Evaluation by policy makers of a procedure to describe perceived landscape openness

In the last decade policy makers have increasingly recognized the need to include people's perceptions in methods for describing landscape quality. At the same time, a third wave of Geographic Information Systems (GIS) has become available that make it technically possible to model landscape quality in a realistic manner. However, as there is often a mismatch between science and policy, it remains unclear to what extent perception-based models developed by scientists can be useful to policy makers. The aim of the present study was to evaluate the usefulness to policy making of a GIS-based procedure for describing perceived landscape openness. To this end, a workshop was organized which was attended by eight Dutch policy makers who acted as representatives of their province (region). The Group Decision Room (GDR) technique was used to elicit the policy makers' evaluations of the procedure in an anonymous and reliable manner. The procedure was presented to the policy makers using cases from their own province, which they assessed using a mixture of qualitative and quantitative methods. The results show that policy makers rated the procedure as being highly relevant to policy making, scientifically credible, usable by policy makers and feasible to implement in the policy making process. They especially appreciated the flexibility and transparency of the procedure. The policy makers concluded that the procedure would be of most value for monitoring landscape changes and for analysing impacts on landscape openness in land use scenario studies. However, they requested guidelines for proper implementation of the various options in the procedure. In general, the current study shows that explicit and transparent evaluation of the usefulness of GIS-based tools can aid integration at the science-policy interface and help to ensure that both scientists and policy makers are informed of interrelated options and requirements.     

The Aerosol Research and Inhalation Epidemiology Study (ARIES): PM25 Mass and Aerosol Component Concentrations and Sampler Intercomparisons

ABSTRACT

The Aerosol Research and Inhalation Epidemiology Study (ARIES) was designed to provide high-quality measurements of PM₂₅, its components, and co-varying pollutants for an air pollution epidemiology study in Atlanta, GA.

Air pollution epidemiology studies have typically relied on available data on particle mass often collected using filter-based methods. Filter-based PM_2.5 sampling is susceptible to both positive and negative errors in the measurement of aerosol mass and particle-phase component concentrations in the undisturbed atmosphere. These biases are introduced by collection of gas-phase aerosol components on the filter media or by volatilization of particle phase components from collected particles. As part of the ARIES, we collected daily 24-hr PM_2.5 mass and speciation samples and continuous PM_2.5 data at a mixed residential-light industrial site in Atlanta. These data facilitate analysis of the effects of a wide variety of factors on sampler performance. We assess the relative importance of PM_2.5 components and consider associations and potential mechanistic linkages of PM_2.5 mass concentrations with several PM_2.5 components.

For the 12 months of validated data collected to date (August 1, 1998-July 31, 1999), the monthly average Federal Reference Method (FRM) PM_{2 5} mass always exceeded the proposed annual average standard (12-month average = 20.3 ± 9.5 ug/m³). The particulate SO₄ ^2- fraction (as (NH₄)₂SO₄) was largest in the summer and exceeded 50% of the FRM mass. The contribution of (NH₄)₂SO₄ to FRM PM_2.5 mass dropped to less than 30% in winter. Particu-late NO₃ ^- collected on a denuded nylon filter averaged 1.1 ± 0.9 ug/m³. Particle-phase organic compounds (as organic carbon × 1.4) measured on a denuded quartz filter sampler averaged 6.4 ± 3.1 ug/m³ (32% of FRM PM_{2 5} mass) with less seasonal variability than SO₄ ^2-.     

The dynamic nature of cognition during wayfinding

Much of our day-to-day wayfinding behaviour takes place in familiar large-scale urban environments, yet there is a dearth of studies examining how wayfinding unfolds on a second-by-second basis in this context. Here we used a retrospective verbal report protocol, eye tracking and a highly accurate virtual reality simulation of a real city (London, UK) to examine this issue. Subjects, who were taxi drivers, were able to produce extremely detailed accounts of what they had been thinking during wayfinding, which were validated by independent eye-tracking data. There was a high degree of consistency in the types of thoughts across subjects, permitting classification into a number of distinct categories. Moreover, it was possible to quantify the number of thoughts in each category, their durations and temporal order. Detailed analysis of the verbal reports provided new insights into the processes and strategies involved, and highlighted a greater range of thoughts than has previously been reported in studies of wayfinding. By analysing the temporal order of thoughts it was possible to identify specific relationships between categories. Some of these relationships were predicted by current cognitive models of wayfinding, others were novel, thus shedding new light on how navigation unfolds in a busy city.     

Tar Balls: The End State

Tar balls are frequently reported as an indicator of the extent of the impact of a spill incident. The determination of the density of tar balls is basic to the shoreline cleanup assessment team (SCAT) process, and is frequently used by the media as an indication of oil pollution. The processes involved in the evolution of tar balls are not well understood and there is a paucity of literature on the science of tar ball formation.