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Vrana B Paschke H Paschke A Popp P Schuurmann G 《Journal of environmental monitoring : JEM》2005,7(5):500-508
Lipid-filled semipermeable membrane devices (SPMDs) are receiving increasing attention as passive, in situ samplers for the assessment of environmental pollutant exposure. Although SPMDs have been successfully used in a variety of field studies in surface waters, only a few studies have addressed their characteristics as groundwater samplers. In this study, the performance of the SPMDs for monitoring organic contaminants in groundwater was evaluated in a pilot field application in an area severely contaminated by chemical waste, especially by chlorinated hydrocarbons. The spatial distribution of hydrophobic groundwater contaminants was assessed using a combination of passive sampling with SPMDs and non-target semiquantitative GC-MS analysis. More than 100 contaminants were identified and semiquantitatively determined in SPMD samples. Along the 6 field sites under investigation, a large concentration gradient was observed, which confirms a very limited mobility of hydrophobic substances in dissolved form in the aquifer. The in situ extraction potential of the SPMD is limited by groundwater flow, when the exchange volume of well water during an exposure is lower than the SPMD clearance volume for the analytes. This study demonstrates that SPMDs present a useful tool for sampling and analyzing of groundwater polluted with complex mixtures of hydrophobic chemicals and provides guidance for further development of passive sampling technology for groundwater. 相似文献
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Fatih Ilhan Kubra Ulucan-Altuntas Yasar Avsar Ugur Kurt Arslan Saral 《Frontiers of Environmental Science & Engineering》2019,13(5):73
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Masami Fujiwara Kurt E. Anderson Michael G. Neubert Hal Caswell 《Environmental and Ecological Statistics》2006,13(2):183-197
We present a new method for estimating a distribution of dispersal displacements (a dispersal kernel) from mark-recapture
data. One conventional method of calculating the dispersal kernel assumes that the distribution of displacements are Gaussian
(e.g. resulting from a diffusion process) and that individuals remain within sampled areas. The first assumption prohibits
an analysis of dispersal data that do not exhibit the Gaussian distribution (a common situation); the second assumption leads
to underestimation of dispersal distance because individuals that disperse outside of sampling areas are never recaptured.
Our method eliminates these two assumptions. In addition, the method can also accommodate mortality during a sampling period.
This new method uses integrodifference equations to express the probability of spatial mark-recapture data; associated dispersal,
survival, and recapture parameters are then estimated using a maximum likelihood method. We examined the accuracy of the estimators
by applying the method to simulated data sets. Our method suggests designs for future mark-recapture experiments.
Received: January 2004 / Revised: July 2005 相似文献
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