reconciliation of voc and nox emissions estimates … · tami h. funk steven g. brown ... clinton...

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

6

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


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


Haden 2001

02468

10121416

5 6 7 8 9

Hour

TNM

OC/

NO

x R

atio

Ambient - Avg

Ambient - Median

EI - Low LevelOnly


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


Data Source

TNM

OC

Wei

ght % Unidentified


Deer Park 2001

0%20%40%60%80%

100%

Ambient -Avg

Ambient -Median

EI - LowLevel Only


Data Source

TNM

OC

Wei

ght % Unidentified


Haden 2001

0%20%40%60%80%

100%

Ambient -Avg

Ambient -Median

EI - LowLevel Only


Data Source

TNM

OC

Wei

ght % Unidentified


14

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


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


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.

17

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


Sterling Chemicals Inc - 0010 Average= 0.865 Std. Deviation=0.000


Shell Oil Co - 0039 Average=1.123 Std. Deviation= 0.191


Oil Tanking Houston Inc - 0277


Average= 9.8 Std. Deviation=10.7 0.5

Hoechst Celanese Chemical Group, Inc. - 0003

Average= 0.198 Std. Deviation= 0.015


EXXON MOBIL Chemical Co – 0014

Average=0.896 Std. Deviation=0.340


Equistar Chemicals LP - 0075 Average=0.782 Std. Deviation= 0.162


BP Solvay Polyethylene N. America - 0004



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

reconciliation of voc and nox emissions estimates … · tami h. funk steven g. brown ... clinton...

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