Rank-order concordance among conflicting emissions estimates for informing flight choice

Abstract

Air transport Greenhouse Gas (GHG) emissions estimates differ greatly, depending on the calculation method employed. Among the IPCC, ICAO, DEFRA, and BrighterPlanet calculation methods, the largest estimate may be up to 4.5 times larger than the smallest. Such heterogeneity-and ambiguity over the true estimate-confuses the consumer, undermining the credibility of emissions estimates in general. Consequently, GHG emissions estimates do not currently appear on the front page of flight search-engine results. Even where there are differences between alternative flights' emissions, this information is unavailable to consumers at the point of choice. When external considerations rule out alternative travel-modes, the relative ranking of flight options' GHG emissions is sufficient to inform consumers' decision making. Whereas widespread agreement on a gold standard remains elusive, the present study shows that the principal GHG emissions calculation methods produce consistent rankings within specific routestructure classes. Hence, for many consumers, the flight identified as most GHG efficient is not sensitive to the specific calculation method employed. But unless GHG emissions information is displayed at the point of decision, it cannot enter into consumers' decision making. A credible and ambiguity-free alternative would thus be to display GHG ranking information on the front page of flight search-engine results.

Business Travel GHG Emissions Analysis: Factors, Tools, and Cases for Calculating GHG Emissions and Setting Science-Based Targets for Organizations

“…Other literature since the GHG Protocol has noted the variations in GHG results from using different methodologies, especially for business-related air travel, which is often one of the largest GHG activities within Scope 3. Kaivanto and Zhang (2017) conducted a study of multiple method variations (e.g., IPCC, ICAO, Department for Environment, Food, and Rural Affairs (DEFRA), and BrighterPlanet) used by airline companies and travel booking services. Method choices, such as emissions factors, variations in radiative forcing multipliers, and adjustments for seat class and baggage, were included in the study, and their findings showed inconsistent results as high as4.5 times the difference between the largest and smallest GHG emissions calculations.…”

“…Baumeister and Onkila (2017) went further to propose an ecolabel to help consumers navigate the complex factors that change the climate impacts of each flight. However, as noted earlier by Kaivanto and Zhang, air travel company calculations will still need to align their methods for comparing across companies (Kaivanto and Zhang 2017). Pandey, Agrawal, and Pandey (2011) take a similar approach, as did Birnik (2013), in their study comparing web-based GHG footprint calculators and looking specifically at business-related travel.…”

Can nudging affect tourists’ low-carbon footprint travel choices?

“…Information related to carbon emissions may influence tourists to make more environmentally conscious choices (Carroll et al , 2022; Kaivanto and Zhang, 2017). The effect of different information types and the manner in which information is provided to tourists deserve more research attention.…”

A fuel-payload ratio based flight-segmentation benchmark

“…Although several methods exist for calculating the GHG emissions of scheduled air transport, the dominant component common to all methods is mission fuel (see e.g. Kaivanto and Zhang, 2017). Nevertheless mission fuel is not the only determinant of GHG emissions.…”