Polychlorinated biphenyls (PCBs) are chemicals that have become ubiquitous environmental pollutants due to their past use, persistence, and long-range transport thus requiring continuous monitoring. Therefore, this research was carried out to investigate spatial and temporal trends of seven indicator PCBs and two others (PCB 105 and PCB 156) in the Nairobi River. Levels of PCBs ranged from below detection limit (bdl) to 157.64 ± 1.52 ng g and bdl to 718.78 ± 1.71 ng L for sediment and water, respectively. PCBs 28, 138, and 153 were the most dominant contributing 33.4%, 17.9%, and 14.5% to the total PCBs in sediments and 54.6%, 19.3%, and 14.1% to the total PCBs in water. There was a general increase in ΣPCBs from 18.89 to 151.18 ng g for sediments and 275.52 to 429.84 ng L for water as the River flowed downstream. The dry season recorded the highest ΣPCB in sediments while the rainy season recorded the highest ΣPCBs in water, with levels exceeding the WHO water quality guidelines. Risk assessment revealed that populations living downstream are exposed to high levels of PCBs through the consumption of water. Levels of ΣPCBs downstream also exceeded the sediment quality guidelines meaning that aquatic organisms are threatened.
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http://dx.doi.org/10.1007/s10661-020-08566-x | DOI Listing |
Adv Sci (Weinh)
January 2025
Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Emotion processing is an integral part of everyone's life. The basic neural circuits involved in emotion perception are becoming clear, though the emotion's cognitive processing remains under investigation. Utilizing the stereo-electroencephalograph with high temporal-spatial resolution, this study aims to decipher the neural pathway responsible for discriminating low-arousal and high-arousal emotions.
View Article and Find Full Text PDFJ Am Chem Soc
January 2025
Van 't Hoff Institute for Molecular Sciences, University of Amsterdam, 1098 XH Amsterdam, Netherlands.
We present the synthesis, structural analysis, and remarkable reactivity of the first carbon nanohoop that fully incorporates ferrocene in the macrocyclic backbone. The high strain imposed on the ferrocene by the curved nanohoop structure enables unprecedented photochemical reactivity of this otherwise photochemically inert metallocene complex. Visible light activation triggers a ring-opening of the nanohoop structure, fully dissociating the Fe-cyclopentadienyl bonds in the presence of 1,10-phenanthroline.
View Article and Find Full Text PDFPeerJ
January 2025
Facultad de Ciencias, Universidad Autónoma del Estado de México, Toluca, Estado de México, Mexico.
Heterogeneous environments provide different daily and seasonal thermal conditions for snakes, resulting in temporal and spatial variations in body temperature (Tb). This study analyzes the Tb of in the forest and grassland of a Mexican locality through daily and seasonal profiling. The patterns were obtained from seminatural enclosures in the field with a point sampling strategy to analyze temporal and spatial variations in Tb.
View Article and Find Full Text PDFFront Sociol
January 2025
Faculty of Social and Human Sciences, University of Beira Interior, Covilhã, Portugal.
The platform economy has contributed to new ways of organising business, work, and consumption. To understand the shape and scope of these changes, it is crucial to pay simultaneous attention to these three domains. The new ways of organising, dividing and coordinating work are interlinked with specific ways of consuming services made available by digital platforms.
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.
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