Metal distribution in Clark Fork River sediments

Metals contamination along the watershed and estuarine areas of southern Bohai Sea, China

Distributions and magnitude of metals in water, sediment and soil collected from the watershed and estuarine areas of southern Bohai Sea, were investigated. The largest dissolved concentrations of As, Cu and Zn in water were 347.70, 2755.00, 2076.00 μg/L, respectively, much higher than corresponding drinking water guidelines. The greatest concentrations of Cu, Zn, Cr, Ni, Pb, As and Cd in sediments were 1462.2, 1602.17, 196.43, 67.15, 63.54, 73.86 and 1.41 mg/kg, dw, respectively. The mean concentrations of Cu, Ni, Cd, Zn, Cr, Pb and As in soils were 24.67, 24.73, 0.14, 64.75, 56.52, 25.12 and 9.34 mg/kg, dw, respectively. Land use was confirmed to be an important factor of influence on soil metal concentrations. Metal contents along the watershed of Jie River were significantly greater than in other locations. The detection of metals in relatively high concentrations from different environmental matrices in this region indicates the necessity of further studies.

Temporal bacterial diversity associated with metal-contaminated river sediments

The temporal activity, abundance and diversity of microbial communities were evaluated across a metal-contamination gradient around a Superfund site in Montana. In order to analyze short-term variability, samples were collected from six sites on four occasions over 12 months. Measurements of community activity, diversity and richness, quantified by dehydrogenase activity and through denaturant gradient gel electrophoresis (DGGE), respectively, were higher at contaminated sites adjacent to the smelter, relative to reference sites. 16S rRNA gene copy numbers, measured by quantitative PCR, showed seasonal variability, yet were generally higher within polluted sediments. Jaccard similarity coefficients of DGGE profiles, found sites to cluster based primarily on geographical proximity rather than geochemical similarities. Intra-site clustering of the most polluted sites also suggests a stable metal-tolerant community. Sequences from DGGE-extracted bands were predominantly Beta and Gammaproteobacteria, although the communities at all sites generally maintained a diverse phylogeny changing in composition throughout the sampling period. Spearman's rank correlations analysis found statistically significant relationships between community composition and organic carbon (r-value = 0.786) and metals (r-values As = 0.65; Cu = 0.63; Zn = 0.62). A diverse and abundant community at the most polluted site indicates that historical contamination selects for a metal-resistant microbial community, a finding that must be accounted for when using the microbial community within ecosystem monitoring studies. This study highlights the importance of using multiple time-points to draw conclusions on the affect of metal contamination.

Factorial Kriging Analysis as a tool for explaining the complex spatial distribution of metals in sediments

Rivers flowing through urbanized and industrial areas are usually greatly damaged by anthropogenic activities discharging contaminants. Characterizing the spatial distribution of pollutants in sediments is of high importance for selecting a suitable remediation operation, but is a complex task because this spatial variability is the result of various physical and chemical mechanisms occurring at different scales. Factorial Kriging Analysis (FKA) was applied on data collected in a canalized river (Scarpe, France) for that purpose, because this geostatistical technique allows to decompose a given variable into components of different spatial correlations and map them separately. This decomposition is meaningful provided that it can be related to physical phenomena occurring at the identified spatial scales. FKA applied to Cd and Zn concentrations in sediments of the Scarpe river proved to be effective, allowing their mapping to be decomposed in a first map related to a short-range spatial correlation corresponding to hot spots interpreted as the impact of industrial and urban inputs located along the canal, and a second map related to a long-range spatial variability associated with long pollutant plumes interpreted as the effect of one major upstream pollutant input.