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 ngm−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, PM10, and total nitrogen oxide (NOx) concentrations appear to be the major factors affecting benzo(a)pyrene concentrations and its environmental fate.

Riparian vegetation supports high biodiversity providing many services and is, therefore, an important landscape element. Riparian ecosystems are subject to numerous pressures leading to population decline and genetic erosion of riparian plants. This may have cascading effects at various ecosystem levels, including decreasing ecosystem services, so identifying the current status of genetic diversity of riparian tree species is vital to improve the effectiveness of restoration efforts. We aimed to elicit expert views on the status and importance of genetic diversity of tree species, and conservation needs across European riparian ecosystems. Sharing of such information among researchers, managers and policymakers has the potential to enhance ecological restoration and management of riparian ecosystems. We identified experts in riparian genetic resources conservation and management across Europe. These included stakeholders with different perspectives, ranging from researchers to practitioners. We designed a set of questionnaires where our identified experts were asked to answer questions related to the status and conservation of genetic diversity of riparian tree species in their respective countries. Specifically, we asked about societal awareness, legislative tools, good practices and conservation or restoration projects accounting for intraspecific genetic diversity and differentiation of tree species in riparian ecosystems. Questionnaire responses were analysed and discussed in light of the scientific literature to define needs and priorities related to the management and conservation of genetic diversity of riparian tree species. The experts recognized that a combination of in situ and ex situ measures and/or integrative conservation of riparian ecosystems is the most appropriate option for conserving the genetic diversity of riparian tree species. Simultaneous application of conservation measures at the level of priority species, identified by experts, and protection of riparian areas are required. Synthesis and applications. This study revealed the importance of recognizing the ecological processes that shape the genetic diversity of riparian tree species in hydrographic networks (dendritic spatial configuration, specific patterns of gene flow among riparian populations, fragmentation of river by dams) but also the need to overcome socio‐economic barriers, such as lack of policy priority, deficiency in funding and weak legislation framework.