Effect of lime solids and natural organic matter on geosmin removal via powdered activated carbon.

Abstract

Minneapolis Water Works, a 60 million gallon per day water treatment facility, experiences seasonal taste and odor episodes that result in customer complaints. Geosmin, which imparts an earthy or musty odor, is one taste and odor causing compound that has been detected at levels exceeding its odor threshold concentration. Powdered activated carbon (PAC) is added in the lime softening plant to remove geosmin via sorption. It is important to understand how lime solids, contact time, and natural organic matter (NOM) affect PAC performance so that the correct PAC dose and application point are used in order to maximize geosmin removal and minimize PAC cost. Results from jar test experiments suggest that lime and alum do not inhibit the sorption of geosmin when added simultaneously with PAC but that contact time is the most important parameter. Therefore, PAC should generally be added to the water at the point which maximizes contact time. Conversely, PAC contained in settled lime solids exhibited a reduced sorption capacity compared to fresh PAC, indicating that PAC contained in recycled lime solids has minimal impact on geosmin removal at the full-scale treatment plant. Additionally, the impact of NOM on PAC performance was investigated. Using Suwanee River (SR) NOM, an increase in 1 mg/L dissolved organic carbon resulted in a decrease in geosmin removal efficiency of 2.7% (at a PAC dose of 7.5 mg/L). Suwanee River humic acid, SR fulvic acid, and Pony Lake fulvic acid also inhibited geosmin sorption, but the effect was significantly lower. For the three SR NOM types, the inhibitive effective increased as average molecular weight of the NOM decreased. Data from the full-scale plant were in reasonable agreement with laboratory jar test data for PAC added immediately before or after lime. For PAC added at the recarbonation tanks, geosmin removal efficiencies were much higher at the full-scale plant than in the jar test experiments. This could be due to the small sample size (n=4) of the full-scale data set or differences in DOC levels between jar tests and the full-scale plant.