On climbing trees: an Australian perspective on sustainability and political risk>

This paper examines how political risk taking is necessary for gains in sustainability. It provides a personal perspective covering some of the key turning points in Australia (and some global examples) to demonstrate how policy innovation in sustainability will always require political leaders to go out on a limb and then in hindsight the policy will be seen as obvious and normal. The key components of sustainability (vision, interdisciplinary, geographical and sectoral synergies) are used to illustrate stories of tree climbing. Some deeper levels of sustainability applied to thinking, creativity, belonging and spirituality are then used as the framework for illustrating the significance of political risk taking for sustainability.     

Comparative statistical study of hourly precipitation determined by radar-based Stage IV and ground-based methods in the North Central United States

Detailed hourly precipitation data are required for long-range modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants using the CALPUFF model. In sparsely populated areas such as the north central United States, ground-based precipitation measurement stations may be too widely spaced to offer a complete and accurate spatial representation of hourly precipitation within a modeling domain. The availability of remotely sensed precipitation data by satellite and the National Weather Service array of next-generation radars (NEXRAD) deployed nationally provide an opportunity to improve on the paucity of data for these areas. Before adopting a new method of precipitation estimation in a modeling protocol, it should be compared with the ground-based precipitation measurements, which are currently relied upon for modeling purposes. This paper presents a statistical comparison between hourly precipitation measurements for the years 2006 through 2008 at 25 ground-based stations in the north central United States and radar-based precipitation measurements available from the National Center for Environmental Predictions (NCEP) as Stage IV data at the nearest grid cell to each selected precipitation station. It was found that the statistical agreement between the two methods depends strongly on whether the ground-based hourly precipitation is measured to within 0.1 in/hr or to within 0.01 in/hr. The results of the statistical comparison indicate that it would be more accurate to use gridded Stage IV precipitation data in a gridded dispersion model for a long-range simulation, than to rely on precipitation data interpolated between widely scattered rain gauges.

Implications:

The current reliance on ground-based rain gauges for precipitation events and hourly data for modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants results in potentially large discontinuity in data coverage and the need to extrapolate data between monitoring stations. The use of radar-based precipitation data, which is available for the entire continental United States and nearby areas, would resolve these data gaps and provide a complete and accurate spatial representation of hourly precipitation within a large modeling domain.     

Religion and environmental politics in the US House of Representatives

Does religion affect legislators’ behavior on environmental policy in the US? Studies of environmental policy making have not examined this question, although the literature suggests that religion might affect legislative behavior on environmental policy. This study examines the relationship between US House members’ religion and roll-call voting on environmental legislation from 1973 to 2009. It finds significant differences across religious traditions. Legislators’ party and characteristics of constituencies relevant to environmental politics increasingly, but not entirely, mediate these differences.     

Probability analyses of combining background concentrations with model-predicted concentrations

In order to calculate total concentrations for comparison to ambient air quality standards, monitored background concentrations are often combined with model predicted concentrations. Models have low skill in predicting the locations or time series of observed concentrations. Further, adding fixed points on the probability distributions of monitored and predicted concentrations is very conservative and not mathematically correct. Simply adding the 99th percentile predicted to the 99th percentile background will not yield the 99th percentile of the combined distributions. Instead, an appropriate distribution can be created by calculating all possible pairwise combinations of the 1-hr daily maximum observed background and daily maximum predicted concentration, from which a 99th percentile total value can be obtained. This paper reviews some techniques commonly used for determining background concentrations and combining modeled and background concentrations. The paper proposes an approach to determine the joint probabilities of occurrence of modeled and background concentrations. The pairwise combinations approach yields a more realistic prediction of total concentrations than the U.S. Environmental Protection Agency's (EPA) guidance approach and agrees with the probabilistic form of the National Ambient Air Quality Standards.

Implications: EPA's current approaches to determining background concentrations for compliance modeling purposes often lead to “double counting” of background concentrations and actual plume impacts and thus lead to overpredictions of total impacts. Further, the current Tier 1 approach of simply adding the top ends of the background and model predicted concentrations (e.g., adding the 99th percentiles of these distributions together) results in design value concentrations at probabilities in excess of the form of the National Ambient Air Quality Standards.     

Misuse of null hypothesis significance testing: would estimation of positive and negative predictive values improve certainty of chemical risk assessment?

Although generally misunderstood, the p value is the probability of the test results or more extreme results given H₀ is true: it is not the probability of H₀ being true given the results. To obtain directly useful insight about H₀, the positive predictive value (PPV) and the negative predictive value (NPV) may be useful extensions of null hypothesis significance testing (NHST). They provide information about the probability of statistically significant and non-significant test outcomes being true based on an a priori defined biologically meaningful effect size. The present study explores the utility of PPV and NPV in an ecotoxicological context by using the frequently applied Daphnia magna reproduction test (OECD guideline 211) and the chemical stressor lindane as a model system. The results indicate that especially the NPV deviates meaningfully between a test design strictly following the guideline and an experimental procedure controlling for α and β at the level of 0.05. Consequently, PPV and NPV may be useful supplements to NHST that inform the researcher about the level of confidence warranted by both statistically significant and non-significant test results. This approach also reinforces the value of considering α, β, and a biologically meaningful effect size a priori.     

Using the land transformation model to forecast vacant land

Growing or shrinking cities can experience increases in vacant land. As urban populations and boundaries fluctuate, holes can open in once tight urban areas. Many cities chase growth-oriented approaches to dealing with vacancies. It is critical to understand land-use alteration to accurately predict transformations of physical change in order to make better informed decisions about this phenomenon. This research utilizes the land transformation model (LTM), an artificial neural networking mechanism in Geographic Information Systems, to forecast vacant land. Variable influence on vacant land prediction and accuracy of the LTM is assessed by comparing input factors and patterns, using time-series data from 1990 to 2010 in Fort Worth, Texas, USA. Results indicate that the LTM can be useful in simulating vacant land-use changes but more precise mechanisms are necessary to increase accuracy. This will allow for more proactive decisions to better regulate the process of urban decline and regeneration.     

Ambient Air Monitoring for Sulfur Compounds

The role of sulfur compounds in our environment has been the subject of much speculation during the past two decades. An evaluation of the effect of man-made contributions to the biogeochemical sulfur cycle requires a comprehensive examination of source magnitudes, atmospheric concentrations and removal processes. Many voids exist in our present knowledge of these parameters despite the contributions of numerous researchers. Adequate information is needed concerning the various forms of sulfur as well as other critical constituents which exist in our biosphere so that their interrelationship and role in the mechanisms of the sulfur cycle may be more fully understood.     

The Analysis of Airborne Sulfate

This report reviews the current state of analytical methodology for sulfate in airborne particles. Methods for determination of total aerosol sulfate and total soluble sulfate are assessed. A more detailed review of the relatively new techniques for quantitative speciation of airborne sulfate then follows. Size distribution methodology and filter sampling difficulties relating to the collection of airborne sulfate-containing particles are enumerated. Experiments are suggested which use new, improved, and potentially applicable sulfate speciation techniques to obtain a better understanding of the generation, transport, transformation and removal processes that, in turn, determine the identity and concentrations of sulfate species in ambient air.