Taihu Lake region is one of the most industrialized areas in China, and the surface water is progressively susceptible to anthropogenic pollution. The physicochemical parameters of surface water quality were determine...Taihu Lake region is one of the most industrialized areas in China, and the surface water is progressively susceptible to anthropogenic pollution. The physicochemical parameters of surface water quality were determined at 20 sampling sites in Taihu Lake region, China in spring, summer, autumn, and winter seasons of 2005-2006 to assess the effect of human activities on the surface water quality. Principal component analysis (PCA) and cluster analysis (CA) were used to identify characteristics of the water quality in the studied water bodies. PCA extracted the first three principal components (PCs), explaining 80.84% of the total variance of the raw data. Especially, PC1 (38.91%) was associated with NH 4 -N, total N, soluble reactive phosphorus, and total P. PC2 (22.70%) was characterized by NO 3 -N and temperature. PC3 (19.23%) was mainly associated with pH and dissolved organic carbon. CA showed that streams were influenced by urban residential subsistence and livestock farming contributed significantly to PC1 throughout the year. The streams influenced by farmland runoff contributed most to PC2 in spring and winter compared with other streams. PC3 was affected mainly by aquiculture in spring, rural residential subsistence in summer, and livestock farming in fall and winter seasons. Further analyses showed that farmlands contributed significantly to nitrogen pollution of Taihu Lake, while urban residential subsistence and livestock farming also polluted water quality of Taihu Lake in rainy season. The results would be helpful for the authorities to take sound actions for an effective management of water quality in Taihu Lake region.展开更多
This study addressed the relationship of river water pollution characteristics to land covers and human activities in the catchments in a complete river system named Cao-E River in eastern China.Based on the hydrogeoc...This study addressed the relationship of river water pollution characteristics to land covers and human activities in the catchments in a complete river system named Cao-E River in eastern China.Based on the hydrogeochemical data collected monthly over a period of 3 years,cluster analysis(CA) and principal component analysis(PCA) were adopted to categorize the river reaches and reveal their pollution characteristics.According to the differences of water quality in the river reaches and land use patterns and average population densities in their catchments,the whole river system could be categorized into three groups of river reaches,i.e.,non-point sources pollution reaches(NPSPR),urban reaches(UR) and mixed sources pollution reaches(MSPR).In UR and MSPR,the water quality was mainly impacted by nutrient and organic pollution,while in NPSPR nutrient pollution was the main cause.The nitrate was the main nitrogen form in NPSPR and particulate phosphorus was the main phosphorus form in MSPR.There were no apparent trends for the variations of pollutant concentrations with increasing river flows in NPSPR and MSPR,while in UR the pollutant concentrations decreased with increasing river flows.Thus dry season was the critical period for water pollution control in UR.Therefore,catchment land covers and human activities had significant impact on river reach water pollution type,nutrient forms and water quality responses to hydrological conditions,which might be crucial for developing strategies to combat water pollution in watershed scale.展开更多
Introduction:In this study,metal pollution and their sources in surface soils were evaluated by pollution indices and multivariate statistical techniques in association with a geographical information system(GIS).Meth...Introduction:In this study,metal pollution and their sources in surface soils were evaluated by pollution indices and multivariate statistical techniques in association with a geographical information system(GIS).Methods:Surface soil samples were collected in dry season from different locations of Dhaka Aricha highway and analyzed by energy dispersive X-ray fluorescence(EDXRF).Results:Thirteen different metals were found in the tested samples.Pollution indices are determined by enrichment factor in an order of Zr>Sn>P>Mn>Zn>Rb>Fe>Ba>Sr>Ti>K>Ca>Al.The resulting geoaccumulation index(Igeo)value shows the following order:Sn>Zr>P>Mn>Zn>Rb>Fe>Ba>Ti>Sr>K>Ca>Al.Contamination factors(CFs)of the metals range from 1.422 to 3.979(Fe);0.213 to 1.089(Al);0.489 to 3.484(Ca);1.496 to 2.372(K);1.287 to 3.870(Ti);2.200 to 14.588(Mn);5.938 to 56.750(Zr);0.980 to 3.500(Sr);2.321 to 4.857(Rb);2.737 to 6.526(Zn);16.667 to 27.333(Sn);3.157 to 16.286(P);and 0.741 to 3.328(Ba).Pollution load index calculated from the CFs indicates that soils are strongly contaminated by Zr and Sn.Principal component analysis(PCA)of parameters exhibits three major components.R-mode cluster analysis reveals three distinct groups in both site and metal basis clustering that shows a similar pattern with the PCA.Conclusions:These results might be helpful for future monitoring of further increase of heavy metal concentrations in surface soils along highways.展开更多
基金Project supported by the Knowledge Innovation Key Project of the Chinese Academy of Sciences (No. KZCX1-YW-14-5)the National Natural Science Foundation of China (No. 30600086)
文摘Taihu Lake region is one of the most industrialized areas in China, and the surface water is progressively susceptible to anthropogenic pollution. The physicochemical parameters of surface water quality were determined at 20 sampling sites in Taihu Lake region, China in spring, summer, autumn, and winter seasons of 2005-2006 to assess the effect of human activities on the surface water quality. Principal component analysis (PCA) and cluster analysis (CA) were used to identify characteristics of the water quality in the studied water bodies. PCA extracted the first three principal components (PCs), explaining 80.84% of the total variance of the raw data. Especially, PC1 (38.91%) was associated with NH 4 -N, total N, soluble reactive phosphorus, and total P. PC2 (22.70%) was characterized by NO 3 -N and temperature. PC3 (19.23%) was mainly associated with pH and dissolved organic carbon. CA showed that streams were influenced by urban residential subsistence and livestock farming contributed significantly to PC1 throughout the year. The streams influenced by farmland runoff contributed most to PC2 in spring and winter compared with other streams. PC3 was affected mainly by aquiculture in spring, rural residential subsistence in summer, and livestock farming in fall and winter seasons. Further analyses showed that farmlands contributed significantly to nitrogen pollution of Taihu Lake, while urban residential subsistence and livestock farming also polluted water quality of Taihu Lake in rainy season. The results would be helpful for the authorities to take sound actions for an effective management of water quality in Taihu Lake region.
基金Supported by the National Natural Science Foundation of China (No. 40871104)the National High Technology Research andDevelopment Program (863 Program) of China (No. 2007AA10Z218)
文摘This study addressed the relationship of river water pollution characteristics to land covers and human activities in the catchments in a complete river system named Cao-E River in eastern China.Based on the hydrogeochemical data collected monthly over a period of 3 years,cluster analysis(CA) and principal component analysis(PCA) were adopted to categorize the river reaches and reveal their pollution characteristics.According to the differences of water quality in the river reaches and land use patterns and average population densities in their catchments,the whole river system could be categorized into three groups of river reaches,i.e.,non-point sources pollution reaches(NPSPR),urban reaches(UR) and mixed sources pollution reaches(MSPR).In UR and MSPR,the water quality was mainly impacted by nutrient and organic pollution,while in NPSPR nutrient pollution was the main cause.The nitrate was the main nitrogen form in NPSPR and particulate phosphorus was the main phosphorus form in MSPR.There were no apparent trends for the variations of pollutant concentrations with increasing river flows in NPSPR and MSPR,while in UR the pollutant concentrations decreased with increasing river flows.Thus dry season was the critical period for water pollution control in UR.Therefore,catchment land covers and human activities had significant impact on river reach water pollution type,nutrient forms and water quality responses to hydrological conditions,which might be crucial for developing strategies to combat water pollution in watershed scale.
文摘Introduction:In this study,metal pollution and their sources in surface soils were evaluated by pollution indices and multivariate statistical techniques in association with a geographical information system(GIS).Methods:Surface soil samples were collected in dry season from different locations of Dhaka Aricha highway and analyzed by energy dispersive X-ray fluorescence(EDXRF).Results:Thirteen different metals were found in the tested samples.Pollution indices are determined by enrichment factor in an order of Zr>Sn>P>Mn>Zn>Rb>Fe>Ba>Sr>Ti>K>Ca>Al.The resulting geoaccumulation index(Igeo)value shows the following order:Sn>Zr>P>Mn>Zn>Rb>Fe>Ba>Ti>Sr>K>Ca>Al.Contamination factors(CFs)of the metals range from 1.422 to 3.979(Fe);0.213 to 1.089(Al);0.489 to 3.484(Ca);1.496 to 2.372(K);1.287 to 3.870(Ti);2.200 to 14.588(Mn);5.938 to 56.750(Zr);0.980 to 3.500(Sr);2.321 to 4.857(Rb);2.737 to 6.526(Zn);16.667 to 27.333(Sn);3.157 to 16.286(P);and 0.741 to 3.328(Ba).Pollution load index calculated from the CFs indicates that soils are strongly contaminated by Zr and Sn.Principal component analysis(PCA)of parameters exhibits three major components.R-mode cluster analysis reveals three distinct groups in both site and metal basis clustering that shows a similar pattern with the PCA.Conclusions:These results might be helpful for future monitoring of further increase of heavy metal concentrations in surface soils along highways.
