Methodology for Identifying Optimal Locations of Water Quality Sensors in River Systems

A method to optimally site river water quality sensors is expanded and applied to a case study river to explore the application of mathematical siting methods to the design of river sampling networks. Fecal coliform contamination due to flooded swine waste lagoons was modeled as it moves downstream, and optimal sensor locations are located by minimizing the objective function of the optimization problem. The results of the simulations are analyzed by varying the number of allowed sampling locations and the simulated contamination event. For the case study application, the model suggests three sampling locations along the modeled river section. These three suggested sensing points did not greatly vary in location for different river flows and contamination events, indicating the robustness of the model results for this specific case study. Generally, the application of mathematical contaminant modeling is a useful and systematic approach to aid the design of river water quality monitoring networks.     

Modeling toxic compounds from nitric oxide emission measurements

Determining the amount and rate of degradation of toxic pollutants in soil and groundwater is difficult and often requires invasive techniques, such as deploying extensive monitoring well networks. Even with these networks, degradation rates across entire systems cannot readily be extrapolated from the samples. When organic compounds are degraded by microbes, especially nitrifying bacteria, oxides or nitrogen (NO_x) are released to the atmosphere. Thus, the flux of nitric oxide (NO) from the soil to the lower troposphere can be used to predict the rate at which organic compounds are degraded. By characterizing and applying biogenic and anthropogenic processes in soils the rates of degradation of organic compounds. Toluene was selected as a representative of toxic aromatic compounds, since it is inherently toxic, it is a substituted benzene compound and is listed as a hazardous air pollutant under Section 12 of the Clean Air Act Amendments of 1990. Measured toluene concentrations in soil, microbial population growth and NO fluxes in chamber studies were used to develop and parameterize a numerical model based on carbon and nitrogen cycling. These measurements, in turn, were used as indicators of bioremediation of air toxic (i.e. toluene) concentrations. The model found that chemical concentration, soil microbial abundance, and NO production can be directly related to the experimental results (significant at P < 0.01) for all toluene concentrations tested. This indicates that the model may prove useful in monitoring and predicting the fate of toxic aromatic contaminants in a complex soil system. It may also be useful in predicting the release of ozone precursors, such as changes in reservoirs of hydrocarbons and oxides of nitrogen. As such, the model may be a tool for decision makers in ozone non-attainment areas.     

STRATEGIES TO CONTROL NONPOINT SOURCE WATER POLLUTION1

ABSTRACT: Strategies for controlling nonpoint sources of water pollution are discussed in terms of three representative states and eighteen regional agencies. The programs in Virginia, New York, and Wisconsin are seen to exhibit control options which range from voluntary action to strict regulation. Four conclusions are drawn from the analysis. First, nonpoint sources of pollution are a major component of the overall water pollution problem in the three states. Second, technical controls are generally available to solve the problems. Third, existing controls programs are not necessarily technologically sound or cost effective. Finally, existing control programs are capable of instituting solutions to the problems if and only if specified actions take place within the respective states and regions in the future. Critical research needs are identified which will assist states and regions in developing cost effective programs to control nonpoint source pollution.     

APPLICATION OF FAIRNESS CONSIDERATIONS TO PHOSPHORUS CONTROL POLICIES1

ABSTRACT: Alternate solutions to a contemporary water resource management problem are developed: 53 municipalities in Wisconsin's Lake Michigan watershed must reduce their phosphorus input to the lake by 85 percent of their influent load. Different definitions of fairness, based on legal and philosophical principles, form the foundation for 18 distinct policy options. The definitions of fairness include: (1) contractual agreement; (2) precedent; (3) the market system; (4) egalitarianism; and (5) equal treatment of equals and differential treatment of unequals, with equals defined in terms of need, worth, ability to pay, who receives the benefits, and the dictates of existing technology. Two alternatives are seen to dominate: (A) municipalities could form contractual relationships to meet the removal requirement as groups, and enjoy least cost operating schedules that save money for members of each group; and (B) whereas 20 of the municipalities collect 91 percent of all phosphorus collected in the watershed, a removal of 90 percent of their influent phosphorus alone ensures that the watershed meets the standard. Under this option, the other 33 municipalities are not required to remove phosphorus. Reasons for the dominance of the two policies are discussed in detail.     

Consumption of biogenic nitric oxide in hydrated soil

An experimental study was conducted in order to determine the relationship of nitric oxide (NO) consumption to water-filled pore space in soil. A test system that included the capability to blend gases, test soil samples, and analyze off-gases was used to conduct the study. The experimental set consisted of three replicates at five different levels of soil water content and three different levels of soil nitrogen in a sandy loam soil: unamended soil, soil fertilized at 56.2 kg N per ha (50 lb N acre(-1)), and soil fertilized at 112.3 kg N per ha (100 lb N acre(-1)). The average NO consumption rates were 7.1x10(-13) g-NO cm(-3) soil, 3.5x10(-11) g-NO cm(-3) soil, and 1.5x10(-10) g-NO cm(-3) soil, respectively.