In this paper, we explore the computational capabilities of advanced modeling tools to reveal the factors that shape the observed benzene levels and behavior under different environmental conditions. The research was based on two-year hourly data concentrations of inorganic gaseous pollutants, particulate matter, benzene, toluene, m, p-xylenes, total nonmethane hydrocarbons, and meteorological parameters obtained from the Global Data Assimilation System. In order to determine the model that will be capable of achieving a superior level of performance, eight metaheuristics algorithms were tested for eXtreme Gradient Boosting optimization, while the relative SHapley Additive exPlanations values were used to estimate the relative importance of each pollutant level and meteorological parameter for the prediction of benzene concentrations. According to the results, benzene levels are mostly shaped by toluene and the finest aerosol fraction concentrations, in the environment governed by temperature, volumetric soil moisture content, and momentum flux direction, as well as by levels of total nonmethane hydrocarbons and total nitrogen oxide. The types of conditions which provided the environment for the impact of toluene, the finest aerosol, and temperature on benzene dynamics are distinguished and described.

Polycyclic aromatic hydrocarbons (PAHs) refer to a group of several hundred compounds, among which 16 are identified as priority pollutants, due to their adverse health effects, frequency of occurrence, and potential for human exposure. This study is focused on benzo(a)pyrene, being considered an indicator of exposure to a PAH carcinogenic mixture. For this purpose, we have applied the XGBoost model to a two-year database of pollutant concentrations and meteorological parameters, with the aim to identify the factors which were mostly associated with the observed benzo(a)pyrene concentrations and to describe types of environments that supported the interactions between benzo(a)pyrene and other polluting species. The pollutant data were collected at the energy industry center in Serbia, in the vicinity of coal mining areas and power stations, where the observed benzo(a)pyrene maximum concentration for a study period reached 43.7 $\mathrm{ng}{\mathrm{m}}^{-3}$. The metaheuristics algorithm has been used to optimize the XGBoost hyperparameters, and the results have been compared to the results of XGBoost models tuned by eight other cutting-edge metaheuristics algorithms. The best-produced model was later on interpreted by applying Shapley Additive exPlanations (SHAP). As indicated by mean absolute SHAP values, the temperature at the surface, arsenic, PM${}_{10}$, and total nitrogen oxide (NOx) concentrations appear to be the major factors affecting benzo(a)pyrene concentrations and its environmental fate.

The growing demand for metal production promotes the search for alternative sources and novel modalities in metallurgy. Flotation tailings are an important secondary mineral resource; however, they might pose a potential environmental threat due to containing toxic metals. Therefore, proper leaching reagent selection is required. Ozone is an alternative oxidizing agent for metal leaching, as its use prevents contaminating product generation while increasing the noble metal extraction efficiency in the presence of complexing agents. In this study, the feasibility and efficiency of combining the use of thiosulfate and ozone for gold and silver extraction have been investigated as an eco-friendly alternative for recovery from flotation tailings. Two sets of samples from old flotation tailings of Copper Mine Bor (Serbia) were prepared and physico-chemically characterized, then treated in two experimental leaching procedures, followed by thorough XRD and SEM/EDS analyses of the products. It showed that after 1 h of leaching in a water medium at room temperature and a solid-to-liquid phase ratio of 1:4, 88.8% of Cu was obtained, while a high efficiency of Au extraction from solid residue (after Cu leaching) was attained (83.4%). The results suggest that ozone-assisted leaching mediated by Ca-thiosulfate can be an effective eco-friendly treatment for noble metals recovery from sulfide-oxide ores.

Artificial objects, particularly tunnels used for water transport under pressure, impact the geological and hydrogeological environment to a greater or lesser extent, and it is vital to assess their contributions to groundwater quality. Although tunnels are typically lined with concrete, their interaction with the hydrogeological environment intensifies over time. In this study, the detailed spatiotemporal monitoring of all hydrogeological features within the potential influence zone of the hydraulic tunnel of the Pirot Hydropower Plant has been conducted in order to determine the degree of interaction between the artificial object and the natural environment in real time, and to assess the correlation between monitored parameters. Natural conditions of the environment were defined, as well as potential changes through the observing groundwater regimes. The monitoring network included observations of groundwater regimes at seven springs located in close proximity to the hydraulic tunnel, within the tunnel, at three piezometers, and along the river, while methods employed were hydrological monitoring, physicochemical monitoring, and groundwater piezometer sensing. Cross-correlation analysis has been applied for assessing the impact of precipitation dynamics on the spring discharge regime. The results indicate a direct influence of the tunnel on the hydrogeological environment, proving the consistency and high correlation between the monitored parameters.