Mismanaged plastic litter submitted to environmental conditions may breakdown into smaller fragments, eventually reaching nano-scale particles (nanoplastics, NPLs). In this study, pristine beads of four different types of polymers, three oil-based (polypropylene, PP; polystyrene, PS; and low-density polyethylene, LDPE) and one bio-based (polylactic acid, PLA) were mechanically broken down to obtain more environmentally realistic NPLs and its toxicity to two freshwater secondary consumers was assessed. Thus, effects on the cnidarian Hydra viridissima (mortality, morphology, regeneration ability, and feeding behavior) and the fish Danio rerio (mortality, morphological alterations, and swimming behavior) were tested at NPLs concentrations in the 0.001 to 100 mg/L range. Mortality and several morphological alterations were observed on hydras exposed to 10 and 100 mg/L PP and 100 mg/L LDPE, whilst regeneration capacity was overall accelerated. The locomotory activity of D. rerio larvae was affected by NPLs (decreased swimming time, distance or turning frequency) at environmentally realistic concentrations (as low as 0.001 mg/L). Overall, petroleum- and bio-based NPLs elicited pernicious effects on tested model organisms, especially PP, LDPE and PLA. Data allowed the estimation of NPLs effective concentrations and showed that biopolymers may also induce relevant toxic effects.
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http://dx.doi.org/10.1016/j.scitotenv.2023.163447 | DOI Listing |
Mar Pollut Bull
January 2025
Ocean Environment Institute, Oceanic Consulting and Trading, Seoul, Republic of Korea.
This study simulated the dispersion of Cs in the North Pacific using a Lagrangian particle model, incorporating basin-wide atmospheric deposition and direct release from the Fukushima accident. Three experiments examined the impact of vertical diffusion and velocity on dispersion behavior. EXP01 and EXP02 assumed zero vertical velocity with different vertical diffusion coefficients (1 × 10 and 2 × 10 m/s, respectively), while EXP03 used a 3-day average vertical velocity and the same diffusion coefficient as EXP01.
View Article and Find Full Text PDFWater Res X
December 2024
Professor, Department of Civil and Architectural Engineering and Mechanics, The University of Arizona, Tucson, AZ 85721, USA.
Smart meters such as advanced metering infrastructure (AMI) can significantly improve identifying realistic sized leaks in water distribution networks (WDNs). However, to date, detection/localization methods for AMI systems are extremely limited. In this study, to examine the benefits of using AMIs for leak detection within distribution network, a three-dimensional (3D) convolutional neural network (CNN) deep learning (DL) model is proposed that can account for temporally and spatially distributed information of pressures.
View Article and Find Full Text PDFImmersive virtual reality (VR) environments are a powerful tool to explore cognitive processes ranging from memory and navigation to visual processing and decision making-and to do so in a naturalistic yet controlled setting. As such, they have been employed across different species, and by a diverse range of research groups. Unfortunately, designing and implementing behavioral tasks in such environments often proves complicated.
View Article and Find Full Text PDFJ Phys Chem A
January 2025
Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States.
Theoretical simulations of electron detachment processes are vital for understanding chemical redox reactions, semiconductor and electrochemical properties, and high-energy radiation damage. However, accurate calculations of ionized electronic states are very challenging due to their open-shell nature, importance of electron correlation effects, and strong interactions with chemical environment. In this work, we present an efficient approach based on algebraic diagrammatic construction theory with polarizable embedding that allows to accurately simulate ionized electronic states in condensed-phase or biochemical environments (PE-IP-ADC).
View Article and Find Full Text PDFNano Lett
January 2025
Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States.
Although wastewater-based epidemiology has been used extensively for the surveillance of viral diseases, it has not been used to a similar extent for bacterial diseases. This is in part owing to difficulties in distinguishing pathogenic from nonpathogenic bacteria using PCR methods. Here, we show that surface-enhanced Raman spectroscopy (SERS) can be a scalable, label-free method for the detection of bacteria in wastewater.
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