AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
Abstract View
A Meta-Analysis of Black Carbon Emissions from Fire-Prone Ecosystems in the United States
ANDREW MAY, Hanyang Li, Robert J. Yokelson, Gavin McMeeking, The Ohio State University
Abstract Number: 466 Working Group: Biomass Combustion: Emissions, Chemistry, Air Quality, Climate, and Human Health
Abstract Wildland and prescribed fires affect several ecosystems in the United States (US) including the montane forests and chaparral regions in the west and forests and coastal plains of the southeast. These fires can produce large amounts of atmospheric black carbon (BC), but BC emissions estimates are subject to large variability, because instruments that quantify black carbon are operationally different and any given fire is inherently unique. Some of our recent work has focused on constraining instrument differences, but here, our main interest is the “natural” variability of fires. We have sampled roughly 30 different journal publications to develop a dataset comprising both laboratory and field estimates of BC emission factors (EFBC) derived from different techniques for the aforementioned ecosystems, including thermal-optical, light absorption, and incandescence.
There appears to be large variability in reported EFBC values for these ecosystems in the literature with coefficients of variation ranging from 56% to 96% in the laboratory and 14% to 74% in the field. If we account for instrument differences, these ranges are only slightly different (57% to 77% and 14% to 78%, respectively), which is remarkable considering that we estimate the average relative difference between instrument to be roughly 45%. These results suggest that even though the relative difference between two measurement techniques may appear large, this effect may be dampened when compiling EFBC values from different studies for use in emission inventories, and consequently, instrument differences may result in a relatively small contribution to overall uncertainty of fire-related BC in chemistry-climate models.