Inferences About Radionuclide Mobility in Soils Based on the Solid/Liquid Partition Coefficients and Soil Properties

To assist transport modeling in assessments of the radiological impact of a geological repository for radioactive wastes, the mobility of various elements was studied in arable and wetland soils in the Forsmark region, Sweden. Pore water and total element contents were determined for five types of unconsolidated deposits (regolith), spanning a wide range of soil properties with respect to pH and organic matter content. Two soil depths were sampled to capture element mobility in regolith layers affected and unaffected by soil-forming processes. The solid/liquid partition coefficients (K _d values) for most elements varied significantly among regolith types. For most elements, the observed variations in K _d values could be explained by variations in soil properties. For many elements, mobility increased with decreasing soil pH. The results provide a significant addition of data on radionuclide retention in soils, taking account of soil properties and processes.     

History of atmospheric environment

There have been great transitions in the science of air pollution and science publishing since the journal began as the International Journal of Air Pollution in 1958. Atmospheric Environment witnessed the increased understanding of smog photochemistry in the late 1950s and the emerging fears of ozone depletion in the 1970s. The journal has grown, but not without the need to change and occasionally fragment only to reintegrate at a later date. At 9000 pages a year it represents an enormous editorial task that has had to be undertaken by more professional offices. This transition has been helped through the development of electronic tools, but the editorial offices strive to retain their personal relationship with authors and reviewers. An enhanced international perspective recognises the widening contributions made by scientists beyond Europe and North America.     

Modeling the Impacts of Two Bark Beetle Species Under a Warming Climate in the Southwestern USA: Ecological and Economic Consequences

Predicted climate warming is expected to have profound effects on bark beetle population dynamics in the southwestern United States. Temperature-mediated effects may include increases in developmental rates, generations per year, and changes in habitat suitability. As a result, the impacts of Dendroctonus frontalis and Dendroctonus mexicanus on forest resources are likely subject to amplification. To assess the implications of such change, we evaluated the generations per year of these species under three climate scenarios using a degree-day development model. We also assessed economic impacts of increased beetle outbreaks in terms of the costs of application of preventative silvicultural treatments and potential economic revenues forgone. Across the southwestern USA, the potential number of beetle generations per year ranged from 1–3+ under historical climate, an increase of 2–4+ under the minimal warming scenario and 3–5+ under the greatest warming scenario. Economic benefits of applying basal area reduction treatments to reduce forest susceptibility to beetle outbreaks ranged from 7.75/ha (NM) to7.75/ha (NM) to 95.69/ha (AZ) under historical conditions, and 47.96/ha (NM) to47.96/ha (NM) to 174.58/ha (AZ) under simulated severe drought conditions. Basal area reduction treatments that reduce forest susceptibility to beetle outbreak result in higher net present values than no action scenarios. Coupled with other deleterious consequences associated with beetle outbreaks, such as increased wildfires, the results suggest that forest thinning treatments play a useful role in a period of climate warming.     

Compositional analysis of overdispersed counts using generalized estimating equations

Multivariate abundance data are commonly collected in ecology, and used to explore questions of “community composition”—how relative abundance of different taxa changes with environmental conditions. In this paper, we propose a log-linear marginal modeling approach for analyzing such compositional count data, via generalized estimating equations. This method exploits the multiplicative nature of log-linear models for counts, by reparameterizing models that describe marginal effects on mean abundance. This allows partitioning into “main effects” and compositional effects, which is appealing for interpretation. We apply the proposed approach to reanalyze compositional counts of benthic invertebrates from Delaware Bay, and data of invertebrate communities inhabiting Acacia plants in eastern Australia. In both cases we resort to a resampling approach to make inferences about regression parameters, because the number of clusters was not large compared to cluster size.     

Tradeable development rights to protect peri-urban areas: lessons from the United States and observations on Australian practice

As population growth continues there is greater pressure to manage cities and regions sustainably. These pressures are particularly acute in Australia's fastest growing peri-urban regions. Despite efforts to contain and consolidate urban growth, pressure on the peri-urban interface remains a key challenge. The reliance on traditional regulatory approaches to manage land use change in high growth peri-urban areas is proving to be ineffective. The use of market-based instruments (MBIs) are among the many options available to planners and policy makers to manage growth and development. Tradeable development rights (TDRs) are one type of MBI that have been used widely throughout the US to preserve open space and agricultural lands; however, their application in Australia has been limited. This paper uses a simple case study approach to review two Australian peri-urban TDR cases based on the findings of a large-scale US TDR study. The findings suggest that any attempt to implement TDR programmes in Australia should have regard for the key factors found in successful US TDR programmes. Planners also need to develop an intricate understanding of the internal and external factors that influence peri-urban areas.     

A Comparison of Bayesian Methods for Uncertainty Analysis in Hydraulic and Hydrodynamic Modeling

We evaluate and compare the performance of Bayesian Monte Carlo (BMC), Markov chain Monte Carlo (MCMC), and the Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis in hydraulic and hydrodynamic modeling (HHM) studies. The methods are evaluated in a synthetic 1D wave routing exercise based on the diffusion wave model, and in a multidimensional hydrodynamic study based on the Environmental Fluid Dynamics Code to simulate estuarine circulation processes in Weeks Bay, Alabama. Results show that BMC and MCMC provide similar estimates of uncertainty. The posterior parameter densities computed by both methods are highly consistent, as well as the calibrated parameter estimates and uncertainty bounds. Although some studies suggest that MCMC is more efficient than BMC, our results did not show a clear difference between the performance of the two methods. This seems to be due to the low number of model parameters typically involved in HHM studies, and the use of the same likelihood function. In fact, for these studies, the implementation of BMC results simpler and provides similar results to MCMC. The results of GLUE are, on the other hand, less consistent to the results of BMC and MCMC in both applications. The posterior probability densities tend to be flat and similar to the uniform priors, which can result in calibrated parameter estimates centered in the parametric space.