curacao aviation environmental thesis

Running Head: AVIATION EMISSIONS IN CURACAO

Assessment of Curaçao Airport and Airlines Emissions with

Methods of Reduction

by

Jason-Craig Andrew Woolcock

Curaçao Civil Aviation Authority, 2016

THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR

THE DEGREE OF BACHELORS OF SCIENCE IN AIR TRANSPORT MANAGEMENT

CARIBBEAN AEROSPACE COLLEGE

JUNE 2016

© Jason-Craig Andrew Woolcock

AVIATION EMISSIONS IN CURACAO 2

ABSTRACT Greenhouse gas (GHG) emissions from civil aviation contribute to anthropogenic

climate change and are expected to increase significantly in the future. GHG emission

inventories exist for civil aviation at the global scale but not on Curaçao’s subnational scale.

In this thesis, I present what seems to be the first detailed analysis of the carbon footprint

(CF) of civil aviation in Curaçao together with an assessment of what measures can be put in

place to mitigate the CF. I calculated the CF of civil aviation in Curaçao and determined what

measures can be put in place. To reduce the CF of civil aviation in Curaçao, I recommend the

installation of Point of Use (POU) terminals at the passenger boarding bridges, the

construction of renewable energy power-plants for the airport, the use of vectors into final by

airlines wherever possible, the installation of a MD-80 drag reduction package by applicable

airlines, the upgrade of ground support equipment and the lift of the renewable energy power-

plant limit imposed on residential and commercial entities in Curaçao.


Table of Contents ABSTRACT.................................................................................................................2

Glossary of Terms and Units ...................................................................................6

Acknowledgements...................................................................................................8

Chapter 1: Introduction.............................................................................................9

Curaçao Introduction............................................................................................................................. 10 Hypothesis ............................................................................................................................................. 10 Research Questions ............................................................................................................................... 11 Project Plan ........................................................................................................................................... 11 Assumptions and Limitations................................................................................................................ 11 Major Research Results......................................................................................................................... 12 Value of Research ................................................................................................................................. 12 Introduction to Chapters........................................................................................................................ 12

Chapter 2: Aviation and its Impact on Climate Change: A Literature Review...13

Introduction ........................................................................................................................................... 13 Climate Change and its impact on the world ........................................................................................ 14 Calculating the Carbon Footprint of Civil Aviation.............................................................................. 14 Reducing the CF of Aviation ................................................................................................................ 15 Summary ............................................................................................................................................... 16

Chapter 3: Methodology .........................................................................................17

Introduction ........................................................................................................................................... 17 Methodology for Airlines LTO Cycle................................................................................................... 18

Airline Emission Formula................................................................................................................. 21 Data Limitations ............................................................................................................................... 23

Methodology for Airlines en-route climb, cruise and descent profiles................................................. 24 Data Limitations ............................................................................................................................... 25

Methodology for Airport Emissions ..................................................................................................... 26 Data Limitations ............................................................................................................................... 26

Chapter 4: Curaçao’s Aviation Carbon Dioxide Emissions ................................27

Introduction ........................................................................................................................................... 27 CO2 Emissions of Airlines..................................................................................................................... 28

Chart Showing Ratio of CO2 Emissions Among Airlines for 2014................................................... 29 Chart Showing Ration of CO2 Emissions Among Airlines for 2015................................................. 30 Air Berlin .......................................................................................................................................... 30


Air Canada........................................................................................................................................ 30 American Airlines ............................................................................................................................. 31 Avianca ............................................................................................................................................. 31 Avior.................................................................................................................................................. 31 Copa Airlines .................................................................................................................................... 31 InselAir.............................................................................................................................................. 32 JetBlue............................................................................................................................................... 33 KLM .................................................................................................................................................. 33 PAWA................................................................................................................................................ 33 Rutaca ............................................................................................................................................... 33 Sunwing Airlines ............................................................................................................................... 34 Suriname Airways ............................................................................................................................. 34 TUI .................................................................................................................................................... 34 Westjet............................................................................................................................................... 34

Airport CO2 Emissions.......................................................................................................................... 34 Summary ............................................................................................................................................... 35

Chapter 5: Applicable Carbon Dioxide Reduction Measures..............................36

Introduction ........................................................................................................................................... 36 Alternative Airport Energy Sources ...................................................................................................... 36

Solar Energy ..................................................................................................................................... 37 Wind Energy...................................................................................................................................... 37 Wave Energy ..................................................................................................................................... 38

Alternative Aviation Fuels .................................................................................................................... 39 Ground Support Equipment .................................................................................................................. 39 Point of Use Gate Terminals ................................................................................................................. 40 Super 98................................................................................................................................................. 41 Vectors Into Final.................................................................................................................................. 41 Summary ............................................................................................................................................... 42

Chapter 6: Conclusion............................................................................................43

Summary of Results .............................................................................................................................. 43 Recommendations Resulting from Research ........................................................................................ 44

Recommendation 1: The installation of POU terminals................................................................... 44 Recommendation 2: The abolishment or raise in the limit regulation of the feed-in tariff system... 44 Recommendation 3: The installation of wind turbines. .................................................................... 45 Recommendation 4: The upgrade of ground support equipment...................................................... 45 Recommendation 5: Increased Vectors into Final Approaches. ...................................................... 45


Recommendation 6: MD-80 Drag Reduction Packages Installation. .............................................. 46 Contributions of Research..................................................................................................................... 46 Limitations of Research ........................................................................................................................ 46 Suggestions for further research............................................................................................................ 46 Final Thoughts....................................................................................................................................... 47

Bibliography ............................................................................................................48

APPENDIX 1: LTO FUEL BURN CALCULATION DATA........................................51

APPENDIX 2: AIRLINE AND GSE CO2 EMISSIONS ..............................................56

Abbreviations ........................................................................................................................................ 56 Emissions 2014 ..................................................................................................................................... 58 Emissions 2015 ..................................................................................................................................... 60


Glossary of Terms and Units ACERT Airport Carbon Emissions Research Tool

ACI Airport Council International

ACRP Airport Co-operative Research Program

APU Auxiliary Power Unit

ATC Air Traffic Control

CDU Computer Diagnostics Unit

CF Carbon Footprint

CO2 Carbon Dioxide

DC-ANSP Dutch Caribbean Air Navigation Service Provider

EEDB Engine Emission Database

FAA Federal Aviation Administration

FIR Flight Information Region

GHG Greenhouse Gas

ICAO International Civil Aviation Organization

ICE Internal Combustion Engine

IFSET ICAO Fuel Saving Estimate Tool

KW Kilowatt

KWh Kilowatt Hour

LTO Landing and Takeoff Operations

MSL Mean Sea Level

N1 Low Pressure Turbine Rotation Speed

PBN Performance Based Navigation


PCA Pre-conditioned Air

POU Point of Use Terminal

STAR Standard Terminal Arrival Route

ToC Top of Climb

ToD Top of Descent

UID Unique Identification


Acknowledgements I would like to thank Lt. Col (Ret’d) Oscar Derby for presenting me this rare

opportunity to conduct this assessment of Curacao’s aviation emissions. I would also like to

thank Dr. Meredith Derby, Mr. Leroy Lindsay and Ms. Althea Roper for the much needed

support and advice in regards to this thesis.

I will also like to acknowledge the employees at the CCAA and the DC-ANSP for the

greatly appreciated tireless support and limitless information that I needed to execute this

research.

Last but not least, I would like to thank the pilots and station managers of the airlines,

the managers of the ground handling companies and the airport operations and finance

personnel of Hato International that I have interviewed. Without your co-operation, this

research would not have been possible.


Chapter 1: Introduction The Aviation Industry serves as an important means of travel in today’s world.

Today’s global economy is dependent on it as one of its key facilitators. Aviation contributes

about 3.5% of the global GDP as it underpins almost every aspect of modern life. It provides

the quickest means for travelers and cargo of all types to span cities and even continents, a

feat that took a considerably longer time less than 100 years ago. Fueled by increasing

demand, the aviation industry continues to grow at a considerable rate with the need of larger

airports, more aircraft and increased usage of airspace to accommodate the need for travel.

Consequently, as the industry grows, so does its carbon footprint on the environment.

The industry is a contributor to one of the most critical environmental problems,

anthropogenic climate change. In 2010, the aviation industry was measured to be accountable

for 2% of the total carbon dioxide (CO2) global and about 12% of CO2 emissions from all

transportation sources(International Civil Aviation Organization, 2010, p. 38). Air travel is

projected to increase at an annual rate of 4.5% per year towards 2020 (International Civil

Aviation Organization, p. 6) therefore; it is imperative that measures are put in place to

achieve a reduction in carbon emissions. In the face of adverse environmental changes caused

by the notable increases in CO2 emissions, numerous companies, organizations and even

individuals have announced their intent and dedication to pursue means and measures to

combat this emissions issue. In 2009 the International Civil Aviation Organization (ICAO),

the global body tasked with the standards and recommended practices of the aviation

industry, put forth a new goal. ICAO agreed for an annual improvement of 2% in fuel

efficiency of the international civil aviation in-service fleet for the medium-term (up to 2020)

and an aspirational global goal for an annual improvement of 2% in fuel efficiency of the

international civil aviation in-service fleet for the long-term (up to 2050) as part of the

contribution of the sector to stabilize and subsequently reduce aviation’s absolute emissions

contribution to climate change (ICAO Comittee on Aviation Environmental Protection, 2010,

p. 9).

There are numerous activities in the aviation industry that contribute to GHG

emissions. These activities all have to be considered in the complete assessment of Curaçao’s

aviation industry. Apart from emissions that are generated by aircraft, significant emissions

are also contributed by the vast supporting infrastructure that is required for aviation. These

include:


• Airport operations – Runway and taxiway lighting, air conditioning

• Auxiliary airport services – Catering, laundry, and ground services

In sight of this, the assessment and mitigation of CO2 emissions in the aviation sector

is one that requires a multi-layered approach.

Curaçao Introduction

Curaçao is a Caribbean island and also a part of the Netherland Antilles. It spans an

area of 444 km2 or 171.4 square miles and as of the 2015 population census, has 156,971

inhabitants (Central Bureau of Statistics Curaçao). Hato International Airport, ICAO code

name TNCC, is the sole airport that serves this island. Annually, it handles on average more

than 1.6 million passengers, greater than 13,000 tonnes of cargo and facilitates in excess of

22,000 aircraft movements (Curaçao Investment and Export Promotion Agency, 2015),

serving as a key facilitator towards Curaçao’s industries. The Dutch Caribbean Aeronautical

Service Provider (DC-ANSP) provides flight services for all aircraft operating within the

Curaçao FIR. In addition, Curaçao’s main sources of economy are petroleum refining and

bunkering, tourism and shipping (Central Intelligence Agency), all of which heavily rely on

the aviation industry.

Curaçao is not a newcomer in the renewable energy industry. Its first wind turbines

became operational in 1993 with a second wind farm constructed in the year 2000, totaling

12 MW. Following their phenomenal success, in 2011 both wind farms were renovated with

5 turbines each with the total power output of 30 MW between them. As of writing, these

wind farms produce approximately 20% of the islands electrical energy needs(National

Renewable Energy Labratory, 2015, p. 3).

Hypothesis The hypothesis of this thesis is for Curaçao’s aviation sector to achieve a 2%

reduction per year in carbon emissions by 2020.


Research Questions To prove or disprove my hypothesis I was guided by the following two research

questions

1. What is the Carbon Footprint (CF) of Curaçao ’s aviation sector?

2. What measures can be put in place to reduce the CF of Curaçao ’s aviation sector and

by how much?

Project Plan This thesis will be focused on two areas of the environment in Curaçao. They are:

• The airlines that both serve Curaçao and operate within the Curaçao FIR

• Hato International Airport

An environmental assessment will be undertaken to determine the current level of

carbon dioxide production in both areas of focus. Measures towards the reduction of

emissions will be theoretically applied and their potential impact calculated. The hypothesis

will be proven or disproven based on the findings of this research. Conclusions will be drawn

to close the document and recommendations will be given for the improvement of the

aviation environment of Curaçao.

Assumptions and Limitations

In order to increase the accuracy and decrease the erroneousness of the data given,

assumptions and limitations have been placed. These are:

1. Airlines, the airport and the aeronautical service provider in this research repeatedly

use unvaried equipment.

2. Airlines in this research repeatedly use unvaried routes.

3. Airlines, the airport and the aeronautical service provider in this research repeatedly

use unvaried procedures.

4. Cargo, state owned and military traffic are not included in this research.

5. Fuel burned by the airport for energy generation is not included in this research.

6. Fuel burned by airport tenants for energy generation is not included in this research.


Major Research Results In Curaçao, the total aviation CO2 emissions for the year 2014 and 2015 are 69,412

tonnes and 83,773 tonnes respectively. Through this research, it is found that the emissions

can be reduced by a total of 4.67% for the year 2015 using the recommendations within this

thesis. This result is based on the current renewable energy limitation that is imposed on

residential and commercial installations which applies to Hato International Airport. If this

limit was lifted however, the year 2015 emissions can be reduced by a total of 9.86% using

the recommendations within this thesis.

Value of Research This research will provide multiple benefits. One benefit is that it provides a detailed

snapshot of the aviation-generated CO2 emissions in Curaçao. It is also, to the best of my

knowledge, the first of such work in Curaçao. This snapshot will allow us to understand the

present situation in Curaçao as well as to help pinpoint problem areas for emission reduction

focus. Scholars, policymakers and practitioners in the aviation field should find these results

useful.

Secondly, while this thesis focuses on Curaçao’s aviation environment, it can be used

as a template for emissions research in other jurisdictions.

Introduction to Chapters

Following this introductory chapter, the second chapter presents a review of the

literature on the CF of aviation and of how to assess the emissions of the aviation industry.

The third chapter explains the methodology adopted for this thesis, while the fourth chapter is

a detailed microanalysis of the CF of civil aviation in Curaçao. In the fifth chapter, I discuss

measures that can be implemented to reduce the CF and quantify the reduction effect of each

measure. Recommendations are presented in the concluding sixth chapter.


Chapter 2: Aviation and its Impact on Climate Change: A

Literature Review

Introduction This chapter contains a review of literature on the carbon footprint (CF) of aviation.

This serves to establish the context for understanding the specific focus chosen for my

research. Most of these documents are published by the International Civil Aviation

Authority, the global body within the United Nations responsible for the standards and

recommended practices in the industry. Due to the growing concerns and interests in the

environment, they are now leading the charge in aviation environmental protection. Other

important documents are from Airport Cooperative Research Programme. From the published

documents of both these organizations, I understood how to conduct a CO2 emission analysis

of my two areas of concern: the airport and the airlines operating in the Curaçao FIR.

In the review of literature for the environment, there is a wide gamut of published

aviation environmental reports, a subset of global reports that address climate change on a

whole. I reviewed a few documents concerning what climate change is and its impact on the

world. My specific focus however was on literature related to the calculation of the CF and

methods to reduce it. With this, the literature is divided into 3 areas, each addressed in a

separate subsection of this chapter.

The first area of work is related to establishing what climate change is and its effect

on the global environment. This details the changes in the earth’s atmosphere and the

subsequent impacts that it has on the land, the people, the economy and the wildlife. This

section will give light to why anthropogenic climate change is a serious threat and the degree

of urgency that we must take action to lower our emissions.

The second area of work is related to analyzing the methods of calculating the CF of a

country. The four main pollutants emitted are aerosols, water vapor, nitrogen oxides, and

CO2. Of these, CO2 emissions are the dominant climate change-related impact of the aviation

transportation system. For this reason, I chose to focus my research on CO2 emissions.

The third area of work is related to analyzing the methods to reduce the CF of the

aviation sector. I establish that there are many options in the implementation of reduction


measures, however reduction measures must be tailored to suit the conditions present in the

environment.

Climate Change and its impact on the world There are a myriad of climate change documents that exists. The rapid growth of

literature in this subject is a testament to the increasing attention paid to the negative climate

change.

One of the best surmises of the effects of climate change is documented in Turn Down

The Heat (World Bank, 2013). It details the numerous climatic impacts on each continental

region, notably for the Caribbean, a rise in the sea level of over 100 cm and the destruction of

marine ecosystems if temperature climbs above 4 degrees Celsius. As Curacao is a relatively

flat island that heavily relies on tourism, such a rise in sea level would effectively destroy the

beaches and coral reefs that are a main attraction in the tourism industry. As Hato

International Airport’s passengers are mainly tourists, such an environmental change would

have a disastrous impact on tourism and thus, passenger statistics. ICAO’s Aviation’s

Contribution to Climate Change (International Civil Aviation Organization, 2010) and

Environmental Report (International Civil Aviation Organization, 2013) details the various

effects that civil aviation has on the environment, particularly civil aviations role of the CO2

accumulation in the environment.

In addition to expert literature, there exists an increasingly large body of popular

literature discussing the relationship between climate change and aviation emissions. For

example, the BC-based David Suzuki Foundation has analyzed the CO2 intensity of aviation

compared to other modes of transportation, GHGs and contrails produced by airplanes,

aviation emission mitigation measures, and the potential impact of new technologies (David

Suzuki Foundation).

Calculating the Carbon Footprint of Civil Aviation

Upon research, there are a countless number of carbon emission calculators on the

internet with quite a few designed for aviation emission calculation. However, my research

was focused on the emissions contributed within Curacao’s aviation sector. There are


currently no carbon emission calculators that can calculate a detailed snapshot of an aviation

sector. Instead, there are methodologies that are designed to calculate certain prospects of an

aviation sector.

ICAO has produced numerous manuals concerning aviation emissions. These detail

how to calculate the emissions of certain areas of the aviation sector to the potential measures

that exist to reduce these emissions. They are well documented as they layout what data you

will need to calculate the emissions as well as the limitations of each method that is

presented. Airport Air Quality Manual(International Civil Aviation Organization, 2011)

details on how to calculate an Airline Landing and Takeoff (LTO) emissions as well as the

data needed in conducting the research and the limitations of such calculations. Airport

Council Research Programme’s (ACRP) Guidebook on Preparing Airport Greenhouse Gas

Emission Inventories (Airport Cooperative Research Programme, 2009) also gives a

guideline on how to calculate airport and airline emissions as well as details the data needed

in conducting the research and its limitations.

Reducing the CF of Aviation In general, the motivation for calculating the CF of aviation (or any other human

activity) is to provide a basis or rationale for reducing the footprint. In my research, I have

attempted to not only calculate the CF of aviation in Curacao but also to theoretically apply

efforts to reduce it. I therefore reviewed the literature on reducing the CF of aviation. There

are two main areas of change in the aviation industry to reduce carbon emissions,

technological and non-technological.

The generally accepted idea in the literature is that short and medium term emissions

reduction will come from incremental technological changes. These are composed of

advances in alternative aviation fuels, advances in the renewable energy sector and advances

in engine design. ICAO’s Operational Opportunities to Reduce Fuel Burn and Emissions

(International Civil Aviation Organization, 2014) outlines measures that are applicable in

aviation to reduce the CF. With that document, I was able to get the baseline understanding

of what could be done on an aviation standpoint to lower the CF. ACRP Handbook for

Evaluating Emissions and Costs of APU’s and Alternative Systems(Airport Cooporative

Research Programme, 2012) details the fuel burn of aircraft APU’s and the significant

savings to be obtained by operating POU terminals in place of APU’s. Finally, ICAO’s Flight


Path to Sustainable Future (International Civil Aviation Organization, 2013) reviewed the

positive outcome of numerous bio-fueled flights. Of specific note is that Air Canada, using

alternative aviation fuel and other notable methods, reduced that recorded flight’s CO2

emissions by approximately 40%.

Summary There is a broad literature on aviation and its impact on climate change, which for

purposes of this review was divided into three topic areas. The impact of climate change on

the environment was reviewed as well as the role that civil aviation plays in climate change.

It was found that ICAO and ACRP have numerous documents that detail how to assess the

aviation CF of a country. Finally, methods to reduce the aviation CF were detailed by ICAO

and ACRP documents.


Chapter 3: Methodology

Introduction The aviation environment of Curaçao could be split into two main sections, the

emissions of the airport serving Curaçao and the emissions of the airlines serving Curaçao.

The airline emissions can further be split into two categories. First category is the Landing

and Takeoff (LTO) cycles. This would be constituted of the activities between the approach

from and below three thousand feet to the departure below and to three thousand feet. Three

thousand feet is the upper limit mixing altitude regarding the emissions for airports (Airport

Cooperative Research Programme, 2009, p. 22). This height is also important as for my

research as I employ various methods in order to calculate emissions. In terms of emissions

of airlines, this height represents the border between the two methods of data calculation. The

methods of calculations for airlines were derived from various ICAO and ACRP documents,

as well as ICAO and Airport Council International (ACI) tools such as IFSET and Airport

Carbon and Emissions Reporting Tool (ACERT).

There are quite a few aviation emissions calculators that are available online.

However, in my literature review I did not find any similar research completed to wholly

calculate aviation environmental emissions for an airport and the airlines serving it. I did find

however thorough documentation through ICAO and ACRP on how to carry out research in

this field and how to calculate emissions. Through this guide, I devised my own

methodological approach for CO2 emission calculation based on a compilation of existing

methods. In this chapter, the research carried out is divided into three sections with each

explaining the approach used to answer each emission sector that I have established.

There are three separate methods of data calculation that I used in estimating CO2

greenhouse gases for separate areas of my research. These are

1. For the airlines LTO cycle:

This is calculated using the Airport Air Quality Manual’s formulae, ICAO’s

EEDB, data from research regarding equipment description used by the

airlines, data recorded regarding the time in modes for each airline operation

and data from pilots regarding thrust settings for each time in mode. Grounds


Support Equipment (GSE) emissions were also calculated in conjunction with

direct airline emissions.

2. For the airlines en-route climb, cruise and descent profiles:

The IFSET tool was used in this instance to calculate fuel burn in the en-route

climb, cruise and descent profiles of flight. DC-ANSP flight data was used to

provide the altitudes, routes, type of equipment as well as time within the

Curaçao FIR

3. Airport Emissions:

The country’s emission factor and the airports yearly electrical usage were

used to generate emissions data for Hato International. Electrical usage data

was gathered from the airport’s finance department that holds the electrical

energy usage records.

Methodology for Airlines LTO Cycle

To calculate the carbon dioxide emissions generated from airline operations regarding

the LTO cycle, the cycle was split into multiple segments. The segments are comprised of:

1. Aircraft descent and approach from 3,000 feet Mean Sea Level (MSL) to touchdown.

2. Deceleration to taxi.

3. Taxi from the runway to the gate or ramp.

4. Auxilary Power Unit (APU) usage and GSE service.

5. Taxi from gate or ramp to runway.

6. Takeoff.

7. Initial climb from takeoff to 1,000 feet MSL.

8. En-route climb from the 1000 feet MSL throttle back to 3,000 feet MSL.

APU and GSE emissions are not normally included as a component of an LTO.

However, considering the extensive usage of this equipment observed, it was considered

as part of the LTO for ease of data calculation. The mean sea level height of 3,000 feet

was used as the point where I would end one method of calculations used to calculate

emissions and begin another. This point is defined as the mixing height of an aerodrome.


It is used due to the fact that the methodology used to calculate the LTO emissions cannot

account for the decrease in fuel flow as the aircraft gains height. Thus, these emissions

published by the EEDB only refer to operations at or below this mixing height as shown

in the Air Quality Manual (International Civil Aviation Organization, 2011, pp. 3-A1-2).

To lend credibility to my estimates, most of the techniques I used are ICAO and ACRP

defined procedures and certified data to calculate emissions in this section, all of which

are described below.

The Airport Air Quality Manual published by ICAO defines multiple methods in

quantifying the emissions generated by airline activities. As defined by the document, I

used the advanced approach, which requires ICAO’s EEDB database, aircraft fleet

information and thrust settings from the airlines in scope and time-in-mode data from the

airlines in scope. I chose to use the advance approach due to the fact that it is the most

accurate method of quantifying emissions aside from getting actual real-world emission

data from the airlines themselves.

In the advanced approach, the air quality manual defines formulae to be used in

conjunction with the supplied data above. Due to the complexity of the formulae and

large amount of data to be processed, Microsoft Excel was used to calculate the

emissions. ICAO’s EEDB database was downloaded from their website to be used in

conjunction with the model. The aircraft fleet information such as the aircraft, engine and

APU model, APU fuel flow and thrust settings were gathered by interviewing the pilots

directly while in their cockpit during turnaround times. This made it easier as being in the

cockpit, they had the relevant documents at hand to disseminate this information as well

as to retrieve active APU fuel burn information from the Computer Diagnostics Unit

(CDU) equipped on their aircraft. The time-in-mode data was gathered by myself

manually by timing the approach from 3000 feet MSL, landing roll-out, taxi-in, taxi-out,

take-off initial and en-route climb to 3000 feet MSL. I was able to accurately determine

where they crossed 3000 feet and where each phase of operation started by using flight

radar tracking, visual confirmation and live air traffic control (ATC) broadcasts.


The Airlines interviewed and the types of equipment they use are as follows:

AIRLINES AIRCRAFT

AIR BERLIN A330-200

AIR CANADA ROUGE A319-100

AMERICAN AIRLINES B737-800

AVIANCA

A318 A319 A320 A321

AVIOR 737-200

COPA AIRLINES E190 B737-700

INSEL AIR MD-83 MD-82 F70

JETBLUE A320

KLM 747-400 A320-200

RUTACA 737-200

Sunwing Airlines 737-800

SURINAM AIRWAYS 737-300


TUI 787-8 767-300

WESTJET 737-700

Airline Emission Formula

As the thrust settings employed by the airlines can vary between different airlines, the

standard certified thrust settings for each engine dataset couldn’t be used for data precision.

Also, due to the fact that the fuel flow varies exponentially with the thrust setting, it cannot

be modeled by a standard linear equation. The Airport Air Quality Manual (International

Civil Aviation Organization, 2011, pp. 3-A1-15) defines two quadratic formulae for use when

varying thrust settings are given, one when commanded thrust is above 85% maximum rated

thrust and the other when commanded thrust is below 85% and above 65% maximum rate

thrust. Due to the fact that on approach and landing, the airlines were observed to be using

thrust settings consistently below 65%, I elected to modify the second formula with

commanded thrust settings from 85% to and above 30% maximum rated thrust. Using the

EEDB, the formula takes specific fuel flow settings from defined thrust points and models a

curve that more precisely emulates the rise in fuel flow with thrust settings than a linear

equation could.

The formula is defined as below:

Y = AX2 + BX + C

There are three known points as defined by the EEDB:

Y1 = AX12 + BX1 + C

Y2 = AX22 + BX2 + C

Y3 = AX32 + BX3 + C

The calculation of the variables A, B and C are as follows

A = (Y3 –Y1) / ((X3 – X1) * (X1 – X2)) – (Y3 – Y2) / ((X3 – X2) * (X1 – X2))

B = (Y3 – Y1) / (X3 –X1) – A * (X3 + X1)

C = Y3 – A * X32 – B * X3

For each engine Unique Identification (UID), the variables A, B and C are not constant.


X is defined as the thrust setting while Y is defined as the fuel flow. For thrust

settings above 85% maximum rated thrust, X1 is the 30% thrust setting, X2 is the 85% thrust

setting and X3 is the 100% thrust setting. For thrust settings from and below 85% to and

above 30% maximum rated thrust, X1 is the 7% thrust setting, X2 is the 30% thrust setting

and X3 is the 100% thrust setting. Y1, Y2 and Y3 is the corresponding fuel flow in kilograms

per second (kg/s) to the commanded thrust X1, X2 and X3.

If the resulting graph were plotted, it would have an appearance similar to this:

As the formula uses data from the EEDB, it is crucial to get the exact engine model

number, even down to the engine revisions. This is because any revisions to the engine, such

as a new combustor, new injectors, a smoke kit etc. can have a considerable impact on the

fuel consumption and thus CO2 emissions.

The excel sheet used was constructed to automatically retrieve the fuel flow data from

the corresponding thrust points in the EEDB database by using the engine Unique

Identification (UID) entered. From there, it calculates the fuel flow per second from the N1

and Engine Pressure Ratio (EPR) settings collected from the pilots. The N1 and EPR settings

were converted to thrust settings by dividing each setting by the maximum N1 speeds or

EPR’s for each engine. Using the time-in-mode data gathered, the fuel flows in each mode


were multiplied to gain the total fuel burned in each segment of the LTO cycle. This was also

coupled with the fuel burned during APU operation in order to attain the fuel burned during

the LTO cycle, calculated using the APU fuel burn given by the pilots and the gate times

published by the airport. The fuel consumption correction of 3% was also factored into each

LTO phase calculation as recommended by the Air Quality Manual (International Civil

Aviation Organization, 2011, pp. 3-A1-19). Specifically for the Fokker F50 aircraft, as their

Pratt and Whitney PW125 and PW127 engines are not detailed in the EEDB, the LTO fuel

burn figure of 200 kg is used, taken from the Airport Air Quality Manual (International Civil

Aviation Organization, 2011, pp. 3-A1-31).

The DC-ANSP provided me with the traffic data within Curaçao’s Flight Information

Region (FIR) for both the years 2014 and 2015. Using this, I could then extrapolate by excel

query how many times each airline operated a specific aircraft type to and from Curaçao in a

year. This data would then be used to calculate how many LTO’s a particular type of aircraft

had from an airline and as such, how much fuel it burned for that particular year. Using the

standard of 3.157 kg of CO2 emitted for each kilogram of Jet-A burned (International Civil

Aviation Organization, 2011, pp. 3-A1-31), the amount of CO2 that was released for airline

operations in 2014 and 2015 was then calculated. These CO2 results were combined with

GSE equipment CO2 emissions. The emissions for the GSE were calculated using the figures

of 18 kg of CO2 for narrow body aircraft and 58 kg of CO2 for wide-body aircraft, figures

taken from the Airport Air Quality Manual (International Civil Aviation Organization, 2011,

pp. 3-A2-6).

With this, the calculation of aircraft related emissions by in the LTO for Curaçao was

calculated for the years 2014 and 2015.

Data Limitations

My limitations of Curaçao’s airlines LTO CO2 emissions are as follows:

1. EEDB data is created using newly built and certified engines. ICAO recommends a

correction factor of +3% on the fuel flows to simulate operational wear and tear on

the engine. The airlines that serve Curaçao operate an airline fleet that varies wildly in

age. For example, TUI operates a Boeing 787-800, an aircraft that is around 5 years

old in operation while Rutaca operates a Boeing 737-200, an aircraft that is more than


30 years old. While airframe age is not closely representative of the engine age, it

does stand to reason that the engines on a particularly older airframe are more likely

to have greater hours than an engine on a newer airframe. With such a variance, the

correction factor may be over estimating on some airlines and under estimating on

others.

2. EEDB data is created with engines that have no accessories. Accessories such as

engine bleed, hydraulic pumps and electrical generators would increase the load, and

conversely, the fuel burn of an engine. As, in the real world, aircraft engines are

tasked with electrical generation and have hydraulic and pneumatic loads, actual fuel

burn may be higher than estimated.

3. The environment in the EEDB databank is of the international standard atmosphere

(ISA). No corrections have been made for any variances in temperature, pressure and

humidity experienced at Curaçao International Airport, all of which have an impact

on the performance of the engine.

Methodology for Airlines en-route climb, cruise and descent profiles ICAO’s Fuel Saving Estimate Tool (IFSET) was used to generate the climb fuel burn

from above 3,000 feet MSL to cruise altitude in the departure phase, the cruise altitude fuel

burn within Curaçao’s FIR and the descent fuel burn from cruise altitude to 3,000 feet MSL

in the arrival phase. The program uses fleet data from various airlines around the world to

generate an average performance model that would be used to simulate fuel burns of the

parameters entered by the user. The data used to supplement the program was taken from the

average of the flight levels that the airlines used, the time spent within the Curaçao FIR and

the fleet data of the airlines.

First, a profile of the airline being measured was entered. In filling out the operational

definition, the aircraft entered was the aircraft group that aircraft being tested belonged to.

For base flights, only the figure 1 was entered as I aimed to get the fuel burn of a single cycle


and then use the number of cycles provided by the DC-ANSP. The new flights input box was

left blank, as this was not used. The remaining trip distance was also left blank; the program

however uses a default value based on worldwide data.

Secondly, the current procedure was defined. First, the descent action was listed. The

altitude chosen to descend from was the average cruise altitude of the aircraft in that year.

The altitude chosen to descend to was 3,000 feet MSL. With these two parameters entered,

the program automatically calculates optimally how many nautical miles (NM) it would take

for this aircraft to execute this operation. Next, the cruise operation before descent was

defined. The cruise altitude is the average altitude for the aircraft in that year. The distance in

cruise is the total distance covered in the FIR subtracted by the distance covered in descent

that was calculated by the program previously; this would yield the distance covered in cruise

between entry into the Curaçao FIR and Top of Descent (ToD). Next, the climb operation

from 3,000 feet MSL to cruise altitude was defined. The cruise altitude chosen to climb to is

the average altitude for the aircraft in that year. With the initial and cruise altitudes defined,

the program automatically calculates optimally how many nautical miles it would take for

this aircraft to execute this operation. Lastly, the cruise operation after climb was defined.

The cruise altitude is the average altitude for the aircraft in that year. The distance in cruise is

the distance covered in the FIR subtracted by the distance covered in the climb that was

calculated by the program previously; this would yield the distance covered in cruise between

Top of Climb (ToC) and exit out of the Curaçao FIR.

With the definitions outlined, the program was then run to generate an estimate of the

fuel burned in each phase of operation; cruise, climb and descent. These were then entered

into the excel spreadsheet where it was added to the fuel burn of the LTO’s and multiplied by

the amount of LTO’s for the specific year to attain the total fuel burn for the year. It was then

converted to CO2 emissions by multiplying it by the standard conversion factor of 3.157 kg

per 1 kg of Jet-A.

Data Limitations

My limitations in the calculation of the airlines’ climb, cruise and descent emissions

are as follows:

1. The data the program uses to calculate is a generalization of worldwide data gathered

from airlines. The fuel burn estimates are taken and averaged from a worldwide fleet,

which may not be subject to Curaçao’s environment.


2. The program cannot account for winds aloft, temperature and other environmental

factors that can affect aircraft performance.

3. The program only produces fuel burn results that are rounded to the hundreds of

kilograms. This fuel burn generalized estimate coupled with the aircraft general

estimate may yield a large source of error when compared to each individual aircraft’s

real world fuel burn.

Methodology for Airport Emissions The CO2 emission regarding Hato International is relatively simple to calculate. Hato

International Airport utilizes Curaçao’s electrical grid to supply it with electricity during

operations. A company called AquaElectra provides the electricity for use to the country.

Hato International currently does not have any alternate means of electrical energy apart from

the backup generators that are used in the event of a power outage. The emission factor for

the country of Curaçao was researched from the ACERT tool and the total electrical

consumption for the year 2014 and 2015 for Hato International Airport were calculated using

data from the finance department of the airport. Multiplying the total Kilowatts hours (KWh)

used by the airport by the emission factor for the country’s electrical grid, the CO2 emissions

that the airport generates off-site can be derived.

Data Limitations My limitations in the calculation of the airports CO2 emissions are as follows.

1. There may be losses in the transfer of electrical energy from the power station to the

airport. Thus the energy consumed by the airport also would include the energy lost

during transmission, which is not calculated in this research.


Chapter 4: Curaçao’s Aviation Carbon Dioxide Emissions

Introduction The purpose of this chapter is to provide a detailed snapshot of the CO2 emissions

being generated by aviation related activities in the country. The CO2 emissions that this

research details for Curaçao are comprised of:

1. The emissions from airlines that are serving Curaçao while within the Curaçao FIR

2. The airport emissions from activities related towards the service of these airlines.

A chart of emissions between the airlines and the airport can be found below, 1 being

year 2014 and 2 being year 2015.

5,555,552 5,939,640

63,856,787

77,833,750

0

10,000,000

20,000,000

30,000,000

40,000,000

50,000,000

60,000,000

70,000,000

80,000,000

90,000,000

1 2

Chart of Emissions by Source

Airport

Airlines


The CO2 emissions for flights are analyzed by airlines. Calculation results are

summarized in this chapter. Detailed numerical results for all calculation can be found in the

tables in Appendix. Calculations are discussed in the following order:

1. CO2 emissions of the airlines

2. CO2 emissions from the airport

CO2 Emissions of Airlines

To determine the CO2 emissions for the airlines, the emissions for the airlines LTO,

cruise, climb and descent within the Curaçao FIR were calculated and totaled. The CO2

emissions for 2014 were calculated to be 63,857 tonnes. For 2015, the CO2 emissions

increased to 77,834 tonnes, a 22% increase of CO2 emissions from the previous year. This

increase can be mostly attributed to increased aircraft movements at Hato International

Airport.

A total of 15 airlines were analyzed for CO2 emissions. Their totals separately can be

found below.

AIRLINES Tonnes 2014

Tonnes 2015

AIR BERLIN 1,290 1,542

AIR CANADA 224 693

AMERICAN AIRLINES 8,815 9,178

AVIANCA 2,283 2,401

AVIOR 809 1924

COPA AIRLINES 1,205 1,281

INSEL AIR 28,179 33,606

JETBLUE 99 1,131

KLM 13,043 15,605

PAWA 0 971

RUTACA 343 1,173

SUNWING AIRLINES 0 226

SURINAM AIRWAYS 1,496 1,769


TUI 5,865 6,303

WESTJET 206 31

Chart Showing Ratio of CO2 Emissions Among Airlines for 2014

For this year, 63,850 tonnes of CO2 was generated by the airlines. The ratio of which

is shown below:

AIR BERLIN; 2% AIR CANADA;

0%

AMERICAN AIRLINES; 14%

AVIANCA; 4%

AVIOR; 1%

COPA AIRLINES; 2%

INSEL AIR; 44%

JETBLUE; 0%

KLM; 21%

PAWA; 0% RUTACA; 1%

SURINAM AIRWAYS; 2%

TUI; 9%

WESTJET; 0%

CO2 TONNE RATIO 2014


Chart Showing Ration of CO2 Emissions Among Airlines for 2015

For this year 77,834 tonnes of CO2 was generated by the airlines, the ratio of which is

shown below:

A detailed breakdown of each airline is provided below.

Air Berlin

Air Berlin operates a long haul route between Curaçao and the city of Dusseldorf in

Berlin using Airbus A330 aircraft. In 2014 it was the 7th most emitter of CO2 emissions in its

operations, emitting 1,290 tonnes of CO2 through the combination of flight and gate

operations. In 2015, it dropped as the 8th most emitter of CO2 emissions in its operations

though it increased in emissions, emitting 1,542 tonnes of CO2.

Air Canada

Air Canada and Air Canada Rouge operates a medium haul route between Curaçao

and the two cities of Montreal and Toronto respectively in Canada, using the Airbus A319

aircraft. In 2014 it was the 11th most emitter of CO2 emissions in aircraft operations, emitting

AIR BERLIN; 2% AIR CANADA; 1%

AMERICAN AIRLINES; 12%

AVIANCA; 3%

AVIOR; 3%

COPA AIRLINES; 2%

INSEL AIR; 43%

JETBLUE; 1%

KLM; 20%

PAWA; 1% RUTACA; 2%

Sunwing Airlines; 0%

SURINAM AIRWAYS; 2%

TUI; 8%

WESTJET; 0%

C02 TONNE RATIO 2015


224 tonnes of CO2. In 2015, it dropped as the 13th most emitter of CO2 emissions, although its

emissions increased to 693 tonnes of CO2.

American Airlines

American Airlines operates a short haul route between Curaçao and Miami in the

United States using the Boeing 737-800. In 2014 it was the 3rd most emitter of CO2 emissions

in its operations, emitting 8,815 tonnes of CO2. In 2015 it was also the 3rd most emitter of

CO2 and generated a CO2 increase to 9,178 tonnes.

Avianca

Avianca Airlines operates a short haul route between Curaçao and the city of Bogota

in Colombia using the Airbus A318, A319, A320 and A321 family of aircraft. In 2014 it was

the 5th most emitter of CO2 emissions, emitting 2,283 tonnes. In 2015 it was also the 5th most

emitter of CO2 emissions, with its emissions rising to 2,401 tonnes.

Avior

Avior Airlines operates a short haul route between Curaçao and the cities of

Maracaibo and Maiquetia respectively in Venuzuela using the Boeing 737-200. In 2014, it

was the 9th most emitter of CO2 emissions, emitting 809 tonnes. In 2015 it raised to the 6th

most emitter of CO2 emissions, with its emissions more than doubling to 1,924 tonnes.

Copa Airlines

Copa Airlines operates a short haul route between Curaçao and Panama City in

Panama using both the Embraer E190 and Boeing 737-700 aircraft. In 2014 it was the 8th

most emitter of CO2 emissions, emitting 1,205 tonnes of CO2. In 2015, it fell to the 9th most

emitter of CO2 emissions although emissions increased slightly to 1,281.


InselAir

InselAir is the national carrier of Curaçao and uses Hato International as its hub for

operations. It operates flights between Curaçao and the countries of:

• United States

! Charlotte

! Miami

• Dominican Republic

! La Romana

! Santo Domingo

• Jamaica

! Kingston

• Cuba

! Havana

• Colombia

! Barranquilla

! Medellin

• Venezuela

! Barquisimeto

! Caracas

! Las Piedras

! Maracaibo

! Valencia

• Suriname

! Paramaribo

• Guyana

! Georgetown

• Aruba

• Bonaire

• Sint Maarten

• Trinidad and Tobago

! Port of Spain


Their fleet is comprised of the Fokker F50 and F70, McDonald Douglas MD-82 and

MD-83 aircraft. Its emissions are consistently the highest in both years, emitting 28,179

tonnes of CO2 in 2014 and 33,606 tonnes of CO2 in 2015.

JetBlue

JetBlue operates a short haul route between Curaçao and the city of New York in the

United States using the Airbus A320 aircraft. In 2014 it was the 13th most emitter of CO2

emissions, emitting 99 tonnes of CO2. In 2015, it climbed to the 11th most emitter of CO2

emissions, emitting 1,131 tonnes of CO2.

KLM

KLM operates a long haul route between Curaçao and the city of Amsterdam in the

Netherlands using the Boeing 747-400 and the Airbus A330-200. In 2014 and 2015, it was

the 2nd most emitter of CO2 emissions, emitting 13,043 tonnes of CO2 of 2014 and 15,605

tonnes of CO2 in 2015.

PAWA

Pawa Dominicana started short haul operations in 2015 between Curaçao and the city

of Santo Domingo in the Dominican Republic. It is the 12th most emitter of CO2 emissions

for the year 2015 with 971 tonnes of CO2 being emitted.

Rutaca

Rutaca operates a short haul route between Curaçao and the city of Caracas in

Venezuela using the Boeing 737-200. In both 2014 and 2015, it was the 10th most emitter of

CO2 emissions, emitting 343 tonnes of CO2 in 2014 with an increase to 1,173 tonnes of CO2

in 2015.


Sunwing Airlines

Sunwing Airlines operates a medium haul route between Curaçao and the city of

Toronto in Canada using the Boeing 737-800. It only conducted flights in 2015, generating

226 tonnes of CO2 in the process and becoming the 14th most emitter of CO2 for that year.

Suriname Airways

Suriname Airways operates a short haul route between Curaçao and the city of Port-

of-Spain in Trinidad and Tobago using the Boeing 737-300. For 2014 it was the 6th most

emitter of CO2 emissions, emitting 1,496 tonnes of CO2. For 2015 it fell as the 7th most

emitter of CO2 emissions, however its emissions rose to 1,769 tonnes of CO2.

TUI

TUI operates a long haul route between Curaçao and the city of Amsterdam in the

Netherlands using both the Boeing 787-800 and 767-300. In both 2014 and 2015, it was the

4th most emitter of CO2 emissions. The airline emitted 5,865 tonnes of CO2 and 6,303 tonnes

of CO2 in 2014 and 2015 respectively.

Westjet

WestJet operates a medium haul route between Curaçao and the city of Toronto in

Canada using the Boeing 737-700. It was the 12th most emitter of CO2 emissions in 2014,

generating 206 tonnes of CO2 that year. In 2015, it dropped to the 15th most emitter of CO2

emissions, emitting only 31 tonnes of CO2 that year.

Airport CO2 Emissions The electrical usage data for the year 2015 was incomplete. To provide an estimate

for the year 2015, the rise in electrical usage in the months January, February and March

were compared between the two years. I then averaged the rise in KWh and applied it to the

remaining months from 2014. For the year 2014, the airport consumed 7,856,812 KWh of

electricity while in 2015; electrical consumption was 8,400,000 KWh of electricity. The CO2

EF for the country of Curaçao is .7071 kg/KWh, taken from ACERT. The off-site CO2


emissions that have been generated by the airport for the years 2014 and 2015 are 5,556

tonnes and 5,940 tonnes respectively.

Summary In the year 2014, total CO2 emissions from aviation related activities for airlines

serving Curaçao and Hato International Airport were calculated to 69,412 tonnes. This figure

increased to 83,773 tonnes of CO2 for the year 2015. CO2 emissions have thus increased by

20.7% between these two years. This rise is in relation to the fact that passenger and aircraft

movements have increased from 2014 to 2015. Thus aircraft emissions, GSE emissions and

airport emissions would rise as well.


Chapter 5: Applicable Carbon Dioxide Reduction Measures

Introduction In this chapter, energy saving measures that can be put into effect to lower Curaçao’s

aviation carbon footprint will be outlined. I described 6 methods or equipment that can be

used to lower the CF while quantifying the reduction for four of these methods. These are:

1. Alternative Airport Energy Sources

2. Alternative Aviation Fuels

3. Ground Support Equipment

4. Point of Use Gate Terminals

5. Super 98 Drag Reduction Kit

6. Vectors into Final

Alternative Airport Energy Sources Renewable Energy has been a focus in other industries recently as they strive for

ways to reduce their Carbon Footprint. The installation cost of the equipment has fallen since

their inception, making renewable energy a more attractive proposition for airports that are

looking not only to reduce their carbon footprints but to reduce their operating costs as well.

From wind farms harnessing wind energy, solar panels that convert light into electricity and

even wave generators that harness the kinetic energy from waves and tides, there is no

shortage of means for airports to harness the natural energy that is in their surrounding

environments. This would lead to lower consumption bills and also helps airports towards a

zero-emission state, where these renewable energy sources are sufficient to power the entire

airport throughout its day-to-day operations.

Many airports have adopted renewable energy generation means to lower their costs

of operation as well as to lower their emissions. La Palma Airport (ICAO: GCLA) operates

two 660 KW wind turbines on the Airports property. In 2011, these turbines produced 27% of

the airport’s electricity needs (La Palma Airport, 2009, p. 16). Conchin International Airport

(ICAO: VOCI) operates a 12 MW solar plant that produces 100% of the airport’s electrical

needs and surplus energy that is sold to the state’s grid (Font, 2015). Even Hato

International’s sister airport, Beatrix International Airport (ICAO: TNCA), has committed to


green energy and has installed a 3.6 MW solar park above its landside parking lot

(Government of Aruba, 2015).

Currently, the renewable energy tariffs in Curaçao limits residential and commercial

generation systems to a 1-megawatt (MW) capacity. Under this rule, it is not possible for

Hato International Airport to generate enough power to cover their electrical energy

requirements, no matter the source of the renewable energy. For the purpose of this research

and in regards to a zero emission airport, the calculations for the required MW generation

needed to fully supply Hato International shall be carried out. The final calculation shall be

carried out with both the 1 MW restriction and non-restrictions.

Solar Energy

In 2015, Hato International Airport consumed approximately 8,400,000 KWh of

electricity. Per year, Curaçao experiences an average 3,199 hours of sunlight with 27% of

those sunlight hours in cloudy or hazy conditions or low sun intensity (Climatemps, 2014). In

cloudy conditions, solar panels can drop to an average of 17.5% of their rated output capacity

(Llorens, 2014). Using this information, it is calculated that a 1 MW solar plant installed at

Hato International would potentially generate 2,486,423 KWh per year, lowering airport

emissions to 4,181 tonnes from the previous 5,940 tonnes of CO2. This is an improvement of

30% in airport CO2 emissions.

However, to achieve a zero emission airport, the solar array would need to provide

enough electricity to cover the yearly energy consumption of the airport. To achieve this

under the existing conditions, the solar array would need to be able to generate at least 3.4

MW of electricity to fully power Hato International, which is over 3 times the current limit

that is imposed. This energy requirement would be similar to the solar panel array that is

installed at Aruba’s Beatrix Airport, which is rated at 3.6 MW.

Wind Energy

The island of Curaçao has a deep history in harnessing the energy from the wind, with

the first wind farm, a 3 MW plant at Terra Kora, gaining huge success when it came online in

1993. This plant and another wind farm that was built at Playa Kanoa in 2000 were two of the

oldest but most productive wind farms in the Caribbean (National Renewable Energy


Labratory, 2015, p. 3). The consistently high average wind speeds that Curaçao experiences

make the island highly attractive to wind energy developments. NuCapital, a renewable

project developer, purchased both the Tera Kora and Playa Kanoa sites and replaced the

existing generators with five 3 MW Vesta turbines at each site, bringing total wind generation

capacity to 30 MW. A second installation is planned in Tera Kora to raise capacity by an

additional 16.5 MW.

Curaçao has great potential for harnessing wind energy and the airport itself can also

take advantage of it. Airport obstacle height requirements have to be taken into consideration

but limiting the size of the wind turbines as well as placing them offshore can mitigate these

issues. Indeed, La Palma International Airport is an example of an airport that has overcome

such issues with the installation of their wind turbines. As Hato International is located on the

coast of Curaçao, the turbines can be placed and distanced offshore from the airport. Vesta

also incorporates design features such as aviation lights to increase visibility of the turbines.

Such features are already installed on the existing turbines in Playa Kanoa and Tera Kora.

As Curaçao has an average wind of 7 meters per second annually (Wind Finder), 2

Vesta V90-1.8 at a combined power output of 3.6 MW would provide approximately 12,000

MWh per year (Vestas). This is approximately 1 ½ times the energy usage of Hato

International. Surplus energy could then be fed into the grid, providing revenue to the airport.

This surplus will also provide Hato International with room to grow their airport with the

assurance that the existing wind generators will supplant the subsequent growth in electrical

needs. As of writing, The Vesta V90-1.8 is also the smallest wind turbine in Vesta’s

portfolio, in both turbine height and blade area, making it the candidate with the highest

potential of implementation.

Wave Energy

In comparison to solar and wind energy generation, wave energy generation is still in

its inception phase. However, it is accepted that the kinetic energy the seas and oceans

possesses are much greater than both wind and solar energy generation, although harder to

access. “Solar photovoltaics (electric solar panels) typically generate power on the order of a

hundred watts per square meter and wind one thousand watts per square meter of swept area,

but wave energy is typically in the range of several tens of thousands of watts per meter of

wave front. This allows wave energy plants to produce comparable power to wind and solar


energy plants while having smaller footprints” (Colombia Power Technologies). As of

writing, there are not many wave generators that are in service, with wave generation being in

its experimental phases. As such, an actual calculation of the benefit to Hato International

Airport is not possible as there are no precise energy generation figures. It is however, safe to

say that wave energy generation has more power per area than both wind and solar energy

generation. Wave energy generation plants could then have a smaller volume footprint than

both a solar and wind energy plant yet still generate a similar power output as both.

Alternative Aviation Fuels

With a finite supply of fossil fuels and the rising concern of CO2 emissions,

alternative aviation fuels are being developed to solve the issue. The alternative fuels are

being designed as a drop-in replacement to fossil fuel derived jet fuel, requiring no

modification to the existing equipment. These fuels also have a reduction in CO2 emissions

per kilogram of jet fuel.

Alternative aviation fuels are still in its experimental phases for commercial jet

aircraft; however there have been numerous test runs that have been highly successful. Air

Canada Flight 991, as part of the ICAO’s Flightpath to a Sustainable Future, realized a 40%

saving in CO2 emissions when using Jet fuel derived from recycled cooking oil as well as

other fuel saving measures (Air Canada, 2012). Alternative aviation fuels can also be made

from waste biomass and from oils such as Camelina and Janthropa. However, no definite

emissions calculations can be made within the scope of this thesis. However, it is positive

that alternative aviation fuels will be engineered to have lower CO2 emissions per kilogram

of jet fuel compared to their fossil fuel derived counterparts.

Ground Support Equipment

During research of the airport equipment, it was found that the age of the ground

support equipment ranged as far back as the 1980’s. This meant that many of the diesel

engines equipped on the GSEs lacked the modern technology such as catalytic converters,

variable valve timing and turbochargers, all of which aims to improve the economy and lower

emissions of the engine.


Electric GSE has been slowly replacing internal combustion engine (ICE) GSEs at

airports around the world. The main advantage of electric GSEs is that they emit no

emissions directly. Emissions attributed to electric GSEs are off-airport emissions, however

these would be lower than the emissions that comparable ICE GSEs emit. These units are not

without their drawbacks. The high initial cost and current battery technology are limiting the

widespread implementation of a fully electric GSE fleet.

If the GSE fleet at Hato International were an all-electric fleet, it would eliminate the

emissions attributed to the ICE GSEs. In 2015, the current fleet of GSE was calculated to

have emitted approximately 237 tonnes of CO2, which is 0.30% of the emissions emitted in

airline operations. Switching to electric GSE would lower the CO2 emissions close to this

amount. Also, if the airport were to become 100% sustained by renewable energy, then the

true emissions of the electric GSE would be neutralized, along with emissions from the rest

of the airport.

Point of Use Gate Terminals

Point of use (POU) gate terminals is usually comprised of pre-conditioned air (PCA)

and electrical inverter units that are used by parked aircraft at the gates during their

turnaround. These units are usually attached to the underside of the passenger boarding

bridge, providing close proximity to the aircraft it will be servicing. They supply pre-

conditioned air and/or electrical energy that would otherwise be supplied by portable ground

power units and air-conditioning carts or the aircraft’s APU. The key difference in the POU

terminals and the other units are that the POU terminals use the airport’s existing electrical

supply to power its systems, emitting no emissions from the unit itself. Currently at Hato

International, most aircraft use APU power to supply cabin air conditioning and electrical

power during its turnaround. Though APU power is readily available to the aircraft, it is an

inefficient source of power compared to both GPU’s, air conditioning carts and POU’s.

Through preliminary calculations, POU terminals were found to emit an average 81% less

CO2 than APUs during regular operation. These calculations were performed on all

commercial aircraft fleet that uses the passenger boarding bridges in the scope of this thesis

using data from ACRP report 64. If all commercial aircraft flights that had used the passenger

boarding bridges in 2015 had used POU’s for aircraft air conditioning and electrical power,

the airline CO2 emissions for the year would have been 76,114 tonnes compared to the actual


emissions of 77,834 tonnes. This is a reduction in CO2 emissions of just over 2%. If the POU

terminals used 100% renewable energy, then the CO2 emissions for the year would then be

75,706 tonnes, a reduction in emissions of nearly 3%.

Super 98

InselAir, the national carrier of Curaçao, has a fleet of 18 aircraft, 7 of which are

McDonald Douglas MD-80 series aircraft (InselAir Airlines). PAWA also uses the MD-80

series aircraft to serve Curaçao. There is a Federal Aviation Administration (FAA) certified

airframe modification company called Super 98 that offers a drag reduction package that

would decrease fuel burn by more than 3.5%. This drag reduction package can be installed

with minimal downtime to the aircraft and decrease emissions for both MD-82 and MD-83

aircraft (Super 98).

Vectors Into Final Airlines traditionally navigate their way to the Initial approach fix of Hato

International Airport via the Standard Arrival Route (STAR). This is so to facilitate the air

traffic controller and pilots’ job of safely navigating the aircraft to the airport. However it

may encompass additional fuel burn compared to the vector into final approach. For this

approach, the air traffic controller gives heading vectors to the pilots and vectors them into

position for either the downwind, base or final leg pattern of the airport. This may save fuel

as the airline may bypass the STAR that may cover additional nautical miles to the airport. It

does, however, increase the workload of the pilot and the air traffic controller.

During my data gathering, it was noted that KLM, when operating its midday arrival

flight using the Boeing 747-400, repeatedly uses vectors into final. TUI would also use

vectors into final if operating a non-stop route from Amsterdam to Curaçao. Air Berlin, the

other long-haul carrier that serves Curaçao would repeatedly use identical STAR approaches

when arriving into Curaçao. In the case of Air Berlin using the twin engine A330 on the

STAR approach, they spend 7 minutes in the approach phase from 3,000 feet to the runway,

burning 1,455 kilograms of fuel in the process. KLM, using the quadruple engine Boieng

747-400 and the vector into final procedure, would spend 4 minutes in the approach phase

from 3,000 feet to the runway, burning 1,079 kilograms of fuel. TUI, using the 787-800


would also spend 4 minutes in the approach phase from 3,000 feet to the runway. All airlines

enter the Curaçao FIR at the same waypoint, thus needing to cover the same distance to arrive

at Curaçao.

Only a few airlines may significantly benefit from the vector into final procedure,

largely airlines that have Curaçao FIR entry origins that do not closely align with focus

runway of Hato International, runway 11. The table below shows the airlines that strictly

adhere to the STARs and could greatly benefit from a vectored in approach in terms of

emissions reduced for the year 2015.

Airlines that strictly use

STARs

Benefit to vectored

approaches 2015

Air Berlin Reduction in CO2 of 108

tonnes

Avianca Reduction in CO2 of 78

tonnes

A total of 186 tonnes of CO2 could be saved by these airlines using vectored in

approaches, reducing airline emissions by 0.25%

Summary The carbon dioxide emissions can be reduced by the methods detailed above.

However, the effect of the reduction is largely dependent on the waiving or increase of the

renewable energy power-plant generation limit that is currently imposed 1 MW. Under the

current regulations, the reduction measures can reduce carbon dioxide emissions by 3,901

tonnes, a decrease in carbon dioxide emissions of 4.67%. The reduction measures detailing

the electric GSE and POU terminals both do not produce emissions directly. They do

however produce off-airport emissions due to the airports own reliance on grid electricity. If

the airport is a 100% zero emission airport, meaning that the airports renewable energy

sources produce as much energy as the airport consumes, then the electric GSE and POU

terminals will also produce zero emissions. This would result in a reduction of CO2 emissions

by 8,261 tonnes, decreasing carbon dioxide emissions by 9.86%


Chapter 6: Conclusion

Summary of Results The goal of my research was to answer two questions.

1. What is the CF of Curaçao ’s aviation sector?

2. What measures can be put in place to reduce the CF of Curaçao ’s aviation sector and

by how much?

What is the CF of Curaçao ’s aviation sector? In this thesis, the aviation sector in Curaçao

is defined to be emissions from commercial airline flights to and from Curaçao, GSE serving

these airlines and the airport. The total emission for the year 2014 was calculated to be

69,412 tonnes of CO2. This was comprised of Airline and GSE CO2 emissions totaling

63,857 tonnes (92%) and airport emissions totaling 5,556 tonnes (8%). In 2015, the CO2

emissions rose by 21.5% to 83,773 tonnes in response to increased passenger traffic and

airline movements. This was comprised of Airline and GSE CO2 emissions totaling 77,834

tonnes (93%) and airport CO2 emissions totaling 5,940 tonnes (7%).

The greatest contributor to the airline CF is InselAir, emitting 28,179 tonnes of CO2 in the

year 2014 and 33,606 tonnes of CO2 in the year 2015. As InselAir is the national flag carrier

of Curaçao, it also has the most flights daily, which is mostly what contributes to its high CF.

The second greatest contributor to the airline CF is KLM, emitting 13,043 tonnes of CO2 in

the year 2014 and 15,605 tonnes of CO2 in the year 2015.

What measures can be put in place to reduce the CF of Curaçao’s aviation sector and by

how much? The effectiveness of the measures described is mostly limited by the current

renewable energy generation limit. If the regulation is abolished or at least raised to a level

where Hato International Airport can be 100% self sufficient on renewable energy, then the

effectiveness of the measures could be raised significantly. If the feed-in tariff stays in effect

and all the recommended reduction measures are implemented, then Curaçao would save

3,801 tonnes of CO2 in aviation related emissions. This is a reduction of 4.67%, enabling

Curaçao to reduce its aviation carbon emissions by 2% for the first two years under the

current renewable energy regulations.


If the feed in tarrif was at least lifted to the recommended amount of 3.4 MW for solar

energy or 3.6 MW for wind energy, Hato International Airport would then be able to become

self sufficient on renewable energy. This would then save 8,261 tonnes of CO2 in aviation

related emissions. This is a reduction of 9.86%, providing room for Hato International to

grow in operations whilst keeping with the mandate of reduced emissions. With a reduction

of 2% every year for the next 4 years now possible, the hypothesis of the reduction of carbon

emissions by 2% per year towards 2020 is proven.

Recommendations Resulting from Research

Based on an analysis of chapter 4 and chapter 5, I have comprised 6

recommendations. They are ordered from highest to lowest by my perception of their

importance towards the reduction of Curaçao ’s aviation CF.

Recommendation 1: The installation of POU terminals.

In my research, APU emissions at the gate accounted for 2.73% of airline emissions.

The installation of POU terminals will reduce emissions by 2.21%. With the addition of

100% renewable airport electricity, gate emissions will be eliminated completely, reducing

airline emissions by 2.73%. In comparison to the other methods that I have detailed to be

implemented, POU terminals are fairly simple to install to the passenger boarding bridges’

existing architecture and depending on the equipment installed, can supply power to a wide

array of aircraft types.

Recommendation 2: The abolishment or raise in the limit regulation of the

feed-in tariff system.

Hato International Airport cannot become energy self-sustaining under the current 1

MW power generation limit. In my research, it was found that it would need more than 3

times that limited capacity in both wind and/or solar generation in order to generate enough

energy to supply the airport with 100% of its energy needs. The reduction in emissions will

also be amplified when coupled with POU terminals and electric ground support equipment,

rising from a 4.67% reduction in total emissions to a 9.86% reduction in total emissions.


Recommendation 3: The installation of wind turbines.

In reference to my research and considering Curaçao’s environmental conditions,

wind turbines are more advantageous than solar panels for the following reasons:

1. Two Vesta ‘V90-1.8’ totaling 3.6 MW would produce 1 ½ times the energy than a 3.4

MW solar energy plant. This is due to the constant average wind on Curaçao and that

the wind turbines would also produce power in the night as well, compared to the

solar turbines only producing power during the day. This would lessen the reliance on

the country’s grid electricity as a power bank and also provide room for growth

without the need to update or add more wind turbines for additional power.

2. The wind turbines would be located off-airport and would occupy less area than a

solar energy plant of similar capacity.

Recommendation 4: The upgrade of ground support equipment.

The current fleet of GSE has equipment that dates as far back as the 1980’s. Although

GSE emissions make up 0.30% of airline emissions, further increase in airline movements

will also result in an increase of GSE emissions. Updating the equipment with retrofits such

as turbochargers, catalytic converters and variable valve timing is the least expensive way of

reducing emissions. Conversely, ground support emissions could be reduced completely by

having electric GSE combined with a 100% electricity generation renewable energy power

plant.

Recommendation 5: Increased Vectors into Final Approaches.

Where possible, vectors into final can shave minutes from the approach phase, saving

hundreds of kilograms of fuel. This practice should be encouraged with safety as this

procedure places additional workload on the pilots and air traffic controllers.


Recommendation 6: MD-80 Drag Reduction Packages Installation.

Both PAWA and InselAir can benefit greatly from the installation of drag reduction

kits on their aircraft. This kit will not only provide a reduction in emissions but also a

reduction in operating costs for the airlines.

Contributions of Research My research contributes to existing knowledge on both a practical and theoretical

level. On a practical level, I have provided the first detailed snapshot of airline and airport

generated emissions for Curaçao in terms of emission quantities for the years 2014 and 2015.

I have also provided practical measures that can be implemented to lower Curaçao’s CF. This

provides a baseline and guidance for future study and efforts to further reduce aviation GHG

in Curaçao.

At a theoretical level, I have developed a methodology for calculating an aviation CF

portrait. While my research was focused on Curaçao, the methodology can be used as a

template when conducting research in other jurisdictions and other geographical states.

Limitations of Research

The CF calculations in chapter 4 are subject to a number of limitations. First, the

ICAO EEDB engine values were not corrected for variations in temperature and pressure.

Secondly, there were also limitations in my research. The BN-2 Islander operated by

commuter airline DIVI DIVI is not included in this research as the Lycoming TIO-540 also is

not documented in the EEDB. The IFSET generalized specific airframes to fleet type and

then rounded fuel burn estimates to the nearest 100 kg. Finally, the documentation of Hato

International Airport’s electrical usage for 2015 was not complete as of writing. Therefore,

the 2015 energy consumption data had to be modeled from the existing delta between the

months documented in 2015 and the corresponding months in 2014.

Suggestions for further research This research could be used as a template to further expand on emission calculations.

The emission data for the PW125 and PW127 equipped Fokker 50’s and Lycoming TIO-540


equipped Britten-Norman Islanders could be researched and the emissions for these aircraft

calculated. I would also incorporate the Boeing Fuel Flow Method 2 (BFFM2) into my LTO

calculations to account for the variance in temperature and pressure.

The final step for this research is to expand the emissions to the entirety of the

Curaçao FIR. This would include traffic from neighboring islands Aruba and Bonaire as well

as the traffic passing through the FIR. This would entail greatly expanded data gathering, but

the template I have provided allows for expansion of the geographic scale. Applying this

template to a global scale is possible, but would be extremely labor-intensive, time

consuming and costly.

Final Thoughts

Conducting this research illustrated very clearly the complexity of quantifying CO2

emissions for a state and adopting measures to reduce CO2 emissions. Aviation is an integral

part of everyday life in the 21st century and a vital part of the Curaçao n economy; it is also

controlled and influenced by a multitude of stakeholders. While there can be no debate that

the CF of aviation is an environmental problem that needs to be addressed, doing so requires

not only significant cooperation between the affected stakeholders but also more research,

both in the natural and social sciences, on how aviation affects the environment and how its

impact can be reduced.

With my research, I hope to have contributed to the knowledge and insight of

Curaçao’s aviation emissions and in doing so, translate this knowledge into positive action

and create change for the better. The technological developments in doing so are already

developed, with advancements occurring rapidly. The recommendations derived from my

analysis are designed to spur more action to reduce the carbon footprint of aviation.


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APPENDIX 1: LTO FUEL BURN CALCULATION DATA


APPENDIX 2: AIRLINE AND GSE CO2 EMISSIONS

Abbreviations

• CYUL / YUL: Pierre Elliot Trudeau International Airport, Montreal, Quebec, Canada

• CYYZ / YYZ: Lester B. Pearson International, Toronto, Ontario, Canada

• EDDL / DUS: Düsseldorf International Airport, Düsseldorf, North Rhine-Westphalia,

Germany

• EHAM / AMS: Amsterdam Schiphol Airport, Amsterdam, Netherlands

• KCLT / CLT: Charlotte Douglas International Airport, Charlotte, North Carolina,

United States

• KJFK / JFK: John F. Kennedy International Airport, Queens, New York, United

States

• KMIA / MIA: Miami International Airport, Miami, Florida, United States

• MDLR / LRM: La Romana International Airport, La Romana, Dominican Republic

• MDSD / SDQ: Las Americas International Airport, Santo Domingo, Dominican

Republic

• MKJP / KIN: Norman Manley International Airport, Kingston, Jamaica

• MUHA / HAV: José Martí International Airport, Havana, Cuba

• SKBO / BOG: El Dorado International Airport, Bogota, Colombia

• SKBQ / BAQ: Ernesto Cortissoz International Airport, Barranquilla, Atlántico

department, Columbia

• SKRG / MDE: José María Córdova International Airport, Medellin, Antioquia

department, Columbia

• SMJP / PBM: Johan Adolf Pengel International Airport, Paramaribo, Suriname

• SVBM / BRM: Jancinto Lara International Airport, Barquisimeto, Venezuela

• SVJC / LSP: Josefa Camejo International Airport, Paraguana, Venezuela

• SVMC / MAR: La Chinita International Airport, Maracaibo, Venezuela

• SVMI / CCS: Simón Bolívar International Airport, Caracas, Venezuela

• SVVA / VLN: Arturo Michelena International Airport, Valencia, Venezuela

• SYCJ / GEO: Cheddi Jagan International Airport, Georgetown, Guyana

• TNCA / AUA: Queen Beatrix International Airport, Oranjestad, Aruba


• TNCB / BON: Flamingo International Airport, Kralendijk, Bonaire

• TNCC / CUR: Hato International Airport, Willemstad, Curaçao

• TNCM / SXM: Princess Juliana International Airport, Sint Maarten

• TTPP / POS: Piarco International Airport, Port of Spain, Trinidad and Tobago


AIRLINES AIRCRAFT LTO's 2014 Total Fuel Burned per LTO/kg Total Fuel Burned per Year GSEDeparture Arrival ICAO IATA Cruise Descent Climb kg Tonnes

AIR BERLIN EDDL TNCC EDDL-TNCC DUS-CUR A332 51 2891 2000 300 2800 407,526.7 2958 1289520 1290

AIR CANADA CYUL TNCC CYUL-TNCC YUL-CUR A319 0 824 1200 100 1100 0.0 0 0 0CYYZ TNCC CYYZ-TNCC YYZ-CUR A319 22 824 1200 100 1100 70,920.8 396 224293 224

AMERICAN AIRLINES KMIA TNCC KMIA-TNCC MIA-CUR B738 704 861 1800 100 1200 2,788,295.0 12672.00 8815319 8815

AVIANCA SKBO TNCC SKBO-TNCC BOG-CUR A318 125 709 300 100 1100 276,105.5 2250 873915 874SKBO TNCC A319 144 764 300 100 1100 326,086.9 2592 1032048 1032SKBO TNCC A320 50 883 300 100 1100 119,162.8 900 377097 377SKBO TNCC A321 0 1091 300 100 1100 0.0 0 0 0

AVIOR SVMI TNCC SVMI-TNCC CCS-CUR B732 95 1091 0 500 1100 255,680.5 1710 808893 809AVIOR SVMI TNCC F50 0 200 0 200 500 0.0 0 0 0

COPA AIRLINES MPTO TNCC MPTO-TNCC PTY-CUR E190 115 625 600 100 700 232,828.3 2070 737109 737MPTO TNCC B737 49 816 900 100 1200 147,774.9 882 467407 467

DIVI DIVI TNCB TNCC TNCB-TNCC BON-CUR BN2P 1892 0 0 0 0 0.0 0 0 0

INSEL AIR TNCA TNCC TNCA-TNCC AUA-CUR MD83 4 888 800 50 200 7,750.5 72 24540 25TNCA TNCC MD82 548 856 800 50 200 1,044,552.1 9864 3307515 3308TNCA TNCC F70 17 602 700 50 100 24,678.9 306 78217 78TNCA TNCC F50 1380 200 500 50 100 1,173,000.0 24840 3728001 3728SKBQ TNCC SKBQ-TNCC BAQ-CUR MD83 1 888 800 50 200 1,937.6 18 6135 6SKBQ TNCC MD82 4 856 800 50 200 7,624.5 72 24142 24SKBQ TNCC F70 0 602 700 50 100 0.0 0 0 0SKBQ TNCC F50 51 200 500 50 100 43,350.0 918 137774 138TNCB TNCC TNCB-TNCC BON-CUR MD83 102 888 800 50 200 197,638.8 1836 625782 626TNCB TNCC MD82 153 856 800 50 200 291,635.9 2754 923449 923TNCB TNCC F70 14 602 700 50 100 20,323.8 252 64414 64TNCB TNCC F50 1462 200 500 50 100 1,242,700.0 26316 3949520 3950SVBM TNCC SVBM-TNCC BRM-CUR MD83 63 888 0 100 200 74,821.0 1134 237344 237SVBM TNCC MD82 127 856 0 100 200 146,826.9 2286 465818 466SVBM TNCC F70 0 602 0 100 100 0.0 0 0 0SVBM TNCC F50 144 200 0 100 100 57,600.0 2592 184435 184SVMI TNCC SVMI-TNCC CCS-CUR MD83 51 888 0 500 1100 126,869.4 918 401445 401SVMI TNCC MD82 136 856 0 500 1100 334,031.9 2448 1056987 1057SVMI TNCC F70 0 602 0 400 900 0.0 0 0 0SVMI TNCC F50 79 200 0 200 500 71,100.0 1422 225885 226SYJC TNCC SYJC-TNCC GEO-CUR MD83 0 888 0 0 0 0.0 0 0 0SYJC TNCC MD82 0 856 0 0 0 0.0 0 0 0SYJC TNCC F70 0 602 0 0 0 0.0 0 0 0SYJC TNCC F50 0 200 0 0 0 0.0 0 0 0MUHA TNCC MUHA-TNCC HAV-CUR MD83 0 888 0 0 0 0.0 0 0 0MUHA TNCC MD82 0 856 0 0 0 0.0 0 0 0MUHA TNCC F70 0 602 0 0 0 0.0 0 0 0MUHA TNCC F50 0 200 0 0 0 0.0 0 0 0MKJP TNCC MKJP-TNCC KIN-CUR MD83 57 888 1700 100 1000 210,195.2 1026 664612 665MKJP TNCC MD82 1 856 1700 100 1000 3,656.1 18 11560 12MKJP TNCC F70 0 602 0 0 0 0.0 0 0 0MKJP TNCC F50 40 200 1000 100 600 76,000.0 720 240652 241SVJC TNCC SVJC-TNCC LSP-CUR MD83 0 888 0 100 200 0.0 0 0 0SVJC TNCC MD82 0 856 0 100 200 0.0 0 0 0SVJC TNCC F70 0 602 0 100 100 0.0 0 0 0SVJC TNCC F50 184 200 0 50 100 64,400.0 3312 206623 207SVMC TNCC SVMC-TNCC MAR-CUR MD83 2 888 0 500 1100 4,975.3 36 15743 16SVMC TNCC MD82 143 856 0 500 1100 351,224.7 2574 1111390 1111

ICAO CODE Total CO2 EmissionsAir Fuel Burn/kgCITY PAIREmissions 2014


Emissions 2015

curacao aviation environmental thesis

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