External drift kriging of NOx concentrations with dispersion model output in a reduced air quality monitoring network

In the mid nineteen eighties the Dutch NO_x air quality monitoring network was reduced from 73 to 32 rural and city background stations, leading to higher spatial uncertainties. In this study, several other sources of information are being used to help reduce uncertainties in parameter estimation and spatial mapping. For parameter estimation, we used Bayesian inference. For mapping, we used kriging with external drift (KED) including secondary information from a dispersion model. The methods were applied to atmospheric NO_x concentrations on rural and urban scales. We compared Bayesian estimation with restricted maximum likelihood estimation and KED with universal kriging. As a reference we also included ordinary least squares (OLS). Comparison of several parameter estimation and spatial interpolation methods was done by cross-validation. Bayesian analysis resulted in an error reduction of 10 to 20% as compared to restricted maximum likelihood, whereas KED resulted in an error reduction of 50% as compared to universal kriging. Where observations were sparse, the predictions were substantially improved by inclusion of the dispersion model output and by using available prior information. No major improvement was observed as compared to OLS, the cause presumably being that much good information is contained in the dispersion model output, so that no additional spatial residual random field is required to explain the data. In all, we conclude that reduction in the monitoring network could be compensated by modern geostatistical methods, and that a traditional simple statistical model is of an almost equal quality.

Limitations in the use of potassium dichromate as a blood preservative for the analysis of organohalogenated compounds: two month results

For analysis of organochlorine contaminants in human tissue, the "gold standard" for preservation, storage, and shipping is usually freezing. However, this method can be difficult, if samples are taken in remote areas, and costly, when the samples must be shipped on dry ice. Therefore, a more simple and cost effective method of preservation is essential for remote field work. Potassium dichromate (K(2)Cr(2)O(7)) has been successfully employed in the preservation of human and cows' milk as well as chicken eggs. Our previous studies described the use of potassium dichromate for preservation of whole blood for analysis of dioxins, dibenzofurans, and PCBs. Potassium dichromate was found to successfully preserve blood at room temperature for 34 d with no significant differences in the measured concentrations of chemical contaminants or blood lipid level when compared to frozen samples. However, in a follow-up study, 3 months and 6 months of potassium dichromate preservation proved inadequate to preserve the samples for organic pollutant analysis. We noted that the lipid portion of the blood in the chemically preserved samples was declining in level or degrading, while the persistent organic pollutants remained intact at the same levels on a whole weight basis. To narrow down the window of efficacy for the use of potassium dichromate to preserve blood samples for analysis, the present study compared chemical preservation to freezing for an intermediate time period, 2 months. Similar to our previous findings at 3 and 6 months, at 2 months significant lipid degradation was observed in the chemically preserved samples. Chemically preserved samples had significantly higher levels of organochlorine contaminants (dioxins, dibenzofurans, and PCBs) when measured on a blood lipid basis but not on a wet weight basis compared to frozen samples. While 2 months of potassium dichromate preservation was not useful for obtaining accurate measure of dioxins, furans, and PCBs on a lipid basis, previous studies found this method of preservation to be useful for at least one month (Schecter, A., Pavuk, M., P?pke, O., Malisch, R., 2004. The use of potassium dichromate and ethyl alcohol as blood preservatives for analysis of organochlorine contaminants. Chemosphere 57, 1-7). However blood stored at -70 degrees C and at 22 degrees C with potassium dichromate gave similar results when expressed on a wet weight basis.     

A field study of factors influencing the concentrations of a traffic-related pollutant in the vicinity of a complex urban junction

The paper describes a field study focused on the dispersion of a traffic-related pollutant within an area close to a busy intersection between two street canyons in Central London. Simultaneous measurements of airflow, traffic flow and carbon monoxide concentrations ([CO]) are used to explore the causes of spatial variability in [CO] over a full range of background wind directions. Depending on the roof-top wind direction, evidence of both flow channelling and recirculation regimes were identified from data collected within the main canyon and the intersection. However, at the intersection, the merging of channelled flows from the canyons increased the flow complexity and turbulence intensity. These features, coupled with the close proximity of nearby queuing traffic in several directions, led to the highest overall time-average measured [CO] occurring at the intersection. Within the main street canyon, the data supported the presence of a helical flow regime for oblique roof-top flows, leading to increased [CO] on the canyon leeward side. Predominant wind directions led to some locations having significantly higher diurnal average [CO] due to being mostly on the canyon leeward side during the study period. For all locations, small changes in the background wind direction could cause large changes in the in-street mean wind angle and local turbulence intensity, implying that dispersion mechanisms would be highly sensitive to small changes in above roof flows. During peak traffic flow periods, concentrations within parallel side streets were approximately four times lower than within the main canyon and intersection which has implications for controlling personal exposure. Overall, the results illustrate that pollutant concentrations can be highly spatially variable over even short distances within complex urban geometries, and that synoptic wind patterns, traffic queue location and building topologies all play a role in determining where pollutant hot spots occur.     

How changes in job demands and resources predict burnout,work engagement,and sickness absenteeism

The present longitudinal survey among 201 telecom managers supports the Job Demands‐Resources (JD‐R) model that postulates a health impairment process and a motivational process. As hypothesized, results of structural equation modeling analyses revealed that: (1) increases in job demands (i.e., overload, emotional demands, and work‐home interference) and decreases in job resources (i.e., social support, autonomy, opportunities to learn, and feedback) predict burnout, (2) increases in job resources predict work engagement, and (3) burnout (positively) and engagement (negatively) predict registered sickness duration (“involuntary” absence) and frequency (“involuntary” absence), respectively. Finally, consistent with predictions results suggest a positive gain spiral: initial work engagement predicts an increase in job resources, which, in its turn, further increases work engagement. Copyright © 2009 John Wiley & Sons, Ltd.     

Development and Comparison of Multiple Regression Models to Predict Bankfull Channel Dimensions for Use in Hydrologic Models

Channel dimensions are important input variables for many hydrologic models. As measurements of channel geometry are not available in most watersheds, they are often predicted using bankfull hydraulic geometry relationships. This study aims at improving existing equations that relate bankfull width, depth, and cross‐sectional area to drainage area (DA) without limiting their use to well‐gauged watersheds. We included seven additional variables in the equations that can be derived from data that are generally required by hydrologic models anyway and conducted several multiple regression analyses to identify the ideal combination of additional variables for nationwide and regional models for each Physiographic Division of the United States (U.S.). Results indicate that including the additional variables in the regression equations generally improves predictions considerably. The selection of relevant variables varies by Physiographic Division, but average annual precipitation (PCP) and temperature (TMP) were generally found to improve the models the most. Therefore, we recommend using regression equations with three independent variables (DA, PCP, and TMP) to predict bankfull channel dimensions for hydrologic models. Furthermore, we recommend using the regional equations for watersheds within regions from which data were used for model development, whereas in all other parts of the U.S. and the rest of the world, the nationwide equations should be given preference.     

Evaluation by policy makers of a procedure to describe perceived landscape openness

In the last decade policy makers have increasingly recognized the need to include people's perceptions in methods for describing landscape quality. At the same time, a third wave of Geographic Information Systems (GIS) has become available that make it technically possible to model landscape quality in a realistic manner. However, as there is often a mismatch between science and policy, it remains unclear to what extent perception-based models developed by scientists can be useful to policy makers. The aim of the present study was to evaluate the usefulness to policy making of a GIS-based procedure for describing perceived landscape openness. To this end, a workshop was organized which was attended by eight Dutch policy makers who acted as representatives of their province (region). The Group Decision Room (GDR) technique was used to elicit the policy makers' evaluations of the procedure in an anonymous and reliable manner. The procedure was presented to the policy makers using cases from their own province, which they assessed using a mixture of qualitative and quantitative methods. The results show that policy makers rated the procedure as being highly relevant to policy making, scientifically credible, usable by policy makers and feasible to implement in the policy making process. They especially appreciated the flexibility and transparency of the procedure. The policy makers concluded that the procedure would be of most value for monitoring landscape changes and for analysing impacts on landscape openness in land use scenario studies. However, they requested guidelines for proper implementation of the various options in the procedure. In general, the current study shows that explicit and transparent evaluation of the usefulness of GIS-based tools can aid integration at the science-policy interface and help to ensure that both scientists and policy makers are informed of interrelated options and requirements.     

Assessment of Jatropha curcas L. biodiesel seed cake toxicity using the zebrafish (Danio rerio) embryo toxicity (ZFET) test

Consequent to the growing demand for alternative sources of energy, the seeds from Jatropha curcas remain to be the favorite for biodiesel production. However, a significant volume of the residual organic mass (seed cake) is produced during the extraction process, which raises concerns on safe waste disposal. In the present study, we assessed the toxicity of J. curcas seed cake using the zebrafish (Danio rerio) embryotoxicity test. Within 1-h post-fertilization (hpf), the fertilized eggs were exposed to five mass concentrations of J. curcas seed cake and were followed through 24, 48, and 72 hpf. Toxicity was evaluated based on lethal endpoints induced on zebrafish embryos namely egg coagulation, non-formation of somites, and non-detachment of tail. The lowest concentration tested, 1 g/L, was not able to elicit toxicity on embryos whereas 100 % mortality (based also on lethal endpoints) was recorded at the highest concentration at 2.15 g/L. The computed LC50 for the J. curcas seed cake was 1.61 g/L. No further increase in mortality was observed in the succeeding time points (48 and 72 hpf) indicating that J. curcas seed cake exerted acute toxicity on zebrafish embryos. Sublethal endpoints (yolk sac and pericardial edema) were noted at 72 hpf in zebrafish embryos exposed to higher concentrations. The observed lethal endpoints induced on zebrafish embryos were discussed in relation to the active principles, notably, phorbol esters that have remained in the seed cake even after extraction.     

Uranium contents in plants and mushrooms grown on a uranium-contaminated site near Ronneburg in Eastern Thuringia/Germany

Uranium concentrations in cultivated (sunflower, sunchoke, potato) and native plants, plant compartment specimens, and mushrooms, grown on a test site within a uranium-contaminated area in Eastern Thuringia, were analyzed and compared. This test site belongs to the Friedrich-Schiller University Jena and is situated on the ground of a former but now removed uranium mine waste leaching heap. For determination of the U concentrations in the biomaterials, the saps of the samples were squeezed out by using an ultracentrifuge, after that, the uranium concentrations in the saps and the remaining residue were measured, using ICP-MS. The study further showed that uranium concentrations observed in plant compartment and mushroom fruiting bodies sap samples were always higher than their associated solid residue sample. Also, it was found that the detected uranium concentration in the root samples were always higher than were observed in their associated above ground biomass, e.g., in shoots, leaves, blossoms etc. The highest uranium concentration was measured with almost 40 ppb U in a fruiting body of a mushroom and in roots of butterbur. However, the detected uranium concentrations in plants and mushrooms collected in this study were always lower than in the associated surface and soil water of the test site, indicating that under the encountered natural conditions, none of the studied plant and mushroom species turned out to be a hyperaccumulator for uranium, which could have extracted uranium in sufficient amounts out of the uranium-contaminated soil. In addition, it was found that the detected uranium concentrations in the sap samples, despite being above the sensitivity limit, proved to be too low—in combination with the presence of fluorescence quenching substances, e.g., iron and manganese ions, and/or organic quenchers—to extract a useful fluorescence signal, which could have helped to identify the uranium speciation in plants.     

Incinerator Conference Covers Emissions Control Aspects

The success of the application of computer modeling to decision-making will depend on the degree to which the scientifically valid “cause-and-effect” features of the air pollution system are represented. For this reason, dynamic simulation models are to be preferred to statistical and empirical models. A digital simulation model based on a stoichiometrically logical chemical mechanism and trajectory estimating routines was constructed, using Los Angeles source, meteorological and geographic input. The basic physical concept underlying the simulation model is the process of evolution of photochemical pollution in a parcel of air as it moves in a dynamic urban emission/meteorological environment along a given urban wind trajectory. Both the photochemical evolution and the trajectory are numerically integrated by a standard linear multistep predictor-corrector method. Concentrations of photochemical reactants and products (i.e., primary and secondary contaminants) are determined by this numerical integration, which also includes appropriate terms for relevant effects. In five preliminary validation runs, simulated NO₂, NO, and O₃ values were within 20% or 0.05 ppm of those observed at air monitoring stations located near the termini of the runs. The trajectories were plotted on the basis of hourly meteorological data for 22 stations. Six control strategy exercises were conducted to illustrate the application of the model to problem-solving situations.