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Spatial and temporal distribution of acetochlor in sediments and riparian soils of the Songhua River Basin in northeastern China 被引量:9

Spatial and temporal distribution of acetochlor in sediments and riparian soils of the Songhua River Basin in northeastern China
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摘要 The Songhua River Basin is a burgeoning agricultural area in the modern times in China. Particularly in recent years, increasing chemical fertilizers and pesticides have been applied with the development of agricultural production. However, the situation of non- point source pollution (NSP) from agricultural production in this basin is still obscure. In order to solve the problem, the occurrence and distribution of acetochlor in sediments and riparian soils of the Songhua River Basin before rain season and after rain season were investigated. In addition, total organic carbon was analyzed. The result showed that the concentration of acetochlor ranged from 0.47 to 11.76 μg/kg in sediments and 0.03 to 709.37 μg/kg in riparian soils. During the high flow period in 2009, the mean concentration was 4.79 μg/kg in sediments and 0.75 μg]kg in riparian soils, respectively. Similarly, the mean concentration was 2.53 μg/kg in sediments and 61.36μg/kg in riparian soils, during the average flow period in 2010. There was a significant correlation between the concentration of acetochlor and total organic carbon in surface sediments. Moreover, the distribution of acetochlor in sediments of the Songhua River was significantly correlated to land use and topography of the watershed. The investigated data suggested that the concentration of acetochlor in the Songnen Plain and the Sanjiang Plain was higher than that in the other areas of the basin, and riparian buffering zones in these areas bad been destroyed by human activities. The optimal agricultural measures to alleviate the contamination of pesticides should be adopted, including controlling agricultural application of acetochlor and ecological restoration of riparian buffering strips. The Songhua River Basin is a burgeoning agricultural area in the modern times in China. Particularly in recent years, increasing chemical fertilizers and pesticides have been applied with the development of agricultural production. However, the situation of non- point source pollution (NSP) from agricultural production in this basin is still obscure. In order to solve the problem, the occurrence and distribution of acetochlor in sediments and riparian soils of the Songhua River Basin before rain season and after rain season were investigated. In addition, total organic carbon was analyzed. The result showed that the concentration of acetochlor ranged from 0.47 to 11.76 μg/kg in sediments and 0.03 to 709.37 μg/kg in riparian soils. During the high flow period in 2009, the mean concentration was 4.79 μg/kg in sediments and 0.75 μg]kg in riparian soils, respectively. Similarly, the mean concentration was 2.53 μg/kg in sediments and 61.36μg/kg in riparian soils, during the average flow period in 2010. There was a significant correlation between the concentration of acetochlor and total organic carbon in surface sediments. Moreover, the distribution of acetochlor in sediments of the Songhua River was significantly correlated to land use and topography of the watershed. The investigated data suggested that the concentration of acetochlor in the Songnen Plain and the Sanjiang Plain was higher than that in the other areas of the basin, and riparian buffering zones in these areas bad been destroyed by human activities. The optimal agricultural measures to alleviate the contamination of pesticides should be adopted, including controlling agricultural application of acetochlor and ecological restoration of riparian buffering strips.
出处 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2011年第10期1684-1690,共7页 环境科学学报(英文版)
基金 supported by the National Special Water Project in China (No. 2008ZX07526-002-01)
关键词 ACETOCHLOR Songhua River Basin non-point source pollution optimal agricultural measure acetochlor Songhua River Basin non-point source pollution optimal agricultural measure
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