Odor control masterplanning using real life data and tailored tools allows development of strategic plan compliance roadmap

Cognizant that odors are caused by various compounds besides hydrogen sulfide (H2S), Orange County Sanitation District (OCSD) embarked on a detailed analysis of all plant process areas determining the top odorants at its Plant No.1 (P1) and Plant No.2 (P2). Top odorants were identified based on their prevailing concentrations, sensory response, and relative intensities at each location. Once identified, they were repetitively monitored to improve result precision, along with continuous monitors and operational variables to ascertain worst-case scenario concentrations. Using the Weber-Fechner relationship between each odorant concentration and their perceived intensity, the maximum nuisance fenceline concentrations were determined.This masterplan is unique in three key areas. First, instead of the traditional primary focus on H2S or dilutions-to-threshold (D/T) indicators, this effort focused on identifying key odorants as identified by a combination of chemical and sensory methods. Second, air dispersion modeling focused on diurnal and seasonal emissions rates to better simulate real-life plant odor impacts. Third, a one-of-a-kind pilot unit was employed for testing multiple technologies operated under varying operating conditions for determining removal performance of the key odorants. This paper presents a complete record of all work completed for Master Plan development including the unique approaches, technology pilot test results, road-mapping techniques and Capital Improvement Project (CIP) requirements for each mitigation level.Chemical analyses included reduced sulfur, amines, ammonia, and carboxylic acids. Sensory methods included D/T and R/T, as well as the Odor Profile Method (OPM) completed at the University of California, Los Angeles (UCLA). The following nine odorants, along with their odor characteristic constitute the basis of this effort:H2S: Rotten EggMethyl Mercaptan (MM): Rotten VegetableDimethyl Disulfide (DMDS): Rotten GarlicDimethyl Sulfide (DMS), low concentration: Canned CornAmmonia (NH3): Pungent2-Methyl Isoborneol (MIB): Musty2-Isopropyl-3-Methoxypyrazine (IPMP): MustySkatole and Indole: FecalTo determine the best technology or combination of technologies to treat the “most detectable” odorants to levels that are below nuisance concentrations, the project included the following tasks:Analysis of existing OCSD odor data and additional sampling for gaps fillingAir dispersion modelingDetermination of odorants' target concentrationsFoul air treatment pilot testing and engineering of required systems to meet target concentrationsEstimation of the cost to achieve certain levels of serviceAERMOD and CALPUFF models were used to predict offsite odor impacts and dilution ratios pertaining to all sources. Source input emission rates were developed using actual emission rates with application of appropriate diurnal and seasonal correction factors. Weber-Fechner intensity curves for each of the nine odorants were used to determine the required maximum fenceline concentrations pertaining to an intensity score of 3 by the OPM. By determining each odorant's particular target maximum source odorant concentrations (before it becomes a nuisance) through modeling, it was possible to determine which odorants would require abatement at each odorous plant process area.A 5-month long pilot testing of selected, most promising vapor phase technologies was conducted under different operations modes, operating conditions and challenge conditions using an on-site pilot testing rig placed at P2 Trunklines. Inlet and outlet samples from each vessel were analyzed for the concentrations of the nine odorants, OPM, D/T and R/T, and odor intensity values.The following are findings and key conclusions that are further presented herein along with methodologies utilized and lessons learned as part of the Master Plan development at OCSD:The OPM is an effective means for determining the concentrations of key odorants at a WWTP that may otherwise go undetected using traditional means (e.g. below their method reporting limit). D/T analysis is a good indicator of the total odor of a sample and should be used with OPM to obtain a complete description of the possible odorants present.OPM in conjunction with broad spectrum gas chromatography sniff analysis helps identify the key odorants present in samples and to direct further efforts to identify hard to detect odorants (e.g. fecal and musty odorants).Utilizing WWTP trending data is a useful means for developing seasonal and diurnal correction factors to be applied to grab sample analytical results.Reactive (H2S) or “sticky” (fecal) odorants can exhibit considerable decay rates that should be taken into account when quantifying odorant values. Quality assurance work associated with ad/absorption to bag material and decay rates pertaining to musty and fecal odorants allowed development of structured QA/QC procedures for sampling, sample handling and analysis.Use of Teflon™ bags was proven necessary to determine the fecal and musty odorants. Fecal and musty samples collected and analyzed using Teflon™ bags allowed improved sample management and analytical measurement repeatability.Dispersion modeling is an effective tool for predicting offsite odor impact risk and target source odorant concentrations.Technology selection is key to ensuring specific odorants are suitably removed. A tailored approach, with technologies selected for specific odorants, must be implemented with a focus on odorant layers. A single technology that is selected for a specific odorant may cause a previously masked odorant to become a nuisance. A multi-stage approach was considered where a matrix of odorants exists.MM is one of the major target odorant among the sulfur compounds and identifying a technology that can substantially reduce it is key to reducing sulfur-based odors.Completed extensive pilot testing conducted with a focus on specific biological, adsorptive, oxidative vapor phase technologies and removal efficiencies pertaining to the nine “most detectable” odorants allowed determination of treatment technology and mitigation level options.Dispersion modeling incorporating the pilot testing results for determining required technologies and technology combinations for meeting fenceline odor goals served as the iteration engine for determination of treatment goals.Estimation of the cost and engineering requirements to meet the mitigation requirements allowed financial planning for CIP planning, as well as to refine the level of service commitments of OCSD.