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Multivariate Analyses for Monitoring EDCs and PPCPs in a Lake Water
Author(s) -
Park Minji,
Reckhow David,
Lavine Michael,
Rosenfeldt Erik,
Stanford Benjamin,
Park MiHyun
Publication year - 2014
Publication title -
water environment research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 73
eISSN - 1554-7531
pISSN - 1061-4303
DOI - 10.2175/106143014x14062131178592
Subject(s) - sampling (signal processing) , environmental science , environmental impact of pharmaceuticals and personal care products , multivariate statistics , surface water , water quality , principal component analysis , environmental chemistry , ecology , environmental engineering , chemistry , biology , statistics , wastewater , computer science , mathematics , filter (signal processing) , computer vision
The analysis of endocrine disrupting compounds (EDCs) and pharmaceutical and personal care products (PPCP), present at trace level in surface waters, is often expensive, time‐consuming, and complex. Implementing effective monitoring strategies for these compounds is essential to determine the types of analytes, sampling locations, and sampling frequencies. Multivariate analyses were used to investigate the patterns of EDCs and PPCPs in Lake Mead, Nevada, for these purposes. The results of cluster analysis and principal component analysis to identify the patterns among compounds demonstrated that selected pharmaceuticals tended to be present together with each other, whereas hormones did not show patterns with other compounds. The results of cluster analysis and discriminant analysis to investigate the spatial variation of EDCs and PPCPs eliminated redundant sampling locations, verifying the current selection of sampling locations in Lake Mead. The results of autocorrelation provided optimal sampling frequencies for EDCs and PPCPs, suggesting either monthly or quarterly monitoring of these compounds in Lake Mead. The patterns of the compounds could be site specific, depending on weather and hydrological conditions of the water systems, but this study's approaches will facilitate effective assessment and monitoring of EDCs and PPCPs in surface water.