On the basis of field investigations, observations andexperimental data combined with environmental monitoring information,the status and the spatial and temporal patterns of surface waterpollution over the past ten y...On the basis of field investigations, observations andexperimental data combined with environmental monitoring information,the status and the spatial and temporal patterns of surface waterpollution over the past ten years in the Yangtze River Delta havebeen assessed. The water quality of large rivers is still very goodbut most of the medium-sized and small rivers have been veryseriously polluted. The appearance of black and odorous conditions inrivers in the urban areas has increased due to serious pollution byorganic matter with consequent high oxygen demand. Annual increasesin N and P concentrations in lakes have accelerated eutrophication.The water quality of river sin small towns is rapidly deteriorating.The main sources of surface water pollution include industrial anddomestic sewage, animal manures, chemical fertilizers in farmland,and polluted sediments in rivers and lakes.展开更多
Individual participation of pollutants in the pollution load should be estimated even if roughly for the appropriate environmental management of a river basin.It is difficult to identify the sources and to quantify th...Individual participation of pollutants in the pollution load should be estimated even if roughly for the appropriate environmental management of a river basin.It is difficult to identify the sources and to quantify the load, especially in modeling nonpoint source.In this study a revised model was established by integrating point and nonpoint sources into one-dimensional Streeter-Phelps(S-P) model on the basis of real-time hydrologic data and surface water quality monitoring data in the Jilin Reach of the Songhua River Basin.Chemical oxygen demand(COD) and ammonia nitrogen(NH 3-N) loads were estimated.Results showed that COD loads of point source and nonpoint source were 134 958 t/yr and 86 209 t/yr, accounting for 61.02% and 38.98% of total loads, respectively.NH 3-N loads of point source and nonpoint source were 16 739 t/yr and 14 272 t/yr, accounting for 53.98% and 46.02%, respectively.Point source pollution was stronger than nonpoint source pollution in the study area at present.The water quality of upstream was better than that of downstream of the rivers and cities.It is indispensable to treat industrial wastewater and municipal sewage out of point sources, to adopt the best management practices to control diffuse pollutants from agricultural land and urban surface runoff in improving water quality of the Songhua River Basin.The revised S-P model can be successfully used to identify pollution source and quantify point source and nonpoint source loads by calibrating and validating.展开更多
Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality dat...Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality data sets of the Second Songhua River(SSHR) basin in China,obtained during two years(2012-2013) of monitoring of 10 physicochemical parameters at 15 different sites.The results showed that most of physicochemical parameters varied significantly among the sampling sites.Three significant groups,highly polluted(HP),moderately polluted(MP) and less polluted(LP),of sampling sites were obtained through Hierarchical agglomerative CA on the basis of similarity of water quality characteristics.DA identified p H,F,DO,NH3-N,COD and VPhs were the most important parameters contributing to spatial variations of surface water quality.However,DA did not give a considerable data reduction(40% reduction).PCA/FA resulted in three,three and four latent factors explaining 70%,62% and 71% of the total variance in water quality data sets of HP,MP and LP regions,respectively.FA revealed that the SSHR water chemistry was strongly affected by anthropogenic activities(point sources:industrial effluents and wastewater treatment plants;non-point sources:domestic sewage,livestock operations and agricultural activities) and natural processes(seasonal effect,and natural inputs).PCA/FA in the whole basin showed the best results for data reduction because it used only two parameters(about 80% reduction) as the most important parameters to explain 72% of the data variation.Thus,this work illustrated the utility of multivariate statistical techniques for analysis and interpretation of datasets and,in water quality assessment,identification of pollution sources/factors and understanding spatial variations in water quality for effective stream water quality management.展开更多
Our field experiments showed that the cultivation of pearl mussels formed a new biocoene composed of filamentous algae, protozoa, porifera and coelenterate. It effectively reduced nitrogen, phosphorus, chemical oxygen...Our field experiments showed that the cultivation of pearl mussels formed a new biocoene composed of filamentous algae, protozoa, porifera and coelenterate. It effectively reduced nitrogen, phosphorus, chemical oxygen demand and biochemical oxygen demand in the water by 67.3%, 73.2%, 38.1% and 15.5%, respectively, during May to September 1998 when the water eutrophication was developing. This could control water eutrophication and produce pearls, shellfish meat and shells. This is an economical and effective way to control water eutrophication by using the ultra strong filtering capability of freshwater pearl mussels.展开更多
基金National Natural Science Foundation of China (No.49831070) ShanghaiMunicipal Education Commission.
文摘On the basis of field investigations, observations andexperimental data combined with environmental monitoring information,the status and the spatial and temporal patterns of surface waterpollution over the past ten years in the Yangtze River Delta havebeen assessed. The water quality of large rivers is still very goodbut most of the medium-sized and small rivers have been veryseriously polluted. The appearance of black and odorous conditions inrivers in the urban areas has increased due to serious pollution byorganic matter with consequent high oxygen demand. Annual increasesin N and P concentrations in lakes have accelerated eutrophication.The water quality of river sin small towns is rapidly deteriorating.The main sources of surface water pollution include industrial anddomestic sewage, animal manures, chemical fertilizers in farmland,and polluted sediments in rivers and lakes.
基金Under the auspices of Major State Basic Research Development Program of China (973 Program) (No. 2004CB418502,No. 2007CB407205)the Knowledge Innovation Programs of Chinese Academy of Sciences (No. KSCX1-YW-09-13)
文摘Individual participation of pollutants in the pollution load should be estimated even if roughly for the appropriate environmental management of a river basin.It is difficult to identify the sources and to quantify the load, especially in modeling nonpoint source.In this study a revised model was established by integrating point and nonpoint sources into one-dimensional Streeter-Phelps(S-P) model on the basis of real-time hydrologic data and surface water quality monitoring data in the Jilin Reach of the Songhua River Basin.Chemical oxygen demand(COD) and ammonia nitrogen(NH 3-N) loads were estimated.Results showed that COD loads of point source and nonpoint source were 134 958 t/yr and 86 209 t/yr, accounting for 61.02% and 38.98% of total loads, respectively.NH 3-N loads of point source and nonpoint source were 16 739 t/yr and 14 272 t/yr, accounting for 53.98% and 46.02%, respectively.Point source pollution was stronger than nonpoint source pollution in the study area at present.The water quality of upstream was better than that of downstream of the rivers and cities.It is indispensable to treat industrial wastewater and municipal sewage out of point sources, to adopt the best management practices to control diffuse pollutants from agricultural land and urban surface runoff in improving water quality of the Songhua River Basin.The revised S-P model can be successfully used to identify pollution source and quantify point source and nonpoint source loads by calibrating and validating.
基金Project (2012ZX07501002-001) supported by the Ministry of Science and Technology of China
文摘Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality data sets of the Second Songhua River(SSHR) basin in China,obtained during two years(2012-2013) of monitoring of 10 physicochemical parameters at 15 different sites.The results showed that most of physicochemical parameters varied significantly among the sampling sites.Three significant groups,highly polluted(HP),moderately polluted(MP) and less polluted(LP),of sampling sites were obtained through Hierarchical agglomerative CA on the basis of similarity of water quality characteristics.DA identified p H,F,DO,NH3-N,COD and VPhs were the most important parameters contributing to spatial variations of surface water quality.However,DA did not give a considerable data reduction(40% reduction).PCA/FA resulted in three,three and four latent factors explaining 70%,62% and 71% of the total variance in water quality data sets of HP,MP and LP regions,respectively.FA revealed that the SSHR water chemistry was strongly affected by anthropogenic activities(point sources:industrial effluents and wastewater treatment plants;non-point sources:domestic sewage,livestock operations and agricultural activities) and natural processes(seasonal effect,and natural inputs).PCA/FA in the whole basin showed the best results for data reduction because it used only two parameters(about 80% reduction) as the most important parameters to explain 72% of the data variation.Thus,this work illustrated the utility of multivariate statistical techniques for analysis and interpretation of datasets and,in water quality assessment,identification of pollution sources/factors and understanding spatial variations in water quality for effective stream water quality management.
文摘Our field experiments showed that the cultivation of pearl mussels formed a new biocoene composed of filamentous algae, protozoa, porifera and coelenterate. It effectively reduced nitrogen, phosphorus, chemical oxygen demand and biochemical oxygen demand in the water by 67.3%, 73.2%, 38.1% and 15.5%, respectively, during May to September 1998 when the water eutrophication was developing. This could control water eutrophication and produce pearls, shellfish meat and shells. This is an economical and effective way to control water eutrophication by using the ultra strong filtering capability of freshwater pearl mussels.
