full papers proceeding The 9th International Conference on Environmental Engineering, Science and Management_Final

PROCEEDING
THE 9th INTERNATIONAL CONFERENCE ON ENVIRONMENTAL

ENGINEERING, SCIENCE AND MANAGEMENT
(FULL PAPERS)

Organized by:
Environmental Engineering Association of Thailand
University of Phayao
Ministry of Natural Resources and Environment
Ministry of Higher Education, Science, Research and Innovation
Ministry of Industry
Ministry of Energy
Pollution Control Department
Office of Natural Resources and Environmental Policy and Planning

May 27-29, 2020
The Heritage Chiang Rai, Chiang Rai Province, Thailand

Message from President of Environmental Engineering
Association of Thailand

Environmental Engineering Association of Thailand (EEAT) has organized annual National
Conference on Environmental Engineering, Science and Management since 2002.
The main objective of the Conference is to share knowledge and research findings on the
environmental pollution and solution as well as other relevant subjects of the society and
the country. It is our great honor for the year of 2020 to co-host with the School of Energy
and Environment, Payao University to organize the 19th National Conference with the
9th International Conference on Environmental Engineering, Science and Management on 27-29
May, 2020 at The Heritage Chiang Rai, Chiang Rai Province, Thailand.

As already known that Thailand has encountered the pandemic of COVID-19 since nearly the
end of 2019 up to now (May, 2020) which we do not envisage when it will be back to normal
condition. In the meantime, there is an announcement of emergency decree for prohibition of the
conference consisting of a large number of participants as well as the social distancing measures.
With the awareness of the participants’ health, the Conference Organizer has postponed the
19th National and 9th International Conference on Environmental Engineering, Science and
Management to 7-9 October, 2020 at the same hotel with the same schedule conference process
including registration, paper submission, paper reviewing, proceeding preparation, as well as
paper presentation.

The Organizing Committee had compiled all reviewed and qualified abstracts for the proceeding
and electronic file of full paper in conformance with not only the national but also the
international standards. The conference is qualified with keynote address, oral and poster
sessions. In addition, EEAT has received all kinds of support from various relevant
governmental organizations Ministry of Natural Resources and Environment, Ministry of Higher
Education, Science, Research and Innovation, Ministry of Industry, Ministry of Energy,
Pollution Control Department, Office of Natural Resources and Environmental Policy and
Planning.

On behalf of EEAT, I would like to congratulate and express thanks to everyone who collaborate
in the presentations of research findings and many outstanding private sectors namely,
Siam Cement Public Company Limited, PTT Public Company Limited, Electricity Generation of
Thailand (EGAT), Bangchak Corporation Public Company Limited, Association of Three
Co., Ltd. And Research Centre for Environmental and Hazardous Substance Management
(EHSM) of Chulalongkorn University who provide an invaluable support to make the
Conference successful. Finally I wish both National and International Conferences
accomplishment with all the objectives designated.

Emeritus Prof. Thares Srisatit, Ph.D.
President
The Environmental Engineering Association of Thailand

Message from President of University of Phayao

Environmental Engineering Association of Thailand (EEAT) has organized annual National
Conference on Environmental Engineering, Science and Management since 2002. The main
objective of the Conference is to share knowledge and research findings on the environmental
pollution and solution as well as other relevant subjects of the society and the country. On behalf
of University of Phayao, it is our great honor for the year of 2020 to co-host with EEAT to
organize the 19th National Conference with the 9th International Conference on Environmental
Engineering, Science and Management.

As already known that Thailand has encountered the pandemic of COVID-19 since nearly the
end of the previous year up to now which we do not envisage when it will be back to normal
condition. In the meantime, there is an announcement of emergency decree for prohibition of the
conference consisting of a large number of participants as well as the social distancing measures.
With the awareness of the participants’ health, the Conference Organizer has postponed the
19th National and 9th International Conference on Environmental Engineering, Science and
Management to 7-9 October 2020 at the same venue with the same schedule conference process
including registration, paper submission, paper reviewing, proceeding preparation, as well as
paper presentation.

The Organizing Committee had compiled all reviewed and qualified abstracts for the proceeding
and electronic file of full paper in conformance with not only the national but also the
international standards. The conference is qualified with keynote address, oral and poster
sessions.

University of Phayao has received all kinds of support not only from various relevant
governmental organizations Ministry of Natural Resources and Environment, Ministry of Higher
Education, Science, Research and Innovation, Ministry of Industry, Ministry of Energy,
Pollution Control Department, Office of Natural Resources and Environmental Policy and
Planning, Research Centre for Environmental and Hazardous Substance Management (EHSM)
of Chulalongkorn University and but also from many outstanding private sectors namely,
Siam Cement Public Company Limited, PTT Public Company Limited, Electricity Generation of
Thailand (EGAT), Bangchak Corporation Public Company Limited, Association of Three
Co., Ltd., who provide an invaluable support to make the Conference successful.

On behalf of University of Phayao, I would like to congratulate and express thanks to everyone
who collaborate in the presentations of research findings. Finally, I wish both National and
International Conferences accomplishment with all the objectives designated.

Assoc. Prof. Dr. Supakorn Pongbangpho
President of University of Phayao

ORGANIZING COMMITTEE

ADVISORS
Emeritus Prof. Dr. Thares Srisatit

President, Environmental Engineering Association of Thailand
Assoc. Prof. Dr. Warawut Suadee

Vice President, Environmental Engineering Association of Thailand
Assoc. Prof. Dr. Supakorn Pongbaangpoh

President, University of Phayao

CHAIR
Assoc. Prof. Dr. Wanpen Wirojanagud

Vice President, Environmental Engineering Association of Thailand
Assoc. Prof. Dr. Suchat Leungprasert

Technical Committee Chairman, Environmental Engineering Association of Thailand

CO-CHAIR
Assoc. Prof. Dr. Torpong Kreetachat

School of Energy and Environment, University of Phayao
Asst. Prof. Dr. Anusorn Boonpoke

School of Energy and Environment, University of Phayao

INTERNATIONAL PROGRAM / SCIENTIFIC COMMITTEE
Prof. Am Jang, Sungkyunkwan University, Korea
Prof. Chih-Hsiang Liao, Chia Nan University of Pharmacy and Science, Taiwan
Prof. Chitsan Lin, National Kaohsiung University of Science and Technology, Taiwan
Prof. Gyu Tae Seo, Changwon National University, Korea
Prof. Jeonghwan Kim, Inha University, Korea
Prof. Kazuei Ishii, Hokkaido University, Japan
Prof. Kwang-Ho Choo, Kyungpook National University, Korea
Prof. SASAKI Choichi, Hirosaki Unversity, Japan
Prof. Seokoh Ko, Kyunghee University, Korea
Prof. Seungkwan Hong, Korea University, Korea
Prof. SHA Liqing, The Chinese Academy of Sciences, China
Prof. Zhang Yiping, The Chinese Academy of Sciences, China
Assoc. Prof. Amnat Chidthaisong, King Mongkut’s University of Technology Thonburi, Thailand
Assoc. Prof. Qinghai SONG, The Chinese Academy of Sciences, China
Assoc. Prof. Shigeoki Moritani, Hirosaki Unversity, Japan
Assoc. Prof. Sirintornthep Towprayoon, King Mongkut’s University of Technology Thonburi, Thailand
Dr. Brian James, University of London, UK
Mr. Mushtaq Ahmed Memon, International Environmental Technology Centre (IETC) Japan
Mr. Ray Earle, Dublin City University, Ireland
Assoc. Prof. Dr. Wanpen Wirojanagud, Khon Kaen University, Thailand
Assoc. Prof. Dr. Warawut Suadee, Thammasat University, Rangsit Center, Thailand
Assoc. Prof. Dr. Chart Chiemchaisri, Kasetsart University, Thailand
Assoc. Prof. Dr. Torpong Kreetachat, Phayao University, Thailand
Assoc. Prof. Dr. Petchporn Chawakitchareon, Chulalongkorn University, Thailand
Assoc. Prof. Dr. Vissanu Meeyoo, Mahanakorn University of Technology, Thailand
Assist. Prof. Dr. Sarun Tejasen, Chulalongkorn University, Thailand
Assist. Prof. Dr. Dondej Tungtakanpoung, Naresuan University, Thailand
Assoc. Prof. Dr. Suchat Leungprasert, Kasetsart University, Thailand
Assist. Prof. Dr. Achariya Suriyawong, Chulalongkorn University, Thailand

PROCEEDING SUPPORTING STAFFS
Panida Insutha
Pitsanu Pannaracha
Suwanna Polyam

Editorial Remark

Environmental Engineering Association of Thailand in co-host with the School of Energy and
Environment, University of Phayao, in collaboration with the Ministry of Natural Resource and
Environment, Ministry of Higher Education, Science, Research and Innovation, Ministry of
Industry, Ministry of Energy, Pollution Control Department, Office of Natural Resources and
Environmental Policy and Planning, and other supporting agencies have organized the
19th National and the 9th International Conference on Environmental Engineering, Science and
Management on October 7-9, 2020. The main goal of this conference is to be the platform for
knowledge management of academia, researchers, experts and interested people on
environmental management subject, particularly science and engineering related topics. The
academic knowledge drawn from the conference would be advantage to the national and
international society for prevention and mitigation of environmental problems being
substantially come across.

The conference document includes abstracts and full papers being considered for presentation
and publication through the reviewing process of the experts and editorial team. The abstracts
and full papers are compiled in the proceeding and in the electronic file, respectively. The
conference papers will be selected for publication of the EEAT journal if academically
appropriate.

On behalf of the editorial team, we would like to thank the researchers, academia for preparing
abstract, full papers and oral/ poster presentation, as well as experts and other interested people
for participation to this conference. We also would like to express our thanks to the experts and
organizing committee to a meaningful collaboration for reviewing abstracts/papers and giving
helpful comments and recommendations to the authors and accomplish the completeness of
conference document. It is also thankful to the participants, organizing committee who support
the conference coming to fruitfully achieve our goal.

Editorial Team:
Thares Srisatit
Wanpen Wirojanagud
Suchat Leungprasert
Torpong Kreetachat
Anusorn Boonpoke

EEAT EXECUTIVE COMMITTEE 2018-2021

Honorary Eminences
Emeritus Prof. Dr. Thongchai Panswad

Honorary Advisors
Pranee Pantumsinchai, P.E.
Dr.-Ing. Ksemsan Suwarnarat
Dr. Prasert Tapaneeyangkul

President
Emeritus Prof. Dr. Thares Srisatit

Vice President
Assoc. Prof. Dr. Wanpen Wirojanagud
Assoc. Prof. Dr. Warawut Suadee

Central Committee
Assoc. Prof. Dr. Chart Chiemchaisri
Assoc. Prof. Dr. Torpong Kreetachat
Assist. Prof. Dr. Dondej Tungtakanpoung
Assist. Prof. Dr. Sarun Tejasen

Activities Committee Chairman
Assoc. Prof. Dr. Petchporn Chawakitchareon

Technical Committee Chairman
Assoc. Prof. Dr. Suchat Leungprasert

Treasurer
Assoc. Prof. Dr. Vissanu Meeyoo

Secretary General
Assist. Prof. Dr. Achariya Suriyawong

I

CONTENTS

ORAL 1
9
I 002 15
Decolorization and COD Reduction of Effluent from Biogas Chamber by 21
Electro-Fenton Process 27
Preenaphan Tanteerapolchai, Paiboon Sreearunothai, Korakot Sombatmankhong and 35
Maythee Saisriyoot 43
51
I 003
Cultivation of Chlorella sp. in Chicken Farm Biogas Effluent for
CO2 and Nutrient Removal
Kamoldara Reansuwan, Saoharit Nitayavardhana and Sirichai Koonaphapdeelert

I 004
Suitable Electric Canal Bus for Bangkok: First Preview
Oravit Hemachudha and Chugiat Wichiencharoen

I 005
Assessment of Community Flood Vulnerability Indicators in Pak Phanang District,
Nakhon Si Thammarat Province, Thailand
Chaipol Srituravanich, Athit Phetrak, Jenyuk Lohwacharin, Suthirat Kittipongvises,
Nutta Taneepanichskul and Wandee Sirichokchatchawan

I 006
GIS-Assisted Assessment of Surface Water Quality at Moeyungyi Wetland in
Myanmar
Aye N. Thu, Ranjna Jindal, Nawatch Surinkul and Romanee Thongdara

I 007
Investigation of Nutrients Concentrations Distribution in
Moeyungyi Wetland in Myanmar using Geographic Information Systems
Zin K.K. Oo, Ranjna Jindal, Romanee Thongdara and Nawatch Surinkul

I 008
Investigation of the Impact of Taung-Inn-Myount-Inn Open Dumping Site for
Municipal Solid Waste on Soil and Surface/Ground Water in Mandalay City in
Myanmar
Hsu Yee Mon, Ranjna Jindal, Romanee Thongdara and Nawatch Surinkul

I 009
Evaluating Carbon Footprint of the Department of Environmental Engineering,
Chiang Mai University
Sarunnoud Phuphisith and Kanpunyanan Premchit

II

I 010 57
Development of Immobilized Bacteria on Sludge Based Adsorbent for the Post- 65
Treatment of Septic Tank 73
Sirinthip Kedsana and Nawatch Surinkul 79
84
I 011 90
Seasonal activity of cambium in Pinus latteri and Pinus kesiya related to climate 98
variables in northern Thailand 103
Piyarat Songtrirat, Nathsuda Pumijumnong and Supaporn Buajan
111
I 012 117
Material Flow Analysis of Lead in Lead Acid Batteries Supply Chain
Toward Circular Economy
Wanida Suriyanon, Napat Jakrawatana and Nakorn Suriyanon

I 013
Food Losses Analysis in Noodle Production in Northern Thailand
Chuanchom Nitano and Napat Jakrawatana

I 014
Biodegradation of PAHs by The Mixed Cultures of Diesel Degradation Bacteria
Aphinya Fucharoen, Pharkphum Rakruam and Chia-Yuan Chang

I 016
Application of Geo-informatics Technology to Study Land Use Changes for
Agriculture at Wang Wiset District, Trang Province
Dungjai Sirirak and Tidarat Kumlom

I 018
Effects of Vinasse Concentration and Aeration Rate on Fungal Protein Production in
Bubble Column Bioreactor
Akethakorn Thaworn and Saoharit Nitayavardhana

I 020
Occupational Hazard Identification in Plastic Recycling Plants in Thailand: Case
studies of Polyethylene and Polypropylene
Ayaj Ansar, Mongkolchai Assawadithalerd, Danai Tipmanee, Laksana Laokiat,
Pummarin Khamdahsag and Suthirat Kittipongvises

I 021
Long-term Trend of Visibility and PM2.5 in Southern Taiwan
Chayanis Wongrat, Khajornsak Sopajaree and Ying I. Tsai

I 022
Detection and Preliminary Assessment Of Human Exposure to Organophosphate
Flame Retardants (OPFRs) From House Dust
Benjawan Nilyok, Sun Olapiriyakul, Supachai Songngam and
Premrudee Kanchanapiya

III

I 023 124
Ammonium-Nitrogen Removal in Wastewater Through Adsorption Utilizing 132
Bio-Sorbent Matrix 137
Chalisa Jantaraksa and Nawatch Surinkul 145
152
I 024 158
Adsorption of bromoacetonitriles by using activated carbon produced from calico 166
fabric 173
Kanlayanee Yimyam and Pharkphum Rakruam 179

I 025
Characterization of MOF/PVDF Composite Membrane for Dichloroacetic Acid
Removal from Tap Water through Electrochemical Oxidation
Toungnutcha Chantaramusagarn, Jenyuk Lohwacharin and Chalita Ratanatawanate

I 026
Effects of Polyvinyl Alcohol Gel Beads in the Methanogenic Reactor on Performance
Improvement of Two Stage Thermophilic Anaerobic Bioreactor
Kanidtha Hanvajanawong, Jenyuk Lohwacharin and Benjaporn Suwannasilp

I 027
Greenhouse Gas Emissions and Climate Change Impacts from Plastic Waste
Recycling Processes: Polypropylene and Polyethylene as Case Studies
Katreeya Saejew, Mongkolchai Assawadithalerd, Danai Tipmanee, Laksana Laokiat,
Pummarin Khamdahsag and Suthirat Kittipongvises

I 028
Development of Flotation Enhanced Stirred Tank (FEST) Process
for Petroleum Hydrocarbons Removal from Drill Cuttings
Marina Phea, Nattawin Chawaloesphonsiya, Thaksina Poyai, Saret Bun and
Pisut Painmanakul

I 029
Bio-char Production from Co-pyrolysis between Rice Husk and Plastic:
A Morphology Study
Nichakorn Wantaneeyakul and Ketwalee Kositkanawuth

I 031
Comparison of Various Pretreatment Techniques on Enhancing Sugar Yields from
Sugarcane Trash
Pavarisa Chaipet, Wanwipa Siriwatwechakul and Verawat Champreda

I 032
Impact of Bioeconomy Policy on the Monthly Water Scarcity Footprints in the
Northern Biohubs Region
Pitak Ngammuangtueng, Pariyapat Nilsalab and Napat Jakrawatana

IV

I 033 183
Abundance and Distribution of Suspended Microplastics in the Surface Water of
Chao Phraya River Estuary 190
Phyo Zaw Oo, Suwanna Kitpati Boontanon, Narin Boontanon, 197
Shuhei Tanaka and Shigeo Fujii 204
212
I 034 219
Electricity generation using wind stack together with carbon dioxide capture 227
Rawat Yimvilai, Suwanna Kitpati Boontanon and Narin Boontanon
235
I 035 243
Daytime and Nighttime Variation of Chemical Characteristics of PM1.0 and Gaseous 248
Pollutants in the Suburbs of Taiwan in Autumn
Sasipim Somphan, Khajornsak Sopajaree and Ying I. Tsai

I 036
A Study on Influence of Meteorological Factors on PM2.5 over Bangkok, Thailand:
Case study of Bang Na Station
Angkhana Ketjalan, Usa Humphries and Warawut Suadee

I 037
Determination of Emission Factors and Chemical Properties of Particulate Matter
from Biomass Burning
Siripitch Songsompun, Khajornsak Sopajaree and Ying I. Tsai

I 038
Effect of Salinity on Chlorella vulgaris for Increasing Lipid Content
Vicheka Keo and Thaniya Kaosol

I 040
Optimization of Washing Conditions and Adsorption Process for Petroleum
Hydrocarbon Removal from Drill Cuttings Byproduct
Theary Peng Orng, Thaksina Poyai, Nattawin Chawaloesphonsiya,
Saret Bun and Pisut Painmanakul

I 041
Potential of Pollutant Transport from Petroleum Platform Area in the Gulf of
Thailand for Monitoring Plan
Viranya Kittivarakul and Pichet Chaiwiwatworakul

I 042
Assessment of Impact from Biogas Leakage by Area Location of Hazardous
Atmosphere Simulation
Wilasinee Yoochatchaval and Wijitra Wattanapakorn

I 043
Evaluating the Distribution of Microplastics in Patong Beach, Phuket, Thailand
S Tongnonhin, P Akkajit and D Tipmanee

V

I 044 253
Investigation on Micropollutant Degradation and Biotoxicity by using Activated
Sludge and Photocatalysis Processes Treating Landfill Leachate under Different 259
Hydraulic Retention Time
Pitakporn Thankulkit, Supaporn Phanwilai, Sivakorn Angthong and 265
Jarungwit Boonnorat 269
277
I 046 283
Assessment of Drinking Water Quality Through Turbidity and Microbial Indicators 288
in Stored Rainwater of Flood-prone Communities, Nakhon Si Thammarat Province, 295
Thailand 302
Teeraphat Attavinijtrakarn, Athit Phetrak, Jenyuk Lohwacharin, Suthirat
Kittipongvises, Nutta Taneepanichskul and Wandee Sirichokchatchawan

I 048
Experimental Study on Hydrogenation of Metal Hydride in Storage Tank
Thanasak Chumwisoot and Roongrojana Songprakorp

I 049
Composition and Functional Responses of Microbial Community to Temperature and
Substrate in Anaerobic Digestion Process
Mujalin K. Pholchan, Koontida Chalermsan, Piyanuch Niamsup and
Srikanjana Poonpat Poonnoi

I 050
Development of Activated Carbons from Rubber Wood Using Microwave Induced
Phosphoric Acid Activation
Panatda Klingklay, Kittipong Kunchariyakun, Weerawut Chaiwat and
Suthatip Sinyoung

I 055
Environmental Health Needs Assessment for Local Government Flood Response in
Nakhon Si Thammarat, Thailand
Jariya Matrongduang, Nutta Taneepanichskul, Wandee Sirichokchatchawan,
Suthirat Kittipongvises, Athit Phetrak and Jenyuk Lohwacharin

I 056
Assessment of Biomethane Potential (BMP) from Different Kinds of Maize
Residue Component
Nuttawan Suebnanta, Rotjapun Nirunsin, Tanate Chaichana and
Thapana Cheunbarn

I 057
Development of Proactive and Holistic Air Quality Management Approach for
Factories
Sudjit Karuchit, Nares Chuersuwan, Nirun Kongritti and Tananchai Wannasook

I 058
Adsorption of Mercury by Metal-Organic Frameworks in Saline Phase
Korfun Borisutsawad, Chalita Ratanatawanate and Patiparn Punyapalakul

VI 310
317
I 060 324
Factors Affecting on Household Willingness to Participate in Municipal Solid 330
Waste Management in Yangon, Mandalay and Nay Pyi Taw Cities of Myanmar
Nwe Ni Win, Ampai Thongteeraparp, Kobkaew Manomaipiboon and 338
Achara Ussawarujikulchai 345
353
I 061 360
Comparison of MPs Contamination between Downstream and Upstream Sites: 365
A Case Study of Lower Chao Phraya River, Thailand
Khattiya Ounjai, Suwanna Kitpati Boontanon, Shuhei Tanaka and Shigeo Fujii

I 062
Municipal Solid Waste Quantity and Composition Evaluation for Assessment of
Wasteaware Indicators in Special Economic Zone (SEZ), Chiang Rai Province
Chaloemphan Kaewkanta, Yanasinee Suma and Numfon Eaktasang

I 066
Health impacts of life cycle particulate formation from private vehicles and public
buses in Bangkok
Phatcharakorn Sakpheng, Ittipol Paw-armart, Witsanu Attavanich,
Sirima Panyametheekul, Jitti Mungkalasiri, Shabbir H. Gheewala and
Trakarn Prapaspongsa

I 067
Community Participation in Waste Recycling among Myanmar Migrants in
Khok Kham Sub District, Samut Sakhon Province, Thailand
Saranya Sucharitakul, Chalaporn Kamnerdpeth and Hnin Wai Phyo

I 068
The Impact of Aviation Business on global Climate Change
Nisakorn Nakornkao

I 069
Human-associated Escherichia coli Marker: Important Indicator to Evaluate River
Water Quality and Treatment Ability of Surrounding Wastewater Treatment Plants
Pimchanok Nopprapun, Suwanna Kitpati Boontanon, Shigeo Fujii and
Hidenori Harada

I 070
XPS Analysis of Iron Nanoparticles Synthesized using Green Chemistry
Anusara Kaeokan and Apichon Watcharenwong

T-08
Partitioning of Soil Respiration in Primary Dry Dipterocarp Forest
at Nakhon Ratchasima Province, Thailand
Wittanan Tammadid, Phuvasa Chanonmuang, Jumlong Plagsanoi,
Supika Vanitchang, Amnat Chidthaisong and Phongthep Hanpattakit

VII

POSTER 373
379
I 017
The Electricity Production Capability from Palm Oil Mill Effluent (POME) 387
Wilasinee Yoochatchaval and Acharapun Prothirusmee 391
397
I 053 405
Prevalence of Depressive Symptom and Sleep Quality of Local Elderly Resident near 413
Lignite Power Plant, Mae Moh Subdistrict, Lampang Province 419
Chatsuda Mata, Nutta Taneepanichskul, Sattamat Lappharat and 425
Yaowares Chusiri 432

HIROSAKI

H-01
Green Chromatic Coordinate (GCC) Affects CO2 Budget in Beech Forest
Sachinobu Ishida, Motomu Toda, Tsukasa Saito, Yuushi Igari and Daiyu Ito

H-02
The Effects of Aquaculture Wastes Application on Heavy Metal Distribution in
Apple Orchard Soils
Eriko Komori, Chihiro Kato, Hidekazu Kobatake, Akira Endo,
Choichi Sasaki and Nobuhiko Matsuyama

H-03
Engineered Pseudomonas putida Strains Producing cis,cis-Muconic Acid from
Softwood Lignin-Related Phenols
Akihiro KIKUCHI, Haruka SUGITA, Minami HATAMURA,
Miho AKUTSU1 and Tomonori SONOKI

H-04
Environmental Impact of Riverbank Formed by Contaminated Soil
Sachi A. Wakasa, Vladan Marincović, Tomomi Takeda, Junichi Kurihara,
Lidja Đurđevac Ignjatović, Tamara Urosević and Renata Kovacević

H-05
Carbon Footprint Assessment of Akha Mino Coffee Product
Sirasit Meesiri and Anusorn Boopoke

H-06
Fractionation of the main components of rice straw by solvothermal process
Supawan Upajak and Saksit Imman

H-07
Short-Term Effects of Ambient PM2.5 from Biomass Burning on Mortality from
Respiratory Diseases during the Smog Episode in Thailand
Thao Ngoc Linh Nguyen, Sittichai Pimonsree, Patipat Vongruang,
Pham Thi Bich Thao and Kritana Prueksakorn

H-08
Design of Green Roof Application with Gray Water in Tropical Area
Moritani Shigeoki, Tahei Yamamoto, Sukthai Pongpattansiri,
Chuleemas Boonthai Iwai and Anusorn Bunpok

Oral

Presentation

-1-
I 002

Decolorization and COD Reduction of Effluent from Biogas Chamber
by Electro-Fenton Process

Preenaphan Tanteerapolchai1*, Paiboon Sreearunothai2, Korakot Sombatmankhong3, and Maythee Saisriyoot4

1*Graduate student, Thailand Advanced Institute of Science and Technology (TAIST-Tokyo Tech), Sirindhorn
International Institute of Technology, Thammasat University, Pathum Thani 12121, Thailand.;

2Assocoate Professor, School of Bio-Chemical Engineering and Technology, Sirindhorn International
Institute of Technology, Thammasat University, Pathum Thani 12121, Thailand.;

3Researcher, Department of National Metal and Materials Technology Center, 114 Thailand Science Park,
Thanon Phahonyothin, Tambon Khlong Nueng, Amphoe Khlong Luang, Pathum Thani 12120, Thailand.;

4Assistance Professor, Department of Chemical Engineering, Faculty of Engineering,
Kasetsart University 10900, Thailand.

*Phone : 088-2263683, E-mail : [email protected]

ABSTRACT
This work aimed to study the decolorization and COD reduction of effluent from biogas chamber by

Electro-Fenton process, which generates powerful hydroxyl radicals that can degrade the recalcitrant highly
colored compounds in the effluent.

The degradation process of melanoidin from molasses which used molasses as the raw materials in
the production of ethanol produced contaminate in highly form of concentrated organic matter and color
contaminations that need be treated to meet the standard required by Pollution Control Department (PCD).

Experiment was conducted using bench-scale reactor under room temperature of 25 C. The studied
parameters were investigated in this work are the initial pH from 3-11, initial ferrous concentrations from
0.5-9 mM, an applied voltage from 1.0-3.0 volts, and the reaction times from 0-240 minutes. The results
showed that Electro-Fenton process could oxidize refractory organic pollutants in biogas effluent efficiently.
The optimum conditions of pH 3, 3 mM of ferrous concentration, 2.0 V, and the reaction time of 120
minutes were obtained with the color and the COD removal efficiency of 71.7% and 68.1%, respectively.

Keywords : Hydroxyl radicals; Molasses; Melanoidin; EAOPs; Electro-Fenton process; Three-dimensional
Electro-Fenton system

INTRODUCTION
The production of ethanol is one of the major industries in Thailand. However, the production of

ethanol process uses a huge amount of molasses and wastewater. Some of this wastewater is utilized as
feedstock for a biogas reactor, producing more of the biogas. At the end of the process, this biogas reactor
still generates a large amount of wastewater which is needed to be treated prior to discharge to the natural
receiving water. This biogas wastewater is highly colored and is quite recalcitrant to be further treated by
biological process. The quantities of biogas wastewater have been increasing along with the growing demand
of electricity and popularity of biogas power plant.

Most of the treatment plants uses biological process which is the least expensive technique for
removal of biodegradable organic pollutants. Nonetheless, treated effluent from the production of ethanol,
particularly from biogas effluent, still contains a very dark brown color derived from the refractory
melanoidin from molasses used as the raw materials in the production of ethanol. In the past, the color
standard for industrial discharge is objectionable with in many cases causes problem to implementing and
inspecting officers since color is rather subjective. The Pollution Control Department currently intends to
revise this color standard to be more scientific and standardized. The color unit in ADMI (American Dye
Manufacturers Institute) is proposed since it can be measured accurately and precisely The standard values
that allow for discharge are 300 ADMI in color and 120 mg/L in COD (Chemical Oxygen Demand) [1].
Once this proposed color standard is implemented, it will seriously affect the production of ethanol and
biogas. As a result, further treatment for color reduction (tertiary treatment) is needed. Since molasses is
considering refractory to biodegradation because of melanoidin which main compounds are metal sulfate,
phenolics, and high molecular weight polymeric compounds is caused the color of wastewater to have dark

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color [2-3] and difficult to be degraded by biological treatment process. Chemical treatment process is thus
required [4].

One of the most promising processes for the water color treatment is Advanced Oxidation Processes

(AOPs), a subset of which is a chemical process that produces hydroxyl radical (OH ). There is a very high
potential for oxidation to get rid of organic pollutants in water. Organic pollutants are transformed into

intermediate substances in order to eventually become carbon dioxide. Because hydroxyl radicals are very
sensitive to reaction, they need to be produced and used immediately. Advanced oxidation processes that

produce hydroxyl radicals are available in a variety of forms, such as Fenton process, Electro-Fenton process
Electro-Fenton process is Electrochemical Advanced Oxidation Processes (EAOPs). Its process is

one of the advanced oxidation processes, which can generate powerful hydroxyl radicals (OH) via direct and
indirect oxidation [5] and also can oxidize most refractory organic pollutants in air and water. Recently, the
three-dimensional electrochemical (3D-E) oxidation system was employed by many researchers to inserting

some electrodes between two-dimensional electrodes in the conventional electrochemical system to improve
wastewater treatment efficiency [6].

Electro-Fenton process is another important of EAOPs. It can produce OH by the continuous

electrogeneration of H2O2 on the cathode fed with O2 and the addition of ferrous sulfate as shown in the Eqs.
(1) and (2)
O2 + 2H+ + 2e-
→ H2O2 (1)
Fe2+ + H2O2 → Fe3+ + OH + OH-
(2)

In this work, we investigated on decolorization and COD reduction efficiencies of effluent from
biogas chamber by Electro-Fenton process. The effects of various parameters such as initial pH, initial
ferrous concentration, applied voltage, and reaction time were studied in this work.

METHODOLOGY

The Electro-Fenton process was conducted in a rectangular PMMA reactor with dimensions of 20 cm,
7.5 cm, and 7 cm in width, height, and thickness, respectively. The electrodes of Ti/RuO2-IrO2 (5 cm x 4 cm
x 2 mm), graphite felt (5 cm x 4 cm x 3 mm), and foam nickel (5 cm x 4 cm x 1 mm) were used as anode,
cathode, and support electrodes, respectively as shown in Figure 1. Air was purged at the rate of 1.5 L/min at
the bottom of reactor with magnetic stirrer during the treatment experiment.

Foam nickel Ti/RuO2-IrO2
Graphite felt Magnetic bar
Air pump

Fig. 1 Electro-Fenton reactor configuration

Wastewater used was derived from Milloinaire Suphan Biogreen Power Co., Ltd (Suphanburi, Thailand). It
was characterized as shown in Table 1. A 560 mL of effluent from biogas chamber was fed to the reactor
(initial wastewater had a dark brown color with a color value of 14,250 ADMI and COD concentration of
5,037 mg/L). 0.05 mol/L of Na2SO4 aqueous solution was used as the supporting electrolyte to increase the
conductivity.
1 mol/L of H2SO4 or NaOH was used to adjust the pH of wastewater for the study of initial pH on the
decolorization and COD reduction efficiencies. FeSO4.7H2O was added for the study of the initial
concentration of ferrous ion. The applied voltage was adjusted by a power supply (potentiostat/instrument,
Metrohm, PGSTAT 204).

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Table 1 Initial characteristics of wastewater provided from Milloinaire Suphan Biogreen Power Co.,Ltd
(Suphanburi, Thailand)

Parameters Unit Results Analyzed methods
Color ADMI
207,500 ADMI Weighted-Ordinate Spectrophotometer
pH - 7.7 Methhod 2120F.
Conductivity µs/cm Electrometric Method 4500-H+ B
NTU
Turbidity mg/L 39,300 Laboratory method 2510 B
TS (Total solid) mg/L
mg/L 1,240 Nephelometric Method 2130 B
COD mg/L
BOD5 mg/L 71,340 Total Solids Dried at 103-105C
Chloride mg/L
Sulfate 64,521 Open reflux method 5220B
Iron (Fe)
4,703 5-Days BOD Test 5210 B
9,550 0ime mcitem ci temoit et00-lC-.D
1,776 00 4ctctem ci temoit et00-.E -e2OS
35.71
Atomic Absorption Spectrometric Method

3500- Fe

In this work, the water samples were analyzed according to the APHA (1992) standard methods [7] as shown
in the Table 2.

Table 2 Analytical methods

Parameters Methods
Color UV-Vis spectrophotometer
COD Dichromate Close Reflux

H2O2 concentration Iodometric method
The concentration
of soluble iron ions (Fen+) Phenanthroline method
The elemental analysis
Micro ED-XRF

RESULTS AND DISCUSSIONS

This work aimed to study the possibility of decolorization and COD reduction efficiencies of
effluent from the production of ethanol, particularly from biogas effluent by using Electro-Fenton process.
The studied variables included initial pH, initial ferrous concentration, applied voltage, and reaction time.

The wastewater used in this work represent the effluent from the production of ethanol, particularly from
biogas effluent. The decolorization and COD reduction efficiencies were calculated from Eq. (3) and (4),
respectively. The results from this thesis were discussed in the detail as shown in the following.

Decolorization efficiency (%) = (1- ) x 100 (3)

; where C = final ADMI and C0 = initial ADMI

COD reduction efficiency (%) = (1- ) x 100 (4)

; where C = final COD concentration and C0 = initial COD concentration

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1 Effect of initial pH of wastewater

Evaluation of initial pH variation was investigated to examine the minimum initial pH for the
decolorization and COD (Chemical Oxygen Demand) reduction efficiencies of effluent from biogas chamber
by the Electro-Fenton process. The initial pH was varied from 3 to 11 to study the effect of each initial pH
range to the chemical reaction. The experiments were conducted under conditions of 3 sets of electrodes
(1 set is consisted of 1 Ti/RuO2-IrO2, 1 graphite felt, and 1 foam nickel), the addition of the FeSO4.7H2O

concentration of 3 mM was added for the study of the initial concentration of ferrous ion to be act as catalyst,
the applied voltage is 2.0 V, distance between electrode is 0.5 cm, and the controlled volume of wastewater
is 560 mL. The initial color unit (ADMI) and Chemical Oxygen Demand (COD) is 14,250 and 5,037 mg/L,
respectively at controlled temperature of 25 ℃ and reaction time of 120 min. The results of the experiment
can be seen that the decolorization efficiency was increased when decreasing pH as shown in Figure 2 (a).
The pH of 3,5,7,11 obtained the removal efficiency of 71.7%, 62.8%, 53.7%, and 16% respectively. pH 3
was also the optimum initial pH for COD removal as shown in Figure 2 (b). Hydroxyl radicals (OH•) is
highly generated at acidic pH, while at pH higher than 3, the generation of OH• is lower because Fe2+ is
more transformed to Fe3+ and the precipitation of Fe3+ as ferric hydroxide (Fe(OH)3) occurs. The (Fe(OH)3)
stimulates the decomposition of H2O2 to water and oxygen, thus the production of OH• decreased at high
pH [8]. The efficiencies of decolorization and COD reduction were thus decreased.

1.0 16% 13%

1.0

0.8ADMI (C/C0) 53.7% 0.8 53.9%
COD (C/C0)62.8% 49%
0.6 pH 3 71.7% 0.6 68.1%
pH 5 pH 3
pH 5
0.4
pH 7 0.4
pH 11 pH 7
pH 11
0.2
0.2

0.0 30 60 90 120 0.0 30 60 90 120
0 Time (min) 0 Time (min)

(a) Decolorization efficiency (b) COD reduction efficiency

Figure 2 Effect of initial pH on removal efficiency of effluent from biogas chamber by Electro-Fenton
process under the conditions of 560 ml of wastewater (initial ADMI = 14,250 and COD = 5,037
mg/L), initial ferrous concentration is 3 mM, 3 sets of electrodes, distance between electrode is

0.5 cm, applied voltage is 2.0 V and at temperature of 25C in 120 minutes

2 Effect of initial ferrous concentration

In this section, initial concentration of ferrous variation was varied to determine the effect of initial

ferrous concentration on the decolorization and COD (Chemical Oxygen Demand) reduction efficiencies of

effluent from biogas chamber by Electro-Fenton process. This is because ferrous ions is an important

parameter as catalyst that affects the chemical reactions in the water which are the combination of hydrogen
peroxide (H2O2) and a ferrous iron (Fe2+). Hence, its concentration should
performance. This section was conducted by varying the initial concentration significantly affect the process
of ferrous (Fe2+) between 0.5 to

9 mM and also conducted under conditions of initial pH is 3, 3 sets of electrodes (1 set is consisted of 1

Ti/RuO2-IrO2, 1 graphite felt, and 1 foam nickel), distance between electrode is 0.5 cm, the applied voltage is
2.0 V, and the controlled volume of wastewater is 560 ml by initial color unit (ADMI) and Chemical Oxygen

Demand (COD) is 14,250 and 5,037 mg/L, respectively at controlled temperature at 25 ℃ in 120 minutes.

The results found that both color and COD removal efficiencies increased with the increase initial

ferrous concentration from 0.5 mM to 3 mM are 35.5%, 66.2%, and 71.7% for color and 30.6%, 61.8%, and

68.1% for COD, respectively and can be seen that the decolorization and COD reduction efficiencies were

decreased significantly with increasing of initial ferrous concentration from 3 mM to 9 mM are 71.7%,

72.7%, 51.6%, and 49% for color and 68.1%, 64%, 62%, and 53.1% for COD, respectively as shown in

Figure 3 (a) and (b). This is due to the fact that excess amount of ferrous concentration could be oxidized by

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hydroxyl radicals to form a yellow precipitate of Fe3+ (Fe(OH)3) which waste hydroxyl radicals and generate
more iron sludge [9]. Hence, the optimum initial concentration of ferrous in this work should be 3 mM.

1.0 1.0

0.8 0.8

ADMI (C/C0) 30.6% 38%
COD (C/C0)49% 53.1%
0.6 0.5 mM 51.6% 0.6 0.5 mM 61.8%
66.2% 62%
1 mM 71.7% 1 mM 6648%.1%
72.7%
0.4 3 mM 0.4 3 mM 120
5 mM 120 5 mM

7 mM 7 mM

0.2 9 mM 0.2 9 mM

0.0 30 60 90 0.0 30 60 90
0 Time (min) 0 Time (min)

(a) Decolorization efficiency (b) COD reduction efficiency

Figure 3 Effect of initial ferrous concentration on removal efficiency of effluent from biogas chamber by
Electro-Fenton process under the conditions of 560 ml of wastewater (initial ADMI = 14,250 and
COD = 5,037 mg/L), initial pH is 3, 3 sets of electrodes, distance between electrode is 0.5 cm,

applied voltage is 2.0 V and at temperature of 25C in 120 minutes

3 Effect of applied voltage

Intensity of applied voltage is another factor controlling the system performance of Electro-Fenton
process. This experimental part tries to investigate the effect of intensity of applied voltage on the Electro-
Fenton process. The studied conditions were under varying the applied voltage between 1.0 to 3.0 V and also
conducted under conditions of initial pH is 3, the addition of the FeSO4.7H2O concentration of 3 mM was
added for the study of the initial concentration of ferrous ion to be act as catalyst, 3 sets of electrodes (1 set is
consisted of 1 Ti/RuO2-IrO2, 1 graphite felt, and 1 foam nickel), distance between electrode is 0.5 cm, and
the controlled volume of wastewater is 560 ml by initial color unit (ADMI) and Chemical Oxygen Demand
(COD) is 14,250 and 5,037 mg/L, respectively at controlled temperature at 25 ℃ in 120 minutes.

The results found that the 2.0 V provided the highest removal efficiencies both in term of
decolorization and COD reduction followed by 1.0, 2.0, and 3.0 V, i.e., 34.8%, 68.1%, and 52%, for color
and 65.3%, 71.7%, and 56% for COD, respectively as shown in Figure 4 (a) and (b). The increase of the
applied voltage from 1.0 to 2.0 V could enhance the removal efficiency and the production of the

electrogenerated H2O2, this is because more applied voltage caused the dissociation of hydrogen peroxide to
generate more concentration of hydroxyl radicals. Also, higher regeneration of ferrous ion from ferric ion
with the higher voltage increases the efficiency of reactions [10].

However, the removal efficiency decreased with further increase the applied voltage from 2.0 to 3.0
V. This is because higher potential could not only lead to more parasitic reactions such as the decomposition
of H2O2, but also cause higher energy consumption. Therefore, the applied voltage of 2.0 V is selected in this
work. In Electro-Fenton process, the generation of H2O2 at the cathode depends on applied voltage.

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1.0 1.0

0.8ADMI (C/C0) 56% 0.8 1V 34.8%
COD (C/C0) 0.6 2V 52%
0.6 65.3% 0.4 3V
71.7% 0.2 68.1%
1V

0.4 2 V

3V

0.2

0.0 30 60 90 120 0.0 30 60 90 120
0 Time (min) 0 Time (min)

(a) Decolorization efficiency (b) COD reduction efficiency

Figure 4 Effect of applied voltage on removal efficiency of effluent from biogas chamber by Electro-Fenton
process under the conditions of 560 ml of wastewater (initial ADMI = 14,250 and COD = 5,037
mg/L), initial pH is 3, initial ferrous concentration is 3 mM, 3 sets of electrodes, distance between

electrode is 0.5 cm, and at temperature of 25C in 120 minutes

4 Effect of reaction time

The relationship between reaction time and efficiencies of decolorization and COD reduction by
Electro-Fenton process is shown in Figure 5. This section was conducted by varying reaction time the and
also conducted under conditions of initial pH is 3, the addition of the FeSO4.7H2O concentration of 3 mM
was added for the study of the initial concentration of ferrous ion to be act as catalyst, 3 sets of electrodes (1
set is consisted of 1 Ti/RuO2-IrO2, 1 graphite felt, and 1 foam nickel), distance between electrode is 0.5 cm,
the applied voltage is 2.0 V and the controlled volume of wastewater is 560 ml by initial color unit (ADMI)
and Chemical Oxygen Demand (COD) is 14,250 and 5,037 mg/L, respectively at controlled temperature at
25 ℃.

To observe the effect of reaction time on the Electro-Fenton process for every 15,30,60 minutes

interval since 0-240 minutes, the sample were withdrawn from the batch reactor and the decolorization and
COD reduction efficiency were analyzed following Table 2.

In Electro-Fenton process, the color removal gradually increased and attained constant after 2 hours
of degradation time. The results found as shown in Figure 4 (a) and (b). The decolorization and COD

reduction efficiencies directly depends on the concentration of hydroxyl radicals and ferrous ions generated
by the electrodes and longer reaction time leads to a more generation of ions. Decolorization was observed
till complete deployment of the Fenton’s reagent that has been added to the system.

When considering about the decolorization kinetics in a batch electrochemical reactor, the decrease
in color with respect to time will remain constant under a given set of optimized experimental conditions.

However, the rate of color removal strongly depends on the applied voltage and concentration of the reagents
added. The rate of decolorization in a batch electrochemical reactor can be expressed as Eq. (5)

Ct =C0 exp(− kh at) (5)

where, C0 and Ct are the initial absorbance and absorbance at time t for the spent wash at a corresponding
wavelength of 475 nm. kh is heterogenous electrochemical rate constant, a is specific electrode area (Ae/VR;
Ae is electrode area and VR is reactor volume). The rate constant can be calculated from the slope of the plot
–ln (C0 / Ct ) vs time. For Electro-Fenton process, the heterogenous rate constant varies from 2.672 x 10-3 to
3.34 x 10-4 cm s-1 [11].

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1.0 1.0

0.8 0.8

71.7% 68.1%
0.6 72% 0.6 71.3%

72.2% 72.5%
0.4 0.4
ADMI (C/C0)
COD (C/C0)

0.2 0.2

0.0 30 60 90 120 150 180 210 240 270 0.0 30 60 90 120 150 180 210 240 270
0 Time (min) 0 Time (min)

(a) Decolorization efficiency (b) COD reduction efficiency

Figure 5 Effect of reaction time on removal efficiency of effluent from biogas chamber by Electro-Fenton
process under the conditions of 560 ml of wastewater (initial ADMI = 14,250 and COD = 5,037
mg/L), initial pH is 3, initial ferrous concentration is 3 mM, 3 sets of electrodes, distance

between electrode is 0.5 cm, applied voltage is 2.0 V and at temperature of 25C

CONCLUSION

Electro-Fenton process was found to be an effective treatment for wastewater in this work allowing
for the significant decolorization and COD reduction. Biogas wastewater has already undergone a biological

process and the recalcitrant color compound could not be efficiently degraded by a biological treatment
process. Hence, there is a needed of Electro-Fenton process (chemical treatment process) for further
increased of degradation. Oxidation by Electro-Fenton process have several affected parameters on the
system performance. The valued of initial pH present in the solution play an important role for organic

degradation, initial ferrous concentration, applied voltage, and also reaction time have a significant impact
on the performance of Electro-Fenton process both in term of decolorization and COD reduction. The

optimum conditions found in this work to were the initial pH of 3, the initial ferrous concentration of 3 mM,

the applied voltage of 2.0V, and 120 min of reaction time, which achieved the decolorization and COD
removal efficiencies of 71.7% and 68.1%, respectively.

ACKNOWLEDGEMENT
The authors would like to thank Milloinaire Suphan Biogreen Power Co.,Ltd (Suphanburi, Thailand)

for wastewater sample. The authors greatly appreciate for opportunities, and financial support from Thailand
Advanced Institute of Science and Technology (TAIST-Tokyo Tech), Sirindhorn International Institute of

Technology, Thammasat University, Department of Chemical Engineering, Faculty of Engineering,
Kasetsart University, Department of National Metal and Materials Technology Center (MTEC), and National
Science and Technology Development Agency (NSTDA).

REFERENCE

[1] Ministry of Industry Thailand, The declaration of Standard of control wastewater discharge from

industry, 2019 B.C.

[2] A.R. Santal, N.P. Singh, Biodegradation of melanoidin from distillery effluent: Role of microbes and

their potential enzymes, in: D.R. Chamy (Ed.), Biodegrad. Hazard. Spec. Prod., InTech, 2013.

[3] D.N. Olennikov, L.M. Tankhaeva, Physicochemical characteristics and antioxidant activity of

melanoidin pigment from the fermented leaves of Orthosiphon stamineus, Brazilian J. Pharmacogn. 22

(2012): p. 284–290.

[4] J.A. -Henares, F.J. Morales, Antimicrobial activity of melanoidins against Escherichia coli is

mediated by a membrane-damage mechanism, J. Agric. Food Chem. 56 (2008): p. 2357–2362.

[5] M. Susree, P. Asaithambi, R. Saravanathamizhan, M. Matheswaran, Studies on various mode of

electrochemical reactor operation for the treatment of distillery effluent, J. Environ. Chem. Eng. 1

(2013): p. 552–558.

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[6] Z.G. Liu, F.F. Wang, Y.S. Li, T.L. Xu, S.M. Zhu, Continuous electrochemical oxidation of methyl

orange wastewater using a three-dimensional electrode reactor. J. Environ. Sci. 23 (2011): p. 70–73.
[7] APHA (1992), Standard Methods for the Examination of Water and Wastewater, 23nd Edition,

American Public Health Association, American Water Works Association, Water Environment
Federation, Washington D.C.
[8] Bautista, P., Mohedano, A. F., Gilarranz, M. A., Casas, J. A., & Rodriguez, J. J., Application of
Fenton oxidation to cosmetic wastewaters treatment. Journal of Hazardous Materials 143(1-2) (2007):
p. 128–134.
[9] Benitez, F., Acero, J., Real, F., Rubio, F., & Leal, A., The role of hydroxyl radicals for the
decomposition of p-hydroxy phenylacetic acid in aqueous solutions. Water Research 35(5) (2001): p.
1338–1343.
[10] Estrada., A.L., Li, Y.Y., Wang, A., Biodegradability enhancement of wastewater containing cefalexin
by means of the electro-Fenton oxidation process. J. Ha- zard. Mater. 227–228 (2012): p. 41–48.
[11] Susree, M., Asaithambi, P., Saravanathamizhan, R., Matheswaran, M., Studies on various mode of
electrochemical reactor operation for the treatment of distillery effluent. J. Environ. Chem. Eng. 1
(2013): p. 552–558.

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Cultivation of Chlorella sp. in Chicken Farm Biogas Effluent for
CO2 and Nutrient Removal

Kamoldara Reansuwan1, Saoharit Nitayavardhana1,2 and Sirichai Koonaphapdeelert1,2*

1Department of Environmental Engineering, Chiang Mai University, Thailand.
2Energy Research and Development Institute-Nakornping, Chiang Mai University, Thailand.

* Corresponding author, phone: 053-942007, email: [email protected]

ABSTRACT
This study to investigate the growth of microalgae as a mean to remove CO2 from biogas upgrading process
as well as to remove macro-nutrients from a biogas digester effluent. Two batch experiments of lighting and
without lighting conditions were used in this study and the results showed that the growth rate of Chlorella
sp. were 0.95 d-1 and 0.41 d-1, respectively. The growth rate of Chlorella sp. in a lighting condition was
higher than that without lighting by more than 2.3 times. The nitrogen removal rates were 19.17±1.07 and
26.06±4.73 mgL-1d-1, respectively. The phosphorus removal rates were 2.59±0.09 and 4.40±0.38 mg L-1d-1,
respectively. The CO2 consumption rate found in a lighting condition was 582±3.68 mgL-1d-1. On the other
hand, the rate without lighting was 413±4.43 mgL-1d-1, suggesting that Chlorella sp. could utilize CO2 well
under adequate lighting. The results from this study demonstrate that the CO2-rich off gas from a stripping
column can be used to enhance the growth of algae in the effluent. Not only the CO2 can be partially
captured but the wastewater can be simultaneously treated.

Keywords : microalgae, Chlorella sp. nutrient removal, CO2 removal, biogas effluent

INTRODUCTION
Thailand is a developing country with agriculture as one of its main industries. Livestock farming, especially
swine, chicken and cattle, is very common and the revenue from this sector is accounted for 35% of the
whole industry [1]. By using livestock manure and wastewater as raw materials, biogas can be produced
through anaerobic digestion. It was reported that industrial wastewater and livestock manure have a potential
of biogas production, equivalent to 7,800 and 13,000 TJ/year, respectively [2].

Biogas comprises methane (CH4) and carbon dioxide (CO2) as the main components. Carbon dioxide is in a
range of 25-50% by volume and is known as a major anthropogenic greenhouse gas contributing to 87% of
global warming. A novel technique of biogas digester effluent recirculation has been employed to upgrade
the biogas. However, some proportion of CO2 is released to the atmosphere from a gas stripping column used
for the process. In order to reduce the amount of CO2 emitted, cultivation of microalgae can be integrated to
the existing biogas with recirculation system. The photosynthesis mechanism can convert CO2 into biomass.

Microalgae have a simple cell structure and their growth requires light, carbon dioxide, water, and nutrients
(phosphorus and nitrogen as major nutrients). The great flexibility and adaptability of microalgae to grow in
diverse environments mean that they use less land than other terrestrial plant. Thus the competition with food
crops can be avoided. It was reported that the growth rate of microalgae is in average 5–10 times faster than
conventional food crops on the same land area. Popular alga species, i.e. Chlorella vulgaris,
Scenedesmusobliquus and Ourococcusmultisporus, are often selected as they have high biomass yields with
the ability to remove CO2 by 15% and nutrients by 99% [3]. Chlorella sp. was reported to be a suitable strain
for capturing CO2 [4] and its nutrient reduction efficiency was as high as 63.4% of total nitrogen and 81.9%
of total phosphorus [5]. Different algae show different responses to high light intensity. Generally,
photosynthesis (CO2 fixation and growth) increases with increasing light intensity [6].

The objective of this research is to investigate the growth of microalgae as a mean to remove CO2 from
biogas upgrading process as well as to remove macro-nutrients from a biogas digester effluent.

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METHODOLOGY

Algal strains, medium and inoculums preparation

The cultured microalgae, Chlorella sp. were obtained from Faculty of Fishery Technology and Aquatic

Resources, Maejo-Chumphon university, Chiang Mai, Thailand. An inoculum was prepared in a 6-liter bottle
containing 5 liter of medium which consisted of 0.3 gL-1 of urea, 0.15 gL-1 of fertilizer (16-20-0), 0.5 gL-1 of
bran and 0.09 gL-1 calcium oxide [7]. The inoculum was kept under room temperature and was continuously

aerated. The initial Chlorella sp. concentration was 10% (v/v) with the optical density (OD560) of 0.5.

Experimental procedure
Two batch experiments, comprising an experiment with lighting (B1) and an experiment without lighting
(B2), were carried out simultaneously in a twin wastewater treatment reactor with the total volume of 98
liters each. The reactor was operated in a sequencing batch mode. The feed was the effluent from a channel-
type anaerobic digester. A CO2 source was the off-gas from gas stripping column, containing 2% v/v of CO2
in air. The off-gas flow rate was kept constant at 4.5 Lmin-1. In B1 experiment, the reactor was exposed to
the artificial light intensity of 3,000 lux by fluorescent lamps. In B2 experiment, the reactor was covered
with black PVC plastic sheet as shown in Figure 1. The cultivation period was 21 days.

CO2 consumption
The CO2 fixation efficiency is calculated daily in terms of CO2 consumed by the microalgae. The carbon
dioxide consumption rate (PCO2, mg l-1d-1) is derived by using the following equation [8]:

PCO2 = 1.88×P (1)

The increase of biomass concentration (X; gL-1) was used to calculate the maximum specific growth rate
(μmax, d-1). The maximum biomass concentration achieved in culture is designated as Xmax (gL-1), and the
biomass productivity is defined in terms of milligram of biomass produced per day (P, mgL-1d-1). the

biomass productivity is calculated using Equation 2 [8].

P = ∆X/∆t (2)

(a) (b)
Figure 1 (a) experiments with lighting (B1) and (b) without lighting (B2)

Analysis methods
Liquid samples were taken from sampling ports located at the reactor inlet and outlet two times a week. The
standard methods 4500-Norg B., 4500- NO2- B., 4500- NO3- D. and 4500 P. were used to determine the total
nitrogen (TN), and total phosphorous (TP) in water samples, respectively [9]. Other parameters included pH,
temperature, total suspended solid, volatile suspended solid, and chemical oxygen demand using the standard
methods [10]. The alga cell concentration was determined by a direct microscopic counting method using a
hemocytometer and by turbidimetry at 560 nm. The dry cell weight was determined by the method described
in [4]. All analysis was conducted in triplicates. Analysis of variance was performed to calculate significant
differences among treatment means.

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RESULTS AND DISCUSSIONS
Effects of cultivation on alga growth
Two batch experiments of lighting (B1) and without lighting conditions (B2) were conducted in this study
and the results are shown in Figure 2. It can be observed that lighting had significant effect on the growth of
Chlorella sp. . The maximum cell concentration of Chlorella sp. was of 23×106 cells ml-1, with the specific
growth rate 0.95 d-1, the growth rate at a 7 day (B1). The maximum cell concentration in B2 experiment was
15×106 cells ml-1, with the specific growth rate 0.41 d-1 and the growth rate at a 4 day (B2). It was found that
the growth rate in B1 experiment was significantly higher than that in B2 experiment by 2.3 times. The
results showed that Chlorella sp. which was reported to be mixotrophic, could grow well under lighting
conditions. The results are consistent with previous studies that also achieved higher growth of microalgae in
mixotrophic conditions [11]. It was found that the growth of Chlorella sorokiniana was 2 times higher in
mixotrophic a condition than in an autotrophic condition. Because Chlorella sp. grown under mixotrophic
conditions metabolized both heterotrophically and autotrophically, this resulted in a stimulated growth rate.
In addition, Chlorella minutissima was cultured in autotrophic, mixotrophic, and heterotrophic conditions,
the growth rate in mixotrophic condition was more than 2 times and 7 times higher than that in heterotrophic
and autotrophic conditions, respectively [12].

Figure 2 Cell concentrations of Chlorella sp. in B1 and B2 experiments

Removal efficiency of CODf

The initial and final concentrations of organic carbon and nutrients are shown in Table 1. In B1 experiment,
filtered chemical oxygen demand (CODf) was reduced from the initial concentration of 1,121±31 mgL-1 to
598±2 mgL-1 after 21 days of cultivation. The COD removal was approximately 46.6%. In the dark
experiment (B2), the similar removal efficiency was observed as the initial COD of 1,369±9 mgL-1 decreased
to 644±3 mgL-1. In order to confirm that the removal was the result of an uptake by algae, not by any

microorganisms, the wastewater was autoclaved before alga inoculation. The result indicates the similar

COD reduction efficiency. Therefore, it can be concluded that the algae are mixotrophic and able to grow

using both CO2 and organic carbon as their carbon sources. The finding of this study conformed to a

previous study [13] which observed a partial COD reduction by algae.

Table 1 Organic and nutrient concentrations in batch experiments of Chlorella sp. cultivation.

Experiments lighting (B1) without lighting (B2)

pH Initial Final Initial Final
CODf (mgL-1)
TKN (mgL-1) 7.31±0.01 8.21±0.04 7.51±0.02 8.14±0.04
NO2- (mgL-1)
NO3- (mgL-1) 1,121±31 598±2 1,369±9 644±3
TP (mgL-1)
TN (mgL-1) 523±5 411±10 756±18 464±8

4.16±0.10 <0.02±0 1.22±0.02 <0.02±0

10.58±0.37 0±0 11.13±0.12 0±0

71.76±1.49 25.44±1.79 95.89±1.55 31.17±2.18

538±5 411±10 768±18 464±8

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Removal efficiency of total nitrogen and total phosphorus
The total nitrogen (TN) removal are shown in Table 1. In B1 experiment, the initial TN of 538±5 mgL-1 was
reduced to reach 411±10 mgL-1. On the other hand, in B2 experiment, the initial TN was reduced from
768±18 mgL-1 to 464±8 mgL-1. The average TN removal efficiency was 23.50±0.26% for B1 and
39.58±1.45% for B2 experiment, as shown in Fig.3. These results are lower than the 41% efficiency reported
by previous study in mixotrophic condition [11]. this is likely because initial total nitrogen concentrations
were high compared to that in the previous studies. However, the actual removal rate of nitrogen was 19.4
mgL-1d-1, no difference values compared to those observed in this study (19.17 mgL-1d-1 in mixotrophic
condition showed in table 2).
Considering the forms of nitrogen removed, the algae were able to consume NO2- and NO3- efficiently.
Their removal was more than 95% for both nutrients as the algae need these nutrients for metabolism and
growth [5]. The total kjedahl nitrogen (TKN), which is the sum of organic- and ammonia- nitrogen, was
removed by the algae. However, the TKN reduction was only in a range of 21 – 39%. It can be seen that the
TKN removal in B2 experiment was significantly higher than that in B1. This result suggests that the TKN
removing mechanism might be governed by some microbial processes other than photosynthesis.

Total phosphorus removal is shown in Table 1. In B1 experiment, the initial TP was 71.76±1.49 mgL-1 and
the final concentration was 25.44±1.79 mgL-1, accounted for 65% reduction efficiency. Similarly, in B2
experiment, the initial TP was reduced from 95.89±1.55 mgL-1 to 31.17±2.18 mgL-1, resulting in 68%
reduction efficiency. This results agree with the TP removal rates reported in literature. It was found that
phosphorus removal by Chlorella pyrenoidosa in mixotrophic condition were 31.0-77.7% [14]. The
microorganisms in the system was able to consume phosphorus as it was essential for biological energy
transfer mechanisms and cell growth [15]. TP presented in wastewater had direct influence on algal
growth [16].

Figure 3 Nutrient Removal of Chlorella sp.in B1 and B2

Growth kinetic and consumption of CO2
It can be seen in Figure 2 that the algae could grow to reach a certain concentration and then leveled off in
case of B1 experiment. On the other hand, the algae concentration in B2 experiment increased to reach its
maximum and then gradually decreased after 15 days of cultivation. This result occurred due to the limited
availability of carbon and nutrient sources in the wastewater. Table 2 shows the overall biomass productivity
which are 310±1.96 mg L-1d -1 in B1 experiment and 220±2.36 mg L-1d -1 in B2 experiment, indicating the
importance of light for the algal growth. Previous studies reported that biomass production is generally in the
range of 0.26-0.7 gL-1d-1 for moderate to high (2-20%) feed gas CO2 concentrations [17].

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The rate of consumption of CO2 in Table 2 suggests that Chlorella sp. under adequate lighting was able to

utilize carbon dioxide better than that without lighting. The CO2 consumption rate found in B1 experiment
was 582±3.68 mgL-1d-1 as shown in Table 2. On the other hand, the rate in B2 experiment was lower
(413±4.43 mgL-1d-1).

Table 2 Growth kinetic and consumption of CO2 and of nutrients removal for Chlorella sp.

Experiments lighting (B1) without lighting (B2)
Specific Growth Rate,µ (d-1) 0.95±0.05 0.41±0.03
Biomass productivity (mg L-1d-1 ) 310±1.96 220±2.36
Consumption rate of CO2 (mg L-1d-1) 582±3.68 413±4.43
TN removal rate (mg L-1d-1) 19.17±1.07 26.06±4.73
TP removal rate (mg L-1d-1) 2.59±0.09 4.40±0.38
23.50±0.26 39.58±1.45
TN removal efficiency (%) 64.6±3.31 67.5±2.29

TP removal efficiency (%)

Conclusion
In this work, Chlorella sp. was able to grow in high-COD wastewater as a growing medium. Its CO2 uptake
rate was high, especially in the condition with adequate lighting. Under no lighting, the algae were able to
grow as well but at a lower growth rate. While obtaining a moderate removal of COD, the culture could
remove nutrients efficiently. In particular, NO2- and NO3- removal were exceptionally high.
The results from this study demonstrate that the CO2-rich off gas from a stripping column in a biogas
upgrading system can be used to enhance the growth of algae in the biogas digester effluent. Not only the
CO2 can be partially captured, but the wastewater can be simultaneously treated.

Acknowledgments
This research was partly supported by the Energy Policy and Planning Office, Ministry of Energy, Thailand
and the Graduate School Chiang Mai University. The authors would like to thank the Energy Research and
Development Institute–Nakornping Chiang Mai University for providing test facilities and technical
supports.

References
[1] Charoensook, R., Knorr, C., Brenig, B., Gatphayak, K. 2013. Thai pigs and cattle production, genetic

diversity of livestock and strategies for preserving animal genetic resources. Maejo Int. J. Sci. Technol,
7:113–132.

[2] Tippayawong, N., Thanompongchart, P. 2010. Biogas quality upgrade by simultaneous removal of CO2
and H2S in a packed column reactor.Energy, 35:4531–4535.

[3] Min, K. J., Reda A. S., Seong, H.K., El, S. S., Sang, H. L., Akhil, N. K., Youn, S. L., Sungwoo, H., and

Byong, H. J. 2013. Cultivation of microalgae species in tertiary municipal wastewater supplemented
with CO2 for nutrient removal and biomass production, Ecological Engineering, 58:142– 148.
[4] Wassa, T., Sirasit, S., and Benjamas, C. 2014. Biocapture of CO2 from biogas by oleaginous microalgae
for improving methane content and simultaneously producing lipid, Bioresource Technology, 17: 90-99.

[5] Ramesh prabu, R., David, D.W.T., and Paris, H.C. 2015. Carbon dioxide fixation of freshwater

microalgae growth on natural water medium, Ecological Engineering, 75:86-92.

[6] Salih, F. M. 2011. Microalgae Tolerance to High Concentrations of Carbon Dioxide: A review.

Environmental Protection. 2: 648-654.

[7] Kajonkiet, T. 2007. Algal Culture Manual. Faculty of Fisheries Technology and Aquatic Resources,

Maejo University, 45 pages.

[8] Nain, E.A., Alejandro, R.M., Yunuen, C.L., 2013. Effect of Nitrogen Content and CO2 Consumption
Rate by Adding Sodium Carbonate in the Lipid Content of Chlorella vulgaris and

Neochlorisoleoabundans, International Journal of Environmental Protection, 3(10):13-19.
[9] APHA-AWWA-WPCF, 1992, Standard Method for the Examination of Water and Wastewater, 18th ed.,

American Public Health Association, Washington D.C USA.

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[10] Lindberg, A., and Rasmuson, A. C. 2006. Selective desorption of carbon dioxide from sewage sludge
for in-situ methane enrichment – part I: pilot-plant experiments, Biotechnology and Bioengineering,
95(5):794-803.

[11] Kim, S., Park, J., Cho, Y.B., Hwang, S.J., 2013. Growth rate, organic carbon and nutrient removal rates
of Chlorella sorokiniana in autotrophic, heterotrophic and mixotrophic conditions, Bioresource
Technology, 144: 8–13.

[12] Bhatnagar, A., Chinnasamy, S., Singh, M., Das, K.C., 2011. Renewable biomass production by
mixotrophic algae in the presence of various carbon sources and wastewaters. Applied Energy,
88:3425–3431.

[13] Romos, T.E.R., Sforza, E., Morandini,M. And Bertucco, A., 2014. Cultivation of Chlorella
protothecoides with Urban Wastewater in Continuous Photobioreactor : Biomass Productivity and
Nutrient Removal, Appl Biochem Biotechnol, 172:1470-1785.

[14] Wang, H., Xiong, H., Hui, Z., Zeng, X., 2012. Mixotrophic cultivation of Chlorella pyrenoidosa with
diluted primary piggery wastewater to produce lipids. Bioresource Technology, 104: 215–220.

[15] Tian, Y.F., Zhi, K.Y., Jian,W., Z., Ying, W. L., Da,W.L., Shanmugaraj,B.M., Wei,D.Y., Jie,S.L., and
Hong,Y.L. 2015. Examination of metabolic responses to phosphorus limitation via proteomic analyses
in the marine diatom Phaeodactylum tricornutum, Published online 2015 May
28. doi: 10.1038/srep10373.

[16] Xin, L., Hu, H.Y., Ke, G., and Sun, Y.X., 2010. Effects of different nitrogen and phosphorus
concentrations on the growth, nutrient uptake, and lipid accumulation of a freshwater microalga
Scenedesmus sp. Bioresource Technology, 101(14):5494-5500.

[17] Simon, J., Leo, J.P.B., Mohamed, S., Yussuf K., and Hussein, Z. 2015. Algal remediation of CO2 and
nutrient discharges: A review. Water Research, 87:356-366.

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Suitable Electric Canal Bus for Bangkok: First Preview

Oravit Hemachudha1* and Chugiat Wichiencharoen2

1*Lecturer, 2Associate Profoessor, Department of Urban Management, Institute of Metropolitan
Development, Navamindradhiraj University, Bangkok 10300, Thailand.
*Phone: 02-164-2636. Fax : 02-164-2636, E-mail: [email protected]

ABSTRACT
In an earlier time, Bangkok was vivisected by khlongs or canals, much like the Italian port and called
“Venice of the Orient (East)”. Today, most canals have been reclaimed, but the few that survive still serve as
a mean of passenger transportation. Plan to extend services to support river boat, bus and rail mass transit
was established and at least 200 qualified boats will be required. The traditional transport vehicle, 60-seated
boat with ordinary one haul bottom, is noisy, generating wave to erode canal bank and inducing air pollution
from diesel engine propeller. This first preview intended to find the available suitable boat to serve as
“Suitable Electric Canal Bus for Bangkok”.
The Delphi Technique (Collective Expert Judgement) was adopted by gathering information of electric boat
from available sources (website, presentations, etc.), then comparing of boats characteristics. After setting
up of scoring criterion, the selected qualified experts scored and ranked on the compliance/adaptability to the
criterion to find the boat of highest score from consensus among them.
After this preview, at a contest, the onboard boat test ride for two piers (round trip about 1,000 m. in Khlong
Phadung Krung Kasem) will be assigned to 40 volunteers to rate the score of each boat in 3 rides at different
boat loading (full, half) and water level/wave conditions. The final evaluation of the suitable boat will be
made which will be in the next research.

Keywords: electric canal bus; Bangkok; canal; khlong; electric boat; suitable boat

INTRODUCTION
In an earlier time, Bangkok was vivisected by khlongs or canals (led to the Chao Phraya River), much like
the Italian port and called “Venice of the Orient (East) [1]” as shown in Figure 1.

Figure 1 Mid-river Port of Bangkok; redrawn from a sketch circa1860 [2]

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Today, most canals have been reclaimed, but the few that survive still serve as a mean of passenger
transportation. Bangkok Metropolitan Administration (BMA) assigned Krungthep Thanakom Co., Ltd. (KT)
to provide canal bus service in Khlong Pasicharoen (R2), Khlong Bangkok Yai (R3), Khlong Saensab(R4)
and Khlong Phadung Krung Kasem (R5) with plan to extend services (R1) to support river boat, bus and rail
mass transit [3] as shown in Figure 2. At least 200 qualified boats will be required.

R1/R2 Khlong Pasicharoen
R3 Khlong Bangkok Yai
R4 Khlong Saensab
R5 Khlong Phadung Krung Kasem

Figure 2 Canal Bus Service Planning

The traditional transport vehicle, 60-seated boat with ordinary one haul bottom, is noisy, generating wave to
erode canal bank and inducing air pollution from diesel engine propeller.
A recent study on Canal Transportation Improvement, Oravit (2016) [4], suggests (from Klong Pasicharoen
boat passenger interview and a seminar) that the 60-seated boat with low wave generated, stable, low noise,
low emission, ventilation fan, personal life saver, CCTV (Closed Circuit Television), GPS (Global
Positioning System) and travelling speed more than 10 kph (5.4 knot). The electric catamaran boat will
fulfill the requirement.

METHODOLOGY
The Delphi Technique (Collective Expert Judgement) was adopted as follows.
1. Gathering information of electric boat from available sources: website, presentations, etc.
2. Comparting of boat characteristics.
3. Scoring criterion setting
4. Selection of qualified experts (graduated in Civil Engineering with experience in the field for more than

10 years) within the Institute of Metropolitan Development, Navamindradhiraj University.
5. Scoring and ranking based on the criterion with compliance/adaptability for each requirement (safety,

cost, performance, public information and service) by each expert.
6. Find the boat of highest score from consensus among them.
After the above preview, at a contest, the onboard boat test ride for two piers (round trip about 1,000 m. in
Klong Phadung Krung Kasem) will be assigned to 40 volunteers to rate the score of each boat in 3 rides at
different boat loading (full, half) and water level/wave conditions. This final evaluation of the suitable boat
will be made in the next research.

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RESULTS AND DISCUSSIONS
Result of the characteristics which was previewed on available 6 electric boats found on websites and leaflets
[5-10] is shown in Table 1.

Table 1 Comparing of Boat Characteristics

Boat No. Characteristics

1 2.6x7.0x1.8 m. Aluminium flat bottom boat

Air Marshal Morakot 3-Infrared Turbine Engine

4 solar panals

7-10 hp. 24 kph. 20 passengers

2 400,000 Baht (no motor)/ 2.0 Mbaht (estimated)
Koh Mak 3.5x7.0 m. Catamaran boat
AC Induction Motor
6x2 sqm. Solar panals
3 hp. 8 kph. 12 passengers

3 1,500,000 Baht
KU Green 2.5x8.5 m. V bottom boat
Induction Motor
6 Solar panals/8x12 v. Battery
8 kph. (estimated) 12 passengers

2.0 Mbaht (estimated)
4 (Taiwan/Ting Hai) 4.5x13 m. Catamaran boat
Love River E-Boat 1 FRP (Fibre Reinforced Plastic)

2x20 kw. Induction Motor
3 kw. Solar Panals
54 Kwh. LFP (Lithium Iron Phosphate) Battery
18 kph. 36 passengers 10.0 Mbaht (estimated)
5 3.2x12.5 m. Modified flat bottom boat
Krungthep Thanakom 2 2x10 kw. Cruise 10.0 RXL Motor
40 hp. 16 kph. 40 passengers

6 5,000,000 Baht
EA Boat Aluminium/Catamaran boat
2x90 kw. Motor
800 kwh. Lithium Ion battery

18 kph. (estimated) 200 parssenger
> 10.0 Mbaht(estimated)

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The ranking criterion from consensus among experts is shown in Table 2.
Table 2 Scoring Criterion

Requirement 5 Scoring Criterion 1
432
None
1.Safety None
None
1.1 Life Saver All + Good All Some Few
1.2 Cruise Assist Yes + Yes Some Few <20/>60
Poor rear Good side Poor side None
1.3 Boarding Good rear loading loading loading
Very
loading 40-49 30-39 20-29 Very
Good Moderate Poor Very
1.4 Maximum Passenger 50-60 eAxtpednrisvievre

1.5 Safety Instruction Excellent Bad
<5
2. Cost Low Moderate High Expensive High V
2.1 Vehicle Low Moderate High Expensive None
2.2 Operating Cost Low Moderate High Expensive
2.3 Maintenance Cost At ponton Bad
2.4 Ticketing On pier On boat At seat Bad
Poor
3. Performance entry 5-9 Bad
3.1 Docking Low V Bad
3.2 Speed (kph.) Excellent Good Moderate Poor side Bad
3.3 Stability loading
3.4 Loading/Unloading >20 15-20 10-14

Catamaran Modified Flat Flat

Good rear Poor rear Good side

loading loading loading

4. Public Information Excellent Good Moderate Poor
4.1 Onboard Excellent Good Moderate Poor
4.2 Enquiries
5. Service Excellent Good Moderate Poor
5.1 Seat Type Excellent Good Moderate Poor
5.2 Cleansing Excellent Good Moderate Poor
5.3 Comfort

The consensus scoring and ranking of the 6 boats is shown in Table 3. The Krungthep Thanakom 2 has the

highest average score (total) of 4.44 while the EA Boat and Love River E-Boat 1 follow at the score of 4.39 and

4.37.

In this first preview, the available information was limited and required some estimation. The final stage of
finding the most suitable boat for canal bus in Bangkok can be obtained by arranging a “Bangkok Electric Boat
Contest”.

CONCLUSION

The first preview of electric boat available has been presented which needs more finding on the boat
passenger attitude to select the most suitable boat for canals bus in Bangkok which will bring back “Venice
of the Orient” to Bangkok again in the near future.

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Table 3 Boat Scoring and Ranking

Requirement Score
123456

1.Safety

1.1 Life Saver 444555

1.2 Cruise Assist 123545

1.3 Boarding 334555

1.4 Maximum passenger 2 1 1 3 4 1

1.5 Safety Instruction 3 3 3 5 5 5

Average Score 2.60 2.60 3.00 4.60 4.60 4.20

2. Cost

2.1 Vehicle 555142

2.2 Operating Cost 554343

2.3 Maintenance Cost 5 5 4 1 3 2

2.4 Ticketing 154545

Average Score 4.00 5.00 4.25 2.50 3.75 3.00

3. Performance

3.1 Docking 434555

3.2 Speed (kph.) 522444

3.3 Stability 251545

3.4 Loading/Unloading 3 2 4 5 5 5

Average Score 3.50 3.00 2.75 4.75 4.50 4.75

4. Public Information

4.1 Onboard 223555

4.2 Enquiries 543555

Average Score 3.50 3.00 3.00 5.00 5.00 5.00

5. Service

5.1 Seat Type 323545

5.2 Cleansing 444555

5.3 Comfort 323545

Average Score 3.33 2.67 3.33 5.00 4.33 5.00

Average Score (Total) 3.39 3.25 3.27 4.37 4.44 4.39

Rank 4 6 5 3 1 2

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REFERENCE
[1] http://www.thailaws.com/download/thailand/veniceofeast.pdf
[2] Mouhot, H., Travels in the Central Parts of Indo-China (Siam), Cambodia, and Laos, During the years

1858, 1859, and 1860, London 1864.
[3] http//www.otp.go.thuploadstiny_uploadsPDF2562-0725620718-05.pdf (in Thai)
[4] Oravit Hemachudha, Development of Bangkok Public Transportation (Phase 1), Proceedings of the

first National Conference of Navamindradhiraj University, Navamindradhiraj University 2018,
pp.140-143(in Thai)
[5] http://www.xn--12cmaam3eno6bybj3a2e7ak2dmhe5b1u9a3ktd.com/?p=371 (in Thai)
[6] http://dasta.or.th/th/aboutus/about-history/about-history/item/3462- (in Thai)
[7] http://www.nationtv.tv/main/content/378555290/.
[8] Ting Hai Co., Ltd., Company Leaflet 2017
[9] https://www.bangkokpost.com/business/tourism-and-transport/1629387/ea-allots-b1-5bn-for-
electrified-boats-cars
[10] https://www.amarintv.com/news-update/news-12973/272363/(in Thai)

9th International Conference on Environmental Engineering, Science and Management
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Assessment of Community Flood Vulnerability Indicators in Pak
Phanang District, Nakhon Si Thammarat Province, Thailand

Chaipol Srituravanich1, Athit Phetrak2, Jenyuk Lohwacharin3, Suthirat Kittipongvises4,
Nutta Taneepanichskul5, and Wandee Sirichokchatchawan6*

1Graduate student, College of Public Health Sciences, Chulalongkorn University, Bangkok 10330, Thailand;
2Lecturer, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand; 3Lecture, Department of

Environment Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand;
4Assistant Professor, Environmental Research Institute, Chulalongkorn University, Bangkok 10330, Thailand;
5Assistant Professor, College of Public Health Sciences, Chulalongkorn University, Bangkok 10330, Thailand;

6*Lecture, College of Public Health Sciences, Chulalongkorn University, Bangkok 10330, Thailand;
*Corresponding author: Tel: 02-2188042 E-mail: [email protected]

ABSTRACT
Objective: To assess community flood vulnerability index using household survey in Pak Phanang

district of Nakhon Si Thammarat province, Thailand. To determine the exposure, susceptibility, resilience
indicators and their components (social, economic, physical and environment) for conducting community
flood vulnerability index in Pak Phanang district of Nakhon Si Thammarat province, Thailand. To estimate
community flood vulnerability index of social, economic, environment and physical components for Pak
Phanang district, Nakhon Si Thammarat province, Thailand. To provide actionable recommendations for
strengthening flood preparedness among the stakeholders.

Methodology: A cross-sectional study was conducted in Pak Phanang district, Nakhon Si Thammarat
province, Thailand. A total of 312 households, previously affected by floods, were sampling by random walk
method and interviewed using a questionnaire developed in this study. The data was analysed and presented
as frequency, percentage, mean and standard variation. Flood vulnerability index was computed using the
following equation: Flood vulnerability index = (Exposure + Susceptibility) – Resilience.

Results: Flood vulnerability index for exposure, susceptibility and resilience were very small
(0.105414, 0.118665, and 0.137337, respectively). Therefore, the overall flood vulnerability index in this
study (0.086742) was also small. It indicated that the studied community had small vulnerability to floods.
Additionally, scores of flood vulnerability index calculated in this study were very small when compared to
previous studies such as Ghana, where scores were high in all indices and categories.

Conclusion: This study determines the flood vulnerability assessment at the community level.
Interestingly, the results showed that resilience score for flood vulnerability index had the highest scores
among the three indicators, namely exposure, susceptible and resilience. Whereas exposure had the lowest
flood vulnerability index. Therefore, building resilience in the community such as populating the land with
diverse species of trees and financing resilience planning for household at risk are recommended.

Keywords : community flood vulnerability; flood vulnerability index; exposure; susceptibility; resilience;
Pak Phanang district

INTRODUCTION
A myriad of global issues contributes to extreme weather conditions in many parts of the world.

Floods are among the most frequent and one of the major disasters, causing devastating damage and
disruption of social communities and loss of human life worldwide. In the past four decades, the world faced
millions of deaths and disastrous economic losses from floods [1]. Under the glossary of the
Intergovernmental Panel on Climate Change (IPCC), flood is defined as “the overflowing of the normal
confines of a stream or other body of water or the accumulation of water over areas that are not normally
submerged. Floods include river (fluvial) floods, flash floods, urban floods, pluvial floods, sewer floods,
coastal floods, and glacial lake outburst floods” [2]. Various types of floods are often classified by the cause
and nature of floods, which also dictate on the degree of impact towards affected communities and
populations [3]. Fluvial flooding and flash flooding are amongst the most common types of floods. Both
fluvial and flash flooding are normally caused by intense rainfalls resulting in the overflow of water onto

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normally dry land. While the former usually occurs over a long period of time, the latter generally happens
within six hours from the onset of raining [4].

Impacts of floods are not include only mortality and morbidity but also damages of agricultural
fields, properties and infrastructures. Moreover, both communities and individuals will suffer the
consequences of floods, which may happen at any period (before, during and after) of the events. These raise
many concerns on well-being and health of those affected by floods. It is worth emphasizing that not all
fatalities, which mostly occur during floods, are caused by drowning. Other health impacts such as
malnutrition, injuries, communicable diseases, vector- and rodent-borne diseases, mental health issues and
chemical poisoning are also important [3]. The impacts of floods are likely to be at a much larger scale in
poorer communities. Therefore, it is crucial to consider the complexity of the impacts and consequences of
floods, especially in the less developed or low resources area [5].

Asia is considered as the most flood-affected area in the world. The region is accounted for almost
fifty percent of flood-related fatalities in the past twenty-five years, especially South Asia and Southeast
Asia, which are among the most flood prone area and where the occurrence of flooding has been severely
increased in the past decades. This may be a consequence of tightly linked together between growing of
population, industrialization, urbanization and environmental degradation [6]. In 2011, nearly 10 million
people encountered flooding in Southeast Asia from an extended monsoon, typhoons and storms, which
lasted from July to September. The scenario has been acknowledged as the worst flood during the past half-
century. More than five million people in Thailand were affected, and more than 800 lives were killed.
Millions of people were forced to move from their home. Overall, the unavoidable of damages and economic
losses from the 2011 flooding is equivalent to almost 47 billion US dollars [7].

To improve safety and well-being, as well as reducing health impacts of communities and
individuals in flood prone areas, government sectors and local authorities are the main stakeholders in flood
management and building of a disaster response strategy. Decrease of vulnerability is the first and foremost
necessity to affirm the achievement of this objective. The first step towards this is to assessing flood
vulnerability in flood-prone area including the affected communities and individuals. The crucial part of
flood vulnerability assessment is to select appropriate indicators for flood vulnerability index (FVI) [8].
There are three factors in FVI, which are exposure, susceptibility and resilience. These three factors make up
the general principle of flood vulnerability as “the extent to which a system is susceptible to floods due to
exposure, a perturbation, in conjunction with its capacity/incapacity to be resilient, to cope, recover or adapt”
by Balica, Douben and Wright (2009) [9]. Since, vulnerability to floods does not only depend on the
location, but also related to culture, lifestyle and characteristics of communities and individuals.
Vulnerability also indicates the severity of health impacts from flood-related illnesses, which can be greatly
different among communities and individuals [10]. Therefore, FVI is also measuring according to four main
components, which are social, economic, physical and environment. It is important to pay attention on the
interaction between these components and the three factors (exposure, susceptibility and resilience), since it
represents the basis of conducting FVI [11]. Hence, the FVI indicators in this study were selected according
to the aforementioned components and factors.

In Thailand, there have been many major flooding events since the year 2011. Even though, many
parts of Thailand suffer from floods every year. The impacts of floods are greatly varied among different
regions and provinces. Nakhon Si Thammarat is a province located in the Southern part of Thailand. It is one
of the prone areas for various extreme weather events including floods and typhoon. The 2016 flooding is
also amongst many devastating examples Nakhon Si Thammarat province has ever experienced.
Communities and individuals were strike by the flood, which affected and killed more than 330,000
households and 91 lives, respectively [12].

Being one of the flood-prone provinces in Thailand, Nakhon Si Thammarat has been facing
devasting negative flood consequences. Despite experiencing many flood-related events in the province,
certain flood-prone districts still face severe damage and economic loss. Additionally, public health and
health impacts from floods are often been undefined and overlooked, especially the impacts before and after
the floods. Therefore, this study aimed to assess community flood vulnerability index using household
survey in Pak Phanang district of Nakhon Si Thammarat province, Thailand. Exposure, susceptibility and
resilience indicators, along with their components (social, economic, physical and environment) were
determined. In addition, the results of this study could serve as actionable recommendations for supporting
and strengthening flood preparedness, flood disaster planning and management among the stakeholders; with
the aim to reducing overall damage and improving safety and well-being of communities.

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METHODOLOGY
A cross-sectional study was conducted in Pak Phanang district, Nakhon Si Thammarat province,

Thailand (Figure1). Among all the household in the community we include a household member aged 18
years old and above who live in Pak Phanang district, Nakhon Si Thammarat province, Thailand and had
previous flood experience. They have to be able to communicate in Thai language. We exclude those who is
unwilling to participate in this study.

Figure 1 Study area
For the sampling technique, Pak Phanang district was purposively selected from Nakhon Si
Thammarat province, Thailand. Both the province and the district were selected since they were flood-prone
areas with history of many flooding events in the past. Later, Laem Talumphuk sub-district was selected as a
flood-prone community in the study. After that, a random walk sampling technique [13] was applied at the
study area for selection of the households. In this study, the primary healthcare center of the district was
selected to be the starting location for a random walk sampling. A total of 312 households, previously
affected by floods, were sampling by random walk method [13] and interviewed using a questionnaire
developed in this study [14, 15]
Data were collected and retrieved from two main sources which were through a structure
questionnaire and secondary data, respectively. There were three main steps for the FVI calculation. Firstly,
the indicators which were reviewed from various studies in order to select the appropriate indicators for this
study. The indicators were selected according to exposure, susceptibility and resilience; along with the
related components as shown in Table 1. The indicators selected in this study were normalized and weighted
before calculating for the FVI. The unequal method by Iyengar and Sudarshan (1982) [16] was applied for
the normalization and weighting of all selected indicators.
Second step was the analysis of the data collected from household surveys using the questionnaire.
The structured questionnaire was developed for collection of data on vulnerability indicators from the
literature reviews. The questionnaire was also developed following the indicators in Table 1. The scale from
1 to 5 was applied in the questionnaire and was directly converted to a score of vulnerability.
Finally, the secondary data from local government and information available online were applied for
some indicators such as land use and population density. The data was analysed and presented as frequency,
percentage, mean and standard variation.
FVI was computed using the following equation:

FVI = (Exposure + Susceptibility) – Resilience [9].

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Table 1 Selected flood vulnerability indicators according to Exposure, Susceptibility, Resilience and
related components.

Social components Exposure Susceptibility Resilience
Population density Past experience Shelters
Economic Population in flood prone area Education Warning system
components Percent of young and elder Preparedness and Awareness Emergency service
Cultural heritage Population with access to sanitation Institutional capacity
Environment Water quality Water supply quality Evacuation routes
component Percent of urbanized area Energy supply Availability of drinking water
Hospitals
Land use (secondary data) Mobility/Health of people Investment in counter measures
Percent of urbanized area Flood protection measures Dams/Storage capacity
Proximity to river Income Flood insurance
Quality of infrastructure Recovery time
Land use (secondary data) Unemployment Past experience
Types of vegetation Regional GDP/ capita Dikes/Levees
Forest change rate Child mortality Recovery time
Percent of urbanized area Environmental concern
Topography (Secondary data) Natural reservations
Heavy rainfall Quality of infrastructure Dams/Storage capacity
Flood duration Child mortality Roads
Reture periods Mobility/Health of people Dikes/Levees
Proximity to river
Physical components Temperature (average yearly)
Flow velocity

RESULTS AND DISCUSSIONS
The total sample comprised of 312 households. The results from the questionnaire found that majority of

the representatives in the households were female (67.6%) while males constituted 32.4%. Almost half were aged
between 40 and 59 years (44.9%). More than two thirds were married (72.8%). Most of the study households
(46.8%) had between 1 to 3 members. Approximately 93% of the study households had monthly income below
15,000baht. In addition, most of the representatives had primary education (64.7%) followed by secondary
education, no formal education and higher education (high school or higher), respectively. It was found that 99%

of the households in this study used collected rainwater as the sources of water for drinking and utilizing during

floods.

Exposure considers the indicators which explain how social entities such as households or economic

activities like agriculture, etc., are exposed to flood events. By considering the composite index of exposure

factor, the FVIexposure is equal to 0.105414 indicating small vulnerability to flood.
Susceptibility considers the indicators which evaluate the sensitivity of an element at risk before and

during a flood event. By considering the composite index of susceptibility factor, the FVIsusceptibility is equal to
0.118665 indicating small vulnerability to flood.

Resilience factor considers indicators which clarify the ability of a Human-Environment system to persist

if exposed to flood by recovering during and after the event. By considering the composite index of resilience

factor, the FVIresilience is equal to 0.137337 indicating small vulnerability to flood.

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The values of the indicators were used in the following general equation of vulnerability to determine the

overall flood vulnerability index. The FVIoverall is equal to 0.086742 indicating small vulnerability to flood.
As shown in Table 2, FVI for exposure, susceptibility and resilience were very small (0.105414,

0.118665, and 0.137337, respectively). Therefore, FVIoverall (0.086742) was also small. These pointed out that the
study communities had small vulnerability to floods. Additionally, FVI scores calculated in this study were very

small when compared to previous studies such as Ghana, where scores were high in all indices and categories
[17]. Nevertheless, there are many methods for assessing the flood vulnerability index. Calculating of FVI will be

most useful if it can be compared with the actual situations in the communities.

Table 2 Community flood vulnerability indicators and flood vulnerability index

Mean Normalized Weight FVI of
value each FVI total
indicator
Exposure Indicator 3.980769 0.745192 0.034853 0.105414
Population in flood prone area 2.073718 0.268429 0.036342
Cultural heritage 1.580128 0.193376 0.06464 0.118665
Water quality 187.33person/km2 0 0 0.086742
Population density 0.078% [Dec2019] 0 0
Percent of young and elder 0.137337
Susceptibility Indicator 2.625 0.40625 0.060856
Past experience 3.804487 0.701122 0.051065
Education 2.102564 0.275641 0.035342
Awareness 1.967949 0.241987 0.031225
Preparedness 3.996795 0.749199 0.033901
Population with access to sanitation 2.503205 0.375801 0.029206
Energy supply 2.891026 0.297009 0.039234
Hospitals 0.070513 0.070513 0.155275
Mobility/Health of people 2.083333 0.270833 0.032394
Flood protection measures 4.849359 0.96234 0.062573
Income 1.384615 0.192308 0.080625
Quality of infrastructure
Resilience Indicator 4.304487 0.173878 0.033171
Shelters 4.064103 0.233974 0.035523
Warning system 4.224359 0.19391 0.039234
Emergency service 2.923077 0.358974 0.044044
Institutional capacity 4.291667 0.177083 0.037943
Evacuation routes 4.025641 0.24359 0.033791
Availability of drinking water 2.810897 0.547276 0.028765
Recovery time

CONCLUSION
This study has presented the flood vulnerability assessment at the community level. By selecting the

indicators under four vulnerability related components, the computed scores of the vulnerability indicators in
the community has allowed a classification of vulnerability scale for all four FVI (exposure, susceptibility,
resilience and overall). Interestingly, we found that FVIresilience had the highest scores among the three.
Whereas exposure had the lowest FVI. Therefore, building resilience in the community such as populating
the land with diverse species of trees and financing resilience planning for household at risk are
recommended.

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ACKNOWLEDGEMENT
This work is supported by the Thailand Science Research and Innovation (TSRI), project number

SRI6230303.

REFERENCE
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Climate and Water Extremes.
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[7] Haraguchi, M., and Lall, U. 2015. Flood risks and impacts: A case study of Thailand’s floods in 2011
and research questions for supply chain decision making. International Journal of Disaster Risk
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[8] De Moel, H., Asselman, N.E.M. and Aerts, J.C.J.H. 2012. Uncertainty and sensitivity analysis of
coastal flood damage estimates in the west of the Netherlands. Natural Hazards and Earth system
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[9] Balica, S. F., Douben, N., and Wright, N. G. 2009. Flood vulnerability indices at varying spatial
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[11] Balica, S. F. 2007. Development and application of flood vulnerability indices for various spatial
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P. T. 2015. Community vulnerability assessment index for flood prone savannah agro-ecological zone:
A case study of West District, Ghana. Weather and Climate Extremes. 10: 56-69.

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GIS-Assisted Assessment of Surface Water Quality at Moeyungyi
Wetland in Myanmar

Aye N. Thu1* Ranjna Jindal2 Nawatch Surinkul3 and Romanee Thongdara4

1*Masters Student; 2Visiting Professor; 3Assistant Professor and 4Assistant Professor, International Masters and
PhD Programs in Environmental and Water Resources Engineering, Department of Civil and Environmental

Engineering, Faculty of Engineering, Mahidol University, Phutthamonthon Nakhon Pathom, 73170
Thailand; *Phone : 0620129313, Fax : (66) 2 889 2138 Ext. 6386, E-mail : [email protected]

ABSTRACT
The aim of this study was to assess the surface water quality at Moeyungyi Wetland (MW) in Myanmar and
provide the ideas for the wetland water quality enhancement due to the water supply for drinking and
domestic usages to the local communities. For that purpose, surface water sampling was conducted in two
separate events: during the month of October, 2019 (rainy season), and January, 2020 (dry season),
collecting samples from ten selected locations in the MW. pH, temperature, dissolved oxygen (DO),
electrical conductivity (EC) and turbidity in the water samples were measured using the water quality
checker-Horiba. A digital depth sounder was used to determine the water depth. Biological oxygen demand
(BOD5), iron, nitrate and phosphate in the water samples were determined at the laboratory. Ordinary
Kriging (OK) Interpolation via ArcGIS 10.4 was used to mapping the selected water quality parameters for
analyzing the distribution patterns. Euclidean Distance via ArcGIS 10.4 was applied to assess the distances
between the wetland boundary and land use conditions around the wetland including agricultural area,
livestock grazing area, villages, resort area and factory area (quarry mill). After having the distance
evaluation thematic layers, Weighted Overlay Analysis (WOA) via ArcGIS 10.4 was used to calculate the
weightages of thematic layers to have a wetland water quality map in the study area. The results indicated
that the water in the MW was polluted throughout the year with the high levels of turbidity, BOD5 and iron;
low values of pH throughout the wetland and low concentration of DO at some locations during two seasons.
Moreover, the result from WOA showed that land use conditions around the wetland could create the threat
to the wetland water quality. Therefore, the authors recommended that the wastewater from multiple sources
of contamination should be treated before being drained into the MW.

Keywords: Surface Water Quality Assessment; Moeyungyi Wetland; GIS; Ordinary Kriging (OK);
Euclidean Distance; Weighted Overlay Analysis (WOA)

INTRODUCTION
Wetlands are important natural resources in Myanmar [1]. Based on the survey of 99 wetlands in Myanmar,
55 sites are important bird sanctuaries and biodiversity areas (IBAs). Out of these, 35 sites are qualified to be
RAMSAR sites [2]. Among them, Indawgyi, Inle and Moeyungyi wetlands are famous wetlands as well as
Bird Areas in Myanmar [1]. During the RAMSAR convention in 1971, the conservation and wise sustainable
use of wetlands and their resources was taken into consideration [3]. In this study, Moeyungyi wetland
(MW) was selected as it is one of the most important wetland habitats in Myanmar. It provides the huge
amount of water for the agro-irrigation during the summer paddy cultivation. The use of chemical fertilizers
and pesticides for the crops is a serious threat for the water quality in the MW. Moreover, although one of
the functions of wetlands is to improve the water quality [4], the water quality of the MW is being threatened
because of the land encroachment by paddy fields and livestock grazing; use of chemical fertilizers;
pesticides and herbicides for agriculture; water over use and the threat from surrounding land use conditions.
This has caused the challenging problem in the study area such as increased water demand and wastewater
volumes to be handled [5]. There are many advantages as well as risks of water-related health problems from
wetlands because the wetlands not only serve as water supply source but also waste disposal systems. When
over- burdened with these roles, they can become degraded causing worsening health problems and
negatively affecting the livelihoods of communities [6]. Hence, the assessment of surface water quality in the
MW is needed to be conducted. The primary objective of this study was to assess the surface water quality in
the MW and to compare with water quality standards as well as investigating the spatial distribution of
selected water quality parameters using OK interpolation method. In addition, based on land use conditions

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surrounding the wetland, Euclidean Distance and Weighted Overlay Analysis were applied to calculate the
weightages of distance evaluation thematic layers to have a wetland water quality map in the study area.

METHODOLOGY
Study Area
Moeyungyi Wetland, with a total area of 10,359 hectares, is located in the southern part of Bago Region in
Myanmar. Bago region is divided into two parts: Bago (east) and Bago (west). In the Bago eastern region,
there are 14 townships including Bago Township. MW is situated in Bago Township, Bago Region at the
coordinates of Latitude 17˚ 32΄ 57˝N and Longitude 096˚ 36΄ 58˝E [5] as shown in Figure 1.

Figure 1 Study Area
MW is divided into different zones including core zones, transition zones and wise use zones as shown in
Figure 1. The core zones (red color) are the protected areas in the wetland. The transition zones (yellow
color) serve to provide sustainable livelihoods through fishing, livestock grazing, etc. The wise use zones
(green color), are the outer areas where people live and work, using the natural resources of the area in a
sustainable manner [7]. Bago River is one of the major sources of water to the MW [8]. There are three other
major inflows to MW including Pyinpon (River), Weipein and Payakalay Streams. Major outflows from the
wetland are Zwebat and Kapin Streams through sluice gates at the east of the wetland [9]. There are 17
villages around MW with a total population of about 50,000 that depend on the wetland resources for their
livelihoods. The communities around the MW can use the water not only directly but also indirectly from the
wetland mainly for agriculture and livestock breeding as well as for drinking and home consumption [5].
Surface Water Sampling
The location of the 10 selected sampling points (represented as point1 – point 10) in the area of interest is
shown in Figure 1. The points were chosen to determine the surface water quality including in inflows
(western side of wetland), open water area (middle of wetland) and the outflow (eastern side of wetland).
Surface water samples were collected in two events: during the month of October, 2019 (rainy season), and
January, 2020 (dry season) using cleaned polyethylene bottles and transported to the laboratory for analyses.
Analytical Methods
On-site measurement of physico-chemical parameters including pH, temperature, DO, EC and turbidity in
the surface water was done using the water quality checker-Horiba (U-50-Horiba). A high frequency digital
depth sounder (Hondex PS7) was used to determine the water depth. Surface water samples were transported
to the laboratory for chemical analyses following APHA standard methods for BOD5, iron, nitrate and
phosphate determinations [10].
Ordinary Kriging (OK) Interpolation Method using GIS: Ordinary Kriging (OK) interpolation was used to
obtain the spatial distribution of selected water parameters to assess which were exceeding the standards.
Euclidean Distance and Weighted Overlay Analysis (WOA) using GIS: Euclidean Distance was used to
obtain the distances between the wetland boundary and land use conditions around MW including

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agricultural and livestock grazing area, villages, resort and factory area (quarry mill). An output wetland
quality map was produced by calculating the weightages of distance evaluation thematic layers in WOA in
ArcGIS 10.4.

RESULTS AND DISCUSSION
Comparison of MW Surface Water Quality with Standards
Drinking water and surface water quality standards are not published in Myanmar. Hence, the mean values
of the selected physical and chemical parameters in surface water samples from the MW were compared
with surface water quality standards in India [11] as well as with the WHO drinking water standards [12]
because of the use of wetland water by local communities around MW for drinking and domestic purposes.
The mean values of surface water parameters investigated in two sampling events are presented in Table 1.
Table 1 Mean Values of Physico-chemical Parameters in Moeyungyi Wetland Surface Water during

First Sampling Event (October, 2019) and Second Sampling Event (January, 2020)

Variables Mean Value Mean Value WHO Standards India’s Surface
(October, 2019 (January, 2020 2017
(Rainy Season) (Dry Season) Water Standards
Class-Ab*

pH 5.4 5.8 6.5-8.5 6.5-8.5

Temperature (°C) 33 27.1 25 -

Turbidity (NTU) 35 147 4 -
EC (μS/cm) 20 130 - -

Depth (m) 1.56 1.17 - -
DO (mg/L) 4.4 6.75 - ≥6
BOD5 (mg/L) 9.6 4.2 - ≤2
Iron (mg/L) 1.7 2.8 0.3
-

Nitrate (mg/L) 1.2 0.05 50 -

Phosphate (mg/L) 1.16 0.53 - -

b* “Class A – drinking water source without conventional treatment but after disinfection”

Based on the results from Table 1, the average surface water pH in MW in the first sampling (rainy season)

and second sampling (dry season) were 5.4 and 5.8, respectively and below the lower limit defined by WHO
drinking water standards and India‟s surface water standards for Class A (6.5-8.5). Thus, the water in the

wetland was acidic in both seasons due to the discharge of untreated wastewater, which is loaded with a large

amount of organic acids from the urban and rural activities. The pH measurement is one the most important

tests used in water chemistry because it affects the solubility and availability of nutrients [13] and [14].

Water temperature is an important indicator to assess the water quality since it directly influences the amount

of DO that is available to aquatic organisms [15] and [13]. The mean values of water temperature in MW in

two seasons were 33 °C and 27.1 °C, respectively and higher than the WHO standard of 25 °C.

The turbidity level is the indicator to assess the clarity of the water and measures the amount of suspended

particles in the wetland [16]. The mean turbidity levels in the wetland in two seasons were 35 NTU and 147

NTU, respectively and quite high as compared with the standard limit (4 NTU) of WHO. Similar turbidity

levels were reported at Inle Lake in Myanmar in a study that also revealed that the turbidity level was higher

in the dry season than in the rainy season [17]. High turbidity level in the MW could be due to the organic or

inorganic constituents from the urban and rural activities. EC is an estimate of the total amount of dissolved
ions in the water [18]. The mean EC values in MW in two seasons were 20 μS/cm and 130 μS/cm,

respectively. Similarly high EC values were observed in a study in Buriganga River in Bangladesh in the dry

season [18]. The mean water depths in the MW in two seasons were 1.56 m and 1.17 m, respectively. The

mean water depth in the dry season was relatively shallower than in the rainy season due to the water

distribution for the summer paddy fields in the wetland [5]. DO is an indicator of organic pollution [19].

Sufficient DO in the water is very important to aquatic life for respiration [20] and [14]. The mean values of DO
in both seasons were 4.4 mg/L and 6.7 mg/L, respectively and slightly below the permissible limit of India‟s
surface water standards class-A, ≥6 mg/L in the rainy season. Low DO could be due to high amount of

biodegradable organic wastes including livestock wastes dumped into the wetland with the water flow and

extensive use of fertilizer in agricultural lands leading to the excessive growth of algae which could reduce

DO in the wetland. BOD is an important parameter to indicate the organic load in the water body. The mean

values of BOD5 in MW observed in two seasons were 9.6 mg/L and 4.2 mg/L, respectively, exceeding the

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permissible limit (≤2 mg/L) of India‟s surface water standards class-A. Thus, there is chemical pollution and
requires biological treatment [19]. High values of BOD5 and turbidity, and low DO levels were also observed
in Sukhna Lake in India during the rainy season [21]. The results indicated that MW water was substantially
contaminated in rainy season. This could be due to the discharge of effluents from the factory (quarry mill)
and untreated wastewater from the urban and rural activities with the water flow into the wetland.
Excess iron in water is the result from industrial effluents [22]. Iron concentrations in MW water in two
seasons appeared to be very high. The mean iron concentrations recorded in two seasons, 1.7 mg/L and 2.8
mg/L were much higher than WHO standards of 0.3 mg/L. As shown in Table 1, the mean nitrate
concentrations in two seasons were 1.2 mg/L and 0.53 mg/L, respectively, meeting the WHO standards, 50
mg/L, respectively. The mean phosphate concentrations in two seasons were 1.16 mg/L and 0.05 mg/L,
respectively. The villagers around the MW are engaged in the agro-irrigation using chemical fertilizers and
pesticides containing nitrate and phosphate not only in the rainy season but also in the dry season [5].
Distribution of Selected Water Quality Parameters in MW using GIS
The concentrations of pH, turbidity, DO, BOD5 and iron in Moeyungyi Wetland Surface Water during First
Sampling Event (October, 2019) and Second Sampling Event (January, 2020) are tabulated in Table 2.
Table 2 Concentrations of Selected Surface Water Quality Parameters at Various Locations in

Moeyungyi Wetland Surface Water during Two Sampling Events (Rainy and Dry) Seasons

Variables Point Point Point Point Point Point Point Point Point Point
1 2 3 4 5 6 7 8 9 10

pH Rainy 6.04 5.29 4.69 4.91 5.06 5.55 6.01 5.91 6.04 4.37
Dry 6.2 6.64 5.26 4.93 5.71 5.99 6.08 6.79 6.66 4.22

Turbidity Rainy 13.1 51.5 36.8 39.2 47.8 36.9 30.7 38.7 30.2 21.9
Dry 70.3 230 82 102 217 226 96.1 142 169 135

BOD5 Rainy 10 12 10 8 8 8 10 10 12 8
Dry 4 4 2 4 6 64444

DO Rainy 5.67 3.57 2.76 5.13 5.06 3.62 5.66 5.79 4.61 3.57
Dry 8.3 4.89 4.8 6.62 7.82 6.32 7.66 8.06 7.9 5.12

Iron Rainy 1.17 3.2 1.6 1.36 1.34 1.6 1.56 1.7 1.82 1.1
Dry 1.77 3.18 1.12 3.3 3.8 4.8 1.78 3.1 2.2 3.1

Based on the results shown in Table 2, Ordinary Kriging interpolation method was applied for mapping the

selected surface water quality parameters for analyzing the distribution patterns. The spatial distribution

maps of surface water variables (pH, turbidity, DO, BOD5 and iron) are illustrated in Figure 2.

(Rainy) (Dry)
pH pH

(Rainy) (Dry)

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(Rainy)

(Rainy) (Dry)

(Rainy) (Dry)

Figure2 The Spatial Distribution of Surface Water Quality Parameters (pH, Turbidity, DO, BOD5
and Fe) in Moeyungyi Wetland during Rainy Season and Dry Season using OK Interpolation

Based on Figure 2, the spatial distribution of pH in the wetland water tended to decrease from west (water
entering side from the urban area) to the east of the MW (water outlet or downstream area) during the rainy
and dry seasons. It can be said that the decreased pH was found in the downstream area during two seasons
due to the deposition of acid from rain and the discharge of untreated wastewater containing a large amount
of organic acids from the rural activities. Low pH can affect the wetland environment. The spatial variation
analysis result of turbidity suggested that the turbidity level at all locations in the MW appeared similarly
distributed throughout the wetland. From this observation, it can be said that the wetland water is very poor
with high turbidity level throughout the year. High turbidity level due to the organic or inorganic constituents
from the urban and rural activities can affect the wetland environment.
Spatial variation analysis result of DO in two seasons showed that the concentrations of DO around the
locations in the northern side of the wetland were observed very poor. This is because of the high amount of
biodegradable organic wastes including livestock wastes dumped entering into the wetland and the excessive
algae growth in the wetland by using the extensive fertilizer from the agricultural land. DO concentrations in
the middle of the wetland were appeared well DO in two seasons. The DO result can be suggested that DO
values decreased in the wetland near the land use patterns including resort, grazing land and agricultural
land; increased in the wetland area, which represented the open water during two seasons.
During the rainy season, the distribution of BOD5 and iron tended to decrease from western side to the
eastern side of the wetland. This is due to the the discharge of effluents from the factory (quarry mill) and
untreated wastewater from the urban and rural activities with the water flow into the wetland. In the dry
season, the BOD5 and iron concentrations were increased in the downstream area. This result may be due to

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the deposition of BOD5 and iron concentrations from the rainy season in the MW. The spatial variation
analysis result of iron was nearly the same with the spatial variation result of BOD5 in two seasons.
Evaluation of Wetland Water Quality using GIS
Euclidean Distance: Water quality degradation from multiple sources of contamination has become a
critical global issue. Therefore, evaluation of the distances between the sources of contamination and the
wetland boundary was very important in assessing the water quality of MW. The distance evaluation maps of
agricultural area, livestock area, villages, resort area and factory area (quarry mill) from the wetland
boundary by using Euclidean Distance Tool are illustrated in Figure 3.

Figure 3 Distance Evaluation Maps of Land Use Pattern in and around Moeyungyi Wetland
Based on Figure 3, the agricultural lands are located within and surrounding the MW. Therefore, the distance
between the agricultural area and the MW became the most important criteria to evaluate the wetland quality.
Degradation of wetland could occur at MW through water diversions, irrigation and changed land use
towards agricultural lands. Land encroachment for cultivation is one of the serious threats for the sustenance
of the MW [5]. Grazing livestock in the MW can lead to potentially significant negative outcomes, increased
water turbidity, damage to aquatic habitats and soil structure problem etc. It was found that the raising of
livestock is a problem for the deterioration of the water quality of the wetland by the faeces of the
animals [5]. Most of the villages around the MW engaged with livestock grazing depending on the wetland.
Therefore, evaluating the distance between the livestock area and the MW was important to assess the
wetland quality. Most of the villages are located within 1000m from the wetland. Therefore, domestic
wastewater can affect the wetland water quality. Thus, the distance between the villages and the wetland
became the important criteria in evaluating the wetland water quality.
Wastes from the resort such as liquid waste and used oils should not be disposed into the streams and rivers
directly: the wastes should be treated such that it is in line with the „Ministry of Industry Effluent Standards‟
before disposed of at water courses and proper waste management plans to be developed [5]. According to
the reference, evaluating the distance between the resort area and the wetland was considered as an important
criterion as the resort is located in the upstream area. Effluents from the quarry mill (factory) can be a serious
threat to become water pollution in the MW. The factory is located in the west of the wetland. Therefore, the
effluents from the mill can flow directly into the wetland through the streams. Thus, the distance between the
mill and the wetland became the important criteria to evaluate the wetland water quality.

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Weighted Overlay Analysis: To identify the wetland water quality, the distance evaluation thematic layers of
land use pattern were used to overlay each other using WOA. The rank assigning from 1 to 5 for each
individual criteria was done based on their distances and weight was assigned for the influences and effects
of different land use criteria to identify the wetland area with the best water quality. The final score of a
theme was equal to the product of the rank and weightage. Ranking and weighting based on the distances of
land use criteria from the wetland are tabulated in Table 3.

Table 3 Ranking and Weighting the
Distances of Land Use Criteria
around Moeyungyi Wetland

Figure 4 Evaluation of Moeyungyi Wetland Water
Quality by Weighted Overlay Analysis

An output wetland water quality map was produced by calculating weightages of land use conditions based
on the distances from the wetland boundary as shown in Figure 4. It pointed out that approximately (22.13%)
of the wetland area in the middle of MW, far from the land use conditions, had the good water quality. The
rest of about (77.87%) of the MW area, near the land use conditions had the poor water quality.

CONCLUSIONS
The mean values of surface water quality parameters in the rainy season including pH, temperature, turbidity, EC,
depth, DO, BOD5, iron, nitrate and phosphate were found to be 5.4, 33 ֯C, 35 NTU, 20 μS/cm, 1.56 m, 4.4mg/L,
9.6 mg/L, 1.7 mg/L, 1.2 mg/L and 1.16 mg/L, respectively. On the other hand, 5.8, 27.1 ֯C, 147 NTU, 130
μS/cm, 1.17 m, 6.75 mg/L, 4.2 mg/L, 2.8 mg/L, 0.05 mg/L and 0.53 mg/L were recorded in the dry season.
Based on the water quality analysis results, the water quality of MW was declined with high levels of water
temperature, turbidity, BOD5 and iron; low values of pH through the year when compared with the water quality
standards. Moreover, low concentration of DO was observed in the wetland during the rainy season. Furthermore,
based on the results of spatial distribution by Ordinary Kriging interpolation, it can be said that the water quality
of the wetland was polluted mainly in the wetland area near the land use conditions. During Weighted Overlay
Analysis based on the distance evaluations of land use conditions from the wetland boundary, the results indicated
that most of the wetland area of approximately 8,067 hectares of the total wetland area of 10,359 hectares in the
MW was polluted and the rest of about 2292 hectares in the MW had the good water quality.
According to the results, it can be said that the water from Moeyungyi Wetland is not suitable for drinking
purpose not only in the rainy season but also in the dry season. For the sustainable consumption of wetland water,
wastewater from urban and rural area must be treated before being drained into the wetland. In addition, the
authorized person should provide the social awareness trainings about the importance of conservation and
sustainable use of water resources in urban and rural areas around the wetland. Regular assessing and monitoring
of surface water quality in Moeyungyi Wetland is important to keep the water sustainability.

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ACKNOWLEDGEMENTS
The authors would like to acknowledge Norwegian Government for providing scholarships for Myanmar
(CBIM-2) with the financial support for this research. Nature and Wildlife Conservation Division of Forest
Department, Myanmar and E Guard Environmental Services, Myanmar are also acknowledged for their great
support during the data collection for this research.

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by Using GIS and a Heavy Metal Pollution Index (HPI) Model in a Coal Mining Area, India.

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Investigation of Nutrients Concentrations Distribution in
Moeyungyi Wetland in Myanmar using Geographic Information

Systems

Zin K.K. Oo1*, Ranjna Jindal2, Romanee Thongdara3 and Nawatch Surinkul4

1*Masters student, 2Visiting Professor, 3Assistant Professor,, 4Assistant Professor, International Masters and
PhD Programs in Environmental and Water Resources Engineering, Department of Civil and Environmental

Engineering, Faculty of Engineering, Mahidol University, Phutthamonthon Nakhonpathom, Thailand;
*Phone: 0982931650, Fax : (66) 2 889 2138 Ext. 6386, E-mail: [email protected]

ABSTRACT
Nutrients enter the lakes, wetlands and any similar water bodies from various human activities that are
reflected in their water quality. Some amounts of nutrients are required for the health of the water bodies‟
ecosystems. However, too much nutrients in a water body may cause the problems of eutrophication and
dissolved oxygen (DO) depletion. Moeyungyi Wetland is not only a wetland wildlife sanctuary in Myanmar
but also an Important Bird Area (IBA) in Asia. This study is aimed at investigating the distribution of
nutrients concentrations in the Moeyungyi Wetland with the focus to find the hotspot areas of the wetland
and its trophic states because no such study has been conducted to investigate the nutrients levels of the
wetland yet. Investigations were carried out in the first sampling event on October 2019 at 15 sampling
points distributed throughout the wetland to determine the concentrations of Dissolved Oxygen (DO),
Chemical Oxygen Demand (COD), Total Phosphorus (TP), Chlorophyll-a (Chl-a) and Secchi Depth (SD).
Based on the results, the average values of DO, COD, TP, Chl-a and SD were found to be 4.77 mg/L, 15.92
mg/L, 19.80 µg/L, 15.97 µg/L and 0.49 m respectively. The trophic state index (TSI) in the wetland ranged
from 43.9 to 68.5. Therefore, the results indicated that many areas of the wetland have eutrophic conditions
with extensive macrophyte problem while some areas have mesotrophic conditions with moderately clear
water. The distribution of the parameters in the wetland were also plotted by using GIS through Ordinary
Kringing interpolation technique. Based on the distribution plots, the concentrations of the investigated
parameters in general decreased along the water flow from west (entering points, resort area and agricultural
fields) to the east of the wetland (flash out point). This trend is similar to some other wetlands as reported in
the literature reviews.

Keywords: Nutrients, Wetlands, Eutrophication, DO Depletion, Spatial Interpolation, Trophic States

INTRODUCTION
Nutrients enter the lakes, wetlands and any similar water bodies from various human activities that are
reflected in their water quality. Some amounts of nutrients are required in a water body for its ecosystem to
be healthy but too much nutrients may cause the problems of excessive plants and algal growth
(eutrophication) and dissolved oxygen (DO) depletion. A water body may have eutrophication naturally but
that would take over a hundred years. However, human activities such as releasing agricultural runoffs and
domestic as well as industrial effluents into the nearby water bodies can accelerate the process of
eutrophication [1]. Eutrophication mainly occurs when a water body is receiving the excess nutrients [2].
Trophic State Index (TSI) is a classification system designed to rate water bodies based on the amount of
biological activity they sustain. Trophic states of a water body are based on its fertility which depends upon
the amount of nutrients in it [3]. Generally, trophic state index (TSI) of a water body can be classified into
four classes: (1) oligotrophic, (2) mesotrophic, (3) eutrophic and (4) hyper-eutrophic [4].
A wetland is a land area which is wet, permanently or seasonally. Wetlands have plants and so act as the
„living filter‟ and usually improve the quality of the water that passes through them [5]. Due to their water
purifying capacity, wetlands have become an alternative natural treatment option to treat wastewaters
especially from diffused sources, e.g., agricultural runoff with high nutrients that may cause eutrophication
in the receiving water bodies [1]. Wetlands play an important role in ecosystem services all around the
world 2004 [6]. Wetlands provide various kinds of useful products and services, not only to the
communities living nearby its periphery but also to the people living outside of its vicinity area and are
contributing the wellbeing of human and poverty alleviation. The products provided by the wetland are

9th International Conference on Environmental Engineering, Science and Management
The Heritage Chiang Rai, Thailand, May 27-29, 2020