An Activity-Based Framework for the Atmospheric Emission Burden of International Motorsport Events: Illustrative Application to the 2024 Shanghai Formula 1 Chinese Grand Prix
Year: 2026
Type: article
Abstract: The climate-relevant emission burden of internationally attended sporting events is rarely quantified. The data that determine it, namely where spectators come from and how they travel, are also rarely collected. We develop a transparent activity-based framework for event-scale greenhouse gas and co-pollutant inventories. The framework grades every parameter by provenance, separates person-times from unique attendees, propagates uncertainty by Monte Carlo simulation and attributes mitigation with exact Shapley values. We also list the event-specific data that an application requires. We illustrate the framework with the 2024 Shanghai Formula 1 Chinese Grand Prix (about 200,000 spectator person-times), combining official attendance data with documented assumptions. Under these assumptions, the event emitted 24,306 t CO2e (uncertainty interval 20,656–32,980 t), of which aviation contributed 78.7% and race-car fuel 0.4%. Aviation also supplied 94% of the 96.5 t of NOX; only 5–6 t of this was released in landing-and-take-off cycles. Ambitious 2030 measures cut gross emissions by 27.6–43.9%, leaving 56% of a frozen-technology baseline. The results depend on unverified spectator travel assumptions, which dominate the uncertainty. A spectator origin-and-mode survey would therefore be the most valuable addition to future event inventories.
Source: Atmosphere
Institutions: Baoshan University, Mahasarakham University
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7225663139