Environmental monitoring of historical change in arsenic deposition with tree bark pockets

ICP-MS analysis recorded historical change (c. 1846 to 2002) in the arsenic concentration of bark included within the trunks (tree bark pockets) of two Japanese oak trees (Quercus crispula), collected at an elevated location approximately 10 km from the Ashio copper mine and smelter, Japan. The arsenic concentration of the bark pockets was 0.016 +/- 0.003 microg cm(-2) c. 1846 (n = 5) and rose 50-fold from c. 1875 to c. 1925, from approximately 0.01 to 0.5 microg cm(-2). The rise coincided with increased copper production in Ashio from local sulfide ores, from 46 tons per year in 1877 to 16,500 tons per year in 1929. Following a decline in arsenic concentration and copper production, in particular during the Second World War, a second peak was observed c. 1970, corresponding to high levels of production from both local (6,000 tons per year) and imported (30,000 tons per year) ores, smelted from 1954. Compared to the local ores, the contribution of arsenic from imported ores appeared relatively low. Arsenic concentrations declined from c. 1970 to the present following the closure of the mine in 1974 and smelter in 1989, recording 0.058 +/- 0.040 microg cm(-2) arsenic (n = 5) in surface bark collected in 2002. The coincident trends in arsenic concentration and copper production indicated that the bark pockets provided an effective record of historical change in atmospheric arsenic deposition.     

The application of HPLC-F and GC-MS to the analysis of selected hydroxy polycyclic hydrocarbons in two certified fish bile reference materials

Four selected hydroxy polycyclic aromatic hydrocarbons (OH-PAHs), 2-hydroxy-naphthalene (2-OH-NPH), 1-hydroxy-phenanthrene (1-OH-PHE), 1-hydroxy-pyrene (1-OH-PYR) and 3-hydroxy-benzo[a]pyrene (3-OH-BaP) have been analysed in two certified fish bile reference materials (CRMs) for exposure monitoring of PAHs in the aquatic environment. The two materials, BCR 720 and BCR 721, consist of bile from fish exposed to contaminated sediment and dispersed crude oil, respectively. Both bile samples have been analysed by two different analytical techniques, gas chromatography-mass spectrometry (GC-MS) and high performance liquid chromatography-fluorescence detection (HPLC-F), and the separation performance, detection limits, recoveries and reproducibility for the four target compounds were evaluated. HPLC-F requires a simple sample preparation and the separation capacity is adequate for quantification of 1-OH-PYR and 3-OH-BaP. Detection limits are excellent for 1-OH-PYR (6 pg injected) and 3-OH-BaP (3 pg injected) and generally improved with increasing molecular size. Recoveries ranged from 48 to 99% for the four selected compounds, depending on compound and concentration. Sample preparation prior to GC-MS analysis was more demanding, as reflected by the obtained recoveries for 2-OH-NPH, 1-OH-PHE and 1-OH-PYR (35 to 61%). The sensitivity improved with decreasing molecular size, 2-OH-NPH (1.2 pg injected), 1-OH-PHE (2.4 pg injected) and 1-OH-PYR (6 pg injected). Because of the superior separation power of GC and the extra selectivity of MS detection, GC-MS was the method of choice for the determination of 2-OH-NPH and 1-OH-PHE in both CRMs. In fish bile samples these two compounds are more likely to suffer from chromatographic overlap, and HPLC-F was not sufficiently selective. Determination of 1-OH-PYR was performed with success by both methods, but HPLC-F would be preferred because of the simpler and less time-consuming sample preparation. Detectable concentrations of 3-OH-BaP were present in BCR 720 and could only be determined by HPLC-F. The present work aims to present HPLC-F and GC-MS as complementary methods for the quantitative analysis of OH-PAHs in fish bile.     

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.     

Further studies using X-ray fluorescence to sample lead contaminated carpeted surfaces

The sampling of carpeted surfaces to test for lead contamination primarily focuses upon vacuum techniques. Vacuum sampling techniques, however, require time-consuming, expensive laboratory analysis of the dusts obtained and are unable to determine total lead load on the carpet. X-ray fluorescence (XRF) analysis is an on-site, inexpensive, non-destructive, quick technique for predicting metals levels in a variety of media, such as water, soil, filter paper and painted surfaces. A 1992 study of the feasibility of XRF to analyze for lead and soil loadings on carpeted surfaces indicated that XRF can detect lead at a low enough level to warrant further study. This paper expands this earlier study and developes lead and soil loading calibration curves for three different carpet types based upon XRF lead L-beta peak areas and XRF iron and barium K-alpha peak and background areas. Results indicate that variation in the data can be reduced through modifications of the XRF analysis technique, thus reducing the statistically determined detection level, and that carpet type does affect the calibration. Detection levels of approximately 70 mg/m² for lead and 5 g/m² for soil were obtained. Overall, good agreement was found between results of this study and the earlier one. XRF shows excellent potential for quantitative analysis of lead on carpeted surfaces.     

Matrix diffusion effects in the cleanup of heterogeneous aquifers

Simple mathematical models are developed to account for the rather slow mass transport of nonaqueous phase liquid (NAPL) into aqueous solution in groundwater during flushing operations. The models are based on the assumption that this bottleneck in the process is associated with diffusion in the aqueous phase in the porous medium from the location of the NAPL drops/ganglia in a region of relatively low permeability out into a region of substantially higher permeability, somewhat analogous to diffusion from a block of porous rock into a nearby fracture, where the fracture system overwhelmingly dominates the overall permeability. The models include batch flushing, flushing in a laboratory column, and a one-dimensional model for flushing by means of a single recovery well.     

Assessing land use impacts on flood processes in complex terrain by using GIS and modeling approach

A distributed hydrologic modeling and GIS approach is applied for the assessment of land use impact in the Steinsel sub-basin, Alzette, Grand-Duchy of Luxembourg. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results show that the direct runoff from urban areas is dominant for a flood event compared with runoff from other land use areas in this catchment, and tends to increase for small floods and for the dry season floods, whereas the interflow from forested, pasture and agricultural field areas contributes to the recession flow. Significant variations in flood volume, peak discharge, time to the peak, etc., are found from the model simulation based on the three hypothetical land use change scenarios.     

Optimizing the removal of small fish passage barriers

Removing small artificial barriers that hinder upstream migrations of fish is a major problem in riparian habitat restoration. Because of budgetary limitations, it is necessary to prioritize barrier removal and repair decisions. These have usually been based on scoring and ranking procedures, which, although simple to use, can be very inefficient in terms of increasing the amount of accessible instream habitat. We develop a novel decision-making approach, based on integer programming techniques, which optimizes repair and removal decisions. Results show based on real datasets of barrier culverts located in Washington State that scoring and ranking is over 25% below the optimum on average and a full 100% below in the worst case, producing no net habitat gain whatsoever. This is compared to a dynamic programming method that was able to find optimal solutions in less than a second, even for problems with up to several hundred variables, and a heuristic method, which found solutions with less than a 1% average optimality gap in even less time.     

Application of a checklist for quality assistance in environmental modelling to an energy model

Large, complex energy models present considerable challenges to develop and test. Uncertainty assessments of such models provide only partial guidance on the quality of the results. We have developed a model quality assistance checklist to aid in this purpose. The model checklist provides diagnostic output in the form of a set of pitfalls for the model application. The checklist is applied here to an energy model for the problem of assessing energy use and greenhouse gas emissions. Use of the checklist suggests that results on this issue are contingent on a number of assumptions that are highly value-laden. When these assumptions are held fixed, the model is deemed capable of producing moderately robust results of relevance to climate policy over the longer term. Checklist responses also indicate that a number of details critical to policy choices or outcomes on this issue are not captured in the model, and model results should therefore be supplemented with alternative analyses.     

Using environmental stressor information to predict the ecological status of Maryland non-tidal streams as measured by biological indicators

In Maryland, U.S., an interim framework has recentlybeen developed for using biologically based thresholds, or `biocriteria', to assess the health of nontidal streams statewide at watershed scales. The evaluation of impairment is based on indices of biological integrity from the Maryland Biological Stream Survey (MBSS). We applied logistic regression to quantify how the biotic integrity of streams at a local scale is affected by cumulative effects resulting from catchment land uses, point sources, and nearby transmission line rights-of-way. Indicators for land use were developed from the remote sensing National Land Cover Data and applied at different scales. We determined that the risk of local impairment in nontidal streams rapidly increases with increased urban land use in the catchment area. The average likelihood of failing biocriteria doubled with every 10% points increment in urban land, thus an increase in urban land use from 0 to 20% quadruples the risk of impairment. For the basins evaluated in this study, catchments with more than 40–50% urban land use had greater than 80% probability of failing biocriteria, on average. Inclusion of rights-of-way and point sources in the model did not significantly improve the fit for this data set, most likely because of their low numbers. The overall results indicate that our predictive modeling approach can help pinpoint stream ecosystems experiencing or vulnerable to degradation.     

Characterization of microbial communities from coastal waters using microarrays

Molecular methods, including DNA probes, were used to identify and enumerate pathogenic Vibrio species in the Chesapeake Bay; our data indicated that Vibrio vulnificus exhibits seasonal fluctuations in number. Our work included a characterization of total microbial communities from the Bay; development of microarrays that identify and quantify the diversity of those communities; and observation of temporal changes in those communities. To identify members of the microbial community, we amplified the 16S rDNA gene from community DNA isolated from a biofilm sample collected from the Chesapeake Bay in February, 2000. The resultant 75 sequences were 95% or more similar to 7 species including two recently described Shewanella species, baltica and frigidimarina, that have not been previously isolated from the Chesapeake. When the genera of bacteria from biofilm after culturing are compared to those detected by subcloning amplified 16S fragments from community DNA, the cultured sample exhibited a strong bias. In oysters collected in February, the most common bacteria were previously unknown. Based on our 16S findings, we are developing microarrays to detect these and other microbial species in these estuarine communities. The microarrays will detect each species using four distinct loci, with the multiple loci serving as an internal control. The accuracy of the microarray will be measured using sentinel species such as Aeromonas species, Escherichia coli, and Vibrio vulnificus. Using microarrays, it should be possible to determine the annual fluctuations of bacterial species (culturable and non-culturable, pathogenic and non-pathogenic). The data may be applied to understanding patterns of environmental change; assessing the health of the Bay; and evaluating the risk of human illness associated with exposure to and ingestion of water and shellfish.