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Development of Mobile Tracer Correlation Strategies for Quantification of Emissions from Landfills and Other Large Area Sources
Citation:
Footer, T. AND E. Thoma. Development of Mobile Tracer Correlation Strategies for Quantification of Emissions from Landfills and Other Large Area Sources. Air & Waste Management Association Conference on Air Quality Measurement Methods and Technology, Durham, NC, April 24 - 26, 2012.
Impact/Purpose:
Visuals for conference. See cleared extended abstract Tracking # ORD-00219
Description:
Emission measurements from large area sources such as landfills are complicated by their spatial extent and heterogeneous nature. In recent years, an on-site optical remote sensing (ORS) technique for characterizing emissions from area sources was described in an EPA-published preliminary test method called OTM 10. Although the ORS techniques and instruments discussed in OTM 10 are powerful in approach, they can be somewhat expensive to deploy. It also can be difficult in some cases to piece together many on-site measurements to provide a complete picture of facility emissions. As part of EPA’s Geospatial Measurement of Air Pollution (GMAP) program, a mobile tracer correlation approach is being developed to provide whole-facility emission measurements from landfills and other areas sources. This approach, called GMAP Remote Emissions Quantification by Tracer Correlation (REQ-TC), uses sensitive spectroscopic instruments mounted on a mobile platform to simultaneously measure methane (CH4) and a tracer gas, such as acetylene (C2H2), at distances up to 2 km from the site. The GPS-enabled, instrumented vehicle allows a rapid “snapshot” emissions measurement of the entire landfill to be executed providing complimentary data to on-site measurements while being comparatively easy and cost effective to execute. This abstract summarizes current efforts to develop the GMAP-REQ-TC method which builds on published studies but uses novel instrumentation such as cavity ring-down spectroscopy (CRDS)to improve the robustness and implementation viability of the approach.