Keyword search (4,164 papers available)

"Sampling" Keyword-tagged Publications:

Title Authors PubMed ID
1 Variation the in relationship between urban tree canopy and air temperature reduction under a range of daily weather conditions Locke DH; Baker M; Alonzo M; Yang Y; Ziter CD; Murphy-Dunning C; O' Neil-Dunne JPM; 38352758
BIOLOGY
2 Identification of the driving factors of microplastic load and morphology in estuaries for improving monitoring and management strategies: A global meta-analysis Feng Q; An C; Chen Z; Lee K; Wang Z; 37336353
ENCS
3 Dense Sampling Approaches for Psychiatry Research: Combining Scanners and Smartphones McGowan AL; Sayed F; Boyd ZM; Jovanova M; Kang Y; Speer ME; Cosme D; Mucha PJ; Ochsner KN; Bassett DS; Falk EB; Lydon-Staley DM; 36797176
PSYCHOLOGY
4 How well do covariates perform when adjusting for sampling bias in online COVID-19 research? Insights from multiverse analyses Joyal-Desmarais K; Stojanovic J; Kennedy EB; Enticott JC; Boucher VG; Vo H; Košir U; Lavoie KL; Bacon SL; 36335560
HKAP
5 Air monitoring of tire-derived chemicals in global megacities using passive samplers Johannessen C; Saini A; Zhang X; Harner T; 36152723
CHEMBIOCHEM
6 Bayesian Learning of Shifted-Scaled Dirichlet Mixture Models and Its Application to Early COVID-19 Detection in Chest X-ray Images Bourouis S; Alharbi A; Bouguila N; 34460578
ENCS
7 The Epistemology of Evolutionary Psychology Offers a Rapprochement to Cultural Psychology Gad Saad 33224071
JMSB
8 SPARK: Sparsity-based analysis of reliable k-hubness and overlapping network structure in brain functional connectivity. Lee K, Lina JM, Gotman J, Grova C 27046111
PERFORM

 

Title:Identification of the driving factors of microplastic load and morphology in estuaries for improving monitoring and management strategies: A global meta-analysis
Authors:Feng QAn CChen ZLee KWang Z
Link:https://pubmed.ncbi.nlm.nih.gov/37336353/
DOI:10.1016/j.envpol.2023.122014
Publication:Environmental pollution (Barking, Essex : 1987)
Keywords:Anthropogenic activitiesEstuaryExtractionMicroplasticMorphologySampling
PMID:37336353 Category: Date Added:2023-06-20
Dept Affiliation: ENCS

Description:

Estuaries are one of the primary pathways for transferring microplastics (MPs) from the land to the ocean. A comprehensive understanding of the load, morphological characteristics, driving factors, and potential risks of MPs in estuaries is imperative to inform reliable management in this critical transboundary area. Extracted from 135 publications, a global meta-analysis comprising 1477 observations and 124 estuaries was conducted. MP abundance in estuaries was tremendously variable, reaching a mean of 21,342.43 ± 122,557.53 items/m3 in water and 1312.79 ± 6295.73 items/kg in sediment. Fibers and fragments take up a majority proportion in estuaries. Polyester, polypropylene, and polyethylene are the most detected MP types. Around 68.73% and 85.51% of MPs detected in water and sediment are smaller than 1 µm. The redundancy analysis revealed that the explanatory factors influencing the morphological characteristics of MP differed between water and sediment. Regression analysis shows that MP abundance in water is significantly inversely correlated with mesh/filter size, per capita plastic waste, and the Human Development Index, whereas it is significantly positively correlated with population density and share of global mismanaged plastic waste. MP abundance in sediment significantly positively correlated with aridity index and probability of plastic entering the ocean, while significantly negatively correlated with mesh/filter size. Analysis based on Geodector identified that the extraction method, density of flotation fluid, and sampling depth are the top three explanatory factors for MP abundance in water, while the share of global mismanaged plastic waste, the probability of plastic being emitted into the ocean, and population density are the top three explanatory factors for MP abundance in sediment. In the studied estuaries, 46.75% of the water and 2.74% of the sediment are categorized into extremely high levels of pollution, while 73.08% of the water and 43.48% of the sediment belong to class V of the potential ecological index.





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