Copper, zinc and cadmium in marine cage fish farm sediments: an extensive survey

The diet of cage-farmed Atlantic salmon contains a range of trace metals, some of which have toxic properties, e.g. zinc, copper and cadmium. A survey of metal concentrations (ICP-MS analysis) in surface sediments of ca. 70 stations was carried out in both May and December 2000 around a Scottish fish farm. Additionally, at 13 stations on 2 orthogonal transects centered on the farm, sediments were analysed at 1cm intervals to 8 cm depth. Maximum concentrations in surface sediments were 921, 805 and 3.5 microg g(-1) for Zn, Cu and Cd, respectively, and were found at stations near the fish farm. The calculated losses from the farm (feed input minus fish output) were 87.0%, 4.3% and 14.0% of the background-corrected inventories for Zn, Cu and Cd, respectively, indicating that for Cu and Cd at least, the feed is not the only source.     

Destruction of Aspergillus versicolor,Penicillium chrysogenum,Stachybotrys chartarum,and Cladosporium cladosporioides spores using chemical oxidation treatment process

The survival of aqueous suspensions of Penicillium chrysogenum, Stachybotrys chartarum, Aspergillus versicolor, and Cladosporium cladosporioides spores was evaluated using various combinations of hydrogen peroxide and Fe²⁺ as catalyst. Spore concentrations of 10⁶–10⁷ colony forming units per milliliter (CFU/mL) were suspended in water and treated with initial hydrogen peroxide and iron concentrations ranging from 0.05 to 10 percent and 100 to 200 ppm, respectively. After four hours of reaction time, samples were plated on agar plates, and the viable fraction of spores was determined by the number of colonies formed. Hydrogen peroxide concentrations above 50,000 ppm resulted in greater than 6‐log₁₀ reduction of viable spores for both catalyzed and noncatalyzed reactions. Iron had a strong catalytic effect when added to solutions with hydrogen peroxide concentration above 5,000 ppm and resulted in two to three orders of magnitude greater reduction compared to hydrogen peroxide alone. Additional samples taken after 24 hours of reaction time showed that the effect of the addition of 100 and 200 ppm of Fe²⁺ catalyst was mostly kinetic, and noncatalyzed hydrogen peroxide had sporicidal effects similar to catalyzed hydrogen peroxide. This study identified initial reagent concentrations of hydrogen peroxide and Fe²⁺ that accomplish a 6‐log₁₀ reduction of viable mold spores within reaction times of 4 and 24 hours. © 2007 Wiley Periodicals, Inc.     

Efficient search procedures for extreme pollutant values

Extreme pollutant values are of great interest in water quality monitoring because of their frequent toxicological significance. The principal barrier to the detection of these values, however, is the cost of extensive and comprehensive monitoring. This paper demonstrates an efficient method to determine the maximum sample measurement from a finite set of sequential samples without explicitly testing them all. It is assumed that the process of sample measurement is distinct from collection and has higher costs. It is further assumed that the measurements have high positive autocorrelation.A methodology is presented based on a common industrial testing procedure referred to as composite sampling—the physical pooling or compositing of a set of sequential samples before measurement. A method known as primary first order compositing (PFOC) was found to be superior to the traditional technique of random sampling, particularly if small composite sizes are utilized.The authors are, respectively, operations research analyst, Vancouver, B. C.; Associate Professor and Chairman, Policy Analysis Division, Faculty of Commerce and Business Administration, University of British Columbia; and Associate Professor, Management Science Division, Faculty of Commerce, U.B.C.     

Scale,context, and decision making in agricultural adaptation to climate variability and change

This work presents a framework for viewing agricultural adaptation, emphasizing the multiple spatial and temporal scales on which individuals and institutions process information on changes in their environment. The framework is offered as a means to gain perspective on the role of climate variability and change in agricultural adaptation, and developed for a case study of Australian agriculture. To study adaptation issues at the scale of individual farms we developed a simple modelling framework. The model highlights the decision making element of adaptation in light of uncertainty, and underscores the importance of decision information related to climate variability. Model results show that the assumption of perfect information for farmers systematically overpredicts adaptive performance. The results also suggest that farmers who make tactical planting decisions on the basis of historical climate information are outperformed by those who use even moderately successful seasonal forecast information. Analysis at continental scales highlights the prominent role of the decline in economic operating conditions on Australian agriculture. Examples from segments of the agricultural industry in Australia are given to illustrate the importance of appropriate scale attribution in adapting to environmental changes. In particular, adaptations oriented toward short time scale changes in the farming environment (droughts, market fluctuations) can be limited in their efficacy by constraints imposed by broad changes in the soil/water base and economic environment occuring over longer time scales. The case study also makes the point that adaptation must be defined in reference to some goal, which is ultimately a social and political exercise. Overall, this study highlights the importance of allowing more complexity (limited information, risk aversion, cross-scale interactions, mis-attribution of cause and effect, background context, identification of goals) in representing adaptation processes in climate change studies.     

Accelerated soil dissipation of tebuconazole following multiple applications to peanut

Repeated application may increase rates of pesticide dissipation in soil and reduce persistence. The potential for this to occur was investigated for the fungicide, tebuconazole (alpha-[2-(4-chlorophenyl)ethyl]-alpha-(1,1-dimethylethyl)-1H-1,2,4-triazole-1-ethanol), when used for peanut (Arachis hypogaea L.) production. Soil samples were collected from peanut plots after each of four tebuconazole applications at 2-wk intervals. Soil moisture was adjusted to field capacity as necessary and samples were incubated in the laboratory for 63 d at 30 degrees C. Untreated plot samples spiked with the compound served as controls. Results indicated accelerated dissipation in field-treated samples with the time to fifty percent dissipation (DT50) decreasing from 43 to 5 d after three tebuconazole applications. Corresponding increases in rates of accumulation and decay of degradates were also indicated. Best-fit equations (r2 = 0.84-0.98) to dissipation kinetic data combined with estimates of canopy interception rates were used to predict tebuconazole and degradates concentration in soil after each successive application. Predicted concentrations compared with values measured in surface soil samples were from twofold less to twofold greater. Use of kinetic data will likely enhance assessments of treatment efficacy and human and ecological risks from normal agronomic use of tebuconazole on peanut. However, the study indicated that varying soil conditions (in particular, soil temperature and water content) may have an equal or greater impact on field dissipation rate than development of accelerated dissipation. Results emphasize that extension of laboratory-derived kinetic data to field settings should be done with caution.     

Estimating the economic burden from illnesses associated with recreational coastal water pollution--a case study in Orange County, California

A cost-of-illness framework was applied to health and income data to quantify the health burden from illnesses associated with exposure to polluted recreational marine waters. Using data on illness severity due to exposure to polluted coastal water and estimates of mean annual salaries and medical costs (adjusted to 2001 values) for residents of Orange County, California, we estimated that the economic burden per gastrointestinal illness (GI) amounts to 36.58 dollars, the burden per acute respiratory disease is 76.76 dollars, the burden per ear ailment is 37.86 dollars, and the burden per eye ailment is 27.31 dollars. These costs can become a substantial public health burden when millions of exposures per year to polluted coastal waters result in hundreds of thousands of illnesses. For example, exposures to polluted waters at Orange County's Newport and Huntington Beaches were estimated to generate an average of 36,778 GI episodes per year. At this GI illness rate, one can also expect that approximately 38,000 more illness episodes occurred per year of other types, including respiratory, eye, and ear infections. The combination of excess illnesses associated with coastal water pollution resulted in a cumulative public health burden of 3.3 million dollars per year for these two beaches. This paper introduces a public health cost variable that can be applied in cost-benefit analyses when evaluating pollution abatement strategies.     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.