Pedro Walfir Martins Souza Filho

Iron ore is essential to modern society and to the transition toward renewable energy systems. However, mineral exploitation completely transforms vegetation and may generate significant environmental impacts. Therefore, effective tools are needed to monitor the rehabilitation of degraded areas (RDA). This study aims to develop a key performance indicator to monitor the RDA (RDA KPI), defined as the total revegetated area divided by the total mined area. For this purpose, high spatial resolution optical images (0.5–2 m) from 2003, 2005, 2011, 2012, 2013, 2015, 2017, 2019, 2021, and 2022 were employed and were calibrated to improve area estimation and class discrimination. Land cover and land use (LCLU) mapping was performed using geographic object-based image analysis (GEOBIA). After this process, change detection analysis was performed using the from–to approach with classified datasets from 2003, 2013, and 2022. Classification accuracy exceeded 80% for all years, while quantity and allocation disagreements remained below 7%. The results revealed that revegetated areas increased from approximately 570 ha in 2003 to 1,228 ha in 2022, and mining areas increased from 1,449 ha to 3,083 ha. Over the same period, RDA KPI increase from 19% to 26%. Change detection also revealed that forest was the class most converted to mining areas (10.34 km²) and subsequently the main source of revegetated areas (4.59 km²). The proposed RDA KPI provides an objective metric to evaluate revegetation progress and may support environmental management and mine closure planning in open-pit mining areas.

There is limited evaluation of the effectiveness of legal environmental protection on private properties in Brazil. This study updates the implementation progress and compensation potential under the Native Vegetation Protection Law (LPVN) in the Itacaiúnas River Basin (BHRI, 41,300 km²), located in Pará, the state with the highest deforestation rates in the Amazon over the past two decades. In 2021, the total Legal Reserve (RL) deficit in BHRI exceeded the surplus by 413 km². A significant portion of this deficit (55% or 2399 km²) could be addressed through compensation, with 3721 km² available within the basin, often in the same or neighboring municipalities. Despite nearly fifteen years since the enactment of the LPVN, progress remains slow in halting deforestation and restoring vegetation. By 2021, 1496 km² of RL deficit should have been under restoration or compensation for medium and large properties. However, only half of the 2008 RL deficit had been addressed. Likewise, just 25% of the 2008 Permanent Preservation Area (APP) deficit had been restored by 2021. Meanwhile, ongoing deforestation in RL and APPs, especially in settlements and small properties, highlights the need for more effective implementation mechanisms. While the state of Pará has made strides in registering and analyzing the Rural Environmental Registry (CAR), implementation of the Environmental Regularization Program (PRA) still faces major challenges. Innovative approaches, such as agroforestry, could help align restoration goals with landowners’ economic interests. Overcoming barriers to regulatory compliance will require coordinated efforts and stronger enforcement mechanisms.

The Verde River Watershed (VRW) in southeastern Amazonia is undergoing extensive channel modification and sediment disturbance from illegal alluvial gold mining, yet site-specific geochemical baselines capable of separating natural from mining-derived metal enrichment remain lacking. We integrated morphostratigraphic reconstruction with high-density geochemical analyses of potentially toxic elements (PTE: As, Ba, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Sn, V, Zn) in stratigraphically constrained alluvial deposits to establish pre-anthropogenic background (natural) values and quantify enrichment in recently reworked sediments. Over the past ~7,600 years, sediment geochemistry has been shaped by shifts in provenance between mineralized mafic and felsic lithologies and by climatic variability, producing naturally elevated Cu (93–455 mg/kg), Cr (124–352 mg/kg), and Ni (40–107 mg/kg) that in some cases exceed Brazilian and international sediment quality guidelines (threshold, probable, and severe effect levels) without anthropogenic input. While these natural concentrations generally indicate low ecological risk, comparisons between lithology-specific backgrounds and residues from illegal mining sites show that Cu, Co, and Ni are the most consistently and significantly enriched PTE, whereas Hg, historically the focus in Amazonian mining studies, remains below moderate contamination factors at most sites. These results highlight that stratigraphy-anchored backgrounds are critical for distinguishing geogenic from anthropogenic signatures in tropical alluvial systems, thereby improving ecological risk assessment and guiding targeted monitoring and remediation in mining-impacted Amazonian watersheds. PTE.

The state of Bahia in Brazil possesses significant, yet underexploited, iron ore reserves. To support the initial stages of mineral exploration in this vast region, cost-effective and rapid large-scale mapping methods are essential. This paper presents a workflow based on publicly available remote sensing data for a state mineral prospectivity mapping (MPM) for iron. The methodology employs a Random Forest (RF) classification model on Sentinel-2 multispectral images, trained with a randomly selected dataset in the image at varying distances defined from the location of known iron mines in the state. The Spectral Angle Mapper (SAM) algorithm was used to categorize the samples according to spectral similarity features with laboratory-confirmed ore signatures from samples collected in the mine pit area. The resulting MPM successfully delineated known iron districts and highlighted new, unexplored areas with potential. A quantitative evaluation of the model yielded an overall accuracy of 69.8%, a macro-average F1-score of 0.697, and a Cohen’s Kappa coefficient of 0.623, indicating a reasonable agreement beyond random chance. This work demonstrates a validated, low-cost, and simple approach for regional-scale MPM, offering a valuable reconnaissance tool for preliminary exploration, particularly in extensive and data-scarce regions.

Evaluate the compound effect of land use and cover and ENSO (El Niño-Southern Oscillation) on the streamflows of two paired subbasins of the Itacaiúnas River Basin (IRB), Brazilian Eastern Amazon. Specific discharge data were determined using rating curves for the period from 01/27/2020 to 01/27/2022. ERA5-Land reanalysis data were used to assess mean precipitation and land use and land cover maps were used to assess changes in land cover dynamics. The region was influenced by La Niña of weak intensity that lasted 3 years. In 2020, during the rainy season, the sign of land cover prevailed in subbasins hydrographs variability. Thus, the main flow rates of the pasture were higher than those of the forest. And during the dry season, the mean flow rates of the forest were the highest. However, in 2021, the La Niña signal became moderate in intensity, modifying the hydrographs. The two subbasins did not undergo significant changes in land use and cover from 2020-2021 and were subjected to the same climatic conditions. Therefore, the increase in minimum discharge in the pasture subbasin in 2021 was a consequence of the moderate La Niña event in the Niño region 3.4.