Use of the aquatic protozoa to formulate a community biotic index for an urban water system

Protozoan were collected from 16 stations in water system of Changde City (China) using the PFU method. Sampling programs were conduced on a yearly basis, with seasonal frequency at diverse sites in the water system and 488 species of protozoa was identified. At the same time, Water sampling from these stations was conducted and various water chemical parameters, including DO, COD, BOD5, NH3, TP, and Volatile Phenol, were analyzed. The aim of the research was, on one hand, using chemical method to take an investigation to the water pollution status of Changde City; on the other hand, using protozoan to make an evaluation to the water quality. With the chemical water parameters and protozoa data, a biotic index was derived for the investigated region. The species pollution value (SPV) of 469 protozoa species was established, and the community pollution value (CPV) calculated from SPV was used to evaluate water quality. The method of the biotic index was tested and the result showed that CPV calculated from SPV had a close correlation with the degree of water pollution (p < 0.00001). This indicated that the method of the biotic index is reliable. The water quality degrees divided by CPV were suggested. (c) 2004 Elsevier B.V. All rights reserved.

Estimating water quality pollution impacts based on economic loss models in urbanization process in Xi'an；China

IEECAS SKLLQG

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.