Modelling of wastewater transformations in gravity sewers and full-scale sewer network applications: Assessment and
Jinhao Kang1, Nan Zhao1, Danfeng Ding1
1State Key Laboratory of Urban-rural Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China; School of Environment, Harbin Institute of Technology, Harbin 150090, China.
Abstract:
In-sewer wastewater transformation processes alter wastewater treatment plant (WWTP) influent quality and undermine system efficiency, yet the impacts remain insufficiently quantified. This study developed a gravity sewer wastewater transformation model (WAT-GS) under plant-wide modeling framework, integrating hydraulics, interphase mass transfer and biochemical processes. Key parameters were identified by sensitivity analysis, calibrated and validated with laboratory and field data. The model accurately reproduced flow, COD and nitrogen profiles with mean absolute errors below 17 %, confirming its predictive capability under field conditions. Under dry-weather conditions, the field sewer network exhibited COD collection rate of 89.9 %. Of the 32,348 kg·d⁻¹ COD entering the network, 29,104 kg·d⁻¹ reached the WWTP, while 3244 kg·d⁻¹ were lost through sewage-phase biochemical reactions (308 kg·d⁻¹) and mass transfer to sediments/biofilms (2937 kg·d⁻¹), within which 2088.5 kg·d⁻¹ was converted to gases, and 1159 kg·d⁻¹ was retained in sediments. While nitrogen and phosphorus were almost completely collected. These transformations reduced organic loads and altered C/N/P ratios of downstream WWTP influent, exerting impacts on nutrient removal. Low collection rate fractions (colloidal COD) were rapidly depleted by in-sewer transformations, whereas fractions with high collection rate (solute and particulate COD) were primarily governed by upstream loading and hydraulic mixing. COD losses were primarily driven by sedimentation and methanogenesis, occurring predominantly within trunk mains, which represented only 13.7 % of sewer length, accounted for 51.6 % of total losses. This study provided a modeling framework for simulating in-sewer transformation processes and tracking pollutant fate, enabling robust pollutant collection rate assessment and performance optimization for sewer system.
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