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COMPUTER MODELING IDENTIFIES SEWER GAS GENERATION FACTORS AND CORRECTIVE MEASURES

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Abstract:

In response to odour complaints from residents along the Gordon Avenue, City of London trunk sewer, a comprehensive sampling and flow monitoring program of the sewer system was conducted to determine sulfide generation and release mechanisms. Since the measured data alone were not sufficient to identify parameters and operating conditions responsible for sulfide generation and release, computer modeling of the sewer system was undertaken. For the modeling, the 14 km long sewer was separated into sections based on sudden changes in flow rate or hydraulic conditions and changes in pipe diameter or slope. The model was calibrated to identify sections of the sewer with significant sulfide generation and release. Sulfide generation was estimated using Pomeroy's Z formula and sulfide loss was estimated using forms of the Pomeroy Parkhurst equation. The model showed that sulfide generation was highest upstream of the Gordon Avenue section of trunk sewer and that sulfide loss to the atmosphere was highest at Gordon Avenue, with an average sulfide concentration in the sewer gas of 12 ppm. The correlation between measured values and predicted values for sulfide concentration was good.

Factors contributing to sulfide generation were identified as septage addition, low flow velocities, low slopes and long sewer sections. Factors contributing to sulfide release were identified as septage addition, turbulence, high flow velocities, steep slopes and changes in pipe diameter. The effect of diverting septage was assessed using the calibrated model. The results suggested that H2S generation and release could be reduced by approximately 40 % to 60 % as a result of septage diversion.

Computer modeling results showed that if the sewer slope along Gordon Avenue were reduced and the pipe diameter increased, H2S release could be reduced by 62%. The combined effect of septage diversion and change in hydraulics would reduce H2S release by 81% at Gordon Avenue, and 51% throughout the entire sewer system.

Document Type: Research Article

DOI: https://doi.org/10.2175/193864703784755643

Publication date: 2003-01-01

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