Deriving field-based sediment quality guidelines from the relationship between species density and contaminant level using a novel nonparametric empirical Bayesian approach

This paper describes a novel statistical approach to derive ecologically relevant sediment quality guidelines (SQGs) from field data using a nonparametric empirical Bayesian method (NEBM). We made use of the Norwegian Oil Industrial Association database and extracted concurrently obtained data on species density and contaminant levels in sediment samples collected between 1996 and 2001. In brief, effect concentrations (ECs) of each installation (i.e., oil platform) at a given reduction in species density were firstly derived by fitting a logistic-type regression function to the relationship between the species density and the corresponding concentration of a chemical of concern. The estimated ECs were further improved by the NEBM which incorporated information from other installations. The distribution of these improved ECs from all installations was determined nonparametrically by the kernel method, and then used to determine the hazardous concentration (HC) which can be directly linked to the species loss (or the species being protected) in the sediment. This method also enables an accurate estimation of the lower confidence limit of the HC, even when the number of observations was small. To illustrate the effectiveness of this novel technique, barium, cadmium, chromium, copper, mercury, lead, tetrahydrocannabinol, and zinc were chosen as example contaminants. This novel approach can generate ecologically sound SQGs for environmental risk assessment and cost-effectiveness analysis in sediment remediation or mud disposal projects, since sediment quality is closely linked to species density.     

Numerical investigation of pollutant transport characteristics inside deep urban street canyons

A validated LES model was employed to simulate the street canyons of aspect ratio (AR) 3, 5, and 10. Three, five, and eight vertically aligned primary recirculations were found for the three cases, respectively, which showed decreasing strength with decreasing height. The ground-level wind speeds were found to be very small, making it extremely difficult for the ground-level pollutants to disperse. Local maxima of turbulence intensities were found at the interfaces between the primary recirculations and the shear layer. The pollutant trajectory followed the primary recirculations. High pollutant concentration and variance were found near the buildings where wind flowed upward. Large gradients of pollutant concentration and variance were also observed at the interfaces between the primary recirculations and the shear layer. Detailed analyses of concentration budget showed that the advection terms were responsible for pollutant redistribution within primary recirculations, while the turbulent transport terms were responsible for pollutant penetration between primary recirculations as well as pollutant removal from the street canyon.     

Fatigue Life Behaviour of Glass/Kenaf Woven-Ply Polymer Hybrid Biocomposites

Investigation on the fatigue life of hybrid composites is critical to extend their applications and acceptance among industries; however, there is a lack of research focus on fatigue performance of the hybrid composite. In this study, the fatigue life of glass/kenaf woven-ply hybrid composite with thermoplastic and thermoset polymer matrix was investigated. Hybrid composites consist of two different fibre configurations: kenaf/glass/kenaf and glass/kenaf/glass. Thermoplastic hybrid composites were manufactured through the hot press moulding compression method, while thermoset hybrid composites were fabricated through the vacuum-assisted resin infusion method. The tensile strength and fatigue strengths of the kenaf/glass/kenaf composite have been identified to be significantly lower than those of the glass/kenaf/glass composite regardless of the types of matrix used. However, thermoplastic-based kenaf/glass/kenaf composites are less fatigue sensitive compared to glass/kenaf/glass composites; however, this phenomenon is vice versa for thermoset composites due to the epoxy matrix, which limits the stiffening effect in natural fibres.     

An ensemble Kalman filter for atmospheric data assimilation: Application to wind tunnel data

In the previous work (Zheng et al., 2007, Zheng et al., 2009), a data assimilation method, based on ensemble Kalman filter, has been applied to a Monte Carlo Dispersion Model (MCDM). The results were encouraging when the method was tested by the twin experiment and a short-range field experiment. In this technical note, the measured data collected in a wind tunnel experiment have been assimilated into the Monte Carlo dispersion model. The uncertain parameters in the dispersion model, including source term, release height, turbulence intensity and wind direction have been considered. The 3D parameters, i.e. the turbulence intensity and wind direction, have been perturbed by 3D random fields. In order to find the factors which may influence the assimilation results, eight tests with different specifications were carried out. Two strategies of constructing the 3D perturbation field of wind direction were proposed, and the result shows that the two level strategy performs better than the one level strategy. It is also found that proper standard deviation and the correlation radius of the perturbation field play an important role for the data assimilation results.