Significance of Regional Source Contributions to Urban PM-10 Concentrations

Based on data collected in St. Louis, Philadelphia and other eastern U.S. cities, we conclude that a significant fraction of the PM-10 concentration is "background." In these urban areas the background fraction ranges from 35 to 80 percent of the daily, monthly or annual concentration. The bulk of the background appears to be of regional origin. The average chemical makeup of eastern U.S. PM-10 is sulfate as SO₄, 21-34 percent; crustal material, 14-39 percent; "unknown" (carbonaceous matter, ammonium, nitrate and water), 36-51 percent, all of which is difficult to apportion to specific sources. Dispersion modeling using a local source inventory can account only for a small portion of the total PM-10 mass. Emission roll-back of local sources may have a limited effect on reducing total concentrations of PM-10.     

Potential and Shortcomings of Numerical Weather Prediction Models in Providing Meteorological Data for Urban Air Pollution Forecasting

The last decade progress in numericalweather prediction (NWP) modelling and studies of urbanatmospheric processes for providing meteorological data forurban air pollution forecasting is analysed on examples ofseveral European meteorological centres. Modern nested NWP models are utilising land-use databasesdown to 1 km resolution or finer, and are approaching thenecessary horizontal and vertical resolution suitable forcity scale. The recent scientific developments in the fieldof urban atmospheric physics and the growing availabilityof high-resolution urban surface characteristics datapromise further improvements of the capability of NWPmodels for this aim. A strategy to improve NWP data forthe urban air pollution forecasting is suggested.     

Modeling flow and nitrate fate at catchment scale in Brittany (France)

In the intensive pig-farming (Sus scrofa) area of Brittany (western France), many surface and subsurface water resources are contaminated by nitrate (NO3) with concentrations that chronically exceed the European Community 50 mg L(-1) drinking standard. To ensure sustainable water supply, the fate of NO3 must be considered in both surface water and ground water. The fate of N was investigated in a Britain catchment, the Co?t-Dan watershed, with an integrated management tool: the hydrological SWAT model coupled with the ground water model MODFLOW, and its companion contaminant and solute transport model MT3DMS. The model was validated with respect to water quantity during a 6-yr period and for the NO3 concentration during a 44-mo period, at two gauging stations in the catchment. The coupled models reproduced accurately the measurements. At the basin outlet, the Nash-Sutcliffe coefficients were 0.88 for monthly flow for the entire period and 0.87 for monthly N load. Alternative scenarios were simulated and showed potential benefits of decreasing manure application from 210 to 170 kg N ha(-1) as required by the European Commission Nitrates Directive.     

Does size matter? Comparing the party politics of climate change in Australia and Norway

ABSTRACT

The implications of state size for the party politics of climate change are examined, and in particular its effect in facilitating or impeding cross-party consensus on the issue. This issue is explored through an in-depth, qualitative comparison of Australia and Norway, which are shown to be comparable in important respects yet differ in terms of their size and climate politics. Original primary data is presented from 44 interviews with policymakers and policy-shapers in both countries, which shows that, to the limited extent that state size moderates the parties’ behaviour, it is the countries’ geographical – not economic – size that matters. Institutional factors are found to play a more significant role, however, and the corporatist features of state-business cooperation, strong ENGOs and compensatory welfare arrangements are highlighted as particularly important.     

Countryside Biogeography of Moths in a Fragmented Landscape: Biodiversity in Native and Agricultural Habitats

Abstract: Studies of fragmented landscapes, especially in the tropics, have traditionally focused on the native fragments themselves, ignoring species distributions in surrounding agricultural or other human-dominated areas. We sampled moth species richness within a 227-ha forest fragment and in four surrounding agricultural habitats (coffee, shade coffee, pasture, and mixed farms) in southern Costa Rica. We found no significant difference in moth species richness or abundance among agricultural habitats, but agricultural sites within 1 km of the forest fragment had significantly higher richness and abundance than sites farther than 3.5 km from the fragment. In addition, species composition differed significantly between distance classes ( but not among agricultural habitats), with near sites more similar to forest than far sites. These results suggest that (1) different agricultural production regimes in this region may offer similar habitat elements and thus may not differ substantially in their capacities to support native moth populations and (2) that the majority of moths may utilize both native and agricultural habitats and move frequently between them, forming "halos" of relatively high species richness and abundance around forest fragments. Correlations between species richness and the amount of nearby forest cover, measured over circles of various radii around the sites, suggest that halos extend approximately 1.0–1.4 km from the forest edge. The extent of these halos likely differs among taxa and may influence their ability to survive in fragmented landscapes.     

Determining association networks in social animals: choosing spatial–temporal criteria and sampling rates

Social Network Analysis has become an important methodological tool for advancing our understanding of human and animal group behaviour. However, researchers tend to rely on arbitrary distance and time measures when defining ‘contacts’ or ‘associations’ between individuals based on preliminary observation. Otherwise, criteria are chosen on the basis of the communication range of sensor devices (e.g. bluetooth communication ranges) or the sampling frequencies of collection devices (e.g. Global Positioning System devices). Thus, researchers lack an established protocol for determining both relevant association distances and minimum sampling rates required to accurately represent the network structure under investigation. In this paper, we demonstrate how researchers can use experimental and statistical methods to establish spatial and temporal association patterns and thus correctly characterise social networks in both time and space. To do this, we first perform a mixing experiment with Merino sheep (Ovis aries) and use a community detection algorithm that allows us to identify the spatial and temporal distance at which we can best identify clusters of previously familiar sheep. This turns out to be within 2–3 m of each other for at least 3 min. We then calculate the network graph entropy rate—a measure of ease of spreading of information (e.g. a disease) in a network—to determine the minimum sampling rate required to capture the variability observed in our sheep networks during distinct activity phases. Our results indicate the need for sampling intervals of less than a minute apart. The tools that we employ are versatile and could be applied to a wide range of species and social network datasets, thus allowing an increase in both the accuracy and efficiency of data collection when exploring spatial association patterns in gregarious species.     

Phosphorus management in Europe in a changing world

Food production in Europe is dependent on imported phosphorus (P) fertilizers, but P use is inefficient and losses to the environment high. Here, we discuss possible solutions by changes in P management. We argue that not only the use of P fertilizers and P additives in feed could be reduced by fine-tuning fertilization and feeding to actual nutrient requirements, but also P from waste has to be completely recovered and recycled in order to close the P balance of Europe regionally and become less dependent on the availability of P-rock reserves. Finally, climate-smart P management measures are needed, to reduce the expected deterioration of surface water quality resulting from climate-change-induced P loss.     

A Decision‐Analytic Approach to Managing Climate Risks: Application to the Upper Great Lakes1

Brown, Casey, William Werick, Wendy Leger, and David Fay, 2011. A Decision‐Analytic Approach to Managing Climate Risks: Application to the Upper Great Lakes. Journal of the American Water Resources Association (JAWRA) 47(3):524‐534. DOI: 10.1111/j.1752‐1688.2011.00552.x Abstract: In this paper, we present a risk analysis and management process designed for use in water resources planning and management under climate change. The process incorporates climate information through a method called decision‐scaling, whereby information related to climate projections is tailored for use in a decision‐analytic framework. The climate risk management process begins with the identification of vulnerabilities by asking stakeholders and resource experts what water conditions they could cope with and which would require substantial policy or investment shifts. The identified vulnerabilities and thresholds are formalized with a water resources systems model that relates changes in the physical climate conditions to the performance metrics corresponding to vulnerabilities. The irreducible uncertainty of climate change projections is addressed through a dynamic management plan embedded within an adaptive management process. Implementation of the process is described as applied in the ongoing International Upper Great Lakes Study.