Contamination and distribution of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/F) in agriculture fields in Ya-Er Lake area, China

The contamination and distribution of polychlorinated dibeinizo-p-dioxins and dibenzofurans (PCDD/Fs) from two agricultural fields of a heavily polluted lake area in China (Ya-Er Lake) are presented. The vertical distribution pattern of total PCDD/Fs in soil cores reveals that the maximum concentration was in the layer of 20-30 cm. The concentrations in the top layer of soil at the two sites were similar (17.48 ng/kg at Site 1 and 18.10 ng/kg at Site 2), but the maximum concentration of Site 1 (120.8 ng/kg) was two times higher than that of Site 2 (64.39 ng/kg). The maximum concentration of PCDD/Fs in mud cores in rice fields (0-50 cm) at Sites 1 and 2 was in the layer of 0-10 cm. The maximum PCDD/F concentration in the top layer in mud at Site 1 (203.1 ng/kg) was higher than that at Site 2: (143.3 ng/kg). Significant correlations were found between the mind PCDD/Fs and the organic carbon content (R = 0.9743, P< 0,05 at Site 1; R = 0.9821, P< 0.05 at Site 2), the two variables being highly correlated (R = 0.9049, P< 0.05, at Site 1; R = 0.9916, P< 0.05 at Site 2). All correlation coefficients were significant at the 95% level. Concentrations were highly correlated with organic carbon, indicating that sorption to organic carbon was the dominant mechanism. Using principal component analysis, the homologue profiles of soil, mud, and plants (rice and radish) were compared. The PCDD/F patterns in plants were found not to be correlated to those in soil and mud. This suggests that atmospheric deposition may be the main source of PCDD/Fs in rice grain. However, mixed exposure involving uptake mechanisms and atmospheric deposition is considered main the source of PCDD/F pollution in radishes. (C) 2002 Elsevier Science (USA).

Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis

Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.

Assessment of metal contamination in surface sediments of Jiaozhou Bay, Qingdao, China

An assessment of metal contamination in surface sediments of the Jiaozhou Bay, Qingdao, one of the rapidly developing coastal economic zones in China, is provided. Sediments were collected from 10 stations and a total of 15 heavy metals were analyzed. Concentrations of metals show significant variability and range from 210 to 620 ppm for Ti, 2.7 to 23 ppm for Ni, 4.2 to 28 ppm for Cu, 5.2 to 18 ppm for Pb, 12 to 58 ppm for Zn, 0.03 to 0.11 ppm for Cd, 5 to 51 ppm for Cr, 1.5 to 9.9 ppm for Co, 5.3 to 19 ppm for As, 12 to 32 ppm for Se, and 19 to 97 ppm for Sr. Based on concentration relationships and enrichment factor (EF) analyses, the results indicate that sediment grain size and organic matter played important roles in controlling the distribution of the heavy metals in surface sediments of the Jiaozhou Bay. The study shows that the sediment of the Jiaozhou Bay has been contaminated by heavy metals to various degrees, with prominent arsenic contributing the most to the contamination. The analysis suggests that the major sources of metal contamination in the Jiaozhou Bay are land-based anthropogenic ones, such as discharge of industrial waste water and municipal sewage and run-off. Notably, the elevated heavy metal concentrations of the Jiaozhou Bay sediments could have a significant impact on the bay's ecosystem. With the rapid economic development and urbanization around the Jiaozhou Bay, coastal management and pollution control should focus on these contaminant sources, as well as provide ongoing monitoring studies of heavy metal contamination within the bay.