Earth

This study addresses the global challenge of superficial soil contamination by heavy metals, focusing on differentiating natural geogenic sources from anthropogenic contributions in complex industrial–urban environments. We develop an integrated geostatistical and multivariate framework combining soil metal concentration analysis with AERMOD atmospheric dispersion modeling using a comparative multi-model machine learning approach (including Extreme Gradient Boosting, Random Forest, and Ridge Regression). Applied to the industrialized area of Taranto, Southern Italy, this approach incorporates spatial autocorrelation and multiple environmental predictors to identify contamination patterns and sources. The results reveal variable predictive accuracy across metals, with RF generally outperforming the other algorithms. The model achieved its highest performance for copper (R² = 0.58, RMSE = 25.82), Tin (R² = 0.53, RMSE = 5.95), and chromium, while showing instability for others. These disparities highlight the differential influence of remote sensing data on contamination mapping. The framework advances the quantitative assessment of soil pollution by linking atmospheric deposition and spatial processes with causal interpretability.

Europe is dealing with environmental problems that require cooperation beyond national and regional borders. Air pollution, water pollution, biodiversity loss, and waste management are the major issues that are not only complex but also cross borders. Therefore, it is necessary to provide collaborative responses that go beyond the capacity of individual countries. This inquiry centers on the question of what the best way is to set up and govern the transnational cooperation in Europe to confront these major environmental challenges. A systematic bibliographic review of the research conducted between 2010 and 2025 forms the basis of this work. The research combines semantic analysis and Latent Dirichlet Allocation (LDA) modeling to study 80 selected publications to find the tenets of the themes discussed. The identified topics are urban climate change adaptation and mitigation, climate policy and management, adaptation and vulnerability frameworks, land use and biodiversity impacts, and future climate projections and assessment. The findings show that there are strong synergies between biodiversity and climate adaptation, resilience, and environmental governance, as well as the great influence of climate change on the water management sector. The study has unveiled the significance of institutional policy frameworks in bringing about environmental cooperation across borders. In addition, it depicts the relationship between local urban projects and supra-regional policy strategies, in which the two can merge and function efficiently as long as they are working towards the common goal of environmental sustainability. This study is meant to shed more light on the area of environmental governance research, discovering areas that need more exploration, and providing some signposts on how to improve environmental involvement in Europe.

This study investigates temporal and spatial variation in torrential flood hazards and sediment dynamics in two ungauged watersheds in southeastern Serbia from 1991 to 2023. By integrating classical hydrological models with modern geospatial and photogrammetric techniques, watershed responses to environmental and anthropogenic changes are quantified. Torrential flood potential was estimated and peak discharges were calculated using both the rational and SCS-Unit hydrograph methods, while sediment transport was assessed through Gavrilović’s erosion potential model and a modified Poljakov model. A key innovation is the use of UAV-based and close-range photogrammetry for 3D grain-size analysis, marking the first such application in Serbia. The mean torrential flood potential decreased by 4.4% in the Petrova Watershed and 4.2% in the Rasnička Watershed. Specific peak discharges for a 100-year return period declined from 1.62 to 1.07 m³·s⁻¹·km⁻² in Petrova and from 1.60 to 1.34 m³·s⁻¹·km⁻² in Rasnička. Sediment transport during a 1% probability flood was reduced from 4.97 to 2.53 m³·s⁻¹ in Petrova and from 13.87 to 9.48 m³·s⁻¹ in Rasnička. Grain-size analyses revealed immobile coarse bedload in the Petrova and active sediment transport in the Rasnička River, where D50 and D90 decreased between 2023 and 2024. The findings highlight the effectiveness of a synergistic methodological approach for analyzing complex watershed processes in data-scarce regions. The study provides a replicable model for flood hazard assessment and erosion control planning in similar mountainous environments undergoing socio-environmental transitions.