title: Comparison of operational design criteria for subsurface flow constructed wetlands for wastewater treatment.
abstract: Many communities are investigating the use of constructed wetlands as a simple, viable alternative to poorly operating on-site wastewater treatment. Currently, the most popular design models in the U.S.A. for subsurface flow units are the US Environmental Protection Agency (EPA) and the Tennessee Valley Authority (TVA) methods. However, there has been limited data verifying if the operating performance is up to design standards. In order to address this problem, this paper documents the performance of such treatment systems over a broad range of conditions in North Alabama. The operational data is used to determine a best-fit value of reaction rate constant and proposes improved input parameters for both design models. According to this data, the average plug-flow reaction rate constant was calculated to be 0.70 d-1 for the EPA method, while the recommended organic loading criterion is 11.4 m2/kg BOD5 per day into the wetland for the TVA method.
authors.affiliation: Civil and Environmental Engineering Department, University of Alabama in Huntsville, Huntsville, Alabama 35899, USA.
authors.forename: K M
authors.initials: KM
authors.lastname: Leonard
authors.forename: G W
authors.initials: GW
authors.lastname: Swanson
mesh_terms: D000465:Algorithms; D000641:Ammonia / Q000378:metabolism; D001673:Biodegradation, Environmental; D008432:Mathematical Computing; D009584:Nitrogen / Q000378:metabolism; D010084:Oxidation-Reduction; D010101:Oxygen Consumption; D012621:Seasons; D012989:Soil Pollutants / Q000032:analysis; D013696:Temperature; D013714:Tennessee; D014481:United States; D014484:United States Environmental Protection Agency; D014872:Water Movements; D014874:Water Pollutants, Chemical / Q000032:analysis; D018508:Water Purification / Q000379:methods* / Q000706:statistics & numerical data
chemical_list: D012989:Soil Pollutants; D014874:Water Pollutants, Chemical; D000641:Ammonia; D009584:Nitrogen