کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4483242 | 1316882 | 2011 | 12 صفحه PDF | دانلود رایگان |
Accurate analysis of tracer-breakthrough curves is dependent on the removal of measured background concentrations from the measured tracer recovery data. Background concentrations are commonly converted to a single mean background concentration that is subtracted from tracer recovery data. To obtain an improved estimate for the mean background concentration, a statically-robust procedure addressing left-censored data and possible outliers in background concentration data is presented. A maximum likelihood estimate and other robust methods coupled with outlier removal are applied. Application of statically-robust procedures to background concentrations results not only in better estimates for mean background concentration but also results in more accurate quantitative analyses of tracer-breakthrough curves when the mean background concentration is subtracted.
► This study examines the importance of background tracer concentrations on breakthrough curves.
► Calculations consider outliers removal and outliers accommodation.
► Measured concentrations below detection limits are considered in calculations for the sample mean, median, etc.
► Various substitution methods were used in comparison with a maximum likelihood estimation.
► Results suggest the maximum likelihood estimation method may be best after outliers removal.
Journal: Water Research - Volume 45, Issue 10, May 2011, Pages 3107–3118