Search

Linear regression techniques were used to develop practical models to predict total organic carbon (TOC) breakthrough in bituminous granular activated carbon (GAC) adsorbers. Models were developed for two field-scale GAC sizes (8x30 and 12 x 40 mesh) and two empty bed contact times (EBCTs) (10 and 20 min). Model input parameters include two water quality variables, influent TOC concentration (TO[C.sub.0]) and pH, that impact performance. The dependent variables for the models were normalized breakthrough time, throughput in bed volumes, to six fractional (TOC/TO[C.sub.0]=0.2, 0.3, 0.4, 0.5, 0.6, and 0.7) and three mass (TOC=1.0, 1.5, and 2.0 mg/L) effluent concentrations. Model development was performed using small-scale breakthrough data from 35 different source waters; external model validation was performed with small-scale breakthrough data from 14 source waters; a sensitivity analysis was performed to ensure that the models effectively capture expected breakthrough trend; and a scalability test was performed to verify the models' ability to predict breakthrough for field-scale GAC adsorbers. DOI: 10.1061/(ASCE)EE.1943-7870.0000145 CE Database subject headings: Activated carbon; Adsorption; Water treatment; Organic matter; Granular media. Author keywords: Activated carbon treatment; Water treatment; Models; Natural organic matter.

Temperature differences have been attributed to differences in seasonal changes in removal of natural organic matter (NOM) by drinking water biofilters. Bench-scale sand biofilters treating NOM isolated from a surface water source were operated in parallel at 5, 20, and 35 degrees C to isolate the effect of temperature from other parameters.

A study of nanofiltration foulants found that pretreatment of surface water fouled with mainly biological matter could produce better results than simply using chemical cleaning techniques on the membrane. The prevention of the deposition of the cells in feedwater can be obtained by pretreatment. Chemical treatment seemed to cause morphological changes in the biofilm while failing to reduce its thickness.

Investigations into the nature of nanofiltration foulants showed that the film of foulants is of biological in nature and can be prevented more successfully by feedwater pretreatment than chemical cleaning of the fouled membrane. Studies showed that the film can only be removed by alkaline/detergent cleaning and that flux can be restored without removing the film by the pretreatment of feedwater to reduce the chances of microbial growth.

The study characterized the microbial community found in biological filters used in the treatment of drinking water from the Ohio River. Depth profiles were also constructed for the microbial community structures using phospholipid fatty acid analysis. Fingerprinting by arbitrarily primed polymerase chain reaction as well as assessments of carbon source utilization patters were also performed. Preozonation and filter depth served as the basis for the differentiation of microbial communities from the profiles collected.

The Sequence Optimizer for Wastewater Treatment, employing fuzzy sets and heuristic search in its operations, provides insight on versatile methods to clear wastewater of chemical contamination. The fuzzy sets develop relationships between treatment strategies and waste-stream pollutants, following which the heuristic approach provides details on cost-effective treatment methods of purifying wastewater.