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典型城市化河流中新兴关注污染物的空间自相关和时间变化。

Spatial autocorrelation and temporal variation of contaminants of emerging concern in a typical urbanizing river.

机构信息

Fujian Key Laboratory of Watershed Ecology, CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.

Fujian Key Laboratory of Watershed Ecology, CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Department of Environmental Sciences, The University of Haripur, Haripur 22620, Pakistan.

出版信息

Water Res. 2022 Apr 1;212:118120. doi: 10.1016/j.watres.2022.118120. Epub 2022 Jan 24.

Abstract

The distribution and fate of contaminants of emerging concern (CECs) was studied in relation to hydrological conditions, land use characteristics, and spatial contiguity in Houxi River. Thirty-four CECs were detected in the surface water during a three-year sampling campaign. Caffeine was most prevalent (99% frequency), while bisphenol A had the highest median concentration (78.2 ng/L) among the detected CECs. Caffeine and the other prevalent CECs lincomycin and bisphenol A, with median concentrations of 3.89 ng/L, 0.26 ng/L, and 78.2 ng/L, respectively, were positively correlated with land use types related to anthropogenic activities (grass, barren, built up, and cropland areas and landscape indexes for human activities). The analysis of similarities revealed significant annual variations, with increasing trends in both the concentrations and detection frequencies of CECs. Spatial variations were demonstrated by higher concentrations and detection frequencies downstream compared to upstream. The singular value decomposition analysis revealed that the downstream sites were the major contributors (55.6%-100%) to the spatial variability of most CECs. Moran's I analysis based on downstream contiguity indicated strong spatial autocorrelation among the connected sites for most CECs. This was further supported by longer correlation lengths for 18 CECs than the average distance between the sampling sites. The spatial autocorrelation can be attributed to the physicochemical properties of CECs and local hydrological dynamics, including temperature, wind speed, and sunshine hours. For most CECs, local contribution predominated over neighbor influence with an average value of 75.5%. The results of this study provide new insight to evaluate CEC distributions, which will be beneficial to policymakers for the management and prioritization of CEC contaminants in the Houxi watershed.

摘要

本研究考察了侯西河的水文条件、土地利用特征和空间连续性与新兴关注污染物(CECs)分布和归宿的关系。在为期三年的采样过程中,检测到了 34 种 CECs。在检测到的 CECs 中,咖啡因(99%的频率)最为普遍,双酚 A(78.2ng/L)的中位数浓度最高。咖啡因和其他常见的 CECs,林可霉素和双酚 A,其中位数浓度分别为 3.89ng/L、0.26ng/L 和 78.2ng/L,与与人为活动相关的土地利用类型(草地、荒地、建成区和耕地以及人类活动的景观指数)呈正相关。相似性分析显示出显著的年度变化,CECs 的浓度和检测频率均呈上升趋势。空间变化表现为下游的浓度和检测频率均高于上游。奇异值分解分析表明,下游站点是大多数 CECs 空间变异性的主要贡献者(55.6%-100%)。基于下游连通性的 Moran's I 分析表明,对于大多数 CECs,连通站点之间存在很强的空间自相关。这进一步得到了 18 种 CECs 的相关长度比采样点之间的平均距离更长的支持。空间自相关可归因于 CECs 的物理化学性质和局部水文动力,包括温度、风速和日照小时数。对于大多数 CECs,本地贡献占主导地位,邻居影响平均为 75.5%。本研究的结果提供了评估 CEC 分布的新视角,这将有利于决策者对侯西河流域 CEC 污染物的管理和优先级排序。

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