Project


Title

Synthesis of Comprehensive Emissions Measurements and Multi-Scale Modeling for Understanding Secondary Organic Qerosol Chemistry in Wildland Smoke Plumes
Principal Investigator(s):
  • Kelley C. Barsanti
    University of California-Riverside
Co-Principal Investigator(s):
  • Serena H. Chung
    Washington State University
  • Brian K. Lamb
    Washington State University
  • Robert J. Yokelson
    University of Montana
Completion Date: October 9, 2018

Cataloging Information

Keyword(s):
  • air quality
  • biomass burning
  • PM2.5
  • secondary organic aerosol
  • smoke plumes
  • VOC - volatile organic compounds
JFSP Project Number(s):
14-1-03-44
Record Maintained By:
Record Last Modified: November 20, 2019
FRAMES Record Number: 56787

Description

The air quality and fire management communities are faced with increasingly difficult decisions regarding critical fire management activities, given the potential contribution of wildfires and prescribed burns (wildland fires) to fine particulate matter (PM2.5). Unfortunately, in model frameworks used for air quality management, the ability to represent PM2.5 from biomass burning (BB) is severely limited. Particularly uncertain is the formation of secondary organic aerosol (SOA) in BB smoke plumes. This is due in large part to incomplete identification and quantification of the compounds emitted from fires and the mechanisms by which they form SOA under ambient conditions. Thus there is great need for improved emissions inventories and validated smoke models in air quality modeling frameworks that better capture (semi-) volatile (S/VOC) emissions and formation and aging mechanisms, as a function of fuel type and burn characteristics. We have assembled a uniquely qualified team with expertise in fire emissions, SOA modeling, chemical transport modeling, and atmospheric chemistry to: 1) provide improved EFs for wildland fuels with an emphasis on those critical to understanding SOA; 2) develop a detailed model to accurately represent SOA in smoke plumes; and 3) use the detailed model as a tool, along with measurements, to implement and deliver an operational modeling frameworkaccessible to air quality and land managerswith an improved ability to predict SOA formation, and thus PM2.5, from wildland fires. These goals will be achieved through the following objectives: 1. Identify and quantify S/VOC emissions from selected conifer, shrub, and grass species. 2. Quantify SOA formation potentials for S/VOCs of interest, and identify the most relevant precursors and reaction mechanisms for SOA formation and aging. 3. Evaluate sensitivity of SOA formation to uncertainties in emissions, including as influenced by burn characteristics. 4. Modify the AIRPACT framework to include the most relevant SOA precursors and formation and aging mechanisms. 5. Evaluate implementation of improvements in AIRPACT using satellite products and field data. 6. Identify priorities for future measurement and modeling efforts, including by comparing calculated emission factors with NEI emission factors. The proposed work thus addresses each of the research questions outlined in Task 3 Contribution of smoke emissions to secondary organic aerosols. We propose to use FLAME-IV (4th Fire Lab at Missoula Experiment) laboratory data, BBOP (Biomass Burning Observation Project) field data, and multi-dimensional modeling to complete the project objectives. FLAME-IV yielded the most complete gas-phase measurements of BB smoke to date, including the first application of comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC×GC/TOFMS), along with other complementary techniques. Synthesis of the FLAME-IV emissions data will yield new insights into the gas-phase precursors that contribute to BB-SOA and allow publication of a comprehensive emission-factor (EF) database for wildland-relevant fuels. Using the EFs generated from the FLAME-IV data, we propose to develop and apply a process-level box model that explicitly describes the reactions leading to SOA formation and aging. The box model will be used to identify high-priority S/VOCs and formation/aging mechanisms, including those needing further study, and to develop simplified parameterizations for inclusion in the AIRPACT air quality framework. Using AIRPACT we propose to evaluate the contributions of BB to SOA in the Pacific Northwest and to document the magnitude of change in SOA and PM2.5 in the Western US relative to the standard NEI 2011 inventory. EFs and AIRPACT predictions will be validated using BBOP field data.