1. Introduction
Given the economic and cultural developments worldwide, mega sporting events have become increasingly popular. However, high-density CO2 emissions due to venue construction, venue operations, transportation, personnel accommodation, and catering during the preparation, holding, and end stages of such events generate negative impacts on the climate. In recent years, amid concerns about global warming, many countries have set targets for carbon peaking and carbon neutrality. In addition, experts and scholars have conducted a growing number of studies on quantifying greenhouse gas (GHG) emissions generated by various events.
A number of current studies have discussed the environmental impacts of various types of sporting, cultural, and commercial events. For instance, scholars have calculated the environmental impacts of event participants [
1,
2,
3], solid waste disposal at events [
4], event sites [
5], trade fairs [
6,
7], religious events [
8], event transportation [
9,
10], the location of infrastructure around events [
6,
11], and event tourism [
12]. However, studies focusing on the carbon footprints of sporting events remain underdeveloped. Although a few experts [
13,
14] have studied the GHG emissions of sporting events with different boundaries, their research lacks portions of construction or venue operation, which are considered significant [
15]. Meanwhile, no standardized and uniform carbon footprint calculation frameworks or methodologies exist.
The process of calculating the carbon footprint of mega sporting events is not consistent in terms of whether it should include various components, such as venue construction, post-event utilization, personnel transportation, and accommodation during the holding stage. Sara et al. [
6] and Gallo et al. [
7] argued that the preparation and assembly phases of events account for a larger share of emissions when quantifying their environmental impacts and cannot be ignored. Furthermore, Parkes et al. [
16] asserted that the CO
2 emissions from the post-event utilization phase are much larger than those of the event’s hosting stage. Therefore, sustainable management plans for events should focus on and incorporate the post-event utilization phase as part of their legacy. Pereira et al. [
9] concluded that transportation accounted for 61% of the overall emissions by calculating the carbon footprint of Premier League clubs. In another study, Pereira et al. [
17] found that transportation would be the largest source of CO
2 emissions by accounting for the CO
2 emissions of the 2030 FIFA World Cup, with tourism accommodation in second place.
Uniform protocols and approaches for assessing the carbon footprints of major sporting events have been established. In 2019, the Ministry of Ecology and Environment of the People’s Republic of China published the “Implementation Guidelines for the Carbon Neutrality of Large-Scale Events” (for trial implementation) to regulate the execution of carbon neutrality for major events [
18]. Although the standard provides some useful suggestions for organizers of mega sporting events, it does not provide CO
2 emission indicators. Collins et al. [
19] adopted an ecological footprint analysis and environmental input–output modeling to conduct a comprehensive quantitative environmental impact assessment of mega sporting events. However, the input–output method is commonly used for macro-level studies, such as those of countries, industries, or upstream emissions over a life cycle [
20,
21]. In addition, it is not applicable to the calculation of the micro-scale carbon footprints of individual mega sporting events. A number of research works [
6,
22] adopted the process-based life-cycle approach to calculate CO
2 emissions. This approach has the advantage of identifying the specific types of energy and materials that contribute to emissions and facilitating the development of strategies for conserving energy and lowering carbon dioxide emissions.
In examining the CO
2 emissions associated with transportation during large-scale sporting events, researchers have utilized a range of methodologies. David M. Herold et al. [
23] investigated the transportation choices of spectators at football matches in Austria to assess their carbon footprints. Data collection was conducted through online surveys and on-site questionnaires, targeting 19% of season ticket holders and home game spectators. Stavros Triantafyllidis et al. [
24] examined the traveling behaviors and carbon dioxide emissions of participants in mass sporting events held in rapidly growing cities. They collected information via questionnaires, which included participants’ postal codes, departure and return locations, and the modes of transportation used. Spinellis et al. [
25] used the shortest arc of latitude and longitude between the origin and destination as the ideal route by air when computing the carbon footprint of transport. Desiere et al. [
26] calculated the carbon footprint of academic conferences due to transportation by assuming transportation modes based on distance with a dividing line of 600 km. In addition, Dolf et al. [
15] determined travel data, such as the mode of transport, distance, and occupancy rates, for an audience through questionnaires. However, the above methods are imprecise or difficult to replicate.
Life-cycle assessment (LCA) is a globally recognized method for quantitatively assessing environmental impacts. Considering a life-cycle approach, the stages of a mega sporting event encompass the preparation, execution, and conclusion phases. In the “Carbon Footprint Methodology for the Olympic Games”, the IOC applied an LCA to calculate the GHG emissions for the Olympic Games. Ana Antunes et al. [
27] employed LCA to analyze ten demolition strategies for buildings at their end of life. The results indicated that selective demolition and on-site treatment strategies have the least environmental impact, while transportation distance significantly affects the environmental footprint. Case studies were used to validate the findings, demonstrating that optimizing demolition strategies and treatment methods can substantially reduce the environmental impact of building waste. Similarly, Murat Kucukvar et al. [
28] used LCA to analyze the stadiums of the FIFA World Cup in Qatar in 2022, focusing on the health impacts during the production, construction, operation, and end-of-life stages of container stadiums. The study compared temporary one-year operations with permanent 50-year operations, revealing that in the temporary scenario, circular design reduced the health impacts by 60%, significantly lowered material carbon footprints, and decreased dependence on imported construction materials. Lidia Piccerillo et al. [
14] also utilized LCA to assess the environmental impact of the 75th Italian National University Championships and calculated the carbon footprint of participants during the event. The findings showed that transportation contributed the most to CO
2 emissions. Neugebauer et al. [
29] used information that complied with the ISO 14040 [
30] and ISO 14044 [
31] standards and adopted the LCA approach for the first time to conduct a comprehensive evaluation of CO
2-equivalent emissions. The information came from four phases of an international conference: the preparation of the conference, conference execution, and the pre-/post-conference activities; the main influencing factors were identified, and future sustainable orientations were explored. However, few studies have applied LCA to the carbon footprints of mega sporting events for several reasons, such as the overly complex data collection and difficulty in establishing boundary conditions.
Table 1 summarizes the present research on CO
2 emissions from sporting events. While some research has partially addressed greenhouse gas (GHG) emissions for different event types, there remains a lack of comprehensive and standardized methodologies for analyzing the carbon footprints of large-scale sporting events.
The uncertainty of LCA quantification results has an important impact on the analysis of the carbon footprints of mega sporting events [
33]. During the computation procedure, a lack of data, unrepresentative data, random sampling errors, measurement errors, misclassifications, missing data, incomplete system boundary settings, different scenario settings, model assumption errors, and other factors may produce uncertainty in the results [
12]. Given that no unified standardized LCA and uncertainty analysis methods have been established, the results of GHG impacts estimated using LCA methods are only approximate values [
34]. The same research question may yield different results [
35] and may even lead to wrong decisions on environmental impacts [
36]. Therefore, it is necessary to further study the uncertainty and possible value ranges based on the results of LCAs. Given the importance of uncertainty analysis, a number of experts and scholars have examined it in recent years. Researchers have discussed the sources of uncertainty [
37], definitions [
38,
39,
40], analysis methods [
41,
42], and so on. Some scholars have carried out research on uncertainty in LCAs. For example, some researchers carried out a study on the uncertainty in the whole life cycle of roadway drainage systems [
42]. Certain scholars proposed a methodology incorporating sensitivity analyses and uncertainty analyses to address the uncertainties inherent in comparative building LCAs [
43]. In general, parameters, scenarios, and model uncertainty are three common basic sources, among which parameter uncertainty is particularly significant because of the extensive data required in the computation process [
37,
44]. The authors of [
37,
44] stated that parameter uncertainty pertains to variability in a model’s input data and the spread of outcomes resulting from its propagation within the model. Scenario uncertainty arises from variations in the settings of system boundary scopes, the values taken, etc. Model uncertainty stems from the selection of varying or imperfect parameters in the structure and model used for analysis. The most widely used uncertainty analysis methods are statistical analysis and the data quality indicator (DQI). Statistical analysis methods can produce accurate results when large sample data are available. However, the application of statistical analysis methods is constrained by the insufficient data gathered during events and the lack of a comprehensive database in China. Relying on data indicators and expert judgment, the DQI method offers a semi-quantitative solution that effectively addresses data scarcity. Moreover, it is applicable to situations in which the event or project has a fixed single scarcity of data. Experts have also used some other methods, such as sensitivity analysis [
45] and scenario analysis [
46]. Although numerous studies have been conducted on the calculation of CO
2 emissions, the investigation of associated uncertainties remains insufficient, particularly in the context of the life-cycle processes of mega sporting events [
38]. Yingjie Chen [
47] extended the traditional STIRPAT model by including seven driving factors, thereby creating a more practical approach for calculating energy consumption and CO
2 emissions in the construction of large public buildings. Ahmad Bin Thaneya [
48] developed a framework for categorizing various types of uncertainties and systematically addressed these uncertainties using scenario-aware Monte Carlo simulation (MCS). Andreia Santos [
49] proposed incorporating feature factor uncertainty into life-cycle assessments.
Assessing the impacts of carbon footprints generated by mega sporting events can contribute to the identification of important impact sources and mitigation strategies. However, the existing research on the carbon footprints of mega sporting events is still at the level of qualitative analysis, but a comprehensive quantitative model framework and methodology for uncertainty analysis is lacking. Therefore, the need for research on the analysis of the carbon footprints of mega sporting events has become urgent. This study presents the quantification and analysis of the carbon footprint and carbon removal associated with a mega sporting event in Beijing. Consequently, the current study undertook the following steps. (1) A qualifying model was built to assess the life-cycle carbon footprints of mega sporting events, including the processes of venue construction, basic operation, special operation, catering, accommodation, and transportation. This model was used to further develop a framework for approximating the carbon footprints of mega sporting events. (2) A predictive model for traffic activity was also built using the model and simulation-based methods to provide an approach to evaluating the CO2 emissions of transportation. (3) This study analyzed the parameter uncertainties of the carbon footprints of mega sporting events by using a semi-quantitative method to quantify the uncertainties due to input parameters. (4) This study contributes to the knowledge of carbon assessments by assessing the carbon footprint of a case in Beijing. Moreover, this research proposes improvements in data collection. Scenario and model uncertainties were also investigated by using scenario analysis, and mitigation strategies were proposed. This study contributes to the refinement of existing methodologies, and the findings can be transferred to future events.
5. Discussion
Through the assessment and analysis of the carbon footprint of a case, this study investigated the characteristics of mega sporting events to expand the understanding of their carbon footprints.
Through this case analysis, we hope to put forward suggestions and policies for the reduction of the emissions of mega sporting events and the improvement of data accuracy. In addition to the measures mentioned above, there are some important points that we should address here.
5.1. In the Preparation Stage
The organizer should reduce the construction of new venues. Existing venues can be used or renovated. If a mega sporting event requires a new stadium, the carbon footprint of the preparation phase will be high. Therefore, the cost and benefits should be fully considered when selecting the destination for an event. Reducing the number of new stadiums, using existing venues, or adapting to existing venues can reduce CO2 emissions. When new stadiums have to be built, measures should be taken to reduce CO2 emissions. Firstly, a low-carbon performance design should be adopted to ensure that less energy and resources are consumed in the subsequent use of the venue—for example, a reasonable building orientation design and reasonable design of the interior environment. Secondly, low-carbon building materials should be chosen to minimize CO2 emissions in the production and transportation of building materials. Thirdly, low-carbon management in construction should be strengthened. The introduction of industrialized prefabricated-assembly construction materials and the use of prefabricated concrete, staircases, floors, and other components can reduce CO2 emissions during the construction process. CO2 emissions during construction can also be reduced by saving on energy consumption, water consumption, and material consumption and using energy-saving equipment.
5.2. In the Holding Stage
This holding stage is also a phase in which energy consumption and CO2 emissions are concentrated. Therefore, low-carbon management should be carried out during the holding stage. During the holding stage, there are some measures for energy conservation and emission reduction that can be taken. (1) Clean energy, such as green electricity and solar energy, should be adopted. (2) The catering industry should promote vegetarian food, reduce the packaging of consumables, and give priority to local suppliers. (3) Vehicles that run on clean energy, such as ferries, should be used within the competition area. (4) An intelligent carbon management platform should be set up to monitor, manage, and analyze real-time energy consumption and water consumption for waste classification, HVAC, lighting, sports equipment, and facilities.
5.3. In the Post-Event Stage
The post-event stage also has an impact on the carbon footprint of the event. However, it was not included in the scope of this research. Since this stage involves the demolition of temporary buildings, the reuse of venues, and other situations, the scope of carbon footprint analysis and calculation is difficult to uniformly define. There is not a widely used international method for calculating CO2 emissions in the post-event stage. In the future, it is necessary to explore relevant carbon footprint calculation methods. Considering the results of the carbon footprint analysis of the Beijing case, we suggest that reasonable post-event usage plans be set up. (1) The event venue can be developed into a place for promoting sports knowledge for the public and providing high-quality sports infrastructure and services. (2) The advantages of the venue can be used, full-season operation modes can be explored, and sporting events and mass entertainment events can be undertaken in various seasons. (3) Cultural heritage can be developed, distinctive cultural brands can be built, full use can be made of explicit and implicit cultural heritage, sports and culture tourism can be planned, the characteristic regional culture can be publicized, and the economic development of surrounding shops can be promoted.
5.4. The Assumptions and Limitations of the Model
The CO2 emission data from the end stage of mega sporting events depends on the usage of venues after the events. Therefore, when analyzing the Beijing case, referring to the data from the AIJ-LCA, the demolition phase accounted for about 10% of the new construction process. This calculation method was not precise enough.
The COVID-19 pandemic protection policy only permitted locals from Beijing to attend the events, thereby limiting the estimation of CO2 emissions within the host city. Due to the lack of detailed information, we assumed that there was only one supply distribution center in the host city for the estimation of supply transportation, which may have caused bias in the estimation of CO2 emissions resulting from supply transportation.
6. Conclusions and Future Work
(1) A quantitative model for assessing the carbon footprint over the entire life cycle of a mega sporting event was built in this study. The model was shown to ensure the accuracy of calculations through an uncertainty analysis, thus improving the precision of carbon footprint research for mega sporting events. This laid the foundation for quantitative low-carbon evaluations of mega sporting events.
(2) This work also proposed a method for quantifying CO2 emissions from transportation for people and logistics, particularly by obtaining traffic volumes. The estimation was evaluated using model-based and simulation-based methods, including a VISSIM simulation, a support vector, a regression (SVR) model, and an XGBoost model. The proposed method is an optimal solution to the difficulty of collecting and quantifying traffic volumes.
(3) The case study indicated that the preparation stage of a mega sporting event accounts for the highest CO2 emissions at 92.1%, followed by 7.5% in the holding stage and 0.4% in the end stage. The total life-cycle CO2 emissions of a sustainable scenario of the mega sporting event in Beijing were 205,080.3 t CO2e, and the per capita CO2 emissions during the event’s holding stage amounted to 0.26 t CO2e/person.
(4) This study adopted a combination of data quality evaluations and Monte Carlo simulations to collect and compare data on typical carbon footprint emission processes and to determine the uncertainty of various data and results. Using scenario analysis, the impacts of system boundaries, parameter selections, probability distribution forms, and temporal correlations on carbon footprint were investigated. Based on an uncertainty analysis of 10,000 sets of Monte Carlo simulation data using this model, it was concluded that the uncertainty caused by the uncertainty in the input parameters was 0.0617, indicating that the uncertainty of the model was low, and the reliability of the results was high.
The quantitative low-carbon evaluation of large-scale sporting events is an important direction for future work. On the one hand, due to the complexity of large-scale sporting events, the principles for each stage are not unified. On the other hand, further improvement is needed to quantitatively calculate the carbon footprints of mega sporting events using the model proposed in this study.