Performance of Balanced Two-Stage Empirical Predictors of Realized Cluster Latent Values from Finite Populations: A Simulation Study

Predictors of random effects are usually based on the popular mixed effects (ME) model developed under the assumption that the sample is obtained from a conceptual infinite population; such predictors are employed even when the actual population is finite. Two alternatives that incorporate the finite nature of the population are obtained from the superpopulation model proposed by Scott and Smith (1969. Estimation in multi-stage surveys. J. Amer. Statist. Assoc. 64, 830-840) or from the finite population mixed model recently proposed by Stanek and Singer (2004. Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 1119-1130). Predictors derived under the latter model with the additional assumptions that all variance components are known and that within-cluster variances are equal have smaller mean squared error (MSE) than the competitors based on either the ME or Scott and Smith's models. As population variances are rarely known, we propose method of moment estimators to obtain empirical predictors and conduct a simulation study to evaluate their performance. The results suggest that the finite population mixed model empirical predictor is more stable than its competitors since, in terms of MSE, it is either the best or the second best and when second best, its performance lies within acceptable limits. When both cluster and unit intra-class correlation coefficients are very high (e.g., 0.95 or more), the performance of the empirical predictors derived under the three models is similar.     

Biological removal of pharmaceuticals and personal care products during laboratory soil aquifer treatment simulation with different primary substrate concentrations

Pharmaceuticals and personal care products (PPCPs) have been detected in bodies of water worldwide, yet their effects on the environment are not fully understood. Recent toxicity studies suggest that mixtures of PPCPs at low concentrations may be detrimental to exposed organisms, highlighting the need to remove PPCPs from wastewater treatment plant effluent before it is discharged to the environment. In this study, the utility of biofilm-based PPCP removal as a means to prevent environmental PPCP contamination was investigated. The removal of 14 PPCPs, each at an initial concentration of 10 μg/L, was studied in laboratory sand columns inoculated with wastewater treatment plant effluent. The examined PPCPs included biosol, biphenylol, p-chloro-m-cresol, p-chloro-m-xylenol, chlorophene, sodium diclofenac, gabapentin, gemfibrozil, 5-fluorouracil, ibuprofen, ketoprofen, naproxen, triclosan, and valproic acid. Ten of the PPCPs were removed by greater than 95% during column passage, while the four other compounds proved more recalcitrant. The effect of the concentration (either 50 or 1000 μg/L) of an easily degradable primary substrate (acetate) supplied along with the mixture of PPCPs was examined. Most of the tested PPCPs were removed consistently by the biofilms regardless of the concentration of acetate, although the extent of removal for three compounds showed dependence on acetate concentration, and two behaved with no reproducible pattern over time. Biofilm protein measurements indicated that the mixture of PPCPs supplied to columns suppressed biofilm growth, suggesting toxicity of the PPCPs to the biofilm communities. This laboratory-scale experiment suggests that biofilm-based water treatment strategies, such as soil aquifer treatment and slow sand filtration, may be well-suited for the removal of many PPCPs from impacted water.     

Destruction of estrogenic activity in water using UV advanced oxidation

The transformation of the steroidal Endocrine Disrupting Compounds (EDCs), 17-beta-estradiol (E2) and 17-alpha-ethinyl estradiol (EE2) by direct UV photolysis and UV/H(2)O(2) advanced oxidation was studied from the perspective of the removal of estrogenic activity associated with the compounds. First, experiments were performed to link the oxidation of E2 and EE2 with subsequent reduction in estrogenic activity. No statistically significant difference between removal rates was observed, implying that the oxidation products of E2 and EE2 are not as estrogenic (measured by the Yeast Estrogen Screen (YES)) as the parent compounds. Utilizing the YES, 90% removal of estrogenic activity of E2 and EE2 at environmentally relevant concentrations ( approximately 3 microg L(-1)) was achieved using a combination of 5 mg L(-1) H(2)O(2) and a UV fluence of less than 350 mJ cm(-2). Thus, these compounds, when considered at environmentally relevant levels, are significantly degraded at much lower UV fluences than previously thought. A steady state OH radical model was used to predict oxidation of EE2 in laboratory and natural waters.     

Denitrification from drinking water using a membrane bioreactor: chemical and biochemical feasibility

Interest is growing in developing membrane bioreactors (MBRs) to replace ion exchange for nitrate removal from drinking water. However, few published studies have successfully managed to retain exogenous or biologically derived carbon. This study determined an optimum C:N by substrate breakthrough rather than maximum nitrate removal. By dosing 相似文献