ARE RURAL RESIDENTS WILLING TO PAY ENOUGH TO IMPROVE DRINKING WATER QUALITY?1

ABSTRACT: The concentrations of iron and sulfate in community water supplies are a concern for a number of areas in southwestern Minnesota. This study used the contingent valuation method to determine how much consumers would be willing to pay to improve their drinking water quality. On average, individuals were willing to pay US$5.25 per month (in 1995 U.S. dollars) to reduce the level of iron and US$4.33 per month to reduce the level of sulfate in their water to the USEPA's secondary standards for drinking water quality. Respondents with negative perceptions of their drinking water quality were willing to pay more to improve water quality. The aggregate annual willingness to pay (WTP) for all consumers in community water systems in southwestern Minnesota that were out of compliance with water quality standards were estimated to be US$2.4 million and US$2.0 million (in 1995 dollars) for reducing the levels of iron and sulfate, respectively. Yet the total WTP of consumers who use small community water systems may not be enough to pay the full cost of providing improved water in those systems. Economies of scale in water treatment and difficulties in financing improvements mean that technical innovation, government assistance, or institutional changes may be needed to improve water quality in these areas.     

MODELING LIGHT ATTENUATION,SECCHI DISK,AND EFFECTS OF TRIPTON IN SENACA RIVER,NEW YORK,USA1

The development, testing, and application of a probabilistic model framework for the light attenuation coefficient for downwelling irradiance (K_d) and Secchi disc transparency (SD) that resolves the effects of several light attenuating constituents, including phytoplankton and nonliving particles (tripton), is documented. The model is consistent with optical theory, partitioning the magnitudes of the light attenuating processes of absorption and scattering according to the contributions of attenuating constituents as simple summations. The probabilistic framework accommodates variations in the character and concentrations of these constituents and ambient conditions during measurements, and recognizes a linear relationship between the magnitudes of absorption and scattering by tripton. The model is tested and applied for a 21 km reach of the Seneca River, New York, that features optical gradients caused by an intervening hypereutrophic lake and dam, and a severe infestation of the exotic zebra mussel. The model is applied to resolve the roles of phytoplankton and tripton in regulating measured longitudinal patterns of SD along the study reach of the river and increases in SD since the zebra mussel invasion, and to predict decreases in K_d since the invasion.     

PREDICTING FECAL COLIFORM BACTERIA LEVELS IN THE CHARLES RIVER,MASSACHUSETTS, USA1

In Massachusetts, the Charles River Watershed Association conducts a regular water quality monitoring and public notification program in the Charles River Basin during the recreational season to inform users of the river's health. This program has relied on laboratory analyses of river samples for fecal coliform bacteria levels, however, results are not available until at least 24 hours after sampling. To avoid the need for laboratory analyses, ordinary least squares (OLS) and logistic regression models were developed to predict fecal coliform bacteria concentrations and the probabilities of exceeding the Massachusetts secondary contact recreation standard for bacteria based on meteorological conditions and streamflow. The OLS models resulted in adjusted R²s ranging from 50 to 60 percent. An uncertainty analysis reveals that of the total variability of fecal coliform bacteria concentrations, 45 percent is explained by the OLS regression model, 15 percent is explained by both measurement and space sampling error, and 40 percent is explained by time sampling error. Higher accuracy in future bacteria forecasting models would likely result from reductions in laboratory measurement errors and improved sampling designs.     

Estimating the economic burden from illnesses associated with recreational coastal water pollution--a case study in Orange County, California

A cost-of-illness framework was applied to health and income data to quantify the health burden from illnesses associated with exposure to polluted recreational marine waters. Using data on illness severity due to exposure to polluted coastal water and estimates of mean annual salaries and medical costs (adjusted to 2001 values) for residents of Orange County, California, we estimated that the economic burden per gastrointestinal illness (GI) amounts to 36.58 dollars, the burden per acute respiratory disease is 76.76 dollars, the burden per ear ailment is 37.86 dollars, and the burden per eye ailment is 27.31 dollars. These costs can become a substantial public health burden when millions of exposures per year to polluted coastal waters result in hundreds of thousands of illnesses. For example, exposures to polluted waters at Orange County's Newport and Huntington Beaches were estimated to generate an average of 36,778 GI episodes per year. At this GI illness rate, one can also expect that approximately 38,000 more illness episodes occurred per year of other types, including respiratory, eye, and ear infections. The combination of excess illnesses associated with coastal water pollution resulted in a cumulative public health burden of 3.3 million dollars per year for these two beaches. This paper introduces a public health cost variable that can be applied in cost-benefit analyses when evaluating pollution abatement strategies.     

Effect of Si-rich substances on phosphorous adsorption by sandy soils

Environmental Science and Pollution Research - The poor adsorption capacity of sandy soils is one of the primary reasons of a high level of phosphorus (P) leaching. Silicon (Si)-rich soil...