Abstract
Estrogens are female sex hormones, and the major naturally occurring estrogens are estrone (E1), 17α-estradiol (E2α), 17β-estradiol (E2β), and estriol (E3). Concentrated animal feeding operations (CAFOs) and wastewater treatment facilities release a large amount of estrogens into surface water. Additionally, livestock manure and biosolids, which are widely used as fertilizers, have the potential to spread estrogens onto agricultural land. Estrogens either in surface water or on land surface go through prevalent and complex attenuations and transformations due to bio-transformation, sorption, photo-transformation, and plant uptake. Estrogens on the land surface can be transported into surface water through various pathways such as the surface runoff. Once estrogens get into surface water, they can impair the normal reproductive functions of aquatic animals at low concentrations. Thus, it is quite important to estimate estrogen levels in surface water in order to assess and mitigate the potential health risks caused by those estrogens. As a modeling framework can help to conduct this analysis, the goal of this study is to develop a quantitative modeling framework to simulate levels of the three most prevalent natural estrogens, E1, E2α, and E2β, in rivers. This study first adopted a wash-off model to quantify the transport of E1, E2α, and E2β from land to rivers by surface runoff. This study also developed a comprehensive transformation model to quantify the transformation and attenuation of E1, E2α, and E2β. This study then assembled these two mathematical models to develop a quantitative modeling framework, which can be implemented by the Hydrological Simulation Program - FORTRAN (HSPF), to simulate estrogen levels in rivers. Finally, this modeling framework was applied to the South River Watershed in Virginia and the Redwood River Watershed in Minnesota to track the fate and transport of estrogens from various sources such as wastewater treatment plants (WWTPs), manure and biosolids used for land application, grazing farm animals, and septic systems. For both watersheds, a component analysis was conducted to quantify estrogens contributed by each source and a sensitivity analysis was conducted to investigate factors that can impact estrogen levels in rivers. The modeling results for both watersheds indicate that storm events just after manure land application can transport a large amount of estrogens to surface water and elevate estrogen levels. Buffer stripes are suggested in this case to reduce the mass of estrogens that are flushed into surface water. The modeling results for both watersheds also show that the simulated estrogen levels are sensitive to cattle grazing time in streams, and thus fencing off rivers to keep cattle out of the water is recommended to reduce the amount of estrogens that are directly released into streams by cattle. Additionally, the modeling results for both watersheds show that manure used for land application release a large amount of estrogens onto the land surface and the simulated estrogens levels are sensitive to the manure application rate, the manure storage before land application is thus encouraged in order to reduce the estrogen content in manure. This framework can be applied to watersheds to predict the temporal and spatial variation of estrogens in rivers, to quantify estrogens contributed by various sources, to investigate the factors that can lead to high estrogen levels, and to determine the best management practices (BMPs) of controlling estrogens in surface water.
