Global change impacts on the Upper Danube Catchment (Central Europe): a study of participatory modeling

Participatory modeling (PM) has become an essential concept in environmental impact assessment and planning in the field of water resources. In this paper, we focus on the use of PM to support the development of the integrated regional modeling system DANUBIA as a scientific concept to analyze the previously unknown impacts of global change, i.e., the combined effects of climate, demographic, economic, social and ecological change, on the Upper Danube Catchment (Germany). We use this case study to examine the specific conditions for PM in the field of complex integrated models on a regional scale. We describe the stepwise PM process and discuss the respective results, focusing on (1) the stakeholder dialogue’s contribution in supporting the development of new, complex modeling systems, particularly on a regional scale, (2) conditions of stakeholder involvement in issues related to the distant future, such as climate change impacts on regional water availability, and (3) limitations of PM and scientists’ motivation to carry out participatory research at all. We conclude that the PM process was not entirely successful in improving the scientific quality and practical applicability of the developed models because the process goals were manifold and overambitious, and the definition of the problem of “global change impacts on a regional scale” was too weak and uncertain to allow for a clear common objective of modelers and stakeholders. We claim that there is a lack of incentives for scientists, particularly natural scientists, to commit to PM activities.     

A bayesian network for comparing dissolved nitrogen exports from high rainfall cropping in southeastern Australia

Best management practices are often used to mitigate nutrient exports from agricultural systems. The effectiveness of these measures can vary depending on the natural attributes of the land in question (e.g., soil type, slope, and drainage class). In this paper we use a Bayesian Network to combine experiential data (expert opinion) and experimental data to compare farm-scale management for different high-rainfall cropping farms in the Hamilton region of southern Australia. In the absence of appropriate data for calibration, the network was tested against various scenarios in a predictive and in a diagnostic way. In general, the network suggests that transport factors related to total surface water (i.e., surface and near surface interflow) runoff, which are largely unrelated to Site Variables, have the biggest effect on N exports. Source factors, especially those related to fertilizer applications at planting, also appear to be important. However, the effects of fertilizer depend on when runoff occurs, and, of the major factors under management control, only the Fertilizer Rate at Sowing had a notable effect. When used in a predictive capacity, the network suggests that, compared with other scenarios, high N loads are likely when fertilizer applications at sowing and runoff coincide. In this paper we have used a Bayesian Network to describe many of the dependencies between some of the major factors affecting N exports from high rainfall cropping. This relatively simple approach has been shown to be a useful tool for comparing management practices in data-poor environments.     

Modeling thermoelectric power generation in view of climate change

In this study we investigate how thermal power plants with once-through cooling could be affected by future climate change impacts on river water temperatures and stream flow. We introduce a model of a steam turbine power plant with once-through cooling at a river site and simulate how its production could be constrained in scenarios ranging from a one degree to a five degree increase of river temperature and a 10–50% decrease of stream flow. We apply the model to simulate a large nuclear power plant in Central Europe. We calculate annual average load reductions, which can be up to 11.8%, assuming unchanged stream flow, which leads to average annual income losses of up to 80 million €. Considering simultaneous changes in stream flow will exacerbate the problem and may increase average annual costs to 111 million € in a worst-case scenario. The model demonstrates that power generation could be severely constrained by typical climate impacts, such as increasing river temperatures and decreasing stream flow.     

Real-world vehicle emissions: a summary of the Sixteenth Coordinating Research Council On-Road Vehicle Emissions Workshop

The Coordinating Research Council held its 16th workshop in March 2006, with 83 presentations describing the most recent mobile source-related emissions research. In this paper, we summarize the presentations from researchers who are engaged in improving our understanding of the contribution of mobile sources to air quality. Participants in the workshop discussed evaluation of in-use emissions control programs, effects of fuels on emissions, emission models and emission inventories, results from gas- and particle-phase emissions studies from spark-ignition and diesel-powered vehicles, and efforts to improve our capabilities in performing on-board emissions measurements, as well as topics for future research.     

Real-world vehicle emissions: a summary of the Seventeenth Coordinating Research Council On-Road Vehicle Emissions Workshop

The Coordinating Research Council, Inc. (CRC) held its 17th On-Road Vehicle Emissions Workshop in March 2007, where results of the most recent on-road vehicle emissions research were presented. We summarize ongoing work from researchers who are engaged in improving our understanding of the role and contribution of mobile sources to ambient air quality and emission inventories. Participants in the Workshop discussed efforts to improve mobile source emission models, light- and heavy-duty vehicle emissions measurements, on- and off-road emissions measurements, effects of fuels and lubricating oils on emissions, as well as emerging issues and topics for future research.