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Predicting the total PAHs concentrations in sediments from selected congeners using a multiple linear relationship

In this study, we observed that four congeners, including naphthalene (Nap), acenaphthylene (Acy), phenanthrene (Phe), and benz(a)anthracene (BaA), are the characteristic congeners for predicting the emission and the sediment concentrations of polycyclic aromatic hydrocarbons (PAHs). A novel multipl...

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Detalles Bibliográficos
Autores principales: Wang, Weiwei, Xu, Huaping, Qu, Xiaolei, Yang, Kun, Lin, Daohui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8885927/
https://www.ncbi.nlm.nih.gov/pubmed/35228618
http://dx.doi.org/10.1038/s41598-022-07312-2
Descripción
Sumario:In this study, we observed that four congeners, including naphthalene (Nap), acenaphthylene (Acy), phenanthrene (Phe), and benz(a)anthracene (BaA), are the characteristic congeners for predicting the emission and the sediment concentrations of polycyclic aromatic hydrocarbons (PAHs). A novel multiple relationship of the total PAHs concentrations (C(∑PAHs)) in sediments with the concentrations of four congeners was established (p < 0.01, R(2) = 0.95) using published data over the past 30 years. Moreover, the multiple linear relationship of the total PAHs emission factors with the emission factors of four congeners was also established (p < 0.01, R(2) = 0.99). Interestingly, the ratio of multicomponents coefficient from the multiple linear relationship in sediments to that from the multiple linear relationship in emission sources correlated positively with octanol–water partition coefficient (logK(ow)) (p < 0.01, R(2) = 0.88) of the four PAHs congeners. Therefore, a novel model was established to predict C(ΣPAHs) in sediments using the emissions and logK(ow) of the four characteristic PAHs congeners. The percent sample deviation between calculated C(∑PAHs) and their observed values was 54%, suggesting the established model can accurately predict C(ΣPAHs) in sediments.