为研究河流沉积物内源污染与人类活动的响应关系,采集成都市内33个点位的河流表层沉积物,采用SMT和DGT方法监测沉积物中各形态磷及生物有效性磷含量,结合多元统计方法分析其空间分布特征,计算沉积物及其孔隙水中有效态磷的释放通量.结果表明,成都市河流表层沉积物各形态磷存在空间差异性;成都市河流表层沉积物TP的平均含量为1132.41 mg·kg^-1,高于成都市土壤背景值365.00 mg·kg^-1,Ca-P为最主要磷形态,平均占TP的70.58%;研究区域可划分为3类,第1、3类的磷形态结构差异大,而第2类小,且第1、3类各形态磷含量普遍高于第2类;ω(DGT-P)分别与水体ω(DTP)、具有生物有效性的ω(Fe/Al-P)和ω(OP)均有良好的相关性,DGT技术可作为快速原位检测沉积物生物有效磷含量的可靠方法;有效态磷释放量较高的为N8 >W11 >N2,分别为20.05、17.13、14.79 mg·(m^2·d)^-1,其释放能力与人类活动密切相关.
A total of 33 surface sediments were collected from rivers in Chengdu. The content of phosphorus species was measured with the chemical continuous extraction method (SMT) and in situ monitoring techniques (DGT). Multivariate statistical analysis was used to analyze the spatial distribution of phosphorus species in sediments. The release flux of DGT-P in sediments and their pore water was calculated in this study. It is helpful to understand the influence of sediment endogenous pollution and human activities on the environment. The results show that the phosphorus species have a spatial variability. The average content of TP in the surface sediments is 1132.41 mg·kg^-1, which is higher than the background value of 365.00 mg·kg^-1 in Chengdu. The Ca-P is the most dominant species, accounting for 70.58% of the TP on average. The study area is divided into three groups based on spatial clustering. Groups 1 and 3 show large differences of phosphorus morphological structures, while Group 2 is small. The contents of phosphorus in the surface sediment of Groups 1 and 3 are generally higher than those of Group 2. The DGT-P concentration has a good correlation with the soluble DTP concentration, bioavailable Fe/Al-P, and OP concentration, respectively. The DGT technology can be used as a fast, in situ, reliable method for measurements of the bioavailable content of sediments. The higher release fluxes of bioavailable phosphorus are N8, W11, and N2, which are 20.05, 17.13, and 14.79 mg·(m^2·d)^-1 respectively. The available phosphorus release capacity is closely related to human activities.
Chinese Journal of Environmental Science
multivariate statistical analysis