[1] Effective process control is crucial in implementing remediation actions for petroleum-contaminated sites. However, in dealing with in situ bioremediation practices, difficulties exist in incorporating numerical simulation models that are needed for process forecasting within real-time non-linear optimization frameworks that are critical for supporting the process control. With such difficulties, it is desired that a statistical relationship between remediation system performance and operating condition be established. Nevertheless, in the remediation systems, many variables can be either continuous or discrete, and the relations among them can be either linear or non-linear. These lead to complexities in the related multivaraite analyses. In this study, a forecasting system has been developed for supporting remediation design and process control based on techniques of NAPL-biodegradation (non-aqueous phase liquid biodegradation) simulation and stepwise-cluster analysis (SCA). The results indicate that the developed system is effective in forecasting the effects of multiple cleanup actions under various conditions. The predicted benzene concentrations have acceptable error levels compared with the outputs of numerical simulation. An optimization model for obtaining optimum operating conditions is then proposed to illustrate how the SCA method can be used for supporting optimization of bioremediation operations. A unique contribution of this research is the development of a multivariate inference system associated with simulation and optimization efforts for tackling the complex in situ bioremediation practices.

No abstract

The adsorption isotherm and the mechanism of the buffering effect are important controls on phosphorus (P) behaviors in estuaries and are important for estimating phosphate concentrations in aquatic environments. In this paper, we derive phosphate adsorption isotherms in order to investigate sediment adsorption and buffering capacity for phosphorus discharged from sewage outfalls in the Yangtze Estuary and Hangzhou Bay near Shanghai, China. Experiments were also carried out at different temperatures in order to explore the buffering effects for phosphate. The results show that P sorption in sediments with low fine particle fractions was best described using exponential equations. Some P interactions between water and sediment may be caused by the precipitation of CaHPO₄ from Ca²⁺ and HPO₄²⁻ when the phosphate concentration in the liquid phase is high. Results from the buffering experiments suggest that the Zero Equilibrium Phosphate Concentrations (EPC₀) vary from 0.014 mg L⁻¹ to 0.061 mg L⁻¹, which are consistent with measured phosphate concentrations in water samples collected at the same time as sediment sampling. Values of EPC₀ and linear sorption coefficients (K) in sediments with high fine particle and organic matter contents are relatively high, which implies that they have high buffering capacity. Both EPC₀ and K increase with increasing temperature, indicating a higher P buffering capacity at high temperatures

A successful experiment with a physical model requires necessary conditions of similarity. This study presents an experimental method with a semi-scale physical model. The model is used to monitor and verify soil conservation by check dams in a small watershed on the Loess Plateau of China. During experiments, the model-prototype ratio of geomorphic variables was kept constant under each rainfall event. Consequently, experimental data are available for verification of soil erosion processes in the field and for predicting soil loss in a model watershed with check dams. Thus, it can predict the amount of soil loss in a catchment. This study also mentions four criteria: similarities of watershed geometry, grain size and bare land, Froude number (Fr) for rainfall event, and soil erosion in downscaled models. The efficacy of the proposed method was confirmed using these criteria in two different downscaled model experiments. The B-Model, a large scale model, simulates watershed prototype. The two small scale models, D(a) and D(b), have different erosion rates, but are the same size. These two models simulate hydraulic processes in the B-Model. Experiment results show that while soil loss in the small scale models was converted by multiplying the soil loss scale number, it was very close to that of the B-Model. Obviously, with a semi-scale physical model, experiments are available to verify and predict soil loss in a small watershed area with check dam system on the Loess Plateau, China.

No abstract