Real-World Emissions from Heavy

Haulers in Alberta Oil Sands Mining

John G. Watson1 (John.Watson@dri.edu) Judith Chow1, Xiaoliang Wang1, Steven D. Kohl1, Barbara

Zielinska1, Allan H. Legge2, and Kevin E. Percy3

1Desert Research Institute, Reno, NV, U.S.A. 2Biosphere Solutions, Calgary, Canada

3Wood Buffalo Environmental Association, Ft. McMurray, Canada

Presented at

North American Oil and Gas Conference

Calgary, AB, Canada

October 22, 2014

Study Objectives

• Integrate modern measurement systems to quantify multipollutant emissions with multiple effects

• Measure real-world emission factors for gaseous and particulate emittants

• Obtain VOC and PM2.5 source profiles for emission inventory development and source apportionment

What do we mean by “multipollutant” and “multiple effect”? Future air quality management will address more than criteria

contaminants

Chow, J.C.; Watson, J.G. (2011). Air quality management of multiple pollutants and multiple

effects. Air Quality and Climate Change Journal, 45(3):26-32.

https://www.researchgate.net/publication/234903062_Air_quality_management_of_multiple_pollu

tants_and_multiple_effects?ev=prf_pub.

-25

25

75

125

175

225

275

325

375

1 2 3 4 5 6 7 8 9 10

Decile

Em

issio

n F

acto

r [g

CO/k

gF

ue

l]

CO

PM

0.025

0.275

0.225

0.175

0.125

0.075

0.375

0.325

-0.025

Em

issio

n F

acto

r [g

PM

/kg

Fu

el]

-1%

3%

0%

4%

0%

2%

1%

3%

1%

2%

2%

7%

3%

12%

5%

14%

12%

18%

78%

35%

Mazzoleni et al., 2004, JAWMA, 54(6):711-726

What do we man by real-world emissions?

Average emission rates measured in the laboratory for engine certification

don’t represent the full range of equipment, fuels, and operating conditions

Engine certification tests are performed on engine

dynamometers independent of the application Sample ISO 8178 Non-Road Steady-State Test Cycle Weighing Factors

Mode Number

1 2 3 4 5 6 7 8

Torque, %

100 75 50 10 100 75 50 0

Speed Rated speed Intermediate speed Low idle

Type C1* Factors

0.15 0.15 0.15 0.10 0.10 0.10 0.10 0.15

• Engines behave differently within and outside of the vehicle

• Engines are not subject to same aging and maintenance conditions

• Fuels are different

• Operating cycles differ, especially for transient operations

Diesel engines are the world’s workhorses • Advantages:

– High fuel efficiency (40-50% as compared to 25-35% for gasoline engines), more powerful, and more durable due to:

Higher compression ratio

Fuel-lean combustion

No throttling loss

• Disadvantages:

– Heavier and more expensive

– Emit more NOx and PM

– Noisier and harder to start in cold weather than gasoline engines

Ideal for off-road applications!

Rudolf Diesel (1858‒1913)

Four-stroke Diesel Cycle: • Air intake • Compression • Fuel injection • Exhaust

http://auto.howstuffworks.com/diesel1.htm#

The AOSR heavy hauler fleet operates all the

time and is growing rapidly

• Several hundred heavy haulers operate in the AOSR

• Each truck operates >6000 hr/yr and consumes > 1 million L/yr of diesel fuel

• Surface mining operations account for >75% of diesel fuel consumption

M.J. Bradley & Associates (2008)

Caterpillar 797B heavy haulers constitute most of the

fleet

Parameter CAT 797B

Introduction to Service 2002

Nominal Payload Capacity 345 tonnes

Gross Operating Weight 624 tonnes

Engine Power 3,370 hp (2,513 kW)

Displacement 117.1 Liter

Top Speed (Loaded) 42 mph (68 km/h)

Fuel Capacity 1,800 US gal (6,814 Liter)

Emission Standards Tier 1

Four Caterpillar 797B heavy haulers

were tested in three oil sands facilities

Trucks CAT

797B-1 CAT

797B-2 CAT

797B-3 CAT

797B-4

Facility B A A C

Study year 2009 2009 2010 2010

# of trucks in the fleet

60 41 41 23

Continuous and integrated samples of ~300

separate pollutants were measured

Residence time is ~3 sec

3 – 35 times dilution ratio

Muffler

Elbow

Connector

Engine

Exhaust

ThermocoupleOmega TJ36-CASS-116U-6-SB

For Exhaust T URG-2000-30ENG

Cyclone

7.1 µm Cut

0.8 L/min

Residence

Chamber

PM2.5

impactor

Teflon + Citric acid

(mass, babs, element,

isotope, NH3)

Pump

Quartz + K2CO3

(Ions, WSOC, carbohydrates,

organic acids, HULIS, SO2)

Quartz + AgNO3

(EC/OC, markers, H2S)

Nuclepore

(Lichen study)

5 L

/min

5 L

/min

5 L

/min

5 L

/min

Filter

sampler

Flow

meter

TSI DustTrak DRX

(PM1, PM2.5, PM4,

PM10, PM15)

3 L

/min

0.0

5 L

/min

Magee AE51

(BC)

0.7

L/m

in

TSI CPC 3007

(Concentration 0.01-2.5 µm)

PP

Sy

ste

ms

CO

2 s

en

so

rs

Testo 350

(CO, CO2, NO, NO2,

SO2, O2,T, P)

PID 102+

(Total

VOCs)

0.1

6 L

/min

1 L

/min

0.0

1 L

/min

Module 2:

Continuous Gas

Monitoring

Teflon

Filter

1 liter

Canister

(CH4, C2-C12)

1 L

/min

Dilu

ted

1 L

/min

Un

dilu

ted

1 L

/min

Ba

ck

gro

un

d

DryerHEPA

HEPA

Filter

Activated

CharcoalAir

CompressorValve

32 L/min

5.8

8 L

/min

Makeup Flow

For Balance

Flowmeter

3.75 L/min25.88 L/min

3.17 L/min

32.8 L/min

Dilutor

Module 1: Sample

Conditioning

Heavy HaulerExhaust Pipe

CaCl2 Desiccant

Valves

Pump

1 L

/min

Valve

Pump

DNPH

(Carbonyls)

Insulated

Transfer

Line

Water

Trap

Module 3:

Integrated

Sampling

Module 4:

Continuous PM

Monitoring

Module 5:

Power Supply

Valve

Filter

Measurement systems are located in interconnected modules

Testo 350CO2

SensorsPID Analyzer

Filter PacksCanisterPump for

Makeup FlowFlowmeters

Pumps

CPC DRX OPCComputer Deep Cycle

Marine BatteryVoltage

Regulator

Battery Monitor

Sample Conditioning Module Continuous Gas Module

Integrated Sample Module Continuous PM Module Power Supply

Each module measures = 80 cm L × 52 cm W × 32 cm H; Modules 1-4 weighs ~25 kg each, and power supply module with two battery weighs 80 kg.

Sample

Introduction

Elutriator Dilution

Air/Sample Mixer

Residence

ChamberDilution Air

Introduction

Air Compressor Valve Flowmeter Carbon Filter

HEPA

Filter

Stream for

Undiluted

CO2

Dryer Teflon

Filter

Cyclone

Stream to

Module 2

Stream to

Module 3

Stream to

Module 4

Stream to

Background

CO2

Samples were drawn from the exhaust pipe (muffler

outlet) of CAT 797B and diluted to ambient

temperatures

Driver

cabin

Sampling

platform

Sampling

modules

Muffler

Flange connecting

to the body

Exhaust pipe

Sampling port

Thermocouple

Sample

transfer line

Samples were taken during real-world

complete operating cycles

Loading Traveling with load

Dumping Traveling without load

EFP: Emission factor in g pollutant per g fuel CMFfuel: Carbon mass fraction of the fuel (86.2% for diesel) CP: Concentration of pollutant P in g/m3 CCO2: Concentrations of CO2 in g/m3 CCO: Concentrations of CO in g/m3

MC: Atomic weight of carbon (12 g/mole) MCO2: Molecular weight CO2 (44 g/mole) MCO: Molecular weight CO (28 g/mole) This equation assumes all carbon in fuel is converted to CO2 and CO.

Fuel-based Emission Factors (EF) are determined

CO

CCO

CO

CCO

PfuelP

M

MC

M

MC

CCMFEF

2

2

Moosmüller et al. (2003)

Differences between CAT 797B trucks are within experimental

variations (Higher emissions for CO, NOx, and particle number at Facility C)

9.6

0.7

49.3

0.50.5 0.5x1015

6.5

1.0

52.4

0.8

0.5

5.4

10.7

0.2

50.3

0.6

0.9

2.9

14.3

0.6

70.0

0.9

10.1

0.1

1

10

100

1000

Emis

sio

n F

cto

r (g

/kg

fue

l)

Pollutant

CAT797B-1 (Facility B) CAT797B-2 (Facility A)

CAT797B-3 (Facility A) CAT797B-4 (Facility C)

NMHC NOxCO BlackCarbon

PM2.5Particle

Number

NOx is expressed as NO2

Real-world operations emitted higher CO and NOx, lower

NMHC, and comparable PM2.5 to certification tests

• Real-world/Certification Ratio

– CO: 111-243%

– NMHC: 12-66%

– NOx: 131-187%

– PM2.5:65-112% Note: NOx is expressed as NO2

Emittant

Em

issio

n F

acto

r (g

/kg

fu

el)

0.1

1

10

100CAT 797B-1

CAT 797B-2

CAT 797B-3

CAT 797B-4

Certification

CO NMHC NOx PM

2.5

CAT 797B-3 (with fuel additive) reported 60–85% higher CO and BC,

70% lower NMHC, similar NOx, 27–56% less PM2.5 and particle

number than CAT 797B-2 (no additive)

The fuel additive does not have significant impact on emissions in Facility A. The two trucks tested one year apart (CAT 797B-2 in 2009 and CAT 797B-3 in 2010) reported comparable emissions.

6.5

1.0

52.4

0.8

0.5

5.4x1015 (#/kg fuel)10.7

0.2

50.3

0.6

0.9

2.9x1015

0.1

1

10

100

1000Em

issi

on

Fct

or

(g/k

g fu

el)

Pollutant

CAT797B-2 (Facility A, w/o Fuel Aditive)

CAT797B-3 (Facility A, w/ fuel additive)

NMHC NOxCO Black

CarbonPM2.5

Particle

Number

Different methods used to estimate emissions for the NPRI give different

results Method 1: Emission Rate = EF (g/kg fuel) × Fuel consumption (Facility A)

• Used 1985 EPA AP-42 EFs

Method 2: Emission = EFTier1 (g/kWh) × Operating Hr × Rated Vehicle Power × Load Factor (Facility A)

• Load factor is taken conservatively (59% or 100% recommended by EPA; CAT estimated 20‒50%; one facility estimated 35‒48%)

Method 3: Emission = max(EFTier1, EFcert composite) ×1.1/BSFC × Fuel consumption (Facility B)

BSFC = brake-specific fuel consumption (kg fuel/kWh)

0

20

40

60

80

100

120

140

CO NMHC NOx PM

Em

iss

ion

s (

ton

ne

s/t

ruck

/yr)

Emittant

Method 1

Method 2

Method 3

Real-World

Emissions varied by operating conditions (time series)

i. Idling: Concentration stable

and low.

ii. Leaving parking lot: All

concentrations increase.

iii. Top of uphill: Spikes of

concentrations.

iv.Leaving with load: high

concentration spikes when

accelerating.

v. Leaving after dumping:

concentration spikes when

climbing uphill.

vi.Waiting for load: low

concentration except when

moving forward in line.

Ground Speed(mph)

0

10

20

CO2

(ppm)

0

20000

40000

60000

80000

CO(ppm)

010002000300040005000

NOx

(ppm)

0

2000

4000

Black CarbonConcentration

(mg/m3)

0

20

40

60

80

NumberConcentration

(cm-3

)

01e+82e+83e+84e+85e+86e+8

PM2.5

Concentration

(mg/m3)

0

1e+2

2e+2

Total VOCs(ppm)

0100200300400500600

EngineSpeed(rpm)

600

900

1200

1500

Time (hh:mm)

12:35 12:40 12:45 12:50 12:55 13:00 13:05 13:10 13:15 13:20

Elevation(m)

240

260

280

300

i. Idle ii. Leaving

parking lot iv. Leaving

with load

v. Leaving

after dumping

Leaving

with load

iii. Top of

uphill road

vi. Waiting

for load

(c) CO2 analyzer

(b) Emission analyzer

(d) Emission analyzer

(a) PID analyzer

(f) micro-aethalometer

(e) CPC

(i) GPS

(h) Truck

(j) GPS

(g) DustTrak DRX

Traveling with load has the highest emission rates

0.0

0.5

1.0

1.5

2.0

2.5

Idle Traveling w/ load Traveling w/o

load

VO

Cs

Em

iss

ion

(g

/s)

Truck Operation

Total VOCs

0

1

2

3

4

5

6

7

Idle Traveling w/ load Traveling w/o load

CO

Em

iss

ion

(g

/s)

Truck Operation

CO

0

2

4

6

8

10

12

Idle Traveling w/ load Traveling w/o load

NO

Em

iss

ion

(g

/s)

Truck Operation

NO

0

0.04

0.08

0.12

0.16

Idle Traveling w/ load Traveling w/o load

PM

2.5

Em

iss

ion

(g

/s)

Truck Operation

PM2.5

NMHCs consist mostly of alkenes and alkanes (~10-80%).

Abundance is normalized to the sum of 56 photochemical assessment monitoring station (PAMS) compounds

Compound % of PAMS

Ethylene 28.3%

Propylene 15.4%

n-Heptane 5.6%

Acetylene 5.4%

1-Butene 4.9%

n-Decane 4.5%

Isobutane 4.1%

Isopentane 3.7%

Toluene 3.6%

Ethane 3.6%

Benzene 3.4%

Isobutylene 2.9%

n-Nonane 1.9%

2-Methyl-1-Pentene 1.8%

1-Pentene 1.7%

n-Octane 1.4%

n-Butane 1.3%

1-Heptene 1.3%

Propane 1.3%

m/p-Xylene 1.3%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Alkanes andCylcoalkanes

Alkenes Alkyne Aromatics

Ab

un

dan

ce N

orm

aliz

ed

to

Su

m o

f PA

MS

NMHC Group

CAT 797B-1

CAT 797B-2

CAT 797B-3

CAT 797B-4

EC and OC are the most abundant (~68 - 88%) components in PM2.5

source profiles; Elevated P, S, Ca, and Zn suggest the origin from lube oil.

NO2-

NO3-

PO4≡

SO4=

NH4+

Na+

Mg++

Ca++

OCEC

Al

SiP

S

Cl

K

Ca

Sc

Ti

Fe

Cu

Zn

Ga

Sr

Zr

Nb

Mo

Ag

Sn

Sb Ba

La

Ce

Sm

Eu

Ir

Au PbUr

0.001

0.01

0.1

1

10

100

Ch

em

ica

l Ab

un

da

nc

e (

%)

Chemical Species

CAT 797B-1

Ch

em

ical A

bu

nd

an

ce (

%)

OC21%

EC56%

Elements2%

Soluble ions8%

Unidentified13%

CAT 797B-4

OC21%

EC67%

Elements1%

Soluble ions2%

Unidentified9%

CAT 797B-1

OC36%

EC49%

Elements2%

Soluble ions4%

Unidentified9%

CAT 797B-2

OC14%

EC55%

Elements1%

Soluble ions3%

Unidentified27%

CAT 797B-3

Particle-bound PAHs show two distinct

abundance groups

0.00

0.02

0.04

0.06

ph

en

an

thre

ne

an

thra

ce

ne

flu

ora

nth

en

e

pyre

ne

ben

zo

[a]a

nth

race

ne

ch

rys

en

e+

tri

ph

en

yle

ne

ben

zo

[b]f

luo

ran

then

e

ben

zo

[j+

k]f

luo

ran

then

e

ben

zo

[a]f

luo

ran

then

e

ben

zo

[e]p

yre

ne

ben

zo

[a]p

yre

ne

pery

len

e

ind

en

o[1

,2,3

-cd

]pyre

ne

dib

en

zo

[a,h

]an

thra

cen

e

ben

zo

[gh

i]p

ery

len

e

co

ron

en

e

dib

en

zo

[a,e

]py

ren

e

9-f

luo

ren

on

e

dib

en

zo

thio

ph

en

e

1 m

eth

yl p

he

na

nth

ren

e

2 m

eth

yl p

hen

an

thre

ne

3,6

dim

eth

yl p

he

na

nth

ren

e

me

thylf

luo

ran

then

e

rete

ne

ben

zo

(gh

i)fl

uo

ran

the

ne

ben

zo

(c)p

hen

an

thre

ne

benzo(b)naphtho[1,2-…

cyclo

pen

ta[c

d]p

yre

ne

Ma

ss

Pe

rce

nta

ge o

f O

rga

nic

Carb

on

(%

)

PAHs

CAT 797B-1

CAT 797B-2

CAT 797B-3

CAT 797B-4

Particle-bound n-Alkanes show abundances

between C19 and C30

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

n-p

en

tad

eca

ne

(n

-C15

)

n-h

exa

de

ca

ne

(n

-C1

6)

n-h

ep

tad

ecan

e (

n-C

17)

n-o

cta

de

ca

ne

(n

-C18

)

n-n

on

ad

eca

ne

(n

-C1

9)

n-i

co

san

e (

n-C

20)

n-h

en

eic

os

an

e (

n-C

21

)

n-d

oco

sa

ne

(n

-C2

2)

n-t

ric

os

an

e (

n-C

23

)

n-t

etr

aco

sa

ne

(n

-C24

)

n-p

en

taco

sa

ne

(n

-C25

)

n-h

exa

co

sa

ne

(n

-C2

6)

n-h

ep

taco

sa

ne

(n

-C27

)

n-o

cta

co

sa

ne

(n

-C28

)

n-n

on

aco

sa

ne

(n

-C2

9)

n-t

ria

co

nta

ne

(n

-C30

)

n-h

en

tria

co

tan

e (

n-C

31

)

n-d

otr

iaco

nta

ne

(n

-C3

2)

n-t

ritr

iac

tota

ne

(n

-C3

3)

n-t

etr

atr

iacto

an

e (

n-C

34)

n-p

en

tatr

iaco

nta

ne

(n

-C35

)

n-h

exa

tria

co

nta

ne

(n

-C36

)

n-h

ep

tatr

iaco

nta

ne

(n

-C37

)

n-o

cta

tria

co

nta

ne

(n

-C38

)

n-n

on

atr

iaco

nta

ne

(n

-C3

9)

n-t

etr

aco

nta

ne

(n

-C4

0)

**

Ma

ss

Pe

rce

nta

ge o

f O

rga

nic

Carb

on

(%

)

n-Alkanes

CAT 797B-1

CAT 797B-2

CAT 797B-3

CAT 797B-4

Summary • Real-world emissions were characterized for

four CAT 797Bs under normal operations.

• Real-world operations emitted higher CO and NOx, lower NMHC, and comparable PM2.5 to certification tests.

• Emission estimation methods differ by facility and from the real-world measurements

• Truck emission source profiles showed 10 – 80% alkenes and alkanes in non-methane hydrocarbons, and 68 – 88% carbon (OC and EC) in PM2.5.

How to use this information

• Criteria Contaminants

– Develop a more accurate and consistent estimate of fleet emissions, based on distributions of load factors and fuel consumption available from tracking systems

• Greenhouse Gases

– Estimate mine fleet Global Warming Potentials (GWP) for life-cycle assessments

• Toxics Inventory

– Revise emission estimates

• Source Apportionment

– Use chemical profiles to identify contributions to adverse ecosystem responses

• Anticipate future emission requirements

– Ultrafine particles and black carbon (EU and California are moving in this direction)

Future engines will substantially reduce emissions as

they penetrate the fleet

http://www.tandfonline.com/doi/pdf/10.1080/10473289.2001.10464315

http://www.tandfonline.com/doi/pdf/10.1080/10473289.2011.599277

0.1

1

10

100

Em

iss

ion

Fa

cto

r (g

/kg

fu

el)

Truck Tiers (Model Year)

CO NMHC

NOx PM

Base(<1988)

T0(1988-2000)

T1(2000-2006)

T2(2006-2011)

T4(2011-2015)

797B

/T282B

http://www.awma.org/publications/

journal

Acknowledgements

• Sponsor: Wood Buffalo Environmental Association (WBEA, Ft. McMurray, Alberta). The content and opinions expressed by the authors in this presentation do not necessarily reflect the views of WBEA or of the WBEA membership

• Special appreciation to: Drs. Ken Foster and Yu-Mei Hsu, Ms. Carna MacEachern, Ms. Veronica Chisholm, and environmental officers and staffs at each facility