Odor Allocation / Attribution Using Ultra-low Real Time Analytical Capability and Deep Data Analysis to Fingerprint Facilities
The city of Milpitas, California had been receiving over 1200 odor complaints each year to the local Air Quality Management District (AQMD). For the previous four years, The Bay Area Air Quality Management District (BAAQMD) had engaged the services of an environmental engineering firm to do a full-scale odor panel test consisting of panels, nasal rangers, and MS bag analysis. The final results of this testing resulted in the creation of an odor “blob” map that indicated that all local facilities were producing offensive odors. The study data was inconclusive.
The BAAQMD hired Montrose to work with the incumbent environmental engineering firm to analyze the ambient air quality of the Milpitas area, and to determine which facilities were producing specific odor plumes, and to identify the types of odors found and the facility (or facilities) responsible
Due to the unique meteorological and geographic conditions of the area, plumes would build up during the early morning and evening hours when the winds would shift – allowing numerous odor plumes to enter the city. Possible sources for odorous plumes were a landfill, wet fermentation food waste compost facility and a 110M gallon per day wastewater treatment plant – all located adjacent to a large tidal estuary west of the city. All these locations have the potential to produce offending odors with different characteristics. To date, no one had been able to accurately track each emissions source and identify it with any degree of accuracy.
Montrose began analysis by using real-time ambient air testing with a Proton Transfer Reaction Time of Flight Mass Spectrometry (PTR-TOF-MS) mobile laboratory van with 1 second data acquisition and meteorological (MET) station and a Global Positioning Systems (GPS) (The MET and GPS was utilized to ensure that testing was downwind of facilities and to map roadways vs plumes in real-time). Bag samples were taken from each process in all facilities and the estuary in addition to fenceline monitoring of each facility to develop an accurate “fingerprint”. Data analysis from the facilities resulted in the tracking and documentation of over 550 individual compounds in real time to low part per trillion levels. To provide additional data, the mobile lab traveled throughout the city and collected samples overnight around receptors of interest (City parks and schools) – collecting over 1 terabyte of data.
All the collected data was fed into a Sartorius Multivariate Analysis (MVA) software using Principle Component Analysis (PCA) to accurately determine where the compounds in detected plumes came from and the exact process in the facility. Data showed each plume from the facilities was statistically unique, allowing for the direct attribution of the source of the plume to the facility and process. Additionally, the research identified a source of odor from an estuary drainage pipe that was producing large amounts of reduced sulfurous compounds that no one was aware of its operation. This discovery was made possible by simply mapping streets at 40 ft intervals while conducting sampling.
This detailed analysis helped pinpoint which facility was responsible for each odor complaint and assisted in developing a model that allows bag samples to be obtained during an odor event that can be used for analysis and allocation.