ENFORCEMENT LIMITATIONS IN WATER QUALITY CONTROL1

The Federal role in the enforcement of water quality requirements is of recent development. It began with the enactment in 1956 of the Federal Water Pollution Control Act as permanent law. It has been expanded by successive amendments to the Act to cover the pollution of navigable as well as interstate waters which endangers the health or welfare of persons, and to cover violations of water quality standards established for interstate waters. Two different enforcement procedures are prescribed in the law to be followed in the two types of enforcement actions. While questions have arisen of jurisdiction, States' rights, and disregard or duplication of local efforts, such questions do not lastingly impede the exercise of Federal enforcement authority and are of value in establishing a body of precedents. Limitations have their basis in the statutory distinctions between interstate and intrastate pollution which govern the application of the enforcement authority, even though a case of intrastate pollution may be as serious or more serious than a case of interstate pollution. An additional limitation results from the statutory time intervals between procedural stages in an action. Lack of data is a limitation but can always be overcome and at most causes delay. State laws which protect the confidentiality of required reports are more of a limitation. Investigative teams may obtain the needed information, however, for consideration in public meetings. Public support for effective water quality control measures, especially enforcement, and for the expenditures needed to enhance the environment, is widespread. Such support may be instrumental in modifying or eliminating existing statutory limitations.     

Temperature and wetland plant species effects on wastewater treatment and root zone oxidation

Constructed wetlands are widely used for wastewater treatment, but there is little information on processes affecting their performance in cold climates, effects of plants on seasonal performance, or plant selection for cold regions. We evaluated the effects of three plant species on seasonal removal of dissolved organic matter (OM) (measured by chemical oxygen demand and dissolved organic carbon) and root zone oxidation status (measured by redox potential [Eh] and sulfate [SO4(2-)]) in subsurface-flow wetland (SSW) microcosms. A series of 20-d incubations of simulated wastewater was conducted during a 28-mo greenhouse study at temperatures from 4 to 24 degrees C. Presence and species of plants strongly affected seasonal differences in OM removal and root zone oxidation. All plants enhanced OM removal compared with unplanted controls, but plant effects and differences among species were much greater at 4 degrees C, during dormancy, than at 24 degrees C, during the growing season. Low temperatures were associated with decreased OM removal in unplanted controls and broadleaf cattail (Typha latifolia L.) microcosms and with increased removal in beaked sedge (Carex rostrata Stokes) and hardstem bulrush [Schoenoplectus acutus (Muhl. ex Bigelow) A. & D. L?ve var. acutus] microcosms. Differences in OM removal corresponded to species' apparent abilities to increase root zone oxygen supply. Sedge and bulrush significantly raised Eh values and SO4(2-) concentrations, particularly at 4 degrees C. These results add to evidence that SSWs can be effective in cold climates and suggest that plant species selection may be especially important to optimizing SSW performance in cold climates.     

Butyltin contamination of sediments and benthic fish from the East,Gulf and Pacific coasts of the United States

Butyltin concentrations were determined in sediments, tissues and stomach contents of fish collected in 41 embayments on the East, Gulf and Pacific coasts of the U.S.A. between 1986 and 1991 as part of the National Oceanic and Atmospheric Administration's (NOAA) National Benthic Surveillance Project (NBSP). A total of 99 sediments, 108 fish liver samples from 11 fish species, and 10 composites of fish stomach contents were analyzed for tetrabutylin, tributylin, dibutylin and monobutylin. Tributyltin (TBT) was detected (i.e. > 10 ng/g) in 38 of the sediments samples analyzed and was generally the predominant bulytin present; concentrations of total butyltins ranged from 15 to 1600 ng/g wet weight. The highest concentrations were found in sediments from urban sites, especially sites on the West coast. Many of the fish liver and stomach contents samples also contained butyltins. Tributyltin represented 83 (7.1)% [mean (SEM); n=15], 64 (6.6)% (n=12) and 36 (7.8)% (n=12) of the total butyltins in livers from white croaker, winter flounder and Atlantic croaker, respectively, suggesting possible species differences in biotransformation of TBT. The concentrations of butyltins in stomach contents indicated that diet can be a significant route of exposure of fish to butyltins. Between 1986 and 1991 butyltin concentrations in sediments and fish generally appeared to be declining; however, no statistically significant temporal trends were observed at individual sites or for the sites overall.The U.S. government's right to retain a non-exclusive, royalty free license in and to any copyright is acknowledged.     

External drift kriging of NOx concentrations with dispersion model output in a reduced air quality monitoring network

In the mid nineteen eighties the Dutch NO_x air quality monitoring network was reduced from 73 to 32 rural and city background stations, leading to higher spatial uncertainties. In this study, several other sources of information are being used to help reduce uncertainties in parameter estimation and spatial mapping. For parameter estimation, we used Bayesian inference. For mapping, we used kriging with external drift (KED) including secondary information from a dispersion model. The methods were applied to atmospheric NO_x concentrations on rural and urban scales. We compared Bayesian estimation with restricted maximum likelihood estimation and KED with universal kriging. As a reference we also included ordinary least squares (OLS). Comparison of several parameter estimation and spatial interpolation methods was done by cross-validation. Bayesian analysis resulted in an error reduction of 10 to 20% as compared to restricted maximum likelihood, whereas KED resulted in an error reduction of 50% as compared to universal kriging. Where observations were sparse, the predictions were substantially improved by inclusion of the dispersion model output and by using available prior information. No major improvement was observed as compared to OLS, the cause presumably being that much good information is contained in the dispersion model output, so that no additional spatial residual random field is required to explain the data. In all, we conclude that reduction in the monitoring network could be compensated by modern geostatistical methods, and that a traditional simple statistical model is of an almost equal quality.

Spatial statistics for modeling of abundance and distribution of wildlife species in the Masai Mara ecosystem, Kenya

This study illustrates the use of modern statistical procedures for better wildlife management by addressing three key issues: determination of abundance, modeling of animal distributions and variability of diversity in space and time. Prior information in Markov Chain Monte Carlo (MCMC) methods is used to improve estimates of abundance. Measures of autocorrelation are included when modeling distributions of animal counts, and a diversity index to indicate species abundance and richness for large herbivores is developed. Data from the Masai Mara ecosystem in Kenya are used to develop and demonstrate these procedures. The new abundance estimates are up to 35% more accurate than those obtained by existing methods. Significant temporal changes in spatial patterns are found from a space-time analysis of elephant counts over a 20-year period, with strong interactions over 5 km and 6 months space and time separations, respectively. The new diversity index is sensitive to both high abundance and species richness and is also able to capture year to year variation. It indicates an overall marginal decrease in diversity for large herbivores in the Mara ecosystem. The space-time analyses and diversity index can easily be computed thereby providing tools for rapid decision making.     

Incinerator Conference Covers Emissions Control Aspects

The success of the application of computer modeling to decision-making will depend on the degree to which the scientifically valid “cause-and-effect” features of the air pollution system are represented. For this reason, dynamic simulation models are to be preferred to statistical and empirical models. A digital simulation model based on a stoichiometrically logical chemical mechanism and trajectory estimating routines was constructed, using Los Angeles source, meteorological and geographic input. The basic physical concept underlying the simulation model is the process of evolution of photochemical pollution in a parcel of air as it moves in a dynamic urban emission/meteorological environment along a given urban wind trajectory. Both the photochemical evolution and the trajectory are numerically integrated by a standard linear multistep predictor-corrector method. Concentrations of photochemical reactants and products (i.e., primary and secondary contaminants) are determined by this numerical integration, which also includes appropriate terms for relevant effects. In five preliminary validation runs, simulated NO₂, NO, and O₃ values were within 20% or 0.05 ppm of those observed at air monitoring stations located near the termini of the runs. The trajectories were plotted on the basis of hourly meteorological data for 22 stations. Six control strategy exercises were conducted to illustrate the application of the model to problem-solving situations.