cBalance has been engaging with Wipro, an Indian Information Technology Services Corporation, to estimate their GHG emissions from air travel since 2015.
The objective of the project has been to estimate GHG emissions from air travel, analyze Wipro’s flying patterns, estimate possible reductions in GHG emissions and recommend strategies to reduce GHG emissions.
The analysis was adhered to GHG Protocol’s Corporate Standard, accompanied by IPCC Guidelines 2006 to calculate airline specific emission factors (insert footnote)
Following the equation:
GHG Emissions = Activity Data x Emission Factor
Here, the Activity Data was the distance between Airport A to Airport B, calculated using great circle equation.
Emission factor was given in terms of kg CO2e / pax-km for each airline, distinguished based on whether the flight was International or Domestic and whether the flight was short, medium or long haul (this was determined based on the distance).
For FY 2014-2015 estimated GHG emissions were 170.1 thousand tonnes CO2e, with 1,269.8 million pax-km traveled across 5.0 lac flights
For FY 2015-2016 estimated GHG emissions were 152.9 thousand tonnes CO2e, with 1,134.4 million pax-km traveled across 4.7 lac flights
During these two cycle of analysis, other than estimating the GHG emissions from air travel, the major emphasis was on quantifying reduction potential and study reduction strategies. This was achieved by modeling two scenarios :
Best-In-Class Switch :
The goal of this scenario was to determine, for a given flight, the best airline in terms of emission factor ranking for its specified route. This helped us and Wipro quantify reduction potential just by switching over to a more efficient airline.
The estimated GHG emissions reduction from Best-In-Class switch for FY 2014-2015 were 59.9 thousand tonnes CO2e and for FY 2015-2016 were 36.9 thousand tonnes CO2e
Multi-stop to Non-stop Switch :
The goal of this scenario was to determine possible reductions in GHG emissions switching from a multi-stop flight to a non-stop flight.
The estimated GHG emissions reduction from Multi-stop to Non-stop switch for FY 2014-2015 were 19.4 thousand tonnes CO2e and for FY 2015-2016 were 11.7 thousand tonnes CO2e
In total, 79.3 thousand tonnes CO2e and 48.6 thousand tonnes CO2e reductions were estimated respectively for FY 2014-2015 and FY 2015-2016
A white paper titled Reducing Air Travel Emissions can be read here, where we have ranked airlines based on their GHG Emission Factor.
FY 2016-2017 & FY 2017-2018
For FY 2016-2017 estimated GHG emissions were 130.2 thousand tonnes CO2e, with 923.7 million pax-km traveled across 2.1 lac flights
For FY 2017-2018 estimated GHG emissions were 116.5 thousand tonnes CO2e, with 836.8 million pax-km traveled across 1.9 lac flights
Since the recommendations of flying the best-in-class airline, flying non-stop over multi-stop and choosing to travel via railways and/or use video calling services were already implemented, during these cycle only emission estimation was conducted on the business unit level.
For future development, the goal is to implement emissions and a financial budgeting system with respect to flying on a business unit level with the idea that it would create responsible air travel amongst employees.
Details on the Business Units wise emissions for FY 2016-2017 can be viewed here.
Furthermore, click here to view a comparison between Economy vs Business Class emissions between FY 2016-2017 and FY 2017-2018
Wipro, an Indian IT services multinational company desiring to become greener, commissioned cBalance to calculate its carbon footprint from business air travel so that strategies could be implemented to reduce these emissions. Wipro has an international presence and a wide geographic base and, thus, must use air transport in order to meet the needs of its clients. In the 2013-14 financial year, Wipro reported 103 thousand tons of CO2e GHG emissions from business travel, which was 13% of its total! Here lied a great opportunity for Wipro to substantially reduce its carbon footprint. So we set out to:
• estimate the carbon emissions factors for domestic and international airlines used by Wipro in 2014-15
• estimate a GHG inventory of Wipro’s business air travel based on the GHG Protocol Corporate Accounting and Reporting Standard,
• make a rankings index of domestic and international airline carriers sorted by their GHG emissions factors,
• recommend a best-in-class air carrier for each sector of company air travel,
• model choices that could reduce GHG emissions (choosing the best airline, reducing the number of stops in a journey)
Not only would this be useful for Wipro, the results of the study could be potentially used by the public at large to reduce their own carbon footprints by simply by making the right decision at the time of booking a flight.
Methodology:
The scope of the project covered all airline business travel, international and domestic, of Wipro during the 2014-15 fiscal year: nearly 500,000 flight legs and about 1.3 billion passenger-km traveled. While about 60% of the flights were domestic, over three quarters of the distance traveled was from international flights.
The GHG emissions inventory was taken following the GHG Protocol’s Corporate Standard, which covers the accounting and reporting of the six greenhouse gases following the Kyoto Protocol: carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulphur hexafluoride (SF6), and requires adherence to the principles of relevance, completeness, consistency, transparency, and accuracy. Only the first three greenhouse gases, carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), are considered, as emissions of the other three were below the materiality threshold as defined by the ‘completeness’ principle. Operational boundaries have been specified according to the standard, which entails categorizing emissions as either direct or indirect emissions and choosing the scope for indirect emissions. The measured unit of reference flow is passenger-km of air travel and the unit of analysis is Metric Tonne of CO2e.
Wipro provided the raw data set (flights, airport codes, and carrier codes) and collection began by devising and administering a list of data needs identified by the Standard. Domestic short-haul and long-haul flights were defined as shorter and longer than 500 km, respectively, and international short-haul flights as up to 2,000 km, medium-haul flights as between 2,000 and 5,000 km, and long-haul flights as greater than 5,000 km. cBalance corrected errors and invalid entries in these data.
To develop emission factors, LTO (landing/takeoff) and cruise mode emissions were calculated for all aircraft models. Next, best-case per-passenger emission factors for finite distances were derived for every aircraft model (using maximum passenger capacity and load factor of 1). The same was done for additional finite distances on every aircraft model. Then, the per-passenger emissions for finite distances for each airline was calculated by summing the LTO and cruise-mode emissions (accounting for weighted average airline passenger capacities, airline-wide passenger load factors, and passenger to freight ratios). Finally, the same was done for additional finite distances for each airline. Unfortunately, the relative frequency of operation or share of annual passenger-kms performed by a given aircraft model in an airline’s fleet could not be taken into consideration due to the unavailability of the necessary data regarding domestic airline operations. Incorporating such statistics to arrive at a weighted average would provide a more rigorous approach.
Scenario Modelling:
cBalance also modelled two different scenario comparisons. The first compared the baseline to the best-in-class and found that if international flights were switched to the best-in-class scenario, it would result in savings of 41% of GHG emissions. For all Wipro’s international flights, the total savings would be 70.44 thousand tonnes of CO2e emissions. For domestic US flights, the best-in-class scenario results in 37% savings (7.47 thousand tonnes), and for domestic Indian flights the savings are 20% (3.92 thousand tonnes). The second compared multi-stop to non-stop flights and found that for international flights, 25% savings resulted from using non-stop flights, and for US domestic flights, the savings were 50%.
Conclusions:
From the fourth quarter of the 2015-16 fiscal year to the first quarter of the next, Wipro reduced the number of segments flown by 8.7%, but GHG emissions decreased 30% cumulatively and 23% per segment. Wipro was able to achieve such huge emission reductions by merely flying 7% fewer multi-stop segments and choosing ‘cleaner’ airlines.
Based on these findings, cBalance recommends that if the difference between the two airlines is less than 15%, pick the non-stop flight on the ‘dirtier’ airline instead of a flight on a ‘cleaner’ airline with a layover. If the difference is greater than 15%, on the other hand, pick a flight on a ‘cleaner’ airline with a layover as opposed to a non-stop flight on a ‘dirtier’ airline.
Air travel is a highly unsustainable activity that should be avoided when possible. Companies are pledging to take advantage of the teleconferencing capabilities enabled by our age of high speed internet to avoid unnecessary face-to-face meetings. When it is impossible to avoid such flights, companies and individuals can choose the optimal airline, reduced number of stops, and economy class, to reduce their GHG emissions. Something as easy as picking a non-stop flight can save dozens of kilograms of CO2e emissions. For some perspective on what that means, a large tree breathes about 12 kilos of CO2 a year. This is an easy way to reduce one’s carbon footprint.