Balancing environmental sustainability with the social goals of scientific organisations: a ‘COM-B’ behaviour change strategy to reduce greenhouse gas emissions from international scientific conferences, meetings and educational events

doi:10.21203/rs.3.rs-4430720/v1

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Balancing environmental sustainability with the social goals of scientific organisations: a ‘COM-B’ behaviour change strategy to reduce greenhouse gas emissions from international scientific conferences, meetings and educational events

https://doi.org/10.21203/rs.3.rs-4430720/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 02 Nov, 2024

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Objective

To estimate the environmental impact of two exemplar in-person academic events and, using the COM-B behaviour change framework of capability, opportunity, motivation, identify strategies that could be applied by organisers and participants to reduce this impact.

Methods

We calculated the greenhouse gas (GHG) emissions from two European PhD summer schools, one geographically peripheral and one central, organised by a European academic society, the European Academy of Nursing Science. We used participant distances from home university cities to the event sites to calculate individual GHG travel emissions. We incorporated on-site emissions into per-participant totals, and examined the relative contributions of travel and on-site factors to individual and total event emissions. We calculated the financial costs of individual participant attendance.

Results

Our exemplar events contributed between 41 tonnes and 99 tonnes CO₂e emissions per event, a per-participant mean between 0.324, (SD 0.173) and 0.724, (SD 0.263) tonnes, representing 2 to 5.5 times the daily per-person European average. Distance from home was the largest contributor to emissions, with the peripheral event associated with 2.5 times the emissions of the central event, driven by aviation as flying was the only viable means to travel long distances. On-site emissions were no more than 26% of the total event emissions profiles. Costs were similar for both events.

Implications

Whilst organisers can provide participants with the opportunity to travel shorter distances and to sites where ground-based travel options are available, participants may not act on opportunities unless their capabilities and motivation are enhanced. We describe a behaviour change programme, structured using the COM-B model, that identifies strategies for organisers and participants to use to reduce the GHG emissions of academic events. A multi-component behavioural change programme including environmental change, enablement, education, incentivisation and persuasion is likely to be more successful than single strand approaches.

In 2023, immediately prior to the UN COP28 meeting, the United Nations (UN) Environment Programme issued a chilling assessment of the state of the world’s environment¹. Against targets to limit global warming to 1.5°C^2,3, they predict that current activities will result in global greenhouse gas (GHG) emissions 55% higher than the levels required to meet this target. Despite a significant slowing down in the rate of increase, GHG emissions globally will still rise by a predicted 1.1% in 2023, a record high⁴. At this rate of increase, the world has a mere seven years from 2023 before the chances of limiting global warming to 1.5% are less than 50%⁴. The only way to bridge the gap is by taking ‘immediate and unprecedented mitigation action in this decade’ (p28) ¹ by totally eliminating carbon dioxide emissions⁵.

These mitigation actions generally focus on decarbonising sectors of the world economy that are responsible for the majority of GHG emissions, principally the energy and agricultural sectors, together with consideration of the impact of ‘multi-parametric’ factors such as aviation, economic growth, digitalisation and the development of eco-technologies⁶. Successful mitigation requires moving energy production to renewable sources as well as enhancing both existing and novel carbon capture technologies⁷. Alongside mitigation is adaption⁸, “a response strategy to anticipate and cope with impacts that cannot be (or are not) avoided under different scenarios of climate change” (p1104). Indeed, as part of the negotiations leading up to the United Nations’ 2015 Paris Agreement³, 17 Sustainable Development Goals (SDGs) were agreed, including ensuring access to affordable, safe, sustainable, and modern energy for all, taking urgent action to tackle climate change and its effects.

Whilst actions to reduce GHG emissions require action from national and supranational entities, policy makers also recognise that a range of diverse stakeholders, including local communities, should all play an active role in climate mitigation actions. Various policy initiatives have been developed including the European Union’s (EU) ‘energy communities’^9,10 to assist in meeting a target of reducing the average emissions per capita to 2.4 tonnes by 2030¹¹, from 7.7 metric tonnes in 2021¹². Indeed, it has become apparent that without the involvement of multiple organisational, community and individual stakeholders, initiatives often deliver less than they promised¹³, even though community attitudes to energy use transformation are often positive^14,15.

As much of our knowledge on the climate emergency comes from the work of scientists employed by universities, academics are one of these communities well placed to take the lead in reducing GHG emissions from their activities¹⁶. In one analysis, universities were classed as a medium priority stakeholder group¹³ to be involved in efforts to decarbonise their activities. Academic life involves on-and off-site activities that create considerable GHG emissions. For example, in 2019, business travel emissions, including academics travelling to conferences, comprised approximately 17% of Stanford University’s total carbon footprint, and 22% of their external emissions footprint¹⁷. Travel in general is a very significant contributor to GHG emissions, with business travel – which includes travel by academics and scientists – accounting for 15–20% of all travel^18,19. Indeed, international aviation, often used by academics travelling to meetings, conferences and field work, is the fastest growing source of GHG emissions (28% higher in 2023 than 2022) ²⁰, and a substantial contributor to GHG emissions. Furthermore, once at a conference venue, participants will also interact with hotels, conference centres, cities, food and supply chains which will all have GHG emissions profiles.

In this article we present a behaviour change programme to reduce overall GHG emissions from in-person academic meetings and conferences. We base our programme on an audit of two exemplar activities by identifying the components of these activities and their contribution to GHG emissions. Finally, we identify and categorise mitigation strategies that academic organisations and participating individuals can take, placing these into a behaviour change model ²¹ to drive the transformations necessary to reduce GHG emissions.

For the lay person, discussions about sustainability are usually thought to be about managing the environmental impact of human activities. Whilst the definition of sustainability is somewhat contested²², the related concept of ‘sustainable development’, defined as ‘development that meets the needs of the present without compromising the ability of future generations to meet their own needs’²³, also includes broader action on technical, environmental, cultural, economic and social sustainability.

Academic societies, particularly in areas of healthcare, aim to contribute to many social areas of development. In terms of the UN’s Sustainable Development Goals³, two specifically apply: goal 3, ensure healthy lives and promote wellbeing for all at all ages; goal 4, ensure inclusive and equitable quality education and promote lifelong learning for all. This combination of health and education is a specific focus of healthcare orientated societies, particularly those that focus on the education, supervision and mentorship of healthcare professionals.

One of the traditional methods used by such societies to action these goals has been the conference. Conferences are social spaces²⁴ whereby researchers and educators come together from different countries to network, gain and disseminate new knowledge, foster collaboration, spread good practice and reduce knowledge and clinical practice inequalities. However, the objectives of face-to-face meetings outlined above²⁴ often require participants to travel internationally to achieve these admirable social goals, in direct conflict with the need to reduce GHG emissions and contribute to environmental sustainability. As noted by Leochico and colleagues, ‘large scientific conferences aimed at enhancing health-related knowledge, ironically, often implies leaving huge carbon footprints, a practice that may seem contrary to what healthcare professionals are advocating’²⁵ (p1).

Organising exclusively online, hybrid, zonal/local, or other ‘Nearly Carbon Neutral’ events²⁶ will lead to the most dramatic reductions in GHG emissions²⁷. Many academics adapted to the travel and face-to-face interaction restrictions during the 2020 COVID-19 pandemic by using online platforms for teaching and research. One study that modelled a continuation of these behaviours post-pandemic showed that GHG emissions from academic activities could be reduced by almost 50% compared to pre-pandemic behavioural norms²⁸. However, many academics think that these behaviours are only suitable for international administrative meetings²⁹. Many academic participants do not believe that virtual communications can achieve the networking and educational objectives of scientific conferences and educational events^26,29–31. Participants at conferences report benefitting greatly from face-to-face interactions, and by informal social connections made outside the scheduled programme. This belief is so entrenched, that In one study, when presented with three choices – transportation mode shifting (from aviation to ground-based), moving to virtual conferencing, abstention from involvement – it was transportation mode shifting that was rated most acceptable by respondents²⁹.

Balancing social good with environmental harm is a core challenge that must be faced by academic societies before 2030. As concern has grown about anthropogenic impacts on our environment^1,3, profit and non-profit organisations are increasingly encouraged, if not required by legislation, to undertake and report emissions audits³². The global standard for these reports is structured against three ‘scopes’³³.

Scope 1 emissions cover those produced directly by the organisation itself through its own activities – for example, manufacturing processes, product delivery etc. Scope 2 includes indirect emissions caused by others who produce the energy consumed in the manufacturing process, such as electricity produced by power stations. Scope 3 is essentially all other emissions from sources that the organisation does not own or control. For most organisations scope 3 is over 70% of their total emissions³⁴. One particular problem for academic societies that organise conferences and meetings is that emissions caused by their activities are almost 100% scope 3 (albeit some may also be classified as scope 2 emissions from event host sites) and, therefore, outside their direct control.

Unlike profit and not for profit organisations, academic societies are not formally required to report their emissions. There is, however, great merit in auditing emissions in order to understand the impact of their activities on the environment. Until academic societies understand their GHG emissions profile they cannot target those mitigating actions which will achieve the largest reductions in GHG emissions. As noted by many in the for-profit community, ‘Many of those emissions are unavoidable, but almost all of them can be reduced’³⁵ (p34). As an example, emissions from aviation travel can appear difficult to reduce, given that in many instances there are few travel alternatives with lower emission characteristics. However, high-speed trains with far fewer GHG emissions are a feasible alternative to aviation when travelling between 300–800 km, equivalent to 3–6 hour journeys times³⁶.

These issues were addressed in a scoping review of 11 articles which assessed the GHG emissions produced by academic conferences²⁵. The review authors collated reported strategies that academic societies could take to reduce their GHG emissions²⁵. These ranged from moving conferences entirely online, through hub and spoke and hybrid conferences, to face-to-face venue choices and on-site strategies, including through sustainable food procurement choices, sourcing power from renewable energy companies, and so forth. However, few of the constituent articles focussed on the key issue of individual participant behaviour change. Conference attendance is so deeply embedded in academic culture that whilst organisers must make corporate changes, it is also necessary for individuals then take advantage of the opportunities brought about by these changes. As noted by Garnett and Balmford, whilst governmental action must be the major force for change, organisations are a third group who can bridge the gap between governmental and individual behaviour change³⁷.

This conundrum is well understood in healthcare. Many effective treatments and health interventions provided by health systems are not adopted by those who might best benefit from them. Type 2 diabetes, for example, can often be prevented and reversed by lifestyle choice, but despite this knowledge many with the condition or at risk of developing diabetes do not take up or maintain these proven strategies and programmes^38,39. Likewise, handwashing by healthcare professionals is known to reduce infection rates in hospitals, yet compliance by doctors, nurses and other health workers can be less than 50%⁴⁰. Change is hard to do and even harder to maintain.

As a consequence, behaviour change strategies within the related field of ‘implementation science’⁴¹ have been developed to reinforce desired changes in behaviour. One popular model is ‘COM-B’ which postulates that for individuals to change their Behaviour they need the Capability to do so, along with the Opportunity and personal Motivation²¹. Within this model is the ‘behaviour change wheel’ in which the COM-B elements are surrounded by specific interventions to boost capability, opportunity and motivation, together with policy actions to enable the specific interventions to take place effectively.

In this article, we take an explicit behaviour change perspective to the problem of academic conference GHG emissions. To do so, we examine the GHG emissions from activities for European PhD students run by the European Academy of Nursing Science (EANS), an exemplar of an academic society. EANS is a network of individual nurse scientists from universities across Europe which aims to advance nursing and midwifery science in Europe (https://www.eansnursing.eu). It provides a forum for established and developing nurse researchers to meet, network and develop a European perspective to their work. Annually, EANS holds a summer conference, scientific meetings, regular webinars and a summer school for nurses and midwives undertaking PhDs in Europe.

Questions

What is the GHG emission cost in carbon dioxide equivalent attributable to two differently located European summer schools for PhD students hosted by the European Academy of Nursing Science as exemplars for in-person academic events?

What factors are the main contributors to these emissions?

What are the differences in financial costs to student and faculty participants of attending differently located events?

What strategies will have the greatest impact in reducing GHG emissions?

Participants

Participants were faculty and PhD students attending two academic events – summer schools for European PhD students organised by EANS – in 2018 in Ghent, Belgium and in 2019 in Lisbon, Portugal. The summer schools are multinational learning environments designed to provide doctoral students with a common European perspective for their research, to learn advanced research methods and to enhance the opportunities for them to collaborate with other European researchers. Over 100 doctoral students and around 30 faculty attend each annual summer school, which lasts two weeks, with students attending between five and 12 days each.

Data availability

We had access to a fully anonymised dataset provided by EANS, including only the name of participants’ affiliated university city, and stripped of all individual personal identifiers. Given that all data were anonymized before access and analysis, we did not seek informed consent from participants. No personally identifiable data was available or accessed and the study posed no potential risks to individuals or individual privacy.

Travel

For participants travelling from countries different from the summer school venue we calculated individual participant’s return flight journey distances in kilometres (kms), between their nearest home country international airport and airports nearest to each summer school venue, using A to B figures given by the Great Circle Map https://www.greatcirclemap.com/. We used www.skyscanner.net to identify available direct economy class return flights between the nearest international airport to the participant’s home base and an airport near to the venue served by flights from their home. Where a direct flight was not available, we identified flights with connections during one day of travel. For participants from the same country as the summer school venue we made the assumption that they would travel by rail, and calculated those individuals’ return rail travel in kms from their home base to the venue using Google http://maps.google.com road map distances as a proxy for rail distances, since actual rail distances are not readily available. So as to not artificially inflate the carbon costs, we departed from our core assumption in a very few instances based on local knowledge, for example: where the home base of participants (e.g., Maastricht in The Netherlands) was so close to the venue (Ghent, Belgium) that no one would expect such a participant to choose air travel over rail; people from Lund and Malmo in southern Sweden will cross an international border to take a flight from Copenhagen not a Swedish airport due to Copenhagen airport’s close proximity to that area of Sweden. For participants taking flights, we also calculated individual’s return rail travel in kms from their home base and their departure airport, and their return rail journeys from the airport nearest the destination to the summer school venue using the same method. Where there were no trains available for these journeys, we calculated kms using coach travel.

GHG emissions: travel

We calculated the GHG emissions of all travel in kg CO2e using the UK Government GHG Conversion Factors for Company Reporting 2022⁴² https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2022, multiplying the published conversion factors in this tool by the number of kms for each individual’s journey. For flights we used the per person per km short haul economy conversion figures (0.15102 kg CO2e per km); for rail the national rail conversions (0.03549 kg CO2e per km) and for coach 0.02733kg CO2e per km.

GHG emissions: venues

We used published data on the environmental impact of services provided by the summer school venue, including hotel rooms at a bed and breakfast rate, lunchtime meals and several social events. We excluded evening meal consumption because these were not provided by the site, would have been incurred by participants at home and would have varied greatly according to individual participant preferences and budgets. For hotel and meeting rooms, we used a web-based tool that uses data from the Cornell Hotel Sustainability Benchmarking index (https://www.hotelfootprints.org). For all meals we calculated the GHG emissions based on the region of Europe where the summer school was held⁴³. We used data on population dietary preference averages^43,44 and assumed 10% of the sample would choose a vegetarian option with an average consumption of 700kcal per person for lunches and socials, and 1200kcal per person for the gala dinner. Finally, we calculated individual computing GHG emissions for students and faculty at eight hours per day at 0.48 kg CO2e per day (assuming 175 kg CO2e per year) plus wireless internet provision at 0.10 kg CO2e, multiplied by the number of event days attended per individual⁴⁵.

Financial costs

As historical cost data were not available for travel, for all travel modes we used 2023 costs in Euros for a predicted event in 2023 on dates similar to the events in question. Using the flight data identified for the calculation of kms above, we used www.skyscanner.net to select economy class return fares for the flight or flights selected. For rail and coach travel, we consulted the national rail companies’ web pages for prices of current second class return fares. For hotel costs we were able to use the actual venue costs incurred. We multiplied the hotel costs by the number of days each student and faculty staff member spent at the summer school.

Analysis

For travel, we calculated total event and mean per person kms travelled, kg CO2e, and financial costs with standard deviations (SD) from the individual per person data. We summed the travel distances, GHG emissions and financial costs for each individual participant to calculate the total travel distances, kg CO2e and financial data by mode of travel per event. We included on-site kg CO2e data for each participant and similarly amalgamated these data. Finally, we combined all kg CO2e data to produce an overall estimate of the GHGs of each event and the contribution of each aspect of the event (travel, travel mode, onsite impact) to the overall emissions and financial figures.

In Ghent 2017, 122 participants attended for between three to 12 days each. According to our assumptions above, 111 (90.1%) would have used air travel for some of their journey (Table 1). Similarly, in Lisbon 2018 there were 137 participants of whom 130 (94.9%) would have flown. The average return distance travelled by air for participants to Ghent was 1,565.85km, (SD 1,087.37) and by total rail journeys 347.34km (235.75). Corresponding figures for Lisbon were 3,904.88km, (SD 1,693.27) for flights and 117.79km (159.31) for rail.

Insert Table 1 somewhere near here

The mean per participant GHG emissions for travel were 248.80 kg CO2e (SD 166.16) for Ghent and 593.90 (255.62) for Lisbon, (Table 2) to which air travel contributed the greater proportion compared to rail (95.05% for Ghent and 99.30% for Lisbon). Average on site GHG emissions were 85.34 kg CO2e (SD 39.49) per participant for Ghent and 129.80 (64.69) for Lisbon. On site emissions contributed 25.55% of the GHG costs in Ghent and, although higher in Lisbon, only 17.94% of the total GHG emissions due to the overall GHG emissions being inflated by higher emissions from travel. In total the GHG emission cost of the Ghent event was 40.77 tonnes CO2e and Lisbon 99.15 tonnes at an average per participant of 334.14 (SD 173.34) kg CO2e for Ghent and 723.70 (262.49) for Lisbon.

Insert Table 2 somewhere near here

Financial cost: the total cost of travel and accommodation combined for the Ghent event was a mean of €825.01 (SD 303.08) and for Lisbon €761.07 (286.14) (Table 3). Flight costs to Lisbon were higher than Ghent, but were outweighed by higher hotel and rail costs to the Ghent venue.

Insert Table 3 somewhere near here

We found that the total GHG emission cost of annual academic summer schools for European PhD students varied between 41 tonnes and 99 tonnes, representing a per participant mean of between 0.334, (SD 0.173) and 0.724, (SD 0.263) tonnes CO₂e per event. The main driver of these emissions and their variation was the distance travelled from participants’ home base to the venue location. On average, participants had to travel around 2.5 times further to the venue on the periphery of Europe compared to the one situated more centrally. Given the time involved in using ground-based travel options, a mean distance of almost 4,000 kms would require most participants to choose air travel, at a GHG emission rate 4.3 times that of rail. Although making a much smaller contribution overall, the geographically peripheral location was in a part of Europe where the venue GHG emissions were also higher, which increased the difference between event emissions.

Financial costs were quite similar between the events. Although flight costs were more for Lisbon, Ghent had higher costs due to the price of hotels chosen by the event organisers and higher airport to venue rail costs. Whereas Lisbon has its own airport linked by efficient urban transfer systems, Ghent requires additional train travel from the nearest two airports to hotels. Nonetheless, the difference was only around €60 per person on average out of a mean total of between €761-€825 per event.

To put the GHG emissions into perspective, for these events the daily GHG footprint per person per day of attendance was 0.04 (Ghent) and 0.11 (Lisbon). In 2021 the European Union annual per-capita GHG emission footprint was 7.7 tonnes or 0.02 tonnes per day¹². Therefore, every person attending would have a GHG emission footprint of two to 5.5 times higher than the daily average for 2021. Compared to the European Commission’s 2030 target of 2.3 tons of CO2 per person per year¹¹, these figures are between 5.7 to 16 times higher per person per day. Or to put it another way, in total these events generated the equivalent of between 5.5 and 13.5 European citizens’ annual 2021 GHG emissions, and between 16 and 40 citizen’s annual emissions against the 2030 target.

Looking ahead to 2030 and beyond, rapid European renewable and efficiency energy investment to meet the EU 2030 GHG reduction targets¹¹ will significantly reduce on-site scope 2 emissions from power usage (at least 30% according to some estimates) ⁴⁶. However, even if sites could be classed as ‘carbon-neutral’, the contribution of on-site emissions to the overall GHG emissions profile of the academic events analysed here is at most 26%. Therefore, such changes, albeit very welcome, will still leave 75% or more of GHG emissions present, reinforcing the overwhelmingly dominant contribution of aviation GHG emissions to the overall GHG emissions profile. Given the lack of decarbonising options for aviation, reducing kilometres travelled by flying will be the most effective strategy to reduce future academic event GHG emissions.

Implications: the behaviour change model

The results of our analysis show that for individual academic face-to-face conference participants to make less-polluting choices, event organisers must provide them with the structural opportunity to do so. Here, opportunity is defined as “all the factors that lie outside the individual that make the behaviour possible or prompt it.” (p4). For face-to-face scientific events, venue location and sustainable on-site components are the ‘Opportunity’ element of the COM-B behaviour change model²¹.

If totally virtual events will not deliver against the event objectives, organisers must do all they can to facilitate participants who attend face-to-face events reduce their GHG emissions, mainly through transportation mode-shifting. Our findings demonstrate that to reduce GHG emissions from face-to-face events, event organisers must first choose venues that are as close to the home base of as many participants as possible in order to provide them with the opportunity to reduce their overall GHG travel emissions. Organisers must also find places where there are rich alternative ground-based transport options such as high-speed electrified train lines and good onward connections. In terms of venue characteristics, progress on renewable energy investment to meet the EU 2030 GHG reduction targets¹¹ is not equally distributed across different countries⁴⁷ and, notwithstanding the dominant contribution of aviation to overall event GHG emissions, choosing countries that have a greater proportion of renewable energy production compared to fossil fuels as event hosts will reduce the contribution of sites to future event GHG profiles. Choosing accommodation with superior energy efficiency performance that sources energy from renewables will also reduce event GHG emissions, as will food choices by organisers given that, for example, plant-based nutrition including seasonal and field grown vegetables is associated with significantly lower GHG emissions compared with meat and dairy products⁴⁸. As part of the application process organisers may contract with ethical and explicitly sustainable travel agencies that provide bookings for travel and accommodation with lower GHG emissions characteristics.

Opportunity, however, is insufficient. Even with these structural opportunities being present, the majority of participants will of necessity and habit likely default to current standard travel, hotel and dietary choices with a significant GHG emissions profile³⁰. Two other factors are necessary to change individual behaviour: capability and motivation. Unless participants’ capabilities and motivation to make more environmentally sustainable choices are enhanced, it is likely that many will not do so.

Capability is defined as “the individual's psychological and physical capacity to engage in the activity concerned. It includes having the necessary knowledge and skills.” ²¹ (p4). Notwithstanding the need to ensure that events are accessible to all, we would assume that the majority of participants will most likely have the physical capability to undertake a less GHG emitting ground-based journey. However, even if theoretically willing to do²⁹, they may not have some psychological capabilities, particularly in terms of knowledge about scheduling, routes and connections. Exactly how to make lower emissions choices may be a barrier to behaviour change given that it is much more difficult to put together a rail or other ground-based journey across international borders than to book a flight. Individual train company websites may not link connecting trains, and routes may appear opaque. In order to address this knowledge deficit, organisers can remedy knowledge gaps by providing resources to participants during the application process. A number of websites exist (e.g., www.seat61.com) that provide extremely detailed guidance on train-based travel. These can be made available for participants to use when planning their journeys, addressing the psychological capability deficit.

The final element of the COM-B behaviour change model is motivation, defined as “all those brain processes that energize and direct behaviour, not just goals and conscious decision-making. It includes habitual processes, emotional responding, as well as analytical decision-making.” ²¹ (p4). Flying to academic meetings might be classified as a habitual process, which despite opportunity and capability elements will not change unless people are motivated to do so^29–31.

As well as facilitatory factual information to increase capability, organisers can provide participants with morally based impact-orientated information. Indeed, providing data on the environmental impact of aviation has been shown to increase behavioural intentions to reduce air travel³⁰. Direct feedback on the GHG emissions consequences of different travel choices can act as an emotional and persuasive reinforcer of different actions, a strategy that has been incorporated into policy at Griffith University, Australia after a study showed that academics were supportive of such a strategy⁴⁹. Such emotional information can motivate participants to engage with the factual information provided in the capability component of our behaviour change model and from the element of opportunity to behave more sustainably.

Equally, explicit emission information on the accommodation and food choices provided by organisers can sensitise participants to more environmentally sustainable behaviours specific to the event and in general, as can a published environmental sustainability policy that accompanies application forms. Once again, event organisers can embed this information into the application process so that participants are able to compare and contrast the results of their individual travel, accommodation and food choices. Tools are available online, for example https://travel-footprint-calculator.irap.omp.eu/home.html⁵⁰; https://travelandclimate.org/⁵¹ that allow individuals to compare and contrast different choices and the impact these have on GHG emissions.

One significant barrier to individuals making more sustainable ground-based travel choices is cost. Budget airlines often outcompete rail companies on price. Even if academics are willing to spend longer travelling by ground-based modes, they are less willing to pay more to do so^29,30, particularly if they are not recompensed accordingly by their employer, or indeed if employers insist that individuals take the cheaper option. Financial incentives apply across both capability and motivation behaviour change domains. Event organisers can use financial incentives as a powerful behaviour change strategy by making ground-based travel modes more financially attractive and by ensuring that participants are not out of pocket. Reduced registration fees or direct subsidies for participants travelling more sustainably can act as a motivator, but can also strengthen capability to make such choices for early career academics on limited budgets.

We provide a model in table form (Table 4) and as a diagram (Fig. 1) to demonstrate that a combination of opportunity, capability and motivational strategies can be put together to help scientific and academic events reduce their GHG emissions profile for face-to-face events. We also provide the EANS sustainability policy as a supplementary file (S1 EANS Sustainability Policy). Our paper here is unique as, unlike other published reviews that have collated and then listed ideas²⁵, we have placed these strategies in a coherent and widely utilised behaviour change framework that emphasises both structural change from organisations and individuals’ personal agency. We have categorised these levers and triggers using the intervention definitions from the COM-B behaviour change framework²¹. Interventions include environmental change, enablement, education, incentivisation and persuasion. The combination of strategies will be key. No one single action by organisers and/or participants will be sufficient in of itself. In our figure, darker colour denotes interventions by organisers only; lighter colour for both organisers and event participants.

Insert Table 4 somewhere near here

Finally, we must acknowledge that interventions to reduce GHG emissions by scientific organisations and individual academics attending events organised by such societies exist in a context⁵² dominated by an academic culture of collaboration and internationalisation. Universities and research centres are central stakeholders¹³ whose actions will determine individual behaviour. Universally, promotion and renumeration criteria set by universities include international collaboration, particularly for those wanting to progress to the professoriate⁵³. As noted earlier, academics hold entrenched beliefs that face to face networking^29–31 is the best way to foster these international collaborations necessary for their careers and are, therefore, incentivised to attend and organise global meetings and conferences to progress in their careers. As institutions of education and research, universities are increasingly being called to act as 'key catalysts' in driving shifts toward environmental sustainability through advocacy and activism¹⁶. One of these catalytic actions should be to adopt human resource policies that incentivise, rather than penalise, academics who choose carbon friendly strategies such as restricting their international travel or taking long and expensive ground-based journeys to international events.

Therefore, whilst the strategies we outline are not all-inclusive, our model does provide an exemplar for other organisations to add to and amend. We have not detailed sustainable changes already made by EANS by hybridising structural teaching resource allocations for the summer schools, for example, by reducing the number of faculty attending events in-person. The strength of our model is the combination of structural and individual factors, operating via organisations’ actions and individual actors’ agency. Our framework is specifically designed around ways in which organising societies can enable, and participants make, sustainable personal choices to help reduce GHG emissions from academic meetings. We now intend to test this framework during 2024 and 2025 to determine how successful it is in driving down GHG emissions from EANS summer school events. We would also like to invite other organisations test the framework in reducing the GHG emissions from their own conferences, meetings and events.

Strengths and limitations

One strength of our study is that we have used real data on participant departure cities and event venues, including fine grained analysis of rail routes, not just point-to-point distances as some GHG emissions calculators tend to do. Secondly, we have also directly compared two very disparate venues using this detailed data, rather than modelling ‘what ifs’, allowing us to directly quantify the contribution of two sites’ location on emissions for both travel and on-site contributions.

One limitation was our inability to include journey distances from participants’ home to the nearest airport or train station as we did not have data on participant home addresses. However, this is likely to be only a small additional contributor to the overall GHG emissions picture, and an effect that is equally spread across both events, so is unlikely to alter our main findings.

Equally, our travel mode assumptions may not have been valid for everyone – some participants may have travelled by train or bus from other countries, especially to Ghent. However, even if we have overestimated the flight GHG emissions for Ghent, our conservative analytical position will have reduced the actual difference between the events, and the GHG emissions from Ghent may actually have been lower still. Taking this conservative analytical position strengthens our main finding, that it is distance travelled by participants that drives GHG emissions.

The final and most obvious limitation is that we have only analysed the GHG contribution of European events attended solely by European academics. Intercontinental travel would hugely increase GHG emissions. The impact of significant numbers of participants travelling from outside Europe would probably wipe out the differential between the two sites. Europe is also well provided for with ground-based transport, a situation not enjoyed by other parts of the world, again limiting travel choices for participants in other settings. Nonetheless, the elements that drive GHG emissions for academic events remain pertinent wherever they might be situated, particularly for intra-continental or intra-regional travel.

Academic societies organising conferences to deliver their social, cultural and educational goals can find themselves in conflict with sustainable environmental objectives, as their activities generate excess GHG emissions. Our analysis of two such events demonstrates that venue location is the main driver of such emissions. Venues closer to the centre of the potential participant catchment area will incur far fewer overall GHG emissions than those where participants must travel further, as will venues that have a good non-aviation travel infrastructure and sustainable energy, accommodation and food policies. Individual participants attending such events retain considerable personal agency, and so building their capabilities and enhancing motivation must go arm in arm with organisations setting the context for behaviour change. If such societies continue to organise face-to-face events, persuading academic participants to make less polluting behavioural choices requires action by the societies to increase participants’ opportunity, improve their capability and enhance motivation, all within the academic cultural context set by the university sector. Societies must use a mix of strategies, including environmental change, enablement, education, incentivisation and persuasion to drive down the GHG emissions profile of their events. The ‘COM-B’ behavioural change framework gives such societies a formal structure on which to base their actions and reduce their GHG emissions. We present this model and an example strategy document to the academic community as a service to help others reduce the GHQ emissions caused by academic societies delivering their social and educational objectives through conferences and meetings.

Author Contributions

DAR and MD were responsible for the conception and design of the study, data acquisition, data analysis and interpretation, drafting and revising the article. FB, BCF, JG, LH, EM, RM, DPdG, MS, VSV, LMT-S were responsible for data analysis and revising the article. All authors approved the submitted version and agree to be personally accountable for its content.

Acknowledgements

We would like to thank the Board of EANS for giving us access to the anonymised dataset used in this study, and thank Professor Jamie Shutler, from the University of Exeter’s Centre for Geography and Environmental Science for helpful comments on a previous draft of this manuscript. The study received no funding.

Competing Interests

All authors declare no financial or non-financial competing interests.

Data Availability

The datasets generated and analysed during the current study are available in the Western Norway University of Applied Sciences open data repository, https://dataverse.no/dataverse/hvl, https://doi.org/10.18710/M2RTDJ.

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Balancing environmental sustainability with the social goals of scientific organisations: a ‘COM-B’ behaviour change strategy to reduce greenhouse gas emissions from international scientific conferences, meetings and educational events

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