Sensitivity of two dispersion models (AERMOD and ISCST3) to input parameters for a rural ground-level area source

As of December 2006, the American Meteorological Society/U.S. Environmental Protection Agency (EPA) Regulatory Model with Plume Rise Model Enhancements (AERMOD-PRIME; hereafter AERMOD) replaced the Industrial Source Complex Short Term Version 3 (ISCST3) as the EPA-preferred regulatory model. The change from ISCST3 to AERMOD will affect Prevention of Significant Deterioration (PSD) increment consumption as well as permit compliance in states where regulatory agencies limit property line concentrations using modeling analysis. Because of differences in model formulation and the treatment of terrain features, one cannot predict a priori whether ISCST3 or AERMOD will predict higher or lower pollutant concentrations downwind of a source. The objectives of this paper were to determine the sensitivity of AERMOD to various inputs and compare the highest downwind concentrations from a ground-level area source (GLAS) predicted by AERMOD to those predicted by ISCST3. Concentrations predicted using ISCST3 were sensitive to changes in wind speed, temperature, solar radiation (as it affects stability class), and mixing heights below 160 m. Surface roughness also affected downwind concentrations predicted by ISCST3. AERMOD was sensitive to changes in albedo, surface roughness, wind speed, temperature, and cloud cover. Bowen ratio did not affect the results from AERMOD. These results demonstrate AERMOD's sensitivity to small changes in wind speed and surface roughness. When AERMOD is used to determine property line concentrations, small changes in these variables may affect the distance within which concentration limits are exceeded by several hundred meters.     

An evaluation of global QSAR models for the prediction of the toxicity of phenols to Tetrahymena pyriformis

This study presents an analysis of the ability of a two-parameter response surface, a multiple linear regression and a neural network model to produce global quantitative structure-activity relationships (QSARs) to predict the toxic potency of phenols to Tetrahymena pyriformis. The phenolic toxicity data set analysed is characterised by multiple mechanisms of toxic action. The study aimed to evaluate the confidence that can be applied to the modelling of the differing mechanisms of action. Assessment of confidence was decided in terms of whether the statistics for the global models reflect the ability of the QSARs to model the individual mechanisms of toxic action present in the data set. The results showed that the global statistics only reflected the ability of models to predict the two non-covalent mechanisms (polar narcosis and respiratory uncoupling), with the metabolically transformed and electrophilic mechanism (pre-electrophiles and soft electrophiles) being modelled poorly by all three model building methods. The results confirm the difficulty in modelling electrophilic mechanisms of toxic action. The results also highlight the fact that this poor predictivity is often 'hidden' in good statistical fit of some global models. In particular these results emphasise that for practical predictive purposes the mechanistic applicability domain is required to give confidence to estimated toxicity values.     

Comparative analysis of two tobacco surveillance questionnaires used in NHANES: accuracy of self-reported smoking status

National Health and Nutrition Examination Survey (NHANES) uses two tobacco use surveillance questionnaires. One is administered during an at-home interview (HI) and the other, during an examination session at a mobile examination center (MEC). NHANES data for the years 1999–2012 were used to evaluate the consistency of responses to tobacco surveillance questions in HI and MEC interview. In addition, accuracy of self-reported smoking status was evaluated. Of those who reported to be daily cigarette smokers during HI, 18.7% reported to be either some-day smokers or nonsmokers during MEC interview. Of those who reported to be some-day cigarette smokers during HI, 22.1% reported to be daily smokers and 17.5% reported to be nonsmokers. Also, 4.1% of those who reported to be nonsmokers during HI reported to be either daily or some-day smokers during MEC interview. Using serum cotinine measurements taken during MEC interview, 27.1% were found to be smokers and 72.9% were found to be nonsmokers. In general, a moderate to high agreement, as measured by the κ statistic, was found between the self-reported responses to tobacco use questions during the home and MEC interviews as well as between smoking statuses based on self-reported and serum cotinine measurements.     

Prediction of mass and momentum transport in turbulent plane wall jets over smooth and transitionally rough surfaces

This paper is concerned with the prediction of mass and momentum transport in turbulent wall jets developing over smooth and transitionally rough plane walls. The ability to accurately predict the resulting wall shear stresses and vertical profiles of the Reynolds stresses in these flows is prerequisite to the accurate prediction of bed scour, sediment re-suspension and transport by turbulent diffusion. The computations were performed by solving the Reynolds-averaged forms of the equations describing conservation of mass, momentum and concentration. The unknown correlations that arise from the averaging process (the Reynolds stresses in the case of the momentum equation, and the turbulent mass fluxes in the case of concentration) were obtained from the solution of modeled differential equations that describe their conservation. Since these models are somewhat more complex than those typically used in practice, their benefits are demonstrated by comparisons with results obtained from simpler, eddy-viscosity based closures. Comparisons with experimental data show that results of acceptable accuracy can be obtained only by using the appropriate combination of models for the turbulent fluxes of mass and momentum that properly account for the reduction of the Reynolds stresses due to wall damping effects, and for the modification of the mass transfer rates due to interactions with the mean rates of strain.     

Modelling the Distribution and Quality of Sand and Gravel Resources in 3D: a Case Study in the Thames Basin,UK

Three-dimensional (3D) models are often utilised to assess the presence of sand and gravel deposits. Expanding these models to provide a better indication of the suitability of the deposit as aggregate for use in construction would be advantageous. This, however, leads to statistical challenges. To be effective, models must be able to reflect the interdependencies between different criteria (e.g. depth to deposit, thickness of deposit, ratio of mineral to waste, proportion of ‘fines’) as well as the inherent uncertainty introduced because models are derived from a limited set of boreholes in a study region. Using legacy borehole data collected during a systematic survey of sand and gravel deposits in the UK, we have developed a 3D model for a 2400 km² region close to Reading, southern England. In developing the model, we have reassessed the borehole grading data to reflect modern extraction criteria and explored the most suitable statistical modelling technique. The additive log-ratio transform and the linear model of coregionalization have been applied, techniques that have been previously used to map soil texture classes in two dimensions, to assess the quality of sand and gravel deposits in the area. The application of these statistical techniques leads to a model which can be used to generate thousands of plausible realisations of the deposit which fully reflect the extent of model uncertainty. The approach offers potential to improve regional-scale mineral planning by providing an enhanced understanding of sand and gravel deposits and the extent to which they meet current extraction criteria.