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Estimating the global warming emissions of the LCAXVII conference: connecting flights matter

  • Miguel F. AstudilloEmail author
  • Hessam AzariJafari
ACLCA CORNER

Abstract

Purpose

Conferences are an important element of scientific activity but can also be a major cause of environmental burden. With this in mind, we analysed the global warming emissions of the 2017 annual conference of the American Center for Life Cycle Assessment (ACLCA), in order to estimate the carbon footprint and identify potential ways to reduce it.

Methods

We used survey data from participants as well as literature sources to complete an attributional assessment of the greenhouse gas emissions per participant. A method to calculate the ‘ideal’ location is proposed, which can be used to identify ‘unreasonably’ distant conference locations.

Results and discussion

The average emissions per participant were found to be 952 kg CO2eq, but with a large variability due to differences in travelled distance. Connecting flights were found to increase emissions up to 32% compared to direct flights, due to the increased number of take-offs and landings.

Conclusions

Results indicate that future studies should use distance-dependent flight emissions to increase the accuracy of the assessment. Some measures, such as meat-free menus, had a relatively minor contribution to emission reductions, but could be important as scientists advocating for the reduction of environmental burden should lead by example.

Keywords

Conference footprint Global warming Travel footprint 

1 Introduction

The objective of organising scientific conferences is to bring a community of scientists, engineers and other specialists together to solve specific problems and update the current state of the knowledge. Although participating in any conference plays an essential role in scientific endeavours, over the years, scholars have argued for the importance of minimising the environmental footprint of scientific conferences (EPA 2017; Favaro 2014; Spinellis and Louridas 2013). Indeed, several studies indicate that conference participation is one of the most substantial burdens associated with research (Bossdorf et al. 2010; Spinellis and Louridas 2013; Stroud and Feeley 2015).

Previous estimates of the carbon footprint of a conference vary widely, from 92 to 3000 kg CO2eq/participant (Bossdorf et al. 2010; Stroud and Feeley 2015). Transport-related emissions tend to dominate in most of the life cycle assessment (LCA) indicators, including global warming (GW) emissions (Hischier and Hilty 2002). Notwithstanding, food and accommodation have been reported to be responsible for 31% of total conference CO2eq emissions (Bossdorf et al. 2010); therefore, mitigation strategies should consider them. A thorough review of the literature is provided as Electronic Supplementary Material.

The potential carbon footprint of the LCAXVII conference organised by the American Center for Life Cycle Assessment (ACLCA) was evaluated to suggest effective means for establishing sustainable academic practices. This event was held on October 3–5, 2017, at a hotel in Portsmouth, New Hampshire, with the participation of 228 delegates. In this conference, 41 sessions were held and 40 poster presentations were included in the conference program. The conference had a number of measures taken to reduce environmental impact, such as serving meat-free menus, and not offering PET water bottles or canned sodas during the conference.

2 Methods

2.1 Goal and scope

In order to better understand the environmental burden of an international conference and explore some potential ways to reduce it, LCA was used to give a comprehensive view of the emissions attributable to the conference. The focus was on emissions from transportation as it is well known to be the primary source of emissions (Hischier and Hilty 2002; Bossdorf et al. 2010). The accuracy of the estimate is improved over past studies by considering factors that are usually neglected in the literature such as:
  • The multimodal nature of transport (car, train and plane)

  • How travelled distance affects the average emissions per flight

  • Differences between travelled and ‘as the crow flies’ distance

  • The potential effect of connecting flights

  • The ‘optimal’ location of the conference

We used CO2eq emissions as the indicator for environmental burden using 100-year global warming potential (GWP100) characterisation factors. Despite its limitations, the ‘carbon footprint’ is considered to be a good proxy for energy-related activities (Kalbar et al. 2017). For validation, we studied the correlation between CO2eq emissions and other environmental indicators from the impact assessment method ReCiPe (Goedkoop et al. 2009). Figure A1 (in the Electronic Supplementary Material) shows that all indicators in the ReCiPe methodology are strongly linearly correlated with greenhouse gas emissions for the flight-related burden. Therefore, we consider CO2eq as a good proxy for environmental burden in this context. For consistency, all the sources used in this conference report use the GWP values provided in the IPCC 2007 report.

Cradle-to-grave emissions associated with accommodation were taken from the literature while emissions from food provision were calculated based on the menu. Scientific conferences can be combined with other professional and personal activities. In such cases, part of the emissions of travel could be allocated to other activities, reducing the burden of the conference. Maximising the utility of the travel could be a way to reduce emissions, but in this study, all emissions from travel were attributed to the conference, as we only had anecdotal evidence of multi-purpose travels.

2.2 Inventory

The environmental burden from transportation was based on responses to an online questionnaire sent to all participants before the conference. We collected 122 responses, albeit some incomplete, which represented 54% of the participants. In some instances, we needed to make a series of assumptions to fill data gaps. These are documented in the Electronic Supplementary Material.

The origin of the participants was geolocated, and the travel ‘as the crow flies’ distance (i.e. geodesic distance) to the conference was estimated using geocoding tools (Geopy 2015). For those travelling by car, the travelled distance was estimated using Google Maps API (2017). The estimated road travelled distance was strongly linearly correlated (p = 1.8e−28 R2 = 0.97) with the geodesic distance, and about 30% larger. For those travelling by plane, the geodesic distance was scaled to take into account real-world flying constraints that deviate planes from optimal routes. Scaling factors were obtained from Reynolds (2014). We used US estimates for flights from North America and values of flights across the Atlantic for transoceanic flights. Distances from the airport to the conference venue were also estimated using Google Maps API (2017). Snippets of the python code used to execute different tasks are provided in the Electronic Supplementary Material.

The life cycle CO2eq emissions of flight transport are taken from Cox et al. (2018). This publication is the state of the art in air transport emissions and it accounts for several issues rarely addressed in the literature, such as the GWP of nitrogen oxides (NOx,) water vapour and aviation-induced cloudiness. It also models separately landing, cruise and take-off, providing distance-dependent emission factors (EF). The publication reports emissions for travel distances between 100 and 1200 km, which were used to fit a power function (p = 1.08e−7, R2 = 0.96) (Fig. A2 in the Electronic Supplementary Material). When connecting flights were reported, the average EF was estimated assuming the connection divided the total journey into two equidistant flights. We note that for any given distance, a 50–50 split results in maximum emissions for the modelled function. The inventory distinguishes between different years of construction and the average age of the US air fleet was used for this study. For the rest of the transport modes (train, car and bus), life cycle emissions were obtained from the dataset reports in ecoinvent 3.4 (cut-off version). We assumed participants returned to the same location using the same transport modes.

Other studies assessed optimal locations, restricting the potential locations to origins of participants (Stroud and Feeley 2015). In our study, we did not impose such a limitation and the ‘optimal’ conference location was estimated as the geometric median (i.e. the point that minimises the total Euclidean distance for all participants). We used an implementation of the algorithm proposed by Vardi and Zhang (2000) provided by Orson Peters (Pers. Comm).

The conference gave a vegetarian menu in addition to some local seafoods, such as crab and fish. The details of the conference menus were obtained from the organiser, including breakfast, lunch and two coffee breaks. Emissions from food provision were estimated using the CarbonScopeData database. This LCI database provides data on embodied CO2eq for a broad range of agricultural processes and food products in the North American context. The required energy for cooking the food on the conference menu was extracted from Hager and Morawicki (2013) using liquefied petroleum gas as a fuel for heating energy. Quantifying potential emission reductions with respect to a meat-based menu requires estimating the likely changes in production systems due to a change in demand (consequential LCA). The potential emission reductions due to dietary change were derived from Goldstein et al. (2016).

According to the survey, 82% of the delegates stayed at a hotel. In addition, 15% of the participants stayed in households, using systems such as Airbnb™. We assumed that three persons were accommodated in each house. An average electricity consumption of 604 kWh/month was considered for household stays according to the consumption regime in New Hampshire (EIA Average Monthly Bill-Residential 2016). For the delegates, who stayed at hotels, the inventory was adopted from the literature (Filimonau et al. 2011), including energy consumption for hotel operational processes, such as air conditioning and hot water, as well as non-operational processes, such as laundry. The heat and electricity grid mixes for New Hampshire were extracted from EIA and US Census Bureau websites, respectively, and the obtained values were included in the analysis of the accommodations for hotels and houses. The inventories of all the background processes, such as infrastructure, were obtained from ecoinvent v.3.4.

3 Results and discussion

3.1 Transport

The average greenhouse gas emissions due to transport were estimated to be 883 (s = 824) kg CO2eq per participant. Taken as reference median per capita emissions from 2010 (Blanco et al. 2014), the average emissions per participant were around 6 and 57% of the annual per capita emissions in high-income and low-income countries respectively. Average emissions are similar to those estimated by Spinellis and Louridas (2013) but much higher than those from other conferences where fewer participants came by plane (e.g. Bossdorf et al. 2010). As illustrated in Fig. 1, the CO2eq emissions vary considerably between participants, mainly because of the variation in distance travelled. Among those travelling shorter distances, there is a wide variability of emissions. For instance, travelling alone by car (the worst non-flying option) has lower CO2eq/km than flying for trips of less of 750 km, but has around five times more emissions per kilometre than buses or trains. Twenty percent of participants with the highest emissions accounted for 50% of total emissions (Fig. A3 in the Electronic Supplementary Material).
Fig. 1

Total CO2eq emissions per participant as a function of geodesic distance to the conference. Markers differentiate participants that took a connecting flight, took a direct flight or used alternative means of transport

Figure 1 also shows how connecting flights may have a detrimental environmental effect. Taking several flights means more take-offs and landings, increasing emissions per kilometre flown. The finding suggests that conferences should prioritise locations that minimise the need for connecting flights, possibly close to big airports. Flight emissions as a function of distance were compared with reference values of intercontinental and intracontinental flights from the ecoinvent database (Fig. A2). For distances shorter than 5000 km, applying a constant emission from literature can considerably underestimate emissions from flights.

If the same participants would have come to the optimal conference location (i.e. the location that minimises—Euclidean—distance), the average distance would have been 1913 km/participant. This is 6% lower than the actual average distance travelled. We note that this potential for reduction assumes that conference location does not affect the origin of the attendees. This is a potentially unrealistic assumption, but the proximity of the ideal and actual conference location suggests the distance to the conference is an important factor for participation. A more reliable estimate could be calculated using participation data from multiple years, which would give a more representative sample of the participants that go to the ACLCA annual conference. Carbon codes of conduct have been proposed for researchers Favaro (2014), and such an indicator could facilitate the identification of unreasonably distant conference locations.

3.2 Food and accommodation

The average carbon footprint from the hotel and house accommodations were estimated to be 6.85 and 5.12 kg CO2eq/person/night, respectively. For the homestay participants, a similar result is reported by Tsai et al. (2014), where they reported a 6.3 kg CO2eq/person/night emission for an average of 2.76 tourists in household side activities in Taiwan. For the hotel accommodation, there is a wide range of results in the literature. As reported by De Grosbois and Fennell (2011), the variety of results can be from 6.04–23.7 kg CO2eq/person/night in studies with similar scope but with different room type (luxury, economy etc.) and different locations.

The LCAXVII conference provided vegetarian food as means to reduce the environmental impact of the conference. Provisions for breakfast, breaks and lunch accounted for 1.3 kg CO2eq/person/day, which is slightly higher than the results of other studies, such as Leuenberger et al. (0.9 kg CO2eq/person for an average of five vegetarian main courses). The higher emissions of the conference can be attributed to the coffee breaks (0.08 kg CO2eq/person per break) and breakfast menu (0.34 kg CO2eq/person). Results from Goldstein et al. (2016) indicate a change to the vegetarian menu from an omnivorous diet would reduce GW emissions by 46%. Thus, the omnivorous diet is about 1.85 more GW intensive. Therefore, the decision to serve a vegetarian menu avoided about 3 kg CO2eq/person for the 3 days of the conference. The relative contribution of food-related emissions in this study is about 1%, lower than in Bossdorf et al. (2010). The difference can be explained partially because it was a vegetarian menu, but mostly because transport emissions to this conference were much higher. We note that these estimates ignore the fact that some participants may already follow a vegetarian diet, and that testing vegetarian diets may have knock-on effects on changing dietary habits.

4 Conclusions

This study estimated the cradle-to-grave life cycle emissions of an international scientific conference held in Portsmouth, New Hampshire, in the USA. Results indicate that transport choices have a substantial impact on the emissions per participant. Applying distance-dependent emission factors for flights show emissions from ‘short’ flights would have been considerably underestimated using a constant emission factor. Using distance-independent emission factors ignores the impact of connecting flights, which turns out to be a very relevant factor in the estimation of transport CO2eq footprint due to the increase in take-offs and landings. Thirty-three percent of the respondents reduced their carbon footprint using alternatives to planes. Nonetheless, planes were the preferred transport mode for travels over 500 km. The distance to the location that would minimise the total distance travelled by potential participants can be used as an indicator of the suitability of conference locations. Such an indicator can also be used to discard unreasonable distant conference locations.

Accommodation and (vegetarian) food accounted for a relatively minor share of total CO2eq emissions (1 and 2%, respectively). Despite the ‘small’ contribution, they should not be disregarded and can serve as levers to reduce the impact of a conference, as transport-related emissions are conditioned by the country’s transport infrastructure. However, conference organisers may have more choices when it comes to selecting venues and menus for the conference.

Although some measures have a relatively small impact, conferences should try to reduce impact in the measure of their abilities. If scientists do not lead by example, they could be seen as hypocritical. With a public perception on climate change sharply influenced by motivated cognition (Kahan et al. 2012), practices perceived as hypocritical could have an adverse effect on GW mitigation efforts.

Notes

Acknowledgements

The authors thank the ACLCA board, Debbie Steckel and Prof. Ben Amor for giving us the opportunity to participate in the conference and conduct the survey. The authors also thank Joris Deschamps, Marianne Pedinotti-Castelle and Mohammad Davoud Heidari for their participation in an earlier version of the footprinting of the conference. Finally, we thank Brian Cox and co-authors for providing an early version of their results.

Supplementary material

11367_2018_1479_MOSM1_ESM.pdf (498 kb)
ESM 1 (PDF 497 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Interdisciplinary Research Laboratory on Sustainable Engineering and Ecodesign (LIRIDE), Civil Engineering DepartmentUniversité de SherbrookeSherbrookeCanada

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