Factor analysis of trace-element data from tree-bark samples in The Netherlands

Monte Carlo-assisted factor analysis has been applied to a data set of 20 trace-element concentrations in tree-bark samples obtained from 123 locations in The Netherlands, with the aim to investigate the suitability of bark as a biomonitor for air pollution. A Monte Carlo approach was used to give more insight to the uncertainties and significance levels of the factor analysis results. Notwith-standing a rather strong influence of soil material on the concentration levels, factor analysis enabled the identification of five significant pollution source types, all of which corresponded with source types found in an earlier biomonitoring study in The Netherlands using epiphytic lichens. A more detailed comparison with the lichen results showed a remarkable difference in lead concentrations between bark and lichen. It was concluded that bark can be successfully employed as a biomonitor for air pollution. The power of factor analysis to adequately determine the soil contribution may render extensive sample washing procedures superfluous.     

Ammonia uptake by plants

The paper considers the methodology and results of experimental determination of dry deposition and ammonia uptake by isolated plant leaves. Analytical expressions are proposed which allow a transition from rates obtained in an isolated chamber to dry ammonia deposition by standing crops leaves.     

Characterizing soils for hazardous waste site assessments

This paper provides a review and justification of the minimum data needed to characterize soils for hazardous waste site assessments and to comply with the Comprehensive Environmental Response, Compensation and Liability Act (CERCLA). Scientists and managers within the regulatory agency and the liable party need to know what are the important soil characteristics needed to make decisions about risk assessment, what areas need remediation and what remediation options are available. If all parties involved in characterizing a hazardous waste site can agree on the required soils data set prior to starting a site investigation, data can be collected in a more efficient and less costly manner. Having the proper data will aid in reaching decisions on how to address concerns at, and close-out, hazardous waste sites.This paper was prepared to address two specific concerns related to soil characterization for CERCLA remedial response. The first concern is the applicability of traditional soil classification methods to CERCLA soil characterization. The second is the identification of soil characterization data type required for CERCLA risk assessment and analysis of remedial alternatives. These concerns are related, in that the Data Quality Objective (DQO) process addresses both. The DQO process was developed in part to assist CERCLA decision-makers in identifying the data types, data quality, and data quantity required to support decisions that must be made during the remedial investigation/feasibility study (RI/FS) process. Data Quality Objectives for Remedial Response Activities: Development Process (US EPA, 1987a) is a guidebook on developing DQOs. This process as it relates to CERCLA soil characterization is discussed in the Data Quality Objective Section of this paper.     

Use of cluster and principal component analyses to profile areas in California where ground water has been contaminated by pesticides

An empirical approach to profiling areas of ground water contamination by pesticides was devised that did not rely upon determining the level of vulnerability between land areas and that did not assume any particular pathway for ground water contamination. Climatic and soil data were obtained for 1-square mile sections of land in California where pesticide residues had been found in well water samples and the detection was attributed to legal agricultural applications. These sections were designated as known contaminated (KC) sections. Climate and soil data were also obtained for sections which lacked either well sampling data or a positive pesticide detection. These sections were designated as candidate sections. Statistical procedures were used to cluster groups of KC sections first with respect to climate characteristics and then with respect to soil characteristics. Principal components analysis (PCA) was used to construct a statistical profile of soil variables for each cluster of KC sections. A method based on the PCA was developed to compare the similarity of soil profiles derived for each KC section cluster to individual candidate sections. Since the profiling scheme was based only on data from KC sections, candidate sections that did not match any KC cluster profile could only be considered dissimilar to contaminated sections, receiving a status of not-classified. This profiling method is flexible and it can be revised to incorporate updated well sampling information.     

Evaluation of the Industrial Source Complex short-term model in a large-scale multiple source region for different stability classes

The original Industrial Source Complex Model (ISCST, 90346) and its latest version, the ISCST2 (92090), are evaluated for the 1- and 24-hour averaging periods, using six statistical parameters. The confidence limits on two parameters were obtained using the bootstrap, jacknife, seductive, and robust resampling techniques. Evaluation is conducted in a multiple point source environment and in all the different stability categories, using a year of meteorological data, emission inventory of the Lucas County, in Toledo, Ohio, and monitoring data from two nearby stations for the year 1987. This was representative of a real time situation in which the ISCST is generally applied for regulatory work. The sensitivity analysis shows that the ISC is a poor performing model in the 1-h and 24-h averaging period, neutral and stable categories, and modifications to it are necessary in order to improve its performance. Its performance changes depending on the chosen paired values. A better relative performance is observed in the unstable category relative to the neutral and stable categories. Improved model performance may be achieved by applying modifications to the physics on which the model is based.     

Field scale variability of cadmium and zinc in soil and barley

CaCl₂-extractable soil Cd and Zn contents have been suggested as a measure of bioavailability. To investigate the ability of this measure to reflect spatial patterns of Cd and Zn concentrations in barley (Hordeum vulgare L.) in an arable field, plant and soil samples were taken from a 0.5 ha area sandy soil contaminated with Cd and Zn. Cd and Zn contents in barley and yield were spatially variable. Yield was low, which may have been caused by Zn toxicity or atrazine turnover. For Cd, CaCl₂-extractable soil contents explained only 17% of the variation in Cd contents in grain, and for Zn no significant correlation was observed. Nevertheless, surface plots of CaCl₂-extractable soil contents and contents of barley grain illustrated their corresponding spatial patterns. Despite the poor linear correlation between CaCl₂-extractable soil-Cd and grain-Cd, a stochastic model for long term behaviour of Cd in field soils predicted observed variability in Cd contents of barley grain well from spatial variability of soil pH and organic matter content. The probabilistic model predicted behaviour of Cd in terms of probability, and was more appropriate than the deterministic approach.     

Ambient air concentrations of PCDDs,PCDFs, coplanar PCBs,and PAHs at the Mississippi Sandhill Crane National Wildlife Refuge,Jackson County,Mississippi

Our objective was to determine the levels of selected airborne contaminants in ambient air at the Mississippi Sandhill Crane National Wildlife Refuge, Mississippi, that might be affecting the health of endangered cranes living there. Two high-volume air samplers were operated at separate locations on the Refuge during May–September 1991. The sampling media were micro-quartz filters in combination with polyurethane foam plugs. Composite bimonthly samples from each station were analyzed for polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), coplanar polychlorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons (PAHs). Overall, residue concentrations were low. The toxic PCDD isomer 2,3,7,8-tetra-CDD was not detected, nor was penta-CDD. There was no difference (P>0.05) in residue concentrations between stations or over time and meteorological parameters were not correlated with residue concentrations. Because contaminant levels and patterns may differ seasonally, we recommend that air samples collected during winter months also be analyzed for these same chemical groups.     

Effects of exposure of aquatic snails to sublethal concentrations of waste drilling fluid

Static bioassays were carried out using two aquatic snails (Pilia sp. and Lanistes sp.) as test organisms in soft natural dilution water, with waste drilling fluid as the test material, at 28±2°C. Comparison of results for the control and different concentrations of the waste drilling fluid were made by means of the F-statistic method. The waste drilling fluid was practically non-toxic to the two aquatic snails.     

Criteria for the evaluation of alternative environmental monitoring variables: Theory and an application using winter flounder (Pleuronectes americanus) and Dover sole (Microstomus pacificus)

The design of environmental monitoring programs is frequently hampered by a lack of objective, quantitative criteria for evaluating alternative monitoring variables. In this paper we describe two such criteria, which we call samples required — the number of samples required to detect a given change in value — and information imparted — the amount of environmental information revealed by the monitoring variable. We then use these criteria to evaluate fin erosion in winter flounder (Pleuronectes americanus) and Dover sole (Microstomus pacificus) as marine environmental monitoring variables. Two methods for determining the samples required use contaminated and reference areas to estimate the sample statistics of a hypothetical impacted population. The first method is based on the overall difference in the proportions of diseased fish in the reference and hypothetical populations. The second treats the proportion of diseased fish in individual trawls as the variate and determines the samples required based on the mean and variance of the reference and contaminated populations. We use both methods to predict the number of trawls needed to detect an increase of 200% in fin erosion in the reference population. The first method had greater statistical power but assumes spatially homogeneous populations. The second method accounts for environmental patchiness. For Dover sole it predicted 1661 trawls would be needed to detect the 200% increase. An estuarine winter flounder population would require 74 trawls, and an oceanic winter flounder population would require 142.5 trawls. It appears that fin erosion in winter flounder may be a useful indicator of environmental contamination, but several stipulations apply. Migration may inflate the number of diseased fish observed in the reference population, and a more detailed etiology of the disease is required, including an understanding of what contaminants are responsible for manifestation of the disease.