1. Biogenic Emissions in Southeast Texas
Ji Hee Song
Environmental and Water Resources Engineering
University of Texas at Austin

2. Outline Characteristics of Isoprene Meteorological data
from the TexAQS 2000 episode
Biogenic emission model
Time varying distribution of Isoprene emissions
Comparison of emission by different model version
My first task was to see the performance of CAMx model, comparing with observed data from NOAA aircraft.
The time period of my interest was from August 25 to September 1 in 2000.

3. Isoprene Highly reactive hydrocarbon
Mostly emitted by trees and plants
; oaks, popular, etc.
Isoprene + NOx
 Ozone formation

4. GloBEIS 3.0 (Global Biosphere Emissions and Interactions System version 3.0)

5. Inputs to GloBEIS 3.0 Meteorology based on MM5 outputs
Satellited based cloud cover data
Texas specific landcover data

6. Hourly Biogenic Emissions in tons Strongly related to sunlight
year
day
hour
Isoprene
TMT
OVC
NOx
2000
238 31 22
2.5 1 30 2 29 21
2.4 3 20 4 28 5 27 19
2.3 6 26 7 73 8
147 39
2.6 9
206 44
2.8 10
253 48 34
2.9 11
292 52 37
3.1 12
319 55
3.3 13
328 57 40
3.4 14
316 41
3.5 15
290 58
3.6 16
234 17
146 18 53 47 33 42 38 35 25
2.7 23 24
Daily Totals
2603
999
713
68.6
Hourly Biogenic Emissions in tons Strongly related to sunlight
For the temperature and cloud cover sensitivity, modified GloBEIS 2 was used.
First the temperature,

7. Distribution on the ArcMap
Isoprene emissions
w/ Graduated colors
Units : g/each cell

8. Hourly Based Isoprene Distribution
7:00 am
12:00 pm
However, these four graphs show that varied temperature and cloud cover input data don’t shift the result much.
Which indicates that the isoprene concentration is not very sensitive to temperature and cloud cover.
3:00 pm
5:00 pm

9. Comparison of model results (GloBEIS 3.0 vs. Modified GloBEIS 2.0)
Older version of GloBEIS underpredicted the isoprene emissions
The conclusion.
Model is well predicted the isoprene concentration, however, the discrepancy is due to the meteorological data such as rapid changing wind direction.
And anthropogenic sources, which can not be predicted by the model.
And certain types of landcover data.

10. Special Thanks to..
Dr. David Maidment from University of Texas, Austin
Dr. David T. Allen from University of Texas, Austin
Alex Guenther from NCAR
Christine Wiedinmyer from NCAR
Mark Estes from ENVIRON
Yosuke Kimura from University of Texas, Austin
Matt Russell from University of Texas, Austin
Gary McGaughey from University of Texas, Austin
Special thanks to …

11. Questions?