Modeling the relationship of aeration, oxygen transfer and treatment performance in aerated horizontal flow treatment wetlands

Mechanical aeration is commonly used to improve the overall treatment efficacy of constructed wetlands. However, the quantitative relationships of air flow rate (AFR), water temperature, field oxygen transfer and treatment performance have not been analyzed in detail until today. In this study, a reactive transport model based on dual–permeability flow and biokinetic formulations of the Constructed Wetland Model No. 1 (CWM1) was developed and extented to 1) simulate oxygen transfer and treatment performance for organic carbon and nitrogen of two pilot–scale horizontal flow (HF) aerated wetlands (Test and Control) treating domestic sewage, and, 2) to investigate the dependence of oxygen transfer and treatment performance on AFR and water temperature. Both pilot–scale wetlands exhibited preferential flow patters and high treatment performance for chemical oxygen demand (COD) and NH4–N at AFRs of 128–700 L m−2 h−1. A reduction of the AFR in the Test system from 128 to 72 L h−1 m−2 substantially inhibited NH4–N removal. Conservative tracer transport as well as reactive transport of dissolved oxygen (DO), soluble and total chemical oxygen demand (CODs, CODt), NH4–N and NOx–N measured in pilot–scale experiments were simulated with acceptable accuracy (E1¯=0.39±0.26). An equation to estimate the volumetric oxygen transfer coefficient was found to be: kLa,20=0.511ln(AFR). Simulated treatment performance depended on kLa,20 in a non–linear manner. A local sensitivity analysis of the calibrated parameters revealed porosity, hydraulic permeability and dispersion length of the fast flow field as well as kLa,20 as most important. An optimal AFR for a spatially and temporally continuous aeration pattern for treatment wetlands treating similar influent was estimated to 150–200 L h−1 m−2. This study provides insights into aeration mechanisms of aerated treatment wetlands and highlights the benefits of process modeling for in–depth system analysis.