Development of Emissions Inventory for Inland Water ...

Development of Emissions Inventory for Inland Water

Transport in Bangkok, Thailand

Final Report

Submitted to:

Climate and Clean Air Coalition

& Thailand Pollution Control Department

Submitted by:

Dr. Ekbordin Winijkul Environmental Engineering and Management

Asian Institute of Technology (AIT)

31st August 2020

Table of Content

PROJECT OVERVIEW AND KEY FINDINGS 1

CHAPTER 1

1.1

1.2

1.3

INTRODUCTION

Background

Objectives

Scope of the project

3

3

3

4

CHAPTER 2

2.1

2.2

2.3

2.4

2.5

2.6

2.7

2.8

METHODOLOGY

Framework of methodology

Data collection

Emission estimation

Emission estimation of all boat groups

Excel calculation tool for inland water transport emission

Emission comparison

Emission impact area from inland water transport

Emission reduction policy recommendations

5

5

7

9

14

15

16

16

16

CHAPTER 3

3.1

3.2

SUMMARY OF ACTIVITY DATA AND EMISSION

FACTORS

Activity data

Emission factors

18

18

22

CHAPTER 4

4.1

4.2

4.3

4.4

4.5

4.6

EMISSION INVENTORY RESULTS

Emission inventory results

Emission comparison

Spatial and temporal distribution of emission

Inland water transport emission impact area

Excel emission calculation template for inland water transport

Emission control strategies

24

24

36

38

44

45

46

CHAPTER 5

5.1

5.2

5.3

SUMMARY AND LIMITATIONS

Summary

Recommendations for citizen and boat operator

Limitations in emission estimation

49

49

50

50

REFERENCES

51

APPENDICES

Appendix 1

Appendix 2

Appendix 3

Survey of boat trips and information of each boat group

Emission share of different boat types

Spatial distribution of emission

53

53

66

73

1

PROJECT OVERVIEW AND KEY FINDINGS

The project “Development of emission inventory for inland water transport in Bangkok,

Thailand” aims at estimating emission for inland water transport in Bangkok, focusing on

public boats in Chao Phraya river and Saen Seap canal, and provides recommendation on

the policies to reduce emission from inland water transport in Bangkok. The EI results in

2019 were developed in this study to provide the information to Thailand Pollution Control

Department (PCD) to prepare the management plan for reducing emission from inland water

transport in Bangkok. This project was supported by the Climate and Clean Air Coalition’s

(CCAC) Solutions Center and the United Nation Environment Programme (UNEP). The

project period is October 2019 – August 2020. The team started the preliminary survey in

October 2019 and conducted the main survey during January to May 2020. The emission

inventory template and progress report were submitted to CCAC and PCD in December

2019 and May 2020, respectively. The final MS Excel emission calculation template is

transferred to PCD and CCAC together with this final report. This final report presents the

EI results for inland water transport in Bangkok and policy recommendations to reduce

emission from this sector.

The project collected activity data such as engine load factor, travelling distance, boat trips,

number of passengers, operating time during cruising and idling. The emission factors were

calculated based on NONROAD model methodology proposed by the United States

Environmental Protection Agency which incorporated the effects of engine size, age, load

factor and sulfur content in fuel. Idling emission factors were also estimated to capture

emission from boats while idling during embarking and waiting for passengers at the pier.

Seven categories with thirteen routes of Chao Phraya boats (Green flag, Orange flag, Yellow

flag, No flag, Gold flag, Blue flag and Shuttle boats), two routes of Saen Saep boats and

twenty three routes of cross river ferries were included in this study. The inventory covered

thirteen pollutants, including Hydrocarbon (HC), Carbon Monoxide (CO), Oxides of

Nitrogen (NOx), Non-methane Hydrocarbon (NMHC), Methane (CH4), Ammonia (NH3),

Nitrous Oxide (N2O), Carbon Dioxide (CO2), Sulfur Dioxide (SO2), Particulate Matter

(PM10 and PM2.5), Black Carbon (BC) and Organic Carbon (OC). Then, the emission

reduction policies were proposed to reduce emission from inland water transport.

Key findings of the project are summarized below:

In term of PM2.5, BC, and CO2, emissions from public inland water transports in 2019 were

12.1, 6.1, and 19,011 tons/year, respectively. These emissions were equivalent to the

emission of only 380 in-used buses while the total number of in-used buses in Bangkok were

estimated to be 14,148 in 2019. When considering emission per passenger, the emission per

passenger of inland water boats was 0.006 g/km-passenger which was almost the same as

the emission per passenger of buses and vans. However, when comparing the emission per

passenger with the emission from buses with different standards, this emission of inland

water boats was the same level of the emission of Euro 2 buses while the majority (about

36%) of the bus in Bangkok are Euro 3. As such, inland water boats emit more PM2.5 per

passenger per kilometer than the majority of buses in Bangkok.

The PM2.5 emission was spatially distributed in the study area, and the emission was used as

inputs to run the dispersion model with the meteorological data in 2015. The results showed

that the emission from inland water boats could contribute to a maximum of 1-4 μg m3⁄ of

24-hr average PM2.5 concentration in the distance of one kilometer away from the river or

2

canal, contributing significantly to the PM2.5 concentration and people lives along the river

and canal, and passengers taking boats for daily commute. People living along the San Seap

canal and the Chao Phraya river, especially the area close to the busy piers, should wear

mask or use air purifier in the houses during rush hours. Similarly, boat passengers should

wear mask at the piers and on the boats to reduce personal exposure to the pollutant.

Switching boat engines to Tier 4/Euro 6 with 10 ppm sulfur fuel could reduce 98% of PM2.5

emission from the current situation. Using 10 ppm sulfur fuel with the existing engines

would only reduce PM2.5 emissions by 5% from the current situation. Thus, the best policy

recommendation for PM2.5 emission reduction from boats are promoting the use of 10 ppm

sulfur and switching to Tier 4/Euro 6 engines. Use of electric motors will bring tail-pipe

emissions to zero and can significantly reduce air pollution along the river and canals. Other

recommendations include limiting the age of engines, and reducing idling through better

operations in stations and route planning. The researchers also acknowledge the potential of

inland waterways to help decongest traffic congestion in Bangkok. Expansion and

improvement of inland passenger transport could lead overall reduction of air pollution in

the city, while providing better mobility to its citizens.

This project also developed an MS Excel emission calculation template for inland water

transport which can be used to assess the emission of inland water transport for other cities.

Many major cities in Southeast Asia, and the world, are in major rivers and canals connecting

to the coast. While many inland waterways are used for freight, not many cities are looking

at passenger transport. Bangkok provides a good example in connecting road and waterway

public transport. Inland waterways have the potential to alleviate road traffic and reduce

overall emission from transport.

3

CHAPTER 1

INTRODUCTION

1.1 Background

Every year during November to March, Thailand has been facing with the problem of high

Particulate Matter with diameter less than or equal to 2.5 μm (PM2.5) concentrations in the

Bangkok Metropolitan Region or BMR. The high level of PM2.5 causes adverse effects to

people health and affect economy of Thailand, e.g. affect tourism. Thailand Pollution

Control Department (PCD) with other organizations has urged people to aware of the

problem and protect themselves during the high PM2.5 episodes. PCD also uses air quality

management tools which are emission inventory, air quality monitoring and air quality

modeling to manage air quality during the episode. However, the emission inventory which

is one of the important components in air quality management does not up-to-date and cover

all the sources in Bangkok.

Previous studies suggested that three categories of emission sources; traffic, open burning

and secondary aerosols, contributed about nearly one-third each to the PM2.5 pollution in

Bangkok. However, emission from inland water transport has not been studied and has not

been included in the previous inventories. Old engines on the boats with large amount of

black smoke emission during boat departing and embarking the ports may contribute

significantly to the total emission in Bangkok. Studying the emission from inland waterway

is, thus, necessary to better understand and manage PM2.5 emission sources in Bangkok.

To assist in the continuous effort in maintaining an up-to-date emission inventory, the

template that is easy and convenient for users and specifically for the local sources are

required, and will be developed by the end of 2019. This study will add a separate calculation

sheet to the emission inventory template that will be developed for Bangkok, focusing on

emission calculation for inland water transport in Bangkok. It will then be used to evaluate

control strategies and gives policy recommendation, preparing the policy makers for

management of the coming PM2.5 episodes.

1.2 Objectives

This study aims at estimating emission for inland water transport in Bangkok, focusing on

public boats in Chao Phraya river and Saen Seap canal. The specific objectives of this study

are indicated as follows;

1. To estimate spatial and temporal emission for inland water transport in Chao Phraya

river and Saen Saep canal;

2. To develop an excel calculation tool for inland water transport emission estimation;

3. To identify policies and measures to reduce emission from inland water transport in

Bangkok.

4

1.3 Scope of the project

The scope of this project includes:

1. The selected domains were the Chao Phraya river and Saen Saep canal in Bangkok;

2. The study focused only the Chao Phraya company’s boats and the Cross river ferries

registered in the Marine Department statistics in the Chao Phraya river, and the Saen

Saep boats in the Saen Saep canal which operated during 5.00 a.m. to 8.00 p.m.;

3. The developed emission inventory was based on the survey data in 2019 and 2020;

4. The study focused on primary pollutants which were Particulate Matter (PM2.5 &

PM10), Carbon Monoxide (CO), Black Carbon (BC), Organic Carbon (OC), Carbon

Dioxide (CO2), Methane(CH4), Non-methane hydrocarbon (NMHC), Oxides of Nitrogen

(NOx), Ammonia (NH3), Nitrous Oxide (N2O) and Sulfur Dioxide (SO2);

5. The emission calculation template was developed for the inland water transport

based on an existing Atmospheric Brown Clouds (ABC) emission inventory template

(Shrestha et al, 2013).

5

CHAPTER 2

METHODOLOGY

2.1 Framework of methodology

Figure 2.1 Framework of methodology

This project was separated into three phases; Phase 1: Study area selection; Phase 2: Data

collection; and Phase 3: Emission estimation. In Phase 1, Bangkok where Chao Phraya

express boats, Cross river ferries and Saen Saep express boats was selected for the study

area as presented in Figure 2.2.

Impact area assessment Other sectors in Bangkok

Policy

recommendation

6

Figure 2.2 (a) Thailand (b) Bangkok Metropolitan Administration (BMA)

(c) Chao Phraya river and Saen Saep canal

The methodology for data collection (Phase II) was discussed in Section 2.2 while that for

emission estimation (Phase III) was discussed in Section 2.3 and 2.4. Then, the development

of excel calculation sheet was discussed in Section 2.5. In Section 2.6, emission from this

study was compared to other study. The area of impact by emission from inland water

transport was estimated by AERMOD model and discussed in Section 2.7. Finally, policy

review and recommendation were discussed in Section 2.8.

7

2.2 Data collection

2.2.1 Survey data

As discussed in section 2.1, Chao Phraya boats, Saen Saep boats and cross river ferries were

three major groups of the boats included in this project. The survey was planned to conduct

for one week in each month for each boat group on both weekday and weekend during

different times of the day. The purpose of the survey was to collect information on the

operating time during idling and cruising condition, boat trips, travel distance and engine

load factor (LF) of each group of the boats. Then, number of trips (A) and the operating time

during idling and cruising were used to calculate activity hours (Tt) for each group of the

boat.

For the travelling distance and cruising & idling times of each boat group, this study used

GPS devices (GlobalSat Data Logger DG-100) to identify time and speed of boats in

different operating modes. In Equation 2.1, travelling hour (T) for all groups of boats in the

different routes was estimated by GPS. Also, the LF was estimated by the ratio between

actual and maximum cruising velocities of the boat obtained from the GPS, as presented in

Equation 2.2 (Browning & Bailey, 2006).

Tc = T- Ti (Equation 2.1)

𝐿𝐹 = (𝐴𝑆

𝑀𝑆)3

(Equation 2.2)

Where;

Tc: Time for cruising (hour)

Ti: Time for idling (hour)

T: Total time for one trip (hour)

LF: Load Factor

AS: Actual speed of boat (km/h)

MS: Maximum speed of boat (km/h)

The required sample size for the survey was calculated based on the statistical sampling

method as shown in Table 2.1 with the number of boats from the survey. This survey was

conducted to collect the information from different boat types as planned during the survey

period as shown in Table 2.2.

Table 2.1 Total number of boats, required sample size and number of surveys in different

boats groups

Boat type Total number of

boats under

operation

Calculated sample

size

Number of boats

from survey

Chao Phraya boats 60 52 52

Chao Phraya Tourist

Boatsa (blue flag)

4 4 4

Shuttle boatsa 8 8 8

Cross river ferries 88 73 73

Saen Saep boats 34 32 32

Total 194 169 169 a Number of boats were obtained from chaophrayariverline.com

Note: Chao Phraya Tourist boats or blue flag and Shuttle boats are subgroup of Chao Phraya boats.

8

Table 2.2 Survey period of each boat group

Boat group

2019 2020

October November December January February

Chao Phraya

boats X X X X

Cross river

ferries X X X X X

Saen Saep

boats X X X

2.2.2 Secondary data

Secondary data, such as engine age, engine technology, fuel quality, were obtained from the

Chao Phraya Express Boat Company and the Marine Department. These data were used for

emission factor estimation since the emission factors were affected by age of the engine,

engine model year (technology type), fuel quality (sulfur content) and engine power/size

(USEPA, 2010).

A summary of the required data and the sources of data in Phase 2 (data collection phase) is

presented in Table 2.3.

Table 2.3 Summary of data collection

Required Data Details Sources of data

Primary

data

Total operation time, idling

time and cruising time per

trip

Survey data

Boat trips per week Survey data

Current boat routes Survey data

Distance Survey data

Secondary data

Age of engine Chao Phraya Express Boat Company

Year of engine model Marine Department, Chao Phraya

Express Boat Company

Number of boats Marine Department Statistics, Chao

Phraya Express Boat Company and

Chao Phraya’s website

Fuel quality Chao Phraya Express Boat Company,

Private boat company

Engine power Marine Department Statistics, Chao

Phraya Express Boat Company

Maintenance program Marine Department, Chao Phraya

Express Boat Company

9

2.3 Emission estimation

Emission was calculated by Equation 2.3 for cruising and idling conditions. Emission factors

in this study were adjusted with the operating conditions of the engines, such as LF, engine

power, sulfur content in fuel, age of engine and engine technology.

𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 = [𝐴 ∗ 𝑇𝑡 ∗ 𝑃𝑜𝑤𝑒𝑟 ∗ 𝐿𝐹] ∗ [𝐸𝐹𝑎𝑑𝑗 ∗ 10−6 ] (Equation 2.3)

Where;

A: Activity (trip/month)

LF: Load factor (Unitless) Power: Average power (hp) Tt: Travelling time per trip (h)

EFadj: Adjusted Emission factor (g/hp-h)

2.3.1 Emission factors (EFs) calculation during cruising condition

Emission in this study included HC, CO, NOx, NMHC, CH4, NH3, N2O, CO2, SO2, PM10, PM2.5, BC and OC. The EFs for boat activities were calculated based on USEPA (2010) by

adjusting with local boat conditions. Thus, the developed EFs were suited for Bangkok’s

emission estimation.

In this study, all PM emissions from the boat engines were assumed to be PM10 and 97%

was assumed to be PM2.5 (USEPA, 2010). The USEPA (2010) provided different equations

for each pollutant to calculate emission factors depending on parameters affecting emission

as given in Equation 2.4, 2.5 and 2.6. These Equations were used to calculate EFs for all

boat groups at the cruising mode.

𝐸𝐹𝑎𝑑𝑗(𝐻𝐶,𝑁𝑂𝑥,𝐶𝑂)= 𝐸𝐹𝑠𝑠 ∗ 𝑇𝐴𝐹 ∗ 𝐷𝐹 (Equation 2.4)

𝐸𝐹𝑎𝑑𝑗(𝑃𝑀) = 𝐸𝐹𝑠𝑠 ∗ 𝑇𝐴𝐹 ∗ 𝐷𝐹 − 𝑆𝑃𝑀𝑎𝑑𝑗

(Equation 2.5)

𝐸𝐹𝑎𝑑𝑗(𝐶𝑂2,𝑆𝑂2) = 𝐸𝐹𝑠𝑠 ∗ 𝑇𝐴𝐹 (Equation 2.6)

Where;

SPMadj = adjustment to PM EFs to account for variations in sulfur content (g/hp-hr)

EFss = steady state emission factor (g/hp-hr)

EFadj = final emission factor used after adjustment to account for DF

TAF = transient adjustment factor (unitless)

DF = deterioration factors (unitless)

The emission factors of CO2 and SO2 were calculated based on the Brake Specific Fuel

Consumption (BSFC) which was the fraction between the rate of fuel consumption and the

power produced. The values of the BSFC of nonroad engines was discussed later (Table

2.7).

In Equation 2.4, 2.5 and 2.6, the Transient Adjustment Factor (TAF) and steady-state

emission factor (EFss) of HC, NOx, CO, CO2, SO2 and PM were required. The EFss was

obtained from the emission testing of the new engine (engine age = 0 years) of the specific

engine model year and power. Engine technology (Base/Tier 0, Tier 1, Tier 2, Tier 3 and

Tier 4) and engine power were obtained from the secondary data collection. For TAF that

10

represents the ratio between the transient and steady-state factor, it was set to 1 for boats

(USEPA, 2010).

The deterioration factors (DF) was required for calculating EFs for HC, NOx, CO and PM

in Equation 2.4 and 2.5. It represented the engine’s emission change as a function of the

technology and engine age. The DF was linked with the cumulative usage hours of the

engine which were calculated by multiplying engine age (in years) from the secondary data

collection with average activity (hour per year) from survey. Moreover, the DF was linked

with the engine load factor and the median life at full load (in hours). The equations of DF

are given in Equation 2.7 and 2.8.

𝐷𝐹 = 1 + 𝐴 ∗ (𝐴𝑔𝑒 𝐹𝑎𝑐𝑡𝑜𝑟)𝑏; 𝐹𝑜𝑟 𝑎𝑔𝑒 𝑓𝑎𝑐𝑡𝑜𝑟 ≤ 1 (Equation 2.7)

𝐷𝐹 = 1 + 𝐴; 𝐹𝑜𝑟 𝑎𝑔𝑒 𝑓𝑎𝑐𝑡𝑜𝑟 > 1 (Equation 2.8)

Where:

Age Factor = fraction of median life expanded = cumulative hours x load factor

median life at full load,in hours

A, b = constants for a given pollutant/technology type; b ≤ 1

According to USEPA (2010), there was no data of LF of boats. In this study, the propulsion

load was estimated by the Propeller Law which described the propulsion power varied by

the cube of speed as presented in Equation 2.2. This law assumed that the lower limit of the

LF was approximately 10% of the full load, and could be as low as 2% of the full load when

maneuvering at 5.8 knot (USEPA, 2009). For the boat travelling with the river current

(downstream), the actual speed should be the boat speed minus the river speed. For the boat

travelling against river current, the actual speed should be the boat speed plus the river speed.

However, the speed of the river and canal flows in Bangkok were very slow (0 to 0.94 km/h)

(Department of Drainage and Sewerage, 2020). Thus, the effects of the river and canal flows

were insignificant, and the maximum speed of boat was equal to the maximum speed

acquired from the GPS datalogger.

Median life at the full load (in hours) which was the cumulative hour at which 50% of the

engine population was removed from the fleet are listed by engine power size and engine

type (USEPA, 2010) in Table 2.4 and Table 2.5. The engine type in this study was diesel,

and the engine power information were obtained from the data collection. Thus, the median

life in hours at full load was identified.

Table 2.4 Horsepower classes for median life (USEPA, 2002)

HP Class Diesel (hp) 2-stroke (hp) 4-stroke (hp)

HP1 ≤16 ≤3 ≤6

HP2 17-25 3-16 6-16

HP3 26-50 16-25 16-25

HP4 51-100 26-50 26-50

HP5 101-175 51-100 51-100

HP6 176-300 101-175 101-175

HP7 301-600 176-250 176-250

HP8 601-750 301-600 301-600

11

Table 2.4 Horsepower classes for median life (USEPA, 2002) (Continued)

HP Class Diesel (hp) 2-stroke (hp) 4-stroke (hp)

HP9 751+ 601-750 601-750

HP10 - 751+ 751+

Table 2.5 Expected engine life in hours at full load (USEPA, 2002)

Engine

Type

HP1 HP2 HP3 HP4 HP5 HP6 HP7 HP8 HP9 HP10

Diesel 2500 2500 2500 4667 4667 4667 7000 7000 7000 -

2-stroke

Gasoline

150 200 750 - - - - - - -

4-stroke

Gasoline

200 400 750 1500 3000 3000 3000 3000 3000 3000

CNG/LPG 200 400 750 1500 3000 3000 3000 3000 3000 3000 CNG: compressed natural gas, LPG: liquefied petroleum gas

The constant A in Equation 2.7 and 2.8 can be varied in a wide range of deterioration

patterns. For example, setting A equal to 1.0 would result in emissions at the engine’s

median life being two times the emissions (DF = 1+1) of the new engine. For constant “b”,

it defined as the shape of deterioration function which can be set at any level between 0 and

1. For diesel engine, b was equal to 1. This resulted in a linear pattern of deterioration

meaning the rate of deterioration was constant throughout the median life of an engine.

Because of no information on the deterioration rate of the nonroad diesel engines, the

deterioration factors were selected based on the data derived from the highway engines. The

derivation of the constant “A” for the diesel engines based on technology types are given in

Table 2.6.

Table 2.6 Deterioration Factor for Nonroad Diesel Engines (USEPA, 2010)

Pollutant Relative Deterioration Factor (A)

Base/Tier 0 Tier 1 Tier 2 Tier 3

HC 0.047 0.036 0.034 0.027

CO 0.185 0.101 0.101 0.151

NOx 0.024 0.024 0.009 0.008

PM 0.473 0.473 0.473 0.473

For the emission factor of PM, the adjustment due to variations in fuel sulfur level (SPMadj)

was required (Equation 2.5) since the sulfur in fuel contributed to PM emission. The default

value of sulfur level used in Equation 2.9 was 0.33 weight percent (soxbas). In this project,

the actual sulfur content from the secondary data collection was used for “soxdsl” in

Equation 2.9 and 2.11.

𝑆𝑃𝑀𝑎𝑑𝑗= (𝐵𝑆𝐹𝐶 ∗ 453.6 ∗ 𝑠𝑜𝑥𝑐𝑛𝑣 ∗ 7.0 ∗ 0.01 ∗ (𝑠𝑜𝑥𝑏𝑎𝑠 − 𝑠𝑜𝑥𝑑𝑠𝑙) (Equation 2.9)

Where;

SPmadj =PM sulfur adjustment (g/hp-hr)

BSFC =in-use adjusted brake-specific fuel consumption (lb fuel/hp-hr)

453.6 = conversion from lb to grams

12

7.0 = grams PM sulfate/grams PM sulfur

Soxcnv = grams PM sulfur/grams fuel sulfur consumed = 0.02247

0.01= conversion from percent to fraction

Soxbas = default certification fuel sulfur weight percent = 0.33 weight percent

Soxdsl = episodic fuel sulfur weight percent of sulfur (specified by user)

For the term “soxcnv * 7.0”, soxcnv was the fraction of diesel sulfur that converted to PM

which was 0.02247 for all technology types, and 7.0 was the grams of sulphate PM emission

per gram sulfur. The values of BSFC were derived from the engine test result in the United

States during year 1988 to 1995 (USEPA, 2010). The BSFC of two engine size ranges are

given in Table 2.7.

Table 2.7 Average engine test results for BSFC (USEPA, 2010)

Engine (reference) BSFC (lb/hp-hr) BSFC (g/hp-hr)

Average (50 to 100 hp) 0.408 185.23

Average (≥ 100hp) 0.367 166.62 Note: If the unit of g/kWh is required, use the equation [(g/kWh) × 0.7457 = (g/hp-hr)] for conversion.

From Equation 2.6, emission factors of CO2 and SO2 were calculated by EFss and TAF. For

EFss, it was calculated from the chemical balance of carbon and sulfur in the fuel and the

exhaust gases, as shown in Equation 2.10 and 2.11. The carbon that went to the exhaust as

HC emission was subtracted to correct the amount of the unburned fuel.

𝐶𝑂2 = (𝐵𝑆𝐹𝐶 ∗ 453.6 − 𝐻𝐶) ∗ 0.87 ∗ (44

12) (Equation 2.10)

𝑆𝑂2 = (𝐵𝑆𝐹𝐶 ∗ 453.6 ∗ (1 − 𝑠𝑜𝑥𝑐𝑛𝑣) − 𝐻𝐶) ∗ 0.01 ∗ 𝑠𝑜𝑥𝑑𝑠𝑙 ∗ 2 (Equation 2.11)

Where:

SO2 and CO2 = in g/hp-hr

BSFC = the in-use adjusted fuel consumption in lb/hp-hr

453.6 = the conversion factor from pounds to grams

Soxcnv = the fraction of fuel sulfur converted to direct PM =0.02247

HC = the in-use adjusted hydrocarbon emissions in g/hp-hr

0.01= the conversion factor from weight percent to weight fraction

Soxdsl = the episodic weight percent of sulfur (specified by user)

2 = grams of SO2 formed from a gram of sulfur

2.3.2 Summary of the methodology to calculate the adjusted emission factors (EFadj)

under cruising condition

All parameters and equations for calculating the adjusted emission factors under cruising

condition are given in Table 2.8.

13

Table 2.8 Summary of the parameters and equations for EFadj

Pollutants EFss (g/hp-hr) TAF DF SPmadj

HC Based on

technology and

engine power

1

Eq2.7 & Eq2.8 -

CO Eq2.7 & Eq2.8 -

NOx Eq2.7 & Eq2.8 -

PM Eq2.7 & Eq2.8 Eq2.9

CO2 Eq2.10 - -

SO2 Eq2.11 - -

Emission estimation for BC, OC, NMHC, CH4, NH3 and N2O

For other pollutants, i.e., BC, OC, NMHC, CH4, NH3 and N2O, where USEPA (2010) does

not provide emission factors, this project used information from Winijkul (2015) which

developed EFs based on the on-road heavy duty vehicles and GAINS (2020) as shown in

Table 2.9. The ratios of BC/PM2.5 and OC/PM2.5 are also shown in Table 2.9. For NMHC,

CH4, NH3 and N2O, GAINS (2020) defined the ratios of 0.964:0.036 for NMHC:CH4 and

0.0008 and 0.0048 g/hp-hr for the EFs of NH3 and N2O, respectively.

Table 2.9 Fraction of BC and OC from PM2.5

Vehicle standard BC/PM2.5 OC/PM2.5 Sources

No standard 0.50 0.40

Winijkul (2015)

Euro I 0.65 0.26

Euro II 0.65 0.26

Euro III 0.61 0.34

Euro IV 0.83 0.16

Euro V 0.83 0.16

Euro VI 0.07 0.92

2.3.3 Emission factors during idling condition

For idling condition, the idling factor (IF) developed from the ratio between idling and

cruising emission of the on-road heavy duty diesel vehicles was calculated. Table 2.10 shows

the idling factors used in this project.

Table 2.10 Fractional adjustment of emission factor for idling condition

Pollutants

The fraction adjustment of idling factor

Idling/Cruising Sources

HC 0.84 Tong, Hung, & Cheung (2011)

CO 2.61 Park et al. (2011)

NOx 1.07 Park et al. (2011)

NMHC 0.84 -

CH4 0.84 -

NH3 1.00 *

N2O 1.00 *

14

Table 2.10 Fractional adjustment of emission factor for idling condition (Continued)

Pollutants

The fraction adjustment of idling factor

Idling/Cruising Sources

CO2 1.00 *

SO2 1.00 *

PM10 0.25 -

PM2.5 0.25 Park et al. (2011)

BC 0.25 -

OC 0.25 - * Applied equal to EFs during cruising condition under the assumption that these pollutants didn’t significantly change in

this study. IF for NMHC and CH4 were similar to HC. For PM10, BC and OC, IF were similar to PM2.5.

2.4 Emission estimation of all boat groups

Emission in this project estimated by using Equation 2.3 and 2.12 based on the EFadj

calculated for cruising and idling time separately. For emission during idling condition, the

IF was applied to the adjusted emission factors as presented in Equation 2.12. Next, emission

during cruising and idling were summed up as total emission (Equation 2.13).

Emission for cruising time (Equation 2.3):

𝐸𝑐 = [𝐴 ∗ 𝑇𝑡 ∗ 𝑃𝑜𝑤𝑒𝑟 ∗ 𝐿𝐹 ∗ 𝑃𝑜𝑤𝑒𝑟] ∗ [𝐸𝐹𝑎𝑑𝑗 ∗ 10−6 ]

Emission for idling time:

𝐸𝑖 = [𝐴 ∗ 𝑇𝑡 ∗ 𝑃𝑜𝑤𝑒𝑟 ∗ 𝐿𝐹 ∗ 𝑃𝑜𝑤𝑒𝑟] ∗ [𝐼𝐹 ∗ 𝐸𝐹𝑎𝑑𝑗 ∗ 10−6] (Equation 2.12)

Total Emission: 𝐸 = ∑(𝐸𝑐 + 𝐸𝑖) (Equation 2.13)

Where;

A: Activity (trip/month)

LF: Load factor (Unitless) Power: Average power (hp) Tt: Travelling time per trip (h)

EF: Emission factor (g/hp-h)

Et = Emission for cruising time (tons/month)

Ei = Emission for idling time (tons/month)

IF = Idling factor

EFadj = Final adjustment EFs of idling time and cruising condition (g-pollutant/hp-hr)

2.4.1 Data analysis

Data collected in Phase 2 were analyzed with the following steps:

Step 1: Number of boats and the engine powers were obtained from the Marine Department,

except for the Chao Phraya tourist boat and Shuttle boat which were collected from the

website (chaophrayariverline.com). Then, the Chao Phraya express boat was classified into

subgroup based on routes, operating time and engine power;

15

Step 2: Travelling distance, boat route and boat trip of each boat group were determined by

the survey data;

Step 3: The average hours of each trip during cruising and idling were extracted from the

GPS dataloggers;

Step 4: The EFs were calculated depending on age of engine, engine technology, LF and

sulfur content;

Step 5: The emission of boat groups was calculated and summed to total emission in

Bangkok;

Step 6: Temporal and spatial distribution of emission were estimated based on the survey

data.

2.4.2 Temporal distribution of emission

The emission in each hour of Chao Phraya boats, Saen Saep boats and Cross river ferries

were calculated based on the survey data.

2.4.3 Spatial distribution of emission

The emission per unit area was calculated. In this project, the study area was separated into

the grid cells of 500 x 500 m2. In each cell, total emission from all boats in that cell was

calculated by allocating emission to each grid cell that the boats crossed (cruising emission,

Equation 2.14) and idled (idling emission).

𝐸𝑖 = ∑𝐸𝑖

𝑁𝑔 (Equation 2.14)

Where;

𝐸𝑖 = Total emission of pollutants “i” which released by all “n” boats in grid cell

∑𝐸𝑖 = Total emission of pollutants “i” between each pier

𝑁𝑔 = Number of grid cells between each pier

The emission along each route was calculated and put in the ArcMap v.10.5 for spatial

distribution.

2.5 Excel calculation tool for inland water transport emission

Atmospheric Brown Clouds – Emission Inventory Manual (ABC-EIM) was developed in an

excel calculation or excel-based workbook sheet which can be used as a tool for compilation

and estimation of emission of the ABCs precursors. The current excel tool (ABC tool) for

inland water transport is given in Figure 2.3. User needs to fill in the blue-colored cells

which included activity data and chose the emission factor values. Currently, the excel tool

for calculating emission from inland water transport was simple and could be improved.

Thus, an excel tool for inland water transport was modified based on the calculation

methodology in this study.

16

Figure 2.3 Current excel tool (ABC tool) for inland water transport

2.6 Emission comparison

The emission inventories developed for Bangkok city such as GAINS (2020), Kim Oanh

(2020), were used to compare with the emission from this study. However, in Kim Oanh

(2020), the inland water transport emission was calculated from the estimated fuel

consumption which may not represent actual fuel consumption in the inland water transport

(both passenger and fridge transport). For GAINS (2020), total on-road emission in Bangkok

was selected. However, comparing emission calculated in this study with the previous

studies provided the confirmation of the magnitude of the emission from inland water

transport in this study.

2.7 Emission impact area from inland water transport

Since the emission from inland water transport was generated in two specific area which are

Chao Phraya river and Saen Saep canal, this study used AERMOD model to assess the area

that the emission from inland water transport contribute to the concentration in the local

area. The AERMOD model was setup and run using the meteorological data from Bangna

station (Station ID: 48453) in Bangkok in 2015. The model was run based on the spatial

distribution of PM2.5 emission developed in Section 2.4.3. However, the daily emission

which was estimated during the operating times of different routes was apportioned to 24-

hour emission as the input to the model. Then, the model was run for the maximum 24-hr

average concentration of PM2.5.

2.8 Emission reduction policy recommendation

Table 2.11 provides three scenarios of emission reduction measures which were proposed

in this study. The emission reduction from each measure was estimated using the excel tool

developed in section 2.4.4. Emission standard (Tier system) in Table 3.11 referred to

nonroad standard in the U.S. Comparing with the on-road heavy duty standard in Europe

(Euro standard), in term of PM emission, Tier 0 engine is comparable with Euro 1 engine,

and Tier 4 engine is comparable with Euro 6 engine.

17

Table 2.11: Emission Reduction Measures Investigated in This Study

Scenario 1 Scenario 2 Scenario 3

Switch boat engines to Tier 4

technology and use 10 ppm

sulfur fuel

Use engine with current

technology (Tier 0), but use

10 ppm sulfur fuel (current

was 50 ppm)

Use engine with current

technology (Tier 0), but

reducing idling time by 50%

18

CHAPTER 3

SUMMARY OF ACTIVITY DATA AND EMISSION FACTORS

3.1 Activity data

Survey and secondary data were collected from the Marine Department, Chao Phraya

Express Boat Company and Private Boat Companies (Supatra & Konsong family). The

survey data included travelling distance, current boat routes, boat trips, time during cruising

and idling, and load factor of each boat group. Secondary data were age of engine, year of

engine model, number of boats of each boat group (which were used daily) and fuel quality.

a) Secondary data collection

Number of boats and main engine power were obtained from the Chao Phraya Express Boat

Company and Marine Department. Number of boats and engine sizes used in each boat

groups are summarized in Table 3.1.

Table 3.1 Summary of number of boats and engine sizes for each engine group

Main group Subgroup Number of boats Classification criteria Engine

power(hp)

Chao Phraya

boats

No flag

60

Routes and operation

time

355

Green flag 355x2

Orange flag 355

Yellow flag 355

Gold flag 355x2

Chao

Phraya

Tourist

boat

4

247x2

Shuttle

boat 8 150x2

Saen Saep boats - 34 300-350

Cross river ferries - 88 100-450

The age of the engine and the engine model year were not much different among different

groups, as presented in Table 3.2. From the survey, all boat used on-road engines. Moreover,

secondhand engines were used in some routes of Cross river ferries and Saen Saep boats.

So, the information of both engine age and engine model were estimated by the mechanics

who did the maintenance for these boats.

19

Table 3.2 Age of engine and engine model year of each boat group

Boat Group Age of engine (year) Engine model year

Chao Phraya boats 16-20 < year 1999

Saen Saep boats 15-20 1996-2000

Cross River ferries 15-20 Before 1996/1999

The fuel used in all boats was diesel which had the sulfur content of 0.005% or 50 ppm

which was the same as the sulfur content of on-road vehicles in Thailand. For all boat groups

in this project, only the main engines were used for operation (no auxiliary engine).

b) Survey data

The total of 169 surveys were conducted during October 2019 to February 2020 to collect

the data, i.e. load factor, boat routes, traveling distance, operating time for cruising and idling

condition, and boat trips per month. Table 3.3 – 3.7 show the survey information of the cross

river ferries with low hp, Cross river ferries with high hp, Chao Phraya boats, and Saen Saep

boats, respectively.

Table 3.3 Summary of survey data of the cross river ferries (100-300 hp)

No. Routes LF

Distance

(km/round

trip)

Activity time

(min/trip) Average

Monthly

trip Cruising

time/trip

Idling

time/trip

1. Pakkret-Wat Toey 0.31 0.51 3.21 1.30 4300

2. Pakkret-Watchareewongse 0.24 0.36 3.90 1.19 4232

3. Koh Kret-Wat Sanamnuea 0.43 0.31 2.44 6.09 5276

4. Nonthaburi-

Bangsrimueng 0.23 0.56 5.25 5.15 5900

5. Thewes- Bowornmongkon 0.36 0.71 6.25 4.19 1888

6. Thewes-Karuhabodee 0.38 0.71 6.22 9.34 1248

7. Wang Lang-Tha Phrachan 0.22 0.54 4.30 7.61 2296

8. Wang Lang-Maharaj 0.25 0.51 4.66 4.77 1820

9. Wang Lang-Tha Chang 0.24 0.8 7.37 7.84 2104

10. Tha Chang-Wat Rakang 0.22 0.38 4.01 4.43 1476

11. Tha Tien-Wat Arun 0.33 0.44 4.77 9.10 2344

12. Pakklong Talad-

Kallayanimit 0.31 0.42 5.10 4.70 1508

13. Rachawongse-Dindang 0.24 0.46 4.31 8.32 2972

20

Table 3.4 Summary of survey data of the cross river ferries (100-300 hp) (continue)

No. Routes LF

Distance

(km/round

trip)

Activity time (min/trip) Average

Monthly

trip Cruising

time/trip

Idling

time/trip

14. Sri Phraya-Klongsan 0.24 0.63 4.5 6 4788

15. Oriental-Wat Suwan 0.29 0.44 5.29 4.76 2892

16. Sathorn-Pepsi 0.25 0.63 6.45 7.7 1832

17. Klong Toei-Bangkrachao 0.37 0.75 6.56 0.5 1708

18. Bangna-Taluen 0.31 0.91 6.66 6.0 736

19. Wiboonsri-Phra

Samutchedee 0.55 2.88 18.30 6.26 2776

Table 3.5 Summary of survey data of the cross river ferries (300-750 hp)

No. Routes LF Distance

(km/trip)

Activity time (min/trip) Average

Monthly

trip Cruising

time/trip

Idling

time/trip

1. Sathu Phradit-Klong

Lat Luang 0.32 1.03 8.83 3.44 1228

2 Rama 3- Klong Ladpo 0.31 0.65 5.92 7.93 1812

3. Bangnanok-

Bangnampuengnok 0.31 0.68 6.56 6.00 2040

4. Petra-Phra Pradang 0.28 0.74 7.32 7.12 3256

Table 3.6 Summary of survey data of the Chao Phraya boats (300-750 hp)

Flag

Number of

routes

Routes

LF

Distance

(km/trip)

Activity time (hr/trip) Average

monthly

trip Cruising Idling

Green

Route 1 Pakkret - Sathorn 0.29 27.94 1.28 0.23 340

Route 2 Pakkret -

Nonthaburi 0.29 9.71 0.42 0.11 80

Orange Route 3

Nonthaburi – Wat

Rajsingkorn 0.28 19.91 1.08 0.17 2516

No flag

Route 3

Nonthaburi – Wat

Rajsingkorn 0.28 19.91 1.42 0.40 176

Route 4 Nonthaburi-Wat

Soi Thong 0.28 5.03 0.42 0.12 40

21

Table 3.6 Summary of survey data of the Chao Phraya boats (300-750 hp) (continue)

Flag

Number of

routes

Routes

LF

Distance

(km/trip)

Activity time (hr/trip) Average

monthly

trip Cruising Idling

Yellow

Route 5 Nonthaburi –

Sathorn 0.29 18.14 1.00 0.11 492

Route 6 Sathorn-

Ratburana 0.29 5.26 0.25 0.07 80

Gold Route 7 Sathorn -

Prannok 0.34 5.29 0.42 0.11 1080

Blue Route 8 Phra Arthit-

Sathorn/Asiatique 0.35 9.47 0.50/0.67 0.23/0.24 1472

Shuttle

boat

Route 9

Icon-Siam-

Lhong 1919-

Rachawongse

0.26 2.25 0.38 3.96 1232

Route 10 Icon-Siam -

Sathorn 0.28 1.07 0.24 0.17 1336

Route 11 Icon-Siam -Wat

Muangkae 0.27 0.23 0.19 0.04 1760

Route 12 Icon-Siam -Sri

Phraya 0.29 0.26 0.10 0.07 2016

Table 3.7 Summary of survey data of the Saen Saep boats (300-750 hp)

No.

Routes

LF

Distance

(km/trip)

Activity

time(hr/trip)

Average

monthly trip

Cruising

Idling

1. Sriboonrueng -

Pratunam 0.14 13.25 0.61 0.21 7756

2. Phan Fa Lilat-

Pratunam 0.15 3.98 0.20 0.07 7332

From Table 3.3-3.7, the summary of the survey data were:

- The LF of different boat groups were almost the same since the average ratios were 0.29

for boats with 100-300 hp and 0.28 for boats with 300-750 hp. Therefore, the LF of 0.29

and 0.28 was used for the emission estimation for boats with 100-300 hp and 300-750

hp, respectively.

- The total of 37 routes of traveling distance, cruising and idling time of each boat route

were extracted from GPS dataloggers which included 19 routes with 100-300 hp and 4

routes with 300-750 hp of Cross river ferries, 12 routes of Chao Phraya boats and 2

routes of Saen Saep boats with 300-750 hp.

- The most frequent trips in Cross river ferries, Chao Phraya boats and Saen Saep boats

were Nonthaburi-Bangsrimuang with 5,900 trips/month, Nonthaburi-Wat Rajsingkorn

22

(orange flag) with 2,516 trips/month and Sriboonrueng-Pratunam with 7,756

trips/month.

3.2 Emission Factors

The engine LFs were extracted from the survey data, and the value of 0.29 and 0.28 were

applied to all boat groups with 100-300 hp and 300-750 hp, respectively. Since the boat

engine ages were between 15-20 years, and the engine model year was more than 20 years,

all engines were considered to be Tier 0. This assumption was based on the fact that the first

heavy duty emission standard (comparable to EURO 1/Tier 0, in term of PM emission level)

was implement in 1998 (21 years ago), and the mechanics provided the information that

some of the engines were secondhanded engines. Note that there was no emission standard

for boat in Thailand.

The EFs were calculated based on the methodology discussed in Chapter 2, and the 50 ppmS

fuel would be used in Tier 0 - Tier 2 engines, while 15 and 10 ppmS fuels would be used in

Tier 3 and Tier 4 engines, respectively. The final adjusted EFs of total thirteen pollutants of

the engines size between 100-300 hp and 300-750 hp with Tier0 - Tier4 emission standards

were calculated based on the survey and secondary data collected in this project (Table 3.8

and 3.9 for cruising and idling conditions, respectively).

23

Table 3.8 Final adjusted EFs for cruising condition (g/hp-hr)

Table 3.9 Final adjusted EFs for idling condition (g/hp-hr)

HC CO NOx NMHC CH4 NH3 N2O CO2 SO2 PM10 PM2.5 BC OC

Tier 0 0.367 0.71 3.20 8.58 0.69 0.03 0.001 0.005 528.87 0.016 0.51 0.49 0.25 0.10

Tier 1 0.367 0.33 0.85 5.68 0.32 0.01 0.001 0.005 530.01 0.016 0.24 0.24 0.15 0.04

Tier 2 0.367 0.33 0.85 4.07 0.32 0.01 0.001 0.005 530.01 0.016 0.11 0.10 0.07 0.02

Tier 3 0.367 0.19 0.87 2.51 0.18 0.01 0.001 0.005 530.46 0.005 0.14 0.14 0.08 0.03

Tier 4 0.367 0.13 0.09 0.28 0.13 0.005 0.001 0.005 530.62 0.003 0.01 0.01 0.01 0.001

Tier 0 0.367 0.71 3.20 8.58 0.69 0.03 0.001 0.005 528.87 0.016 0.51 0.49 0.25 0.10

Tier 1 0.367 0.18 1.38 5.99 0.17 0.01 0.001 0.005 530.49 0.016 0.18 0.17 0.11 0.03

Tier 2 0.367 0.17 1.14 4.24 0.16 0.01 0.001 0.005 530.51 0.016 0.08 0.08 0.05 0.01

Tier 3 0.367 0.17 1.17 2.51 0.16 0.01 0.001 0.005 530.51 0.005 0.10 0.10 0.06 0.02

Tier 4 0.367 0.13 0.12 0.28 0.13 0.005 0.001 0.005 530.62 0.003 0.01 0.01 0.01 0.001

Engine Power (hp) Technology Type BSFC (lb/hp-hr)Cruising EFadj (g/hp-hr)

100-300

300-750

HC CO NOx NMHC CH4 NH3 N2O CO2 SO2 PM10 PM2.5 BC OC

Tier 0 0.367 0.60 8.35 9.18 0.58 0.02 0.001 0.005 528.87 0.02 0.13 0.12 0.06 0.02

Tier 1 0.367 0.28 2.21 6.08 0.27 0.01 0.001 0.005 530.01 0.02 0.06 0.06 0.04 0.01

Tier 2 0.367 0.28 2.21 4.35 0.27 0.01 0.001 0.005 530.01 0.02 0.03 0.03 0.02 0.004

Tier 3 0.367 0.16 2.27 2.69 0.15 0.01 0.001 0.005 530.46 0.005 0.04 0.03 0.02 0.01

Tier 4 0.367 0.11 0.23 0.30 0.11 0.00 0.001 0.005 530.62 0.003 0.002 0.002 0.002 0.0003

Tier 0 0.367 0.60 8.35 9.18 0.58 0.02 0.001 0.005 528.87 0.02 0.13 0.12 0.06 0.02

Tier 1 0.367 0.15 3.61 6.41 0.14 0.01 0.001 0.005 530.49 0.02 0.04 0.04 0.03 0.01

Tier 2 0.367 0.14 2.97 4.53 0.14 0.01 0.001 0.005 530.51 0.02 0.02 0.02 0.01 0.003

Tier 3 0.367 0.14 3.05 2.69 0.14 0.01 0.001 0.005 530.51 0.005 0.02 0.02 0.01 0.01

Tier 4 0.367 0.11 0.30 0.30 0.11 0.00 0.001 0.005 530.62 0.003 0.002 0.002 0.002 0.0003

Idling EFadj (g/hp-hr)

100-300

300-750

Engine Power (hp) Technology Type BSFC (lb/hp-hr)

24

CHAPTER 4

EMISSION INVENTORY RESULTS

4.1 Emission inventory results

Emission inventory was developed for all thirteen pollutants for cruising and idling

conditions of the boats. The average monthly survey data (collected during five months

survey period) was multiplied with 12 months to be annual emission assuming that the boat

activities were consistent for all twelve months.

The detailed information of emission of all thirteen pollutants during cruising and idling

condition of all boat groups are provided in Appendix 2. The pollutants discussed in this

Chapter were PM2.5 and CO where the emission show significantly differences between

cruising and idling conditions. Emission of other pollutants show similar patterns to

emission of either PM2.5 or CO.

4.1.1 Total annual emissions

a) Total annual emissions of the Chao Phraya express boats in 2019

The emission was calculated for six groups of boats by the flag color (Green, Orange,

Yellow, No flag, Gold, and Blue flags) and one group with the Icon-Siam destination (shuttle

boat). The annual emission of the Chao Phraya express boat is presented in Table 4.1.

Table 4.1 Annual emission of the Chao Phraya express boat (tons/year)

Pollutant

(tons/year)

Operation Condition

Cruising Idling Total

HC 6.9 1.7 8.6

CO 31.1 23.7 54.8

NOx 82.5 26.0 108.5

NMHC 6.6 1.6 8.2

CH4 0.2 0.1 0.3

NH3 0.01 0.01 0.02

N2O 0.06 0.01 0.07

CO2 5083 1493 6576

SO2 0.17 0.05 0.22

PM10 4.9 0.4 5.3

PM2.5 4.7 0.4 5.1

BC 2.4 0.2 2.6

OC 0.9 0.1 1.0

Among the seven routes of boats, orange flag route dominated the emission which was about

1-10 times higher than emission of other flags (depending on the pollutant), followed by

Shuttle boat, Blue flag, Gold flag, Green flag, Yellow flag and No flag. The Orange flag

boats have the highest emission due to its most frequent boat trips which operated from 5.00

a.m. to 7.00 p.m.

Figure 4.1 illustrates the share of CO and PM2.5 from the seven routes of the Chao Phraya

boat (other pollutants showed similar pattern as provided in Appendix 2).

25

Figure 4.1 Emission share of CO and PM2.5 of Chao Phraya boats

Form Figure 4.1, Orange flag boats accounted for 32.2% and 34.6% of CO and PM2.5

emission, respectively. The emission share between cruising and idling of CO and PM2.5 of

the Chao Phraya boats are presented in Figure 4.2 and 4.3, respectively. The emission shares

between cruising and idling of other pollutants are provided in Appendix 2.

Figure 4.2 Emission share between cruising and idling conditions of CO for seven groups

of Chao Phraya boats

For CO emission (Figure 4.2), Orange flag boats were the main emitter with 32.3% (19.7%

cruising and 12.6% idling) of total emission, followed by 19.6% from Shuttle boats (9.5%

cruising and 10.1% idling), 16.9% from Blue flag boats (8.2% cruising and 8.7% idling),

11.4% from gold flag boats (6.8% cruising and 4.7% idling ), 9.7% from green flag boats

(6.6% cruising and 3.1% idling), 5.5% from yellow flag boats (4.1% cruising and 1.4%

idling), and 4.5% from No flag boats (1.9% cruising and 2.6% idling).

0

5

10

15

20

25

30

35

Orange flag,

32.26%

Shuttle boat,

19.62%

Blue flag,

16.95%

Gold flag,

11.44%

Green flag,

9.66%

Yellow flag,

5.52%

No flag,

4.55%

19.67%

9.5% 8.25% 6.76% 6.58% 4.09% 1.92%

12.59%

10.12%

8.7%

4.68% 3.09%

1.43%2.63%

Pe

rce

nta

ge

(%

)

CO

Cruising Idling

Green flag, 9.66%

Orange flag, 32.26%

Yellow flag,5.52%No Flag, 4.55%

Gold flag, 11.44%

Blue flag, 16.95%

Shuttle boat,

19.62%CO

Green flag, 11.41%

Orange flag, 34.62%

Yellow flag,7.08%No Flag, 3.54%

Gold flag, 11.01%

Blue flag, 14.95%

Shuttle boat, 17.39%PM2.5

26

Figure 4.3 Emission share between cruising and idling conditions of PM2.5 for seven

groups of Chao Phraya boats

In Figure 4.3, similar pattern with CO was observed. Total PM2.5 emission was primality

from Orange flag boats which contributed 34.6% (32.7% cruising and1.9% idling ), followed

by 17.4% from Shuttle boat (15.7% cruising and 1.7% idling), 15.0% from Blue flag boats

(13.6% cruising and 1.4% idling), 11.4% from Green flag boats (10.8% cruising and 0.6%

idling), 11.0% from gold flag boats (10.2% cruising and 0.8% idling), 7.1% from Yellow

flag boats (6.9% cruising and 0.2% idling) and 3.5% from No flag boats (3.1% cruising and

0.4% idling). However, the idling emission from PM2.5 was not as significant as the idling

emission from CO.

b) Total annual emissions of Saen Saep express boats in 2019

The emission of Saen Saep boats included two routes which were Nida and Golden

Mountain routes. The annual emission of the Saen Saep canal boats is presented in Table

4.2.

0

5

10

15

20

25

30

35

Orange

flag,

34.62%

Shuttle

boat,

17.39%

Blue flag,

14.95%

Green flag,

11.41%

Gold flag,

11.01%

Yellow flag,

7.08%

No flag,

3.54%

32.65% 15.74% 13.57% 10.82% 10.23% 6.88% 3.15%

1.97%

1.65%

1.38%

0.59% 0.79%

0.2%

0.39%

Pe

rce

nta

ge

(%

)

PM2.5

Cruising Idling

27

Table 4.2 Annual emission of Saen Saep boats from Nida and Golden Mountain routes

(tons/year), 2019

Pollutants

Cruising Idling

Total

emission

(ton/year)

Nida route

(Sriboonrueng-

Pratunam)

Golden

Mountain route

(Phan Falilat-

Pratunam)

Nida route

(Sriboonrueng-

Pratunam)

Golden

Mountain route

(Phan Falilat-

Pratunam)

HC 4.2 1.3 1.4 0.4 7.3

CO 18.8 5.7 19.4 5.4 49.3

NOx 50.4 15.3 18.1 6.0 89.8

NMHC 4.0 1.2 1.1 0.4 6.7

CH4 0.15 0.05 0.04 0.01 0.25

NH3 0.010 0.001 0.002 0.001 0.01

N2O 0.03 0.01 0.01 0.003 0.05

CO2 3105 945 1042 345 5437

SO2 0.10 0.03 0.03 0.01 0.17

PM10 3.0 0.9 0.2 0.1 4.2

PM2.5 2.9 0.9 0.2 0.1 4.1

BC 1.4 0.4 0.1 0.1 2.0

OC 0.6 0.2 0.1 0.1 1.0

Among two routes, Nida route (Sriboonrueng-Pratunam) dominated the total emission of

PM2.5 (76.5% of total emission) where Golden Mountain route (Phan Falilat-Pratunam)

contributed about 23.5% of total emission. PM2.5 emission mainly contributed during

cruising condition which contributed to 3.8 tons/year while emission during idling condition

was 0.3 tons/year. For CO, the emission during idling condition (24.8 tons/year) was higher

than the emission during cruising condition (24.5 tons/year). Note that Saen Saep canal had

more piers for boats to stop and idling than Chao Phraya river.

Figure 4.4 illustrates the share of total emission of CO and PM2.5 from two routes of Saen

Saep boats (other pollutants showed similar pattern as provided in Appendix 2).

Figure 4.4 Emission share of CO and PM2.5 of Saen Saep boats

From Figure 4.4, Nida route (Sriboonrueng-Pratunam) accounted for 77% of both CO and

PM2.5 emission. The emission share between cruising and idling of CO and PM2.5 of Saen

28

Saep boats are presented in Figure 4.5 and 4.6, respectively. The emission shares between

cruising and idling of other pollutants are provided in Appendix 2.

Figure 4.5 Emission share between cruising and idling conditions of CO for two routes of

Saen Saep boats

For the CO emission (Figure 4.5), Nida route (Sriboonrueng-Pratunam) was the main emitter

with 77.4% (38.1% cruising and 39.3% idling) of total emission. Golden Mountain Route

contributed 22.7% of total CO emission (11.6% cruising and 11.1% idling).

29

Figure 4.6 Emission share between cruising and idling conditions of PM2.5 for two routes

of Saen Saep boats

From Figure 4.6, cruising emission dominated the emission of PM2.5 which was different

from the case of CO emission (Figure 4.5). The total PM2.5 emission was primality from

Nida route (Sriboonrueng-Pratunam) which contributed 76.5% of total emission (70.7%

cruising and 5.9% idling).

30

c) Total annual emissions of cross river ferries in 2019

The emission was calculated from twenty-three routes of the cross river ferries. The annual emission of cross river ferries is presented in Table

4.3.

Table 4.3 Annual emission of the cross river ferries by different routes (tons/year), 2019

Routes HC CO NOx NMHC CH4 NH3 N2O CO2 SO2 PM10 PM2.5 BC OC

Pakkret-

Wat Toey 0.2 1.5 2.3 0.2 0.01 0.0001 0.001 136.0 0.004 0.1 0.1 0.04 0.01

Pakkret-

Watchareewongse 0.2 2.1 2.3 0.1 0.01 0.0001 0.001 130.7 0.004 0.03 0.03 0.02 0.004

Koh Kret-

Wat Sanamnuea 0.7 7.3 9.3 0.6 0.03 0.001 0.005 546.2 0.01 0.2 0.2 0.1 0.1

Nonthaburi-

Bangsrimueng 0.6 6.4 8.4 0.6 0.02 0.001 0.004 494.7 0.02 0.2 0.2 0.1 0.1

Thewes-Bowornmongkon 0.1 0.6 0.9 0.1 0.00 0.0001 0.001 55.4 0.002 0.04 0.03 0.01 0.001

Thewes-Karuhabodee 0.2 1.7 2.2 0.2 0.01 0.0001 0.001 129.9 0.004 0.1 0.1 0.0 0.01

Tha Phrachan-Wang

Lang 0.3 3.0 4.0 0.3 0.01 0.0001 0.003 232.5 0.01 0.1 0.1 0.1 0.02

Wang Lang-Maharaj 0.2 2.0 2.7 0.2 0.01 0.0001 0.002 160.2 0.01 0.1 0.1 0.0 0.02

Wang Lang-

Tha Chang 0.3 2.9 4.2 0.3 0.02 0.0001 0.002 251.0 0.01 0.1 0.1 0.1 0.03

Wat Rakang-

Tha Chang 0.2 1.9 2.5 0.2 0.01 0.0001 0.001 148.2 0.00 0.1 0.1 0.0 0.02

Tha Tien-

Wat Arun 0.4 4.5 5.5 0.4 0.01 0.001 0.003 321.3 0.01 0.1 0.1 0.1 0.02

Pakklong-Kallayanimit 0.1 1.3 1.9 0.1 0.01 0.0001 0.001 110.9 0.00 0.1 0.1 0.0 0.01

31

Table 4.3 Annual emission of the cross river ferries by different routes (tons/year), 2019 (continue)

Routes HC CO NOx NMHC CH4 NH3 N2O CO2 SO2 PM10 PM2.5 BC OC

Rachawongse-Dindang 0.2 2.4 3.1 0.2 0.01 0.0001 0.001 181.5 0.01 0.1 0.1 0.0 0.02

Sri Phraya-Klongsan 0.7 7.0 9.4 0.6 0.03 0.001 0.005 551.6 0.02 0.3 0.3 0.1 0.1

Oriental-

Wat Suwan 0.2 2.3 3.3 0.2 0.01 0.0001 0.002 196.9 0.01 0.1 0.1 0.1 0.02

Sathorn-Pepsi 0.3 2.8 4.0 0.3 0.02 0.0001 0.002 238.4 0.01 0.1 0.1 0.1 0.03

Sathupradit-Klong Lat

luang 0.3 3.2 4.5 0.3 0.02 0.0001 0.002 263.2 0.01 0.1 0.1 0.1 0.03

Rama 3-

Klong Latpo 0.3 3.2 4.3 0.3 0.01 0.0001 0.003 252.5 0.01 0.1 0.1 0.1 0.03

Klong Toei-Tuapai 0.0 0.1 0.2 0.0 0.00 0.0001 0.000 13.4 0.0004 0.01 0.01 0.01 0.000

Bangna-Taluen 0.1 0.7 1.0 0.1 0.00 0.0001 0.001 58.2 0.002 0.04 0.03 0.01 0.001

Bangnanok-

Bangnampuengnok 0.3 2.6 3.8 0.3 0.02 0.0001 0.002 225.0 0.01 0.1 0.1 0.1 0.03

Petra-Phra Pradang 0.4 3.9 5.6 0.4 0.02 0.001 0.003 331.7 0.01 0.2 0.2 0.1 0.04

Wiboonsri-Phra

Samutchedi 0.6 5.0 7.9 0.6 0.02 0.001 0.004 473.6 0.02 0.3 0.3 0.2 0.1

Total emission

(ton/year) 6.7 68.1 93.4 6.4 0.3 0.01 0.05 5503 0.2 2.7 2.6 1.3 0.6

Among the twenty-three routes, five routes which mainly dominated the emission were Sri Phraya-Klongsan route, Nonthaburi-Bangsrimuang,

Koh Kret-Wat Sananua, Wiboonsri-Phra Samutchedee, and Petra-Phra Pradang routes.

32

Figure 4.7 illustrates the share of CO and PM2.5 from five routes which mainly dominated

the emission of Cross river ferries. For other pollutants, the emissions were provided in

Appendix 2.

Figure 4.7 Emission share of CO and PM2.5 from five routes which mainly contributed the

total emission of cross river ferries

Form Figure 4.7, the highest emission routes were Koh Kret-Wat Sanamnua route which

accounted to 10.7% of CO emission and Wiboonsri-Phra Samutchedee route which

accounted to 10.9% of PM2.5 emission. The emission share between cruising and idling of

CO and PM2.5 of the Chao Phraya boat are presented in Figure 4.8 and 4.9, respectively.

Figure 4.8 Emission share between cruising and idling conditions of CO for five highest

emission routes of cross river ferries

Koh Kret-Wat Sanamnua, 10.65%

Sri Phraya-Klongsan, 10.30%

Nonthaburi-

Bangsrimuang, 9.36%

Wiboonsri-Phra

Samutchedee, 7.39%

Tha Tien-Wat Arun,

6.54%

Others, 55.76%

COWiboonsri-Phra Samutchedee, 10.85%

Sri Phraya-Klongsan, 9.69%

Nonthaburi-

Bangsrimuang, 8.53%

Koh Kret-Wat

Sanamnua, 8.53%

Petra-Phra Pradang,

6.59%

Others, 55.76%

PM2.5

33

For the CO emission (Figure 4.8), Koh Kret-Wat Sanamnua route was the main emitter with

10.7% (1.3% cruising and 8.8% idling) of total emission, followed by 10.3% from Sri

Phraya-Klongsan (1.3% cruising and 9.4% idling), 9.4% from Nonthaburi-Bang Srimueng

(1.3% cruising and 1.8% idling), 7.4% from Wiboonsri-Phra Samutchedee (2.2% cruising

and 5.2% idling), and 6.5% from Tha Tien-Wat Arun (0.6% cruising and 5.9% idling).

Figure 4.9 Emission share between cruising and idling conditions of PM2.5 for five highest

emission routes of cross river ferries

From Figure 4.9, cruising emission dominated the total emission, but the ratio between

cruising and idling emission were different among routes due to the times when each boat

stopped and waited at the piers. Total PM2.5 emission was primality from Wiboonsri-Phra

Samutchedee route which contributed 10.8% (8.9% cruising and 1.9% idling), followed by

9.7% from Sri Phraya-Klongsan route (6.2% cruising and 3.5% idling), 8.5% from

Nonthaburi-Bangsrimueng route (5.4% cruising and 3.1% idling ), 8.5% from Koh-Kret-

Wat Sanamnua route (5.0% cruising and 3.5% idling ), and 6.6% from Petra-Phra Pradang

route (3.9% cruising and 2.7% idling ).

34

4.1.2 Annual emission of inland water transportation in Bangkok in 2019

Table 4.4 provides emission of all thirteen pollutants for the three groups of boats in this

study.

Table 4.4 Annual emission of inland water transport in Bangkok (tons/year), 2019

Pollutants

Total emission in tons/year

Chao Phraya

boats Saen Saep boats

Cross river

ferries Total emission

HC 10.2 7.2 6.7 24.1

CO 78.4 46.4 68.1 192.9

NOx 134.4 89.8 93.4 317.6

NMHC 9.8 6.8 6.4 23

CH4 0.3 0.3 0.3 0.9

NH3 0.01 0.01 0.01 0.03

N2O 0.09 0.05 0.05 0.2

CO2 8071 5437 5503 19011

SO2 0.2 0.2 0.2 0.6

PM10 5.6 4.2 2.7 12.5

PM2.5 5.4 4.1 2.6 12.1

BC 2.7 2.0 1.3 6.1

OC 1 0.8 0.6 2.4

The total HC, CO, NOx, NMHC, CH4, NH3, N2O, CO2, SO2, PM10, PM2.5, BC, OC emissions

in 2019 from inland water transport in Bangkok were 24.1, 192.9, 317.6, 23, 0.9, 0.03, 0.2,

19011, 0.6, 12.5, 12.1, 6.1 and 2.4 tons/year, respectively. Chao Phraya boats dominated

total emissions in the domain.

PM2.5 emission of Chao Phraya boats was 5.4 tons/year, followed by Saen Saep boats (4.1

tons/year) and Cross river ferries (2.6 tons/year). For CO emission which mainly contributed

while idling, Chao Phraya boats also largely dominated the total emission with 78.4

tons/year.

Figure 4.10 Total emission share of CO and PM2.5 for Chao Phraya boats, Saen Saep boats

and cross river ferries

35

From Figure 4.10, Chao Phraya boats accounted for 40.0% and 44.9% of CO and PM2.5

emission, respectively. The emission share between cruising and idling of CO and PM2.5 of

three boat groups are presented in Figure 4.11 and 4.12, respectively.

Figure 4.11 CO emission share between cruising and idling conditions

For CO emission (Figure 4.11), Chao Phraya boats were the main emitter with 40.6% of

total emission (28.4% cruising and 12.3% idling), followed by cross river ferries with 35.3%

(6.4% cruising and 28.9% idling), and Saen Saep boats with 24.1% (12.7% cruising and

11.4% idling). When considering the ratio between cruising and idling, the ratios of CO were

2.3:1, 1.1:1 and 0.2:1 for Chao Phraya boats, Saen Saep boats, and cross river ferries,

respectively. CO emission of cross river ferries during idling was significantly higher than

the others since the cross river ferries had more routes and shorter distance between piers,

making them spending long time for idling. Moreover, some routes spent more time waiting

(idling) at pier than cruising time.

0

5

10

15

20

25

30

35

40

45

Chao Phraya boats, 40.64% Saen Saep boats, 24.06% Cross river ferries, 35.30%

28.38% 12.7% 6.43%

12.27%

11.35% 28.87%

Perc

enta

ge (

%)

CO

Cruising Idling

36

Figure 4.12 PM2.5 Emission share between cruising and idling conditions

From Figure 4.12, total PM2.5 emission was primarily from Chao Phraya boats which

contributed 44.9% (42% cruising and 2.9% idling), followed by Saen Saep boats which

contributed 33.8% (31.2% cruising and 2.6% idling), and cross river ferries which

contributed 21.3% (14.6% cruising and 6.7% idling).

The ratios between cruising and idling emission of PM2.5 were 14.4:1, 11.8:1 and 2.2:1 for

Chao Phraya boats, Saen Saep boats and cross river ferries, respectively. Cruising emission

from Chao Phraya boats was much higher than idling emission since they had the longest

traveling distance (5-24 km) among the boat groups, and some routes had the total cruising

time approximately 6 times higher than idling time for one trip.

4.2 Emission comparison

The emission in this project was compared with the emission from other studies. However,

there was no direct comparison of emission from this study with the other studies since the

scopes were not the same.

- Kim Oanh (2020): emission inventory includes not only public inland water

transport, but also all water transport (public and goods transport) in Bangkok.

- GAINS (2020): emission inventory includes all on-road transport in Bangkok.

Table 4.5 shows the comparison of the emission inventories developed for on-road mobile

source in Bangkok, i.e. GAINS (2020), emission inventory developed for all inland water

transport in Bangkok, i.e. Kim Oanh, 2020, and emission inventory developed in this project

(only public inland water transport).

0

5

10

15

20

25

30

35

40

45

Chao Phraya boats, 44.89% Saen Saep boats, 33.79% Cross river ferries, 21.32%

41.97%31.15%

14.62%

2.92%

2.64%

6.69%

Perc

enta

ge (

%)

PM2.5

Cruising Idling

37

Table 4.5 Emission comparison between this study and other studies

Pollutants GAINS (2020)

(ton/year)

Kim Oanh (2020)

(tons/year)

This study

(tons/year)

Emission year 2020 2018 2019

Sector On-road vehicles in

Bangkok

Public and goods

inland water transport

in Bangkok

Public inland water

transport in Bangkok

HC N/A 98 24

CO 67760 243 193

NOx 41470 674 317

NMHC N/A 95 23

CH4 2460 3 0.9

NH3 210 64 0.03

N2O 170 19 0.2

CO2 4,430,000 N/A 19011

SO2 90 N/A 0.6

PM10 2500 73 13

PM2.5 2180 70 12

BC 1240 28 6

OC 740 11 2 N/A=not available

The comparison of emission between Kim Oanh (2020) and this study showed that the

emission estimated in Kim Oanh (2020) was higher than the emission in this project by 1 to

5 times, except CH4 and N2O. In particular, PM2.5 and CO emission from this project were

about 20% and 80% of the PM2.5 and CO emission from Kim Oanh (2020). The major cause

of the differences was that Kim Oanh (2020) included emission from all inland water

transport (public and goods transport), but this study included only emission from public

inland water transport. Also, activity data from Kim Oanh (2020) was estimated from the

projection of total fuel consumption of inland water activities in Thailand to the fuel

consumption in Bangkok while the fuel consumption from survey was used in this study.

From Table 4.5, when comparing emission estimation in this project with the emission from

GAINS (2020) which represented total on-road emission in Bangkok, the emission from this

project was approximately 0.01-0.8% of the emission from on-road transport. Thus, it can

be concluded that emission from the inland water transports contributed less than 1% of total

on-road transport in Bangkok. However, with the limited operating routes of the inland water

transport, the emission from inland water transport was concentrated along the Chao Phraya

river and Saen Seap canal which is different from the emission from on-road vehicles which

contributed to all over Bangkok area. Thus, the impact area of emission from inland water

transport was concentrated on the local communities along the water ways, and it was

explained by the dispersion model results in Section 4.4.

To put the emission comparison on the same scale, Table 4.6 shows the emission comparison

between public boat emission in this project and on-road public transport in Bangkok in term

of grams of emission per kilometer per passenger.

38

Table 4.6 Emission comparison between this study and on-road vehicles in Bangkok (g/km-

passenger)

Pollutants Kim Oanh (2020)

(g/km-passenger)

This study

(g/km-passenger)

Emission

year 2018 2019

Sector On-road vehicles in

Bangkok Public inland water transport in Bangkok

Type Van Bus Chao Phraya

boats

Saen Saep

boats

Cross river

ferries

HC N/A N/A 0.01 0.01 0.72

CO 0.65 0.53 0.06 0.05 7.40

NOx 0.07 0.10 0.12 0.10 10.20

NMHC 0.03 0.06 0.009 0.007 0.700

CH4 0.14 0.02 0.001 0.001 0.026

NH3 0.004 0.001 0.001 0.001 0.001

N2O 0.001 0.001 0.001 0.001 0.005

CO2 16 5 7 6 602

SO2 0.001 0.005 0.001 0.001 0.018

PM10 0.003 0.007 0.006 0.005 0.296

PM2.5 0.003 0.007 0.006 0.004 0.287

BC N/A N/A 0.003 0.002 0.144

OC N/A N/A 0.001 0.001 0.057 N/A=not available

Note: Van = 13 passengers, not included driver, Bus = 65 passengers (average between 50 and 80), Chao Phraya boats and

Saen Saep boats = 70 passengers, not included driver and ticket taker (average between 60 and 80), and Cross river ferries

= 40 passengers, not included driver and ticket taker (average between 30 and 50).

From Table 4.6, the emission intensity in term of g/km-passenger of Chao Phraya boats and

Sean Saep boats were almost the same or slightly lower than those of vans and buses.

However, the emission intensity in term of g/km-passenger of Cross river ferries was much

higher than those of vans and buses due to short operating distances of the ferries. However,

when comparing the emission per passenger with the emission from buses with different

standards, this emission of inland water boats was the same level of the emission of Euro 2

buses while the majority (about 36%) of the bus in Bangkok are Euro 3. As such, inland

water boats emit more PM2.5 per passenger per kilometer than the majority of buses in

Bangkok.

4.3 Spatial and temporal distribution of emission

4.3.1 Spatial emission distribution

Spatial distribution of emission in this project was done in ArcMap for the total, cruising

and idling emission in tons/year in the resolution of 500 x 500 m2 grid map. The spatial

distribution of CO and PM2.5 emission are provided in Figure 4.13 and 4.14, respectively.

The spatial distribution of other pollutants are provided in Appendix 3.

39

-

(1) (2) (3)

Figure 4.13 CO emission from inland water transport in tons/year in a grid map of 500x500 m2:

(1) cruising condition (2) idling condition (3) total emission

40

(1) (2) (3)

Figure 4.14 PM2.5 emission from inland water transport in tons/year in a grid map of 500x500 m2:

(1) cruising condition (2) idling condition (3) total emission

41

From Figure 4.13 and 4.14, the emission distribution patterns are nearly similar between the

two pollutants. The observations were as follow:

- The emission in the red, orange and yellow grids showed high emission intensity area

from Chao Phraya river boats since these piers had most frequent trips (green flag,

orange flag, yellow flag, no flag, gold flag, blue flag boats, and four routes of shuttle

boat). Moreover, these piers were in the vicinity of the tourist routes, and these piers

were functioned as the interchange piers from Chao Phraya boats to cross river ferries

and BTS sky train to downtown. High emission intensity area of the Saen Saep canal

boats were observed in the yellow grids contributed at the piers which were at the final

destination of each route and the interchange piers.

- For the other grids with low emission, low emission intensity was observed because

some flags of the Chao Phraya boats did not operate every day, such as Green flag, No

flag and Yellow flag boats, resulting in lower emission among those piers. Also, the

green grid on the south of the river line in Figure 4.13 and 4.14 referred to emission from

the cross river ferries which showed no connection between these piers to the other parts

of the map.

When comparing emission between Chao Phraya river and Saen Saep canal, the Chao

Phraya river has significantly higher emission intensity than emission intensity of the Saen

Saep canal due to the fact that Chao Phraya river had many more boats. Although the Saen

Saen canal is located near downtown, but the Chao Phraya river has more tourist attraction

points than the Saen Saep canal.

4.3.2 Temporal emission distribution

There was no significant monthly variation observed during the survey and by reviewing the

data from the Marine Department. Thus, this project provided the temporal distribution of

emission in term of hourly emission over the survey period. Figure 4.15 and 4.16 provide

PM2.5 and CO emission of cruising and idling condition during weekday and weekend.

42

Figure 4.15 Temporal distribution of PM2.5 emission during cruising and idling condition during weekday and weekend

(Note: All four graphs were provided in different scales)

43

Figure 4.16 Temporal distribution of CO emission during cruising and idling condition during weekday and weekend

(Note: All four graphs were provided in different scales)

44

Overall, during 6.00-9.00 a.m. and 3.00-7.00 p.m. on the weekday were rush hours for

commuters, resulting in higher frequency of boat trips to accommodate more

passengers/commuters. Thus, the higher emission was also observed during these rush hours.

The boat group which dominated the PM2.5 emission was the Chao Phraya boats during

cruising condition, while the boat group which dominated the CO emission was the cross

river ferries during idling condition.

During the weekend, there was no pattern of rush hours for Chao Phraya boats. The emission

of Chao Phraya river boats started to increase around 8.00-9.00 a.m. and continued about the

same level until 6.00 p.m. This emission pattern was observed since the tourist routes which

included Blue flag boats (tourist boats), Gold flag and shuttle boats started operating for

Icon-Siam destination during the weekend. For Cross river ferries and Saen Saep canal boats,

the emission pattern showed two peaks, one in the morning and another in the afternoon

which were the same as the pattern observed during the weekday.

4.4 Inland water transport emission impact area

The AERMOD model was run and provided maximum 24-hr average PM2.5 concentration

as presented in Figure 4.17 (right).

Figure 4.17 Inland water transport emission impact area: (Left) PM2.5 emission inventory;

(Right) Max. 24-hr average PM2.5 concentration in μg m3⁄

From Figure 4.17, inland water transport in this study contributed to the maximum of 1-4

μg m3⁄ of 24-hr average PM2.5concentration in the area of 1 km away from the river and

canal while the lower concentration is expanded to 4-5 km away from the river. Thus,

Maximum 24-hr

average PM2.5

concentration in μg m3⁄

45

emission from inland water transport contribute more to local community along the water

ways and their passengers taking boats for daily commute.

4.5 Excel emission calculation template for inland water transport in Bangkok

The emission inventory template for inland water transport in an existing ABC-EIM for

Bangkok has been updated with the information collected in this study (Figure 4.18).

Figure 4.18 Example of an updated version of template for inland water calculation

The updated version added the following information to the template:

- Two engine sizes (100 < hp < 300 and 300 < hp < 750) which are commonly used for

inland water transport in Bangkok;

- Emission of all thirteen pollutants, including HC, CO, NOx, NMHC, CH4, NH3, N2O,

CO2, SO2, PM10, PM2.5, BC, OC;

- Input cell for Sulfur content in fuel which affected SO2, PM10, PM2.5, BC, OC emission;

- Emission factors for emission standards of Tier 0 to Tier 4;

- Separated calculation between cruising and idling emission.

According to the previous version of the calculation template, users were required to fill in

activity data and chose the emission factor values. When compared with an updated version,

beside activity data and emission factor values, users had more information to select, i.e. the

engine size, engine technology and fuel quality, cruising and idling condition. However, the

template, even though include lots of parameters in an updated version, it was still based on

fuel consumption as the only required input for easy update and use by different users. The

other inputs were provided as suggested values in the template which could be selected by

the users.

46

4.6 Emission control strategies

4.6.1 Reviewing the existing emission reduction measures

By reviewing the emission reduction practices obtained during the secondary data collection,

engine maintenance, i.e. having a checklist and a system repaired, were the only options

currently implemented in the Chao Phraya express boat, the Cross river ferries and the Saen

Saep boats.

Based on the national agenda for PM2.5 concentration reduction (PCD & MNRE, 2019),

emission reduction measures of the inland water transport have not been included in the

report. However, there was a list of emission reduction measures for on-road transport which

included: 1) roadside inspection; 2) lower sulfur content in fuel; and 3) regulating Euro VI

engine standard. Thus, in this study, emission reduction scenarios were developed based on

these three measures.

4.6.2 Emission reduction scenarios

This study investigated three emission reduction scenarios for inland water transport which

were:

- Scenario 1: Changing engines to Tier 4 technology and using 10 ppm sulfur fuel;

- Scenario 2: Using engine with current technology (Tier 0), but using 10 ppm sulfur fuel

(the current sulfur content in fuel was 50 ppm);

- Scenario 3: Using engine with current technology (Tier 0), but reducing idling time by

50%.

The PM2.5, CO and SO2 emission reduction from the three scenarios were provided in Table

4.7, Table 4.8 and Table 4.9, respectively.

Table 4.7 PM2.5 emission from the three emission reduction scenarios (tons/year)

Boat Groups Baseline

(2019)

S1:

Tier4+0.001%S

S2:

Tier0+0.001%S

S3: Tier 0+ 50%

Idling time

Chao Phraya

boats 5.4 0.1 5.3 5.2

Saen Saep boats 4.0 0.1 4.1 3.9

Cross river ferries 2.5 0.1 2.1 2.2

Total emission

(tons/year) 12.1 0.3 11.5 11.3

% Reduction

from baseline - 97.7% 4.5% 6.4%

From Table 4.7, PM2.5 emission of the first scenario were reduced by 97.7% from the

baseline. For the second and the third scenarios, PM2.5 emissions of Chao Phraya boats, Saen

Saep boats and cross river ferries didn’t change much from the baseline (about 5%

reduction).

47

It could be summarized that the PM2.5 emission was highly related to the engine technology.

In this scenario, replacing all Tier 0 by the cleanest engine technology (Tier 4), and using

low sulfur fuel (10 ppm) which was required for the use of Tier 4 engine, showed

dramatically reduction in PM2.5 emission. The other two scenarios, thus, do not contribute

much to the emission reduction of PM2.5 since the engines were still Tier 0 engines.

Table 4.8 CO emission from the three emission reduction scenarios (tons/year)

Boat Groups Baseline

(2019)

S1:

Tier4+0.001%S

S2:

Tier0+0.001%S

S3: Tier 0+ 50%

Idling time

Chao Phraya

boats 78.4 2.6 78.4 43.0

Saen Saep boats 46.4 1.7 46.4 35.4

Cross river ferries 68.1 7.9 68.1 39.9

Total emission

(tons/year) 192.9 12.2 192.9 118.3

% Reduction

from baseline - 93.7% 0% 38.6%

From Table 4.8, the highest emission reduction also found in scenario one (reaching 93.7%

of CO emission reduction). However, when considering the scenario three which the idling

time was reduced to 50%, CO emissions were reduced by 38.6% (from 192.9 tons/year to

118.34 tons/year). Since there was no cost involvement in this scenario, changing the current

operation practice by reducing the idling time could contribute significantly to the CO

emission reduction.

Table 4.9 SO2 Emission from the three emission reduction scenarios (tons/year)

Boat Groups Baseline

(2019)

S1:

Tier4+0.001%S

S2:

Tier0+0.001%S

S3: Tier 0+ 50%

Idling time

Chao Phraya

boats 0.2 0.06 0.2 0.2

Saen Saep boats 0.2 0.05 0.2 0.1

Cross river ferries 0.2 0.06 0.1 0.1

Total emission

(tons/year) 0.6 0.17 0.5 0.4

% Reduction

from baseline - 71.7% 16.7% 25.0%

From Table 4.18, SO2 emission of all boat groups was reduced by 71.7% (from 0.6 tons/year

to 0.17 tons/year) in the first scenario, 16.7% (from 0.6 tons/year to 0.5 tons/year) in the

second scenario, and 25% (from 0.6 tons/year to 0.45 tons/year) in the third scenario.

Moreover, reducing sulfur dioxide emission also contribute to an additional reduction of

secondary PM2.5 emission.

Although the first scenario still showed much higher emission reduction of SO2 compared

to other scenarios, but the cost associated with the first scenario was much more than the

cost of the other two scenarios. Thus, in this case, the combination of the policy between

scenario two and three which may require some investment (for fuel quality improvement),

can provide significant SO2 emission improvement.

48

4.6.3 Emission reduction policy recommendations

From the section 4.6.2, the emission reduction results from the three scenarios were analyzed

and used to provide recommendations for inland water transport emission management as

follow:

1. Immediate policies: Promoting inspection and maintenance as well as idling reduction

campaign;

2. Short-term policies (1-3 years): Using 10ppm sulfur fuel for inland water transport in

Bangkok;

3. Long-term policies (4-6 years): Limiting the ages of the engines for inland water

transport in Bangkok, and switching boat engines to Tier 4/Euro 6 or electric engines.

49

CHAPTER 5

SUMMARY AND LIMITATIONS

5.1 Summary

An emission inventory results in this project developed for the public inland water transport

activities in Bangkok in 2019. The survey of activity data which were engine load factor,

travelling distance, boat trips and operating time during cruising and idling was conducted

during October 2019 to February 2020. The emission factors were calculated based on the

methodology in USEPA (2010) which incorporated the effects of engine size, age, load

factor and sulfur content in fuel in Bangkok. The EI covered thirteen pollutants, including

HC, CO, NOx, NMHC, CH4, NH3, N2O, CO2, SO2, PM10, PM2.5, BC and OC. Thirteen routes

of Chao Phraya boats, two routes of Saen Saep boats and twenty-three routes of cross river

ferries were included in this study. Then, the emission was spatially distributed in the grid

of 500x500 m2 covering the study area. The temporal distribution of the emission was

developed in term of emission during different hours in a day while the monthly emission

was assumed to be constant. Finally, the policy recommendations were proposed based on

the three emission reduction scenarios in this study. The main conclusions of this project are

summarized below:

1. The emissions from public inland water transports in 2019 of HC, CO, NOx, NMHC,

CH4, NH3, N2O, CO2, SO2, PM10, PM2.5, BC and OC were 24.1, 192.9, 317.6, 23.0, 0.9,

0.03, 0.2, 19011, 0.6, 12.5, 12.1, 6.1 and 2.4 tons/year, respectively. Chao Phraya boats

were the major contributor to the total emission which accounted for 44.7% of PM2.5

emission and 40.7% of CO emission, followed by Saen Saep boats which contributed

33.8% and 24.1% of total PM2.5 and CO emission, and cross river ferries which

contributed 21.3% of PM2.5 emission and 35.3% of CO emission;

2. Emission inventory in this study was compared with the previous inventories, including

Kim Oanh (2020) which estimated emission from all inland water transport (passenger

and goods transport) in Bangkok. The PM2.5 and CO in this study (passenger boats only)

were estimated to be 20% and 80% of the PM2.5 and CO estimated for both inland water

passenger and good transports in Kim Oanh (2020). However, our AERMOD model

simulation showed that emission from inland water transport in this study could

contribute to the maximum of 1-4 μg m3⁄ of 24-hr average PM2.5 concentration in the

area of 1 km away from the canal and river, contributing to local community and

passengers taking boats for daily commute.

3. Spatial distribution of emission showed that emission in the Chao Phraya river was much

more than the emission in the Saen Saeb canal. The Chao Phraya river boats were the

main emission source since more boat trips were operated in the Chao Phraya, and its

piers were located in the vicinity area of tourist routes and connected to the BTS sky

train and downtown;

4. During the weekday during 6-9 a.m. and 3-7 p.m. (rush hours), the hourly emission was

higher than the hourly emission during any other times in the day. During the weekend,

overall emission was lower than the emission during weekday. Emission from the Chao

Phraya boats started to increase around 8-9 a.m. and stayed at the same level until 6 p.m.

due to the all-day operation of the Icon-Siam destination routes. For the cross river ferries

and the Saen Saep canal boats, the emission pattern peaked in the morning and afternoon,

50

the same as the pattern observed during the weekday, because some people lived in the

downtown area still commuted to work.

5. Emission inventory template in an existing AIT-EIM template for Bangkok has been

updated with the inland water transport emission calculation. The updated template

included more engine sizes which correspond to the engine sizes used in Bangkok, more

pollutants, the effects of sulfur content in fuel to emission, more engine emission

standards, and the separation of idling and cruising emission.

6. Three emission control scenarios were studied: Changing the boat engines to Tier 4 with

fuel sulfur content of 10 ppm, using current engines with fuel sulfur content of 10 ppm,

and reducing idling time to 50%. Thus, the policy recommendation were 1) Promoting

inspection and maintenance as well as idling reduction campaign; 2) Using 10ppm sulfur

fuel for inland water boats in Bangkok; and 3) Limiting boat engine ages and changing

boat engine to Tier4/Euro 6 or electric engine.

5.2 Recommendations for citizen and boat operator

1. At the busy piers with the idling time more than two minutes, the boat operator should

turn the engine off instead of idling.

2. The operator could provide better terminal operations to reduce idling time of the boats,

and reduce exposure time of the passengers.

3. Boat passengers should wear mask at the piers and on the boats to reduce personal

exposure to the pollutant.

4. People living along the San Seap canal and the Chao Phraya river, especially the area

close to the busy piers, should wear mask or use air purifier in the house during rush

hours.

5.3 Limitations in emission estimation

1. In this study, fuel consumption data was provided by the mechanics and the boat

operators. However, to get more accurate result, fuel consumption should be directly

measured by installing fuel meter on the boat engines.

2. The idling emission in this project was calculated based on the assumption that only one

boat waiting at the piers at the time. However, sometimes, there were more than one

boats waiting at the piers.

3. In this study, emission when starting the engine did not included in the calculation.

4. Emission should be measured locally for each group of boats validate the values used for

calculation to reduce uncertainties in emission estimation which will directly affect

emission factors and load factors used in the emission calculation.

51

REFERENCES

Browning, L., & Bailey, K. (2006). Current methodologies and best practices for preparing

port emission inventories [PowerPoint slides]. Retrieved from

https://www3.epa.gov/ttn/chief/conference/ei15/session1/browning_pres.pdf

Department of Drainage and Sewerage. (2020, April 9). FW.PKG.01 : จุด วัดสะพานพระราม 8.

Retrieved from http://weather.bangkok.go.th/flow/StationDetail?id=21

EMEP/EEA. (2016). EMEP/EEA air pollutant emission inventory guidebook. Copenhagen,

Denmark: European Environmental Agency.

Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS). (2019). Available at

https://gains.iiasa.ac.at/gains/emissions.ASN/index.menu?open=none&switch_version

=GAINS&switch_lang=lang_en. Accessed on November 2019.

Kim Oanh. (2020, January). PCD-AIT emission inventory database workbook version 1.0.

Bangkok, Thailand: Pollution Control Department

Park , S. S., Kozawa, K., Fruin , S., Mara, S., Hsu, Y. K., Jakober, C., . . . Herner, J. (2011).

Emission Factors for High-Emitting Vehicles Based on On-Road Measurements of

Individual Vehicle Exhaust with a Mobile Measurement Platform. Air & Waste

Management Association. doi:10.1080/10473289.2011.595981

Pollution Control Department and Ministry of Natural Resources and Environment. (2019).

Plan for solving dust pollution problems in Bangkok. Bangkok: Pollution Control

Department.

Shrestha, Ram & Oanh, Nguyen Thi & Shrestha, Rajendra & Rupakheti, Maheswar &

Rajbhandari, Salony & Agustian, Didin & Kanabkaew, Thongchai & Iyngararasan,

Mylvakanam. (2013). Atmospheric Brown Clouds Emission Inventory Manual.

United State Environmental Protection Agency. (2009). Current methodologies in preparing

mobile source port-related emission inventories. Retrieved from

https://www.epa.gov/sites/production/files/2016-06/documents/2009-port-inventory-

guidance.pdf

United States Environmental Protection Agency. (2002). Media Life, Annual Activity, and

Load Factor Values for Nonroad Engine Emissions Modeling. Washington, D.C:Author.

United States Environmental Protection Agency. (2010). Exhaust and Crankcase Emission

Factors for Nonroad Engine Modeling-Compression-Ignition. Washington, D.C: Author.

Winijkul, E. (2015). Multinational emission inventories for land-based nonroad engines and

residental combustion (Doctoral dissertation, University of Illinois at Urbana-

Champaign). Retrieved from https://www.ideals.illinois.edu/handle/2142/78373.

52

APPENDICES

53

APPENDIX 1. Survey of boat trips and information of each boat group

วนัเดอืนปี (Day) (Flag) สธีง 05.00-5.59 06.00-06.5907.00-07.5908.00-08.5909.00-09.5910.00-10.5911.00-11.5912.00-12.5913.00-13.5914.00-14.5915.00-15.5916.00-16.5917.00-17.5918.00-18.5919.00-19.5920.00-20.59 รวม

ธงเขยีว (Green Flag) 5 5 1 2 2 3 1 19

ธงสม้ (Orange Flag) 1 4 5 4 3 4 3 3 3 3 3 4 4 3 1 48

ประจ ำทำง (No Flag) 1 4 2 7

ธงเหลอืง (Yellow Flag) 5 4 3 3 5 3 23

ธงทอง (Gold Flag) 3 4 4 4 4 4 4 4 4 4 3 42

ธงฟ้ำ (Blue Flag) 3 6 8 4 4 4 5 6 4 4 4 52

ไอคอนสยำม-สีพ่ระยำ

(IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66

ไอคอนสยำม-วดัมว่งแค

(IconSiam-Wat Muangkae) 4 4 4 4 4 4 4 4 4 4 4 44

ไอคอนสยำม-สำทร

(IconSiam-Sathorn) 3 3 3 4 3 4 3 3 3 3 3 35

ไอคอนสยำม-ลง้1919-รำชวงศ ์

(IconSiam-Lhong1919-

Rachawongse)4 4 4 4 4 4 4 4 4 4 4 44

1 15 18 8 26 31 32 29 28 29 31 35 35 34 28 0 380

ธงเขยีว (Green Flag) 5 5 1 2 2 3 1 19

ธงสม้ (Orange Flag) 1 4 4 4 3 4 3 3 3 3 3 6 4 3 1 49

ประจ ำทำง (No Flag) 1 4 2 7

ธงเหลอืง (Yellow Flag) 5 4 3 3 5 3 23

ธงทอง (Gold Flag) 3 4 4 4 4 4 4 4 4 4 3 42

ธงฟ้ำ (Blue Flag) 3 6 4 4 4 4 5 6 4 4 4 48

ไอคอนสยำม-สีพ่ระยำ

(IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66

ไอคอนสยำม-วดัมว่งแค

(IconSiam-Wat Muangkae) 4 4 4 4 4 4 4 4 4 4 4 44

ไอคอนสยำม-สำทร

(IconSiam-Sathorn) 3 3 3 3 3 4 3 3 3 3 3 34

ไอคอนสยำม-ลง้1919-รำชวงศ ์

(IconSiam-Lhong1919-

Rachawongse)4 4 4 4 4 4 4 4 4 4 4 44

1 15 17 8 26 31 28 28 28 29 31 37 35 34 28 0 376

ธงเขยีว (Green Flag) 5 5 1 2 2 3 1 19

ธงสม้ (Orange Flag) 1 4 4 4 3 4 3 3 3 3 3 6 4 3 1 49

ประจ ำทำง (No Flag) 1 4 2 7

ธงเหลอืง (Yellow Flag) 5 4 3 3 5 3 23

ธงทอง (Gold Flag) 3 4 4 4 4 4 4 4 4 4 3 42

ธงฟ้ำ (Blue Flag) 3 6 5 4 4 4 5 6 4 4 4 49

ไอคอนสยำม-สีพ่ระยำ

(IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66

ไอคอนสยำม-วดัมว่งแค

(IconSiam-Wat Muangkae) 4 4 4 4 4 4 4 4 4 4 4 44

ไอคอนสยำม-สำทร

(IconSiam-Sathorn) 3 3 3 3 3 4 3 3 3 3 3 34

ไอคอนสยำม-ลง้1919-รำชวงศ ์

(IconSiam-Lhong1919-

Rachawongse)4 4 4 4 4 4 4 4 4 4 4 44

1 15 17 8 26 31 29 28 28 29 31 37 35 34 28 0 377

ธงเขยีว (Green Flag) 5 5 1 2 2 3 1 19

ธงสม้ (Orange Flag) 1 4 3 4 3 4 3 3 3 3 3 6 4 3 1 48

ประจ ำทำง (No Flag) 1 4 2 7

ธงเหลอืง (Yellow Flag) 5 4 3 3 5 3 23

ธงทอง (Gold Flag) 3 4 4 4 4 4 4 4 4 4 3 42

ธงฟ้ำ (Blue Flag) 3 3 5 4 4 4 5 6 4 4 4 46

ไอคอนสยำม-สีพ่ระยำ

(IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66

ไอคอนสยำม-วดัมว่งแค

(IconSiam-Wat Muangkae) 4 4 4 4 4 4 4 4 4 4 4 44

ไอคอนสยำม-สำทร

(IconSiam-Sathorn) 3 3 3 3 3 4 3 3 3 3 3 34

ไอคอนสยำม-ลง้1919-รำชวงศ ์

(IconSiam-Lhong1919-

Rachawongse)4 4 4 4 4 4 4 4 4 4 4 44

1 15 16 8 26 28 29 28 28 29 31 37 35 34 28 0 373

ธงเขยีว (Green Flag) 5 5 1 2 2 3 1 19

ธงสม้ (Orange Flag) 1 4 4 4 3 4 3 3 3 3 3 6 4 3 1 49

ประจ ำทำง (No Flag) 1 4 2 7

ธงเหลอืง (Yellow Flag) 5 4 3 3 5 3 23

ธงทอง (Gold Flag) 3 4 4 4 4 4 4 4 4 4 3 42

ธงฟ้ำ (Blue Flag) 3 4 5 4 4 4 5 6 4 4 4 47

ไอคอนสยำม-สีพ่ระยำ

(IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66

ไอคอนสยำม-วดัมว่งแค

(IconSiam-Wat Muangkae) 4 4 4 4 4 4 4 4 4 4 4 44

ไอคอนสยำม-สำทร

(IconSiam-Sathorn) 3 3 3 3 3 4 3 3 3 3 3 34

ไอคอนสยำม-ลง้1919-รำชวงศ ์

(IconSiam-Lhong1919-

Rachawongse)4 4 4 4 4 4 4 4 4 4 4 44

1 15 17 8 26 29 29 28 28 29 31 37 35 34 28 0 375

5 75 85 40 130 150 147 141 140 145 155 183 175 170 140 0 1881

ธงเขยีว (Green Flag) 0

ธงสม้ (Orange Flag) 4 5 6 5 6 6 6 6 6 6 6 6 6 2 76

ประจ ำทำง (No Flag) 0

ธงเหลอืง (Yellow Flag) 0

ธงทอง (Gold Flag) 3 4 4 4 4 4 4 4 4 4 3 42

ธงฟ้ำ (Blue Flag) 3 6 8 5 4 4 5 6 5 3 2 51

ไอคอนสยำม-สีพ่ระยำ

(IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66

ไอคอนสยำม-วดัมว่งแค

(IconSiam-Wat Muangkae) 4 4 4 4 4 4 4 4 4 4 4 44

ไอคอนสยำม-สำทร

(IconSiam-Sathorn) 3 3 3 4 3 4 3 3 3 3 3 35

ไอคอนสยำม-ลง้1919-รำชวงศ ์

(IconSiam-Lhong1919-

Rachawongse)4 4 4 4 4 4 4 4 4 4 4 44

0 4 5 6 28 33 35 33 31 32 32 33 32 30 24 0 358

ธงเขยีว (Green Flag) 0

ธงสม้ (Orange Flag) 4 5 6 5 6 6 6 6 6 6 6 6 6 2 76

ประจ ำทำง (No Flag) 0

ธงเหลอืง (Yellow Flag) 0

ธงทอง (Gold Flag) 3 4 4 4 4 4 4 4 4 4 3 42

ธงฟ้ำ (Blue Flag) 3 6 8 5 4 4 5 6 5 3 2 51

ไอคอนสยำม-สีพ่ระยำ

(IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66

ไอคอนสยำม-วดัมว่งแค

(IconSiam-Wat Muangkae) 4 4 4 4 4 4 4 4 4 4 4 44

ไอคอนสยำม-สำทร

(IconSiam-Sathorn) 3 3 3 3 3 4 3 3 3 3 3 34

ไอคอนสยำม-ลง้1919-รำชวงศ ์

(IconSiam-Lhong1919-

Rachawongse)4 4 4 4 4 4 4 4 4 4 4 44

0 4 5 6 28 33 35 32 31 32 32 33 32 30 24 0 357

0 8 10 12 56 66 70 65 62 64 64 66 64 60 48 0 715

รวม

รวม

รวม

วนัจันทร(์Monday)

วนัอังคำร(Tuesday)

วนัพธุ(Wednesday)

รวม

รวม

รวม

วนัพฤหัส(Thrusday)

รวมวนัรำชกำร

รวมวนัหยดุรำชกำร

วนัศกุร(์Friday)

วนัเสำร(์Saturday)

วนัอำทติย(์Sunday)

รวม

54

APPENDIX 1 (Continued)

(Day)วันที ่ 05.00-05.59 06.00-06.59 07.00-07.59 08.00-08.59 09.00-09.59 10.00-10.59 11.00-11.59 12.00-12.59 13.00-13.59 14.00-14.59 15.00-15.59 16.00-16.59 17.00-17.59 18.00-18.59 19.00-19.59 20.00-20.59 (Total)รวม

33 156 149 115 59 49 43 46

34323431374594132142

171

861

7 27 27 19 9 9 5 6 6 6 14 17 7 6 6

1634389366

169

8 30 26 17 9 6 6 6 6 6 14 18 8 7 3 170

180

6 30 30 17 9 6 6 6 6 6 14 17 8 7 3 171

2

6 29 28 19 9 8 7 8 7 8 12 22 7 8 2

8 7 8 7 8 12 19 8 6

(Total trips in one

week)รวมทัง้ส ิน้

12 12 12 12 12 14

44 46 78 107 52 40 984

6 7 9

6

6 26

77

(Total trips of

weekend) รวม

วันหยดุรำชกำร

14 17 21 14 12

6 6 6 6 6 1

14 6 172

(Sunday)วันอำทติย์

21 22 9

6 6 6 6

(Total trips of

weekday)รวมวันรำชกำร

(Saturday) วันเสำร์ 8 10 12

33

(The boat trip of inbound of Saen Saep boats) จ ำนวนเทีย่วเรอืโดยสำรคลองแสนแสบจ ำแนกตำมเวลำและวนัทีส่ ำรวจ (ขำลอ่ง) (สำยนดิำ้)(ศรบีญุเรอืง-ประตนู ำ้)(หลงัคำสงู)

(Monday) วันจันทร ์

(Tuesday) วันอังคำร

(Wednesday) วันพธุ

(Thursday)วันพฤหัสบดี

(Friday)วันศกุร์

956 8 8 58 6 6 6 6

(Day)วันที ่ 05.00-05.59 06.00-06.59 07.00-07.59 08.00-08.59 09.00-09.59 10.00-10.59 11.00-11.59 12.00-12.59 13.00-13.59 14.00-14.59 15.00-15.59 16.00-16.59 17.00-17.59 18.00-18.59 19.00-19.59 20.00-20.59 รวม

33 37 88 118 97 81 47

6 7 18 23 22 16 8

(Total trips in one

week)รวมทัง้ส ิน้808

776

23 37 41 63 52 45 45 47 45 50 100 141 119

20 29 32 53 41 33 33 34

12 12 13 12 13 12

4 6 5 10 8 5 7 6 6 7 18 20 18 18 10 148

157

3 6 6 9 9 6 6 6 6 7 18 23 22 16 11

5 7 7 12 8 6 6 6

154

158

4 7 5 9 8 8 7 8 8 8 17 27 18 16 9 159

4 3 9 13

(The boat trip of outbound of Saen Saep boats)จ ำนวนเทีย่วเรอืโดยสำรคลองแสนแสบจ ำแนกตำมเวลำและวนัทีส่ ำรวจ (ขำขึน้) (สำยนดิำ้)(ประตนู ำ้-ศรบีญุเรอืง)(หลงัคำสงู)

76

(Total trips of

weekend) รวม

วันหยดุรำชกำร

3 8 9 10 11

7 6 6 6 10 10

23 22 160

(Sunday)วันอำทติย์ 1 4 4

(Total trips of

weekday)รวมวันรำชกำร

(Saturday) วันเสำร์ 2 4 5

(Monday) วันจันทร ์

(Tuesday) วันอังคำร

(Wednesday) วันพธุ

(Thursday)วันพฤหัสบดี

87 6 6 6 6 6

23 5 6 6

8 8 7 8 7 8 17 25 17 15 9

(Friday)วันศกุร์

947 6 13 12

(Day)วันที ่ 05.00-05.59 06.00-06.59 07.00-07.59 08.00-08.59 09.00-09.59 10.00-10.59 11.00-11.59 12.00-12.59 13.00-13.59 14.00-14.59 15.00-15.59 16.00-16.59 17.00-17.59 18.00-18.59 19.00-19.59 20.00-20.59 รวม

(The boat trip of inbound of Saen Saep boats) (Golden Mountain Line)จ ำนวนเทีย่วเรอืโดยสำรคลองแสนแสบจ ำแนกตำมเวลำและวนัทีส่ ำรวจ (ขำลอ่ง) (สำยภเูขำทอง)(ประตนู ำ้-ผำ่นฟ้ำลลีำศ)

(หลงัคำเตีย้)

173

(Total trips of

weekend) รวม

วันหยดุรำชกำร

2 10 27 25 12 11 13

48 45 56 97 89 51 884(Total trips in one

week)รวมทัง้ส ิน้29 91 123 112 52 45 46

(Sunday)วันอำทติย์ 1 4 11 10 6 5 6

13 12 12 15 14 7

16 15 6 6 7 6 6 6 9 8 2 94

7 6 6 6 6 5 79

7 6 9 18 19 9 9 153(Friday)วันศกุร์ 3 14 20 19 8 6 6

154

(Thursday)วันพฤหัสบดี 6 20 20 16 9 6 6 6 6 8 14 14 8 7 146

10 15 13 9 5 149

(Wednesday) วันพธุ 4 17 21 18 8 7 5 6 7 8 21 18 7 7

6 17 17 19 7 8 8 8 7

(Monday) วันจันทร ์ 8 13 18 15 8 7 8 8 7 9

(Total trips of

weekday)รวมวันรำชกำร27 81 96 87 40 34 33 35 33 44 82 75 44 33 744

(Saturday) วันเสำร์ 1 6

14 11 11 5 1 143

(Tuesday) วันอังคำร

(Day)วันที ่ 05.00-05.59 06.00-06.59 07.00-07.59 08.00-08.59 09.00-09.59 10.00-10.59 11.00-11.59 12.00-12.59 13.00-13.59 14.00-14.59 15.00-15.59 16.00-16.59 17.00-17.59 18.00-18.59 19.00-19.59 20.00-20.59 รวม

จ ำนวนเทีย่วเรอืโดยสำรคลองแสนแสบจ ำแนกตำมเวลำและวนัทีส่ ำรวจ (ขำขึน้) (สำยภเูขำทอง)(ผำ่นฟ้ำลลีำศ-ประตนู ำ้)(หลงัคำเตีย้)

50 44 49 93 90 70 867(Total trips in one

week)รวมทัง้ส ิน้24 80 111 104 62 45 45

13 12 13 11 14 16 174

(Total trips of

weekend) รวม

วันหยดุรำชกำร

1 10 21 25 14 12 12

7 5 7 5 7 6 1 79(Sunday)วันอำทติย์ 1 4 8 10 6 6 6

6 7 6 6 7 10 4 100(Saturday) วันเสำร์ 6 13 15 8 6 6

37 32 36 82 76 54 33 726(Total trips of

weekday)รวมวันรำชกำร23 70 90 79 48 33 33

8 5 7 20 17 13 8 2 155(Friday)วันศกุร์ 3 14 20 18 9 6 5

6 6 7 14 14 10 6 2 143(Thursday)วันพฤหัสบดี 6 16 18 16 10 6 6

6 6 8 19 18 10 6 2 146(Wednesday) วันพธุ 4 12 18 15 10 6 6

8 8 7 16 14 10 6 1 147(Tuesday) วันอังคำร 5 14 18 15 10 8 7

(Monday) วันจันทร ์ 5 14 16 15 9 7 9 9 7 7 13 13 11 7 1 143

55

APPENDIX 1 (Continued)

เสน้ทำง(Routes) 05.00-5.59 06.00-06.5907.00-07.5908.00-08.5909.00-09.5910.00-10.5911.00-11.5912.00-12.5913.00-13.5914.00-14.5915.00-15.5916.00-16.5917.00-17.5918.00-18.5919.00-19.59 รวม

ปำกเกร็ด-วดัเตย

(Pakkret-Wat Toey)68 101 99 67 62 59 60 62 59 64 67 71 90 80 66 1075

ปำกเกร็ด-วชัรวีงศ ์

(Pakkret-Watchareewongse)66 91 93 66 68 60 60 65 60 65 62 81 82 70 69 1058

เกำะเกร็ด-วดัสนำมเหนือ

(Koh Kret-WatSanamnuea)40 100 114 95 90 90 90 90 90 90 90 90 90 90 70 1319

นนทบรุ-ีบำงศรเีมอืง

(Nonthaburi-Bangsrimueng)81 149 165 118 74 70 66 67 66 66 109 114 117 111 102 1475

เทเวศร-์วดับวรมงคล

(Thewes-Bowornmongkon)20 47 51 41 28 28 30 28 27 23 25 33 31 33 27 472

เทเวศร-์วดัคฤหบดี

(Thewes-Karuhabodee)0 40 36 29 23 22 20 20 16 14 18 23 21 20 19 321

ทำ่พระจันทร-์วงัหลัง

(Tha Phrachan-Wang Lang)36 38 34 36 37 44 43 39 43 38 40 42 44 31 29 574

วงัหลัง-มหำรำช

(Wang Lang-Maharaj)0 34 34 35 33 35 33 32 32 29 29 33 37 29 30 455

วงัหลัง-ทำ่ชำ้ง

(Wang Lang-Tha Chang)32 42 42 40 33 35 33 34 32 32 33 36 37 34 31 526

วดัระฆงั-ทำ่ชำ้ง

(Wat Rakang-Tha Chang)0 31 31 37 28 26 25 20 24 24 23 28 25 26 21 369

ทำ่เตยีน-วดัอรุณ

(Tha Tien-Wat Arun)18 34 44 41 39 42 46 44 41 40 43 43 40 39 32 586

ปำกคลองตลำด-วดักัลยำณมิติร

(Pakklong-Kallayanimit)26 29 32 23 25 21 22 23 21 25 25 29 26 24 26 377

รำชวงศ-์ดนิแดง

(Rachawongse-Dindang)7 53 80 72 50 43 39 40 41 38 46 53 78 64 39 743

สีพ่ระยำ-คลองสำน

(Sri Phraya-Klongsan)24 68 113 102 92 88 83 85 78 76 79 80 80 78 71 1197

โอเรยีนเตล-วดัสวุรรณ

(Oriental-Wat Suwan)0 66 79 75 50 47 41 43 43 40 50 60 66 33 30 723

สำทร-เป๊ปซี ่

(Sathorn-Pepsi)15 41 53 49 31 28 23 24 19 26 26 27 38 34 24 458

สำธปุระดษิฐ-์คลองลัดหลวง

(Sathupradit-Klong Latluang)6 28 31 31 21 18 16 20 17 16 16 20 25 24 18 307

คลองเตย-ท่ัวไป

(Klong Toei-Tua Pai)69 63 59 54 0 0 0 0 0 15 23 38 35 38 33 427

รำมำ3-คลองลัดโพธิ ์

(Rama 3-Klong Latpo)20 38 46 41 26 22 24 22 25 29 33 22 37 38 30 453

บำงนำ-ตำเลือ่น

(Bangna-Taluen)8 12 11 20 9 8 8 7 7 7 20 18 17 20 12 184

บำงนำนอก-บำงน ้ำผึง้นอก

(Bangnanok-Bangnampuengnok)26 40 63 48 26 25 25 24 27 25 34 32 45 41 29 510

เภตรำ-พระประแดง

(Petra-Phra Pradang)51 74 77 57 39 38 41 40 38 41 61 68 77 68 44 814

วบิลูยศ์ร-ีพระสมทุรเจดยี์

(Wiboonsri-Pra Samutchedee)47 71 71 53 48 31 30 23 28 28 46 50 54 58 56 694

56

APPENDIX 1 (Continued)

No. Boat

number

Boat size Engine

Passenger Long

(m.)

Width

(m.)

Depth

(m.)

Weight

(tongross) Brand

Power

(Kw) Piston

1 145 26.00 3.80 1.65 39.15 Volvo Penta 385.42 6 90

2 146 27.50 3.50 1.65 35.52 Cummin 355 6 90

3 149 26.64 4.50 1.60 47.39 Cummin 355*2 6*2 90

4 150 26.64 4.50 1.60 47.36 Cummin 355*2 6*2 90

5 152 27.70 3.90 1.30 36.90 Cummin 355 6 90

6 153 29.40 3.90 1.40 35.33 Cummin 302 6 90

7 154 27.50 3.90 1.20 40.60 Cummin 302 6 90

8 155 27.36 3.60 1.09 28.75 Cummin 355 6 90

9 156 27.12 3.60 1.48 33.92 Cummin 355 6 90

10 157 27.68 3.35 1.60 31.92 Cummin 355 6 90

11 158 28.85 3.76 1.40 36.45 Cummin 355 6 90

12 159 27.60 3.72 1.50 35.60 Cummin 355 6 90

13 160 26.82 3.64 1.60 34.76 Cummin 355 6 90

14 161 26.75 3.64 1.60 35.86 Cummin 355 6 90

15 163 28.57 3.46 1.58 34.21 Cummin 355 6 90

16 164 26.49 .90 1.37 33.71 Cummin 355 6 90

17 165 26.33 3.70 1.64 36.65 Volvo Penta 384 6 90

18 167 26.33 3.70 1.64 36.65 Cummin 355 6 90

19 168 28.86 3.56 1.60 36.24 Cummin 355 6 90

20 169 27.94 3.60 1.64 36.16 Cummin 355 6 90

21 170 29.95 3.64 1.64 40.73 Cummin 355 6 90

22 171 28.35 3.50 1.50 33.51 Cummin 355 6 90

23 172 27.65 3.68 1.64 36.92 Volvo Penta 400 6 90

24 173 28.98 3.50 1.30 31.70 Cummins 355 6 90

25 174 27.86 3.60 1.40 33.41 Cummins 355 6 90

26 175 29.48 3.40 1.60 34.70 Cummins 355 6 90

27 176 28.36 3.76 1.50 34.80 Cummins 355 6 90

28 177 28.98 3.71 1.30 32.65 Cummins 355 6 90

29 178 29.14 3.64 1.56 37.22 Cummins 355 6 90

30 179 32.90 3.52 1.50 39.18 Cummins 355 6 90

31 180 29.48 3.78 1.45 37.75 Cummins 355 6 90

32 181 28.87 3.42 1.52 33.24 Cummins 355 6 90

33 182 27.10 3.64 1.50 36.33 Cummins 355 6 90

34 183 29.71 3.48 1.45 31.03 Cummins 355 6 90

35 184 28.55 3.50 1.45 33.08 Cummins 405 6 90

36 185 29.90 3.85 1.45 42.70 Cummins 355 6 90

37 186 30.35 3.86 1.45 38.14 Cummins 355 6 90

38 187 30.15 3.86 1.45 59.67 Cummins 355 6 90

39 188 30.15 3.86 1.45 59.67 Cummins 355 6 90

40 189 30.76 3.67 1.35 35.48 Cummins 355 6 90

41 190 30.75 4.00 1.50 43.00 Volvo Penta 385.45 6 90

42 191 30.90 3.90 1.50 42.72 Cummins 355 6 90

43 192 30.00 3.80 1.50 51.66 Cummins 355 6 90

44 193 30.00 3.80 1.50 51.66 Cummins 355 6 90

45 194 30.00 3.80 1.50 51.66 Cummins 355 6 90

46 195 30.20 3.80 1.50 40.00 Cummins 355 6 90

57

APPENDIX 1 (Continued)

No. Boat

number

Boat size Engine

Passenger Long

(m.)

Width

(m.)

Depth

(m.)

Weight

(tongross) Brand

Power

(Kw) Piston

47 201 29.35 5.25 1.35 56.32 Cummins 355*2 6*2 120

48 202 29.58 5.27 1.60 58.62 Cummins 355*2 6*2 120

49 203 29.80 5.30 1.50 59.31 Cummins 355*2 6*2 120

50 204 30.52 5.26 1.40 59.12 Cummins 355*2 6*2 120

51 205 29.92 5.16 1.40 59.12 Cummins 355*2 6*2 120

52 206 29.30 5.20 1.70 59.00 Cummins 355*2 6*2 120

53 207 29.80 5.30 1.50 59.31 Cummins 355*2 6*2 120

54 208 30.52 4.90 1.50 59.70 Cummins 355*2 8*2 120

55 209 29.95 5.18 1.50 56.46 Cummins 355*2 6*2 120

56 210 29.80 4.85 1.60 59.00 Cummins 355*2 6*2 120

57 211 28.95 4.0 1.40 46.00 Volvo Penta 385*2 6*2 180

58 212 28.85 4.45 1.50 44.00 Volvo Penta 385*2 6*2 120

59 213 30.55 4.80 1.70 54.00 Cummins 355*2 6*2 120

60 214 28.86 5.20 1.60 58.00 Volvo Penta 385*2 6*2 120

58

APPENDIX 1 (Continued)

No. Station Number of

boats

Number of service boats Boat

Owner Boat name

Boat

size

Engine

name

Engine

power

(hp)

Piston Passenger Weekday Saturday Sunday

1 Pakkret – Wat Toey 5 4 3 4 เอกชน

นาทนาวี 9.29 Isuzu 169.95 6 15

สุขเกษม6 2.38 Guardner 131.86 4 12

สุขเกษม9 3.55 Isuzu 101.00 4 15

สุขเกษม11 6.31 Isuzu 100.61 4 15

สุขเกษม14 8.87 Nisson 243.43 6 20

2 Pakkret –

Wachareewongse 6 4 4 4

เทศบาลนครปากเกร็ด,

อบต. บางตะไนย ์

วชัรีวงศ ์1 12.54 Hino 187.64 4 50

วชัรีวงศ ์3 4.35 Isuzu 96.53 4 10

วชัรีวงศ ์5 13.05 Isuzu 175.39 6 20

วชัรีวงศ ์7 7.82 Isuzu 99.25 4 15

วชัรีวงศ ์8 26 Nisson 263.77 6 63

ดาวบา้นนา3 11.3 Isuzu 187.64 6 32

3 Nonthaburi – Bang Sri

Mueng 7 4 4 4 กรมเจา้ท่า

จ.ส.น.1 27.2 Guardner 152.14 6 120

จ.ส.น.5 10.29 Guardner 51.66 4 30

จ.ส.น.8 23.52 Guardner 151.04 6 100

จ.ส.น.9 27.2 Guardner 152.28 6 120

จ.ส.น.10 23.23 Guardner 150.92 6 100

จ.ส.น.11 23.49 Guardner 91.09 6 90

จ.ส.น.12 23.49 Guardner 91.09 6 90

59

APPENDIX 1 (Continued)

No. Station Number of

boats

Number of service boats Boat

Owner Boat name

Boat

size

Engine

name

Engine

power

(hp)

Piston Passenger Weekday Saturday Sunday

4 Thewes –

Bawornmongkon 3 2 1 1 เอกชน

บวรมงคล 2 8.83 Guardner 40.79 4 14

บวรมงคล 3 9.57 Guardner 76.14 5 26

ประเสริฐเจริญทรัพย ์ 16.21 Guardner 91.28 6 30

5 Thewes – Wat

Karuhabodee 2 1 1 1

กรมเจา้ท่า&เอกชน

คฤหมงคล 1 11.75 Hino 157.72 6 30

6 Tha Phrachan – Wang

Lang 5 2 2 2 สุภทัรา

สภ. 69 28.2 Guardner 183.55 6 15

สภ. 71 28.68 Guardner 152.28 4 12

สภ. 76 36.59 Cummins 354.86 4 15

สภ. 77 49.7 Cummins 354.86 4 15

สภ. 78 32 Guardner 182.46 6 20

7 Tha Maharaj – Wang

Lang 5 2 2 2 สุภทัรา

สภ. 69 28.2 Guardner 183.55 6 90

สภ. 70 28.2 Isuzu 152.28 6 90

สภ. 72 28.68 Guardner 152.28 6 90

สภ. 77 49.7 Cummins 354.86 6 90

สภ. 78 32 Guardner 182.46 6 90

60

APPENDIX 1 (Continued)

No. Station Number of

boats

Number of service boats Boat

Owner Boat name

Boat

size

Engine

name

Engine

power

(hp)

Piston Passenger Weekday Saturday Sunday

8 Tha Chang – Wang

Lang 8 2 2

2 สุภทัรา

สภ. 70 28.2 Isuzu 152.28 6 90

สภ. 71 28.68 Guardner 152.28 6 90

สภ. 72 28.68 Guardner 152.28 6 90

สภ. 73 29.59 Guardner 182.57 6 90

สภ. 74 29.59 Guardner 152.28 6 90

สภ. 75 34.09 Cummins 354.86 6 90

สภ. 76 36.51 Cummins 354.86 6 90

สภ. 78 32 Guardner 182.46 6 90

9 Tha Chang – Wat

Rakang 5 2 2 2 สุภทัรา

สภ. 78 8.87 Nisson 243.43 6 90

สภ. 69 9.29 Isuzu 169.95 6 90

สภ. 70 2.38 Guardner 131.86 4 90

61

APPENDIX 1 (Continued)

No. Station Number of

boats

Number of service boats Boat

Owner Boat name

Boat

size

Engine

name

Engine

power

(hp)

Piston Passenger Weekday Saturday Sunday

10 Tha Tien – Wat Arun 4 3 3 3 เอกชน

โพธ์ิอรุณ 12 21.11 Nisson 202.58 6 60

โพธ์ิอรุณ 15 34.09 Nisson 167.91 6 60

โพธ์ิอรุณ 18 38.1 Guardner 182.46 6 60

โพธ์ิอรุณ 20 37.31 Guardner 182.57 6 60

11 Assadang – Wat

Kalayanimit 1 1 1 1

กรมเจา้ท่า &เอกชน

กลัยาณ์ 12 16.44 Layland 203.94 6 60

12 Rachawongse –

Dindang 5 4 4 4

เอกชน&กรมเจา้ท่า

ปราณี 30.4 Guardner 87.21 6 50

ปราณี 20 31.32 Guardner 91.28 6 60

ปราณี 21 31.32 Guardner 91.28 6 60

ปราณี 44 33.11 Guardner 152.27 6 60

ปราณี 45 33.11 Guardner 152.27 6 80

62

APPENDIX 1 (Continued)

No. Station Number of

boats

Number of service boats Boat

Owner Boat name

Boat

size

Engine

name

Engine

power

(hp)

Piston Passenger Weekday Saturday Sunday

13 Sri Phraya – Klongsan 4 3 3 3 เอกชน

ปัญจทรัพย ์2 24.33 Nisson 263.77 6 63

ปัญจทรัพย ์3 30.06 Nisson 263.77 6 70

ปัญจทรัพย ์4 27.46 Nisson 263.77 6 63

ปัญจทรัพย ์8 65.27 Nisson 283.99 6 100

14 Oriental – Wat Suwan 4 3 3 2 กรมเจ่าท่า&

เอกชน

ป. บูรพา 22.99 Hino 167.23 6 45

ป. บูรพา 1 22.94 Hino 161.79 6 45

เกียรติชูชยั 19 32.62 Nisson 182.19 6 40

น าโชคชยั 10 31.25 Isuzu 161.79 6 50

15 Sathorn – Pepsi 4 2 2 2 กรมเจา้ท่า&

เอกชน

สาธร 1 33.7 Nisson 223.14 6 90

สาธร 2 33.7 Nisson 223.14 6 90

สาธร 3 52.09 Isuzu 274.64 6 110

63

APPENDIX 1 (Continued)

No. Station Number of

boats

Number of service boats Boat

Owner Boat name

Boat

size

Engine

name

Engine

power

(hp)

Piston Passenger Weekday Saturday Sunday

16 Sathuphradit – Wat

Bang Pueng 2 1 กรมเจา้ท่า ประภามณฑล 20.2 Deutz 43.51 3 30

17 Sathuphradit – Klong

Latluang 2 2 1 1 กรมเจา้ท่า

พญาภุชงค์นาคราช 1

35.3 Cummins 354.86 6 40

พญาภุชงค์นาคราช 2 54.72 Isuzu 425.99 6 40

18 Rama 3 – Klong Lat Po 2 2 2 2 เอกชน ลดัโพธ์ิ 65.56 Cummins 323.59 6 60

19 Klong Toey – Tuapai 3 2 2 - เอกชน

ช. ทรัพยส์มบูรณ์ 2

3.4 Yunmar 29.91 3 30

เกษมสาคร 2.34 Isuzu 28.55 4 30

ส. ชูเกียรติ 2.15 Isuzu 40.57 4 30

20 Bangnanok –

Bangnampuengnok 5 3 2 2 เอกชน

มนสัสกุล 1 91.96 Hino 324.57 6 120

สมบตัิมนสั 2 17.22 Hino 365.14 6 70

สมบตัิมนสั 3 53.32 Hino 318.15 6 70

สมบตัิมนสั 7 43.72 Hino 365.14 6 70

64

APPENDIX 1 (Continued)

No. Station Number of

boats

Number of service boats Boat

Owner Boat name Boat size

Engine

name

Engine

power

(hp)

Piston Passenger Weekday Saturday Sunday

21 Bangna – Ta Luen 2 1 1 1

กรมสรรพาวุธทหารเรือ &

เอกชน

สมบตัิมนสั

32.59

Guardner

182.57

6

50

คงสาคร 1 คงสาคร 1 7.15 Hino 169.03 6 16

22 Petra – Phra Phradang 6 4 4 4 เอกชน

ชลโภค 1 40.15 Nisson 304.28 6 80

ภมรธาร 1 40.15 Nisson 304.28 6 80

ธนาภพ 1 40.15 Guardner 182.57 6 80

ราชเภตรา 33.25 Guardner 182.19 6 100

ลาโภ 1 40.15 Guardner 182.57 6 80

65

APPENDIX 1 (Continued)

No. Station Number of

boats

Number of service boats Boat

Owner Boat name Boat size

Engine

name

Engine

power

(hp)

Piston Passenger Weekday Saturday Sunday

23 Wiboonsri – Phra

Samut Chedi 12 5 5 5

เอกชน&

องคก์ารบริหารส่วนจงัหวดั

สิทธิโชค 3 8.5 A.E.C 40.79 6 50

สิทธิโชค 16 15.37 Hino 141.4 6 70

สิทธิโชค 17 17.15 Hino 111.65 6 85

สิทธิโชค 18 13.98 Hino 141.4 6 73

สิทธิโชค 25 9.83 Hino 167.36 6 55

สิทธิโชค 26 14.69 Hino 141.4 6 50

สิทธิโชค 27 19.35 A.E.C 142 6 100

สิทธิโชค 30 24.16 Leyland 176.75 6 90

66

APPENDIX 2 Emission share of different boat types (%)

Pollutants Green Orange Yellow No

flag Gold Blue

Shuttle

boat

HC 10.70 33.60 6.51 3.84 11.51 15.70 18.14

CO 9.66 32.26 5.52 4.55 11.44 16.95 19.62

NOx 10.62 33.62 6.33 4.06 10.93 16.00 18.43

NMHC 10.80 33.86 6.43 4.00 10.92 15.78 18.20

CH4 10.56 34.16 6.83 4.35 12.42 15.53 16.15

NH3 13.19 13.19 12.09 4.40 13.19 21.98 21.98

N2O 14.40 31.41 4.45 3.93 14.40 17.02 14.40

CO2 10.68 33.71 6.38 4.03 10.86 15.94 18.40

SO2 9.30 32.56 5.58 6.05 13.95 13.95 18.60

PM10 11.41 34.62 7.04 3.61 11.03 15.03 17.25

PM2.5 11.41 34.62 7.08 3.54 11.01 14.95 17.39

BC 11.37 34.51 7.06 3.53 10.98 15.29 17.25

OC 11.81 34.45 7.09 3.35 10.83 14.76 17.72

67

APPENDIX 2 (Continued)

Pollutant Green (%) Orange (%) Yellow (%) No flag (%) Gold (%) Blue (%) Shuttle boat (%)

Total C I Total C I Total C I Total C I Total C I Total C I Total C I

HC 10.70 9.30 1.40 33.60 27.91 5.70 6.51 5.81 0.70 3.84 2.67 1.16 11.51 9.42 2.09 15.70 11.74 3.95 18.14 13.49 4.65

CO 9.66 6.58 3.09 32.26 19.67 12.59 5.52 4.09 1.42 4.55 1.92 2.63 11.44 6.76 4.68 16.95 8.26 8.70 19.62 9.50 10.12

NOx 10.62 8.90 1.72 33.62 26.64 6.98 6.33 5.55 0.78 4.06 2.60 1.46 10.93 8.34 2.59 16.00 11.17 4.83 18.43 12.85 5.58

NMHC 10.80 9.34 1.46 33.86 28.03 5.83 6.43 5.83 0.61 4.00 2.79 1.21 10.92 8.74 2.18 15.78 11.77 4.00 18.20 13.59 4.61

CH4 10.56 9.32 1.24 34.16 27.95 6.21 6.83 6.21 0.62 4.35 3.11 1.24 12.42 9.32 3.11 15.53 12.42 3.11 16.15 13.04 3.11

NH3 13.19 10.99 2.20 13.19 2.20 10.99 12.09 10.99 1.10 4.40 3.30 1.10 13.19 10.99 2.20 21.98 10.99 10.99 21.98 10.99 10.99

N2O 14.40 13.09 1.31 31.41 26.18 5.24 4.45 1.21 0.16 3.93 2.62 1.31 14.40 13.09 1.31 17.02 13.09 3.93 14.40 10.47 3.93

CO2 10.68 9.04 1.64 33.71 27.08 6.63 6.38 5.64 0.75 4.03 2.64 1.39 10.86 8.48 2.39 15.94 11.35 4.59 18.40 13.06 5.33

SO2 9.30 9.30 1.40 32.56 27.91 4.65 5.58 4.65 0.70 6.05 4.65 1.40 13.95 9.30 4.65 13.95 9.30 4.65 18.60 13.95 4.65

PM10 11.41 10.84 0.57 34.62 32.53 2.09 7.04 6.85 0.19 3.61 3.23 0.38 11.03 10.27 0.76 15.03 13.70 1.33 17.25 15.60 1.65

PM2.5 11.41 10.82 0.59 34.62 32.65 1.97 7.08 6.88 0.20 3.54 3.15 0.39 11.01 10.23 0.79 14.95 13.57 1.38 17.39 15.74 1.65

BC 11.37 10.98 0.39 34.51 32.55 1.96 7.06 6.67 0.39 3.53 3.14 0.39 10.98 10.20 0.78 15.29 13.73 1.57 17.25 15.69 1.57

OC 11.81 10.83 0.98 34.45 32.48 1.97 7.09 6.89 0.20 3.35 2.95 0.39 10.83 9.84 0.98 14.76 13.78 0.98 17.72 15.75 1.97

Note: C: cruising, I: idling

68

APPENDIX 2 (Continued)

Pollutant

Route 1 (%)

(Sriboonrueng-Pratunam)

Route 2 (%)

(Phan Falilat-Pratunam)

Total C I Total C I

HC 77.04 57.81 19.23 22.96 17.57 5.39

CO 77.35 38.08 39.27 22.65 11.60 11.05

NOx 76.25 56.10 20.14 23.75 17.08 6.67

NMHC 76.25 59.44 16.81 23.75 18.14 5.60

CH4 76.00 60.00 16.00 24.00 20.00 4.00

NH3 92.31 76.92 15.38 7.69 7.69 7.69

N2O 80.00 60.00 20.00 20.00 20.00 6.00

CO2 76.26 57.10 19.16 23.74 17.39 6.35

SO2 76.47 58.82 17.65 23.53 17.65 5.88

PM10 76.54 70.62 5.92 23.46 21.56 1.90

PM2.5 76.53 70.66 5.87 23.47 21.52 1.96

BC 76.47 70.59 5.88 23.53 21.57 1.96

OC 75.90 69.88 6.02 24.10 21.69 2.41

69

APPENDIX 2 (Continued)

Routes HC CO NOx NMHC CH4 NH2 N2O CO2 SO2 PM10 PM2.5 BC OC

Pakkret-Wat Toey 2.56 2.16 2.45 2.50 3.17 1.95 2.00 2.47 1.97 2.93 3.10 2.99 1.80

Pakkret-Watchareewongse 2.26 3.04 2.43 2.19 3.17 1.95 2.00 2.38 1.97 1.10 1.16 1.50 0.72

Koh Kret-Wat Sanamnuea 9.77 10.65 9.98 9.69 9.52 9.75 9.98 9.93 4.92 8.79 8.53 8.98 8.99

Nonthaburi-Bangsrimueng 8.87 9.36 9.02 8.91 6.35 9.75 7.98 8.99 9.83 8.06 8.53 8.23 8.99

Thewes-Bowornmongkon 1.05 0.91 1.00 0.94 0.63 0.39 2.00 1.01 0.98 1.47 1.16 0.97 0.18

Thewes-Karuhabodee 2.41 2.42 2.37 2.34 3.17 1.95 2.00 2.36 1.97 2.20 2.33 2.24 1.80

Tha Phrachan-Wang Lang 4.06 4.42 4.24 4.22 3.17 2.92 5.99 4.23 4.92 4.03 3.88 3.74 3.60

Wang Lang-Maharaj 2.86 2.86 2.90 2.97 3.17 2.92 3.99 2.91 4.92 2.93 3.10 2.99 3.60

Wang Lang-Tha Chang 4.66 4.29 4.53 4.53 6.35 3.90 3.99 4.56 4.92 5.13 5.04 5.24 5.39

Wat Rakang-Tha Chang 2.71 2.73 2.70 2.66 3.17 2.92 2.00 2.69 1.97 2.56 2.33 2.24 3.60

Tha Tien-Wat Arun 5.71 6.54 5.90 5.63 3.17 9.75 5.99 5.84 4.92 4.40 4.65 4.49 3.60

Pakklong-Kallayanimit 1.95 1.88 2.00 2.03 3.17 1.95 2.00 2.02 1.47 2.56 1.94 2.24 1.80

Rachawongse-Dindang 3.16 3.57 3.32 3.28 3.17 2.92 2.00 3.30 4.92 2.56 2.71 2.99 3.60

Sri Phraya-Klongsan 9.92 10.30 10.05 10.00 9.52 9.75 9.98 10.02 9.83 9.52 9.69 8.98 8.99

Oriental-Wat Suwan 3.61 3.42 3.56 3.59 3.17 2.92 3.99 3.58 4.92 4.03 3.88 3.74 3.60

Sathorn-Pepsi 4.36 4.17 4.32 4.38 6.35 2.92 3.99 4.33 4.92 4.40 4.65 4.49 5.39

Sathupradit-Klong Lat luang 4.81 4.68 4.78 4.84 6.35 2.92 3.99 4.78 4.92 4.76 5.04 5.24 5.39

Rama 3-Klong Latpo 4.51 4.67 4.60 4.69 3.17 3.90 5.99 4.59 4.92 4.40 4.65 4.49 5.39

Klong Toei-Tuapai 0.30 0.13 0.24 0.31 0.32 0.19 0.20 0.24 0.20 0.37 0.39 0.75 0.02

Bangna-Taluen 1.20 0.98 1.05 1.09 0.63 0.97 2.00 1.06 0.98 1.47 1.16 1.05 0.18

Bangnanok-Bangnampuengnok 4.21 3.76 4.06 4.22 6.35 3.90 3.99 4.09 4.92 4.76 4.65 4.49 5.39

Petra-Phra Pradang 6.17 5.67 6.00 6.09 6.35 9.75 5.99 6.03 4.92 6.96 6.59 6.73 7.19

Wiboonsri-Phra Samutchedi 8.87 7.39 8.51 8.91 6.35 9.75 7.98 8.61 9.83 10.62 10.85 11.22 10.79

70

APPENDIX 2 (Continued)

Pollutants

Koh Kret-Wat

Sanamnue (%)

Nonthaburi-Bang

Srimuang (%)

Tha Tien-Wat Arun

(%)

Sri Phraya- Klongsan

(%)

Petra-Phra Pradang

(%)

Wiboonsri-Phra

Samutchedee (%)

Total C I Total C I Total C I Total C I Total C I Total C I

HC 9.77 2.86 6.92 8.87 3.01 5.86 5.71 1.35 4.36 0.66 3.46 6.47 0.41 2.86 3.31 8.87 5.11 3.76

CO 10.65 1.26 9.38 9.36 1.31 8.05 6.54 0.57 5.96 7.01 1.54 8.75 3.86 1.25 4.42 7.39 2.23 5.15

NOx 9.98 2.46 7.52 9.02 2.56 6.46 5.90 1.11 4.79 9.38 3.03 7.02 5.6 2.45 3.55 8.51 4.37 4.13

NMHC 9.69 2.81 6.88 8.91 2.97 5.94 5.63 1.25 4.38 0.64 3.59 6.41 0.39 2.81 3.28 8.91 5.16 3.75

CH4 9.52 2.22 6.35 6.35 2.22 3.17 3.17 0.95 3.17 0.03 2.54 6.35 0.02 2.22 3.17 6.35 3.81 3.17

NH3 9.75 1.95 9.75 9.75 1.95 9.75 9.75 0.97 3.90 0.001 2.92 9.75 0.001 1.95 2.92 9.75 3.90 2.92

N2O 9.98 2.59 7.98 7.98 2.59 5.99 5.99 1.20 4.59 0.005 3.99 5.99 0.003 2.00 3.99 7.98 3.99 3.99

CO2 9.93 2.57 7.35 8.99 2.68 6.31 5.84 1.16 4.68 551.63 3.17 6.86 331.72 2.56 3.47 8.61 4.57 4.04

SO2 4.92 1.97 4.92 9.83 2.46 4.92 4.92 0.98 4.92 0.02 2.46 4.92 0.01 1.97 4.92 9.83 3.93 4.92

PM10 8.79 5.13 3.66 8.06 5.13 2.93 4.40 2.20 2.20 0.26 6.23 3.30 0.19 5.13 1.83 10.62 8.79 1.83

PM2.5 8.53 5.04 3.49 8.53 5.43 3.10 4.65 2.33 2.33 0.25 6.20 3.49 0.17 5.04 1.55 10.85 8.91 1.94

BC 8.98 5.24 3.74 8.23 5.24 2.99 4.49 2.24 2.24 0.12 5.98 2.99 0.09 5.24 1.50 11.22 8.98 2.24

OC 8.99 5.39 3.60 8.99 5.39 3.60 3.60 1.80 1.80 0.05 5.39 3.60 0.04 5.39 1.80 10.79 8.99 1.80

Note: C: cruising, I: idling

71

APPENDIX 2 (Continued)

Pollutants Chao Phraya boats Saen Saep boats Cross river ferries

HC 42.57 29.91 27.51

CO 40.64 24.05 35.30

NOx 42.33 28.27 29.39

NMHC 42.84 29.40 27.75

CH4 42.22 27.78 30.00

NH3 33.50 34.48 32.02

N2O 47.56 26.99 25.46

CO2 42.45 28.60 28.95

SO2 42.86 26.12 31.02

PM10 44.74 33.55 21.71

PM2.5 44.63 33.88 21.49

BC 44.68 33.39 21.93

OC 44.44 33.25 22.30

72

APPENDIX 2 (Continued)

Pollutants Chao Phraya boats Saen Saep boats Cross river ferries

Total C I Total C I Total C I

HC 42.57 35.58 6.99 29.91 22.55 7.36 27.51 11.05 16.47

CO 40.64 28.38 12.27 24.06 12.7 11.35 35.30 6.43 28.87

NOx 42.33 34.16 8.18 28.27 20.69 7.58 29.39 10.11 19.28

NMHC 42.84 35.73 7.11 29.40 22.81 6.59 27.75 11.01 16.74

CH4 42.22 35.56 6.67 27.78 22.22 5.56 30.00 10.00 20.00

NH3 33.50 24.63 8.87 34.48 27.09 7.39 32.02 7.39 24.63

N2O 47.56 40.73 6.82 26.99 20.37 6.62 25.46 10.18 15.27

CO2 42.45 34.60 7.86 28.60 21.30 7.30 28.95 10.39 18.55

SO2 42.86 35.10 7.76 26.12 19.59 6.53 31.02 9.80 21.22

PM10 44.74 41.82 2.92 33.55 30.93 2.62 21.71 15.03 6.68

PM2.5 44.89 41.97 2.92 33.79 31.15 2.64 21.32 14.62 6.69

BC 44.68 41.73 2.95 33.39 30.77 2.62 21.93 15.06 6.87

OC 44.44 41.36 3.08 33.25 30.41 2.84 22.30 14.60 7.70

Note: C: cruising, I: idling

73

APPENDIX 3. Spatial distribution of emission

74

APPENDIX 3 (Continued)

75

APPENDIX 3 (Continued)