World Triathlon has a number of sustainability pledges and is currently part of two international initiatives. These are the Support for Climate Action Framework (UNCCC/IOC) and Clean Seas (UNEP/IOC).
Under the Support for Climate Action Framework, signatories are requested to commit to achieving the specific climate goals of halving emissions by 2030 and aiming to achieve net-zero by 2040. These are referred to as the “Action Targets” of the Framework.
Further along in the Framework, World Triathlon has committed to the following “Action Objectives”:
- Achieving a clear trajectory for the global sports community to combat climate change, through commitments and partnerships according to verified standards, including measuring, reducing, and reporting greenhouse gas emissions, in line with the well below 2 degree scenario enshrined in the Paris Agreement;
- Using sports as a unifying tool to federate and create solidarity among global citizens for climate action.
You can read more about the five principles of the Framework here.
Under the Clean Seas initiative, signatories are to work with event organisers to combat marine plastic pollution.
In light of these environmental pledges, there is one obvious area to consider when it comes to the carbon footprint of elite triathlon: travel.
By nature, elite triathlon is an intercontinental enterprise with races taking place around the world and athletes travelling across countries and continents to race in them. That entails an awful lot of flying.
On both the WTCS and World Cup levels, athletes have to travel around the world. In 2022, for example, the WTCS took place in Leeds, then traversed the Atlantic to Montreal, then flew back to Europe for Hamburg. Maybe it would have made a little more sense to do the European races in one block before moving on.
To cluster more races into regional groups is already a practice for some World Cup races. It is common for the Tongyeong World Cup in October to be clustered with another race in the region. In 2021 that was with the Haeundae World Cup whereas in 2022 it was with the Miyazaki World Cup.
Clustering races, though, does not solve the problem alone.
The Travelling Salesman Problem
The Travelling Salesman Problem essentially starts from a simple premise: a travelling salesman has to visit multiple cities to sell his/her goods. To do this, they want to find the most efficient way of going from city to city.
This is actually a relevant part of AI (artificial intelligence) research. One way of approaching the problem from that front would be to use a Constraint Solver. Essentially, one could input the constraints of the different locations and run the solver to produce the most efficient route.
To a degree, the same concept applies to triathlon.
Every city that hosts a WTCS or World Cup has paid for the privilege and we cannot say who should or should not be able to host a race. So assuming all the races stay the same, a constraint solver could be used to tackle the issue of optimising the World Triathlon calendar.
The “Travelling Triathlete Problem”
Before AI scholars start renaming the Travelling Salesman Problem the Travelling Triathlete Problem, there are a few points to note. Triathletes have a rather pesky habit of wanting to go home between races, to see friends and family, to return home to familiar comforts. Selfish, right.
They also have the added issue of not racing every single event on the calendar. By contrast, in Formula 1, every team races every event, so it is easier to identify when the travel is inefficient. In the future, F1 will seek to group races together regionally in order to reduce its carbon footprint.
As we do not know exactly how athletes would want to travel between races to go home or on holiday or when they would race, it is much harder to fully solve the Travelling Triathlete Problem using relevant AI methods. (Although it is definitely possible to improve the calendar with such approaches).
All things considered, then, if World Triathlon wants to improve its carbon footprints and meet its obligations under the Common Action Framework, travel would be a good place to start. World Triathlon travel can absolutely be optimised, starting with clustering.
And then, later down the line, if the athletes would be so kind as to only travel to and from races like robots, World Triathlon travel could be entirely solved using a constraint solver.
