exposing an in vivo reporter model, Xenopus laevis, to 4′–OH–PPF decreased TH signaling and increased msi1 mRNA and protein, confirming TH-antagonistic properties. Next, we investigated the metabolite's effects on mouse subventricular zone-derived neural stem cells (NSCs). Exposure to 4′–OH–PPF dose-dependently reduced neuroprogenitor proliferation and dysregulated genes implicated in neurogliogenesis. The highest dose induced Msi1 mRNA and protein, increasing cell apoptosis and the ratio of neurons to glial cells. Given these effects of the metabolite alone, we considered if combined infection with ZIKV worsened neurogenic events. Only at the fourth and last day of incubation did co-exposure of 4′–OH–PPF and ZIKV decrease viral replication, but viral RNA copies stayed within the same order of magnitude. Intracellular RNA content of NSCs was decreased in the combined presence of 4′–OH–PPF and ZIKV, suggesting a synergistic block of transcriptional machinery. Seven out of 12 tested key genes in TH signaling and neuroglial commitment were dysregulated by co-exposure, of which four were unaltered when exposed to 4′–OH–PPF alone. We conclude that 4′–OH–PPF is an active TH-antagonist, altering NSC processes known to underlie correct cortical development. A combination of the TH-disrupting metabolite and ZIKV could aggravate the microcephaly phenotype.

The Amazon coastal zone has become contaminated with organic pollutants, such as polycyclic aromatic hydrocarbons (PAHs). However, information about their distribution and sources in this area is scarce, despite increasing deforestation and oil exploitation. Therefore, individual PAHs were analysed in the sediments of the Oyapock estuary, which is located in the Amazon coastal zone. This study provides information about the spatial and short-term temporal distributions of PAHs and discusses the major sources of PAHs to better understand the anthropogenic processes occurring in adjacent areas. The concentrations of all sixteen priority PAHs defined by the US EPA (United States Environmental Protection Agency, ∑₁₆PAHs) ranged from 10.9 to 138.8 ng g⁻¹ with a mean and standard deviation = 37.9 ± 20.5 and indicated that this estuary is not contaminated, while the mean levels were similar to those found in other Amazon regions and pristine areas along the coast of Brazil. No significant differences were found in the sedimentary PAHs levels between the wet and dry sampling campaigns, despite the different climatic conditions. Diagnostic ratios, positive matrix factorization (PMF) and cluster analysis have shown that the majority of the investigated PAHs were derived from combustion processes (at least 55.1%, as estimated by the PMF model). Localized source inputs from oil and its by-products concomitantly with natural/biogenic sources appear to be secondary sources. The PAH contribution from biomass and wood combustion was approximately 13.6% and was relatively lower than other regions of the Amazon that are undergoing massive biomass burning. As the first study of PAHs in this region, this study provides vital information on the healthy state of the estuary and can serve as a baseline for assessing the impacts of acute oil disasters or the chronic input of PAHs as a result of human settlements.

One of the worst socio-environmental disasters to mark the history of Brazil and the world occurred in November 2015 and involved the mining sector. The collapse of the Fundao dam released approximately 43 million m³ of iron ore tailings, which moved downstream to reach the Doce River. This resulted in the contamination of water, soil, and sediments along the entire course of the river, which also affected its mouth in the Atlantic Ocean. Four years after the disaster, several socio-environmental problems continue to persist in the affected areas. In this context, the reservoirs built along the Doce River deserve special attention as they are artificial environments that are highly vulnerable to changes in water parameters. This study aims to determine water quality indicators of these reservoirs using remote sensing data and image processing methods, including semi-analytical algorithms, to comprehend the progress of eutrophication processes. Operational land imager/Landsat-8 data (from 2013 to 2019) were used to map the suspended particulate matter (SPM), euphotic zone (Zₑᵤ) and chlorophyll-a (Chl-a) before and after the collapse. The results showed significant changes in SPM and Zₑᵤ in the reservoirs after the collapse. Non-conformity of these parameters is observed even now, and they tend to intensify during rainy periods when resuspension processes of sediments occur. Moreover, there has been an increase in the eutrophication of reservoirs as noticed by the significant increase in Chl-a after the disaster, especially in January, July, and August.

Studies have reported significant reductions in air pollutant levels due to the COVID-19 outbreak worldwide global lockdowns. Nevertheless, all of the reports are limited compared to data from the same period over the past few years, providing mainly an overview of past events, with no future predictions. Lockdown level can be directly related to the number of new COVID-19 cases, air pollution, and economic restriction. As lockdown status varies considerably across the globe, there is a window for mega-cities to determine the optimum lockdown flexibility. To that end, firstly, we employed four different Artificial Neural Networks (ANN) to examine the compatibility to the original levels of CO, O₃, NO₂, NO, PM₂.₅, and PM₁₀, for São Paulo City, the current Pandemic epicenter in South America. After checking compatibility, we simulated four hypothetical scenarios: 10%, 30%, 70%, and 90% lockdown to predict air pollution levels. To our knowledge, ANN have not been applied to air pollution prediction by lockdown level. Using a limited database, the Multilayer Perceptron neural network has proven to be robust (with Mean Absolute Percentage Error ∼ 30%), with acceptable predictive power to estimate air pollution changes. We illustrate that air pollutant levels can effectively be controlled and predicted when flexible lockdown measures are implemented. The models will be a useful tool for governments to manage the delicate balance among lockdown, number of COVID-19 cases, and air pollution.

COVID-19 pandemic has led to concerns on the circulation of SARS-CoV-2 in the environment, its infectivity from the environment and, the relevance of transmission via environmental compartments. During 31 weeks, water samples were collected from a heavily contaminated stream going through an urban, underprivileged community without sewage collection. Our results showed a statistically significant correlation between cases of COVID-19 and SARS in the community, and SARS-CoV-2 concentrations in the water. Based on the model, if the concentrations of SARS-CoV-RNA (N1 and N2 target regions) increase 10 times, there is an expected increase of 104% [95%CI: (62–157%)] and 92% [95%CI: (51–143%)], respectively, in the number of cases of COVID-19 and SARS. We believe that differences in concentration of the virus in the environment reflect the epidemiological status in the community, which may be important information for surveillance and controlling dissemination in areas with vulnerable populations and poor sanitation. None of the samples were found infectious based cultures. Our results may be applicable globally as similar communities exist worldwide.