Drivers of CO2 emissions in international aviation: the case of Japan (2024)

The 2014 Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) stated that greenhouse gas (GHG) emissions generated by the international aviation industry accounted for approximately 6.52% of transport sector emissions, and that annual CO₂ emissions from aviation are rapidly increasing at a rate of 3% to 4% a year (IPCC 2014). Japan's transportation sector emitted 200 million tons of CO₂ in 2015, accounting for 20% of the nation's total CO₂ emissions (MLIT 2016b). Although CO₂ emissions from air transportation constitute a mere 5% of Japan's overall transport emissions, these values include only the CO₂ emissions associated with domestic flights, and thus exclude international flights (MLIT 2016b). Therefore, the CO₂ emissions from aviation reported by the Japanese government did not consider the CO₂ emissions associated with international flights. We must estimate the CO₂ emissions generated by both domestic and international flights when evaluating the CO₂ emissions associated with the airline industry.

The International Civil Aviation Organization (ICAO) introduced a global market-based measures (GMBM) program, the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA), to complement the global carbon reduction target (ICAO 2016b). During the first phase, from 2021 to 2026, airlines must reduce CO₂ emissions relative to the average baseline emissions for 2019 and 2020. Those exceeding the upper limit must buy an allowance (ICAO 2016b). During the second phase, from 2027 to 2035, all ICAO member states, except for developing countries and countries with low CO₂ emission levels, must also participate in this scheme (ICAO 2016b). Japan has been a participant since the first phase of its execution (ICAO 2016c). The scheme's upper limit for CO₂ emissions generated by international flights is designed to reduce CO₂ emissions and ensure that airlines operate in an environmentally friendly manner.

From the demand perspective, the World Tourism Organization (UNWTO) estimated that the tourism industry contributed 7% to global gross domestic product (GDP) in 2018, and that global tourism would continue to grow at an annual rate of 3% to 5% (UNWTO 2016). Studies have analyzed the environmental burdens associated with increasing tourism demands (Peeters and Dubois 2010, Gössling and Peeters 2015, Lenzen et al 2018). (Lenzen et al 2018) estimated the carbon footprint of global tourism and revealed that global demand was responsible for 8% of all greenhouse gas (GHG) emissions in 2013. The aviation industry was identified as one of the main contributors to the carbon footprint produced by tourism demand (Lenzen et al 2018).

Studies (Peeters and Dubois 2010, Gössling and Peeters 2015, Lenzen et al 2018) have confined themselves to addressing the important question of how airline companies can mitigate CO₂ emissions while maintaining current flight schedules and aircraft. (Schefczyk 1993) and Barros and Peypoch (2009) analyzed airlines' operational performance using data envelopment analysis (Farrell 1957, Charnes et al 1978). (Arjomandi and Seufert 2014) and (Liu et al 2017) analyzed airline performance using an environmental DEA approach and characterized CO₂ emissions as undesirable. (Liu et al 2017) analyzed the performance of 12 Chinese airlines from 2007 to 2013, finding that CO₂ emissions decreased by approximately 12% due to technological innovation.

Studies have also estimated CO₂ emissions generated by the passenger and freight transport sectors (Scholl et al 1996, Schipper et al 1997, Kveiborg and Fosgerau 2007, Eom et al 2012, Loo and Li 2012, Cristea et al 2013) and have examined the factors affecting CO₂ emission changes associated with these sectors (Lakshmanan and Han 1997, Mazzarino 2000, Kwon 2005, Lu et al 2007, Timilsina and Shrestha 2009, Papagiannaki and Diakoulaki 2009, Wang et al 2016, Andreoni and Galmarini 2012, Achour and Belloumi 2016, Fan and Lei 2016). (Andreoni and Galmarini 2012) identified the drivers of change in CO₂ emissions associated with aviation activities for both passenger and freight transportation in 27 European countries from 2001 to 2008, and found that the expansion of the aviation sector's market scale was the most important factor in the increase in CO₂ emissions (Andreoni and Galmarini 2012).

Andreoni and Galmarini (2012, p 596) stated about their study that, 'unfortunately, since Eurostat data are not disaggregated by the passenger and freight transports, the decomposition analysis presented in this paper cannot disaggregate between travelers and goods.' However, estimating CO₂ emissions—disaggregated between travelers and goods, according to origin—is the most important aspect of the methods intended to reduce CO₂ emissions produced by the aviation sector. The number of travelers is increasing. An upper limit on CO₂ emissions associated with international flights will be set in 2021. Thus, the aviation sector—particularly the airline industry—must participate in reduction activities targeted at international aviation.

Many studies have examined CO₂ emissions produced by the aviation sector and the operations of individual airlines. To the best of our knowledge, however, only a few studies (Miyoshi and Mason 2009, Baumeister 2017, Lee et al 2017) have estimated the CO₂ emissions generated by individual airlines or considered the effects of operational factors, such as the number of flights as a scale effect, or the number of passengers per flight as an efficiency effect.

This study focuses on Japan's two major airlines, Japan Airlines (JAL) and All Nippon Airways (ANA). First, we created a detailed database comprising direct flights in Japan's international passenger transport sector (departures and arrivals) in terms of the numbers of flights and aircraft in 2005, 2010, and 2015 at the company level. We estimated the amounts of direct and indirect CO₂ emissions associated with more than 40 thousand international flights in Japan. Second, we developed a new decomposition analysis framework to analyze the supply-and-demand factors for the CO₂ emissions associated with aviation. Finally, we discuss the major driving forces of increasing CO₂ emissions due to the aviation sector, and some methods of reducing them.

The remainder of this paper is organized as follows. Section 2 explains the study's methodology. Section 3 presents the study's data. Section 4 discusses the results, section 5 compares our results with existing studies, and section 6 summarizes our conclusions.

This study estimates the CO₂ emissions associated with international flights between Japan and other countries, and analyzes the factors driving changes in them using an index decomposition method (Ang and Choi 1997, Ang et al 1998, 2003, Ang and Zhang 2000, Ang and Liu 2007). Index decomposition analysis has been widely used in environmental studies to discuss energy issues (Nag and Parikh 2000, Shrestha et al 2009, Malla 2009), greenhouse gas emissions (Torvanger 1991, Lise 2006, Bhattacharyya and Matsumura 2010, Hammond and Norman 2012), and toxicity (Shrestha and Timilsina 1998, Fujii et al 2017). (Fujii et al 2017) identified the main drivers of changes in toxicity emissions in US industrial sectors from demand and supply sides using an input–output structural decomposition method (Hoekstra and van den Bergh 2003, Nagashima 2018, Han et al 2019). This study develops a new decomposition analysis framework that considers both demand and supply factors in aviation emissions, following (Fujii et al 2017).

The amount of direct CO₂ emissions in year associated with jet fuel combustion owing to international flights to a specific region operated by airline company is calculated as

where is either JAL or ANA, and indicates a region in which the company is operating (1 = North America; 2 = Europe; 3 = Asia and Oceania). Moreover, is CO₂ emission intensity (t-CO₂/L) at the region level, which indicates the CO₂ emissions per unit of aviation fuel consumption associated with international flights to region . represents fuel efficiency (L/km), the amount of aviation fuel consumption () per flight distance for region (). We use the 'catalog-based' fuel efficiency (L/km) of aircraft models that fly between international airports in Japan and those the specific region, and estimate the annual total jet fuel combustion (L) for each air route by multiplying the catalog-based fuel efficiency by the cumulated round-trip flight distance for the air route over one year. The annual total aviation fuel combustion for each region is estimated by summing up the jet fuel combustion over all air routes between international airports in Japan and those in the region. Finally, we define region-specific average fuel efficiency by dividing the annual total aviation fuel combustion for region by the annual total of all cumulated round-trip flight distances for the air routes between international airports in Japan and those in the region. If the airline company introduces greener aircraft with better fuel efficiency (i.e. a lower value of ) for air routes to the region, then the aviation fuel combustion for the region will decrease.

Equation (1) also includes , where represents the number of passengers on international air routes to region in year , and represents the distance per passenger. For driving force , we consider the physical flight service to passengers provided by the airline company. We further define , where represents the total number of flights on international air routes for region operated by airline company in year . Accordingly, indicates the number of passengers per flight on air routes in region . Airline companies try to increase passenger efficiency calculated by .

Thus, the total CO₂ emissions for airline company can be estimated by using the following five factors: emission intensity (EI), fuel efficiency (FE), total number of flights (TN), distance per passenger (DP), and passenger per flight (PF). The three factors of EI, FE, and TN, can be interpreted as supply factors in the sense that airline companies can determine them via the operation of their business. Conversely, the two factors of DP and PF can be interpreted as demand factors in the sense that consumers can determine them based on their preferences.

Equation (2) represents direct CO₂ emissions from fuel combustion by company in year . As the emission intensity for jet fuel combustion is fixed over time, the decomposition analysis framework for the change in aviation emissions between years 0 and t can be formulated by using the logarithmic mean Divisia index (LMDI) method (see Ang et al 1998) as follows:

where . Here, if is equivalent to . The four terms on the right-hand side of equation (3) represent the influences of the four drivers affecting the change in aviation CO₂ emissions among the airline company.

Equation (2) does not include CO₂ emissions associated with the refinement of jet fuel. We estimate refinery emissions as follows:

where is the CO₂ emissions intensity for the refinement of one liter of jet fuel. Summing the refined emissions of the aviation jet fuel for region yields the refined emissions of airline company s.

One important consideration is that introducing new aircraft models with higher fuel efficiency helps reduce CO₂ emissions in flight, and helps increase the CO₂ emissions associated with the manufacturing of new aircraft purchased by the airline company. This study estimates the manufacturing emissions of airline company s in year t as follows:

where is the CO₂ emission intensity corresponding to the production of aircraft models at a purchaser's price of one million dollars, and is the purchase price of aircraft model k produced by aircraft manufacturer j. Summing the CO₂ emissions of aircraft models k produced by Airbus (j = 1) and Boeing (j = 2) yields the manufacturing emissions of airline company s.

We collected the following data on the international flights and aircraft models for JAL and ANA for 2005, 2010, and 2015:

• (1)

  Number of international flights per week (JTB Corporation 2005, 2010, MLIT 2015)

• (2)

  Aircraft models used in the international flights (JTB Corporation 2005, 2010, MLIT 2015a)

• (3)

  Round-trip distance between each departure and arrival city (ICAO 2020)

• (4)

  Fuel efficiency of each aircraft model (The Boeing Company 2020, ANA 2020)

• (5)

  Emission intensity of jet fuel combustion (National Institute for Environmental Studies, Japan 2019)

• (6)

  Embodied emission intensities of jet fuel refinery (Nansai 2019, Nansai et al 2020)

• (7)

  Aircraft price (Airbus 2018, The Boeing Company 2020)

The database of fuel efficiency and timetable used in this study is provided in the supplementary files (available online at stacks.iop.org/ERL/15/104036/mmedia). We assume an equal aircraft sales price for JAL and ANA. The fuel efficiency of each aircraft model in L/km is calculated by dividing the catalog-based fuel capacity (L) by the catalog-based range of the aircraft (km). Since data on the actual fuel efficiency of aircraft models are unavailable, the catalog-based efficiency (L/Km) in our study is defined by dividing the fuel capacity of an aircraft by its achievable range in the case where the fuel is full and all seats are occupied¹. In this study, we tried to evaluate/compare individual functions of each aircraft type under the assumption. Peeters et al (2005) and (Miyoshi and Mason 2009) considered the distance flown, and showed that the fuel intensity and the carbon emissions in g/km per passenger varied by ±20% to ±30% depending on flight range. Therefore, following the previous studies (Peeters et al 2005, Miyoshi and Mason 2009), the margin of error of the fuel combustion phase CO₂ emissions would range from ±20% to ±30%². Examining the gap between actual and catalog-based fuel efficiency is left for a future study. The emission intensity of jet fuel combustion in flight is 2.46 (kg-CO₂/L; National Institute for Environmental Studies 2019). The Japanese carbon emission factor for jet kerosene is obtained from actual measurement (National Institute for Environmental Studies 2019). Using the database, we estimated the CO₂ emissions associated with the international flight activities of two Japanese airline companies (JAL and ANA) for 2005, 2010, and 2015. The companies own a combined total of 483 aircraft: 226 for JAL and 257 for ANA, accounting for 98% of the total number of aircraft in Japan in 2015 (JAL 2016, ANA 2016, MLIT 2019). Thus, Japan's airline market is dominated by these two companies. JAL went bankrupt in January 2010. Accordingly, we focus on Japan's two major airline companies, and the past decade has centered around JAL's bankruptcy.

Data on the number of flights are provided per week, and the timetable of each airline company is revised twice a year. Therefore, we convert the per-week values into annual values based on the assumption that the summer timetable from April to October has 30 weeks, and the winter timetable from November to March has 22.

The embodied CO₂ emission intensities of aircraft production, , were estimated using the World Input–Output Database (WIOD; Timmer et al 2015, Corsatea et al 2019). Specifically, we focused on the 'other transport equipment' sector in France and the United States in the World Input–Output Tables in 2005, 2010, and 2014, and calculated the embodied CO₂ emission intensities of 56 sectors across 43 countries and regions as , where reflect the direct CO₂ emission intensities of the 56 sectors in the 43 countries and regions, is the identity matrix, and is the intermediate input coefficient matrix based on the WIOD (e.g. Kagawa et al 2015). We used the vector elements of the 'other transport equipment' sector in France and the United States in as the embodied CO₂ emission intensities (t-CO₂ per US dollars) of aircraft production in the two nations.

4.1.Airline market

Before proceeding to the environmental analysis, it is worthwhile investigating the airline market in Japan. JAL and ANA dominate the market. As noted above, JAL and ANA own 483 aircraft combined. JAL's and ANA's sales of international passenger flights in 2005 were 690 and 230 billion yen, respectively (JAL 2005, ANA 2005), whereas their sales in 2015 were 448 and 515 billion yen, respectively (JAL 2015, ANA 2015). The following figures are important: (1) total sales for the two airlines increased by 4.3% during the study period between 2005 and 2015; and (2) ANA's market share for international passenger flights increased from 25% to 53% during the study period, whereas JAL's decreased considerably from 75% to 47% due to its bankruptcy in January 2010. Here, market share is calculated by dividing the sales for international passenger flights of each airline company by the total sales for the two airlines.

4.2.CO₂ emissions in flight

4.3.Decomposition analysis

For a relevant study, (Andreoni and Galmarini 2012) decomposed CO₂ emissions from airline industry in the EU 27 countries and found that an expansion of the aviation market (i.e. an increase in the GDP share of the airline industry) contributed to the increasing CO₂ emissions. On the contrary, the present study reveals that an increase in the number of international flights operated by the Japanese airline companies contributed to an increase in CO₂ emissions. It is important to note that (Andreoni and Galmarini 2012) could not distinguish between passengers and freight transportation due to data constraints, however the present study uses detailed timetable data, which allows us to provide detailed CO₂ emissions inventory data by flight. Due to the different definitions on the aviation sector, it is difficult to compare the results of (Andreoni and Galmarini 2012) with those of this study.

(Yu et al 2020) estimated the 'direct' CO₂ emissions from 'domestic and international' flights operated by the Chinese aviation sector. According to the results from (Yu et al 2020), while the average yearly distance flown by Chinese airline companies increased during the study period during 1979 to 2017, its factor had a relatively small impact on increasing CO₂ emissions in the aviation industry—13%, on a yearly average. Meanwhile, this study defines a new factor of 'distance per passenger and flight' (i.e. physical flight service per passenger) and shows that the distance-per-passenger effect contributed to increasing CO₂ emissions in the aviation industry (JAL and ANA in this study) between 2005 and 2015 by 3.1% on a yearly average. Compared with the number of flights effect, accounting for 1.5% on a yearly average, we find that the distance per passenger effect had a relatively large impact of increasing CO₂ emissions in the aviation industry in Japan. Thus, this study provides a different angle of interpreting how distance matters in CO₂ emissions from the aviation industry.

Since previous studies estimated the aviation emissions by country and region, and decomposed the change in CO₂ emissions, they cannot evaluate the CO₂ emissions of individual airline companies. Therefore, from previous studies, it is difficult to propose a CO₂ emissions reduction policy at airline company level necessary for CORSIA, where emission limits are set for each airline company. It is important to note that the CO₂ emissions of each airline company are simultaneously affected by both supply-side factors such as practical flight operations, and demand-side factors such as passenger demand. In this study, we developed a new decomposition analysis framework to simultaneously analyze a tradeoff relationship between the supply-side factors and the demand-side factors.

This study estimated the CO₂ emissions associated with international flights by JAL and ANA, and identified their drivers through an index decomposition analysis. The results show that changes in aircraft models and the total number of flights affected the CO₂ emissions attributable to the aviation industry most significantly. The introduction of the Boeing 787, the fuel efficiency of which is greater than that of conventional models, led to remarkable CO₂ emission reductions (of 2.8 Mt-CO₂) for both companies between 2005 and 2015.

Conversely, CO₂ emissions from both companies increased by 2.9 million tons from 2010 to 2015 due to an increase of TN, which was the strongest driving force. The Boeing 787 reduction effect was canceled out by the TN effect in the Japanese aviation industry. Although the supply factor is critical in the mitigation of carbon emissions generated by aviation, it is not practical to include this factor in policy discussions regarding CO₂ reduction given the increasing demand for aviation (see figure 1). Tokyo International Airport (Haneda Airport) has the capacity to increase its number of international flights. This airport is expected to handle a 1.7-fold increase in flights in 2021, the year of the Tokyo Olympic Games, relative to its 2015 number (MLIT 2017). This is expected to boost the number of international flights in Japan and the CO₂ emissions associated with them.

However, Japanese airline companies must mitigate their CO₂ emissions from international flights because the Japanese government is participating in CORSIA (ICAO 2016c). Importantly, we have also found that an environmental and business strategy of introducing greener aircraft with greater fuel efficiency, such as the Boeing 787, was not enough to reduce CO₂ emissions.

The FE's reduction effect due to the introduction of new aircraft increased CO₂ emissions in the manufacturing phase. We estimated the amount of CO₂ emissions generated by JAL and ANA from the production of new aircraft in equation (5) as 6940Kt-CO₂ between 2000 and 2015. These emissions were as large as the annual flying-phase emissions of the two companies. Therefore, airline companies need to evaluate in greater detail the life-cycle of CO₂ emissions beyond the flying phase, including in the production phase, to mitigate the CO₂ emissions produced by aviation activities.

Furthermore, the DP effect was the main factor in the increase of CO₂ emissions from 2005 to 2015, and accounted for 3.6 million tons of CO₂. During this decade, consumers preferred longer distances. To combat global warming, France introduced an eco-tax on airlines flying from French airports (Reuters 2019). The French government announced that it would 'add €1.50 ($1.68) to the cost of a plane ticket in economy class within the European Union (EU) and €3 to an economy ticket outside the EU. In business class, the levies will be €9 and €18 respectively' (Climate Home News 2019).

The French tax policy, based on seat classes, is not effective in reducing CO₂ emissions, because the eco-tax is imposed on consumers uniformly, regardless of flying distance. In 2018, the Swedish government introduced an air travel tax based on the flight's destination (Swedish Tax Agency 2018). For an eco-tax to reduce the CO₂ emissions attributable to both flying distance and aircraft type, it needs to be imposed based on aircraft type as well as flying distance, which would increase taxes on long-haul routes and less fuel-efficient aircraft.

The Japanese government has suggested improving aircraft and fostering greener operations by utilizing market mechanisms such as carbon emission trading, and by introducing bio-jet fuel to mitigate CO₂ emissions owing to international flights (MLIT 2015b). Furthermore, the International Air Transport Association (IATA) has also emphasized the importance of bio-jet fuel for CO₂ emission reduction (IATA 2018). Bio-jet fuel is commercialized in European countries and the United States. Additionally, the EU established the EU emissions trading system (EU-ETS) framework, which offsets CO₂ emissions from the combustion of bio-jet fuel (European Commission 2014). Studies by the National Aeronautics and Space Administration (NASA), as well as other research, predict that bio-jet fuel will lead to a reduction in CO₂ emissions from the aviation industry of approximately 50% to 70% (NASA 2017). This forecast will accelerate the use of biofuel in the aviation industry (Kousoulidou and Lonza 2016, Wise et al 2017, Yilmaz and Atmanli 2017, Staples et al 2018). Both JAL and ANA have invested in research and development of bio-jet fuel and conducted tests of flights powered by it (JAL 2009, ANA 2012). Thus, using bio-jet fuel will be crucial in reducing aviation emissions and enhancing passenger safety. Furthermore, it will be important to introduce a 'smart control system' to determine how to replace older aircraft with newer ones to meet airlines' long-term climate targets. Smart control systems can simulate the aviation emissions associated with the manufacturing/replacement and use phases given various driving factors, such as fuel efficiency, the number of flights, flight distance, and the number of passengers—all of which were considered in this study—as well as sales.