Air pollutants emission from vehicles

Zhejiang University Qingyu Zhang

•  Introduction •  Methodology

•  Emission factors study •  Emission inventories establishment •  Haze of hangzhou attributed by vehicles •  Air pollutants emission reduction scenarios analysis

•  Results and discussion

Contents

Introduction Ø Rapid growth on fuel consumption of motor vehicles

Ø Annual growth rate over 10% during 2002-2012

Ø Air pollution in urban cities

Coal smoke type

Complex type

Schematic diagram showing the remote sensing system in operation

Air pollution factors study

Schematic diagram for chassis dynamometer test in operation

Type of oil

Pollutant

Max emission factor g/

L（appearance）

Min emission factor g/

L（appearance）

Pollutant

Max emission factor g/

L（appearance）

Min emission factor g/

L（appearance） g

CO 287.74(2010年) 98.46(2030年)

PM10 0.144(2010年) 0.046 (2030年)

d 15.11(2007年) 7.61 (2030年) 0.526(2006年) 0.213 (2030年) g

VOCs 10.82(2007年) 2.18(2030年)

CO2 2322.21(2030年) 2002.16(2010年)

d 2.89(2004年) 0.86 (2030年) 2469.96(2030年) 2452(2006年) g NOx 11.20(2004年) 1.64(2030年） Zhang, et al, 2008. Atmospheric Environment,

40(20), 4989–5002 d 10.35(2007年) 5.07 (2030年)

Emission factor of vehicle(g-gasoline, d-diesel)

Variance of the emission factor——vehicle

0

5

10

15

20

25

30

35

2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030年份

CO

, VO

Cs,

NO

x, P

M10

排放因子

, g/L

2000

2080

2160

2240

2320

2400

2480

2560

CO

2排放因子

,g/L

g-CO/10g-VOCsg-NOxg-PM10×10d-COd-VOCsd-NOxd-PM10×10g-CO2d-CO2

Emission factor

Emission factor C

O2

SO2emission factor

NOx emission factor PM10

emission factor

GIS Emission

inventories

Energy Combustion

Products

Establishment of air pollution inventories based on GIS

VOCs

GIS Emission index of PM10 for industry

GIS Emission index of SO2 for industry

GIS Emission index of NOx for industry

GIS Emission index of NOx for vehicle

GIS Emission index of PM10 for vehicle

GIS Emission index of PM10

Zhang, et al, 2008. Atmospheric Environment,

40(20), 5150–5165

780 790 800 810 820 830 840

3330

3340

3350

3360

3370

3380

02468101214161820222426283032343638404244

vis-total

Ø Distribution of visibility：

780 790 800 810 820 830 840

3330

3340

3350

3360

3370

3380

02468101214161820222426283032343638404244

vis-other

The worst average dairy visibility for emission without vehicle (km)

The worst average dairy visibility for total emission（km）

Visibility Without vehicle Total emission source

annual average visibility in Hangzhou (km)

4.4 2.4

Proportion of area in Hangzhou with haze(<10km)

93.5% 100%

Proportion of area in Hangzhou with sever haze（<2km）

23.6% 46.4%

The influence on visibility from vehicle exhaust

The component of extinction for PM2.5 The component of extinction for PM2.5 in domestic and aboard

34.44%

9.33%

25.63%

8.98%8.98%

12.64%

SO4

NO3

NH4

POM EC other

22.19%

3.35%30.32%

11.23%

11.1%21.81%

SO4

NO3

NH4

POM EC

Roadside station Yunxi

Location year PM2.5 SO42- NO3

- NH4+ POM EC

Roadside station 2010 114.7 14.5(12.6) 10.3(9.0) 10.3(9.0) 29.4(25.6) 10.7(9.3) Yunxi 77.5 16.9(21.8) 8.6(11.1) 8.7(11.2) 23.5(30.3) 2.6 (3.4) Lin’an 1999 47 11.5(24.5) 7.0(14.9) 5.2(11.1) 25.0(53.2) 1.7(3.6) Pearl River Delta 2002 41.3 10.1(24.5) 0.4(1.0) 4.1(9.9) 17.4(42.1) 1.7(4.1) Beijing 1999 136 20.4(15.0) 10.9(8.0) 6.8(5.0) 40.8(30.0) 3.5(2.6) Shanghai 2000 91.2 18.5(20.3) 9.9(1.09) 7.7(8.4) 28.6(31.3) 8.1(7.3) Atlanta,US 1999 34.4 11.0(32.0) 0.7(11.0) 3.8(11.0) 10.5(30.5) 0.7(2.0) Philadelphia, US 1999 17.4 4.1(23.6) 3.8(14.9) 2.6(14.9) 6.0(34.5) 2.5(14.4)

The component of extinction for PM2.5 in Hangzhou

780 790 800 810 820 830 840

3330

3340

3350

3360

3370

3380

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

780 790 800 810 820 830 840

3330

3340

3350

3360

3370

3380

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

ü Vehicle emission accounted for 50%-60% in total emission source

Ø The contribution of vehicle for the worsen visibility

Influence on annual visibility by vehicle emission

Influence on the worst daily visibility by vehicle emission

ü The worst area affected by vehicle was in junctional zone of Xihu and Gongsu. Accounting for >50%

C O (ppm)

-0.5

1.5

3.5

5.5

7.5

9.5

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

1st2nd3rd4th5th

Model Year

Prevention and cure measure of pollutants from vehicle

•  Five levels analysis on vehicles in different years

CO

Ø Control the high discharge emission

0

800

1600

2400

3200

4000

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

1st2nd3rd4th5th

H C ( p pm)

Model Year

Prevention project for airborne pollutants of vehicle

•  Five levels analysis on vehicles in different years (a)

0

400

800

1200

1600

2000

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

1st2nd3rd4th5th

N O ( p pm)

Model Year

(b) HC

NOx

HC and NOx

Age

emission

“Twelve-Five planning”countermeasure study on emission reduction of vehicle pollutants

u  setting reduction scenarios

u BAU—— current policy；

u ESV——on the basis of BAU; phase out high pollutant vehicles；

u HOR——on the basis of ESV; improve the

quality of oil；

u AER——on the basis of ESV; apply new energy vehicle

Distribu,on  of  PM2.5  before  and  a8er  reduc,on

Conclusion

•  There is an exponential relationship between the EFs and accumulated mileages for each type of vehicles

•  The haze of city attributed to vehicles is over 50%

•  It is important to reduce air pollutants from vehicles