Mining activities are conducted to extract valuable minerals from the Earth, which are used to manufacture many objects. However, these operations generate landform alterations, such as deep excavations, artificial embankments, and landscape reshaping. In this study, landform changes were monitored in a mining area in Mazapil, Zacatecas, Mexico, using geomatic techniques. Multitemporal Landsat satellite images and digital elevation models (DEMs) from different years were used to detect and quantify landform alterations and estimate the volumes of removed material. The results show ground depressions greater than −333 m and waste material accumulations greater than +152 m, with an average standard deviation of ±3.6 m. A total excavation volume of 413.524 million m³ and a total fill volume of 431.194 million m³ were quantified, with an estimated standard deviation of ±810 m³. The proposed methodology proved effective for the remote quantification of large-scale relief disturbances in open-pit mining areas. It can also be used for environmental monitoring and hydrological risk assessment in active and inactive mining areas.

This study assessed the spatial distribution and composition of airborne particulate matter within a 10 km long urban green corridor in Zacatecas, Mexico, using magnetic biomonitoring with Tillandsia recurvata and SEM-EDS particle characterization. A total of 44 samples were collected from distinct urban park contexts (e.g., commercial zones, malls, bus stops), revealing mass-specific magnetic susceptibility χ values ranging from −6.71 to 61.1 × 10⁻⁸ m³ kg⁻¹. Three compositional groups were identified based on a PCA performed using elemental concentrations from SEM-EDS and magnetic data, which are associated with traffic emissions and industrial inputs. SEM-EDS images confirmed abundant magnetite-like particles (1–8 μm) with hazardous metals including Pb (up to 5.6 wt.%), Ba (up to 67.6 wt.%), and Cr (up to 31.5 wt.%). Wind direction data indicated predominant SSW–NNE transport, correlating with hotspots in central and northeastern park areas. Overall, vegetated zones exhibited markedly lower magnetic loads (mean χ = 8.84 × 10⁻⁸ m³ kg⁻¹) than traffic-exposed sites (mean χ = 17.27 × 10⁻⁸ m³ kg⁻¹), representing an approximate 50% reduction in magnetic particle accumulation, which highlights the effective role of continuous vegetation cover as a functional green barrier that attenuates the lateral transport and deposition of airborne particulate matter within the park. This research highlights the applicability of combined magnetic and microscopic techniques for evaluating the dynamics of airborne pollution in urban parks and supports their use for identifying both pollution hotspots and mitigation zones, reinforcing the role of urban green spaces as biofunctional filters in cities facing vehicular air pollution.

Mining activities are conducted to extract valuable minerals from the Earth, used in the manufacture of many objects. However, these operations have been associated with significant landform alterations, such as deep excavations, artificial embankments, and landscape reshaping. In this study, remote sensing (RS) and geographic information systems (GIS) techniques were applied to verify landform changes induced by open-pit mining in Mazapil, Zacatecas, Mexico. Multi-temporal Landsat 5 and 8 satellite images, along with digital elevation models (DEMs) from 1998 and 2014, were used to detect variations in land cover and terrain shape. Analyses revealed ground depressions greater than −333 m and waste accumulations greater than +152 m, with an average standard deviation of ±3.6 m. A total excavation volume of 413,524,124 m³ and an embankment volume of 431,194,785 m³ were quantified, with an estimated standard deviation of ±810 m³. Despite limitations related to DEM resolution, data availability, and restricted mine access, the proposed method proved effective for the remote quantification of large-scale topographic alterations in open-pit mining areas. The integration of satellite imagery, multi-temporal DEMs, and geospatial analysis constitutes a cost-effective and replicable methodology for environmental monitoring, landscape modeling, and hydrological risk assessment in both active and post-mining environments.

This study assessed the spatial distribution and composition of airborne particulate matter within a 10-km long urban green corridor in Zacatecas, Mexico, using magnetic biomonitoring with Tillandsia recurvata and SEM-EDS particle characterization. A total of 44 samples were collected from distinct urban park contexts (e.g., commercial zones, malls, bus stop), revealing mass-specific magnetic susceptibility χ values ranging from 0.87 to 97.0 × 10⁻⁸ m³kg⁻¹. Three compositional groups were identified based on a PCA performed using elemental concentrations from SEM-EDS and magnetic data, which are associated with traffic emissions and industrial inputs. SEM-EDS images confirmed abundant magnetite-like particles (1–8 μm) with hazardous metals including Pb (up to 5.6 wt.%), Ba (up to 67.6 wt.%), and Cr (up to 31.5 wt.%). Wind direction data indicated predominant SSW-NNE transport, correlating with hotspots in central and northeastern park areas. Overall, vegetated zones displayed significantly lower magnetic loads (mean χ = 8.84 × 10⁻⁸ m³kg⁻¹, σ = 6.65 × 10⁻⁸ m³kg⁻¹) compared to traffic-exposed sites (mean χ = 17.27 × 10⁻⁸ m³kg⁻¹, σ = 12.44 × 10⁻⁸ m³kg⁻¹), emphasizing the pollution mitigation role of green barriers. This research highlights the applicability of combined magnetic and microscopic techniques for evaluating the dynamics of airborne pollution in urban parks and supports their use as biofunctional filters in cities facing vehicular air pollution.