INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION

Modeling Impact of Bus Rapid Transit on Air Quality : A Case

Study of Klang Valley, Malaysia

MSc Geo-Information Science and Earth Observation MSc Geo-Information Science and Earth Observation for Environmental Modeling and Management (GEM), for Environmental Modeling and Management (GEM),

International Institute for Geo-Information Science and International Institute for Geo-Information Science and Earth Observation (ITC)Earth Observation (ITC)

6 March 20086 March 2008Shamsul Ridzuan IdrisShamsul Ridzuan Idris

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Introduction Statement of problem Research objective Methodology Analysis Interpreting Results

List of Content

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Speed of urbanization in selected countries

Introduction

Adapted from Morichi (2005)

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Problem associated with rapid urban development high level of motorization better income leads to high car

ownership limited land space for road

Introduction

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Why select Bus Rapid Transit (BRT) in this study area? rapid economic development increase in population, housing and economic

activities – increase in mobility improved bus service but slow public acceptancedeclining public modal split

How can it be a benefit to scientific community? little is known whether BRT can bring beneficial

impact to environment while reducing traffic congestion

Introduction

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Different Types of BRT

Introduction

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Introduction

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Urbanization Pattern in the Klang Valley from 1988-1999

Introduction

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Introduction

Transportation Network in the Klang Valley

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most of roads are at full capacity

over reliance on private vehicles

declining public modal split

Statement of Problems

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The main objective is to model the potential impact of bus rapid transit on air quality

To establish mutual impact of BRT routing on planning and accessibility

To examine the possible impact of BRT to traffic on the corridor

To examine the possible impact of BRT to vehicle emission

To relate the benefit and cost of BRT system to environment

Research Objectives

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Methodology

TransportationAdministrativeLand Use

GIS Analysis(A)

Car Traffic Modeling

(B)

Emission Mapping

(C)

GIS Database

Literature Review

Assessment of public transportation service

Problem Identification

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Identify suitable corridor Justify selected corridor

Traffic volumeNumber of car trips

Buffer Accessibility Proximity

Analysis : Suitability and Accessibility

Collection of Suitable Sites for Transit Zone in Klang Valley – Kabir, 2004

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1. Federal Highway

2. West Port Access (South West of Klang Valley)

3. Jalan Cheras - Kajang (South East of Klang Valley)

4. Jalan Sungai Buloh/Middle Ring Road Phase II

5. Middle Ring Road Phase I (within Federal Territory)

6. Jalan Damansara

Analysis : Suitable Corridor for BRT

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Historical Data

Projection

0

200000

400000

600000

800000

1000000

1200000

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

YEAR

TR

AF

FIC

VO

LU

ME

BR101

BR807

BR806

BR805

Analysis : Annual Traffic Volume on Selected Station for BRT Corridor

-

50,000

100,000

150,000

200,000

250,000

300,000

350,000

Traffic Station

Car

Tra

ffic

Vo

lum

e

2005

2007

2010

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Analysis : Car Traffic Modeling in Klang Valley

Klang District

Petaling District (include major city of Shah Alam, Subang Jaya and Petaling Jaya)

Kuala Lumpur Federal Territory

Origin and Destination Car Trips for district of Klang, Petaling and Kuala Lumpur in 2010

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41%

13%13%

10%

9%

7%7%

RESIDENTIAL

AGRICULTURE

INDUSTRY

OTHERS

INSTITUTIONAL

RECREATIONAL

COMMERCIAL

Analysis : Landuse within Five Kilometer of BRT Corridor

Accessibility of Service Area within five kilometer from BRT Station

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Accessibility Analysis : Service Area

Proximity to Bus Stop within Walking Distance

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Accessibility Analysis : Proximity to Bus Stop

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Car Traffic Modeling vs. Actual Car Traffic Volume for 2005

Analysis : Validation of Car Traffic Volume on Selected Station

R2 coefficient determination of 0.8233

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Analysis : Impact to traffic

-

50,000

100,000

150,000

200,000

250,000

300,000

350,000

BR101

BR102

BR105

BR106

BR109

BR111

BR802

BR803

BR804

BR805

BR806

BR807

BR813

WR10

5

WR10

6

Traffic Count Station

Car

Tra

ffic

Vo

lum

e

No BRT

With BRT

(33.5%)

(23.4%)

(40.4%)

Comparison of Car Traffic Volume at Selected Traffic Station in 2010

Projection of Total Car Traffic Volume in Klang Valley

2005 – 3,923,916 car trips

2007 - 4,079,176 car trips

2010 – 4,312,059 car trips

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Result of Car Traffic in 2010 for Klang Valley

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Result of Car Traffic on BRT Corridor

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Analysis : Impact to traffic

Projection of Impact to Car Traffic Volume on BRT Corridor in 2010

(33.5%)(23.4%

)

(40.4%)

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Car Traffic Modeling

Raster Map of line source Raster Map of CO emission

Map of line sources with car

traffic volumeCO emission factors

CO emission map with BRT

CO emission map without BRT

Comparison of CO emission map with and without BRT system

Emission Mapping(C)

Total Car Trips (D)

Vehicle emission database

Amount of CO emission

CO emission factor

Analysis : Impact to vehicle emission

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Analysis : Impact to vehicle emission

Result from Reduction of CO Emission with BRT System in 2010

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Benefit Cost Ratio of Corridor Segments

Analysis

0.0000

0.0500

0.1000

0.1500

0.2000

A B C D E F G H

Corridor Segment

Ben

efit/

Cos

t Rat

io

Value added to air quality increases till ‘E’ and decreases afterward

After ‘H” there is no longer benefit being added to air quality

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“Traffic Evaporation” (Goodwin et al. 1998) of up to 40% on BRT corridor

Reduction on average of 31% of Carbon Monoxide emission

Interpretation of Results

BRT system may bring positive impact to air quality, by reducing traffic and CO emission from private cars on the selected corridorBRT system may also shift the impact of air quality and car traffic to road outside the corridor

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Thank you

sridzuan74@yahoo.com

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Comparison of Car Traffic in 2010

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Need for an updated geodatabase

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Rail Based Public Transportation Service

Service Name Operation start

Length (Km) Number of Stations

Passenger/day

KTM – Komuter 1995 157 40 120000

STAR 1998 27 25 100000

PUTRA 1999 29 24 120000

Monorail 2003 10 11 1000*

ERL 2002 57 4 6500

         

Source: Ministry of Transportation, Malaysia