Improved Approaches to Calculating Dilution and Attenuation Factor in Contaminant Hydrogeology

Dilution and attenuation factor (DAF) has a major influence on soil-to-groundwater screening level calculation for protection of contaminant migration from soil into groundwater at solid waste management units (SWMUs). Risk assessment guidance prepared by U.S. Environmental Protection Agency for site investigation and remediation suggests a default DAF of 20. If the base assumptions included in the default DAF are recognized to be not representative of site conditions at a SWMU, calculation of site-specific DAF is recommended when sufficient data are collected to justify using a different DAF value for development of soil screening levels. Commonly used methods of calculating DAF include analytical and numerical simulations that often require too many parameters to be obtained in practice. This paper proposes a probability method to develop site-specific DAF. The approach uses data that are readily available through field reconnaissance and site-specific investigation. A case study is presented in which the probability method was applied to an actual SWMU, and the calculated DAF is compared with that calculated from a dilution method. The probability-based DAF is 67 at 90% probability percentile, which is comparable to the dilution-based DAF of 76. Based on the calculated site-specific DAFs, SSLs could be developed for the contaminants of potential concern and used for evaluation of migration pathways from a contamination source through soil to groundwater. .

Pattern-Moving-Based Parameter Identification of Output Error Models with Multi-Threshold Quantized Observations

This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm.

A Novel Bidirectional Interaction Model and Electric Energy Measuring Scheme of EVs for V2G with Distorted Power Loads

With the increasing demand for petroleum resources and environmental issues,new energy electric vehicles are increasingly being used.However,the large number of electric vehicles connected to the grid has brought new challenges to the operation of the grid.Firstly,A novel bidirectional interaction model is established based on modulation theory with nonlinear loads.Then,the electric energy measuring scheme of EVs for V2G is derived under the conditions of distorted power loads.The scheme is composed of fundamental electric energy,fundamental-distorted electric energy,distorted-fundamental electric energy and distorted electric energy.And the characteristics of each electric energy are analyzed.Finally,the correctness of the model and energy measurement method is verified by three simulation cases:the impact signals,the fluctuating signals,and the harmonic signals.