The effect of biodiesel utilization in transportation sector to pollutant emission and external cost case study Jakarta

THE EFFECT OF BIODIESEL UTILIZATION IN

TRANSPORTATION SECTOR TO POLLUTANT EMISSION AND

EXTERNAL COST: CASE STUDY JAKARTA

(

EFEK PENGGUNAAN BIODIESEL PADA EMISI POLUTAN DAN BIAYA

EKSTERNAL DI SEKTOR TRANSPORTASI: STUDI KASUS JAKARTA

₎

SONI SOLISTIA WIRAWAN

A Dissertation

Submitted in partial fulfillment of the requirements for the Degree of Doctor in Agricultural Engineering Sciences

THE GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY (IPB)

BOGOR

i.

STATEMENT OF RESEARCH ORIGINALITY

Hereby, I state that the dissertation entitled “The Effect of Biodiesel Utilization in Transportation Sector to Pollutant Emission and External

Cost: Case Study Jakarta.” is my own work, which has never previously been

published in any university. All of incorporated originated from other published as well as unpublished papers are stated clearly in the text as well as in the references.

Bogor, June 2009

Soni Solistia Wirawan

ii

ABSTRACT

SONI SOLISTIA WIRAWAN. The Effect of Biodiesel Utilization in

Transportation Sector to Pollutant Emission and External Cost: Case Study

Jakarta. Under direction of ARMANSYAH H. TAMBUNAN, MARTIN

DJAMIN, HIROSHI NABETANI, and ARIEF SABDO YUWONO.

World wide numerous studies have proved that biodiesel is an environmentally friendly alternative diesel fuel. Biodiesel is essentially sulphur free and engines fueled by biodiesel emit significantly fewer particulates, hydrocarbons and less carbon monoxide than that of operating conventional diesel fuel. The maximum utilization of biodiesel in Indonesia could improve the air quality level in major cities especially in Jakarta. The most significant hurdle for broader commercialization of biodiesel in Indonesia is its cost. Thus acceptance of biodiesel in Indonesia is more influenced by pricing factor. The advantages of biodiesel such as a renewable energy, lower exhaust gas emission and effect to the longer engine life time are often ignored.

The objective of this research was to assess the effect of biodiesel utilization in transportation sector to the air pollution level, health and economic impact which could be transferred into monetary values in the term of external-cost. Jakarta was selected as a targeted research location due to the fact that Jakarta is the capital city with the most densed population, highest mineral diesel fuel consummer, and most polluted city compared to other big cities in Indonesia

The targeted emission in the study were carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons (HC), sulphur dioxide (SO2) and particulate matter (PM)

from vehicle sources. The external cost of B10 and B20 utilization in 2010, 2015, 2020 and 2025 scenarios compared to the base (non biodiesel) case (B0) in 2005 was calculated by using the analysis of emission dispersion effect method which is most known as Impact Pathway Analysis (IPA). The method consisted of four steps, that are : to quantify the emission, to define the dispersion and transformation of emission for calculating the ambient concentration, to estimate the physical effects by using the dose response function, and to determine the monetary value of the damage for calculating the external costs.

The result showed that utilization of biodiesel could potentially improve air quality level in Jakarta. The utilizations of B10 and B20 in 2010 compared to the base (non-biodiesel) case may reduce external cost by 13.4 and 59.0 billion Rupiah and they increase by 25.2 and 105.7 billion Rupiah in 2025. Since those values may rise as biodiesel blend composition is increased, it necessitates performing simulation on B50 and B100 scenarios. External cost reduction may achieve its maximum value of 447.7 billion Rupiah when B100 is introduced in 2025. Taking into account the diesel fuel consumption for the transportation sector in 2010 and 2025, the reduction translates into external cost of Rp. 4 to 18 per liter for B10 and B20 respectively. Moreover, provided such a diesel engine fueled by B100 is available, the external cost reduction could reach up to Rp. 90 per liter. The implication of this finding suggests that the polluter (motorist) should be willing to pay additional 4 to 90 Rupiah per liter depending on the biodiesel content in the diesel fuel blend.

iii

SUMMARY

SONI SOLISTIA WIRAWAN. The Effect of Biodiesel Utilization in

Transportation Sector to Pollutant Emission and External Cost: Case Study

Jakarta. Under direction of ARMANSYAH H. TAMBUNAN, MARTIN

DJAMIN, HIROSHI NABETANI, and ARIEF SABDO YUWONO.

Biodiesel development in Indonesia has been started since more than ten years ago but gained significant milestones in 2006 when the Indonesian government issued formally blending permit regulation of 10% biodiesel with mineral diesel fuel and PERTAMINA (Mineral oil State owned company) launched biodiesel blend B5 formally at public gasoline station with the trade name of BIOSOLAR. To continue reducing Indonesia’s dependency on fossil resources for its energy source and to improve the air quality level in its major cities, PERTAMINA has been expanding BIOSOLAR market at almost all fuel outlets in Java and will continuously open outlets in all parts of Indonesia. Moreover, the state owned company will increase the blending content at least up to B20 in 2025 as stated on President Decree No. 5/2006 regarding the National Energy Policy.

Despite efforts by the government and Pertamina, broader commercialization of biodiesel in Indonesia could not achieve its target. The most significant hurdle found is its cost. In addition, the consumers mostly still consider the fuel price in selecting the fuel for their cars. Fluctuation of biodiesel price which is usually higher than that of mineral diesel and lack of subsidy given to biodiesel cause the price of biodiesel blend fuel is often higher than the standard mineral diesel fuel. On the other hand, the advantages of biodiesel such as a renewable energy, lower exhaust gas emission and effect to the longer engine life time is often ignored. Overcoming these drawbacks is by imposing the “polluter pay principle” which would internalize as many of the externalities. Having derived monetary values to reflect the external costs of differing technologies, the next step is to devise a mechanism for “internalizing” them into market prices.

The objective of this research was to assess the effect of biodiesel utilization in transportation sector to the air pollution level, health and economic impact which could be transferred into monetary values in the term of external-cost. Jakarta was selected as a targeted research location due to the fact that Jakarta is the capital city with the most densed population, highest mineral diesel fuel consummer, and most polluted city compared to other big cities in Indonesia. The targeted emission in the study are carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons (HC), sulphur dioxide (SO2) and particulate matter (PM) from vehicle sources. The study will determine the external costs of transportation energy use using model simulations. Each simulation was based on the scenario in line with the development pattern of government policy. By comparing the base case (B0) with biodiesel blends cases (B10, B20, B50, B100) for the projection year until 2025, the strategy for reducing the external costs could be compiled.

The study was performed using the analysis of emission dispersion effect method that is mostly known as an Impact Pathway Analysis (IPA). The impact

iv pathways methodology has been used in a large number of research projects and policy application related studies. The method consists of four steps, that are : to quantify the emission, to define the dispersion and transformation of emission for calculating the ambient concentration, to estimate the physical effects by using the dose response function, and to determine the monetary value of the damage for calculating the external costs.

The application of IPA starts from identifying emission sources, defining the emission source characteristics, and determining the type of emission which will be analyzed. Each type of vehicle has a specific emission coefficient depending on its technology and the type of fuel used. Specific study on the performance and emission evaluation on automotive diesel engine as affected by palm biodiesel fuel utilization has been conducted. The result shows that the emission of CO, HC, SO2 and PM decreased considerably with the increase in biodiesel blend. The reduction in particle emission was very sharp at 10% blend (B10), while the sharp reduction in HC emission started at 20% blend (B20). In contrast to those generally found in the previous non palm biodiesel studies, the results in this study shows lower NOx emission as well as higher torque and power for biodiesel blend compare to that of pure petro-diesel fuel. This result could be as a consequence of the properties of the tested palm biodiesel, which has higher cetane number and lower viscosity value compared to the petro-diesel fuel sample. This study result was used for determining the emission coefficient for the model input. Two cases (low and high) of emission coefficient was determined for the model input.

Second step of the Impact Pathways Analysis is calculation of pollutant concentration changes (dispersion). These predictions are carried out by simulating air pollutant concentration or dispersion model. An ideal air pollutant concentration model should be able to predict the amount of specific pollutant emission, for any specified meteorological condition, at any location, for any time of period, with sufficiently reliable confident level. Several aspects should be considered when selecting a good model and they have to be:

(i) suitable with the study objective, (ii) Simple and easy to operate and

(iii) calibrated and model precission have been proven and used by other similar projects.

This study employs the MLuS model because it is simple model, suitable for movable emission source, capable in estimating the pollutant concentration near roadside. In addition many projects in Europe as well as in Indonesia have used this model for their simulation. For this study, vehicle emission is categorised as a line source emission.

Results evaluation of the performed two cases of studies (low and high emission cases) and validation against previous Jakarta’s air quality studies have concluded that the result of external cost of high emission coefficient case is more acceptable. The reason is that low emission coefficient data was determined from almost latest diesel engine tecnology (produced between years 2004 – 2008) and has utilised direct injection method. Thus, the emission coefficient was too small.

Comparing to the base case (B0) in year 2005, the result showed that reduction of external cost because of biodiesel utilization in 2010 gradually rose

v from only 13.4 billion rupiah for B10 case to become 59 billion rupiah for B20, 133.7 billion rupiah for B50 case and reached up to 245 billion rupiah for B100. The cost increases as a function of time due to the continuously growing of fuel consumption and population density. Introducing B20 in 2025 will increase the external cost reduction of 105.7 billion rupiah and reach the maximum value of 447.7 billion Rupiah when B100 used in 2025.

The simplest way to internalize the externality of the utilization of biodiesel is adding the estimated external value to the product price paid directly by the polluter. For this case of study, the value of external cost should be paid by the polluter can be estimated by dividing the external cost with the fuel consumption. Comparison to the base (non-biodiesel) case has resulted in a gradual increase in the reduction of external cost from 4 rupiah per liter of B10 in 2010 to the maximum of 90 rupiah per liter of B100 in 2025. The result seems too small to attract local government of DKI Jakarta to implement the utilization of biodiesel as an environmentally friendly alternative fuel. One should remember however, that this is only one among other external cost parameters that could be internalized. The other advantages of biodiesel including being a renewable energy, supporting the national energy diversification (country energy sustainability) program, biodegradable fuel, and may prolong lifetime can be potentially valued and estimated as the total external cost.

vi

RINGKASAN

SONI SOLISTIA WIRAWAN. The Effect of Biodiesel Utilization in

Transportation Sector to Pollutant Emission and External Cost: Case Study

Jakarta. Under direction of ARMANSYAH H. TAMBUNAN, MARTIN

DJAMIN, HIROSHI NABETANI, and ARIEF SABDO YUWONO.

Pengembangan biodiesel di Indonesia telah dimulai sejak lebih dari sepuluh tahun yang lalu. Akan tetapi kemajuan yang signifikan baru dicapai pada tahun 2006, sejak pemerintah Indonesia secara resmi mengeluarkan ijin pencampuran biodiesel dengan minyak solar maksimum 10% (B10) dan PERTAMINA mulai resmi menjual bahan bakar campuran biodiesel-solar B5 di stasiun pompa pengisian bahan bakar umum (SPBU) dengan merek dagang BIOSOLAR. Untuk mengurangi ketergantungan kepada Bahan Bakar Minyak (BBM) dan memperbaiki tingkat kualitas udara (terutama di kota-kota besar), maka PERTAMINA memperluas penjualan BIOSOLAR dengan membuka outlet di seluruh SPBU di Pulau Jawa dan akan terus membuka di semua wilayah yang tersebar di seluruh Indonesia. Kandungan biodiesel pada campuran juga akan ditingkatkan terus hingga mencapai komposisi B20 pada tahun 2025, sesuai dengan yang target yang telah ditetapkan pada Surat Keputusan Presiden No. 5/2006 tentang Kebijakan Energi Nasional.

Ada beberapa kendala yang menghambat pencapaian target komersialisasi biodiesel oleh PERTAMINA. Hambatan terbesar adalah masalah harga. Faktor harga masih menjadi pertimbangan yang dominan bagi masyarakat di Indonesia dalam menentukan pilihan bahan bakar untuk digunakan pada kendaraannya. Harga biodiesel masih cenderung lebih mahal daripada minyak solar, karena hingga saat ini biodiesel masih dikategorikan dalam klasifikasi “bahan bakar lain” yang harus dijual pada harga keekonomian dan tidak mendapatkan subsidi. Di sisi lain, kelebihan biodiesel sebagai bahan terbarukan yang lebih ramah lingkungan dan memiliki kelebihan terhadap unjuk kerja dan umur mesin masih kurang dipertimbangkan. Salah satu cara untuk mengatasi permasalahan harga ini adalah dengan menerapkan prinsip “polluters pay principle”.

Produsen produk yang menghasilkan polutan wajib membayar sejumlah tertentu kepada masyarakat yang terkena polutan (polluters pay principle) atau melakukan upaya agar polutan yang dihasilkan tidak melebihi ambang batas yang ditentukan. Karena produsen dikenai biaya tambahan maka produsen akan membebankan biaya tambahan ini ke dalam harga produk yang dihasilkan. Konsep yang demikian ini disebut internalisasi eksternalitas. Besaran nilai biaya eksternal dapat dibedakan dari jenis teknologi pembuatan produknya. Setelah nilai biaya eksternal ditentukan, maka langkah selanjutnya adalah menentukan mekanisme dan cara untuk menginternalisasi eksternalitas tersebut ke dalam harga pasar.

Tujuan dari penelitian ini adalah untuk mengetahui efek dari penggunaan biodiesel di sektor transportasi pada tingkat polusi udara dan dampaknya pada kesehatan serta ekonomi, yang kemudian dapat dihitung ke dalam suatu nilai ekonomi dengan istilah biaya eksternal. Kota Jakarta dipilih sebagai lokasi target penelitian, karena Jakarta adalah merupakan ibu kota negara yang memiliki

vii jumlah penduduk yang terpadat, pengguna minyak solar untuk sektor transportasi paling banyak dan sebagai kota dengan tingkat polusi paling tinggi dibandingkan dengan kota-kota besar lainnya yang ada di Indonesia. Jenis emisi yang dihitung pada penelitian ini adalah karbon monoksida (CO), nitrogen oksida (NOx), hidrokarbon (HC), sulphur dioksida (SO2) and partikel (PM) yang dilepaskan dari kendaraan bermotor. Penentuan biaya eksternal dari penggunaan energi di sektor transportasi pada penelitian ini dilaksanakan melalui suatu perhitungan simulasi dengan mempertimbangkan skenario pengembangan BBN seperti yang telah ditetapkan oleh pemerintah. Strategi untuk mengurangi biaya eksternal dapat ditentukan dengan cara membandingkan kasus dasar (B0) dengan kasus penggunaan berbagai komposisi campuran biodiesel-solar (B10, B20, B50, B100) untuk proyeksi tahun 2005 hingga tahun 2025.

Biaya eksternal dihitung menggunakan analisis penyebaran dampak dari emisi atau lebih dikenal dengan sebutan Impact Pathway Analysis (IPA). Metode yang telah banyak digunakan pada berbagai proyek penelitian di dunia ini, terdiri atas empat tahapan yaitu: melakukan kuantifikasi emisi, menentukan penyebaran dan transformasi emisi untuk menghitung konsentrasi ambien, mengestimasi dampak fisik dengan menggunakan fungsi dose respons, dan menentukan nilai moneter dari kerusakan untuk menghitung biaya eksternal.

Penerapan IPA dimulai dari identifikasi sumber emisi, menentukan karakteristik sumber emisi, serta menentukan jenis emisi yang akan dianalisis. Setiap jenis kendaraan mempunyai koefisien emisi tertentu tergantung dari teknologi dan jenis bahan bakar yang digunakan. Hasil evaluasi dari studi dampak penggunaan biodiesel terhadap unjuk kerja mesin dan emisi yang telah dilakukan menunjukan bahwa emisi CO, HC, SO2 dan PM berkurang dengan bertambah besarnya komposisi biodiesel dalam campuran minyak solar.

Pengurangan emisi partikel sangat tajam pada komposisi campuran biodiesel 10% (B10), sedangkan pengurangan emisi HC yang tajam dimulai pada campuran B20. Berbeda dengan hasil yang dikemukakan pada hasil studi biodiesel non sawit pada umumnya, hasil evaluasi biodiesel sawit pada studi ini menunjukkan penurunan emisi NOx dan lebih besarnya torsi dan daya dari campuran biodiesel dibandingkan dengan mesin berbahan bakar minyak solar murni. Hasil yang berbeda ini mungkin sebagai akibat dari sampel biodiesel sawit yang diuji memiliki angka setana yang lebih besar dan viskositas yang lebih kecil dibandingkan dengan sampel minyak solar murni yang diuji. Koefisien emisi yang dihasilkan dari studi ini digunakan sebagai salah satu dari beberapa literatur yang digunakan dalam menentukan koefisien emisi untuk input model. Simulasi perhitungan dilakukan dengan menggunakan dua kasus harga koefisien emisi, yaitu kasus harga koefisien emisi yang rendah dan tinggi sebagai data input.

Langkah kedua dari empat langkah metoda IPA adalah perhitungan perubahan kosentrasi polutan (dispersi). Prediksi dilakukan melalui perhitungan model konsentrasi polutan udara atau dengan model dispersi. Suatu model perhitungan konsentrasi polutan udara yang ideal dapat menghasilkan besarnya emisi polutan yang spesifik, pada berbagai kondisi meteorologi yang spesifik, lokasi dimana saja, pada periode waktu berapa saja, dengan tingkat kepercayaan yang dapat diandalkan. Ada beberapa pertimbangan yang perlu diperhatikan dalam memilih model yang baik: (i) sesuai dengan kasus yang diteliti, (ii)

viii sederhana dan mudah dioperasikan dan (iii) sudah terkalibrasi dan ketelitian model sudah dibuktikan penggunaannya pada proyek yang sejenis. Emisi dari kendaraan bermotor diklasifikasikan sebagai sumber emisi yang bergerak (line source). Model MluS dipilih untuk digunakan pada penelitian ini dengan alasan bahwa MluS merupakan model yang sederhana, sesuai untuk sumber emisi bergerak, model cocok untuk memperkirakan besarnya konsentrasi dekat pinggir jalan dan model ini juga telah banyak digunakan dalam banyak proyek baik di negara-negara Eropa maupun di Indonesia.

Evaluasi hasil simulasi dari dua kasus yang diteliti (kasus koefisien emisi rendah dan tinggi) dan setelah di validasi dengan data hasil penelitian kualitas udara di Jakarta sebelumnya, dapat disimpulkan bahwa besarnya biaya eksternal dari hasil perhitungan kasus koefisien emisi tinggi lebih dapat diterima. Hal ini mungkin disebabkan karena kasus harga koefisien emisi rendah ditentukan dari data mesin diesel dengan teknologi tinggi (kendaraan bermesin diesel yang diproduksi antara tahun 2004 sd 2008 dan telah menggunakan teknologi injeksi langsung (direct injection technologi)), sehingga harga koefisien emisi yang didapatkan terlalu rendah.

Hasil perhitungan menunjukkan bahwa dibandingkan dengan kasus dasar (tidak menggunakan biodiesel) pada tahun 2005, pengurangan biaya eksternal sebagai dampak dari penggunaan biodiesel pada tahun 2010 meningkat secara bertahap dari mulai 13,4 milyar rupiah untuk kasus B10, menjadi 59 milyar rupiah untuk B20, 133,7 milyar rupiah untuk B50 dan mencapai harga 105,7 milyar rupiah untuk B100. Nilai tersebut meningkat terus dengan fungsi waktu, meningkatnya kepadatan penduduk dan bertambahnya konsumsi bahan bakar. Pengurangan biaya eksternal maksimum sebesar 447,7 milyar rupiah dicapai ketika B100 digunakan pada tahun 2025.

Cara yang paling sederhana untuk menginternalisasi eksternalitas dari penggunaan biodiesel adalah dengan menambahkan harga estimasi biaya eksternal ke dalam harga produk yang nantinya akan dibayar langsung oleh pengguna bahan bakar (polluter). Pada penelitian ini harga biaya eksternal dapat diestimasi dengan membagi besarnya biaya eksternal dengan konsumsi minyak solar. Hasil menunjukkan bahwa dibandingkan dengan kasus dasar (tidak menggunakan biodiesel) , pengurangan biaya eksternal akan meningkat mulai dari 4 rupiah per liter pada skenario penggunaan B10 di tahun 2010 sampai dengan maksimum 90 rupiah per liter pada skenario B100 di tahun 2025. Hasil ini mungkin terkesan terlalu kecil untuk menarik pemeritah daerah DKI Jakarta untuk merealisasikan program pemanfaatan biodiesel sebagai bahan bakar yang ramah lingkungan. Akan tetapi mesti diingat bahwa biaya eksternal dari penurunan emisi ini hanyalah salah satu biaya eksternal yang dapat dihitung dan diinternalisasikan ke harga produk. Kelebihan lain dari biodiesel yang merupakan bahan bakar terbarukan, mendukung program pemenuhan energi yang berkelanjutan,

merupakan bahan bakar yang mudah terurai (biodegradable), dapat

memperpanjang umur mesin, dan lain-lain juga berpotensi untuk dinilai dan diestimasi sebagai total biaya eksternal.

ix

@ Copyright 2009 by IPB All rights reserved

1. No part or all of this dissertation may be excerpted without inclusion or mentioning the sources

a. excerption only for research and education use, writing for scientific papers, reporting, critical writing or reviewing of a problem.

b. excerption doesn’t inflict a financial loss in the proper interest of IPB 2.No part or all of this dissertation may be transmitted and reproduced in any forms without a written permission from IPB.

x

THE EFFECT OF BIODIESEL UTILIZATION IN

TRANSPORTATION SECTOR TO POLLUTANT EMISSION

AND EXTERNAL COST: CASE STUDY JAKARTA

(EFEK PENGGUNAAN BIODIESEL PADA EMISI POLUTAN DAN

BIAYA EKSTERNAL DI SEKTOR TRANSPORTASI: STUDI KASUS

JAKARTA)

by

SONI SOLISTIA WIRAWAN

A Dissertation

Submitted in partial fulfillment of the requirements for the Degree of Doctor in Agricultural Engineering Sciences

THE GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

BOGOR

The external assessor for closed examination are:

1.

Dr. Ir. Abdul Kohar I., M.Sc.

2.

Dr. Dadan Kusdiana

The external assessor for opened examination are:

1.

Dr. Ir. Y. Aris Purwanto

xi Title of Dissertation : The Effect of Biodiesel Utilization in Transportation Sector to Pollutant Emission and External Cost: Case Study Jakarta

Name : Soni Solistia Wirawan

NIM : F161060032

Approved by, Advisory Committee

Prof. Dr. Armansyah H. Tambunan Prof. (R). Dr. Martin Djamin, M.Sc.

Chairman Member

Prof.Dr. Hiroshi Nabetani Dr. Arief Sabdo Yuwono

Date of Examination: Date of Graduation:

Member Member

Acknowledged by,

Head of Study Program in Dean of the Graduate School Agricultural Engineering Science

xii

ACKNOWLEDGMENT

For the completion of this dissertation I would like to express my most profound gratitude to Prof. Dr. Armansyah H. Tambunan as the chairman of the advisory committee and all members of advisory committee; Prof. (R). Dr. Martin Djamin, Msc., Prof. Dr. Hiroshi Nabetani and Dr. Arief Sabdo Yuwono for all valuable assistance, supports and their tireless and patient counsel.

I wish to express my sincere appreciation to Dr. Kusmayanto Kadiman, the Minister of Ministry of Research and Technology for introducing me to the “Program Rintisan Pendidikan Gelar Pascasarjana - KNRT” and motivate me to pursue this study program. To Dr. Marzan A. Iskandar, the Chairman of BPPT for his permission and support. I would like also to express my appreciation to Prof. (R). Dr. Wahono Sumaryono for his assistance and constant motivation. To Prof. Dr. Ir. Prawoto, MSAE and Dr. Dadan Kusdiana who have reviewed our article for international journal publication. Particular thanks are also due to Ir. Agus Sugiyono, M.Eng. who introduced me to the MLuS dispersion model, to Ir. Rizqon Fajar, M.Eng. for valuable discussion on vehicle emission coefficient related topic. To all members of BRDST-BPPT and Agricultural Engineering Science Study Program of IPB, who have contributed in various ways to the completion of this dissertation. I would like also to express my appreciation for the support of the following institutions: BRDST-BPPT, BTMP-BPPT, PT. Toyota Astra Motor, PT. Pertamina, BMG, Balai Teknologi Kesehatan dan Lingkungan (BTKL) and Dinas Lalu Lintas Jalan Raya DKI Jakarta. To the Government of Indonesia through the “Program Rintisan Pendidikan Gelar Pascasarjana - KNRT” scholarship program. Thanks to Prof. Dr. Ir. Carunia M. Firdausy, MA., APU and team members who organize this scholarship program.

Finally, I would like to dedicate this research work to my family, my wife (Ika Sandra), my daughters (Nike Nadia and Daniya Fathiya) and my sons (Noval Hudiya and Dafa Fadiya), for their love, continuous encouragement and constant support in my life.

Bogor, June 2009 Soni Solistia Wirawan

xiii

BIOGRAPHY

Soni Solistia Wirawan (author) was born in Bandung on October 10th, 1961 as the youngest of the four children of father Sujud Andjar Sumyana and mother Kustinah Djajadiredja. In 1980, he was graduated from SMAN III Bandung and continued his under graduate study in Mechanical Engineering Faculty of Brawijaya University in Malang and graduated in 1986. He continued his study in Master Degree Program in Mechanical System Engineering Department of Nagaoka University of Technology, Japan in 1996 with scholarship from the government of Japan (Mombusho) and was graduated in 1998. In 2006 he got scholarship for PhD by research program in Agricultural Engineering Science, the Graduate School, Bogor Agricultural University (IPB) from The Ministry for Research and Technology of Indonesia. Author has been working as a researcher at The Agency for the Assessment and Application of Technology (BPPT) since 1987 and since 2002 up to now he is responsible as the head of Engineering Center - BPPT.

During his study in PhD program, one of his paper “The Current Status and Prospects of Biodiesel Development in Indonesia: a review” has been presented at the third Asia Biomass Workshop in Tsukuba, Japan, on November 17, 2006. Four papers have been published in accredited national and international scientific journal; a paper titled “The Effect of Palm Biodiesel Fuel on the Performance and Emission of the Automotive Diesel Engine” has been published in the CIGR Ejournal. Manuscript EE 07 005. Vol. X, April. 2008. A paper titled “Validation of Measured Blend Biodiesel–Mineral Diesel Specification by Using a Simple Calculation Method” has been published in Jurnal Keteknikan IPB, Vol. 21 No. 3, September 2008. A paper titled “Study of Effect of Biodiesel Utilization to the Transportation Sector Emission in Jakarta” has been published in Jurnal Teknologi Lingkungan BPPT, Vol. 9 No. 2, Mei 2008. And a paper titled “Study of Determinantion of Optimum Composition of Biodiesel-Petrodiesel blend Fuel”, has been published in Majalah Teknologi Lingkungan BPPT, Vol. 4 No. 2, May 2008. All of above mentioned papers were written as a part of the author’s PhD program.

xiv

LIST OF CONTENTS

LIST OF TABLES ………... LIST OF FIGURES ………. LIST OF APPENDICES ………. LIST OF NOMENCLATURE ………. LIST OF ABBREVIATIONS ……….. 1. INTRODUCTION

Background of the Research ……… Objective of the Research ….……… Benefit of the Research ………... …….…… Boundaries and Methodology ……….. Outline of Dissertation ………. 2. THE EFFECT OF PALM BIODIESEL FUEL ON THE

PERFORMANCE AND EMISSION OF THE AUTOMOTIVE DIESEL ENGINE

Introduction ………... Materials and Methods ... Result and Discussion ... Conclusion ... 3. THE EFFECT OF BIODIESEL UTILIZATION ON

TRANSPORTATION SECTOR EMISSION IN JAKARTA

Introduction ………... Materials and Methods ... Result and Discussion ... Conclusion ... 4. BIODIESEL BLENDING SCENARIO

Introduction ………... Materials and Methods ... Result and Discussion ... Conclusion ...

Page xvi xx xxii xxiii xxv

1 3 4 4 9

10 19 24 29

30 32 33 44

45 47 48 56

xv 5. EMISSION DISPERSION MODEL

Introduction ………... Materials and Methods ... Result and Discussion ... Conclusion ... 6. EXTERNAL COST ANALYSIS

Introduction ………... Materials and Methods ... Result and Discussion ... Conclusion ... 7. GENERAL DISCUSSION ……… 8. CONCLUSIONS ………... REFERENCES ……….. APPENDICES ...

58 60 65 100

102 106 109 117 119 129 131 138

xvi

LIST OF TABLES

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Comparison of fossil diesel fuel with vegetable oil characteristic ... Vegetable Oil Methyl Esters (VOME) characteristic ... Current worldwide production of nine major vegetable oils... Potential vegetable oil plants in Indonesia …………... Characteristics of pure petro-diesel and biodiesel used in the research Emission of biodiesel blend as compared to euro II regulation ... Reduction in Health Costs caused by the Abatement Policies ... The list of the growth of vehicle number projection input data ……… Parameters for vehicle number projection ………. Specific fuel consumption, mileage and yearly effective operation ... Emission factor for each type of vehicles ………. Comparison of emission value of BAU and biodiesel scenario ... Comparisons of Fossil Diesel Fuel (FDF) and Biodiesel Fuel (BDF) characteristics ………... Comparison of SNI 04-7182-2006, and B20 (EMA) ... Diesel oil 48 specification ………. Price of biodiesel-petrodiesel blend ... Relatif toxicity of air pollutant ... The value of emission parameter ... The value of emission and engine performance parameter (short term engine effect) ... The score of long term engine effect ... The score of price parameter ... The ranking of optimum biodiesel-petrodiesel composition ... Energy source type reated to sector ... Comparison between gaussian and MLuS model ... Standard qualification and air qualities by measure location

in the year of 2006 ……….

Page 11 13 16 18 22 29 31 38 39 40 42 43 46 49 51 52 53 54 54 55 56 56 59 59 67

xvii 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55

Data convention for grids establishment ………... Deviation of calculated grids compare to and BPS existing data ……. Population per area of DKI Jakarta ………... Population projection at district in DKI Jakarta ……… Road length based on district area (in meter), 2006 ... Vehicle number at selected case, 2005 road (base) ……….. Traffic density classification ……… Volume of vehicle passing the toll road according to BPS ………….. Projection of vehicle number and AADT ………. Share of each type of vehicle ……… Emission coefficient (g/km) according to BPPT – KFA study ……… Emission coefficient (g/km) according to Lestari’s study …………... Emission coefficient (g/km) according to MoE ……… Formula for the correlation between the masured engine capacity and emision coefficient (regression result) ... The value of coefficient a according to EPA ... Emission coefficient (g/km) according to Fajar’s study ... Specific fuel consumption for each type of vehicle ... Emission coefficient (g/l) according to Fajar’s study ... High emission coefficient case (g/km) ... Average wind velocity by observation station in Jakarta, 2006 ……… Meteorological data ... German reference concentration Ki*(source: MLuS) ... German average emission coefficient e* (source: MLuS) ... Emission concentration of CO at several location ... AADT and CO emission concentration in year 2002 ... Reference emission coefficient e* for model input ... Reference concentration K* for model input ... Total emission (in thousand ton), low emission coefficient case …….. Emission reduction (thousand ton), low emission coefficient case …... Emission concentration (mg/m3), low emission coefficient case ……..

68 69 70 70 71 73 73 74 75 75 78 79 79 80 80 81 81 82 83 84 88 88 89 89 90 90 90 91 92 93

xviii 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80

Reduction of emission concentration compare to base scenario, low emission coefficient case ……….. Total emission (thousand ton), high emission coefficient case ………. Emission reduction (thousand ton), high emission coefficient case …. Emission concentration (mg/m3), high emission coefficient case ……. Reduction of emission concentration compare to base scenario, high emission coefficient case ………... Comparison between emission load and concentration for low and high emission coefficient for year 2010 case ... Reported health impacts of major diesel engine exhaust component ... Regulated exhaust emission reduction of B30 ... Non-regulated emission of aromatic compounds from fossil diesel fuel (FDF) and B30 ……….. Dose response ... Health cost ………. GDPPPP and GDPPPP/capita for Indonesia and German case ... Indonesian GDP Deflator 1990 – 2005 ... Low emission coefficient external cost summary ………. External cost reduction compare to base scenario ……… High emission coefficient external cost summary ……… External cost reduction compare to base scenario ……… Comparison between low and high emission coefficient value ……… Comparison of external cost estimation result with others existing studies (in Trillion Rupiah) ………... The ranking of optimum biodiesel-petrodiesel composition ... Environmental Impact Classification ... External value should be paid by the polluter (Rp. Per liter) ………… Emission coefficient data sources (g/km) ……….. External cost (rupiah), low emission coefficient case ………... External cost (rupiah), high emission coefficient case ………..

94 95 96 97 98 100 102 105 105 106 107 108 108 110 110 110 110 113 117 121 122 127 138 169 171

xix

LIST OF FIGURES

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

The logical frame of the research ... External Costs Calculation by Impact Pathway Analysis ... External cost simulation flow chart... Base catalyzed transesterification reaction ... Typical biodiesel process flow diagram ... The arrangement of emission test on chassis dynamometer ... Biodiesel test sample Process Flow Diagram ... Biodiesel plant 1.5 ton/day capacity at PUSPIPTEK, Serpong... Emission test cycle based on ECE 83-04 ... Power Vs. engine speed ... Torque Vs engine speed ... Emission profile ... Fuel consumption VS biodiesel blending composition ... The effect of biodiesel on exhaust gas emission ... Flowchart of study to estimate the effect of biodiesel utilization on transportation sector emission in Jakarta ………. RGDP and population in Jakarta ……….. Projection of population and RGDP in Jakarta ……….. Fuel sold by UPMS III in the year of 2005 ………... Number of vehicles in Jakarta 2001 – 2005 ……… Estimated fuel consumption for transportation sector in Jakarta …….. Projection of vehicle number in Jakarta ……… Projection of fuel demand for transportation sector in Jakarta

(BAU/non biodiesel Scenario) ... Projection of emission (BAU scenario) ……… Optimum blending determination flow chart ………. Basic calculation of concentration (MluS model) ... Fading function g(s) ... Average relative pollutant concentration ...

6 7 8 14 15 19 21 22 23 24 25 26 27 27 33 34 34 35 35 36 39 41 42 48 61 63 63

xx 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

Model calculation flow chart ………. Main program flow chart ……… Data grids matrices of Jakarta’s area ……….. Jakarta’s map digitalization ... Jakarta’s road grid data ……….. Hourly vehicle volume ... The view of WRPLOT Software ... WRPLOT format ... Yearly windrose for 2001 – 2005 ……….. Monthly wind rose for 2005 ... The dispersion map of SO2 emission concentration for base case ……. External cost, low emission coefficient case ………. External cost reduction, low emission coefficient case ………. External cost, high emission coefficient case ………. External cost reduction, high emission coefficient case ………. Sensitivity of emission coefficient to each pollutant concentration ... The sensitivity of emission coefficient value to the external cost ... Sensitivity of wind speed to each pollutant concentration ... The sensitivity of wind speed to the external cost ... Sensitivity of fading function to each pollutant concentration ... The sensitivity of fading function to the external cost ……….. Price structure comparison ... The cartesian co-ordinate system used to specify dispersion geometry for Gaussian Dispersion Model ...

64 66 68 69 72 73 85 85 86 87 100 111 111 112 112 114 114 115 115 116 116 124 140

xxi

LIST OF APPENDICES

1 2 3 4 5

The emission coefficient estimation determination method

Gaussian plume mathematical diffussion model ... Map region, population and AADT ... Emission concentration dispersion map ... External cost calculation result ...

Page 138 140 144 147 168

xxii

LIST OF NOMENCLATURE

AADT AADTG C(x,y,z) Ds ei*

ei f fvi fu g g(s) H Hf Δh H ∆Hc IGAV Ki*

Q s s0

s Ts

Annual Average Daily Traffic AADT for German reference case

air concentration at receptor point (x,y,z) stack diameter

Average specific reference emission factor of the pollutant i

Average emission factor of the pollutant i coming from an independent emission model i

Briggs plume rise stability factor Function to consider the traffic data

Function to consider the meteorological data gravitational acceleration

Fading function of the relative pollutant concentrations

Effective height

Effective height as a function of f factor Plume rise

Stack height Combustion Heat

The average relative concentration

Reference concentration at ground level near roadside of the pollutant i

Emission strength Stability parameter

A distance from the roadside that relative concentration of the considered pollutants reach zero

Distance from the roadside Stack gas temperature

[vehicle/day] [vehicle/day] [kg/m3] [m] [g/km, g/l] [g/km, g/l] [-] [-] [-] [m/s2]

[-] [m] [m] [m] [m] [MJ/kg, MJ/liter] [mg/m3]

[mg/m3, ug/ m3] [kg/s] [-]

[m] [m] [K]

xxiii T

u u

Vs

x

xf

γ σy(x) σz(z)

Ambient temperature

Wind speed in effective height

Annual average wind speed in a height of 10 m above ground

Stack gas velocity Downwind distance

Downwind distance as a function of f

Greek Symbols

Elasticity factors

Horizontal dispersion parameter Vertical dispersion parameter

[K] [m/s]

[m/s] [m/s] [m] [m]

[-] [m] [m]

xxiv

LIST OF ABBREVIATIONS

AADT ADO ADB APROBI

ASTM BAU BDF BMG

BPLHD

BPPT

BRDST

BTMP

BPS BSN B10 C CD CO CO2 CNG CPO CVS

Annual Average Daily Traffic Automotive Diesel Oil

Asean Development Bank

Assosiasi Produsen Biofuel Indonesia (Indonesian Biofuel Producer Association)

American Society of Testing and Materials Business As Usual

Biodiesel Fuel

Badan Meteorologi dan Geofisika (Indonesian Bureau of Meteorology and Geophysics)

Badan Pengelola Lingkungan Hidup Daerah (Local Environmental Management Agency)

Badan Pengkajian dan Penerapan Teknologi (Agency for the Assessment and Application of Technology)

Balai Rekayasa Desain dan Sistem Teknologi (Institute for Engineering and Technology System Design)

Balai Termodinamika, Motor dan Propulsi (The

Thermodynamics and Propulsion Engine Research Center) Badan Pusat Statistik (Statistics DKI Jakarta Provincial Office) Badan Standarisasi Nasional (National Standardization Agency) Mixture of 90% vol. fossil diesel fuel with 10% vol. biodiesel Carbon residue

Chassis Dynamometer Carbon Monoxide Carbon dioxide

Compressed Natural Gas Crude Palm Oil

xxv DESDM

DKI Jakarta EC - BPPT EPA EMA ERF FAME FFA FDF GDP GNP HC H2O IDO IPA IPB ITB LEMIGAS

LPG LNG MFO MoE NO2 NOX PAH

PERTAMINA PM

PM10

Departemen Energi dan Sumber Daya Mineral (Department of Energy and Mineral Resources)

Daerah Khusus Ibu Kota Jakarta (The Capital City of Jakarta) Engineering Center - BPPT

Environmental Protection Agency Engine Manufacturers Association Exposure-Response Functions Fatty Acid Methyl Ester Free Fatty Acid Distillate Fossil Diesel Fuel Gross Domestic Product Gross National Product Hydrocarbon

Water vapor

Industrial Diesel Oil Impact Pathway Analysis

Institut Pertanian Bogor (Bogor Agricultural University) Institut Teknologi Bandung (Bandung Institute of Technology) Pusat Penelitian dan Pengembangan Teknologi Minyak dan Gas Bumi (Research and Development Centre for Oil and Gas Technology)

Liquid Petroleum Gas Liquid Natural Gas Marine Fuel Oil

Ministry of Environment Nitrogen Dioxide

Oxides of Nitrogen

Polyaromatic Hydrocarbons State Own Oil Company Particulate Matter

xxvi POME

PUSPIPTEK

RGDP PPPGDP SFS SNI SOF SOx SO2 SPBU

SPM SUTP THC TSP UPMS III USA VHA VOF VOME YOLL

Palm Oil Methyl Ester

Pusat Pengembangan Ilmu Pengetahuan dan Teknologi (Science and Technology Research Center)

Regional Gross Domestic Product

Purchasing Power Parity Gross Domestic Product Specific Fuel Consumption

Standar Nasional Indonesia (Indonesian National Standard) Soluble Organic Fraction

Sulphur Oxides Sulphur Dioxide

Stasiun Pengisian Bahan Bakar Umum (Public Fuel Pump Station)

Suspended Particulate Matter Sustainable Urban Transport Project Total Hydrocarbon

Total Suspended Particle

PERTAMINA’s Marketing Unit III United State of America

Volatile Hydrocarbon Volatile Organic Fraction Vegetable Oil Methyl Ester Years of Life Loss Life

CHAPTER I

INTRODUCTION

Background of the Research

Energy consumption in Indonesia increases rapidly in line with economic and population growth. Currently, Indonesia is very much dependent on fossil fuel for its energy sources and the non fossil alternative renewable energy has not been utilized optimally. Data of fossil energy reserves from the Department of Energy and Mineral Resources [1] shows that the proven reserve of oil is about 9 billion barrels and with an average production rate of 500 million barrels per year, the reserve will be exhausted in 18 years. Around 63% of Indonesia’s final energy demand is still depending on oil (most of them are used in the transportation sector). On the other hand, the national oil production facilities are limited and the capacity is decreasing gradually. Therefore, to satisfy the domestic energy consumption, Indonesia has to import crude oil and finished petroleum products, such as gasoline and diesel fuel. Indonesia has become very dependent on overseas oil supply to fulfill the increasing demand. This situation may worsen the security of fuel supply. The increase of the international crude oil and fuel price has become a burden to the state budget, due to the subsidizing policy of fuel products. For example, when the crude oil price stays at around US$125 per barrel, Indonesia has to provide around 240 trillion rupiahs just for fuel subsidy. This will result in reduced government capacity to finance development programs in needed sectors such as health, education, basic human services, and infrastructures either in rural or in urban areas. This means that the government has very limited resources to stimulate and maintain productivity and economic growth.

In addition, the air pollution level (especially in big cities like Jakarta) is increasing and is becoming a serious problem [2, 3]. Ambient air quality monitoring results suggest that NOx , CO and THC are a serious problem in almost all

areas of Jakarta. PM10 may be considered as a problem in certain areas and motor vehicles are a major contributor of NOx, PM10, CO and THC emission (more than

2 70% of each parameter) [4]. One of the main contributors of the increases of air pollution is transportation. The use of energy in this sector has an environmental impact in the form SO2, NOx, CO, HC and PM. Each type of vehicle has a specific impact and different emission coefficients.

To reduce the high dependency on oil and to improve the air quality level, there is no choice but to maximize the development of utilization on environmental friendly alternative fuel. One alternative is to convert plant oil to methyl esters or famously called biodiesel.

The business of biodiesel in Indonesia is expected to grow as the government intends to boost the biofuel program since the new National Energy Policy has been issued in 2006 [5]. The policy has stated that biofuels are parts of renewable energy sources beside other types of sources such as geothermal, biomass, biogas, wind, river flow, etc. The targets in this policy may include the role of each renewable energy sources in the energy consumption for optimum primary energy mix. In the latter, the role of biofuels is set for more than 5% in the national energy consumption by the year 2025. This policy has been reinforced by the issuance of the President Instruction concerning the regulation biodiesel utilization [6], the National Biodiesel Standard SNI 04-7182-2006 [7], the Decree of the Oil and Gas Directorate General on Biodiesel Blending regulations that allows maximum blending of 10% [8], and the Decree of the Minister of Energy and Mineral Resources on mandatory of biofuel utilization issued on September 2008 [9].

Although the biodiesel development in Indonesia started ten years ago, it has gained a significant milestone in 2006, when PERTAMINA as a state-owned company which carries out business in oil & gas, LNG, energy and petrochemical industries has been selling a blend of 95% diesel fuel and 5% SNI standard biodiesel (B5) which has the trade name of BIOSOLAR since 20 May 2006. To date, PERTAMINA has been selling BIOSOLAR at almost all fuel outlets on the island of Java and Bali. Following the policy of biofuel mandatory utilization arranging phases and by the continuously growing of domestic biodiesel producer, PERTAMINA will open the BIOSOLAR’s fuel outlets in all parts of Indonesia and increase the biodiesel blending content at least up to B20 in 2025. The main

3 current problem in commercialization of biodiesel in Indonesia is the fluctuation of biodiesel price which usually gets higher than fossil diesel oil price, whereas biodiesel is still classified as other fuels which is not subsidized by the government, on the other hand the advantages of biodiesel as an environmentally friendly renewable energy is still less considered. A review of the current status and prospects of biodiesel development in Indonesia has been reported by Wirawan and Tambunan, 2006 [10] .

The reduction of the pollutants emission could have direct implication on the improvement of the air quality in the atmosphere to the impacts on various receptors, including the human beings and those impacts could be transferred into monetary values. In the environmental economic science, environmental impact is known as one form of the loss of externalities which could effect the national effective source allocation and needs the government policy to overcome the problem. Externalities are changes of welfare which are caused by economic activities without being reflected in market price. Applied on transport, negative externalities are costs imposed on society and environment that are not accounted for by the producers and consumers of transport services [11]. Hence, it is necessary to estimate the contribution in external costs in transportation energy sector use due its impact on air pollution to human health.

Objective of the Research

The main objective of this research is:

1. To study the effect of biodiesel fuel in pollutant emission from diesel engine in transportation sector.

2. To perform the external cost analysis in relation to environmental quality and health improvement as affected by biodiesel utilization in transportation sector by using the model simulation.

4

Benefits of the Research

This research would specify the following benefits:

a. Provision of scientific proof of the advantages of biodiesel utilization on environmental improvement (health impacts and economic values).

b. The result could be used as a scientific reference in policy and regulation decision by the government (subsidy, incentive and/or disincentive policy).

Boundaries and Methodology Boundaries

The boundaries of the study can be specified into geographical area, targeted pollutant, time frame and data sources as explained below.

a. Study Area

The study area focuses on the area which comprises the Special District of the capital city of Jakarta which is known as Daerah Khusus Ibukota Jakarta (DKI Jakarta), including North Jakarta, East Jakarta, South Jakarta, West Jakarta and Central Jakarta. Jakarta was selected as a targeted research location due to the fact that Jakarta is the capital city with the most densest population, highest mineral diesel fuel consummer, and most polluted city compared to among others big cities in Indonesia. Seribu islands and sea area are assumed as areas outside Jakarta and were not included in this study. Jakarta is used through-out this report as the terminology for the study area of DKI Jakarta.

b. Targeted Pollutants

The targeted pollutants in the study are nitrogen oxides (NOx), sulfur dioxide (SO2), Particulate Matters (PM), carbon monoxide (CO), and hydrocarbons (HC) from transportation sector vehicle sources fueled with pure mineral diesel fuel case (base case) and biodiesel blends with diesel fuel case (B10, B20, B50 and B100). Industrial and domestic sector sources and other mobile sources such as ships, aircraft and other sources are not estimated in this study.

c. Data Sources

Efforts focused on collecting all previous studies and reliable secondary data on air quality model for the traffic sector and air pollution levels in Jakarta for the

5 period of 1992 to the latest year available. The following are comprehensive studies that focused solely on air quality model for the traffic sector and Jakarta’s air pollution situation and formed part of this study’s background:

• Air Quality Model for the Traffic Sector, Environmental Impacts of Energy Strategies, Indonesian German Research Project [12].

• Study on Air Quality in Jakarta, Indonesia [4]. d. Time Frame

The study’s time frame was set as follows:

• The vehicle emission loads without countermeasures or baseline cases were estimated for year 2005 and predicted for the short/medium term (2010 and 2015), and long term (2020 and 2025). The vehicle emission loads with countermeasure (biodiesel blends with petrodiesel, B10 and B20 case) were predicted for both the short/medium term (2010 and 2015) and long term (2020 and 2025). B50 and B100 cases were also estimated in this study in order to evaluate the conservative contribution of biodiesel utilization in the transportation sector to the overall pollution in Jakarta.

• The health and economic impacts of air pollution were estimated based on the results of simulation as above scenarios.

- 6 -

Background

•63% of energy demand depend on fossil oil

•Reserved oil is limited •40% of diesel oil consumption are imported

•Increases of international crude oil prices

•Air quality of major cities in Indonesia has been deteriorating especially in the city of Jakarta

•Abundant Biofuel Raw Material

National Biofuel Program

Bioethanol, Biodiesel and Bio-oil

R&D Support

•Effect biodiesel to engine performance •Effect biodiesel to emission •Optimum blending

•Advantages and disadvantages of biodiesel

•Others

Existing condition

•Perpres No. 5/2006 •Inpres No. 1/2006 •SNI 04-7182-2006

•Decree No. 3675K/24/DJM/2006 (max. B10)

•Decree No. 32/2008 (Biofuel Mandatory)

•Pertamina formally sale BIOSOLAR

•Plant Installed capacity 2.5 million Kl

Influence Factors

•World oil price •CPO oil price

•Chemical price (methanol, catalyst)

•Global policy (technical and environmental aspect) •Government policy on biofuel (price, tax, incentive, etc) •Tecnology capability (on and off farm)

Commercialization Problems

•Biodiesel still classified as other fuel (economical price, no subsidy). •FAME price is tend to increase and passing the MOPS price. •Consumer still dominantly considered the fuel price to decide to use for their car fuel. •The advantages of biodiesel (renewable energy, lower exhaust gas emission, effect to engine life time) is just putted aside.

Diesel Oil Sample B0

•From Pertamina balongan B0(1)

•From Public Fuel Pump Station B0(2)

Meet Pertamina’s diesel oil standard

Biodiesel Production

Engineering Center – BPPT Meet SNI 04-7182-2006

BXX samples •B0 •B10 •B20 •B30 •B50 •B100 Lab Test Performance: Torque, power, Fuel ConsumptionEmis sion: SO2, NOx, HC, CO, PM

Optimum Blending Assessment

•Lab test result •Literarure study •Experts interview •Short term engine effect •Long term engine effect •Price

Biodiesel Blending Scenario Recommendation

Scenarios

•Time frame: 2005, 2010, 2015, 2020, 2025 •Base case B0 •BXX

Socio Economy Data

•Population growth •Economic growth •Historical data

Vehicle Growth Model

•By type of vehicle •By type of fuel

Emission Coefficient

•By type of emission •By type of vehicle

Emission Quantification

Meteorological data

•Wind speed

Emission Dispersion

MLuSModel

•For Jakarta

•1 x 1 km square grids

•By type of emission

•Fading model

Dose response

Health cost

•Germany health cost •GDPPPP Indonesia and Germany

•Indonesian health cost External Cost Calculation

The Effect of Biodiesel to External Cost

Background of the Research Model Simulation Research Output

The Effect of Biodiesel to: •Pollutant Emission •Pollutant Dispersion Chapter 1 Chapter 4 Chapter 2 Chapter 3 Chapter 5 Chapter 6 Chapter 8: Conclusion Chapter 7: General Discussion

7

Methodology

The external costs are calculated by using the analysis of emission dispersion effect which is mostly known as Impact Pathway Analysis (IPA). The impact pathways methodology has been used in a large number of research projects and policy application related studies. The method consists of four steps, which are : to quantify the emission, to define the dispersion and transformation of emission for calculating the ambient concentration, to estimate the physical effects by using the dose response function, and to determine the monetary value of the damage for calculating the external costs [13, 14, 15]. Figure 2 shows the summary of IPA method. Each calculation steps has an uncertainty due to the availability data limitation and the limitation of methodology of the used model.

Source: Sugiyono, 2005 [13] and Kovacevic et. al., 2001 [14], Wilde et al. 2003 [15]

Figure 2: External Costs Calculation by Impact Pathway Analysis

Generally, this study will determine the external costs of transportation energy use by using the simulation. Each simulation is based on the scenario which is in line with the development pattern of the government policy. By comparing the base case (B0) with biodiesel blends cases (B10, B20, B50, and B100); therefore the strategy for reducing the external costs could be compiled. Figure 3 shows the steps of simulation methods.

The following are principal tasks that have to be undertaken in order to perform the simulation.

8 - A collection and review of all available data with respect to air pollution

levels in Jakarta.

- A review of existing emission coefficient inventory for vehicle pollution sources in Jakarta.

- The selection and development of emission dispersion model to estimate the pollution concentration from vehicle sources in various parts of Jakarta. - A prediction of future pollution loads caused by vehicle pollution sources in

various parts of Jakarta, based on scenario planning variables including the number and type of vehicles, fuel types, etc.

b. To assess the health and economic impacts were:

- To study the influence of biodiesel on exhaust emission and health effects. - A collection, review and summary of earlier studies which attemped to

assess the health impact of mobile source air pollution as well as the economic impact.

- To estimate the value of external cost in relation to environmental quality and health improvement as affected by biodiesel utilization.

Figure. 3. External Cost Simulation Flow Chart VEHICLE GROWTH MODEL

(Number and Type of Vehicle)

EMISSION QUANTIFICATION

EMISSION DISPERSION MODEL

IMPACT ESTIMATION

EXTERNAL COST CALCULATION

Historical Data

Population Growth Economic Growth

SCENARIO:

Emission Coefficient

Meteorological Data 2. Scenario B10, B20, B50 and B100

9

Outline of Dissertation

The dissertation is divided into eight main chapters. Background information related to the research topic selection including the objective and benefits of the research and boundaries and methodology of the research performance will be described in Chapter 1, followed by the description of several studies related to the effect of biodiesel utilization to engine performance and its potential emission reduction. The Effect of Palm Biodiesel Fuel on the Performance and Emission of the Automotive Diesel Engine is presented in Chapter 2, and the Estimation of the Effect of Biodiesel Utilization on Transportation Sector Emission in Jakarta is presented in Chapter 3. The study on the Determination of Optimum Biodiesel-Petrodiesel Blending Scenario was performed and the result is described in chapter 4.

Chapter 5, is the core chapter in estimating Jakarta’s pollution level. It covers the collected previous studies related to the dispersion model input data, the method to determine the emission factor, as well as the air dispersion simulation. Chapter 6, reveals the estimated health and economic impacts (external costs) of air pollution based on the calculated air pollution provided in chapter 5. Finally, the General Discussion based on the previous chapter result information will be described in Chapter 7 and concluded in Chapter 8. Other data including the source of model simulation program, projection of population growth and traffic density map, projection of emission concentration dispersion map and the numerical result of external cost estimation are presented in appendices.

CHAPTER II

THE EFFECT OF PALM BIODIESEL FUEL ON THE

PERFORMANCE AND EMISSION OF AUTOMOTIVE

DIESEL ENGINE

Introduction

Diesel fuels have an essential function in achieving social and economy objectives to establish a sustainable development and to support a country’s activities. Both transportation (private and public cars, trucks, buses, locomotives, etc.) and industrial sectors (electric generators, farm equipment, underground mining equipment, etc.) utilize these fuels extensively. From the standpoint of preserving the global environment and the concern regarding long-term supplies of conventional hydrocarbon-based diesel fuels, it is logical that research and development on different possible sources of petroleum products should be carried with emphasis on yield and quality of the diesel fuels.

Alternative diesel fuels must be technically acceptable, economically competitive, environmentally acceptable and easily available. From the viewpoint of these requirements, triglycerides (vegetable oils/animal fats) and their derivatives may offer as viable alternatives for diesel fuels. Vegetable oils are widely available from a variety of sources, and they are renewable. Depending upon climate and soil conditions, different nations are looking into different vegetable oils for diesel fuel. For example, soy bean oil in the United States, rapeseed and sunflower oil in Europe, palm oil in Southeast Asia (mainly in Malaysia and Indonesia), and coconut oil in the Philippines are being considered as substitutes for diesel fuels. Various findings have reported that direct use of vegetable oils as diesel fuels in conventional diesel engines leads to a number of problems that related to the type and grade of oil and local climatic conditions.

Vegetable oils typically show viscosities ten to twenty times higher than the viscosity of fossil diesel fuel. This high viscosity leads to poor fuel atomization and results in an incomplete combustion [16]. The high flash point attributes to its lower volatility characteristics. This leads to a more deposit formation, carbonization of injector tip, ring sticking and lubricating oil dilution and

11 degradation. Table 1 shows the comparison of fossil diesel fuel with vegetable oil characteristic [17].

Table 1. Comparison of fossil diesel fuel with vegetable oil characteristics

Oil Density at 20 o_C, kg/liter

Kinematics viscosity at 20oC, cSt

∆Hc,

MJ/kg

Cetane Number

Cloud point,

o C.

Pour point, o_C.

Coconut 0,915 30 37,10 40 – 42 28 23 – 26

Palm 0,915 60 36,90 38 – 40 31 23 – 40

Jatropha Curcas 0,920 77 38,00 23 – 41 2 -3

Peanut 0,914 85 39,30 30 – 41 9 -3

Soybean 0,920 61 37,30 30 – 38 -4 -20

Sunflower 0,925 58 37,75 29 – 37 -5 -16

Diesel 0,830 6 43,80 50 -9 -16

Source : Soerawidjaja, T., H., 2006 [17]

It is clear that the problems with substituting vegetable oil for diesel fuel are mostly associated with their high viscosities, low volatilities and polyunsaturated character. Consequently, long term operation on neat vegetable oils or on mixture of vegetable oils with fossil diesel fuel, inevitably would result in an engine breakdown. These problems can be solved by either adapting the engine to the fuel or by adapting the fuel to the engine. Four methods widely used to reduce the high viscosity of vegetable oils to enable their use in common diesel engines without operational problems are pyrolysis, micro emulsification, dilution, and transesterification [18], but only the transesterification reaction can lead to the products commonly known as biodiesel, i.e., Alkyl esters of oil and fats [19, 20].

Pyrolysis denotes thermal decomposition reaction, usually brought about in the absence of oxygen. The cetane number of plant oils is increased by pyrolysis, and the concentrations of sulfur, water and sediment for the resulting product are acceptable. However, according to modern standards, the viscosity of the fuels is considered as too high, ash and carbon residue far exceed the values for fossil diesel, and the cold flow properties of paralyzed vegetable oils are poor [21]. The equipment for thermal cracking and pyrolysis is expensive for modest

12 throughputs. In addition, while the products are chemically similar to petroleum-derived gasoline and diesel fuel, the removal of oxygen during the thermal processing also removes any environmental benefits of using an oxygenated fuel. It produced some low value materials and, sometimes, more gasoline than diesel fuel [20].

Micro emulsification is the formation of thermodynamically stable dispersion of two usually not miscible liquids, brought about by one or more surfactants. Drop diameters in micro emulsions typically range from 100 to 1000A [18]. Various investigators have studied micro emulsification of vegetable oils with methanol, ethanol or 1-butanol [16]. They arrived at the conclusion that micro emulsions of vegetable oils and alcohols cannot be recommended for long-term use in diesel engines for similar reasons applied to neat vegetable oils. The fuels produced are prone to incomplete combustion, the formation of carbon deposits, and an increase in the viscosity of the lubricating oil. Moreover, micro emulsions display considerably lower volumetric heating values as compared to hydrocarbon-based diesel fuel due to their high alcohol contents [18], and they have been assessed insufficient in terms of cetane number and cold temperature behavior.

Dilution of vegetable oils can be accomplished with such materials as diesel fuels, a solvent or ethanol. Most studies concluded that vegetable oil/petrodiesel blends are not suitable for long-term fuelling of direct injection diesel engines. The studies results, yielding engine problems similar to those found for combustion of neat vegetable oils [18, 19].

Another alternative to improve suitability of vegetable oil for diesel engine is by hydrogenating the oil using typical process of commonly found in crude oil refinery. Koyama et al. 2006 (Koyama A., Iki H., Iguchi Y. Applicability of Hydrogenated Palm Oil for Automotive Fuels. 16th Saudi Arabia – Japan Joint Symposium. Dhahran. Saudi Arabia. November 5 – 6. 2006) had tried to directly hydrogenate palm oil at temperature range of 240oC to 360oC and pressure of 6 to 10 MPa with catalyst normally used in hydrodesulphurization . They suggested that the product has a better property in term of oxidation stability than palm oil methyl ester. The relatively better in oxidation stability would make it potentially

13 possible for blending with fossil diesel at higher ratio than currently suggested by the Wide World Fuel Chapter organization of 5%. However, this fuel had relatively higher Cold Flow Plugging Point parameter (CFPP 20oC) than that of FAME (CFPP 12oC), which prohibits its use in winter season and has problems in cold start up. Although this method may offer a great opportunity to substitute the diesel oil, large-scale demonstration of such a finding followed by full commercialization would take some time. On the other hand, transesterification of vegetable oil has reached full commercialization and it would be an ideal choice for diesel oil substitute.

Transesterification [22], also called alcoholysis, is the displacement of alcohol from an ester by another alcohol in a process similar to hydrolysis, except alcohol is used instead of water. The result of fatty acid transesterification is Fatty Acid Methyl Esters (FAME), generally known as biodiesel. Several vegetable oils methyl esters (VOME) characteristic is shown in Table 2 [17]. The resulting biodiesel is quite similar to conventional diesel fuel in its main characteristics. Biodiesel is compatible with conventional diesel and the two can be blended in any proportion. Therefore, transesterification with lower alcohols, however, has turned out to be an ideal modification, so that the term “biodiesel” is now only used to denote products obtained by this technology.

Table 2. Vegetable Oil Methyl Esters (VOME) characteristics

Methyl Ester Density at ₁₅ o_C, kg/liter

Kinematics Viscosity at

40 0C, cSt

∆Hc,

MJ/liter

Cetane number

CFPP,

o_C. Iodine Number, g-I2/(100 g)

Coconut 0,869 2,7 30,80 63 8,0 10

Palm 0,874 4,40 32,40 63 16,0 52

Cooking Oil 0,880 4,20 32,80 49 -5 – +8 60 – 120

Jatropha Curcas 0,879 4,20 32,80 51 95 – 106

Canola 0,882 4,20 32,80 49 -12 114

Sunflower 0,885 4,00 32,80 47 -4 129

Soybean 0,885 4,05 33,50 46 -4 131

14 Biodiesel by definition is a compound of methyl ester derived from the esterification / trans-esterification process of various types of vegetable oils or animal fats. The biodiesel definition has become important since many misleading definitions of biodiesel have been interpreted to define biodiesel as a substitute of diesel fuel from any vegetable oil without esterification or trans-esterification process.

The production processes for biodiesel are well known. There are three basic methods of ester production from oils/fats:

1. Base catalyzed transesterification 2. Acid catalyzed esterification and 3. Enzymatic catalysis

Each reaction has associated optimal operating parameters (temperature, pressure) and conversion, although many available literatures emphasized the base catalyzed route because it is claimed to be the most economical. The overall base catalyzed reaction is shown in Figure 4.

Figure 4. Base catalyzed transesterification reaction

The reaction progresses in three reversible steps: 1) the triglyceride reacts with the alcohol to form diglyceride and fatty acid ester, 2) the diglyceride reacts with the alcohol to form monoglyceride and fatty acid ester, and 3) the monoglyceride reacts with the alcohol to form glycerin and fatty acid ester.

Glycerin

Catalyst

C-OOC-R1

C-OOC-R2

C-OOC-R3

R1-COO-R’ R2-COO-R’ R3-COO-R’ 3R’OH

C-OH

C-OH

C-OH Triglyceride

Alcohol (methanol)

Fatty Acid Ester

With Example of R1, R2, R3

15 The type of alcohol used determines the type of esters formed. Although higher alcohols (ethanol) can be used in the transesterification, methanol is more advantageous. The reason is that the two main products of the reaction, Fatty Acid Methyl Ester (FAME) and glycerol, are hardly miscible and thus form separate phases – an upper ester phase and a lower glycerol phase. Moreover, the price of methanol is cheaper than ethanol, which makes it preferable for commercial biodiesel production. Figure 5 shows the typical biodiesel process flow diagram.

Figure 5. Typical Biodiesel Process Flow Diagram

As explained above, generally, there are three basic catalytic reaction methods of ester production from oils/fats. They are base catalyzed transesterification, acid catalyzed esterification and enzymatic catalysis. The first two types of catalytic reactions mentioned above have received the greatest attention, as for the enzyme-catalyzed system, it requires much longer reaction time than the other systems [23]. Therefore, to date, the enzyme-catalyzed system has only been carried out on the laboratory scale. The base and acid catalyzed reaction method has a long story of development and now a high production cost and energy produced by this method is in the market in some countries. However, there are at least two problems associated with this process; the process is relatively time consuming and it requires purification of the product from catalyst and saponified products. Therefore, this conventional process still requires a high production cost and energy. To solve this problem, Saka and Kusdiana, 2001 [24] studied the (high pressure – high temperature) non-catalyzed transesterification of

16 vegetable oil in supercritical methanol. As a result, the reaction was successful to complete in a very short time within 2 - 4 minutes.

The (low pressure-high temperature) non-catalytic transesterification of triglyceride from palm oil in a bubble column reactor at reaction temperatures of 250, 270, and 290oC under atmospheric pressure have been studied by Joelianingsih et al. 2007 [25]. The result shows that methyl esterification of FFA and transesterification of TG can be conducted simultaneously in the bubble column reactor. The reaction rate of methyl esterification was faster than that of methyl trans-eseterification, but the ME content in the gaseous product was lower. More researchers have reported kinetics for both catalytic and non-catalytic transesterification reaction method.

Four oil crops (rapeseed, sunflower, soybean and palm) dominate the feedstock sources used for worldwide biodiesel production. Table 3 shows that oilseed rape, sunflower, soy and oil palm also constitute the four major oil crops cultivated for human consumption and various industrial applications including the feedstock sources used for biodiesel production. Due to its properties, rapeseed oil still is the feedstock of choice in most European countries including the world’s largest biofuel producers, Germany and France. Sunflower seed oil as the second leading vegetable oil sources for biodiesel production in Europe, is cultivated in Southern European countries, such as Italy, Spain and Greece, because here the semi-arid climates prevent high oil yields for rapeseed. Soybean oil is the most popular biodiesel feedstock in the USA.

Table 3. Current worldwide production of nine major vegetable oils [16]

Vegetable Oils

Estimated production in harvest

year 2003-04 (million metric tons) Vegetable Oils

Estimated production in harvest year 2003-04 (million metric tons)

Soybean 31.83 Cottonseed 3.90

Palm 28.13 Palm Kernel 3.50

Rapeseed 12.57 Coconut 3.33

Sunflower 9.42 Olive 2.81

Peanut 4.81 Total 100.29

If biodiesel fuels are to be economically competitive with fossil diesel, even in the absence of tax concession programs, production cost has to be kept

APPENDIX 5

External Cost Calculation Result:

1.

Low Emission Coefficient Case

2.

High Emission Coefficient Case

Table 79. External cost (rupiah), low emission coefficient case

Table 79a. Base (non biodiesel) scenario (Billion Rupiah contant 2005)

2005 2010 2015

Min Max Avg Min Max Avg Min Max Avg SOx 7.1 7.1 7.1 9.6 9.6 9.6 12.0 12.0 12.0 NOx 10.4 10.4 10.4 16.7 16.7 16.7 22.8 22.8 22.8 HC 2.9 2.9 2.9 4.5 4.5 4.5 6.2 6.2 6.2 PM 279.5 373.9 326.7 436.7 584.2 510.4 592.5 792.7 692.6 CO 141.9 141.9 141.9 234.3 234.3 234.3 327.2 327.2 327.2 TOTAL 441.8 536.2 489.0 701.8 849.3 775.6 960.7 1160.9 1060.8

2020 2025

Min Max Avg Min Max Avg SOx 14.8 14.8 14.8 18.1 18.1 18.1 NOx 29.5 29.5 29.5 37.2 37.2 37.2 HC 8.0 8.0 8.0 10.1 10.1 10.1 PM 767 1026.2 896.6 973.7 1302.6 1138.1 CO 429.9 429.9 429.9 551.3 551.3 551.3 TOTAL 1249.2 1508.3 1378.8 1590.4 1919.3 1754.9

Table 79b. B10 scenario (Billion Rupiah contant 2005)

2005 2010 2015

Min Max Avg Min Max Avg Min Max Avg SOx 7.1 7.1 7.1 8.7 8.7 8.7 10.9 10.9 10.9 NOx 10.4 10.4 10.4 16.7 16.7 16.7 22.8 22.8 22.8 HC 2.9 2.9 2.9 4.4 4.4 4.4 6.0 6.0 6.0 PM 279.5 373.9 326.7 433.8 580.3 507.1 589.5 788.7 689.1 CO 141.9 141.9 141.9 233.9 233.9 233.9 326.6 326.6 326.6 TOTAL 441.8 536.2 489.0 697.5 844.0 770.8 955.9 1155.1 1055.5

2020 2025

Min Max Avg Min Max Avg SOx 12.2 12.2 12.2 16.5 16.5 16.5 NOx 29.4 29.4 29.4 37.2 37.2 37.2 HC 7.7 7.7 7.7 10.0 10.0 10.0 PM 748.1 1000.9 874.5 967.6 1294.5 1131.1 CO 428.5 428.5 428.5 550.4 550.4 550.4 TOTAL 1226.0 1478.7 1352.3 1581.7 1908.6 1745.1

Table 79c. B20 scenario (Billion Rupiah contant 2005)

2005 2010 2015

Min Max Avg Min Max Avg Min Max Avg SOx 7.1 7.1 7.1 7.9 7.9 7.9 9.9 9.9 9.9 NOx 10.4 10.4 10.4 16.6 16.6 16.6 22.7 22.7 22.7 HC 2.9 2.9 2.9 4.3 4.3 4.3 5.9 5.9 5.9 PM 279.5 373.9 326.7 424.4 567.8 496.1 577.6 772.7 675.2 CO 141.9 141.9 141.9 233.4 233.4 233.4 326.1 326.1 326.1 TOTAL 441.8 536.2 489.0 686.7 830.1 758.4 942.2 1137.4 1039.8

2020 2025

Min Max Avg Min Max Avg SOx 12.2 12.2 12.2 14.9 14.9 14.9 NOx 29.4 29.4 29.4 37.1 37.1 37.1

HC 7.7 7.7 7.7 9.8 9.8 9.8

PM 748.1 1000.9 874.5 951.0 1272.3 1111.7 CO 428.5 428.5 428.5 549.6 549.6 549.6 TOTAL 1226.0 1478.7 1352.3 1562.5 1883.8 1723.1

Table 79d. B50 scenario (Billion Rupiah contant 2005)

2005 2010 2015

Min Max Avg Min Max Avg Min Max Avg SOx 7.1 7.1 7.1 5.3 5.3 5.3 6.7 6.7 6.7 NOx 10.4 10.4 10.4 16.5 16.5 16.5 22.6 22.6 22.6 HC 2.9 2.9 2.9 4.1 4.1 4.1 5.6 5.6 5.6 PM 279.5 373.9 326.7 408.9 547 477.9 558.6 747.3 652.9 CO 141.9 141.9 141.9 232.3 232.3 232.3 324.7 324.7 324.7 TOTAL 441.8 536.2 489 667.1 805.2 736.2 918.2 1107 1012.6

2020 2025

Min Max Avg Min Max Avg SOx 8.3 8.3 8.3 10.2 10.2 10.2 NOx 29.3 29.3 29.3 36.9 36.9 36.9

HC 7.3 7.3 7.3 9.4 9.4 9.4

PM 725.4 970.4 847.9 922.9 1234.7 1078.8 CO 426.9 426.9 426.9 547.6 547.6 547.6 TOTAL 1197.1 1442.2 1319.6 1527.0 1838.8 1682.9

Table 79e. B100 scenario (Billion Rupiah contant 2005)

2005 2010 2015

Min Max Avg Min Max Avg Min Max Avg SOx 7.1 7.1 7.1 1.0 1.0 1.0 1.4 1.4 1.4 NOx 10.4 10.4 10.4 16.4 16.4 16.4 22.4 22.4 22.4 HC 2.9 2.9 2.9 3.8 3.8 3.8 5.3 5.3 5.3 PM 279.5 373.9 326.7 383.3 512.8 448.0 527.2 705.3 616.2 CO 141.9 141.9 141.9 230.8 230.8 230.8 322.8 322.8 322.8 TOTAL 441.8 536.2 489.0 635.2 764.7 700.0 879.1 1057.2 968.2

2020 2025

Min Max Avg Min Max Avg

SOx 1.8 1.8 1.8 2.3 2.3 2.3

NOx 29.0 29.0 29.0 36.6 36.6 36.6

HC 7.0 7.0 7.0 8.9 8.9 8.9

PM 687.4 919.6 803.5 876.5 1172.6 1024.5 CO 424.5 424.5 424.5 544.8 544.8 544.8 TOTAL 1149.7 1381.9 1265.8 1469.2 1765.3 1617.2

Table 80. External cost (Rupiah), high emission coefficient case

Table 80a. Base (non biodiesel) scenario (Billion Rupiah constant 2005)

2005 2010 2015

Min Max Avg Min Max Avg Min Max Avg

SOx 7.8 7.8 7.8 10.8 10.8 10.8 13.6 13.6 13.6

NOx 58.7 58.7 58.7 88.9 88.9 88.9 122.0 122.0 122.0

HC 45.5 45.5 45.5 83.3 83.3 83.3 116.8 116.8 116.8

PM 1,208.3 1,616.5 1,412.4 2,008.5 2,687.0 2,347.7 2,751.0 3,680.4 3,215.7

CO 268.1 268.1 268.1 475.0 475.0 475.0 666.2 666.2 666.2

TOTAL 1,588.4 1,996.6 1,792.5 2,666.5 3,345.0 3,005.8 3,669.6 4,599.0 4,134.3

2020 2025

Min Max Avg Min Max Avg SOx 16.9 16.9 16.9 20.7 20.7 20.7 NOx 162.8 162.8 162.8 214.6 214.6 214.6 HC 147.7 147.7 147.7 178.3 178.3 178.3 PM 3,493.6 4,674.0 4,083.8 4,301.3 5,754.4 5,027.8 CO 853.7 853.7 853.7 1,053.4 1,053.4 1,053.4 TOTAL 4,674.8 5,855.1 5,264.9 5,768.3 7,221.4 6,494.9

Table 80b. B10 scenario (Billion Rupiah constant 2005)

2005 2010 2015

Min Max Avg Min Max Avg Min Max Avg

SOx 7.8 7.8 7.8 9.9 9.9 9.9 12.5 12.5 12.5

NOx 58.7 58.7 58.7 88.8 88.8 88.8 121.9 121.9 121.9

HC 45.5 45.5 45.5 83.0 83.0 83.0 116.5 116.5 116.5

PM 1,208.3 1,616.5 1,412.4 1,998.7 2,673.9 2,336.3 2,735.8 3,660.1 3,197.9

CO 268.1 268.1 268.1 474.4 474.4 474.4 665.4 665.4 665.4

TOTAL 1,588.4 1,996.6 1,792.5 2,654.7 3,330.0 2,992.4 3,652.1 4,576.3 4,114.2

2020 2025

Min Max Avg Min Max Avg SOx 15.0 15.0 15.0 19.1 19.1 19.1 NOx 162.4 162.4 162.4 214.3 214.3 214.3 HC 146.9 146.9 146.9 177.9 177.9 177.9 PM 3,424.8 4,581.8 4,003.3 4,282.8 5,729.7 5,006.2 CO 851.8 851.8 851.8 1,052.1 1,052.1 1,052.1 TOTAL 4,600.9 5,757.9 5,179.4 5,746.3 7,193.2 6,469.7

Table 80c. B20 scenario (Billion Rupiah constant 2005)

2005 2010 2015

Min Max Avg Min Max Avg Min Max Avg

SOx 7.8 7.8 7.8 9.5 9.5 9.5 12.1 12.1 12.1

NOx 58.7 58.7 58.7 88.6 88.6 88.6 121.6 121.6 121.6

HC 45.5 45.5 45.5 82.8 82.8 82.8 116.2 116.2 116.2

PM 1,208.3 1,616.5 1,412.4 1,960.9 2,623.4 2,292.2 2,694.2 3,604.4 3,149.3

CO 268.1 268.1 268.1 473.7 473.7 473.7 664.6 664.6 664.6

TOTAL 1,588.4 1,996.6 1,792.5 2,615.5 3,278.0 2,946.8 3,608.7 4,518.9 4,063.8

2020 2025

Min Max Avg Min Max Avg SOx 15.0 15.0 15.0 18.5 18.5 18.5 NOx 162.4 162.4 162.4 214.0 214.0 214.0 HC 146.9 146.9 146.9 177.5 177.5 177.5 PM 3,424.8 4,581.8 4,003.3 4,216.1 5,640.5 4,928.3 CO 851.8 851.8 851.8 1,050.9 1,050.9 1,050.9 TOTAL 4,600.9 5,757.9 5,179.4 5,677.0 7,101.4 6,389.2

Table 80d. B50 scenario (Billion Rupiah contant 2005)

2005 2010 2015

Min Max Avg Min Max Avg Min Max Avg

SOx 7.8 7.8 7.8 6.4 6.4 6.4 8.3 8.3 8.3

NOx 58.7 58.7 58.7 88.2 88.2 88.2 121.1 121.1 121.1

HC 45.5 45.5 45.5 82.1 82.1 82.1 115.4 115.4 115.4

PM 1,208.3 1,616.5 1,412.4 1,902.0 2,544.6 2,223.3 2,623.2 3,509.4 3,066.3

CO 268.1 268.1 268.1 472.1 472.1 472.1 662.5 662.5 662.5

TOTAL 1,588.4 1,996.6 1,792.5 2,550.8 3,193.4 2,872.1 3,530.5 4,416.7 3,973.6

2020 2025

Min Max Average Min Max Average SOx 10.4 10.4 10.4 12.8 12.8 12.8 NOx 161.7 161.7 161.7 213.2 213.2 213.2 HC 146.0 146.0 146.0 176.4 176.4 176.4 PM 3,341.6 4,470.5 3,906.0 4,118.6 5,510.1 4,814.3 CO 849.2 849.2 849.2 1,047.8 1,047.8 1,047.8 TOTAL 4,508.9 5,637.8 5,073.3 5,568.9 6,960.3 6,264.6

Table 80e . B100 scenario (Billion Rupiah constant 2005)

2005 2010 2015

Min Max Average Min Max Average Min Max Average

SOx 7.8 7.8 7.8 2.1 2.1 2.1 3.0 3.0 3.0

NOx 58.7 58.7 58.7 87.5 87.5 87.5 120.2 120.2 120.2

HC 45.5 45.5 45.5 81.4 81.4 81.4 114.6 114.6 114.6

PM 1,208.3 1,616.5 1,412.4 1,813.5 2,426.2 2,119.9 2,510.5 3,358.7 2,934.6

CO 268.1 268.1 268.1 469.9 469.9 469.9 659.9 659.9 659.9

TOTAL 1,588.4 1,996.6 1,792.5 2,454.5 3,067.2 2,760.8 3,408.2 4,256.4 3,832.3

2020 2025

Min Max Avg Min Max Avg

SOx 3.9 3.9 3.9 5.0 5.0 5.0

NOx 160.6 160.6 160.6 211.8 211.8 211.8 HC 145.1 145.1 145.1 175.3 175.3 175.3 PM 3,202.1 4,283.9 3,743.0 3,944.9 5,277.7 4,611.3 CO 845.9 845.9 845.9 1,043.8 1,043.8 1,043.8 TOTAL 4,357.6 5,439.4 4,898.5 5,380.8 6,713.6 6,047.2