Chitosan is very effective in removing metal ions through their adsorption. A preliminary investigation of the adsorption of chromium(III) by chitosan was carried out by means of batch tests as a function of contact time, pH, ion competition, and initial chromium(III) concentration. The rate of adsorption was rather rapid (t_1/2 < 18 min) and influenced by the presence of other metal ions. The obtained data were tested using the Langmuir and Freundlich isotherm models and, based on R² values, the former appeared better applicable than the latter. Chitosan was found to have an excellent loading capacity for chromium(III), namely 138.0 mg Cr per g of chitosan at pH = 3.8, but metal ions adsorption was strongly influenced by the pH. About 76% of the recovered chromium was then removed simply by washing the used chitosan with 0.1 M EDTA (Ethylenediaminetetraacetic acid) solution. This study demonstrates that chitosan has the potential to become an effective and low-cost agent for wastewater treatment (e.g., tannery waste) and in situ environmental remediation.

The release of plastics in freshwater is an increasing concern for ecosystem safety worldwide. There is a large knowledge gap on plastic pollution in Mediterranean freshwater, especially regarding surveys along entire river courses, partly due to the absence of guidelines for standardized monitoring of plastics. The present study analyzes the plastic distribution from source to mouth, also according to the River Continuum Concept, of the environmental matrices (water and sediments) and biota (caddisfly cases) of the Mediterranean River Mignone and their cause-effect relationship. The results of the water quality indices (Extended Biotic Index and Fluvial Functionality Index) were compared with the plastic concentrations observed in the water and sediments to explore what relationship there might be and to understand if the indices could be a proxy of the plastic pollution. Our results showed a significant prevalence of blue fibers, the concentration of which in water and sediment is positively associated. Plastic concentration at each site was not accurately detected by the water quality indices. These results may suggest that the factors considered by water quality indices are not able to detect the contamination of plastic pollution. It is mandatory to identify new tools for assessing the plastic impacts on river ecosystems.

Indoor production of basil (Ocimum basilicum L.) is influenced by light spectrum, photosynthetic photon flux density (PPFD), and the photoperiod. To investigate the effects of different lighting on growth, chlorophyll content, and secondary metabolism, basil plants were grown from seedlings to fully expanded plants in microcosm devices under different light conditions: (a) white light at 250 and 380 μmol·m⁻²·s⁻¹ under 16/8 h light/dark and (b) white light at 380 μmol·m⁻²·s⁻¹ under 16/8 and 24/0 h light/dark. A higher yield was recorded under 380 μmol·m⁻²·s⁻¹ compared to 250 μmol·m⁻²·s⁻¹ (fresh and dry biomasses 260.6 ± 11.3 g vs. 144.9 ± 14.6 g and 34.1 ± 2.6 g vs. 13.2 ± 1.4 g, respectively), but not under longer photoperiods. No differences in plant height and chlorophyll content index were recorded, regardless of the PPFD level and photoperiod length. Almost the same volatile organic compounds (VOCs) were detected under the different lighting treatments, belonging to terpenes, aldehydes, alcohols, esters, and ketones. Linalool, eucalyptol, and eugenol were the main VOCs regardless of the lighting conditions. The multivariate data analysis showed a sharp separation of non-volatile metabolites in apical and middle leaves, but this was not related to different PPFD levels. Higher levels of sesquiterpenes and monoterpenes were detected in plants grown under 250 μmol·m⁻²·s⁻¹ and 380 μmol·m⁻²·s⁻¹, respectively. A low separation of non-volatile metabolites based on the photoperiod length and VOC overexpression under longer photoperiods were also highlighted.

Prompt estimation of phytoplankton biomass is critical in determining the ecological quality of freshwaters. Remote Sensing (RS) may provide new opportunities to integrate with situ traditional monitoring techniques. Nonetheless, wide regional and temporal variability in freshwater optical constituents makes it difficult to design universally applicable RS protocols. Here, we assessed the potential of two neural networks-based models, namely the Case 2 Regional CoastColour (C2RCC) processor and the Mixture Density Network (MDN), applied to MSI Sentinel-2 data for monitoring Chlorophyll (Chl) content in three monomictic volcanic lakes while accounting for the effect of their specific water circulation pattern on the remotely-sensed and in situ data relation. Linear mixed models were used to test the relationship between the remote sensing indices calculated through C2RCC (I_NN) and MDN (I_MDN), and in situ Chl concentration. Both indices proved to explain a large portion of the variability in the field data and exhibited a positive and significant relationship between Chl concentration and satellite data, but only during the mixing phase. The significant effect of the water circulation period can be explained by the low responsiveness of the RS approaches applied here to the low phytoplankton biomass, typical of the stratification phase. Sentinel-2 data proved their valuable potential for the remote sensing of phytoplankton in small inland water bodies, otherwise challenging with previous sensors. However, caution should be taken, since the applicability of such an approach on certain water bodies may depend on hydrological and ecological parameters (e.g., thermal stratification and seasonal nutrient availability) potentially altering RS chlorophyll detection by neural networks-based models, despite their alleged global validity.