Classification of local- and landscape-scale ecological types in the southern Appalachian Mountains

Five local ecological types based on vegetative communities and two landscape types based on groups of communities, were identified by integrating landform, soil, and vegetation components using multivariate techniques. Elevation and several topographic and soil variables were highly correlated with types of both scales. Landscape ecological types based only on landform and soil variables without vegetation did not correspond with types developed using vegetation. Models developed from these relationships could allow classification and mapping of extensive areas using geographic information systems.     

Characterization and removal of odors from refuse material

Odorous gases emitted from refuse wastes were scrubbed through activated carbon columns until odor breakthrough occured. Refuse air samples were collected at the influent and effluent ports of the columns for analysis on a gas chromatograph-mass spectrometric system and for odor determination by dynamic olfactometry. Chromatographic profiles of the gases emitted from refuse material were obtained and volatiles identified included carboxylic acids and some sulphur compounds. Organoleptic tests with a dynamic olfactometer revealed that the odor concentration of refuse air averaged about 50 sou m^–3. The adsorption capacities of four commercial grades of activated carbon for refuse odor were evaluated and compared. Results indicated that chemically impregnated activated carbons that are commonly used for odor control at sewerage facilities were less cost effective than non-chemically impregnated carbons.     

EPA's monitoring program at Love Canal 1980

Summary As stated at the beginning of this paper conclusions reached thus far cannot be discussed in this paper. However, a great deal of information is available for examination.EPA displayed its ability to coordinate widely separated laboratories, both Federal and private, into a smooth working team in a very short period of time. A very comprehensive study plan was also developed and implemented quickly. EPA was fortunate to have already had GCA under contract when the emergency arose. In no small part the success of the field effort was due to the managerial and technical abilities of the GCA team.Within a period of 6 weeks a plan was developed, a prime contractor retained, subcontractors hired, and field activities begun. Within a period of 3 months in excess of 8600 field samples were collected and over 12,000 field and QC samples were analyzed. During this same period 2 major data systems were developed, debugged, and placed into operation.In short this EPA project was probably the most comprehensive multimedia field project ever attempted by EPA and certainly the data is being subjected to the most strenuous quality control measures ever imposed by this Agency. The entire program is presently under peer review and the results are being prepared for publication by EPA Headquarters.Note. Originally intended to be published as part of the special issue on Exposure Monitoring: An International Workshop (Las Vegas, Nevada, October 19–22, 1981).     

Analysis of two-way layout of count data with negative binomial variation

A number of methods has been proposed for dealing with single-factor or factorial experiments when the requirements for performing the normal theory analysis of variance procedure are not satisfied. This paper suggests the use of the likelihood ratio statistic for testing the main effects and the interaction between the factors in two-way layout of count data following negative binomial distributions with a common dispersion parameter. The likelihood ratio statistic for testing the equality of the dispersion parameters of several groups of count data is also derived. The methods is illustrated by an example concerning the study of spatial and temporal variation of bacterial counts.     

Robust graphical methods for diagnosing trend in irregularly spaced water quality time series

Graphical methods can play an important role in the reliable assessment of trends in typically ill behaved river quality data series both as diagnostic tools and as visual corroborative evidence when assumptions required for formal statistical tests are not met. Robust, graphically-oriented trend diagnosis procedures are presented for data series characterized by nonnormal populations, uneven time spacing, nonmonotonic trend and other factors which can create serious problems for standard parametric time series methods. Cleveland's robust locally weighted regression (RLWR) developed for investigating nonlinearity in x-y scatterplots is adapted as a robust/resistant smoothing filter for the analysis of irregular time series comprising quantitative observations. Low powered RLWR trend lines reveal temporally local phenomena, e.g. abrupt jumps (often associated with point source impacts) and periodicities, while higher powered RLWR yields smooth lines characterizing medium and longer term trends. Simple variants of Tukey smoothing concepts are developed for series with censored observations. Applications to Ontario river quality series reveal that graphical evidence is frequently sufficient to obviate the need for formal trend testing. The methods are generally applicable to most time series.