Tracing microplastics in marine fish: Ecological threats and human exposure in the Bay of Bengal.

IF 8.2 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Science of the Total Environment Pub Date : 2025-02-01 Epub Date: 2025-01-20 DOI:10.1016/j.scitotenv.2025.178462
Md Mazharul Islam, A B M Sadique Rayhan, Jun Wang, Md Ali Hossain Shamim, Hongwei Ke, Chunhui Wang, Xuehong Zheng, Ding Chen, Minggang Cai
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Abstract

This research on microplastics (MPs) in marine environments, particularly in Bay of Bengal fish, underscores the limited comprehension of their accumulation and potential health and environmental consequences. The study investigated the abundance of MPs in the organs of nine marine fish species from the north Bay of Bengal, assessing their polymeric risks and implications for human health. The average MPs ingested by each individual was 32.9 ± 3.0 items/ind.10 g-1 predominantly fibers (93.1 %), followed by fragments (6.1 %), with black being the most common color (76.3 %). The primary polymers identified were polyvinyl alcohol (PVA) (19.4 %), polyether sulfone (PES) (10.7 %), polyamide PA (8.7 %), acrylic, and polyethylene (PE), in the 500-5000 (80 %) μm size range. A moderate negative correlation with strong statistical significance was found with girth sizes and MPs concentration of average (Pearson's r = -0.5728, p < 0.0001). Body weight exhibited moderate negative correlations with MPs abundance in fish tissues (Pearson's r = -0.4701, p < 0.0001). Movement behavior analysis showed a negative correlation between MPs in fish tissues and depth range (Pearson's r = -0.4231, p < 0.0001). Demersal species contained more MPs than pelagic species, and carnivorous fishes had higher MPs levels than omnivorous and planktivorous fishes. The contamination factors (CF), pollution load index (PLI), and polymeric hazard index (PHI) were high and associated with untreated industrial and municipal wastewater sources. The estimated daily intake (EDI) of MPs for adults and children indicates significant health risks. The study improves our comprehension of MPs contamination, providing a significant reference for the appropriate governance, tracking, and reducing pollutants in marine animals in coastal waters.

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追踪海洋鱼类中的微塑料:孟加拉湾的生态威胁和人类暴露。
这项关于海洋环境,特别是孟加拉湾鱼类中的微塑料(MPs)的研究,强调了对其积累及其潜在的健康和环境后果的了解有限。该研究调查了孟加拉湾北部九种海洋鱼类器官中MPs的丰度,评估了它们的聚合风险及其对人类健康的影响。每个个体平均摄取的MPs为32.9±3.0个/个。10 g-1主要是纤维(93.1%),其次是碎片(6.1%),黑色是最常见的颜色(76.3%)。鉴定的主要聚合物为聚乙烯醇(PVA)(19.4%)、聚醚砜(PES)(10.7%)、聚酰胺PA(8.7%)、丙烯酸和聚乙烯(PE),粒径在500 ~ 5000 μm(80%)之间。腰围大小与平均MPs浓度呈中等负相关,具有较强的统计学意义(Pearson’s r = -0.5728, p
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来源期刊
Science of the Total Environment
Science of the Total Environment 环境科学-环境科学
CiteScore
17.60
自引率
10.20%
发文量
8726
审稿时长
2.4 months
期刊介绍: The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere. The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.
期刊最新文献
Development and in-vitro assessment of novel oxygen-releasing feed additives to reduce enteric ruminant methane emissions. Corrigendum to "Maternal Zearalenone exposure impacted ovarian follicle formation and development of suckled offspring" [Sci. Total Environ. 788 (2021) 147792]. Modeling dissolved organic carbon export from water supply catchments in the northeastern United States. Tracing microplastics in marine fish: Ecological threats and human exposure in the Bay of Bengal. Assessing biochar's impact on greenhouse gas emissions, microbial biomass, and enzyme activities in agricultural soils through meta-analysis and machine learning.
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