Author
Gui-Rong Liu
Other affiliations: The University of Nottingham Ningbo China
Bio: Gui-Rong Liu is an academic researcher from Nankai University. The author has contributed to research in topics: Collinearity & Mass concentration (chemistry). The author has an hindex of 8, co-authored 12 publications receiving 267 citations. Previous affiliations of Gui-Rong Liu include The University of Nottingham Ningbo China.
Papers
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TL;DR: The toxicities of PAHs in the dated sediments, assessed by BaP equivalent (BaPE) values showed that the BaPE increased gradually from the deep layers to the surface sediments in most lakes, and the vehicular emission posed the highest toxic risk.
64 citations
TL;DR: The vertical characteristics of the levels, relationships, source contributions and locations would support the effective management of the water-soluble ions in particulate matter.
55 citations
TL;DR: The findings can provide useful information to protect the urban human health, as well as develop the effective air control strategies in special short-term anthropogenic activity event.
52 citations
TL;DR: The results showed that gasoline emissions posed the highest cancer risk, even though it contributed less to Σ16PAHs, and the cancer risks for each identified source were quantitatively calculated by combining the incremental lifetime cancer risk (ILCR) values with the estimated source contributions.
52 citations
TL;DR: In this paper, multiple combined models, including the PCA/MLR-CMB, Unmix-cMB, and PMF-cmb models, were developed and employed to analyze the synthetic datasets, in order to understand 1) the accuracies of the predictions by multiple combined model; 2) the effect of Fpeak-rotation on the predictions of the PMF CMB model; and 3) the relationship between the extracted mixed source profiles (in the first stage) and the final predictions.
Abstract: A combined models was developed and applied to synthetic and ambient PM datasets in our prior works. In this study, multiple combined models, including the PCA/MLR-CMB, Unmix-CMB and PMF-CMB models, were developed and employed to analyzed the synthetic datasets, in order to understand 1) the accuracies of the predictions by multiple combined models; 2) the effect of Fpeak-rotation on the predictions of the PMF-CMB model; and 3) the relationship between the extracted mixed source profiles (in the first stage) and the final predictions. 50 predictions based on different combined model solutions were obtained and compared with the synthetic datasets. The average absolute errors (AAE), cluster analysis (CA), and PCA plots were applied to evaluate the precision of the predictions. These statistical methods showed that the predictions of the PCA/MLR-CMB and PMF-CMB model (with Fpeaks from 0 to 1.0) were satisfactory, those of the Unmix-CMB model were instable (some of them closely approached the synthetic values, while other them deviated from them). Additionally, it was found that the final source contributions had good correlation with their marker concentrations (obtained in the first stage), suggesting that the extracted profiles of the mixed sources can determine the final predictions of combined models.
33 citations
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TL;DR: According to the health risk assessment results, the non-carcinogenic risks that human beings suffered from heavy metals were insignificant, however, the carcinogenic risks due to Ni and Cr exceeded the acceptable level.
372 citations
14 Jul 2017
TL;DR: In this article, the recent literature describing polycyclic aromatic hydrocarbons (PAHs) in air, water, soil and sediment, waste sludge, biomonitoring, toxicity, etc.
Abstract: The recent literature describing polycyclic aromatic hydrocarbons (PAHs) in air, water, soil and sediment, waste sludge, biomonitoring, toxicity, are reviewed. Aspects of sampling, sample preparati...
294 citations
TL;DR: The location of point pollution sources and prevailing wind direction were found to be important factors in the spatial distribution of heavy metals and there was significant enrichment of Pb, Zn, Co, Cu and Cr based on geo-accumulation index value.
231 citations
TL;DR: In this article, the authors summarize the advances in real-time PM chemical characterization, focusing on the most widely used mass spectrometric and ion chromatographic techniques, and highlight the new insights gained from those findings and suggest future directions for further advancing our understanding of PM pollution in China via real time chemical characterization.
191 citations
TL;DR: Long-term changes of PM sources at two megacities of Beijing and Nanjing indicated that the contributions of fossil fuel and industrial sources have been declining after stricter emission controls in recent years.
168 citations