Ke Yuan

Dr. Ke Yuan

School of Marine Sciences, Sun Yat-Sen University, Guangzhou, China

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2020 in Science of The Total Environment
Verified
Journal Article
Closed access
RJRuirun Jiang
Ruirun Jiang
JLJiahui Liu
Jiahui Liu
BHBi Huang
Bi Huang
XWXiaowei Wang
Xiaowei Wang
TLTiangang Luan
Tiangang Luan
Ke YuanKe Yuan
Ke Yuan

1 December 2018 in Environmental Pollution
Verified
Journal Article
Closed access
Ke YuanKe Yuan
Ke Yuan
XXXiuqin Xie
Xiuqin Xie
XWXiaowei Wang
Xiaowei Wang
LLLi Lin
Li Lin
LYLihua Yang
Lihua Yang
BCBaowei Chen
Baowei Chen

8 August 2022 in Science of The Total Environment
Verified
Journal Article
Closed access
PLPu Li
Pu Li
YWYuru Wang
Yuru Wang
BHBi Huang
Bi Huang
SGShengqi Guan
Shengqi Guan
TLTiangang Luan
Tiangang Luan
Ke YuanKe Yuan
Ke Yuan

14 July 2024 in Chemical Engineering Journal
Verified
Journal Article
Closed access
BHBi Huang
Bi Huang
BCBaowei Chen
Baowei Chen
XXXiuqin Xie
Xiuqin Xie
ZLZhaohong Li
Zhaohong Li
XHXingwang Hou
Xingwang Hou
Ke YuanKe Yuan
Ke Yuan

6 June 2022 in Water
Verified
Journal Article
Open access
PDF file
Pu LiPu Li
Pu Li
XCXiayu Chen
Xiayu Chen
Haibo NiuHaibo Niu
Haibo Niu
LZLu Zhenhua
Lu Zhenhua
ZZZekun Zhang
Zekun Zhang
Ke YuanKe Yuan
Ke Yuan
With increasing stress posed to the marine ecosystem and coastal communities, prevention and control of coastal pollution becomes urgent and important, in which the identification of pollution sources is essential. Currently, the pollutant source apportionment in coastal areas is mainly based on receptor models, such as the positive matrix factorization (PMF) model. Nevertheless, these models still lack consideration of the changes of pollutant behaviors (e.g., the degradation of pollutants) which cause the differences in pollutant compositions. Subsequently, the source apportionment via receptor models only based on the monitoring data may not be consistent with the one in pollution sources. To fill this gap, a pollutant degradation model was firstly developed in this study. Accordingly, the degradation model was inversed to estimate the pollutant concentrations at their emitting sources, based on the monitoring concentration in the coastal area. Finally, the estimated concentrations were fed to the PMF model for pollutant source apportionment, advancing the PMF model with degradation process. To demonstrate the feasibility and accuracy of the developed model, a case study of source appointment was carried out based on the polycyclic aromatic hydrocarbons (PAHs) in the sediments of the Pearl River Estuary. The results indicated the same types of emission source identified by the original and advanced PMF models, which were oil spill, biomass and coal combustion, and traffic emission. Nevertheless, the contributions of sources were significantly varied between the two models. According to the analyses based on emission inventory, the offsets of the results from the original PMF model were −55.4%, 22.7%, and 42.2% for the emission sources of oil spill, biomass and coal combustion, and traffic emission, respectively. Comparatively, the offsets for the advanced PMF model narrowed down to −27.5%, 18.4%, and −4.4%. Therefore, the advanced PMF model is able to provide satisfactory source apportionment for organic pollutants in coastal areas, and thus further provide a scientific basis for marine pollution prevention and control.

22 October 2026 in Environmental Research
Verified
Journal Article
Closed access
BHBi Huang
Bi Huang
BCBaowei Chen
Baowei Chen
ZLZhaohong Li
Zhaohong Li
EYEntai Yang
Entai Yang
JLJianan Lu
Jianan Lu
Ke YuanKe Yuan
Ke Yuan