On June 15 2006, the World Wildlife Federation (WWF) released a report called 'Killing them Softly', which highlighted concern over the accumulation and toxic effects of persistent organic pollutants present in Arctic wildlife, particularly marine mammals such as the Polar Bear. The Times newspaper ran a full-page article summarising this report and detailed 'legacy' chemicals such as DDT and polychlorinated biphenyls (PCBs), as well as the rise in 'new' chemical contaminants such as brominated flame retardents and perfluorinated surfactants, which are also accumulating in arctic fauna and adding an additional toxic risk. The high levels of these contaminants are making animals like the Polar Bear less capable of surviving the harsh Arctic conditions and dealing with the impacts of climate change. The work in this proposal intends to examine how these chemicals are delivered to surface waters of the Arctic Ocean, and hence the base of the marine foodweb. Persistent organic pollutants reach the Arctic via long-range transport, primarily through the air from source regions in Europe, North America and Asia, but also with surface ocean currents. The cold conditions of the Arctic help to promote the accumulation of these chemicals in snow and surface waters and slows any breakdown and evaporative loss. However, the processes that remove these pollutants from the atmosphere, store them in snow and ice and then transfer them to the Arctic Ocean are poorly understood, and yet these processes may differ depending on the chemcial in question. For example, some chemicals are rather volatile (i.e. they have a tendency to evaporate), so while they can reach the Arctic and be deposited with snowfall they are unlikely to reach the ocean due to ltheir oss back to the atmosphere during the arctic summer. On the other hand, heavier, less volatile chemicals, become strongly bound to snow and particles and can be delivered to seawater during summer melt. Climate change and a warmer world are altering the Arctic and affecting pollutant pathways. For example, the number of ice-leads (large cracks in the sea-ice that give rise to 'lakes' of seawater) are increasing. As a result, the pathways that chemical pollutants take to reach ocean waters are changing and may actually be made shorter, posing an even greater threat to marine wildlife. During ice-free periods, the ocean surface water is in contact with the atmosphere (rather than capped with sea-ice) and airborne pollutants can dissolve directly into cold surface waters. Encouragingly, there is evidence that some of the 'legacy' pollutants are declining in the arctic atmosphere, but many 'modern' chemicals are actually increasing in arctic biota and work is required to measure their input and understand their behaviour in this unusual environment. For example, in sunlit surface snow following polar sunrise (24 h daylight), some of these compounds can degrade by absorbing the sunlight, and in some cases, this can give rise to more stable compounds that subsequently enter the foodchain. Therefore, the quantity of chemical pollutant that is deposited with snowfall and the chemical's fate during snowmelt are important processes to address, especially to understand the loading and impact of these pollutants on the marine ecosystem. This project aims to understand these processes, and to understand which type of pollutants and their quantities pose the greatest threat to wildlife.

By modifying the amount of solar radiation absorbed at the land surface, bright snow and dark forests have strong influences on weather and climate; either a decrease in snow cover or an increase in forest cover, which shades underlying snow, increases the absorption of radiation and warms the overlying air. Computer models for weather forecasting and climate prediction thus have to take these effects into account by calculating the changing mass of snow on the ground and interactions of radiation with forest canopies. Such models generally have coarse resolutions ranging from kilometres to hundreds of kilometres. Forest cover cannot be expected to be continuous over such large distances; instead, northern landscapes are mosaics of evergreen and deciduous forests, clearings, bogs and lakes. Snow can be removed from open areas by wind, shaded by surrounding vegetation or sublimated from forest canopies without ever reaching the ground, and these processes which influence patterns of snow cover depend on the size of the openings, the structure of the vegetation and weather conditions. Snow itself influences patterns of vegetation cover by supplying water, insulating plants and soil from cold winter temperatures and storing nutrients. The aim of this project is to develop better methods for representing interactions between snow, vegetation and the atmosphere in models that, for practical applications, cannot resolve important scales in the patterns of these interactions. We will gather information on distributions of snow, vegetation and radiation during two field experiments at sites in the arctic: one in Sweden and the other in Finland. These sites have been chosen because they have long records of weather and snow conditions, easy access, good maps of vegetation cover from satellites and aircraft and landscapes ranging from sparse deciduous forests to dense coniferous forests that are typical of much larger areas. Using 28 radiometers, and moving them several times during the course of each experiment, will allow us to measure the highly variable patterns of radiation at the snow surface in forests. Information from the field experiments will be used in developing and testing a range of models. To reach the scales of interest, we will begin with a model that explicitly resolves individual trees and work up through models with progressively coarser resolutions, testing the models at each stage against each other and in comparison with observations. The ultimate objective is a model that will be better able to make use of landscape information in predicting the absorption of radiation at the surface and the accumulation and melt of snow. We will work in close consultation with project partners at climate modelling and forecasting centres to ensure that our activities are directed towards outcomes that will meet their requirements.