Quantitative Analysis of Pollutant Emissions in the Context of Demand Responsive Transport

Pollutant Emissions

and DRT Systems

Towards the Integration of a Spatial

Dimension in the Estimations

Julie Prud’homme, Didier Josselin, Jagannath [email protected]

UMR ESPACE – CNRS 6012 – University of Avignon

Julie Prud’homme – GEOG-AN-MOD 2011 (Santander - SPAIN -- 21/06/2011)

Outline

1. Introduction

2. Simulation and results

3. Conclusions

2

INTRODUCTION


Cumul des

émissions

4

Julie Prud’homme – GEOG-AN-MOD 2011 (Santander - SPAIN -- 21/06/2011) 5










Emission Models

● MEET (Methodology of Emission Estimation

from Transports) set up at the conclusion of

an European collaboration [J.Hickman et al. (2003)]

● GREEN-DRT model (Geographical

Reasoning on Emission Estimation from

transports based on road Network shape)

adapted from MEET [J.Prud’homme (2011)]

14


Calculation

of Start Emissions

15

MEET GREEN-DRT

Dependent on temperature and speed of traffic

A single cold startMany starting up

(cold and/or warm)


Consideration of the Road Network in

the Calculation of Emissions in Traffic

MEET GREEN-DRT

Proportion of every type of road

(j) taken by a certain number of

vehicle (ni) of the same type (i)

Detail of every section (t) used

with the information about the

type of road (j) and sequencing of

these

Where

li : Distance averages travelled by the

vehicles of type (i)

pi,j : Proportion of the annual distance

crossed on roads of type (j) with vehicles

of type (I)

Where

DV,t,j : Distance travelled by the vehicle (V)

on sections (t) of type (j)

16



EC1 = ES3 + ES4/2 + (ES1 + ES2 + ES6 )/2

• A fair repartition of emissions

18

EC2 = ES4/2 + ES5 + (ES1 + ES2 + ES6 )/2

Calculation of Unit Emissions

S1 S2 S3 S4 S5 S6 Sections of journey

Emissions in

service

Emissions

without client

Cumulative

emissions

Effective

emissions

SIMULATIONS AND RESULTS


Workflow of GREEN-DRT Model

20

1st stageSele

cti

on o

f th

e s

imula

tion

para

mete

rs

2nd stage 3rd stage 4th stage 5th stage

TasksCreation of

road network

and demand

Optimisation

of DRT

service

Routes

reconstruction

Calculation

of the

quantity of

emitted

pollutants

Cartography

and analysis of

emissions on

the network


Simulations


Simulations

• Simulation of a DRT in three different scales

(different density of stops)

22

Level 1 : Britany34 stops ; 0.0013 stop/km²

Scale = 1:7500000

Level 2 : Agglomeration of Rennes33 stops ; 0.054 stop/km²

Scale = 1:800000

Level 3 : City of Rennes 79 stops ; 1.58 stop/km²

Scale = 1:130000


Simulations

• Scalability (number of client demands)

• Grouping rate (deviation time allowed)

• Unlimited number of vehicle in fleet

50% gasoline, 50% diesel

23


y = 47,559x-1,411

R² = 0,7356

y = 29,47x-1,298

R² = 0,7953

Results

• Confirmation of a reduced vehicles

number and emissions with the increased

grouping rate

24

1,3 2 1,3 2

Grouping average in actual DRT services in Europe


Results

25

25

30

35

1

2

5 10 15 20

Qu

anti

ty o

f p

ollu

tan

t e

mis

sio

ns

(kg)

Gro

up

ing

rate

Deviation time (mn)

Level 1

Grouping rate Pollutant emissions (kg)

0

10

20

30

0

1

2

3

4

5 10 15 20

Qu

anti

ty o

f p

ollu

tan

t e

mis

sio

ns

(kg)

Gro

up

ing

rate

Deviation time (mn)

Level 2


0

5

10

15

0

1

2

3

4

5

5 10 15

Qu

anti

ty o

f p

ollu

tan

t e

mis

sio

ns

(kg)

Gro

up

ing

rate

Deviation time (mn)

Level 3


• Increase of deviation time,

increase of grouping ,

decrease of emissions

(except for level 1)


Results

26

25

30

35

1

2

5 10 15 20

Qu

anti

ty o

f p

ollu

tan

t e

mis

sio

ns

(kg)

Gro

up

ing

rate

Deviation time (mn)

Level 1


0

10

20

30

0

1

2

3

4

5 10 15 20

Qu

anti

ty o

f p

ollu

tan

t e

mis

sio

ns

(kg)

Gro

up

ing

rate

Deviation time (mn)

Level 2


0

5

10

15

0

1

2

3

4

5

5 10 15

Qu

anti

ty o

f p

ollu

tan

t e

mis

sio

ns

(kg)

Gro

up

ing

rate

Deviation time (mn)

Level 3


• Increase of deviation

time, increase of grouping

, decrease of emissions

(except for level 1)

• Breaking point of efficiency


Results

27

25

30

35

1

2

5 10 15 20

Qu

anti

ty o

f p

ollu

tan

t e

mis

sio

ns

(kg)

Gro

up

ing

rate

Deviation time (mn)

Level 1


0

10

20

30

0

1

2

3

4

5 10 15 20

Qu

anti

ty o

f p

ollu

tan

t e

mis

sio

ns

(kg)

Gro

up

ing

rate

Deviation time (mn)

Level 2


0

5

10

15

0

1

2

3

4

5

5 10 15

Qu

anti

ty o

f p

ollu

tan

t e

mis

sio

ns

(kg)

Gro

up

ing

rate

Deviation time (mn)

Level 3


• More stop density increase, better is grouping

1,8

43

Low stop density

Medium stop density High stop density


Conclusions

• DRT : a solution for an economy of

pollutants and vehicle in traffic

• Grouping

detours

increase of distance travelled by vehicles

dependent on characteristics of the road network

« environmental » threshold

28

Pollutant Emissions

and DRT Systems

Towards the Integration of a Spatial

Dimension in the Estimations

Julie Prud’homme, Didier Josselin, Jagannath [email protected]

UMR ESPACE – CNRS 6012 – University of Avignon

Technology

Quantitative Analysis of Pollutant Emissions in the Context of Demand Responsive Transport