Semi-parametric statistical approaches for space-time process prediction

The problem of estimation and prediction of a spatial-temporal stochastic process, observed at regular times and irregularly in space, is considered. A mixed formulation involving a non- parametric component, accounting for a deterministic trend and the effect of exogenous variables, and a parametric component representing the purely spatio-temporal random variation is proposed. Correspondingly, a two-step procedure, first addressing the estimation of the non- parametric component, and then the estimation of the parametric component is developed from the residual series obtained, with spatial-temporal prediction being performed in terms of suitable spatial interpolation of the temporal variation structure. The proposed model formula-tion, together with the estimation and prediction procedure, are applied using a Gaussian ARMA structure for temporal modelling to space-time forecasting from real data of air pollution concentration levels in the region surrounding a power station in northwest Spain.     

Major and trace elements of selected pedons in the USA

Few studies of soil geochemistry over large geographic areas exist, especially studies encompassing data from major pedogenic horizons that evaluate both native concentrations of elements and anthropogenically contaminated soils. In this study, pedons (n = 486) were analyzed for trace (Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Zn) and major (Al, Ca, Fe, K, Mg, Na, P, Si, Ti, Zr) elements, as well as other soil properties. The objectives were to (i) determine the concentration range of selected elements in a variety of U.S. soils with and without known anthropogenic additions, (ii) illustrate the association of elemental source and content by assessing trace elemental content for several selected pedons, and (iii) evaluate relationships among and between elements and other soil properties. Trace element concentrations in the non-anthropogenic dataset (NAD) were in the order Mn > (Zn, Cr, Ni, Cu) > (Pb, Co) > (Cd, Hg), with greatest mean total concentrations for the Andisol order. Geometric means by horizon indicate that trace elements are concentrated in surface and/or B horizons over C horizons. Median values for trace elements are significantly higher in surface horizons of the anthropogenic dataset (AD) over the NAD. Total Al, Fe, cation exchange capacity (CEC), organic C, pH, and clay exhibit significant correlations (0.56, 0.74, 0.50, 0.31, 0.16, and 0.30, respectively) with total trace element concentrations of all horizons of the NAD. Manganese shows the best inter-element correlation (0.33) with these associated total concentrations. Total Fe has one of the strongest relationships, explaining 55 and 30% of the variation in total trace element concentrations for all horizons in the NAD and AD, respectively.     

THE VULNERABILITY OF WETLANDS TO CLIMATE CHANGE: A HYDROLOGIC LANDSCAPE PERSPECTIVE1

ABSTRACT: The vulnerability of wetlands to changes in climate depends on their position within hydrologic landscapes. Hydrologic landscapes are defined by the flow characteristics of ground water and surface water and by the interaction of atmospheric water, surface water, and ground water for any given locality or region. Six general hydrologic landscapes are defined; mountainous, plateau and high plain, broad basins of interior drainage, riverine, flat coastal, and hummocky glacial and dune. Assessment of these landscapes indicate that the vulnerability of all wetlands to climate change fall between two extremes: those dependent primarily on precipitation for their water supply are highly vulnerable, and those dependent primarily on discharge from regional ground water flow systems are the least vulnerable, because of the great buffering capacity of large ground water flow systems to climate change.     

Global sensitivity analysis of a process-based model for ammonia emissions from manure storage and treatment structures

The development of process-based models to estimate ammonia emissions from animal feeding operations (AFOSs) is sought to replace costly and time-consuming direct measurements. Critical to process-based model development is conducting sensitivity analysis to determine the input parameters and their interactions that contribute most to the variance of the model output. Global and relative sensitivity analyses were applied to a process-based model for predicting ammonia emissions from the surface of anaerobic lagoons for treating and storing manure. The objectives were to compare global sensitivity analysis (GSA) to relative (local) sensitivity analysis (RSA) on a process-based model for ammonia emissions. Based on the first-order coefficient, both GSA and RSA showed the model input parameters in order of importance in process model for ammonia emissions from lagoon surfaces were: (i) pH, (ii) lagoon liquid temperature, (iii) wind speed above the lagoon surface, and (iv) the concentration of ammoniacal nitrogen in the lagoon. The GSA revealed that interactions between model parameters accounted for over two-thirds of the model variance, a result that cannot be achieved using traditional RSA. Also, the GSA showed that parameter interactions involving liquid pH had more impact on the model output variance than the single parameters: (i) temperature, (ii) wind speed, or (iii) total ammoniacal nitrogen. This study demonstrates that GSA provides a more complete analysis of model input parameters and their interactions on the model output compared to RSA. A comprehensive tutorial regarding the application of GSA to a process model is presented.     

Sleepiness among night-time drivers: relationship to blood alcohol concentration and other factors

OBJECTIVE: The study aimed to explore the distribution and correlates of subjective sleepiness among the general night-time driving population. METHODS: The survey took place in three British Columbia communities in June 2003 between 21:00 hours to 03:00 hours. Sites and vehicles were selected randomly. Surveyors obtained information on several demographic and situational variables including self-assessed degree of sleepiness and self-reported hours asleep and awake, as well as an objective measure of blood alcohol concentration obtained from a hand-held breath-testing device. RESULTS: The total compliance rate among intercepted drivers was 85%. Among the 2335 drivers responding to the questionnaire, 68.4% indicated that they were wide awake, 27.6% were somewhat sleepy, and 4.1% were very sleepy. Logistic regression quantified the independent contributions of the various factors to subjective sleepiness. Male drivers with positive blood alcohol concentrations under 50 mg% were more likely to report feeling sleepy than those with either higher or with zero blood alcohol concentration. Greater relative risk of sleepiness was also associated with being female, being under age 55, and advanced hour of night. Driving with passengers of the same gender was associated with lower reported sleepiness. CONCLUSIONS: A substantial proportion of night-time drivers are driving while sleepy, especially at late night and early morning hours. The combination of alcohol and sleepiness compounds impairment in experimental studies and deserves greater attention in crash risk studies and as a topic for public education and awareness.     

Control chart for monitoring occupational asthma

INTRODUCTION: Work-related asthma has become the most prevalent occupational respiratory disease in the developed world. Occupational asthma is thought to affect 5%-10% of people worldwide. The first step in the diagnosis of occupational asthma is to establish work-relatedness. Although considerable research has been conducted in the area of occupational asthma, no simple, effective, and statistically sound method has been developed that can be used as an initial step to effectively identify the workers at risk for occupational asthma. The purpose of this research was to investigate whether Shewhart control chart method can be used as an effective method to detect occupational asthma. METHOD: Forty-five workers who completed the study and provided usable peak expiratory flow (a lung function marker) recordings while at work and away from work were included in this study. Control charts were developed using Shewhart's Method. The lower control limit of at work control chart (LCL(W)) was compared to each subject's Personal Best (PB) value. RESULTS: Reviewing the results of this comparison showed LCL(W)<60% PB to have a sensitivity of 85.71%, specificity of 87.50%, and an error rate of 13.33%. When the subjects suspected for false positive and false negative diagnoses were identified, the test produced a sensitivity of 95.24%, a specificity of 95.83% and an error rate of 4.44%. CONCLUSIONS: Our results were as good as, and in some cases better than, published clinical guidelines. IMPACT ON INDUSTRY: Our research showed that the control chart method is an effective, simple, and inexpensive tool for early intervention in workers suspected for occupational asthma.     

Characteristics and risks of drivers with low annual distance driven

OBJECTIVES: It has been noted by several authors that risk (defined only in terms of total expected numbers of crash involvements per total distance driven) paints a misleading picture of crash liability, particularly for the young and the old, as their high risk is associated with risky driving patterns typical of people who drive low annual kms. This article sets out to analyze these driving patterns of low-km drivers and to evaluate the risk of these patterns. As licensing programs tend to focus on young and old drivers, who tend to drive lower annual distances, income and employment data are also analyzed for low-km drivers. This is to provide a better picture for policy makers of the sort of people and the sorts of transportation requirements that their policies may affect. METHODS: Crash data and travel data were disaggregated by driver characteristics and by driving conditions (road type, day and night, weekend and weekday) and combined to form estimates of risk for typical driving patterns of driver groups. Characteristics of driving patterns and of the drivers themselves were derived for groups defined by age and by the amount of annual driving undertaken. RESULTS: Older drivers who drive less tend to have higher risk per km mainly due to their predominantly urban trips. Nevertheless, because older drivers on average manage to reduce their risk per distance driven by choosing driving patterns that are safer than the driving patterns of other age groups, the risk of older drivers as a group is not overestimated. CONCLUSION: Despite being quite different from one another, the low- and high-km driving patterns of younger drivers were found to impose identical risks.