reconciliation of voc and nox emissions estimates … · tami h. funk steven g. brown ... clinton...
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Reconciliation of VOC and NOReconciliation of VOC and NOxxEmissions Estimates with Ambient Emissions Estimates with Ambient Data in the Houston, Texas RegionData in the Houston, Texas Region
Prepared byPrepared byTami H. FunkTami H. Funk Steven G. BrownSteven G. BrownStephen B. ReidStephen B. Reid Martin P. BuhrMartin P. BuhrPaul T. RobertsPaul T. Roberts Lyle R. ChinkinLyle R. Chinkin
Sonoma Technology, Inc.Sonoma Technology, Inc.Petaluma, CAPetaluma, CA
Presented atPresented atU.S. EPA 13U.S. EPA 13thth Annual Emission Inventory ConferenceAnnual Emission Inventory Conference
Clearwater, FLClearwater, FLJune 9, 2004June 9, 2004
STI-2545
2
IntroductionIntroduction
•• Houston Ship Channel (HSC) is a heavily Houston Ship Channel (HSC) is a heavily industrialized area influenced by large industrialized area influenced by large emissions sources: petroleum refineries emissions sources: petroleum refineries and chemical manufacturing facilitiesand chemical manufacturing facilities
•• VOC emissions from these sources can be VOC emissions from these sources can be difficult to quantify (i.e., flares, fugitive)difficult to quantify (i.e., flares, fugitive)
•• Area and mobile sources are also Area and mobile sources are also significant significant
3
Map of HSC RegionMap of HSC Region
STUDY REGION
4
Point Source Clusters in the HSC RegionPoint Source Clusters in the HSC Region
5
Study ObjectivesStudy Objectives•• Explore innovative methods to assess the Explore innovative methods to assess the
spatial, temporal, and chemical speciation of the spatial, temporal, and chemical speciation of the 2000 HSC emission inventory2000 HSC emission inventory
•• Focus on volatile organic compounds (VOC) Focus on volatile organic compounds (VOC) most likely to contribute to ozone formation (most most likely to contribute to ozone formation (most abundant reactive species): abundant reactive species): acetaldehyde; acetaldehyde; formaldehyde; ethylene; propylene; 1,3formaldehyde; ethylene; propylene; 1,3--butadiene; butadiene; all butenes (butylenes); isoprene; all pentenes; toluene; all butenes (butylenes); isoprene; all pentenes; toluene; all xylenes; all ethyltoluenes; and all trimethylbenzenesall xylenes; all ethyltoluenes; and all trimethylbenzenes
•• Make recommendations on possible Make recommendations on possible improvements to the point source inventoryimprovements to the point source inventory
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Overview of ApproachOverview of Approach•• MultiMulti--task effort utilizing surface task effort utilizing surface andand aircraft data for aircraft data for
2000 and 2001 in the Houston2000 and 2001 in the Houston--Galveston area (HGA)Galveston area (HGA)•• ThreeThree--pronged approach: pronged approach:
•• Data requirements: Data requirements: –– hourly, gridded, and speciated hydrocarbon and NOhourly, gridded, and speciated hydrocarbon and NOxx
emission inventoryemission inventory–– speciated surface hydrocarbon and NOspeciated surface hydrocarbon and NOxx datadata–– speciated aloft hydrocarbon and NOspeciated aloft hydrocarbon and NOxx datadata–– wind speed and direction datawind speed and direction data
SourceApportionment
SurfaceVOC/NOx
Comparisons
AloftVOC/NOx
Comparisons
Recommendationsfor inventory
improvements+ + =
7
What Did We Find?What Did We Find?
•• Total VOC/NOTotal VOC/NOxx ratios ratios underestimated by factors of 2underestimated by factors of 2--1010
•• Most underMost under--representation appears representation appears to be from the industrial segment of to be from the industrial segment of the inventorythe inventory
•• Olefins and aromatics appear to be Olefins and aromatics appear to be underestimatedunderestimated
8
HGA Emission Inventory SummaryHGA Emission Inventory SummaryEmissions by source category for the
HGA region for August 29, 2000
0
50
100
150
200
250
300
350
400
VOC NOx
Emis
sion
s (to
ns/d
ay)
PointAreaNon-road MobileOn-road Mobile
9
HGA Emission Inventory SummaryHGA Emission Inventory SummaryDistribution of VOC sources in the region around
Clinton Drive for 0500-0600 CST
Area18%
Mobile23%
Nonroad3% Low-Level
47%
Points56%
Elevated9%
~ 500 km2 region centered at monitoring site
10
TopTop--Down Reconciliation Method Down Reconciliation Method (1 of 2)(1 of 2)
•• Ambient DataAmbient Data–– QualityQuality--assuranceassurance–– Ambient data segregated by time period to include Ambient data segregated by time period to include
data for 0500data for 0500--0900 CDT sampling periods for 0900 CDT sampling periods for weekdays (to minimize photochemical reactions and weekdays (to minimize photochemical reactions and focus on fresh emissions)focus on fresh emissions)
•• Meteorological DataMeteorological Data–– Determines average wind speeds and predominant Determines average wind speeds and predominant
wind directions for 0500wind directions for 0500--0900 CST period0900 CST period–– Determines the spatial extent of the ratio analysesDetermines the spatial extent of the ratio analyses–– Identifies the sources that are most likely to impact Identifies the sources that are most likely to impact
the ambient monitorthe ambient monitor
11
TopTop--Down Reconciliation Method Down Reconciliation Method (2 of 2)(2 of 2)
•• Emissions InventoryEmissions Inventory–– Chemical species in the emission inventory Chemical species in the emission inventory
were matched to the ambient data were matched to the ambient data
–– Emissions were converted from a mass to a Emissions were converted from a mass to a molar basis to compare to the ambient data molar basis to compare to the ambient data reported in ppbC
Hundreds ofspecies reported
in inventory
Speciesmeasured
byAuto-GC
= 60 – 70% mass
reported in ppbC
12
Emission Inventory Emission Inventory –– Ambient ComparisonAmbient ComparisonHourly TNMOC/NOx ratios by site
Clinton 2000
012345678
5 6 7 8 9
Hour
TNM
OC
/NO
x R
atio
Ambient - Avg
Ambient - Median
EI - Low LevelOnly
EI - With ElevatedSources
Clinton 2001
0
2
4
6
8
5 6 7 8 9
Hour
TNM
OC/
NOx
Ratio
Ambient - Avg
Ambient - Median
EI - Low LevelOnly
EI - With ElevatedSources
Deer Park 2001
0
5
10
15
20
5 6 7 8 9
Hour
TNM
OC
/NO
x R
atio
Ambient - Avg
Ambient - Median
EI - Low LevelOnly
EI - With ElevatedSources
Haden 2001
02468
10121416
5 6 7 8 9
Hour
TNM
OC/
NO
x R
atio
Ambient - Avg
Ambient - Median
EI - Low LevelOnly
EI - With ElevatedSources
13
Emission Inventory Emission Inventory –– Ambient ComparisonAmbient Comparison
Relative composition of species groups by siteClinton 2000
0%20%40%60%80%
100%
Ambient -Avg
Ambient -Median
EI - LowLevel Only
EI - WithElevatedSources
Data Source
TNM
OC
Wei
ght % Unidentified
AromaticsOlefinsParaffins
Clinton 2001
0%20%40%60%80%
100%
Ambient -Avg
Ambient -Median
EI - LowLevel Only
EI - WithElevatedSources
Data Source
TNM
OC
Wei
ght % Unidentified
AromaticsOlefinsParaffins
Deer Park 2001
0%20%40%60%80%
100%
Ambient -Avg
Ambient -Median
EI - LowLevel Only
EI - WithElevatedSources
Data Source
TNM
OC
Wei
ght % Unidentified
AromaticsOlefinsParaffins
Haden 2001
0%20%40%60%80%
100%
Ambient -Avg
Ambient -Median
EI - LowLevel Only
EI - WithElevatedSources
Data Source
TNM
OC
Wei
ght % Unidentified
AromaticsOlefinsParaffins
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Emission Inventory Emission Inventory –– Ambient ComparisonAmbient ComparisonRelative species composition for Deer Park (northeast)
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
Etha
ne
Eth
ylen
eP
ropa
ne
Prop
ylen
eIs
obut
ane
1,3-
buta
dien
e
n-Bu
tane
Ace
tyle
ne
C4
olef
ins
C5
para
ffins
isop
rene
C5
olef
ins
C6
para
ffins
met
hyl
hexe
nes
C7
para
ffins
C8
para
ffins
tolu
ene
benz
ene
ethy
lben
zene
xyle
nes
styr
ene
n-no
nane
/C9
C3/
C4/
C5
n-de
cane
/C10 n-
TNM
OC
Wei
ght%
Ambient - Avg
Ambient -Median
EI - Low LevelOnly
EI - WithElevatedSources
PropanePropylene
Benzene
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
Etha
ne
Eth
ylen
eP
ropa
ne
Prop
ylen
eIs
obut
ane
1,3-
buta
dien
e
n-Bu
tane
Ace
tyle
ne
C4
olef
ins
C5
para
ffins
isop
rene
C5
olef
ins
C6
para
ffins
met
hyl
hexe
nes
C7
para
ffins
C8
para
ffins
tolu
ene
benz
ene
ethy
lben
zene
xyle
nes
styr
ene
n-no
nane
/C9
C3/
C4/
C5
n-de
cane
/C10 n-
TNM
OC
Wei
ght%
Ambient - Avg
Ambient -Median
EI - Low LevelOnly
EI - WithElevatedSources
PropanePropylene
Benzene
15
Source Apportionment MethodSource Apportionment Method
Source apportionment gives another view of Source apportionment gives another view of ambient data to compare to inventory:ambient data to compare to inventory:
–– How are the mix of source types in the ambient data How are the mix of source types in the ambient data apportioned compared to the inventory?apportioned compared to the inventory?
–– What is the magnitude of each source type in What is the magnitude of each source type in ambient data compared to inventory?ambient data compared to inventory?
–– What species in which source type appear to be What species in which source type appear to be underunder-- or overestimated in the inventory?or overestimated in the inventory?
–– Can significant sources that are not in inventory be Can significant sources that are not in inventory be identified and quantified?identified and quantified?
16
Positive Matrix Factorization (PMF)Positive Matrix Factorization (PMF)
•• As a multivariate receptor model, PMF As a multivariate receptor model, PMF requires the input of data from multiple requires the input of data from multiple samples and extracts the source samples and extracts the source apportionment information from all the apportionment information from all the sample data simultaneously.sample data simultaneously.
•• PMF requires ambient data only PMF requires ambient data only (species (species x x time) time) –– no source profiles.no source profiles.
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Source Apportionment MethodSource Apportionment Method
•• Hourly speciated VOC data for summer Hourly speciated VOC data for summer 2001 at three sites (>700 samples at each 2001 at three sites (>700 samples at each site site –– larger sample size generally gives larger sample size generally gives better results)better results)
•• Only nighttime data used to avoid Only nighttime data used to avoid photochemistry and to focus on fresh photochemistry and to focus on fresh industrial emissions (mixing heights industrial emissions (mixing heights are low)are low)
•• Analyzed results by wind direction, day of Analyzed results by wind direction, day of week, hourweek, hour
18
Example PMFExample PMF--derived Profile derived Profile ––Motor VehicleMotor Vehicle
Clinton Drive - Motor Vehicle Factor Profile
0
20
40
60
80
100
ETH
AN
ETH
YL
PR
OP
AP
RP
YL
ISB
TAV
13BU
TAN
BU
TAA
CE
TYT2BTEIS
PN
AN
PN
TAT2P
NE
V22D
MB
V2M
PN
AIS
PR
EN
HE
XA
V24D
MP
BE
NZ
CY
HX
AV
2MH
XA
V224TM
PN
HE
PT
MC
YH
XTO
LUV
2MH
EP
NO
CT
EB
EN
ZM
_PX
YN
NO
NN
PB
ZM
ETO
LV
135TMB
OETO
LV
124TMB
ND
EC
V123TM
BN
UN
DC
UID
VO
CR
elat
ive
Load
ing
by S
peci
es (%
)
Acetylene
Benzene
Xylenes Eth-benzene
224-trimethylpentane
Toluene
19
Example Time SeriesExample Time Series
Clinton Drive - Motor Vehicle Factor Strength
0
5
10
15
20
25
30
35
40
45
7/4/
01
7/11
/01
7/18
/01
7/25
/01
8/1/
01
8/8/
01
8/15
/01
8/22
/01
8/29
/01
9/5/
01
9/12
/01
9/19
/01
9/26
/01
10/3
/01
10/1
0/01
10/1
7/01
10/2
4/01
10/3
1/01
Fact
or s
treng
th -
ppbC
Examine temporal variation in factor:• Weekday –
weekend• Time of day• Season• Similar to
inventory?
20
Wind Direction AnalysisWind Direction Analysis
• Use Conditional Probability Function (CPF) to isolate area of influence
• Example: Motor vehicle
• Most influence from freeways to northwest, similar to inventory
0.000.200.400.600.801.00
022.5
45
67.5
90
112.5
135157.5
180202.5
225
247.5
270
292.5
315337.5
0.000.200.400.600.801.00
022.5
45
67.5
90
112.5
135157.5
180202.5
225
247.5
270
292.5
315337.5
21
Source Apportionment ResultsSource Apportionment Results
•• Identified and quantified between 7 and 11 Identified and quantified between 7 and 11 factors at each sitefactors at each site
•• Wind direction analysis results were Wind direction analysis results were consistent with spatial distribution of sources consistent with spatial distribution of sources in emission inventoryin emission inventory
•• Composition of VOCs by factor similar to Composition of VOCs by factor similar to inventory, but some major differences noted:inventory, but some major differences noted:–– Mobile sources appear to be better represented Mobile sources appear to be better represented
than industrial sources than industrial sources –– Propene significantly underestimated at all sitesPropene significantly underestimated at all sites–– Light olefins underestimated near selected Light olefins underestimated near selected
sourcessources
22
Aircraft MethodologyAircraft Methodology
•• Collected VOC canisters within emission Collected VOC canisters within emission plumesplumes–– NONOxx/NO/NOyy ratio analysis to assess the ratio analysis to assess the
photochemical age to gain a better understanding photochemical age to gain a better understanding of the change in the observed VOC/NOof the change in the observed VOC/NOxx ratio with ratio with photochemical processing timephotochemical processing time
•• Flight data paired with wind direction and Flight data paired with wind direction and VOC resultsVOC results
•• Based on spatial examination, a group of Based on spatial examination, a group of point sources were identified as influencing point sources were identified as influencing each sampleeach sample
23
Aircraft Data CollectionAircraft Data Collection
24
Aircraft Analysis ResultsAircraft Analysis Results
Principal source Emission Inventory ΣVOC/NOx
Observed ΣVOC/NOy
Ratio of observed to
expected emissions
Chevron Phillips Chemical Co LP - 0145
Average= 0.588 Std. Deviation=0.004
Average= 14.7 Std. Deviation= 9.0 25.0
The Dow Chemical Co - 0041 Average= 0.131 Std. Deviation= 0.013
Average= 3.8 Std. Deviation= 3.8 29.0
Sterling Chemicals Inc - 0010 Average= 0.865 Std. Deviation=0.000
Average= 7.1 Std. Deviation= 4.2 8.2
Shell Oil Co - 0039 Average=1.123 Std. Deviation= 0.191
Average= 7.2 Std. Deviation= 6.1 6.4
Oil Tanking Houston Inc - 0277
Average= 19.154 Std. Deviation=0.020
Average= 9.8 Std. Deviation=10.7 0.5
Hoechst Celanese Chemical Group, Inc. - 0003
Average= 0.198 Std. Deviation= 0.015
Average= 8.5 Std. Deviation= 7.9 42.9
EXXON MOBIL Chemical Co – 0014
Average=0.896 Std. Deviation=0.340
Average= 8.8 Std. Deviation= 5.1 9.8
Equistar Chemicals LP - 0075 Average=0.782 Std. Deviation= 0.162
Average= 5.2 Std. Deviation= 3.5 6.6
BP Solvay Polyethylene N. America - 0004
Average= 2.548 Std. Deviation=0.937
Average= 6.1 Std. Deviation= 2.7 2.4
25
Aircraft Analysis ResultsAircraft Analysis Results
•• VOC/NOVOC/NOxx ratios appear to be ratios appear to be underestimated in the emission inventory underestimated in the emission inventory by factors ranging from 2 to 43by factors ranging from 2 to 43
•• Alkenes/NOAlkenes/NOxx ratios appear to be ratios appear to be underestimated by factors ranging from underestimated by factors ranging from 3 to 643 to 64
•• Aromatics/NOAromatics/NOxx ratios appear to be ratios appear to be underestimated by factors ranging from underestimated by factors ranging from 3 to 203 to 20
26
Integrated ConclusionsIntegrated Conclusions•• Multiple methods for reconciling the emission Multiple methods for reconciling the emission
inventory were extremely effective and gave inventory were extremely effective and gave good consensusgood consensus
•• Total VOC/NOTotal VOC/NOxx ratios appear to be ratios appear to be underestimated by up to an order of underestimated by up to an order of magnitude (mostly near industrial sources)magnitude (mostly near industrial sources)
•• Olefins appear to be underestimated by a Olefins appear to be underestimated by a factor of 2 to 5, and by 3 to 64 for a single factor of 2 to 5, and by 3 to 64 for a single sourcesource
•• Aromatics also appear to be underestimated Aromatics also appear to be underestimated by a factor of 2 to 5 and from 3 to 20 for a by a factor of 2 to 5 and from 3 to 20 for a single sourcesingle source
27
AcknowledgmentsAcknowledgments
•• Research sponsored by the Houston Research sponsored by the Houston Advanced Research Center (HARC)Advanced Research Center (HARC)
•• HARC contract managers Dr. Jay HARC contract managers Dr. Jay Olaguer and Ms. Anne Brun Olaguer and Ms. Anne Brun
•• The Texas Commission on The Texas Commission on Environmental Quality (TCEQ) provided Environmental Quality (TCEQ) provided the emission inventory data and supportthe emission inventory data and support