New Model for Estimating the Concentration of Natural Estrogens in Wastewater Developed by Ben-Gurion University of the Negev Researchers  ...

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New Model for Estimating the Concentration of Natural Estrogens in Wastewater Developed by Ben-Gurion University of the Negev Researchers   SEDE BOQER, Israel, November 17, 2016 – A simple model for evaluating natural estrogen concentrations in raw sewage was developed by Ben-Gurion University of the Negev (BGU) researchers to help predict how natural estrogen levels change during waste water treatment. The study, published in the journal Science of the Total Environment provides a model for predicting the concentration of several natural estrogens in raw wastewater, a figure that is relevant for regulators, wastewater engineers and environmental scientists. Ph.D. student Pniela Dotan and Dr. Shai Arnon of BGU’s Zuckerberg Institute for Water Research  and Prof. Alon Tal of BGU’s Swiss Institute for Dryland Environmental and Energy Research based their results on data from 61 wastewater plants published in previous reports. To develop their model, they considered information collected from various publications about biochemical oxygen demand (the amount of dissolved oxygen that must be present in water for microorganisms to decompose organic matter), natural estrogen concentrations, and discharges of raw sewage to wastewater treatment plants. According to the researchers, “This new model can predict likely natural estrogen concentrations in liquid waste or sewage discharged into a river or the sea from simple information about flow and biochemical oxygen demand data at a wastewater treatment plant inlet, which are commonly monitored and available.” "This application is especially valuable since current models rely on estimating the concentrations of natural estrogens in raw wastewater, and direct measurement of natural estrogens in raw wastewater can be practically impossible in many developing countries due to the lack of expertise and funds." The researchers’ proposed model was shown to produce slightly more accurate results than existing tools because it is based on a simple linear equation, which plots the relationship between direct and indirect variables, as opposed to other modeling frameworks that require large datasets or census data. The data is from a wide range of wastewater treatment plants from five continents, and can be used for projecting concentrations of natural estrogens from a wide range of mixed domestic and industrial sources. "The model should apply globally, as long as wastewater systems don’t contain significant contributions from industrial sources known for their high natural estrogen or biochemical oxygen demand (BOD) content, such as dairy farms or food processing plants," the researchers say. P . Dotan, A. Tal, S. Arnon, 2016. A simple model for estimating the concentrations of natural estrogens in raw wastewater (2016.09). doi.org/10.1016/j.scitotenv.2016.09.015. The research was supported by the USAID Middle East Regional Cooperation (MERC) Program (grant TA-MOU-11-M31-015). About American Associates, Ben-Gurion University of the Negev American Associates, Ben-Gurion University of the Negev (AABGU) plays a vital role in sustaining David Ben-Gurion's vision: creating a world-class institution of education and research in the Israeli desert, nurturing the Negev community and sharing the University's expertise locally and around the globe. As Ben-Gurion University of the Negev (BGU) looks ahead to turning 50 in 2020, AABGU imagines a future that goes beyond the walls of academia. It is a future where BGU invents a new world and inspires a vision for a stronger Israel and its next generation of leaders. Together with supporters, AABGU will help the University foster excellence in teaching, research and outreach to the communities of the Negev for the next 50 years and beyond. Visit vision.aabgu.org to learn more. AABGU, which is headquartered in Manhattan, has nine regional offices throughout the United States. For more information, visit www.aabgu.org

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  1. LTD «VODTECHCOMPLECS»

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