Spatial Distribution, Chemical Fraction and Fuzzy Comprehensive Risk Assessment of Heavy Metals in Surface Sediments from the Honghu Lake, China.

ABSTRACT: Spatial concentrations and chemical fractions of heavy metals (Cr, Cu, Pb, Zn and Cd) in 16 sampling sites from the Honghu Lake were investigated using an atomic absorption spectrophotometer and optimized BCR (the European Community Bureau of Reference) three-stage extraction procedure. Compared with the corresponding probable effect levels (PELs), adverse biological effects of the studied five sediment metals decreased in the sequence of Cr > Cu > Zn > Pb > Cd. Geo-accumulation index (I_geo) values for Cr, Cu, Pb and Zn in each sampling site were at un-contamination level, while the values for Cd varied from un-contamination level to moderate contamination level. Spatially, the enrichment degree of Cd in lower part of the South Lake, the west part of the North Lake and the outlet were higher than the other parts of Honghu Lake. For metal chemical fractions, the proportions of the acid-extractable fraction of five metal contents were in the descending order: Cd, Cu, Zn, Pb and Cr. Cd had the highest bioaccessibility. Being the above indexes focused always on heavy metals' total content or chemical fraction in deterministic assessment system, which may confuse decision makers, the fuzzy comprehensive risk assessment method was established based on PEI (Potential ecological risk index), RAC (Risk assessment code) and fuzzy theory. Average comprehensive risks of heavy metals in sediments revealed the following orders: Cd (considerable risk) > Cu (moderate risk) > Zn (low risk) > Pb > Cr. Thus, Cd and Cu were determined as the pollutants of most concern. The central part of South Honghu Lake (S4, S5, S6, S9, S12 and S14), east part of the North Honghu Lake (S1) and outlet of outlet of the Honghu Lake (S10) were recommended as the priority control areas. Specifically, it is necessary to pay more attention to S1, S4, S5, S6, S9 and S16 when decision making for their calculated membership values (probabilities) of adjacent risk levels quite close.

SUBMITTER: Li F 

PROVIDER: S-EPMC5858276 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature