Silver nanoparticles (AgNPs) are used in many industries for multiple applications that inevitably release AgNPs into surface water sources. The formation kinetics of disinfection by-products (DBPs) in the presence of AgNPs was investigated during chlorination. Experiments were carried out with raw water from a canal in Songkhla, Thailand, which analyzed the formation potential (FP) of trihalomethanes FP (THMFP), iodo-trihalomethanes FP (I-THMFP), haloacetonitriles FP (HANFP), and trichloronitromethane FP. Increased AgNP concentrations by 10–20 mg/L led to a higher specific formation rate of chloroform which is described by zero- and first-order kinetics. The increase in the specific formation of chloroform as increasing chlorine contact time could enhance both the THMFP rates and the maximum THMFP concentrations in all tested AgNPs. The AgNP content did not have a significant influence on I-THMFP and HANFP concentrations or speciation. The I-THMFP and HANFP increased in a short-chlorination time as mostly complete formation <12 h, and then the rate decreased as the reaction proceeded. The levels of THMs and many emerging DBPs are related to the presence of AgNPs in chlorinated water and chlorine reaction time. THMFP had a higher impact on integrated toxic risk value (ITRV) than I-THMFP and HANFP because of the chlorination of water with AgNPs. The chlorine reaction time was more effective for increasing the ITRV of THMFP than the level of AgNPs. Water treatment plants should control the DBPs that cause possible health risks from water consumption by optimizing water distribution time.

Eyes convey important information about the external and internal worlds of animals. Individuals can follow the gaze of others to learn about the location of salient objects as well as assess eye qualities to evaluate the health, age or other internal states of conspecifics. Because of the increasing prevalence of artificial lighting at night (ALAN), urbanized individuals can potentially garner information from conspecific eyes under both daylight and ALAN. We tested this possibility using a visual modeling approach in which we estimated the maximum distance at which individuals could detect conspecific eyes under daylight and high levels of ALAN. We also estimated the minimum light level at which individuals could detect conspecific eyes. Great-tailed grackles (Quiscalus mexicanus) were used as our study species because they are highly social and are unusual among birds in that they regularly gather at nocturnal roosts in areas with high levels of ALAN. This visual modelling approach revealed that grackles can detect conspecific eyes under both daylight and ALAN, regardless of iris coloration. The grackles could detect conspecific eyes at farther distances in daylight compared to ALAN. Our results highlight the potential importance of lighting conditions in shaping social interactions.

Nanoplastic is recognized as an emerging environmental pollutant due to the anticipated ubiquitous distribution, increasing concentration in the ocean, and potential adverse health effects. While our understanding of the ecological impacts of nanoplastics is still limited, we benefit from relatively rich toxicological studies on other nanoparticles such as nano metal oxides. However, the similarity and difference in the toxicokinetic and toxicodynamic aspects of plastic and metallic nanoparticles remain largely unknown. In this study, juvenile Pacific white shrimp Litopenaeus vannamei was exposed to two types of nanoparticles at environmentally relative low and high concentrations, i.e., 100 nm polystyrene nanoplastics (nano-PS) and titanium dioxide nanoparticles (nano-TiO₂) via dietary exposure for 28 days. The systematic toxicological evaluation aimed to quantitatively compare the accumulation, excretion, and toxic effects of nano-PS and nano-TiO₂. Our results demonstrated that both nanoparticles were ingested by L. vannamei with lower egestion of nano-TiO₂ than nano-PS. Both nanoparticles inhibited the growth of shrimps, damaged tissue structures of the intestine and hepatopancreas, disrupted expression of immune-related genes, and induced intestinal microbiota dysbiosis. Nano-PS exposure caused proliferative cells in the intestinal tissue, and the disturbance to the intestinal microbes was also more serious than that of nano-TiO₂. The results indicated that the effect of nano-PS on the intestinal tissue of L. vannamei was more severe than that of nano-TiO₂ with the same particle size. The study provides new theoretical basis of the similarity and differences of their toxicity, and highlights the current lack of knowledge on various aspects of absorption, distribution, metabolism, and excretion (ADME) pathways of nanoplastics.

Dissolved inorganic nitrogen (DIN) is considered the main factor that induces eutrophication in water, and is readily influenced by hydrodynamic activities. In this study, a 4-year field investigation of nitrogen dynamics in a turbulent river was conducted, and a laboratory study was performed in the approximately homogeneous turbulence simulation system to investigate potential mechanisms involved in DIN transformation under turbulence. The field investigation revealed that, contrary to NO⁻₃ dynamics, the NH⁺₄ concentrations in water were lower in flood seasons than in drought seasons. Further laboratory results demonstrated that limitation of dissolved oxygen (DO) caused inactive nitrification and active denitrification in static river sediment. In contrast, the increased DO levels in turbulent river intensified the mineralization of organic nitrogen in sediment; moreover, ammonification and nitrification were activated, while denitrification was first activated and then depressed. Turbulence therefore decreased NH⁺₄ and NO⁻₂ concentrations, but increased NO⁻₃ and total DIN concentrations in the overlying water, causing the total DIN to increase from 0.4 mg/L to maximum of 1.0 and 1.7 mg/L at low and high turbulence, respectively. The DIN was maintained at 0.7 and 1.0 mg/L after the 30-day incubation under low and high turbulence intensities (ε) of 3.4 × 10⁻⁴ and 7.4 × 10⁻² m²/s³, respectively. These results highlight the critical role of DO in DIN budgets under hydrodynamic turbulence, and provide new insights into the DIN transport and transformation mechanisms in turbulent rivers.

Wastewater and stormwater are both considered as critical pathways contributing microplastics (MPs) to the aquatic environment. However, there is little information in the literature about the potential influence of constructed wetlands (CWs), a commonly used wastewater and stormwater treatment system. This study was conducted to investigate the abundance and distribution of MPs in water and sediment at five CWs with different influent sources, namely stormwater and wastewater. The MP abundance in the water samples ranged between 0.4 ± 0.3 and 3.8 ± 2.3 MP/L at the inlet and from 0.1 ± 0.0 to 1.3 ± 1.0 MP/L at the outlet. In the sediment, abundance of MPs was generally higher at the inlet, ranging from 736 ± 335 to 3480 ± 4330 MP/kg dry sediment and decreased to between 19.0 ± 16.4 and 1060 ± 326 MP/kg dry sediment at the outlet. Although no significant differences were observed in sediment cores at different depth across the five CWs, more MPs were recorded in silt compared to sandy sediment which indicated sediment grain size could be an environmental factor contributing to the distribution of MPs. Polyethylene terephthalate (PET) fibres were the dominant polymer type found in the water samples while polyethylene (PE) and polypropylene (PP) fragments were predominantly recorded in the sediment. While the size of MPs in water varied across the studied CWs, between 51% and 64% of MPs in the sediment were smaller than 300 μm, which raises concerns about the bioavailability of MPs to a wider range of wetland biota and their potential ecotoxicological effects. This study shows that CWs can not only retain MPs in the treated water, but also become sinks accumulating MPs over time.

Granular activated carbon (GAC) has been used to remove per- and polyfluoroalkyl substances (PFASs) from industrial or AFFF-impacted waters, but its effectiveness can be low because adsorption of short-chained PFASs is ineffective and its sites are exhausted rapidly by co-contaminants. To increase adsorption of anionic PFASs on GAC by electrostatic attractions, we modified GAC's surface with the cationic polymer poly diallyldimethylammonium chloride (polyDADMAC) and tested its capacity in complex water matrices containing dissolved salts and humic acid. Amending with concentrations of polyDADMAC as low as 0.00025% enhanced GAC's adsorption capacity for PFASs, even in the presence of competing ions. This suggests that electrostatic interactions with polyDADMAC's quaternary ammonium functional groups helped bind organic and inorganic ions as well as the headgroup of short-chain PFASs, allowing more overall PFAS removal by GAC. Evaluating the effect of polymer dose is important because excessive addition can block pores and reduce overall PFAS removal rather than increase it. To decrease the waste associated with this adsorption strategy by making the adsorbent viable for more than one saturation cycle, a regeneration method is proposed which uses low-power ultrasound to enhance the desorption of PFASs from the polyDADMAC-GAC with minimum disruption to the adsorbent's structure. Re-modification with the polymer after sonication resulted in a negligible decrease in the sorbent's capacity over four saturation rounds. These results support consideration of polyDADMAC-modified GAC as an effective regenerable adsorbent for ex-situ concentration step of both short and long-chain PFASs from real waters with high concentrations of competing ions and low PFAS loads.

Selenium (Se) is regarded as a trace element for humans, but it is toxic in excess. In natural environments, the mobility of Se is dominantly controlled by the Se oxyanions with high solubility such as selenite (Se(IV)). Se(IV) is often associated with the omnipresent ferrihydrite and coexisting organic matter. However, there is little information on the dynamic interactions among Se(IV), fulvic acid, and ferrihydrite. This study investigated the influence of fulvic acid on ferrihydrite-Se(IV) coprecipitates (Fh-Se) transformation for 8 days and the subsequent behavior of Se(IV) at varied pH (5.0, 7.5, and 10.0). Results showed that fulvic acid had different effects on Fh-Se transformation at varied pH values. Fh-Se transformation was promoted by fulvic acid at initial pH 5.0 whereas it was inhibited at initial pH 10.0. Interestingly, at initial pH 7.5, Fh-Se transformation was promoted at a low C/Fe ratio while it was suppressed at a high C/Fe ratio. Besides, fulvic acid induced the generation of more extractable Se(IV) at initial pH 5.0 and more coprecipitated Se(IV) at initial pH 7.5 and blocked the release of Se(IV) at initial pH 10.0. Fulvic acid possibly interacted with Se(IV) via carboxyl complexation and weakened the inhibition of Se(IV) on Fh-Se transformation. Thus, fulvic acid increased the transformation rate of Fh-Se. These findings help to uncover the environmental behavior of Se(IV) and organic matter during ferrihydrite transformation.

To evaluate the chemical status of groundwater bodies (GWB) according to the European Groundwater Directive, EU Member States are required to take into account natural background levels (NBLs) where needed. Assessing the NBLs in coastal GWBs is complicated by seawater intrusion which can be amplified by groundwater withdrawals increasing the salinization of such groundwater systems. This paper proposes a new method for the NBLs assessment in coastal areas based on a double pre-selection (PS) with fixed/dynamic limits. A case study in the Apulia region, located in southeastern Italy, is proposed, where we investigated four adjacent GWBs which form the complex karst, fractured Murgia aquifer, hosted in the Jurassic-Cretaceous carbonate platform, bounded by two seas and sustained by saltwater of marine intrusion in the coastal areas. Data related to 139 monitoring stations (MSs) of the regional groundwater monitoring network were used. The first PS, “static”, based on a fixed limit of anthropogenic contamination markers (NO₃ and NH₄), allows for the elimination of MSs impacted by human activities. On these, the second PS, “dynamic”, based on the identification of Cl anomalous values, allows for the identification of additional MSs affected by saline contamination. The residual dataset of MSs was used for the definition of NBLs of Cl, SO₄, F and B. A statistical comparison with historical Cl observations finally allowed us to verify if the salinity of current groundwater is representative of pristine conditions. The calculated NBLs of salinity parameters are higher for the two coastal GWBs, with chloride values between 0.8 and 2 mg/L. Conversely, fluorides always show very low NBLs. The double PS approach seems more effective for NBLs calculation in coastal aquifers affected by saline contamination, where the use of a fixed Cl limit fails. It may respond to the international needs for a standardized procedure for NBL assessment.

Predicting the occurrence of algal blooms is of great importance in managing water quality. Moreover, the demand for predictive models, which are essential tools for understanding the drivers of algal blooms, is increasing with global warming. However, modeling cyanobacteria dynamics is a challenging task. We developed a multivariate Chain-Bernoulli-based prediction model to effectively forecast the monthly sequences of algal blooms considering hydro-environmental predictors (water temperature, total phosphorus, total nitrogen, and water velocity) at a network of stations. The proposed model effectively predicts the risk of harmful algal blooms, according to performance measures based on categorical metrics of a contingency table. More specifically, the model performance assessed by the LOO cross-validation and the skill score for the POD and CSI during the calibration period was over 0.8; FAR and MR were less than 0.15. We also explore the relationship between hydro-environmental predictors and algal blooms (based on cyanobacteria cell count) to understand the dynamics of algal blooms and the relative contribution of each potential predictor. A support vector machine is applied to delineate a plane separating the presence and absence of algal bloom occurrences determined by stochastic simulations using different combinations of predictors. The multivariate Chain-Bernoulli-based prediction model proposed here offers effective, scenario-based, and strategic options and remedies (e.g., controlling the governing environmental predictors) to relieve or reduce increases in cyanobacteria concentration and enable the development of water quality management and planning in river systems.