Yan Li

Dr. Yan Li

School of Public Affairs, Zhejiang University, Hangzhou 310058, China

Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

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

Representative Publications

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1 June 2021 in Environmental Pollution
Verified
Journal Article
Closed access
MXMingtao Xiang
Mingtao Xiang
YLYan Li
Yan Li
JYJiayu Yang
Jiayu Yang
KLKaige Lei
Kaige Lei
YLYi Li
Yi Li
Yu CaoYu Cao
Yu Cao

Bifeng HuBifeng Hu
Bifeng Hu
XJXiaolin Jia
Xiaolin Jia
JHJie Hu
Jie Hu
DXDongyun Xu
Dongyun Xu
FXFang Xia
Fang Xia
YLYan Li
Yan Li
Heavy metal (HM) contamination and accumulation is a serious problem around the world due to the toxicity, abundant sources, non-biodegradable properties, and accumulative behaviour of HMs. The degree of soil HM contamination in China, especially in the Yangtze River Delta, is prominent. In this study, 1822 pairs of soil and crop samples at corresponding locations were collected from the southern Yangtze River Delta of China, and the contents of Ni, Cr, Zn, Cd, As, Cu, Hg, and Pb were measured. The single pollution index in soil (SPI) and Nemerow composite pollution index (NCPI) were used to assess the degree of HM pollution in soil, and the crop pollution index (CPI) was used to explore the degree of HM accumulation in crops. The bioaccumulation factor (BAF) was used to investigate the translocation of heavy metals in the soil-crop system. The health risks caused by HMs were calculated based on the model released by the U.S. Environmental Protection Agency. The SPIs of all elements were at the unpolluted level. The mean NCPI was at the alert level. The mean CPIs were in the following decreasing order: Ni (1.007) > Cr (0.483) > Zn (0.335) > Cd (0.314) > As (0.232) > Cu (0.187) > Hg (0.118) > Pb (0.105). Only the mean content of Ni in the crops exceeded the national standard value. The standard exceeding rates were used to represent the percentage of samples whose heavy metal content is higher than the corresponding national standard values. The standard exceeding rates of Cu, Hg, and Cd in soil were significantly higher than corresponding values in crops. Meanwhile, the standard exceeding rates of Ni, As, and Cr in crops were significantly higher than corresponding values in soil. The chronic daily intake (CDI) of children (13.8 × 10−3) was the largest among three age groups, followed by adults (6.998 × 10−4) and seniors (5.488 × 10−4). The bioaccumulation factors (BAFs) of all crops followed the order Cd (0.249) > Zn (0.133) > As (0.076) > Cu (0.064) > Ni (0.018) > Hg (0.011) > Cr (0.010) > Pb (0.001). Therefore, Cd was most easily absorbed by crops, and different crops had different capacities to absorb HMs. The hazard quotient (HQ) represents the potential non-carcinogenic risk for an individual HM and it is an estimation of daily exposure to the human population that is not likely to represent an appreciable risk of deleterious effects during a lifetime. All the HQs of the HMs for the different age groups were significantly less than the alert value of 1.0 and were at a safe level. This indicated that citizens in the study area face low potential non-carcinogenic risk caused by HMs. The total carcinogens risks (TCRs) for children, adults, and seniors were 5.24 × 10−5, 2.65 × 10−5, and 2.08 × 10−5, respectively, all of which were less than the guideline value but at the alert level. Ingestion was the main pathway of carcinogen risk to human health.

24 February 2017 in PLOS ONE
Verified
Journal Article
Open access
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Bifeng HuBifeng Hu
Bifeng Hu
Songchao ChenSongchao Chen
Songchao Chen
JHJie Hu
Jie Hu
FXFang Xia
Fang Xia
JXJunfeng Xu
Junfeng Xu
Zhou ShiZhou Shi
Zhou Shi
Rapid heavy metal soil surveys at large scale with high sampling density could not be conducted with traditional laboratory physical and chemical analyses because of the high cost, low efficiency and heavy workload involved. This study explored a rapid approach to assess heavy metals contamination in 301 farmland soils from Fuyang in Zhejiang Province, in the southern Yangtze River Delta, China, using portable proximal soil sensors. Portable X-ray fluorescence spectroscopy (PXRF) was used to determine soil heavy metals total concentrations while soil pH was predicted by portable visible-near infrared spectroscopy (PVNIR). Zn, Cu and Pb were successfully predicted by PXRF (R2 >0.90 and RPD >2.50) while As and Ni were predicted with less accuracy (R2 <0.75 and RPD <1.40). The pH values were well predicted by PVNIR. Classification of heavy metals contamination grades in farmland soils was conducted based on previous results; the Kappa coefficient was 0.87, which showed that the combination of PXRF and PVNIR was an effective and rapid method to determine the degree of pollution with soil heavy metals. This study provides a new approach to assess soil heavy metals pollution; this method will facilitate large-scale surveys of soil heavy metal pollution.

7 July 2017 in Environmental Science and Pollution Research
Verified
Journal Article
Closed access
PDF file
Bifeng HuBifeng Hu
Bifeng Hu
JWJiayu Wang
Jiayu Wang
BJBin Jin
Bin Jin
YLYan Li
Yan Li
Zhou ShiZhou Shi
Zhou Shi

18 August 2023 in Science of The Total Environment
Verified
Journal Article
Closed access
XFXinhui Feng
Xinhui Feng
YLYan Li
Yan Li
XWXize Wang
Xize Wang
JYJiayu Yang
Jiayu Yang
EYEr Yu
Er Yu
FXFen Xiao
Fen Xiao

SWShiyi Wang
Shiyi Wang
YZYanbin Zhang
Yanbin Zhang
JCJieliang Cheng
Jieliang Cheng
YLYi Li
Yi Li
FLFeng Li
Feng Li
Zhou ShiZhou Shi
Zhou Shi
In this research, Ningbo City, a typical industrial city in southeastern China, was selected as the study area, and the concentrations of 12 heavy metals (Cd, Cr, Ni, Pb, Zn, Cu, Hg, As, Co, V, Se, and Mn) were measured at 248 sampling points. Pollution index methods were used to assess the status of soil heavy metal contamination, and the Positive Matrix Factorization (PMF) model and Unmix model were integrated to identify and apportion the sources of heavy metal contamination. The results indicated that nearly 70% of the study area was polluted by heavy metals, and that Ni, Cr, and Zn were the main enriched heavy metals. The five sources identified using the PMF model were a geological source, an atmospheric deposition source, a transportation emissions source, a mixed source of agriculture and industry, and a mixed source of geology and industry. The four sources identified using the Unmix model were a mixed source of geology, agriculture, and industry (14.27%); a transportation emissions source (4.76%); a geological source (14.7%); and a mixed source of geology and industry (66.28%). These results have practical significance, as they can help to carry out pollution source risk assessment and give priority to the management of pollution source control.