Geospatial Variability of Fluorescent Dissolved Organic Matter in Urban Watersheds: Relationships with Land Cover and Wastewater Infrastructure

被引:0
|
作者
Batista-Andrade, Jahir A. [1 ]
Welty, Claire [1 ,2 ]
Vega, Diego Iglesias [1 ]
McClain, Anna [1 ]
Blaney, Lee [1 ]
机构
[1] Univ Maryland Baltimore Cty, Dept Chem Biochem & Environm Engn, Baltimore, MD 21250 USA
[2] Univ Maryland Baltimore Cty, Ctr Urban Environm Res & Educ, Baltimore, MD 21250 USA
基金
美国国家科学基金会;
关键词
humic substances; fluorescence; contaminantsof emerging concern; geostatistical analysis; sewer; septic system; RIVER; STREAMS; DOC;
D O I
10.1021/acs.est.3c07925
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
We investigated the fluorescent dissolved organic matter (FDOM) composition in two watersheds with variable land cover and wastewater infrastructure, including sanitary sewers and septic systems. A four-component parallel factor analysis model was constructed from 295 excitation-emission matrices recorded for stream samples to examine relationships between FDOM and geospatial parameters. The contributions of humic acid- and fulvic acid-like fluorescence components (e.g., C1, C2, C3) were fairly consistent across a 12 month period for the 27 sampling sites. In contrast, the protein-like fluorescence component (C4) and a related ratiometric wastewater indicator (C4/C3) exhibited high variability in urban tributaries, suggesting that some sites were impacted by leaking sewer infrastructure. Principal component analysis indicated that urban areas clustered with impervious surfaces and sanitary sewer density, and cross-covariance analysis identified strong positive correlations between C4, impervious surfaces, and sanitary sewer density at short lag distances. The presence of wastewater was confirmed by detection of sucralose (up to 1,660 ng L-1) and caffeine (up to 1,740 ng L-1). Our findings not only highlight the potential for C4 to serve as an indicator of nearby, compromised sanitary sewer infrastructure, but also suggest that geospatial data can be used to predict areas vulnerable to wastewater contamination.
引用
收藏
页码:7529 / 7542
页数:14
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