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Project Number:
 
14-003
Title:
 
Update and evaluation of model algorithms needed to predict Particulate Matter from Isoprene
Lead PI:
 
William Vizuete
Institution(s) Represented:
 
University of North Carolina - Chapel Hill - William Vizuete
AQRP Project Manager:
 
Elena McDonald-Buller
TCEQ Project Liaison:
 
Jim Price
Awarded Amount:
 
$200,000.00

Abstract
Update and evaluation of model algorithms needed to predict
Particulate Matter from Isoprene
 
Terrestrial vegetation emits into the atmosphere large quantities (~500 teragrams C) of the reactibe diolefin isoprene (C5H8). Isoprene emissions in eastern Texas and northern Louisiana are some of the largest in the United States. Photochemical oxidation of isoprene leads to significant yields of gas-phase intermediates that contribute to fine particulate matter (PM2.5). The production of isoprene-derived PM2.5 is enhanced when mixed with anthropogenic emissions from urban areas like those found in Houston. To predict PM production from isoprene requires fundamental parameters needed to describe the efficiency with which gas phase intermediates react on the surface of atmospheric particles. Recently, EPA updated a regulatory chemical mechanism to include the formation of these new gas-phase isoprene-derived intermediates.  Furthermore, the project investigators recently collaborated with the EPA to update the CMAQ model to predict isoprene-derived PM explicitly across the eastern US. This updated gas- and aerosol-phase framework found in CMAQ remains to be validated against systematically conducted chamber experiments. Thus, we first propose to conduct a series of new experiments at UNC to quantitatively measure the reactive uptake of the two predominant isoprene-derived gas phase intermediates to PM of different inorganic compositions. By providing these new fundamental measurements, we will be able to more directly evaluate the aerosol-phase processes added to the model. This work will produce a model evaluation of isoprene SOA formation against existing UNC outdoor smog chamber experiments. This project will also deliver performance data needed to bound uncertainties in key parameters used by CAMx to predict isoprene derived PM.  This work directly addresses the stated priority area of investigating the transformation of gas-phase pollutants to particulate matter that impact Texas air quality.




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