Final Report

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 INTRODUCTION 3 1.1 Background 3 1.2 Objectives 3 1.3 Scope of the project 4

CHAPTER 2 METHODOLOGY 5 2.1 Framework of methodology 5 2.2 Data collection 7 2.3 Emission estimation 9 2.4 Emission estimation of all boat groups 14 2.5 Excel calculation tool for inland water transport emission 15 2.6 Emission comparison 16 2.7 Emission impact area from inland water transport 16 2.8 Emission reduction policy recommendations 16

CHAPTER 3 SUMMARY OF ACTIVITY DATA AND EMISSION 18 FACTORS 3.1 Activity data 18 3.2 Emission factors 22

CHAPTER 4 EMISSION INVENTORY RESULTS 24 4.1 Emission inventory results 24 4.2 Emission comparison 36 4.3 Spatial and temporal distribution of emission 38 4.4 Inland water transport emission impact area 44 4.5 Excel emission calculation template for inland water transport 45 4.6 Emission control strategies 46

CHAPTER 5 SUMMARY AND LIMITATIONS 49 5.1 Summary 49 5.2 Recommendations for citizen and boat operator 50 5.3 Limitations in emission estimation 50

REFERENCES 51

APPENDICES 53 Appendix 1 Survey of boat trips and information of each boat group 53 Appendix 2 Emission share of different boat types 66 Appendix 3 Spatial distribution of emission 73

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⁄m3of 24-hr average PM2.5 concentration in the distance of one kilometer away from the river or

1 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.

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.

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).

CHAPTER 2 METHODOLOGY

2.1 Framework of methodology

Other sectors in Bangkok Impact area assessment

Policy recommendation

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.

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.

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) 퐴푆 3 퐿퐹 = ( ) (Equation 2.2) 푀푆 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 Calculated sample Number of boats boats under size from survey operation Chao Phraya boats 60 52 52 Chao Phraya Tourist 4 4 4 Boatsa (blue flag) 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.

Table 2.2 Survey period of each boat group

Boat group 2019 2020 October November December January February Chao Phraya X X X X boats Cross river X X X X X ferries Saen Saep X X X boats

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 Total operation time, idling Survey data time and cruising time per Primary trip data Boat trips per week Survey data Current boat routes Survey data Distance Survey data Age of engine Chao Phraya Express Boat Company

Year of engine model Marine Department, Chao Phraya Express Boat Company Secondary data 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

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.

−6 퐸푚푖푠푠푖표푛 = [퐴 ∗ 푇푡 ∗ 푃표푤푒푟 ∗ 퐿퐹] ∗ [퐸퐹푎푑푗 ∗ 10 ] (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.

퐸퐹 = 퐸퐹 ∗ 푇퐴퐹 ∗ 퐷퐹 (Equation 2.4) 푎푑푗(퐻퐶,푁푂푥,퐶푂) 푠푠

퐸퐹푎푑푗(푃푀) = 퐸퐹푠푠 ∗ 푇퐴퐹 ∗ 퐷퐹 − 푆푃푀푎푑푗 (Equation 2.5) 퐸퐹 = 퐸퐹 ∗ 푇퐴퐹 (Equation 2.6) 푎푑푗(퐶푂2,푆푂2) 푠푠

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

9 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.

퐷퐹 = 1 + 퐴 ∗ (퐴푔푒 퐹푎푐푡표푟)푏; 퐹표푟 푎푔푒 푓푎푐푡표푟 ≤ 1 (Equation 2.7) 퐷퐹 = 1 + 퐴; 퐹표푟 푎푔푒 푓푎푐푡표푟 > 1 (Equation 2.8)

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

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 HP1 HP2 HP3 HP4 HP5 HP6 HP7 HP8 HP9 HP10 Type Diesel 2500 2500 2500 4667 4667 4667 7000 7000 7000 - 2-stroke 150 200 750 ------Gasoline 4-stroke 200 400 750 1500 3000 3000 3000 3000 3000 3000 Gasoline 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.

( ) 푆푃푀푎푑푗 = (퐵푆퐹퐶 ∗ 453.6 ∗ 푠표푥푐푛푣 ∗ 7.0 ∗ 0.01 ∗ 푠표푥푏푎푠 − 푠표푥푑푠푙 (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

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.

44 퐶푂 = (퐵푆퐹퐶 ∗ 453.6 − 퐻퐶) ∗ 0.87 ∗ ( ) (Equation 2.10) 2 12 푆푂2 = (퐵푆퐹퐶 ∗ 453.6 ∗ (1 − 푠표푥푐푛푣) − 퐻퐶) ∗ 0.01 ∗ 푠표푥푑푠푙 ∗ 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.

Table 2.8 Summary of the parameters and equations for EFadj

Pollutants EFss (g/hp-hr) TAF DF SPmadj HC Based on Eq2.7 & Eq2.8 - CO technology and Eq2.7 & Eq2.8 - NOx engine power 1 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 Euro I 0.65 0.26 Euro II 0.65 0.26 Euro III 0.61 0.34 Winijkul (2015) 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

The fraction adjustment of idling factor Pollutants 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 *

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

The fraction adjustment of idling factor Pollutants 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):

−6 퐸푐 = [퐴 ∗ 푇푡 ∗ 푃표푤푒푟 ∗ 퐿퐹 ∗ 푃표푤푒푟] ∗ [퐸퐹푎푑푗 ∗ 10 ]

Emission for idling time:

−6 퐸푖 = [퐴 ∗ 푇푡 ∗ 푃표푤푒푟 ∗ 퐿퐹 ∗ 푃표푤푒푟] ∗ [퐼퐹 ∗ 퐸퐹푎푑푗 ∗ 10 ] (Equation 2.12)

Total Emission: 퐸 = ∑(퐸푐 + 퐸푖) (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;

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).

∑퐸푖 퐸푖 = (Equation 2.14) 푁푔

Where; 퐸푖 = Total emission of pollutants “i” which released by all “n” boats in grid cell ∑퐸푖 = Total emission of pollutants “i” between each pier 푁푔 = 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.

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.

Table 2.11: Emission Reduction Measures Investigated in This Study

Scenario 1 Scenario 2 Scenario 3 Use engine with current Switch boat engines to Tier 4 Use engine with current technology (Tier 0), but use technology and use 10 ppm technology (Tier 0), but 10 ppm sulfur fuel (current sulfur fuel reducing idling time by 50% was 50 ppm)

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

Engine Main group Subgroup Number of boats Classification criteria power(hp) No flag 355 Green flag 355x2

Orange flag 60 355 Yellow flag 355 Chao Phraya Gold flag 355x2 boats Chao Routes and operation Phraya time 4 Tourist 247x2 boat Shuttle 8 150x2 boat 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.

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)

Activity time Distance Average (min/trip) No. Routes LF (km/round Monthly Cruising Idling trip) trip time/trip 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 Nonthaburi- 4. 0.23 0.56 5.25 5.15 5900 Bangsrimueng 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 Pakklong Talad- 12. 0.31 0.42 5.10 4.70 1508 Kallayanimit 13. Rachawongse-Dindang 0.24 0.46 4.31 8.32 2972

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

Distance Activity time (min/trip) Average No. Routes LF (km/round Cruising Idling Monthly trip) time/trip time/trip 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 Wiboonsri-Phra 19. 0.55 2.88 18.30 6.26 2776 Samutchedee

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

Activity time (min/trip) Average Distance No. Routes LF Monthly (km/trip) Cruising Idling time/trip time/trip trip Sathu Phradit-Klong 1. 0.32 1.03 8.83 3.44 1228 Lat Luang 2 Rama 3- Klong Ladpo 0.31 0.65 5.92 7.93 1812 Bangnanok- 3. 0.31 0.68 6.56 6.00 2040 Bangnampuengnok 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)

Activity time (hr/trip) Average Distance Number of monthly Flag Routes LF (km/trip) Cruising Idling routes trip Route 1 Pakkret - Sathorn 0.29 27.94 1.28 0.23 340 Green Pakkret - Route 2 0.29 9.71 0.42 0.11 80 Nonthaburi Route 3 Nonthaburi – Wat Orange 0.28 19.91 1.08 0.17 2516 Rajsingkorn Route 3 Nonthaburi – Wat 0.28 19.91 1.42 0.40 176 Rajsingkorn No flag Nonthaburi-Wat Route 4 0.28 5.03 0.42 0.12 40 Soi Thong

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

Activity time (hr/trip) Average Distance Number of monthly Flag Routes LF (km/trip) Cruising Idling routes trip Nonthaburi – Route 5 0.29 18.14 1.00 0.11 492 Sathorn Yellow Sathorn- Route 6 0.29 5.26 0.25 0.07 80 Ratburana Sathorn - Gold Route 7 0.34 5.29 0.42 0.11 1080 Prannok Phra Arthit- Blue Route 8 0.35 9.47 0.50/0.67 0.23/0.24 1472 Sathorn/Asiatique Icon-Siam- Route 9 Lhong 1919- 0.26 2.25 0.38 3.96 1232 Rachawongse Icon-Siam - Shuttle Route 10 0.28 1.07 0.24 0.17 1336 Sathorn boat Icon-Siam -Wat Route 11 0.27 0.23 0.19 0.04 1760 Muangkae Icon-Siam -Sri Route 12 0.29 0.26 0.10 0.07 2016 Phraya

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

Activity No. Routes LF Distance time(hr/trip) Average (km/trip) monthly trip Cruising Idling Sriboonrueng - 1. 0.14 13.25 0.61 0.21 7756 Pratunam Phan Fa Lilat- 2. 0.15 3.98 0.20 0.07 7332 Pratunam

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

(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).

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

Cruising EFadj (g/hp-hr) Engine Power (hp) Technology Type BSFC (lb/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 0.04 100-300 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 0.03 300-750 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

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

Idling EFadj (g/hp-hr) Engine Power (hp) Technology Type BSFC (lb/hp-hr) 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 0.01 100-300 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 0.01 300-750 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

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 Operation Condition (tons/year) 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). 24

Green flag, 11.41% Shuttle boat, Green flag, 9.66% CO PM2.5 Shuttle boat, 17.39% 19.62%

Blue flag, 14.95% Blue flag, 16.95%

Gold flag, 11.01% Orange flag, 34.62% Gold flag, 11.44% Orange flag, 32.26%

No Flag, 3.54% No Flag, 4.55% Yellow flag,5.52% Yellow flag,7.08%

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.

12.59% 35

25 10.12% 8.7% 20

15 4.68% 3.09% Percentage (%) Percentage 10 1.43% 2.63% 5 19.67% 1.92% 9.5% 8.25% 6.76% 6.58% 4.09% 0 Orange flag, Shuttle boat, Blue flag, Gold flag, Green flag, Yellow flag, No flag, 32.26% 19.62% 16.95% 11.44% 9.66% 5.52% 4.55%

Cruising Idling

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).

1.97% PM2.5

30 1.65% 25 1.38%

20 0.59% 0.79% 15

Percentage (%) Percentage 0.2% 10 0.39% 5 32.65% 15.74% 13.57% 10.82% 10.23% 6.88% 3.15% 0 Orange Shuttle Blue flag, Green flag, Gold flag, Yellow flag, No flag, flag, boat, 14.95% 11.41% 11.01% 7.08% 3.54% 34.62% 17.39%

Cruising Idling

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.

Table 4.2 Annual emission of Saen Saep boats from Nida and Golden Mountain routes (tons/year), 2019

Cruising Idling Golden Golden Total Nida route Nida route Pollutants Mountain route Mountain route emission (Sriboonrueng- (Sriboonrueng- (Phan Falilat- (Phan Falilat- (ton/year) Pratunam) Pratunam) Pratunam) 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

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).

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).

29 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- 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 Wat Toey Pakkret- 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 Watchareewongse Koh Kret- 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 Wat Sanamnuea Nonthaburi- 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 Bangsrimueng 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 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 Lang 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- 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 Tha Chang Wat Rakang- 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 Chang Tha Tien- 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 Wat Arun 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

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- 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 Wat Suwan 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 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 luang Rama 3- 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 Latpo 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- 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 Bangnampuengnok 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 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 Samutchedi Total emission 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 (ton/year)

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.

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.

Koh Kret-Wat Sanamnua, 10.65% Wiboonsri-Phra Samutchedee, 10.85% CO PM2.5 Sri Phraya-Klongsan, 10.30% Sri Phraya-Klongsan, 9.69%

Nonthaburi- Nonthaburi- Bangsrimuang, 8.53% Others, 55.76% Bangsrimuang, 9.36% Others, 55.76%

Wiboonsri-Phra Koh Kret-Wat Samutchedee, 7.39% Sanamnua, 8.53%

Tha Tien-Wat Arun, Petra-Phra Pradang, 6.54% 6.59%

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

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 ).

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

Total emission in tons/year Pollutants Chao Phraya Cross river Saen Saep boats Total emission boats ferries 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

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.

12.27% 45 11.35% 28.87% 40 35 30 25 20

Percentage (%) Percentage 15 10 28.38% 12.7% 6.43% 5 0 Chao Phraya boats, 40.64% Saen Saep boats, 24.06% Cross river ferries, 35.30%

Cruising Idling

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.

PM2.5 2.92%

2.64% 45 6.69% 40 35 30 25 20

Percentage (%) Percentage 31.15% 15 41.97% 10 14.62% 5 0 Chao Phraya boats, 44.89% Saen Saep boats, 33.79% Cross river ferries, 21.32%

Cruising Idling

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).

Table 4.5 Emission comparison between this study and other studies

GAINS (2020) Kim Oanh (2020) This study Pollutants (ton/year) (tons/year) (tons/year) Emission year 2020 2018 2019 Public and goods On-road vehicles in Public inland water Sector inland water transport Bangkok transport in Bangkok 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.

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

Kim Oanh (2020) This study Pollutants (g/km-passenger) (g/km-passenger) Emission 2018 2019 year On-road vehicles in Sector Public inland water transport in Bangkok Bangkok Chao Phraya Saen Saep Cross river Type Van Bus boats boats 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.

(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

(1) (2) (3)

2 Figure 4.14 PM2.5 emission from inland water transport in tons/year in a grid map of 500x500 m : (1) cruising condition (2) idling condition (3) total emission

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.

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)

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)

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).

Maximum 24-hr average PM2.5 concentration in μg⁄m3

Figure 4.17 Inland water transport emission impact area: (Left) PM2.5 emission inventory; 3 (Right) Max. 24-hr average PM2.5 concentration in μg⁄m

From Figure 4.17, inland water transport in this study contributed to the maximum of 1-4 3 μg⁄m 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,

44 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.

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)

Baseline S1: S2: S3: Tier 0+ 50% Boat Groups (2019) Tier4+0.001%S Tier0+0.001%S Idling time Chao Phraya 5.4 0.1 5.3 5.2 boats Saen Saep boats 4.0 0.1 4.1 3.9 Cross river ferries 2.5 0.1 2.1 2.2 Total emission 12.1 0.3 11.5 11.3 (tons/year) % Reduction - 97.7% 4.5% 6.4% from baseline

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).

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)

Baseline S1: S2: S3: Tier 0+ 50% Boat Groups (2019) Tier4+0.001%S Tier0+0.001%S Idling time Chao Phraya 78.4 2.6 78.4 43.0 boats Saen Saep boats 46.4 1.7 46.4 35.4 Cross river ferries 68.1 7.9 68.1 39.9 Total emission 192.9 12.2 192.9 118.3 (tons/year) % Reduction - 93.7% 0% 38.6% from baseline

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)

Baseline S1: S2: S3: Tier 0+ 50% Boat Groups (2019) Tier4+0.001%S Tier0+0.001%S Idling time Chao Phraya 0.2 0.06 0.2 0.2 boats Saen Saep boats 0.2 0.05 0.2 0.1 Cross river ferries 0.2 0.06 0.1 0.1 Total emission 0.6 0.17 0.5 0.4 (tons/year) % Reduction - 71.7% 16.7% 25.0% from baseline

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.

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.

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,

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.

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APPENDICES

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

วนั เดอื นปี (Day) (Flag) สธี ง 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 ธงเขยี ว (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 ธงเหลอื ง (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-สพี่ ระยำ (IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66 วนั จันทร(์ Monday) ไอคอนสยำม-วดั มว่ งแค (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-ลง้ 1919-รำชวงศ ์ (IconSiam-Lhong1919- Rachawongse) 4 4 4 4 4 4 4 4 4 4 4 44 รวม 1 15 18 8 26 31 32 29 28 29 31 35 35 34 28 0 380 ธงเขยี ว (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 ธงเหลอื ง (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-สพี่ ระยำ (IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66 วนั อังคำร(Tuesday) ไอคอนสยำม-วดั มว่ งแค (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-ลง้ 1919-รำชวงศ ์ (IconSiam-Lhong1919- Rachawongse) 4 4 4 4 4 4 4 4 4 4 4 44 รวม 1 15 17 8 26 31 28 28 28 29 31 37 35 34 28 0 376 ธงเขยี ว (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 ธงเหลอื ง (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-สพี่ ระยำ (IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66 วนั พธุ (Wednesday) ไอคอนสยำม-วดั มว่ งแค (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-ลง้ 1919-รำชวงศ ์ (IconSiam-Lhong1919- Rachawongse) 4 4 4 4 4 4 4 4 4 4 4 44 รวม 1 15 17 8 26 31 29 28 28 29 31 37 35 34 28 0 377 ธงเขยี ว (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 ธงเหลอื ง (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-สพี่ ระยำ (IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66 วนั พฤหัส(Thrusday) ไอคอนสยำม-วดั มว่ งแค (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-ลง้ 1919-รำชวงศ ์ (IconSiam-Lhong1919- Rachawongse) 4 4 4 4 4 4 4 4 4 4 4 44 รวม 1 15 16 8 26 28 29 28 28 29 31 37 35 34 28 0 373 ธงเขยี ว (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 ธงเหลอื ง (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-สพี่ ระยำ (IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66 วนั ศกุ ร(์ Friday) ไอคอนสยำม-วดั มว่ งแค (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-ลง้ 1919-รำชวงศ ์ (IconSiam-Lhong1919- Rachawongse) 4 4 4 4 4 4 4 4 4 4 4 44 รวม 1 15 17 8 26 29 29 28 28 29 31 37 35 34 28 0 375 รวมวนั รำชกำร 5 75 85 40 130 150 147 141 140 145 155 183 175 170 140 0 1881 ธงเขยี ว (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 ธงเหลอื ง (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-สพี่ ระยำ (IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66 วนั เสำร(์ Saturday) ไอคอนสยำม-วดั มว่ งแค (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-ลง้ 1919-รำชวงศ ์ (IconSiam-Lhong1919- Rachawongse) 4 4 4 4 4 4 4 4 4 4 4 44 รวม 0 4 5 6 28 33 35 33 31 32 32 33 32 30 24 0 358 ธงเขยี ว (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 ธงเหลอื ง (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-สพี่ ระยำ (IconSiam-Sri Phraya) 6 6 6 6 6 6 6 6 6 6 6 66 วนั อำทติ ย(์ Sunday) ไอคอนสยำม-วดั มว่ งแค (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-ลง้ 1919-รำชวงศ ์ (IconSiam-Lhong1919- Rachawongse) 4 4 4 4 4 4 4 4 4 4 4 44 รวม 0 4 5 6 28 33 35 32 31 32 32 33 32 30 24 0 357 รวมวนั หยดุ รำชกำร 0 8 10 12 56 66 70 65 62 64 64 66 64 60 48 0 715

APPENDIX 1 (Continued)

(The boat trip of inbound of Saen Saep boats) จำ นวนเทยี่ วเรอื โดยสำรคลองแสนแสบจำ แนกตำมเวลำและวนั ทสี่ ำ รวจ (ขำลอ่ ง) (สำยนดิ ำ้ )(ศรบี ญุ เรอื ง-ประตนู ำ ้ )(หลงั คำสงู )

(Day)วันท ี่ 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 (Monday) วันจันทร ์ 6 26 21 22 9 8 7 8 7 8 12 19 8 6 2 169 (Tuesday) วันอังคำร 6 29 28 19 9 8 7 8 7 8 12 22 7 8 2 180 (Wednesday) วันพธุ 6 30 30 17 9 6 6 6 6 6 14 17 8 7 3 171 (Thursday)วันพฤหสั บดี 8 30 26 17 9 6 6 6 6 6 14 18 8 7 3 170 (Friday)วันศกุ ร์ 7 27 27 19 9 9 5 6 6 6 14 17 7 6 6 171 (Total trips of 33 142 132 94 45 37 31 34 32 34 66 93 38 34 16 861 weekday)รวมวันรำชกำร (Saturday) วันเสำร์ 8 10 12 8 6 6 6 6 6 6 8 8 5 95 (Sunday)วันอำทติ ย์ 6 7 9 6 6 6 6 6 6 6 6 6 1 77 (Total trips of weekend) รวม 14 17 21 14 12 12 12 12 12 12 14 14 6 172 วันหยดุ รำชกำร (Total trips in one 33 156 149 115 59 49 43 46 44 46 78 107 52 40 984 week)รวมทัง้ สนิ้

(The boat trip of outbound of Saen Saep boats)จำ นวนเทยี่ วเรอื โดยสำรคลองแสนแสบจำ แนกตำมเวลำและวนั ทสี่ ำ รวจ (ขำขนึ้ ) (สำยนดิ ำ้ )(ประตนู ำ ้ -ศรบี ญุ เรอื ง)(หลงั คำสงู ) (Day)วันท ี่ 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 (Monday) วันจันทร ์ 4 3 9 13 8 8 7 8 7 8 17 25 17 15 9 158 (Tuesday) วันอังคำร 4 7 5 9 8 8 7 8 8 8 17 27 18 16 9 159 (Wednesday) วันพธุ 5 7 7 12 8 6 6 6 6 7 18 23 22 16 8 157 (Thursday)วันพฤหสั บดี 3 6 6 9 9 6 6 6 6 7 18 23 22 16 11 154 (Friday)วันศกุ ร์ 4 6 5 10 8 5 7 6 6 7 18 20 18 18 10 148 (Total trips of 20 29 32 53 41 33 33 34 33 37 88 118 97 81 47 776 weekday)รวมวันรำชกำร (Saturday) วันเสำร์ 2 4 5 7 6 6 6 6 6 7 6 13 12 8 94 (Sunday)วันอำทติ ย์ 1 4 4 3 5 6 6 7 6 6 6 10 10 2 76 (Total trips of weekend) รวม 3 8 9 10 11 12 12 13 12 13 12 23 22 160 วันหยดุ รำชกำร (Total trips in one 23 37 41 63 52 45 45 47 45 50 100 141 119 808 week)รวมทัง้ สนิ้

(The boat trip of inbound of Saen Saep boats) (Golden Mountain Line)จำ นวนเทยี่ วเรอื โดยสำรคลองแสนแสบจำ แนกตำมเวลำและวนั ทสี่ ำ รวจ (ขำลอ่ ง) (สำยภเู ขำทอง)(ประตนู ำ ้ -ผำ่ นฟ้ ำลลี ำศ) (หลงั คำเตยี้ )

(Day)วันท ี่ 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 (Monday) วันจันทร ์ 8 13 18 15 8 7 8 8 7 9 14 11 11 5 1 143 (Tuesday) วันอังคำร 6 17 17 19 7 8 8 8 7 10 15 13 9 5 149 (Wednesday) วันพธุ 4 17 21 18 8 7 5 6 7 8 21 18 7 7 154 (Thursday)วันพฤหสั บดี 6 20 20 16 9 6 6 6 6 8 14 14 8 7 146 (Friday)วันศกุ ร์ 3 14 20 19 8 6 6 7 6 9 18 19 9 9 153 (Total trips of 27 81 96 87 40 34 33 35 33 44 82 75 44 33 744 weekday)รวมวันรำชกำร (Saturday) วันเสำร์ 1 6 16 15 6 6 7 6 6 6 9 8 2 94 (Sunday)วันอำทติ ย์ 1 4 11 10 6 5 6 7 6 6 6 6 5 79 (Total trips of weekend) รวม 2 10 27 25 12 11 13 13 12 12 15 14 7 173 วันหยดุ รำชกำร (Total trips in one 29 91 123 112 52 45 46 48 45 56 97 89 51 884 week)รวมทัง้ สนิ้

จำ นวนเทยี่ วเรอื โดยสำรคลองแสนแสบจำ แนกตำมเวลำและวนั ทสี่ ำ รวจ (ขำขนึ้ ) (สำยภเู ขำทอง)(ผำ่ นฟ้ ำลลี ำศ-ประตนู ำ ้ )(หลงั คำเตยี้ ) (Day)วันท ี่ 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 (Monday) วันจันทร ์ 5 14 16 15 9 7 9 9 7 7 13 13 11 7 1 143 (Tuesday) วันอังคำร 5 14 18 15 10 8 7 8 8 7 16 14 10 6 1 147 (Wednesday) วันพธุ 4 12 18 15 10 6 6 6 6 8 19 18 10 6 2 146 (Thursday)วันพฤหสั บดี 6 16 18 16 10 6 6 6 6 7 14 14 10 6 2 143 (Friday)วันศกุ ร์ 3 14 20 18 9 6 5 8 5 7 20 17 13 8 2 155 (Total trips of 23 70 90 79 48 33 33 37 32 36 82 76 54 33 726 weekday)รวมวันรำชกำร (Saturday) วันเสำร์ 6 13 15 8 6 6 6 7 6 6 7 10 4 100 (Sunday)วันอำทติ ย์ 1 4 8 10 6 6 6 7 5 7 5 7 6 1 79 (Total trips of weekend) รวม 1 10 21 25 14 12 12 13 12 13 11 14 16 174 วันหยดุ รำชกำร (Total trips in one 24 80 111 104 62 45 45 50 44 49 93 90 70 867 week)รวมทัง้ สนิ้

APPENDIX 1 (Continued)

เสน้ ทำง(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-วดั เตย 68 101 99 67 62 59 60 62 59 64 67 71 90 80 66 1075 (Pakkret-Wat Toey) ปำกเกร็ด-วชั รวี งศ ์ 66 91 93 66 68 60 60 65 60 65 62 81 82 70 69 1058 (Pakkret-Watchareewongse) เกำะเกร็ด-วดั สนำมเหนือ 40 100 114 95 90 90 90 90 90 90 90 90 90 90 70 1319 (Koh Kret-WatSanamnuea) นนทบรุ -ี บำงศรเี มอื ง 81 149 165 118 74 70 66 67 66 66 109 114 117 111 102 1475 (Nonthaburi-Bangsrimueng) เทเวศร-์ วดั บวรมงคล 20 47 51 41 28 28 30 28 27 23 25 33 31 33 27 472 (Thewes-Bowornmongkon) เทเวศร-์ วดั คฤหบดี 0 40 36 29 23 22 20 20 16 14 18 23 21 20 19 321 (Thewes-Karuhabodee) ทำ่ พระจันทร-์ วงั หลัง 36 38 34 36 37 44 43 39 43 38 40 42 44 31 29 574 (Tha Phrachan-Wang Lang) วงั หลัง-มหำรำช 0 34 34 35 33 35 33 32 32 29 29 33 37 29 30 455 (Wang Lang-Maharaj) วงั หลัง-ทำ่ ชำ้ ง 32 42 42 40 33 35 33 34 32 32 33 36 37 34 31 526 (Wang Lang-Tha Chang) วดั ระฆงั -ทำ่ ชำ้ ง 0 31 31 37 28 26 25 20 24 24 23 28 25 26 21 369 (Wat Rakang-Tha Chang) ทำ่ เตยี น-วดั อรุณ 18 34 44 41 39 42 46 44 41 40 43 43 40 39 32 586 (Tha Tien-Wat Arun) ปำกคลองตลำด-วดั กัลยำณมิ ติ ร 26 29 32 23 25 21 22 23 21 25 25 29 26 24 26 377 (Pakklong-Kallayanimit) รำชวงศ-์ ดนิ แดง 7 53 80 72 50 43 39 40 41 38 46 53 78 64 39 743 (Rachawongse-Dindang) สพี่ ระยำ-คลองสำน 24 68 113 102 92 88 83 85 78 76 79 80 80 78 71 1197 (Sri Phraya-Klongsan) โอเรยี นเตล-วดั สวุ รรณ 0 66 79 75 50 47 41 43 43 40 50 60 66 33 30 723 (Oriental-Wat Suwan) สำทร-เป๊ ปซ ี่ 15 41 53 49 31 28 23 24 19 26 26 27 38 34 24 458 (Sathorn-Pepsi) สำธปุ ระดษิ ฐ-์ คลองลัดหลวง 6 28 31 31 21 18 16 20 17 16 16 20 25 24 18 307 (Sathupradit-Klong Latluang) คลองเตย-ทวั่ ไป 69 63 59 54 0 0 0 0 0 15 23 38 35 38 33 427 (Klong Toei-Tua Pai) รำมำ3-คลองลัดโพธ ิ์ 20 38 46 41 26 22 24 22 25 29 33 22 37 38 30 453 (Rama 3-Klong Latpo) บำงนำ-ตำเลอื่ น 8 12 11 20 9 8 8 7 7 7 20 18 17 20 12 184 (Bangna-Taluen) บำงนำนอก-บำงน ้ำผงึ้ นอก 26 40 63 48 26 25 25 24 27 25 34 32 45 41 29 510 (Bangnanok-Bangnampuengnok) เภตรำ-พระประแดง 51 74 77 57 39 38 41 40 38 41 61 68 77 68 44 814 (Petra-Phra Pradang) วบิ ลู ยศ์ ร-ี พระสมทุ รเจดยี ์ 47 71 71 53 48 31 30 23 28 28 46 50 54 58 56 694 (Wiboonsri-Pra Samutchedee)

APPENDIX 1 (Continued)

Boat size Engine Boat No. Long Width Depth Weight Power Passenger number Brand Piston (m.) (m.) (m.) (tongross) (Kw)

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

APPENDIX 1 (Continued)

Boat size Engine Boat No. Long Width Depth Weight Power Passenger number Brand Piston (m.) (m.) (m.) (tongross) (Kw)

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

APPENDIX 1 (Continued)

Engine Number of Number of service boats Boat Boat Engine No. Station Boat name power Piston Passenger boats Owner size name Weekday Saturday Sunday (hp) นาทนาวี 9.29 Isuzu 169.95 6 15 สุขเกษม6 2.38 Guardner 131.86 4 12 1 Pakkret – Wat Toey 5 4 3 4 เอกชน สุขเกษม9 3.55 Isuzu 101.00 4 15 สุขเกษม11 6.31 Isuzu 100.61 4 15 สุขเกษม14 8.87 Nisson 243.43 6 20 วัชรีวงศ์ 1 12.54 Hino 187.64 4 50 เทศบาลนคร วัชรีวงศ์ 3 4.35 Isuzu 96.53 4 10 Pakkret – ปากเกร็ด, วัชรีวงศ์ 5 13.05 Isuzu 175.39 6 20 2 6 4 4 4 Wachareewongse อบต. บางตะ วัชรีวงศ์ 7 7.82 Isuzu 99.25 4 15 ไนย์ วัชรีวงศ์ 8 26 Nisson 263.77 6 63 ดาวบ้านนา3 11.3 Isuzu 187.64 6 32 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 Nonthaburi – Bang Sri 3 7 4 4 4 กรมเจ้าท่า จ.ส.น.9 27.2 Guardner 152.28 6 120 Mueng 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

APPENDIX 1 (Continued)

Number of service boats Engine Number of Boat Boat Engine No. Station Boat name power Piston Passenger boats Owner size name Weekday Saturday Sunday (hp) บวรมงคล 2 8.83 Guardner 40.79 4 14 Thewes – บวรมงคล 3 9.57 Guardner 76.14 5 26 4 3 2 1 1 เอกชน Bawornmongkon ประเสริฐเจริญ 16.21 Guardner 91.28 6 30 ทรัพย์ Thewes – Wat กรมเจ้าท่า& 5 2 1 1 1 คฤหมงคล 1 11.75 Hino 157.72 6 30 Karuhabodee เอกชน สภ. 69 28.2 Guardner 183.55 6 15 สภ. 71 28.68 Guardner 152.28 4 12 Tha Phrachan – Wang 6 5 2 2 2 สุภัทรา สภ. 76 36.59 Cummins 354.86 4 15 Lang สภ. 77 49.7 Cummins 354.86 4 15 สภ. 78 32 Guardner 182.46 6 20 สภ. 69 28.2 Guardner 183.55 6 90 สภ. 70 28.2 Isuzu 152.28 6 90 Tha Maharaj – Wang 7 5 2 2 2 สุภัทรา สภ. 72 28.68 Guardner 152.28 6 90 Lang สภ. 77 49.7 Cummins 354.86 6 90 สภ. 78 32 Guardner 182.46 6 90

APPENDIX 1 (Continued)

Number of service boats Engine Number of Boat Boat Engine No. Station Boat name power Piston Passenger boats Owner size name Weekday Saturday Sunday (hp) 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

Tha Chang – Wang 8 8 2 2 สุภัทรา สภ. 74 29.59 Guardner 152.28 6 90 Lang 2

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

สภ. 78 8.87 Nisson 243.43 6 90

Tha Chang – Wat 9 5 2 2 2 สุภัทรา สภ. 69 9.29 Isuzu 169.95 6 90 Rakang

สภ. 70 2.38 Guardner 131.86 4 90

APPENDIX 1 (Continued)

Number of service boats Engine Number of Boat Boat Engine No. Station Boat name power Piston Passenger boats Owner size name Weekday Saturday Sunday (hp) โพธิ์อรุณ 12 21.11 Nisson 202.58 6 60 โพธิ์อรุณ 15 34.09 Nisson 167.91 6 60

10 Tha Tien – Wat Arun 4 3 3 3 เอกชน โพธิ์อรุณ 18 38.1 Guardner 182.46 6 60

โพธิ์อรุณ 20 37.31 Guardner 182.57 6 60

Assadang – Wat กรมเจ้าท่า & 11 1 1 1 1 กัลยาณ์ 12 16.44 Layland 203.94 6 60 Kalayanimit เอกชน

ปราณี 30.4 Guardner 87.21 6 50

ปราณี 20 31.32 Guardner 91.28 6 60

Rachawongse – เอกชน&กรม 12 5 4 4 4 ปราณี 21 31.32 Guardner 91.28 6 60 Dindang เจ้าท่า

ปราณี 44 33.11 Guardner 152.27 6 60

ปราณี 45 33.11 Guardner 152.27 6 80

APPENDIX 1 (Continued)

Number of service boats Engine Number of Boat Boat Engine No. Station Boat name power Piston Passenger boats Owner size name Weekday Saturday Sunday (hp) ปัญจทรัพย์ 2 24.33 Nisson 263.77 6 63 ปัญจทรัพย์ 3 30.06 Nisson 263.77 6 70

13 Sri Phraya – Klongsan 4 3 3 3 เอกชน ปัญจทรัพย์ 4 27.46 Nisson 263.77 6 63

ปัญจทรัพย์ 8 65.27 Nisson 283.99 6 100

ป. บูรพา 22.99 Hino 167.23 6 45

ป. บูรพา 1 22.94 Hino 161.79 6 45 กรมเจ่าท่า& 14 Oriental – Wat Suwan 4 3 3 2 เอกชน เกียรติชูชัย 19 32.62 Nisson 182.19 6 40

นาโชคชัย 10 31.25 Isuzu 161.79 6 50

สาธร 1 33.7 Nisson 223.14 6 90

กรมเจ้าท่า& 15 Sathorn – Pepsi 4 2 2 2 สาธร 2 33.7 Nisson 223.14 6 90 เอกชน

สาธร 3 52.09 Isuzu 274.64 6 110

APPENDIX 1 (Continued)

Number of service boats Engine Number of Boat Boat Engine No. Station Boat name power Piston Passenger boats Owner size name Weekday Saturday Sunday (hp)

Sathuphradit – Wat 16 2 1 กรมเจ้าท่า ประภามณฑล 20.2 Deutz 43.51 3 30 Bang Pueng พญาภุชงค์ 35.3 Cummins 354.86 6 40 Sathuphradit – Klong นาคราช 1 17 2 2 1 1 กรมเจ้าท่า Latluang พญาภุชงค์ 54.72 Isuzu 425.99 6 40 นาคราช 2

18 Rama 3 – Klong Lat Po 2 2 2 2 เอกชน ลัดโพธิ์ 65.56 Cummins 323.59 6 60

ช. ทรัพย์สมบูรณ์ 3.4 Yunmar 29.91 3 30 2 19 Klong Toey – Tuapai 3 2 2 - เอกชน เกษมสาคร 2.34 Isuzu 28.55 4 30

ส. ชูเกียรติ 2.15 Isuzu 40.57 4 30

มนัสสกุล 1 91.96 Hino 324.57 6 120

สมบัติมนัส 2 17.22 Hino 365.14 6 70 Bangnanok – 20 5 3 2 2 เอกชน Bangnampuengnok สมบัติมนัส 3 53.32 Hino 318.15 6 70

สมบัติมนัส 7 43.72 Hino 365.14 6 70

APPENDIX 1 (Continued)

Number of service boats Engine Number of Boat Engine No. Station Boat name Boat size power Piston Passenger boats Owner name Weekday Saturday Sunday (hp) กรมสรรพาวุธ

ทหารเรือ & สมบัติมนัส 32.59 Guardner 182.57 6 50 21 Bangna – Ta Luen 2 1 1 1 เอกชน

คงสาคร 1 คงสาคร 1 7.15 Hino 169.03 6 16

ชลโภค 1 40.15 Nisson 304.28 6 80

ภมรธาร 1 40.15 Nisson 304.28 6 80

22 Petra – Phra Phradang 6 4 4 4 เอกชน 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

APPENDIX 1 (Continued)

Number of service boats Engine Number of Boat Engine No. Station Boat name Boat size power Piston Passenger boats Owner name Weekday Saturday Sunday (hp)

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

เอกชน& สิทธิโชค 18 13.98 Hino 141.4 6 73 Wiboonsri – Phra 23 12 5 5 5 องค์การบริหาร Samut Chedi ส่วนจังหวัด 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

APPENDIX 2 Emission share of different boat types (%)

No Shuttle Pollutants Green Orange Yellow Gold Blue flag 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

APPENDIX 2 (Continued)

Green (%) Orange (%) Yellow (%) No flag (%) Gold (%) Blue (%) Shuttle boat (%) Pollutant 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

APPENDIX 2 (Continued)

Route 1 (%) Route 2 (%) Pollutant (Sriboonrueng-Pratunam) (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

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

APPENDIX 2 (Continued)

Koh Kret-Wat Nonthaburi-Bang Tha Tien-Wat Arun Sri Phraya- Klongsan Petra-Phra Pradang Wiboonsri-Phra Pollutants Sanamnue (%) Srimuang (%) (%) (%) (%) 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

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

APPENDIX 2 (Continued)

Chao Phraya boats Saen Saep boats Cross river ferries Pollutants 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

APPENDIX 3. Spatial distribution of emission

APPENDIX 3 (Continued)