Distribution of heavy metals in water and sediments of selected sites of Yamuna river (India)

The concentration of Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn metals in water and sediments of Yamuna river were determined by atomic absorption spectrophotometry in the year 1981. The data showed that there was considerable variation in the concentration of elements from one sampling station to the other which may be due to the variation in the quality of industrial and sewage wasters being added to the river at different sampling stations. The sediment samples collected from different sampling stations were also analysed for calcium carbonate, organic matter, potassium, and phosphorus.     

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.     

The occurrence of acid precipitation on the west coast of the United States

Compilation of published and unpublished data shows acid precipitation to be more widespread in the Pacific coastal states than is generally recognized. Although information is scattered and discontinuous, precipitation is definitely acidic in the Los Angeles Basin and north-central california, and in the Puget Sound region in Washington. Acid rain occurrences have been observed in western and eastern Oregon, but data are inadequate for regional generalization. New stations currently being established in Washington and Oregon, largely in resposnse to the recently renewed activity of Mount St. Helens, will greatly facilitate assessment of precipitation acidity in the Northwest.     

Determination of biomass burning emission factors: Methods and results

Biomass burning, in a broad sense, encompasses different burning practices, including open and confined burnings, and different types of vegetation. Emission factors of gaseous or particulate trace compounds are directly dependent both on the fuel type and the combustion process. Emission factors are generally calculated by stoichiometric considerations using the carbon mass balance method, applied either to combustion chamber experiments or to field experiments based on ground-level measurements or aircraft sampling in smoke plumes. There have been a number of experimental studies in the last 10 years to investigate wildfires in tropical, temperate, or boreal regions. This article presents an overview of measurement methods and experimental data on emission factors of reactive or radiatively active trace compounds, including trace gases and particles. It focuses on fires in tropical regions, that is, forest and savanna fires, agricultural burns, charcoal production, use of fuelwood, and charcoal combustion.     

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.     

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.     

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.