No description available.

No description available.

Transition state theory was applied to the nitrification process in soil-water systems, and a computerized, theoretical rate model was developed to include NH₄⁺ and 0₂ concentrations, pH, temperature, moisture content, and local differences in nitrifying capacities of Nitrosomonas bacteria. The model was restricted to enriched calcareous soils thus simplifying the application of basic physicochemical principles. Experimental rate data from an agricultural and a native desert soil provided verification of a zero order reaction for nitrification with respect to NH₄⁺ concentrations above a certain saturation level, as previously reported. The saturation concentration in soils was found to be about 1.0 to 5.0 ppm. A theoretical linear relationship between activation energy and ionic strength was confirmed by application of the above data. However, each local population of nitrifiers tended to display different values for the slope and intercept of the linear relationship. The structure of the activated complex for NH₄⁺ oxidation to NO₂⁻ was determined to be more like NH2OH or NH₄⁺ than NO₂⁻. As a first approximation, the NH₂OH activated complex was included in the rate model. The equation form for the equilibrium between the reactants and the activated complex was found to differ from the stoichiometric reaction between NH₄⁺ and O₂ to form NH₂OH. The equilibrium expression was found to be more closely approximated by the relationship, 2 NH₄⁺ + O₂ ≶ (ACTIVATED COMPLEX) + + H⁺. A method was developed to compute soil pH values as a function of moisture content. Verification was obtained by using data obtained from the agricultural and native desert soils, including cases where samples were acidified. The calculated pH values were used in the nitrification rate model. Further verification of the model was obtained using data from the literature for two soils from the Northern Great Plains. Data pairing of observed and predicted rates for these soils yielded R values of 0.944 and 0.940. The rate model was programmed in FORTRAN IV computer language and designed to operate in conjunction with existing computer models. Thus, this relatively sophisticated model may be applied to field simulation studies with a minimum of adaptive procedures. The model should aid in obtaining reliable predictions of NO₃⁻ formation and movement under a wide range of field conditions.

Digitized by Kansas Correctional Industries

The temporal and spatial changes in chemical and biological properties of Lake Mead have been investigated, thereby indicating the sources of water pollution and the time of highest pollution potential. Planktonic organisms have been shown to indicate the presence of water problems. Macro- and micro-nutrient analyses have shown that primary productivity is not inhibited by limiting concentrations. A mathematical model has been developed, tested with one set of independent data, and shown worthy of management utility. Although the model works very well for the Lake Mead area, the physical reality of the Multiple Linear Regression equation should be tested on independent data.

by Wong Siu Fun. / Bibliography: leaves 55-59 / Thesis (M.Ph.)--Chinese University of Hong Kong, 1986

No description available.

The temporal and spatial changes in chemical and biological properties of Lake Mead have been investigated, thereby indicating the sources of water pollution and the time of highest pollution potential. Planktonic organisms have been shown to indicate the presence of water problems. Macro- and micro-nutrient analyses have shown that primary productivity is not inhibited by limiting concentrations. A mathematical model has been developed, tested with one set of independent data, and shown worthy of management utility. Although the model works very well for the Lake Mead area, the physical reality of the MLR equation should be tested on independent data.

This research develops an algorithm for solving a class of multiple objective decision problems. These problems are characterized by continuous policy variables, nonlinear constraints, and nonlinear criterion functions. Our underlying philosophy is that of the Gestalt psychologists-- we cannot separate the problem and its solution from the environment in which the problem is placed. The decision maker is necessarily a part of this environment, thus implying that he, as an individual, must be part of the solution of the problem. Another central assumption in this research is that there is not an "optimal" answer to the problem, only "satisfactory" solutions. The reasons for this are based partly on the insensitivities of the body to minute changes and to the insensitivity of our preferences within certain ranges of acceptance. In addition, we assure that the individual is capable of solving decision situations involving a maximum of about 10 goals and that he operates upon them in some sort of serial manner as he searches for a satisfactory alternative. The serial manner is a reflection of his current ranking of the goals. Based on these assumptions we have developed a cyclical interactive algorithm in which the decision maker guides a search mechanism in attempting to find a satisfactory alternative. Each cycle in the search consists of an optimization phase and an evaluation phase, after which the decision maker can define a new direction of search or terminate the algorithm. The optimization phase is based on a linearization technique which has been quite effective in terms of the problems we have attempted to solve. It is capable of solving general nonlinear programming problems with a large number of nonlinear constraints. Although the constraint set must be convex in order to guarantee the location of a global optimum, we can use the method on concave sets recognizing that we may find only a local optimum. An extensive synthetic case study of a water pollution decision problem with 6 conflicting goals is provided to demonstrate the feasibility of the algorithm. Finally, the limitations of the research are discussed. We tentatively conclude that we have developed a method applicable to our research problem and that the method can be applied to "real world" decision situations.

A risk-based approach for addressing several non-structural stream quality management objectives is presented. To estimate risk, the input process, the stream contaminant transport, and the consequence of contamination are modeled mathematically. The transport of soluble contaminant introduced at a point into a turbulent stream medium is modeled as a boundary value problem in which the contaminant satisfies the Kolmogorov forward equation within the medium. Observed properties of turbulence are used to justify the adoption of this equation. The fundamental solution, as the probabilistic response of the stream to an instantaneous unit flux input, is derived and used as the kernel in a stochastic integral representation of the transport problem. The bulk input is used as the forcing function in the integral equation. It is modeled as a sequence of independent pulses with random magnitude and duration and also with random interval between the incidence of adjacent pulses ,. Stochastic simulation is used to construct the moments and the probability distribution of stream concentration and those of several variables associated with the exceedance of the concentration above a specified threshold. The variables include the dosage and the time to the first exceedance. The probability that an observed stream concentration exceeds the threshold within a given interval of time is also constructed. Generalizations of the Chebyshev inequality are extended to the case of a stochastic process. Upper bounds on the constructed probability distributions are calculated using these extensions. Based on previous studies, a rectangular hyperbolic relationship is assumed between dosage and consequence. The relationship is combined with the empirical dosage density function to obtain estimates of value risk of stream concentration for various thresholds. Given an acceptable risk, the corresponding threshold may be used as the stream standard. The reliability function, defined as the complementary density function of exceedance times, may be used as a gauge of the effectiveness of pollution abatement measures. Other illustrated areas of application include the construction of a minimum cost contaminant discharge policy and the determination of the optimal sampling interval for stream surveillance.