An efficient and simple method for measuring (226)Ra using the scintillation cell in a delayed coincidence counting system (RaDeCC)

A delayed coincidence counter (RaDeCC), developed to determine ultra-low levels of (223)Ra (half life = 11.1 days) and (224)Ra (half life = 3.6 days) in seawater, was adapted to measure (226)Ra (half life = 1622 years). After pre-concentration of Ra from seawater onto MnO(2)-coated fiber we show in this study that the (226)Ra activity can be determined using the RaDeCC's ability to record alpha decay of its daughters as total counts. For sufficient ingrowth of (222)Rn, the Mn-fiber is hermetically sealed in a column for a few days. Then, the ingrown (222)Rn is circulated through the RaDeCC air-loop system followed by shutting down of the pump and closure of the scintillation cell for equilibration. Counting may be completed within a few hours for seawater samples. Sample measurements with this method agreed well with data obtained using gamma-ray spectrometry. This proves that a set of Ra isotopes ((223)Ra, (224)Ra, and (226)Ra), commonly used for geophysical studies such as mixing rates of different water masses and submarine groundwater discharge, can be efficiently and rapidly measured using the RaDeCC.     

Simulating a natural fire regime on an Atlantic coast barrier island complex in Florida, USA

The HFire fire regime model was used to simulate the natural fire regime (prior to European settlement) on Kennedy Space Center, Merritt Island National Wildlife Refuge, Canaveral National Seashore, and Cape Canaveral Air Force Station, Florida. Model simulations were run for 500 years and the model was parameterized using information generated from previously published empirical studies on these properties (e.g., lightning fire ignition frequencies and ignition seasonality). A mosaic pattern of frequent small fires dominated this fire regime with rare but extremely large fires occurring during dry La Niña periods. This simulated fire size distribution very closely matched the previously published fire size distribution for lightning ignitions on these properties. A sensitivity analysis was performed to establish which parameters were most influential and the range of variation surrounding empirically parameterized model output. Dead fuel moisture and wind speed had the largest influence on model outcome. A wide range of variance was observed surrounding the composite simulation with the least being 6% in total burn frequency and the greatest being 49% in total area burned. Because simulation modeling is the best option for fire regime reconstruction in many rapidly growing shrub dominated systems, these results will be of interest to scientists and fire managers for delineating the natural fire regime on these properties, the southeastern United States and other fire adapted shrub systems worldwide.     

Predicting Water Quality Impaired Stream Segments using Landscape-Scale Data and a Regional Geostatistical Model: A Case Study in Maryland

In the United States, probability-based water quality surveys are typically used to meet the requirements of Section 305(b) of the Clean Water Act. The survey design allows an inference to be generated concerning regional stream condition, but it cannot be used to identify water quality impaired stream segments. Therefore, a rapid and cost-efficient method is needed to locate potentially impaired stream segments throughout large areas. We fit a set of geostatistical models to 312 samples of dissolved organic carbon (DOC) collected in 1996 for the Maryland Biological Stream Survey using coarse-scale watershed characteristics. The models were developed using two distance measures, straight-line distance (SLD) and weighted asymmetric hydrologic distance (WAHD). We used the Corrected Spatial Akaike Information Criterion and the mean square prediction error to compare models. The SLD models predicted more variability in DOC than models based on WAHD for every autocovariance model except the spherical model. The SLD model based on the Mariah autocovariance model showed the best fit (r² = 0.72). DOC demonstrated a positive relationship with the watershed attributes percent water, percent wetlands, and mean minimum temperature, but was negatively correlated to percent felsic rock type. We used universal kriging to generate predictions and prediction variances for 3083 stream segments throughout Maryland. The model predicted that 90.2% of stream kilometers had DOC values less than 5 mg/l, 6.7% were between 5 and 8 mg/l, and 3.1% of streams produced values greater than 8 mg/l. The geostatistical model generated more accurate DOC predictions than previous models, but did not fit the data equally well throughout the state. Consequently, it may be necessary to develop more than one geostatistical model to predict stream DOC throughout Maryland. Our methodology is an improvement over previous methods because additional field sampling is not necessary, inferences about regional stream condition can be made, and it can be used to locate potentially impaired stream segments. Further, the model results can be displayed visually, which allows results to be presented to a wide variety of audiences easily.     

Benthic algal production across lake size gradients: interactions among morphometry, nutrients, and light

Attached algae play a minor role in conceptual and empirical models of lake ecosystem function but paradoxically form the energetic base of food webs that support a wide variety of fishes. To explore the apparent mismatch between perceived limits on contributions of periphyton to whole-lake primary production and its importance to consumers, we modeled the contribution of periphyton to whole-ecosystem primary production across lake size, shape, and nutrient gradients. The distribution of available benthic habitat for periphyton is influenced by the ratio of mean depth to maximum depth (DR = z/ z(max)). We modeled total phytoplankton production from water-column nutrient availability, z, and light. Periphyton production was a function of light-saturated photosynthesis (BPmax) and light availability at depth. The model demonstrated that depth ratio (DR) and light attenuation strongly determined the maximum possible contribution of benthic algae to lake production, and the benthic proportion of whole-lake primary production (BPf) declined with increasing nutrients. Shallow lakes (z < or =5 m) were insensitive to DR and were dominated by either benthic or pelagic primary productivity depending on trophic status. Moderately deep oligotrophic lakes had substantial contributions by benthic primary productivity at low depth ratios and when maximum benthic photosynthesis was moderate or high. Extremely large, deep lakes always had low fractional contributions of benthic primary production. An analysis of the world's largest lakes showed that the shapes of natural lakes shift increasingly toward lower depth ratios with increasing depth, maximizing the potential importance of littoral primary production in large-lake food webs. The repeatedly demonstrated importance of periphyton to lake food webs may reflect the combination of low depth ratios and high light penetration characteristic of large, oligotrophic lakes that in turn lead to substantial contributions of periphyton to autochthonous production.     

Entscheidungsanalytische Simulation formalisierter Umweltmediationsabläufe

Goal and Scope

During the last 10 years environmental mediation has become a popular instrument in Germany to solve environmental conflicts. Environmental mediation is a voluntary negotiation process that is supported by a neutral third person and in which those involved in a conflict jointly search for solutions that are acceptable to all. The simulation of mediation processes can be used to determine the main factors that influence the progression of the conflict and to assess the potential and limits of environmental mediation.

Methods

In this article a decision-theoretical, dynamic model is discussed which is used to simulate a formalized mediation process. It covers, over and above the standard assumptions, the role of emotions. They are the missing link between a state of conflict, and rational, utility maximizing behavior as it is postulated in standard economics.

Results and Conclusions

With this model, the effects of several different parameter sets have been tested. Here, the willingness of the parties to negotiate and to agree to a compromise solution is discussed as well as the role of the integrated emotions which are envy and anger.

Outlook

Due to the large amount of data produced by the model, the evaluation has so far mainly focused on the results of the mediation process. For future research, a more detailed analysis of the simulation runs as well as experiments can help to make the model more realistic.     

Growth response of bigcone Douglas fir (Pseudotsuga macrocarpa) to long-term ozone exposure in southern California

Long-term radial growth of bigcone Douglas fir (Pseudotsuga macrocarpa) was studied throughout its range in the San Bernardino Mountains of southern California, where ambient ozone has been high for approximately the past 40 years. A gradient of both ozone concentration and precipitation exists from west (high) to east (low). Growth rates of bigcone Douglas fir are considerably lower since 1950 throughout the San Bernardino Mountains, with the largest growth reductions in the western part of the range where ozone exposure is highest. Needle retention is also somewhat lower at high ozone sites. Lower annual precipitation since 1950 may have some impact on long-term growth reductions, and short-term growth reductions induced by drought are an important component of long-term growth reductions at sites with high ozone exposure. An ozone-climate stress complex may be responsible for recent reductions in the growth of bigcone Douglas fir.     

Validation of a test method for the measurement of methanol emissions from stationary sources

Title III of the 1990 Clean Air Act Amendments designated methanol as a pollutant to be regulated. The U.S. Environmental Protection Agency (EPA), through a contract with Research Triangle Institute, has developed a method for measuring methanol emissions from stationary sources. The methanol sampling train (MST) consists of a glass-lined heated probe, two condensate knockout traps, and three sorbent cartridges packed with Anasorb 747. Samples are desorbed with a 1:1 mixture of carbon disulfide (CS2) and N,N-dimethylformamide (DMF). Condensate water and CS2/ DMF samples are analyzed by gas chromatography with flame ionization detection. The MST has a practical quantitation limit of approximately 3 ppm for a 20-L sample. Samples were shown to be stable for at least two weeks after collection. Field tests of the MST and the National Council of the Paper Industry for Air and Stream Improvement (NCASI) methanol sampling method were conducted at two pulp and paper mills. Sampling and analysis procedures followed EPA Method 301 requirements. The sampling location for the first field test was the inlet vent to a softwood bleach plant scrubber, where the methanol concentration was approximately 30 ppm. The mean recovery of spike was 108.3% for the MST method and 81.6% for the NCASI method. Although neither method showed significant bias at the 95% confidence level, the between-methods bias was significantly different. A second field test was conducted at a vent from a black liquor oxidation tank where the methanol concentration was approximately 350 ppm. Mean spike recoveries were 96.6 and 94.2% for the MST and NCASI methods, respectively. The biases of the two methods and the between-methods bias were not significantly different for the second field test.