ORIGINAL RESEARCH
Geochemical Baseline Establishment, Pollution Assessment, and Source Apportionment of Heavy Metals in Estuary Sediments of Northwestern Taihu Lake, China
,
 
,
 
,
 
,
 
Hao Yu 1
,
 
 
 
More details
Hide details
1
Engineering Research Center of Coal Mine Exploration of Anhui Province, Suzhou University, Suzhou, Anhui Province, 23400, China
 
2
School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui Province, 230026, China
 
3
School of Environment, Nanjing Normal University, Nanjing, Jiangsu Province, 210023, China
 
 
Submission date: 2023-03-29
 
 
Final revision date: 2023-06-03
 
 
Acceptance date: 2023-06-13
 
 
Online publication date: 2023-07-24
 
 
Publication date: 2023-09-08
 
 
Corresponding author
Xiaoguang Xu   

Nanjing Normal University, China
 
 
Pol. J. Environ. Stud. 2023;32(5):4653-4663
 
KEYWORDS
TOPICS
ABSTRACT
The scientific and reasonable evaluation of heavy metals pollution in estuarine sediments is crucial for characterizing the environmental quality of the lake, however, it is still unavailable due to the lack of local geochemical baseline concentrations (GBCs) and thus applying background values of soils. In this study, the statistical method of cumulative frequency was employed to obtain the GBCs, which were applied as reference standards for the pollution assessment of heavy metals and source apportionment in estuary sediments of northwestern Taihu Lake. The results showed that the GBCs of Cd, Cu and Zn were higher than soil background values in Jiangsu Province while Ni and Pb displayed a small gap between GBCs and background values. Cd, Ni and Zn presented a degree of moderate pollution or moderate to strong pollution according to geo-accumulation index (Igeo). The pollution load index (PLI) showed that 75% of samples ranged from non-pollution to moderate pollution level while 2.94% of samples exhibited a moderate to high pollution level. The possible sources of heavy metals in the estuary sediments were quantitatively identified by positive matrix factorization (PMF), including agricultural source (23%), the combined contribution of natural sources and traffic emissions (36%) and industrial source (41%).
eISSN:2083-5906
ISSN:1230-1485
Journals System - logo
Scroll to top