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首页> 外文期刊>The Science of the Total Environment >Spatiotemporal toxicity assessment of suspended particulate matter (SPM)-bound polycyclic aromatic hydrocarbons (PAHs) in Lake Chaohu, China: Application of a source-based quantitative method
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Spatiotemporal toxicity assessment of suspended particulate matter (SPM)-bound polycyclic aromatic hydrocarbons (PAHs) in Lake Chaohu, China: Application of a source-based quantitative method

机译:巢湖湖悬浮颗粒物(SPM) - 悬浮颗粒物质(SPM) - 淘汰多环芳烃烃(PAH)的时空毒性评估:基于源的定量方法应用

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摘要

The spatiotemporal associations between the emissions and environmental toxicities of polycyclic aromatic hydrocarbons (PAHs) in lake still remain an issue. Here, we focused on the suspended particulate matter (SPM)-bound PAHs in Lake Chaohu, China to quantitatively estimate their spatiotemporal toxicities from different sources. A source-based quantitative method, positive matrix factorization (PMF)-benzo[a]pyrene-based toxic equivalency (TEQ_(BaP)) model, was applied. Firstly, we investigated the spatiotemporal characteristics of SPM-bound PAHs. The concentrations of ∑_(21) PAHs ranged from 1646 to 19267 ng·g~(-1). Low-ring PAHs were found to have the highest fractions. T-distributed stochastic neighbor embedding (t-SNE)-partitioning around medoid (PAM) technic revealed significantly spatiotemporal variation characteristics of SPM-bound PAHs in Lake Chaohu. Season, location (west or east lake zone), and sample classification (estuary or lake) together governed the patterns. Then, their potential sources were apportioned. Our results found that diagnostic ratios did not work perfectly. However, 3 factors were separated by PMF model. Unburned petroleum (F1), biomass, coal and gasoline combustion (F2), and diesel. straw combustion (F3) were the main sources of PAHs, accounting for 36.16%. 48.96% and 14.88%. respectively. The patterns of the source profiles were season-dependent Finally, the toxicity of SPM-bound PAHs from different sources were predicted by PMF-TEQ_(BaP) model, and the model predictions were satisfactorily acceptable. Overall, predicted ∑_(19)TEQ_(BaP) of SPM-bound PAHs in Lake Chaohu ranged from 20.8 to 947.9 ng·g~(-1). Benzo[e]pyrene (BeP), benzo[a]pyrene (BaP) and benzo[b]fluoranthene (BbF) were the main toxic species. Temporally, PAH toxicity posed significantly seasonal differences. F3 had primary contributions to ∑_(19) TEQ_(BaP). Cutting the diesel consumption and using cleaner energy substitutes were suggested to reduce the PAH toxicity in Lake Chaohu. Overall, we expected this study could give new insights into the spatiotemporal associations between the sources and toxicities of SPM-bound PAHs in lake ecosystem.
机译:湖泊中多环芳烃(PAHS)排放和环境毒性之间的时空协会仍然是一个问题。在这里,我们专注于巢湖湖中的悬浮颗粒物(SPM) - 基本Pahs,以定量估计其来自不同来源的时空毒性。应用了一种基于源的定量方法,施加阳性基质分解(PMF) - 苯并[a]芘基毒物等效(TEQ_(BAP))模型。首先,我们调查了SPM绑定的PAHS的时空特征。 σ_(21)PAH的浓度范围为1646至19267 ng·g〜(-1)。发现低环PAHs具有最高的分数。嵌入(T-SNE)嵌入(T-SNE) - 麦细管(PAM)技术的分区,揭示了巢湖湖中SPM绑定的PAHS的显着不稳定的变化特性。季节,地点(西部或东湖区),以及样品分类(河口或湖泊)共同治理了这些模式。然后,他们的潜在来源分配了。我们的结果发现,诊断比率并没有完全起作用。然而,PMF模型分离了3个因素。未燃烧的石油(F1),生物质,煤和汽油燃烧(F2)和柴油。秸秆燃烧(F3)是PAHS的主要来源,占36.16%。 48.96%和14.88%。分别。源型材的模式最终依赖于季节性,通过PMF-TEQ_(BAP)模型预测了来自不同来源的SPM的PAHs的毒性,并且模型预测是令人满意的可接受的。总的来说,预测Σ_(19)SPM绑定的PAHS的TEQ_(BAP)在湖湖湖畔的chh的范围为20.8至947.9 ng·g〜(-1)。苯并[E]芘(BEP),苯并[a]芘(BAP)和苯并[b]氟(BBF)是主要的有毒物种。暂时,PAH毒性显着提出了季节性差异。 F3对Σ_(19)TEQ_(BAP)具有主要贡献。建议切割柴油消耗和使用更清洁的能量替代品,以减少巢湖湖的PAH毒性。总体而言,我们预计这项研究可以对湖泊生态系统湖泊合并PAHS的来源和毒性之间的时空协会提供新的见解。

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