The present study describes the seasonal distribution of microplastics (MPs) and their associated biofilms in the water column of the Netravathi-Gurupura estuary, southwest India. An average abundance of 8.15 (±3.81) particles/l and 1.14 (±0.78) particles/l was observed during the wet and dry seasons, respectively. Fibres, films, and fragments accounted for majority of the microplastics. Polyethylene terephthalate, polyethylene, polyurethane, polyester, polystyrene, and high-density polyethylene were the major polymers. The risk assessment revealed a low Pollution Load Index, but the Polymer Hazard Index showed higher toxicity. Diatoms from nine genera were observed attached to the microplastic samples with Amphora and Navicula spp. reported in both estuaries during both seasons. The considerable diversity of diatoms, along with other microbial groups, in microplastic-associated biofilms in this study, highlights the urgent need to understand the structure and development of microplastic-associated biofilms and their role in the vertical and horizontal transport of microplastics in tropical estuaries.
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http://dx.doi.org/10.1016/j.marpolbul.2024.116750 | DOI Listing |
Mar Pollut Bull
January 2025
Environmental Research Institute, University of the Highlands and Islands, Thurso, UK.
We evaluate global microplastics particle density distribution using field data from 1972 to 2022, made available by the NOAA (National Oceanic and Atmospheric Administration) NCEI (National Centers for Environmental Information) global marine microplastics database. We resampled the measured microplastics density data from NOAA NCEI into a regularly spaced 1° × 1° grid and applied ordinary block kriging on a 1° × 1° mask map of the global oceans to spatially interpolate the gridded data. Climate data were retrieved from the Climate Data Store of the Copernicus Climate Change Service.
View Article and Find Full Text PDFEnviron Geochem Health
January 2025
School of Civil Engineering, Vellore Institute of Technology, Tamil Nadu, Vellore, 632014, India.
Urban environments are heavily influenced by various activities, leading to contamination of water sources by emerging contaminants (ECs). Among these, caffeine (CAF) and N, N-diethyl-meta-toluamide (DEET) are notable ECs frequently found in domestic sewage due to human activities. Despite extensive research on emerging contaminants, limited studies have focused on the seasonal variations, human health and ecological risks of CAF and DEET in urban groundwater, particularly in Indian cities.
View Article and Find Full Text PDFFront Plant Sci
December 2024
Biogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany.
The Amazon forest is the largest source of isoprene emissions, and the seasonal pattern of leaf-out phenology in this forest has been indicated as an important driver of seasonal variation in emissions. Still, it is unclear how emissions vary between different leaf phenological types in this forest. To evaluate the influence of leaf phenological type over isoprene emissions, we measured leaf-level isoprene emission capacity and leaf functional traits for 175 trees from 124 species of angiosperms distributed among brevideciduous and evergreen trees in a central Amazon forest.
View Article and Find Full Text PDFEcol Evol
January 2025
Colección Nacional de Arácnidos, Departamento de Zoologia, Instituto de Biologia Universidad Nacional Autónoma de México Mexico City Mexico.
Extensive grazing carried out freely by exotic goats represents an important source of anthropogenic degradation in seasonally dry tropical forests of Brazil. The presence of these herbivores may negatively impact the local fauna through the reduction of habitat complexity. In this study, we investigate the effect of goat farming in scorpion assemblage from Brazilian seasonally dry tropical forest.
View Article and Find Full Text PDFJ Emerg Manag
January 2025
Department of Landscape & Urban Planning, Cheongju University, Cheongju, South Korea. ORCID: https://orcid.org/0000-0002-4407-2992.
This study delves into how people responded to Winter Storm Frankie in the United States based on X (formerly known as Twitter®) data according to a multitude of regions, periods, sociodemographic characteristics, census regions, and geographical scales. This study finds that people actively respond to natural disasters on X during the winter storm week. Specifically, the highest number of keywords during the winter storm week is 1.
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