Mobile Monitoring to Locate and Quantify Open Source Emission Plumes August 7, 2013 by Chatten Cowherd, Ph.D.
Presentation Outline Importance of open sources of air pollutants Measurement and modeling challenges Deficiencies in current assessment tool kit Progressive quantification using low-cost screening methods for tiered application Mobile monitoring as an effective tool for locating and quantifying open source emissions Conclusions 2
Source Definition Open sources releases are by definition unconfined (non-ducted) in nature Gaseous emissions that occur as leaks from confined process flows are included Open sources also include conglomerations of scattered ducted sources for which individual characterization is not feasible, as in roadway traffic 3
Example Open (Non-Ducted) Sources Dust releases from soil disturbance (vehicles and wind) Public roads Open pit mines Desert high winds Wildfires Regulated gas emissions (e.g. GHGs) Area sources Processing leaks 4
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Difficult to assess: Multi-gas emissions Spatially complex Temporally variable
Convention Air Pollution Control Designed for applicability to ducted sources Easily identifiable fixed locations Relatively steady emissions Well developed assessment tools apply mostly to point and uniform area sources Emission measurement Dispersion modeling Validation protocols supported by USEPA 7
Idealized Dispersion as Basis for Plume Models 8
Source Complexities in Open Pit Mine Moving point sources of varying intensity 9
Open Source Emission Testing Challenges High natural variability (spatial and temporal) Variations in source location Variations in emission rate Lack of plume containment Plume development influenced by turbulence and buoyancy Plume transport affected by flow obstacles Similar challenges for dispersion modeling and impact assessment 10
Open Source Test Methods Method Name Monitor Location Platform Monitor Configuration Plume (flux) profiling Inverse modeling Plume transect monitoring Within plume flux plane downwind of source Fixed Mobile Samplers at multiple heights (tower) Samplers distributed laterally at one height Vehicle-mounted at one sampling height Lateral scanning From remote position outside plume Fixed Standoff detection (path integrating) 11
Plume (Flux) Profiling: Accepted Reference Profiling tower(s) deployed immediately downwind from source edge Multipoint plume measurements versus height Mass concentration Wind speed Flux = concentration X wind speed Requires stable ambient crosswinds Utilizes simple mass balance calculation scheme independent of dispersion modeling 12
Cross-Wind Plume Dynamics (moving point source) 13
Collocated Plume Profilers 14
Reverse-Impact Dispersion Modeling Measure ground-level pollutant concentration across sampling array in ambient impact zone (>50 m downwind) Collect applicable meteorological data (wind speed and direction, atmospheric stability) Apply dispersion model in reverse What emission rate produces the observed air quality impacts? 15
Progressive Quantification An effective strategy for identifying and quantified undocumented open sources, Start with survey methods using mobile platforms Progress to more direct (and expensive) methods as survey results demonstrate source significance 16
New Measurement Technology High-tech options involving fixed platforms and stand-off detection, e.g., fence-line monitoring Best for long term application on fixed sources Infrared cameras for visualizing emissions from flares Suitable for identifying sources but not emission rates Mobile platforms for drive-by scans of plume structure Suitable for survey analysis of source components 17
Fenceline Monitoring with Lateral Scanning 18
Reference Profiling Array for Validating Lateral Scanning Example sampling array for cross-referencing against standoff detection method involving lateral scanning 19
Mobile Monitor for Road Dust Emissivity Mapping Elutriation Tube Cyclone: Coarse PM Trap Sampling Intake 20
Mobile Monitoring--Road Survey 21
Elements of Mobile Monitor Light-duty host vehicle Continuous concentration monitor Sampling line with inlet above vehicle GPS unit for locating monitoring points Data logger 22
Operation of Mobile Monitor Drive when wind conditions are most suitable for consistent plume transport Moderate wind speeds (5 to 12 mph) Consistent wind direction (low meander) Absence of plume lofting (neutral to stable atmospheres) Drive at constant speed until locating plume(s) Perform multiple scans of identified plumes 23
wind direction Example Sampling Configuration (adapted from Thoma, 2012) driving path CH 4 Spike indicates emission plume 24
Idealized Overlapping Plumes 25
Analysis of Plume Scans Isolate significant plumes obtained from mobile monitoring Repeat monitoring for different wind directions Use information to project locations of sources Apply inverse dispersion modeling to bracket emission rates Refine process to improve quantification 26
Conclusions Open sources are receiving increasing attention as contributors to air quality problems Traditional assessment tools are not well suited to addressing open sources Mobile monitoring is an effective survey method to locate and characterize problematic open sources For sources indicated as significant, more refined (and expensive) methods can be applied Check out www.openairsource.org for more information 27