UNIVERSITI PUTRA MALAYSIA - psasir.upm.edu.mypsasir.upm.edu.my/4768/1/FPAS_2007_9A.pdf ·...

.

UNIVERSITI PUTRA MALAYSIA

MODEL DEVELOPMENT AND INTEGRATED ANALYSIS OF THE IMPACT OF TRAFFIC EMISSIONS ON AIR QUALITY IN URBAN

AREAS IN JAKARTA, INDONESIA

DOLLARIS RIAUATY SUHADI

T FPAS 2007 9




DOCTOR OF PHILOSOPHY UNIVERSITI PUTRA MALAYSIA

2007

ii

MODEL DEVELOPMENT AND INTEGRATED ANALYSIS OF THE IMPACT OF TRAFFIC EMISSIONS ON AIR QUALITY IN URBAN AREAS

IN JAKARTA, INDONESIA

By


Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia, in Fulfilment of the Requirement for the Degree of Doctor Philosophy

June 2007

DEDICATION

TO MY BELOVED HUSBAND AND MY SONS

BSTRACT

Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment of the requirement for the degree of Doctor of Philosophy



By


June 2007

Chairman: Professor Muhamad Awang, PhD

Faculty: Environmental Studies

This research aims to assess air quality status in the urban area of Jakarta and

evaluate the effect of traffic emissions control of selected air pollutants by

employing a Gaussian-plume dispersion model developed in Delphi. Sources of

air pollutants were divided into point, line, and area sources representing three

contributing sectors, i.e. industry, transport, and household. Input data for the

model was obtained from the government statistics and industrial and traffic

surveys conducted in other previous studies. Improvement of the model run-time

was done by developing a parallel implementation coded in a data-parallel

approach. The dispersion model performed reasonably in estimating the

concentrations of SO2 and NOx. Testing of the model resulted in the relative

standard errors of estimates of below 50% indicating the model could be

reproducible. However, the simulation of PM10 concentration resulted in

underestimation. The cause for this was the exclusion of other significant

sources of PM10 beside three contributing source categories under study.

iii

Prediction of future emissions using the 2002 emission data and socio-economic

factors which affect air quality revealed that the emissions of SO2, NOx, and

PM10 would increase by a factor of 1.64, 1.48, and 1.64, respectively in 2010 if

control of the pollutants emissions was not taken. Similarly, simulation of future

air quality under business-as-usual scenario resulted in increased pollutant

concentrations. The number of grids exceeding the annual NOx ambient standard

in 2010 was twice the number of grids exceeding the standard in 2002. Under

the scenario with control measures, the concentrations of pollutants, particularly

the transport-contributed PM10 were reduced by 44%. The reduction of PM10

concentration was a result of simulated implementation of vehicle inspection and

maintenance. Updating the emissions inventory to include other pollutant

contributing sources, and continued improvement of the dispersion model to fit

the best conditions of the urban area are suggested.

K

iv

Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Doktor Falsafah

PEMBANGUNAN MODEL DAN ANALISIS INTEGRASI TERHADAP KESAN SISA PELEPASAN KENDARAAN KEATAS KUALITI UDARA

DI KAWASAN BANDAR JAKARTA DI INDONESIA

Oleh


Juni 2007 Pengerusi: Profesor Muhamad Awang, PhD Fakulti: Pengajian Alam Sekitar

Kajian ini bertujuan untuk menilai tahap kualiti udara di sekitar bandaraya

Jakarta serta penilaian implikasi kawalan pelepasan pencemar udara trafik

dengan penggunaan model dispersi Gaussian yang dibangunkan oleh Delphi.

Sumber bahan pencemar udara telah di bahagikan kepada sumber titik, garisan

dan kawasan mewakili tiga sektor penyumbang iaitu, industri, pengangkutan dan

rumah kediaman. Data yang digunakan untuk model ini diperolehi dari statistic

kerajaan dan kajiselidik industri dan trafik beberapa kajian sebelum ini.

Peningkatan waktu simulasi model telah dilakukan dengan pembinaan kod

implementasi sejajar dalam pendekatan data sejajar. Pencapaian model dispersi

untuk menganggar kepekatan SO2 dan NOx adalah memuaskan. Hasil ujian ke

atas model ini pula menghasilkan sisihan lazim di bawah 50% dan ini

menunjukkan model ini boleh diterima. Walau bagaimanapun, simulasi

kepekatan PM10 menghasilkan keputusan kurang dari jangkaan. Ia adalah

v

vi

berpunca dari terkeluarnya sumber penyumbang PM10 yang lain selain dari tiga

kategori sumber pencemar yang dikaji.

Ramalan pelepasan pencemar masa hadapan dengan menggunakan data

pelepasan dan faktor sosio-ekonomi yang mendatangkan kesan pada kualiti

udara mendapati bahawa pelepasan SO2, NOx dan PM10 meningkat masing-

masing pada faktor 1.64, 1.48, dan 1.64 pada tahun 2010 sekiranya tidak ada

kawalan pada pelepasan pencemar ini. Pada keadaan yang sama, simulasi kualiti

udara masa hadapan pada senario ’perniagaan seperti biasa’ masih menunjukkan

peningkatan kepekatan pencemar. Bilangan grid melampaui standard ambien

NOx tahunan pada tahun 2010 iaitu dua kali ganda bilangan grid melampaui

standard tahun 2002. Di bawah senario dimana adanya langkah-langkah

kawalan, kepekatan pencemar, terutamanya pelepasan PM10 berpunca dari

pengangkutan, menurun sebanyak 44 %. Penurunan kepekatan PM10 adalah

hasil dari implementasi pemeriksaan dan penjagaan kenderaan. Adalah

dicadangkan untuk masa-masa hadapan, inventori pelepasan pencemar perlulah

merangkumi sumber-sumber penyumbang pencemar yang lain disamping

pembaikan beterusan pada model dispersi bersesuaian dengan keadaan yang

terbaik di kawasan bandaraya.

ACKNOWLEDGEMENTS

I would like to thank the Almighty God for the opportunity and grace to have

accomplished this research.

My sincere appreciation is extended to Professor Dr. Muhamad Awang, the

Chairman of my Supervisory Committee, for his continued support and tireless

supervision throughout the course of this program. I also wish to extend my

gratitude to Associate Professor Dr. Mohd Nasir Hassan, Associate Professor Dr.

Ramdzani Abdullah, and Associate Professor Dr. Azizi Hj. Muda for their

guidance and invaluable suggestion provided during the planning and

preparation of this thesis.

I also wish to acknowledge the help from my friends, Trisakti, Ady, Tengku

Sabrina, Penny Iskak, and Susilawati.

My deepest gratitude, however, goes to my husband for his endless support,

understanding and sacrifices, without which I would not have been able to carry

out this research. To my two wonderful sons, Dito and Hazim, thank you for

your love.

vii

I certify that an Examination Committee has met on 25 June 2007 to conduct the final examination of Dollaris Riauaty Suhadi on her Doctor of Philosophy thesis entitled “Model Development and Integrated Analysis on The Impact of Traffic Emission on Air Quality in Urban Areas in Jakarta, Indonesia ” in accordance with Universiti Pertanian Malaysia (Higher Degree) Act 1980 and Universiti Pertanian Malaysia (Higher Degree) Regulations 1981. The Committee recommends that candidate be awarded Doctor of Philosophy. Members of the Examination Committee are as follows: Wan Nor Azmin Sulaiman, PhD Professor Faculty Environmental Studies Universiti Putra Malaysia (Chairman) Azni B.Idris, PhD Professor Faculty Environmental Studies Universiti Putra Malaysia (Internal Examiner) Puziah Abdul Latif, PhD Faculty Environmental Studies Universiti Putra Malaysia (Internal Examiner) Peter Brimblecombe, PhD Professor School of Environmental Sciences University of East Anglica Norwick UK (External Examiner)

________________________________ HASANAH MOHD. GHAZALI, PhD Professor/Deputy Dean School of Graduate Studies Universiti Putra Malaysia Date:

viii

This thesis submitted to the Senate of Universiti Putra Malaysia and has been accepted as fulfillment of the requirement for the degree of Doctor of Philosophy. The members of the Supervisory Committee were as follows:

Muhamad Awang, PhD Professor Faculty Environmental Studies Universiti Putra Malaysia (Chairman)

Ramzani Abdullah, PhD Associate Professor Faculty Environmental Studies Universiti Putra Malaysia (Member)

Mohd Nasir Hassan, PhD Associate Professor Faculty Environmental Studies Universiti Putra Malaysia (Member) Azizi Hj. Muda, PhD. Associate Professor Faculty Environmental Studies Universiti Putra Malaysia (Member)

________________________ AINI IDERIS, PhD Professor/Dean School of Graduate Studies Universiti Putra Malaysia Date: 13 September 2007

ix

x

DECLARATION

I declare that the thesis is my original work except for quotations and citations which have been duly acknowledged. I also declare that it has not been previously, and is not concurrently, submitted for any other degree at Universiti Putra Malaysia or at any other institution. .


Date: 13 September 2007

TABLE OF CONTENTS

Page DEDICATION ii ABSTRACT iii ABSTRAK v ACKNOWLEDGEMENTS vii APPROVAL viii DECLARATION x LIST OF TABLES xiv LIST OF FIGURES xvi LIST ABBREVIATIONS xviii CHAPTER

1 INTRODUCTION 1.1 1.1 Framing the Problem 1.1 1.2 Research Objective 1.5 1.3 Significance of Research 1.5 1.4 Scope of Research 1.6 1.4.1 Calculation of Emissions Loads 1.7 1.4.2 Development of Dispersion Modeling System 1.8 1.4.3 Simulation of Present Air Quality and Testing of Model

Reproducibility 1.9

1.4.4 Assessment of Cost-effectiveness of Pollution Control Measures

1.10

1.4.5 Prediction of Future Emissions Loads 1.10 1.4.6 Simulation of Future Air Quality 1.11 2 LITERATURE REVIEW 2.1 2.1 Pollutant Emission Load 2.1 2.1.1 Emissions Estimation from Point Sources 2.1 2.1.2 Emissions Estimation from Area Sources 2.9 2.1.3 Emissions Estimation from Mobile Sources 2.10 2.2 Air Quality Modeling 2.17 2.2.1 Gaussian Dispersion Models 2.17 2.2.2 Meteorology of Air Pollution 2.39 2.3 Traffic Emissions 2.42 2.3.1 Overview 2.42 2.3.2 Factors Affecting Emissions 2.45 2.4 Policy Options for Transport Emission Control Measures 2.51 2.4.1 Policy Context 2.51 2.4.2 Policy Options 2.53 2.5 Cost-effectiveness Analysis 2.60 2.5.1 CEA Ratios 2.60 2.5.2 CEA with Scale Differences 2.61

2.5.3 Analysis 2.62 3.13 METHODOLOGY 3.1 3.1 Calculation of Emissions Loads 3.1 3.1.1 Industrial Sector 3.3 3.1.2 Household Sector 3.15 3.1.3 Transport Sector 3.18 3.2 Development of Air Quality Dispersion Model 3.29 3.2.1 Meteorological Pre-processing Model: PCRammet 3.30 3.2.2 Properties Representatives of the Meteorological Station

and Study Area 3.32

3.2.3 Hourly Values of Mixing Height 3.35 3.2.4 Pasquill-Gifford Stability Classes 3.36 3.2.5 Winds 3.38 3.3 Simulation of Present Air Quality and Testing of Model

Reproducibility 3.39

3.3.1 Point Sources 3.44 3.3.2 Line Sources 3.45 3.3.3 Area Sources 3.46 3.3.4 Testing of Model Reproducibility 3.47 3.3.5 Graphical Presentation 3.47 3.4 Assessment of Cost-effectiveness of Traffic Emissions Control

Measures 3.48

3.5 Prediction of Future Emissions Loads 3.50 3.5.1 Prediction of Future Emissions Loads under Business-as-

usual Scenario 3.51

3.5.2 Prediction of Future Emissions Loads with Traffic Emissions Control Measures

3.52

3.5.3 Simulation of Future Air Quality 3.53 4 RESULTS AND DISCUSSION 4.1 4.1 Pollutant Emissions in Study Area 4.1 4.1.1. Industrial Sector 4.1 4.1.2 Household Sector 4.10 4.1.3 Transport Sector 4.12 4.1.4 Total Emissions of Pollutants in Study Area 4.20 4.1.5 Spatial Distribution of Pollutant Emissions 4.21 4.1.6 Conclusion 4.27 4.2 Modeling Results 4.28 4.2.1 Profile of Meteorology in Study Area 4.29 4.2.2 Model Verification 4.31 4.2.3 Spatial Distribution of Pollutant Concentrations 4.40 4.2.4 Conclusion 4.45

xii

4.3 Predicted Future Emissions 4.46 4.3.1 Business-as-usual Scenario 4.46 4.3.2 Scenario with Control Measures 4.47 4.3.3 Conclusion 4.52 4.4 Simulation of Future Air Quality 4.53 4.4.1 Business-as-usual Scenario 4.54 4.4.2 Scenario with Control Measures 4.56 4.4.3 Conclusion 4.60 5 CONCLUSION AND RECOMMENDATIONS 5.1 5.1 Conclusion 5.1 5.2 Theoretical Implications 5.3 5.3 Policy Implications 5.4 5.4 Recommendations 5.5

REFERENCES APENDICES BIODATA OF STUDENT

R.1A.1B.1

xiii

LIST OF TABLES

Page Table 2.1 Estimated emissions in Jakarta Metropolitan in 1988 (in ton/year) 2.32.2 Estimated emissions in Jakarta in 1992 (in ton/year) 2.32.3 Air pollutant emissions from fuel burning in Jabodetabek in 1995 (in

ton/year) 2.3

2.4 Estimate of total TSP, PM10 and NOx emissions in Jakarta in 1990 (in ton/year)

2.4

2.5 Total emissions from stationary and mobile sources in Jabodetabek in 1995 (in ton/year)

2.4

2.6 Estimated emission factors for diesel passenger cars in g/km 2.162.7 Emission factors for passenger cars in g/km 2.162.8 Pasquill stability classes 2.212.9 Modified Pasquill’s stability class (in JICA study) 2.212.10 Power-law wind profile exponents (p) 2.222.11 Relationship between Pasquill-Gifford stability classes and

temperature stratification 2.28

2.12 Briggs formulas to calculate McElroy-Pooler (102 < x < 104 meters) – urban area

2.31

3.1 Emission factors of SO2 (industrial sector) 3.53.2 Sulfur content and specific gravity of fuels used 3.53.3 Emission factor of NOx (as NO2) 3.73.4 Emission factor of PM10 3.83.5 Efficiency of particulate removal 3.103.6 Emission factors for LPG and kerosene from residential fuel

combustion 3.16

3.7 Vehicle category and composition (in fraction of total vehicles) 3.233.8 Average travel speed (in km/hour) 3.253.9 Travel speed index 3.263.10 Emission factors of NOx, PM10, and SO2 for each vehicle category

(in g/km) 3.28

3.11 Properties representatives of the AWS 967490 station 3.343.12 Insolation classes as a function of solar altitude for cloud cover ≤ 5/10 3.373.13 Stability classification criteria 3.374.1 Number of factories by industrial type in 2002 4.24.2 Total fuel consumption by industry (incl. power plant) in 1995 4.34.3 Total fuel consumption by industry (incl. power plant) in 2002 4.44.4 Fuel consumption by LPS in 2002 4.54.5 Fuel consumption by factories (industrial area sources) in Jabodetabek

in 2020 4.5

xiv

4.6 Estimated emissions of SO2, NOx, and PM10 by facility type in 2002 (unit in kg/year)

4.6

4.7 Estimated emissions of SO2, NOx and PM10 from industrial area sources (excl. power plants and cement kilns) in 2002 (ton/year)

4.8

4.8 Total air pollutant emissions from industrial sector in Jabodetabek (2002)

4.8

4.9 Spatial distribution of emissions from industries in Jabodetabek, in ton/year (2020)

4.10

4.10 Total emissions loads from household sector in 2002 (ton/year) 4.114.11 Spatial distribution of emissions from household sector in 2002

(ton/year) 4.11

4.12 Vehicle kilometer traveled (106km/year) 4.124.13 Test of significant difference between emissions with different α

values 4.16

4.14 Total emissions from line mobile sources in 2002 (ton/year) 4.184.15 Total emissions from area mobile sources in 2002 (ton/year) 4.194.16 Total emission from transport sector in 2002 (ton/year) 4.204.17 Results of model testing 4.394.18 Projected fuel consumption in industrial sector in 2010 4.464.19 Projected fuel consumption in household and transport sectors in 2010 4.474.20 Total air pollutant emissions in 2010 (business-as-usual scenario) 4.474.21 Cumulative effectiveness of traffic emission control measures 4.484.22 Emissions reduction in 2010 (with control measures) 4.50

xv

LIST OF FIGURES

Page Figure 1.1 Map of Indonesia 1.121.2 Map of the study area of Jabodetabek region 1.132.1 Illustration of the modification of the standard dispersion parameter

curve 2.38

2.2 Temperature profile in the atmosphere 2.422.3 Factors affecting emissions 2.452.4 Policy options for reducing transport emissions 2.573.1 Flow diagram of the research sequence 3.23.2 Locations of large point sources under study in Jabodetabek 2002 3.43.3 Procedure for estimating emission of pollutants from industrial sector 3.143.4 Gridded study area with resolution of 1-km 3.153.5 Procedure for estimating pollutant emissions from households 3.173.6 Road segments made part of line mobile sources under study 3.203.7 Procedure for estimating emissions from transport sector 3.293.8 Structure of dispersion model 3.313.9 Parallelization of dispersion model 3.323.10 Downwind distance x and y from source to receptor 3.403.11 Approximate representation of a line source by multiple volume

sources 3.45

4.1 Air pollutant emissions from industrial sector 4.94.2 Sensitivity analysis of α in emissions (in developed areas) 4.164.3 Sensitivity analysis of α in emissions (in less-developed areas) 4.174.4 Total pollutant emissions in Jabodetabek in 2002 in comparison with

emissions in 1995 (unit in ton/year) 4.21

4.5 Land use map of Jabodetabek, 2002 4.224.6 Distribution of SO2 emission from LPS, 2002 4.234.7 Distribution of SO2 emission from industrial area sources, 2002 4.244.8 Distribution of PM10 emission from household area sources, 2002 4.244.9 Distribution of NOx emissions from line mobile sources, 2002 4.254.10 Distribution of SO2 emission from area mobile sources, 2002 4.254.11 Distribution of NOx emissions from area mobile sources, 2002 4.264.12 Distribution of PM10 emissions from area mobile sources, 2002 4.264.13 Windrose diagram of Jabodetabek, 2002 4.294.14 Frequency of wind speed in Jabodetabek, 2002 4.304.15 Frequency of stability class in Jabodetabek, 2002 4.314.16 Locations of automatic air quality monitoring stations, 2002 4.324.17 Comparison of monitoring data and simulated results for SO2 at JAF1

site, 2002 4.32

4.18 Comparison of monitoring data and simulated results for SO2 at JAF3 site, 2002

4.33

xvi

4.19 Comparison of monitoring data and simulated results for NOx at JAF4

site, 2002 4.33

4.20 Comparison of monitoring data and simulated results for NOx at JAF5 site, 2002

4.34

4.21 Comparison of monitoring data and simulated results for PM10 at JAF1 site, 2002

4.35


4.37


4.37


4.38


4.38

4.26 Distribution of annual simulated concentration of SO2 in the urban area of Jakarta, 2002

4.41

4.27 Distribution of annual simulated concentration of NOx in the urban area of Jakarta, 2002

4.42

4.28 Transport contribution of annual NOx simulated concentration in the urban area of Jakarta, 2002

4.43

4.29 Transport contribution of annual PM10 simulated concentration in the urban area of Jakarta, 2002

4.44

4.30 Distribution of annual simulated concentration of SO2 in the urban area of in 2010 under business-as-usual scenario

4.54

4.31 Distribution of annual simulated concentration of SO2 in the urban area of Jakarta, 2002 (same as Figure 4-26, showed for comparison with Figure 4.30 above)

4.55

4.32 Distribution of annual simulated concentration of NOx in the urban area of Jakarta in 2010 under business-as-usual scenario

4.57

4.33 Distribution of annual simulated concentration of NOx in the urban area of Jakarta, 2002 (same as Figure 4-27, showed for comparison with Figure 4.32 above)

4.57

4.34 Transport contribution of the annual PM10 concentration in the urban area of Jakarta in 2010 under scenario with control measures

4.58

4.35 Transport contribution of the annual PM10 concentration in the urban area of Jakarta in 2010 under business-as-usual scenario

4.58

4.36 Transport contribution of the annual NOx concentration in the urban area of Jakarta in 2010 under business-as-usual scenario

4.59

4.37 Transport contribution of the annual NOx concentration in the urban area of Jakarta in 2010 under business-as-usual scenario

4.59

xvii

LIST OF ABBREVIATIONS ADO Automotive Diesel Oil

BAPEDAL Badan Pengendalian Dampak Lingkungan

BAU business-as-usual

Bodetabek Bogor Depok Tangerang Bekasi

CEA Cost-effectiveness Analysis

CNG Compressed Natural Gas

CO carbon monoxide

CO2 carbon dioxide

CORINAIR Coordination Information on the Environment in the European Community – Air)

EMEP European Monitoring and Evaluation Program

GDP Gross Domestic Product

GIS Geographic Information System

g gram

g/lit gram per liter

GRDP Gross Regional Domestic Product

HC hydrocarbons

HSD High Speed Diesel

IDO Industrial Diesel Oil

IPCC Intergovernmental Panel on Climate Change

IPPS Industrial Pollution Projection System

Jabodetabek Jakarta Bogor Depok Tangerang Bekasi

JICA Japan International Cooperation Agency

xviii

JMDPR Jabotabek Metropolitan Development Plan Review

kg kilogram

kL kiloliter

LPG Liquified Petroleum Gas

LPS Large Point Source

m3 cubic meter

min minute

MFO Marine Fuel Oil

MoMR Ministry of Mining & Natural Resources

MTBE methyl tetra buthyl ether

NMSE Normalized Mean Square Errors

NOx nitrogen oxides

PM10 particulate matter with diameter up to 10 microns

SEE Standard Errors of Estimates

SO2 sulphur dioxide

toe ton oil equivalent

TSP Total Suspended Particulates

U.S.EPA United States of Environmental Protection Agency

μg microgram

UTM Universal Transverse Mercator

VKT Vehicle Kilometer Traveled

VOC Volatile Organic Carbon

WHO World Health Organization

xix

CHAPTER 1

INTRODUCTION

1.1 Framing the Problem

Road transport is a significant source of air pollution in urban centers (Johansson, 1995;

Chin, 1996). The impact of its exhaust emissions on human health and the environment

has raised much concern worldwide. Road transport, like any other modes of transport

has been partly responsible for greater atmospheric impacts such as acid deposition,

stratospheric ozone depletion, and climate change (Colville et al, 2001). To date, urban

traffic air pollution continues to be the focus of many air quality reviews and studies

despite the growing interest shown in global air pollution issues over the last decade.

For many years efforts to reduce traffic air pollution have been made through various

control measures including the introduction of vehicle technology, improvement of

transport system and fuel quality. As a result, traffic emissions have been reduced

substantially and some countries, mostly developed countries, reported that their

nation’s urban air quality has been improved (U.S.EPA, 2002; European Environment

Agency, 2005). In developing countries, however, with accelerating urban growth likely

to cause great increase in car ownership and use, efforts to reduce traffic emissions

remain to be seen. The challenge for the authority will be whether to act upon control

measures now to prevent air quality from getting more severe in the future or to delay

the implementation further until the damage costs in health, productivity, and economy

become enormous.

Many developing countries have developed their own air quality policy and strategy

based on their needs for improved air quality and relative findings of the status of air

quality and level of emissions. In many cases, the common strategy is often derived

from other countries’ experience, which has been proved to be successful. While it is not

necessary for a developing country to start from “the scratch” in finding what control

options work best for the country, the adoption should be done in a careful manner

because a control measure is country-specific. It may work in a certain country but may

not work in other country or may require modification to make it workable.

Indonesia, for example, first embarked its air pollution agenda in 1992 with the issuance

of “Blue Sky” program aimed at reducing air pollution in target provinces. Air quality-

related regulations have been revised or newly issued since then, including the revision

of the national ambient standard and the establishment and continued improvement of

emissions standards for both mobile and stationary sources. Control measures for traffic-

related emissions as stated in the program provisions, which are also in line with

recommendations from previous foreign-funded studies include emission regulations

through inspection and maintenance, phase-out of leaded gasoline, reduction of sulfur

content in diesel fuel, introduction of clean vehicle technology and use of smokeless oil

for two-stroke vehicles (Shah et al, 1997; Japan International Cooperation Agency –

JICA and Environmental Impact Control Agency – BAPEDAL, 1997a).

Despite the availability of regulatory instruments and proposed action plans for

Indonesia, implementation has not begun until today. Lacks of public and political wills

are the major factor, which contributes to the implementation failure of many

1.2

regulations. Provisions with regard to institutional resources, technical procedures, and

detailed administration of the regulations are not clearly defined. Unclear lines of

authority and responsibility of government agencies have often attributed to the delay of

the formulation of these implementing provisions (D. Kuper, personal communication,

October 2, 1996). Other shortcomings, in general, include lack of control and law

enforcement and shortage of well-trained personnel (Shah et al, 1997).

The newly enacted Regional Autonomy Law No. 22/1999 that stipulates in its provisions

an extended transfer of environmental policy resources and regulatory authority from the

central government to local governments is significant for the interest of air pollution

control efforts. Some areas of many environmental problems will be addressed by local

governments. Such transfer would pose a potentially formidable test for both the local

government and the public as they become much closer to the real problem and are more

challenged to tackle the problem. Public participation is central that will help the local

government to move forward to formulate and execute its action plans without further

delay (Shah, 2004).

The Provincial Government of Jakarta, in this regard, has taken initiative and advanced

into setting up a coordinating body that will oversee the implementation of emission

regulations in the Province of Jakarta. The approach is directed towards achieving air

quality objectives (air quality standards) and economic objectives (reduction of damage

costs) by implementing cost-effective air pollution control measures in line with the

national pollution control strategy. Road transport is being the target source of control.

Through active role of advocacy groups and other interest groups in Jakarta, air

1.3

UNIVERSITI PUTRA MALAYSIA - psasir.upm.edu.mypsasir.upm.edu.my/4768/1/FPAS_2007_9A.pdf ·...

Documents

Transcript of UNIVERSITI PUTRA MALAYSIA - psasir.upm.edu.mypsasir.upm.edu.my/4768/1/FPAS_2007_9A.pdf ·...