Ying Liu

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Organization: Tongji University
Department: State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering
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Co-reporter:Daolun Feng, Ying Liu, Yi Gao, Jinxing Zhou, Lirong Zheng, Gang Qiao, Liming Ma, Zhifen Lin, Peter Grathwohl
Environmental Pollution 2017 Volume 230(Volume 230) pp:
Publication Date(Web):1 November 2017
DOI:10.1016/j.envpol.2017.07.022
•PAH deposition flux in Shanghai is categorized as moderate to high on global scale.•Their spatial distribution reveals the influence of urbanization/industrialization.•Atmospheric deposition is the principal pathway of PAHs input to local topsoils.•Other pathways have to be considered for PAH input in urban soil.Atmospheric deposition leads to accumulation of atmospheric polycyclic aromatic hydrocarbons (PAHs) on urban surfaces and topsoils. To capture the inherent variability of atmospheric deposition of PAHs in Shanghai's urban agglomeration, 85 atmospheric bulk deposition samples and 7 surface soil samples were collected from seven sampling locations during 2012–2014. Total fluxes of 17 PAHs were 587-32,300 ng m−2 day−1, with a geometric mean of 2600 ng m−2 day−1. The deposition fluxes were categorized as moderate to high on a global scale. Phenanthrene, fluoranthene and pyrene were major contributors. The spatial distribution of deposition fluxes revealed the influence of urbanization/industrialization and the relevance of local emissions. Meteorological conditions and more heating demand in cold season lead to a significant increase of deposition rates. Atmospheric deposition is the principal pathway of PAHs input to topsoils and the annual deposition load in Shanghai amounts to ∼4.5 tons (0.7 kg km−2) with a range of 2.5–10 tons (0.4–1.6 kg km−2).Download high-res image (381KB)Download full-size image
Co-reporter:Ying Liu, Siyao Wang, Carrie A. McDonough, Mohammed Khairy, Derek Muir, and Rainer Lohmann
Environmental Science & Technology 2016 Volume 50(Issue 20) pp:10894-10902
Publication Date(Web):September 13, 2016
DOI:10.1021/acs.est.6b02891
Compared with dry and wet deposition fluxes, air–water exchange flux cannot be directly measured experimentally. Its model-based calculation contains considerable uncertainty because of the uncertainties in input parameters. To capture the inherent variability of air–water exchange flux of PCBs across the lower Great Lakes and to calculate their annual gross volatilization loss, 57 pairs of air and water samples from 19 sites across Lakes Erie and Ontario were collected using passive sampling technology during 2011–2012. Error propagation analysis and Monte Carlo simulation were applied to estimate uncertainty in the air–water exchange fluxes. Results from both methods were similar, but error propagation analysis estimated a smaller uncertainty than Monte Carlo simulation in cases of net deposition. Maximum likelihood estimations (MLE) of wind speed and air temperature were recommended to quantify the site-specific air–water exchange flux. An assumed 30–40% of relative uncertainty in overall air–water mass transfer velocity was confirmed. MLEs of volatilization fluxes of total PCBs across Lakes Erie and Ontario were 0.78 and 0.53 ng m–2 day–1, respectively, and gross volatilization losses of total PCBs over the whole lakes were 74 kg year–1 for Lake Erie and 63 kg year–1 for Lake Ontario. Mass balance analysis across Lake Ontario indicated that volatilization was the uppermost loss process of aqueous PCBs.
Co-reporter:Ying Liu, Siyao Wang, Carrie A. McDonough, Mohammed Khairy, Derek C.G. Muir, Paul A. Helm, and Rainer Lohmann
Environmental Science & Technology 2016 Volume 50(Issue 10) pp:4932-4939
Publication Date(Web):December 7, 2015
DOI:10.1021/acs.est.5b04586
Polyethylene passive sampling was performed to quantify gaseous and freely dissolved polychlorinated biphenyls (PCBs) in the air and water of Lakes Erie and Ontario during 2011–2012. In view of differing physical characteristics and the impacts of historical contamination by PCBs within these lakes, spatial variation of PCB concentrations and air–water exchange across these lakes may be expected. Both lakes displayed statistically similar aqueous and atmospheric PCB concentrations. Total aqueous concentrations of 29 PCBs ranged from 1.5 pg L–1 in the open lake of Lake Erie (site E02) in 2011 spring to 105 pg L–1 in Niagara (site On05) in 2012 summer, while total atmospheric concentrations were 7.7–634 pg m–3 across both lakes. A west-to-east gradient was observed for aqueous PCBs in Lake Erie. River discharge and localized influences (e.g., sediment resuspension and regional alongshore transport) likely dominated spatial trends of aqueous PCBs in both lakes. Air–water exchange fluxes of Σ7PCBs ranged from −2.4 (±1.9) ng m–2 day–1 (deposition) in Sheffield (site E03) to 9.0 (±3.1) ng m–2 day–1 (volatilization) in Niagara (site On05). Net volatilization of PCBs was the primary trend across most sites and periods. Almost half of variation in air–water exchange fluxes was attributed to the difference in aqueous concentrations of PCBs. Uncertainty analysis in fugacity ratios and mass fluxes in air–water exchange of PCBs indicated that PCBs have reached or approached equilibrium only at the eastern Lake Erie and along the Canadian shore of Lake Ontario sites, where air–water exchange fluxes dominated atmospheric concentrations.
Co-reporter:Ying Liu, Ling Chen, Jianfu Zhao, Yanping Wei, Zhaoyu Pan, Xiang-Zhou Meng, Qinghui Huang, Weiying Li
Organic Geochemistry 2010 Volume 41(Issue 4) pp:355-362
Publication Date(Web):April 2010
DOI:10.1016/j.orggeochem.2009.12.009
We quantified 18 polycyclic aromatic hydrocarbons (PAHs) in 54 surface soil samples covering an area of 6400 km2 in Shanghai. An isopleth map of total concentrations of the 18 PAHs, which was constructed using an ordinary Kriging approach with log transformed data, clarified the regional variability and identified regional hot spots in the urban and industrial areas of Shanghai. These hot spots all suffer from high PAH pollution, suggesting that local human activities (e.g., vehicular traffic, petrochemical industry and coal combustion) may be the main contributors. Coal or oil fired power plants and their locations seem to be a significant factor controlling the PAH concentrations in surface soil. The higher molecular weight PAHs are often accumulated near pollution sources and are more heterogeneous in Shanghai soil, because they are less easily transported and biodegraded than 2 ring PAHs. The total concentrations are not correlated with soil total organic carbon. We successfully applied hierarchical cluster analysis (HCA) and principal components analysis (PCA) based on a centered log ratio procedure to explore the characteristics and possible sources of soil PAHs. The high PAH contamination in the Shanghai surface soil is mainly attributed to the contribution of pyrogenic sources (vehicular traffic pollution and combustion of coal and biomass). Furthermore, we applied PAH percentages by ring number, isopleth maps of total concentrations of 18 PAHs and source diagnostic ratios of PAHs to help assign the pyrogenic sources in Shanghai soils. Such map based approaches have only rarely been applied in investigations published in Organic Geochemistry.
Glycogen synthase kinase 3, GSK3β
Furo[3,4-b]furan-2,4-dione,6-hexyltetrahydro-3-methylene-, (3aS,6R,6aR)-
Galactose
D-Glucose,6-(dihydrogen phosphate)
Mitogen-activated protein kinase p38
Protein kinase Akt