National mobile source emission inventory development

National mobile source emission inventory development

Vahid Hosseini, Ph.D.

Assistant Professor

Mechanical Engineering Department

Sharif University of Technology, Tehran, Iran

M. Reyhanian, E. Banitalebi , F. Esteghamat, S. Mirshi , M. H. Ettehadian, A.Hasani , F. Faraj i

Urban air pollution program

University of California, Irvine, CA September 3, 2013

Fuel, Combustion, and Emission Research Group

Outline

Emission inventories

The case for a measurement campaign

Instruments

Design of experiments

Preliminary results

Work in progress and future works


FCE research group at a glance

o Dealing with combustion and combustion generated air pollution

o A single cylinder research engine test cell is under construction for clean combustion studies such as HCCI and PCCI for low NOx and soot combustion, will be commissioned by the end of 2013.

o An air pollution dispersion model for the city of Tehran (WRF/CAMx) is under development and preliminary results are out.

o Feasibility study for Tehran public transit diesel particulate filter (DPF) retrofit

o National mobile emission inventories is under development.


Outline



Instruments


Preliminary results



Emission inventories (1)

The concentration of various pollutants in the air depends on ◦ Meteorological conditions

◦ Physical effects such as deposition, advection, transport

◦ Chemical effects and photochemical reactions

◦ Production

◦ To gain a detailed understanding of behavior of pollutants in the air, having a precise PRODUTION term is essential

◦ The production term is calculated by multiplying emission factors (per unit activity) by the activity

5


Emission inventories (2)

◦Stationary sources ◦ Houses, commercial buildings, industrial activities, gas stations, transit

terminals, rail road stations and airports

◦Mobile sources ◦ Passenger vehicles, trucks and diesel powered commercial vehicles, off-

road vehicles


Emission inventories in Iran

◦Available emission factors are used for similar sources.

◦There is no comprehensive national emission factor data available for mobile and stationary sources

◦The larger error expected to come from mobile sources

◦The latest detailed mobile source emission inventory was developed by JICA in 1996 for the city of Tehran.


Outline



Instruments


Preliminary results



The cases for the measurement campaign

◦ The case of traffic tunnels

◦ The cases of air pollution dispersion models

◦Diverse data for emission factors per unit mass fuel

CO concentration along a traffic tunnel in Tehran Performance of the air pollution dispersion model


Outline



Methodology, instruments, and error estimation


Preliminary results



Methods to measure emission factors for mobile sources

◦ Inspection/maintenance data

◦Remote sensing




◦Remote sensing

◦ Chassis dynamometer




◦Remote sensing

◦ Chassis dynamometer

◦ Portable Emission Measurement (PEM)


Sample size and characteristics

◦A sample 30 Iranian-made passenger light duty vehicle, gasoline fueled, privately owned and operated


Instrumentation

◦ AVL DiCOM 5-gas analyzer to measure real-time HC, CO, CO2, O2, and NOx

◦ Portable hardware/software to acquire real-time ECU data (mainly engine speed, vehicle speed, manifold absolute pressure, air mass flow, and relative air/fuel ratio)

◦ GPS to locate x,y,z of the vehicle


Error estimation

◦External error analyses based on the accuracy and resolution of the instruments

◦Repeatability tests for random variability

◦Comparison with chassis dynamometer test


Comparison with Chassis dynamometer

0.00

50.00

100.00

150.00

200.00

0 200 400 600 800 1000

THC

[p

pm

]

Time (sec)

THC VS Time

0.00

2000.00

4000.00

6000.00

8000.00

0 200 400 600 800 1000

CO

[p

pm

]

Time (sec)

CO VS Time

0

200

400

0 200 400 600 800 1000

NO

x [p

pm

]

Time (sec)

NOx VS Time

chassis…AVL Dicom 4000


Effective parameters

◦Model and type

◦Age

◦Road

◦Driving cycle

◦Driving behavior

◦ Service and maintenance

◦ Slope

◦A/C on/off

◦ …?


Outline




Design of experiments and effective parameters

Preliminary results



Design of experiments Two-levels full factorial design for four

parameters

Factor Level low (-1) Level high (+1)

A: A/C OFF ON (maximum)

B: Service and maintenance Before After

C: Traffic (driving cycle) Light Heavy

D: Slope (road) Flat Uphill


0

20

40

60

80

1

31

61

91

12

1

15

1

18

1

21

1

24

1

27

1

30

1

33

1

36

1

39

1

42

1

45

1

48

1

51

1

54

1

57

1

60

1

63

1

66

1

69

1

72

1

75

1

Speed (km/h)

Time(s)

0

20

40

60

80

100

120

1 61

11

62

12

63

13

64

14

65

15

66

16

67

17

68

18

69

19

61

01

10

61

11

11

61

21

12

6

Speed (km/h)

Time(s)

Route and traffic (flat)


0

10

20

30

40

50

1

32

63

94 1…

1…

1…

2…

2…

2…

3…

3…

3…

4…

4…

4…

4…

5…

5…

5…

6…

6…

6…

7…

7…

7…

8…

8…

8…

9…

9…

Speed (km/h)

Time(s)

0

10

20

30

40

50

60

70

80

1 8

15

22

29

36

43

50

57

64

71

78

85

92

99

10

6

11

3

12

0

12

7

13

4

14

1

14

8

15

5

16

2

16

9

17

6

18

3

19

0

19

7

20

4

21

1

Speed (km/h)

Time(s)

Route and traffic (Uphill)


BLUE :Flat RED: UPHILL

Road-type effect Cumulative emission plots

CO2 (gr)

NOx (gr)

HC (gr)

CO (gr)


0

5

10

15

20

25

30

Uphill,heavy Traffic Flat, Light traffic Uphill.Light traffic Flat, Heavy traffic

Fue

l Co

nsu

mp

tio

n

(lit

/10

0 k

m)

A/C Effect fuel consumption


0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Uphill, BeforeService Uphill,After Service

HC

0

0.2

0.4

0.6

0.8

1

1.2


NOx

0

5

10

15

20

25


Fuel Consumption lit/100km

Traffic and service effect

service


Driving behavior Cycle characterization


Defining a parameter that describes the driving behavior

Driving aggressiveness factor (DAF)=

standard deviation of all recorded accelerations divided by

(average of all positive accelerations +

absolute value of average of all negative accelerations)


Effects of DAF on NOx

DAF


Effects of DAF on CO and HC


Outline





Preliminary results



Results Road and traffic effects of fuel consumption

0

5

10

15

20

25

30

Highway Flat Highway Uphill Urban Flat Urban Uphill

Fue

l Co

nsu

mp

tio

n

(Lit

/10

0km

)

Fuel Consumption


Results average speed effects on emissions

0

50

100

150

200

250

300

0-20 20-40 40-60 60-80 80-100CO

Pro

du

ctio

n (

gr/k

g Fu

el)

Speed Range (km/h)

CO

0

2

4

6

8

10

12

14

16

0-20 20-40 40-60 60-80 80-100NO

x P

rod

uct

ion

(gr

/kg

Fuel

)

Speed Range (km/h)

NOx

0

0.15

0.3

0.45

0.6

0.75

0.9

1.05

0-20 20-40 40-60 60-80 80-100

HC

Pro

du

ctio

n (

gr/k

g Fu

el)

Speed Range (km/h)

HC


Results vehicle type and millage (all certified Euro II )

0

2

4

6

8

10

CO

Pro

du

ctio

n (

gr/k

g Fu

el)

VEHICLE TYPE

CO

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

HC

Pro

du

ctio

n (

gr/k

g Fu

el)

VEHICLE TYPE

HC

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

NO

x P

rod

uct

ion

(gr

/kg

Fue

l)

VEHICLE TYPE

NOX

SAMAND LX - XU7 40000km

PEUGEOT 206 SD 350000km

TONDAR 115000 km

TONDAR 3200 km


Results comparison with polynomials developed by TRL

for UK

SAMAND LX

Speed [km/h]

0 20 40 60 80

CO

Em

issi

on F

acto

r [g

/km

]

0

10

20

30

40

50

Highway Flat

Highway Uphill

Urban Downhill

Urban Flat

Urban Uphill

TRL EURO 2

SAMAND LX

Speed [km/h]

0 20 40 60 80

NO

x E

mis

sion F

acto

r [g

/km

]

0

1

2

3

4

Highway Flat

Highway Uphill

Urban Downhill

Urban Flat

Urban Uphill

TRL EURO 2


Conclusions

o It is crucially important to repeat the experiments for each set of constant conditions

o Road type and traffic have the most effect on emissions

o A/C effects are mostly on fuel consumption

o Vehicle type and millage changes the emission factors considerably even at the same category of the vehicle and the same emissions standard

o National emission factors tend to be much higher than the available data


Outline





Preliminary results



Work in progress…

o Continuation of data collection for the entire sample size (currently at vehicle number 19 with more than 400 experiments)

o Performing more chassis dynamometer tests with various vehicles and cycles to get a sense of bias error due to the instrument


Future plan (and limitations)

oTo explore ways to estimate evaporative emissions of mobile and stationary sources

oTo develop physical based model using engine test cell data and activity models

oTo measure emission factors of natural gas- and propane-fueled vehicles Taxis Motorcycles Light-duty trucks Diesel vehicles

oTo develop more accurate and relevant activity models


Acknowledgement

American Association for Advancement of Science (AAAS)

The National Academy of Sciences

National Research Council

World Learning

International Visitor Leadership Program

Sharif University of Technology


Before getting to the questions…

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Questions ?

Thank you for your attention

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National mobile source emission inventory development

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