Land use regression model for ultrafine particles in Amsterdam

There are currently no epidemiological studies on health effects of long-term exposure to ultrafine particles (UFP), largely because data on spatial exposure contrasts for UFP is lacking. The objective of this study was to develop a land use regression (LUR) model for UFP in the city of Amsterdam. Total particle number concentrations (PNC), PM10, PM2.5, and its soot content were measured directly outside 50 homes spread over the city of Amsterdam. Each home was measured during one week. Continuous measurements at a central urban background site were used to adjust the average concentration for temporal variation. Predictor variables (traffic, address density, land use) were obtained using geographic information systems. A model including the product of traffic intensity and the inverse distance to the nearest road squared, address density, and location near the port explained 67% of the variability in measured PNC. LUR models for PM2.5, soot, and coarse particles (PM10, PM2.5) explained 57%, 76%, and 37% of the variability in measured concentrations. Predictions from the PNC model correlated highly with predictions from LUR models for PM2.5, soot, and coarse particles. A LUR model for PNC has been developed, with similar validity as previous models for more commonly measured pollutants.     

Evaluation of factors associated with immunoglobulin G,fat, protein,and lactose concentrations in bovine colostrum and colostrum management practices in grassland-based dairy systems in Northern Ireland

The objectives of this study were to investigate colostrum feeding practices and colostrum quality on commercial grassland-based dairy farms, and to identify factors associated with colostrum quality that could help inform the development of colostrum management protocols. Over 1 yr, background information associated with dairy calvings and colostrum management practices were recorded on 21 commercial dairy farms. Colostrum samples (n = 1,239) were analyzed for fat, protein, lactose, and IgG concentration. A subset was analyzed for somatic cell count and total viable bacteria count. Factors associated with nutritional and IgG concentrations were determined using both univariate and multivariate models. This study found that 51% of calves were administered their first feed of colostrum via esophageal tube, and the majority of calves (80%) were fed >2 L of colostrum at their first feed (mean = 2.9 L, SD = 0.79), at a mean time of 3.2 h (SD 4.36) after birth, but this ranged across farms. The mean colostral fat, protein, and lactose percentages and IgG concentrations were 6.4%, 14%, 2.7%, and 55 mg/mL, respectively. The mean somatic cell count and total viable count were 6.3 log₁₀ and 6.1 log₁₀, respectively. Overall, 44% of colostrum samples contained <50 mg/mL IgG, and almost 81% were in excess of industry guidelines (<100,000 cfu/mL) for bacterial contamination. In the multivariate model, IgG concentration was associated with parity and time from parturition to colostrum collection. The nutritional properties of colostrum were associated with parity, prepartum vaccination, season of calving, and dry cow nutrition. The large variation in colostrum quality found in the current study highlights the importance of routine colostrum testing, and now that factors associated with lower-quality colostrum on grassland-based dairy farms have been identified, producers and advisers are better informed and able to develop risk-based colostrum management protocols.     

Adsorption, desorption and isotopic exchange of cadmium on illite: evidence for complete reversibility

Adsorption, desorption and isotopic exchange of Cd on illite clay have been studied at low Cd concentrations and low ionic strength. The results indicate that under the conditions of the experiments Cd sorption on illite is completely reversible. Long equilibration times (7–8 weeks) were shown to be essential because of slow desorption kinetics.     

Mercury in the Arctic atmosphere: an analysis of eight years of measurements of GEM at Alert (Canada) and a comparison with observations at Amderma (Russia) and Kuujjuarapik (Canada)

Eight years of gaseous elemental mercury (GEM) concentration measurements from Alert, Nunavut, Canada (between 1995 and 2002) is presented. The annual time series shows a distinct repeating seasonal pattern with an overall annual median concentration for this time period of 1.58 (S.D.=0.04 ng m(-3)). Strong seasonal variation was observed throughout the years with springtime displaying strong variability in the GEM and overall lower median concentrations due to the so-called mercury depletion events (MDEs). Summer concentrations are higher than the annual average and show a decrease in variability. Fall and winter concentrations are distributed around the annual median concentrations and show little variability. The relationship between the springtime depression and the summer increase shows a change in the behaviour of mercury between 1995 and 2002. Preliminary results suggest that during this period an increasing amount of the mercury lost from the atmosphere in the spring is not returned to atmosphere in summer. A comparison of GEM concentration data from three sites--Alert (Canada), Amderma (Russia) and Kuujjuarapik (Canada)--demonstrated similar monthly distribution of GEM between Alert and Amderma, with the latter not showing as high summer concentrations. Monthly distribution of GEM at Kuujjuarapik varied considerably from the other two sites. MDEs were found to occur at each site in the spring yet displayed different characteristics. MDEs appear to start at Alert shortly after polar sunrise but in Amderma their initiation is delayed approximately 2 months following polar sunrise. MDEs occur in Kuujjuarapik in the springtime despite an incomplete development of the polar day-night cycle. In spring, as soon as air temperature attained temperatures consistently above 0 degrees C, MDEs ended immediately at all three sites. Continued studies into MDEs are warranted, but clearly an important component of future studies must focus on the origins of the variation of GEM behaviour at different sites.     

Mapping of background air pollution at a fine spatial scale across the European Union

Background

There is a need to understand much more about the geographic variation of air pollutants. This requires the ability to extrapolate from monitoring stations to unsampled locations. The aim was to assess methods to develop accurate and high resolution maps of background air pollution across the EU.

Methods

We compared the validity of ordinary kriging, universal kriging and regression mapping in developing EU-wide maps of air pollution on a 1 × 1 km resolution. Predictions were made for the year 2001 for nitrogen dioxide (NO₂), fine particles < 10 µm (PM₁₀), ozone (O₃), sulphur dioxide (SO₂) and carbon monoxide (CO) using routine monitoring data in Airbase. Predictor variables from EU-wide databases were land use, road traffic, population density, meteorology, altitude, topography and distance to sea. Models were developed for the global, rural and urban scale separately. The best method to model concentrations was selected on the basis of predefined performance measures (R², Root Mean Square Error (RMSE)).

Results

For NO₂, PM₁₀ and O₃ universal kriging performed better than regression mapping and ordinary kriging. Validation of the final universal kriging estimates with results from all validation sites gave R²-values and RMSE-values of 0.61 and 6.73 µg/m³ for NO₂; 0.45 and 5.19 µg/m³ for PM₁₀; and 0.70 and 7.69 µg/m³ for O₃. For SO₂ and CO none of the three methods was able to provide a satisfactory prediction.

Conclusion

Reasonable prediction models were developed for NO₂, PM₁₀ and O₃ on an EU-wide scale. Our study illustrates that it is possible to develop detailed maps of background air pollution using EU-wide databases.     

Hydrologic scaling for hydrogeomorphic floodplain mapping: Insights into human‐induced floodplain disconnectivity

Hydrogeomorphic approaches for floodplain modelling are valuable tools for water resource and flood hazard management and mapping, especially as the global availability and accuracy of terrain data increases. Digital terrain models implicitly contain information about floodplain landscape morphology that was produced by hydrologic processes over long time periods, as well as recent anthropogenic modifications to floodplain features and processes. The increased availability of terrain data and distributed hydrologic datasets provide an opportunity to develop hydrogeomorphic floodplain delineation models that can quickly be applied at large spatial scales. This research investigates the performance of a hydrogeomorphic floodplain model in two large urbanized and gauged river basins in the United States, the Susquehanna and the Wabash basins. The models were calibrated by a hydrologic data scaling technique, implemented through regression analyses of USGS peak flow data to estimate floodplain flow levels across multiple spatial scales. Floodplain model performance was assessed through comparison with 100‐year Federal Emergency Management Agency flood hazard maps. Results show that the hydrogeomorphic floodplain maps are generally consistent with standard flood maps, even when significantly and systematically varying scaling parameters within physically feasible ranges, with major differences that are likely due to infrastructure (levees, bridges, etc.) in highly urbanized areas and other locations where the geomorphic signature of fluvial processes has been altered. This study demonstrates the value of geomorphic information for large‐scale floodplain mapping and the potential use of hydrogeomorphic models for evaluating human‐made impacts to floodplain ecosystems and patterns of disconnectivity in urbanized catchments.     

Extraction of Lipids from Cereal Starches with Hot Aqueous Alcohols

Cereal starches were extracted at 100°C with various proportions of lower alcohols and water to establish optimum conditions. Lipid yields generally exceeding 90% were obtained with one two-hour extraction of maize starch at 100°C when using not less than 14 ml of 75–85% methanol, 10 ml of 75% ethanol, 12 ml of 74–78% n-propanol, 14 ml of 74–78% isopropanol, or 17 ml of 84% n-butanol per gram of starch. Similar results were obtained with wheat A-starch ( > 8 μm granule diameter), wheat B-starch ( < 8 μm granule diameter) and rice starch using n-propanol-water, and with rice starch using methanol-water. Yields decreased if the proportions of alcohol and water were not kept within well-defined limits, especially with butanol and ethanol. The preferred conditions for complete recovery of lipids were two 2-hour extractions and one 1-hour extraction at 100°C with not less than 16 ml of 75% n-propanol per gram of starch.     

Peat filter performance under changing environmental conditions

Peat is a candidate filter material for in situ treatment of urban runoff, contaminated groundwater and landfill leachates. Until now research has focused on peat sorption in batch experiments and there is a lack of knowledge on peat performance in filter beds. In this project column tests were carried out to evaluate the capacity of peat to remove As, Cd, Cu, Cr, Ni, Pb and Zn in multi-metal solution under a range of environmental conditions that may be encountered in real-life applications (draining, water stagnation, freezing, change in pH and metal concentrations, input of NaCl and elevated DOC). The removal capacity was 91–98% for Cd, Cu, Zn, Ni and Pb and the efficiency was unaffected by the changes of physical factors, but temporarily inhibited for solutions containing NaCl. Leaching of DOC from peat was detected in the initial samples and temporarily decreased metal removal. The peat filters showed high removal rates for Cd, Cu, Zn, Ni and Pb under all experimental conditions and are recommended for treatment of waters containing these elements. In contrast, peat was not found to be efficient for treatment of As and Cr in the multi-metal contaminated water at the pH range (6.7–8.0) studied.     

Dermal uptake of phthalates from clothing: Comparison of model to human participant results

In this research, we extend a model of transdermal uptake of phthalates to include a layer of clothing. When compared with experimental results, this model better estimates dermal uptake of diethylphthalate and di‐n‐butylphthalate (DnBP) than a previous model. The model predictions are consistent with the observation that previously exposed clothing can increase dermal uptake over that observed in bare‐skin participants for the same exposure air concentrations. The model predicts that dermal uptake from clothing of DnBP is a substantial fraction of total uptake from all sources of exposure. For compounds that have high dermal permeability coefficients, dermal uptake is increased for (i) thinner clothing, (ii) a narrower gap between clothing and skin, and (iii) longer time intervals between laundering and wearing. Enhanced dermal uptake is most pronounced for compounds with clothing–air partition coefficients between 10⁴ and 10⁷. In the absence of direct measurements of cotton cloth–air partition coefficients, dermal exposure may be predicted using equilibrium data for compounds in equilibrium with cellulose and water, in combination with computational methods of predicting partition coefficients.     

A practical evaluation of spectrum-based fault localization

Spectrum-based fault localization (SFL) shortens the test–diagnose–repair cycle by reducing the debugging effort. As a light-weight automated diagnosis technique it can easily be integrated with existing testing schemes. Since SFL is based on discovering statistical coincidences between system failures and the activity of the different parts of a system, its diagnostic accuracy is inherently limited. Using a common benchmark consisting of the Siemens set and the space program, we investigate this diagnostic accuracy as a function of several parameters (such as quality and quantity of the program spectra collected during the execution of the system), some of which directly relate to test design. Our results indicate that the superior performance of a particular similarity coefficient, used to analyze the program spectra, is largely independent of test design. Furthermore, near-optimal diagnostic accuracy (exonerating over 80% of the blocks of code on average) is already obtained for low-quality error observations and limited numbers of test cases. In addition to establishing these results in the controlled environment of our benchmark set, we show that SFL can effectively be applied in the context of embedded software development in an industrial environment.