An Experiment in Participative Environmental Decision Making

Summary The paper presents a method of participatory decision-making involving the authorities at local level, experts and the public. It studies how to solve the problems caused by the heterogeneity of the parties taking part in the decision-making process. The method builds on mutual learning and consideration among the participants following a systematic approach led by a moderator. The method was tested at a workshop simulating a real-life situation. The test case studied at the workshop was the problem of identifying the best site for a low and intermediate level radioactive waste repository among three alternatives. The learning phase was the Krško Nuclear Power Plant cooling problem. The results show that the participants were able to reach agreement on the prioritisation of the alternatives and to end up with suprisingly complex and fully reasonable decision models. We believe that this was achieved particularly due to the well defined procedure that guided the decision-making process, and the ability of all participants to see the influence of their views on the decision model.     

Perceptual deformation induced by visual motion

The perceived position of a moving object can be misleading because the object has advanced while its previous retinal image has been transmitted through the visual stream, leading to a mismatch between actual location and its neural representation. It has been suggested that the human visual system compensates for neural processing delays to retrieve instantaneous position. However, such a mechanism would require a precise measure of the actual delay in order to provide a reliable position estimate. A novel illusory deformation of moving contours demonstrates that humans misjudge the spatial relationship between parts of coherently moving targets, and therefore do not perfectly account for neural delays. The size of this deformation increases with growing speed. In some subjects this illusion can be reversed by varying the luminance of individual dots; a manipulation that affects the neural delays. Our experiments agree with other evidence that the capacity of the visual system to compensate for processing delays is limited.     

Predicting black smoke levels from deposit gauge and SO2 data to estimate long-term exposure in the United Kingdom, 1956–1961

BackgroundIn the UK air quality has been monitored systematically since 1914, providing valuable data for studies of the long-term trends in air pollution and potentially for studies of health effects of air pollutants. There are, however, challenges in interpreting these data due to changes over time in the number and location of monitored sites, and in monitoring techniques. Particulate matter was measured as deposited matter (DM) using deposit gauge monitors until the 1950s when black smoke (BS) filters were introduced. Estimating long-term exposure to particulates using data from both deposit gauge and BS monitors requires an understanding of the relationships between DM, SO₂ and BS.AimsTo explore whether DM and/or SO₂, along with seasonal and location specific variables can be used to predict BS levels.MethodsAir quality data were abstracted from hard copies of the monthly Atmospheric Pollution Bulletins for the period April 1956–March 1961 for any sites with co-located DM, SO₂ and BS data for three or more consecutive years. The relationships between DM, SO₂, and BS were assessed using mixed models.ResultsThere were 34 eligible sites giving 1521 triplets of data. There was a consistent correlation between SO₂ and BS at all sites, but the association between DM and BS was less clear and varied by location. Mixed modelling allowing for repeat measurements at each site revealed that SO₂, year, rainfall and season of measurement explained 72% of the variability in BS levels.ConclusionsSO₂ can be used as a surrogate measure for BS in all monitoring locations. This surrogate can be improved upon by consideration of site specific characteristics, seasonal effects, rainfall and year of measurement. These findings will help in estimating historic, long-term exposure to particulates where BS or other measures are not available.     

Nachwuchsf?rderung in der ?kotoxikologie—New Blood in Ecotoxicology

Ohne Zusammenfassung     

CHEMIFOG_V – A Model to Simulate Radiation Fogs and their Interaction with Vegetation and Chemistry

Radiation fog is an important modifier of atmosphericcompounds in the planetary boundary layer. In vegetated areas effects are especially pronounced due to the enlarged surface area. Besides affectingthe lower boundary of atmospheric models fog acts as amulti-phase reaction chamber leading to acid deposition. Here we present the 1-dimensional radiation fog modelCHEMIFOG_V to simulate regional radiation fogevents. The key feature of the fog model is thedetailed microphysics, where the aerosol/dropletspectrum is describedwith a joint 2-dimensional distribution, but also thedynamics, thermodynamics, and radiative transfer are calculated. Toinvestigate the interaction between fog and the biosphere amulti-layer vegetation module, including a soil module as well as a drydeposition module were coupled. Vegetation influences thedynamics, thermodynamics, and the radiation field of the lowestatmospheric layers. With CHEMIFOG_V, numerical case studieson dry and moist deposition processes on vegetation surfaces wereperformed. Hereby multi-phase chemistry and the processing of aerosolswere considered. The results show that the chemical composition of thedeposited fog droplets is mainly determined by the aerosol composition. Dry deposition fluxes are dependent on the incoming radiation and the leaves' surface conditions with respect to water coverage.Due to chemical aerosol processing and deposition, the aerosol spectrumis significantly modified in the planetary boundary layer.