NONROAD Emissions Model Uncertainty Analysis for the State of … · 2015-09-10 · NONROAD...

NONROAD Emissions Model Uncertainty NONROAD Emissions Model Uncertainty Analysis for the State of GeorgiaAnalysis for the State of Georgia

Rosa ChiAlper Unal, Di Tian, Armistead (Ted) Russell

School of Civil & Environmental EngineeringGeorgia Institute of Technology

International Emission Inventory Conference, "Working for Clean Air in Clearwater," , Clearwater, FL

7-10 June 2004

Georgia Institute of Technology


0 80 16040 Miles±

LegendCounty Boundaries

AUGUSTA

COLUMBUS

ATLANTA

MACON

• Areas at or near non-attainment means Air Quality Modeling!!

• Understanding emissions uncertainty leads to better understanding of AQM limitations, errors, uncertainties…

Motivation

Fall line Air Quality Study


• Assess urban and regional air pollution, identify the sources of pollutants and pollutant precursors, and recommend solutions to the Augusta, Macon, and Columbus metropolitan areas of Georgia.

Why Nonroad?VOC Emissions

• Significant source of emissions in polluted areas

• EPA NONROAD model is user-friendly, easy to manipulate good for uncertainty analysis!!

NOx Emissions

Georgia Institute of TechnologySource: Fall-line Air Quality Study August 2000 Inventory for 11 counties

Objective

• Quantify uncertainty of emissions from the NONROAD model using a bottom-up, emissions-based approach for the state of Georgia


EPA NONROAD Emissions Model

• Includes over 260 off-road equipment type in source categories: Construction, Lawn & Garden, Industrial, Agricultural, etc.

• Does NOT include: Aircraft, Locomotives, Commercial Marine

Georgia Institute of TechnologyPhotos from www.freefoto.com

NONROAD Emissions Calculations

• EMISSIONS = (Population) x (Rated Power) x (Load Factor) x (Activity) x (Emission Factor)

• Complications:– Geographic allocations– Age distribution– Deterioration– Growth– Scrappage


Emission Factors

Deterioration

ActivityPopulation

Growth

EF Corrections

Geographic Allocation

Conversion Factors

Scrappage

Age Distribution

Emissions

HC Conversions

PM Fractions

Rated Power

Load Factor

Hours per Year

Seasonal/ Monthly

Corrections

Activity Corrections

Weekend/ Weekday

Corrections

Temperature RVP Fuel SulfurOxygenate

Average Life


Methods

• Use 1999 average summer day scenario for Georgia

• Sensitivity analysis of NONROAD

• Expert elicitation of uncertainty of major NONROAD

input parameters

• Monte Carlo uncertainty analysis of NONROAD

emissions output uncertainty


Sensitivity Analysis• Determine sensitivity of NONROAD emissions to

input parameters by: base

base

EP

PPEES ×

−−

=)()(

%90%110

%90%110


-50%

0%

50%

100%

150%

RV

P

Sul

fur

Tem

pera

ture

Pop

ulat

ion

Act

ivity

Load

Fac

tor

Use

ful L

ife

Em

issi

onFa

ctor

**

200%

250% VOC Exhaust

VOC EvapVOC Total

NOxCO

PM2.5CO2

SOx

Emission Factor Bootstrap Analysis• Diesel engine emission test certification data available in

NONROAD documentation for model years 1996 +

• AuvTool (Frey, Zheng; NC State) empirical distribution fits and

bootstrap analysis

• Shows uncertainties due to random sampling errors, but not

errors of representativeness

Model YearAverage -5% 5% -21% 21% -4% 3% -16% 16% -10% 10%Maximum -7% 7% -49% 46% -6% 5% -20% 23% -18% 17%Minimum -2% 2% -4% 4% -2% 2% -8% 8% -4% 4%

HP 95% Confidence

Interval

HC 95% Confidence

Interval

NOx 95% Confidence

Interval

CO 95% Confidence

Interval

PM 95% Confidence

Interval


Expert Elicitation• Focus on experts in nonroad emissions modeling, not

air quality modeling

• Experts self-rate based on experience

• Experts give opinions of uncertainties of NONROAD

input parameters

• Expert opinions aggregated as average of answers

weighted by self-rating


Expert Elicitation

Input Parameter

Most Uncertain 95% Confidence Interval

Least Uncertain 95% Confidence Interval

Population +68%, -25% +29%, -23%Geographic Allocation +194%, -50% +10%, -10%Activity +65%, -38% +22%, -22%Load Factor +37%, -41% +23%, -21%Emission Factor +96%, -29% +16%, -14%

Category


Monte Carlo SimulationGenerate random inputs

PopulationActivity

Load FactorEmission Factor

Geographic Allocation

Run NONROAD n times

Calculate statistics on outputs

AverageStandard Deviation

Skew



Monte Carlo Simulation

20.0020.5021.0021.5022.0022.5023.0023.5024.0024.5025.00

0 1000 2000 3000

# Runs

Tons

Per

Day

AvePMBasePM

4.00

5.00

6.00

7.00

8.00

9.00

10.00

0 500 1000 1500 2000 2500 3000

# Runs

Tons

Per

Day Std

DevofPM

Monte Carlo SimulationGeorgia 1999 Summer Day Statewide NONROAD Output Results

InputDistribution THC NOx CO PMNormal 204 205 2581 24Triangle 220 214 2804 26Uniform 227 222 2931 28InputDistribution THC NOx CO PMNormal 24 29 29 30Triangle 23 27 28 28Uniform 26 33 32 33

Average (Tons Per Day)

Standard Deviation as % of Average (%)


Monte Carlo SimulationUncertainty of NONROAD Output Results for State and Counties

Maximum Minimum AverageTHC 35 19 23 24NOx 33 20 29 29CO 38 19 28 29PM 37 22 31 30

County Emissions State Emissions

Standard Deviation for Emissions as % of Average


• Uncertainty differences between counties and pollutants driven by dominant equipment types

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

THC CO

% o

f Tot

al N

ON

RO

AD

Em

issi

ons

AC Refrigeration

Pleasure Craft Outboard

Pleasure Craft Inboard

Recreational Equipment

Railroad Equipment

Industrial Equipment

Lawn & Garden Equipment

Logging Equipment

Lawn & Garden Equipment

Recreational Equipment

Agricultural Equipment

Construction Equipment

Commericial Equipment

Airport Ground Support Equipment


NOx PM


Monte Carlo SimulationPM % Change From Base Case

0 80 16040 Miles±

LegendPM % CHANGE

-80 to -60

-60 to -30

-30 to 0

0 to 30

30 to 72

AUGUSTA

COLUMBUS

ATLANTA

MACON

NOx % Change From Base Case

0 80 16040 Miles±

LegendNOx % CHANGE

-84 to -60

-60 to -30

-30 to 0

0 to 30

30 to 72

AUGUSTA

COLUMBUS

ATLANTA

MACON



0 80 16040 Miles±

LegendPM SD % of Ave

22 to 24

24 to 28

28 to 32

32 to 36

36 to 37

AUGUSTA

COLUMBUS

ATLANTA

MACON

1999 NONROAD PM Uncertainty1999 NONROAD NOx Uncertainty

0 80 16040 Miles±

LegendNOx SD % of Ave

19 to 21

21 to 24

24 to 27

27 to 30

30 to 33

AUGUSTA

COLUMBUS

ATLANTA

MACON


Conclusions


• Uncertainties of NONROAD emissions as calculated in this study were between 24% and 30% (standard deviation as % of mean) for the state of Georgia for THC, NOx, CO, and PM

• Uncertainties of input parameters were often positively skewed uncertainties of output emissions also positively skewed

• Using the Monte Carlo approach in this study resulted in approximately 10% increase of calculated emissions for all studied pollutants.

• Uncertainty analysis of NONROAD model does NOT account for all possible uncertainties underestimation?

On-going and Future Work

• Improvement of distributions of NONROAD input parameters and sampling methods

• Sensitivity analysis of CMAQ model to NONROAD emissions uncertainties in Georgia

• Uncertainty of aircraft, locomotive, commercial marine emissions rest of emissions inventory

• Uncertainty analysis of CMAQ model results


Acknowledgements

Much thanks to…• NONROAD Uncertainty Experts Panel: Ms. Archana

Agrawal (CARB), Dr. Christopher Frey (NC State), Dr. Christian Lindhjem (Environ), Mr. Scott Southwick (GA EPD), and Ms. Kirstin Thesing(Pechan)

• EPA, Georgia Depart of Natural Resources (DNR), and Georgia Power for funding this study


NONROAD Emissions Model Uncertainty Analysis for the State of … · 2015-09-10 · NONROAD...

Documents

Transcript of NONROAD Emissions Model Uncertainty Analysis for the State of … · 2015-09-10 · NONROAD...