Mega-Events, Air Pollution and Health Outcomes: A Systematic Review

Abstract

Air pollution represents a public health threat; it is co-responsible for millions of premature deaths annually and economic losses. Mega-events create abrupt changes in air pollution providing quasi-experimental settings to investigate related health impacts. This systematic review synthesizes the evidence on air pollution level changes during mega-events and associated short-term health effects, including mortality, hospitalizations and early biological responses. A literature search was conducted in PubMed, Embase, Scopus and Web of Science up to 7 April 2025. Study quality was evaluated using the EPHPP Quality Assessment Tool for Quantitative Studies. Thirty-one studies met the inclusion criteria. Mega-events without effective air pollution control measures were associated with increased pollutant levels and higher risks of respiratory and cardiovascular morbidity. Biomarker studies demonstrated rapid and reversible changes in oxidative stress and inflammatory biomarkers in response to short-term variations in air pollution. Instead, significant reductions in air pollution during mega-events were observed upon emission control measures. The evidence is predominantly from Asian countries, no Europe/Africa studies and only one from North America, limiting generalizability. Findings indicate that mega-events may influence air quality which affects human health, reinforcing the value of temporary emission control measures strategies for future mega-events. The systematic review was registered with Prospero (CRD420251032553).

1. Introduction

Air pollution is one of the most serious environmental health concerns worldwide, particularly in urban and densely populated areas where it causes strong negative impacts on public health [1]. When present in the atmosphere at high concentrations, air pollutants can have harmful effects on human health. The most common ones are ozone (O₃), fine particulate matter (PM_2.5, particulate matter with an aerodynamic diameter of 2.5 µm or less), sulphur dioxide (SO₂) and nitrogen oxides (NOx) which originate mainly from traffic, industrial activities and energy production [2]. According to the World Health Organization (WHO) [3], the main pathway of exposure to air pollution is through the respiratory tract. Breathing in these pollutants, leads to inflammation and oxidative stress throughout the body, primarily impacting the lungs, heart and brain and ultimately increasing the risk of all-cause mortality, as well as several respiratory and cardiovascular diseases [4,5]. Consistent epidemiological evidence has linked exposure to ambient air pollution with elevated rates of chronic obstructive pulmonary disease, asthma exacerbations, ischemic heart disease, stroke and heart failure, underscoring its central role in both respiratory and cardiovascular morbidity and mortality [6,7].

The health effects of air pollution depend on both the intensity and duration. Long-term exposure has been linked to chronic heart and lung diseases, metabolic disturbances and sustained oxidative stress. [8] While short-term exposure to pollutants such as PM_2.5, O₃ and NO₂ (Nitrogen dioxide) has been linked to higher rates of all-cause mortality and acute cardiorespiratory events [9]. From a mechanistic perspective, systemic inflammation and oxidative stress are key biological pathways behind both acute and chronic effects. Inhaled pollutants generate reactive oxygen species (ROS) directly or through activation of pulmonary immune cells, causing local airway inflammation and systemic inflammatory signal [10]. Biomarkers such as chemokines, exhaled nitric oxide (FeNo), nitrate/nitrite, 8-hydroxy-2′-deoxyguanosine (8-OHdG), and 8-isoprostane reflect these responses [11]. Chronic activation of inflammatory pathways can lead to tissue damage and disease progression [12], while excess ROS disrupts redox-sensitive signaling cascades, including the Nuclear factor erythroid 2-related factor 2/Antioxidant Response Element (Nrf2/ARE) pathway which regulates cellular defense mechanisms [13]. Early changes in inflammatory cytokines, oxidative stress biomarkers, endothelial function, heart rate and blood pressure can appear soon after exposure and preceding clinical events, providing a biologically plausible link between short-term exposure and acute health outcomes [14,15].

Mega-events represent a distinct and underexplored source of short-term changes in urban air pollution. Mega-events have been defined as “one-off events of a fixed duration that attract a large number of visitors, have a large mediated reach, come with large costs, and have large social and environmental impacts” [16]. Examples include international sporting competitions, political summits and large traditional festivals. Such events are characterized by abrupt changes in population density, mobility patterns, energy demand and construction activity [17]. As a result, they can substantially alter emission profiles over short periods, either worsening air quality through increased traffic and infrastructure-related emissions or improving it through temporary control measures designed to limit environmental and health impacts [18]. For instance, Chen et al. (2013) [19] used the 2008 Beijing Olympic Games to study the effect of strict temporary pollution controls and showed that these measures improved the Air Pollution Index during and shortly after the event, although most benefits had disappeared by October 2009. Overall, mega-events provide a unique opportunity to study short-term changes in air pollution and their immediate health consequences.

Despite a growing number of studies using mega-events as natural experiments in environmental and health research, the evidence remains fragmented across disciplines, pollutants, health outcomes and study designs. [18,20] In particular, there has been limited synthesis of studies simultaneously examining changes in air pollution and corresponding short-term health outcomes before, during and after mega-events. Addressing this gap is thus crucial to understand whether and under which conditions, mega-events can amplify or mitigate acute health risks through air pollution pathways. Prior systematic reviews have predominantly focused on the long-term health impacts of long-term exposure to air pollution [21,22]. For example, Boogaard et al. (2022) [23] reported moderate to high evidence that long-term exposure is associated with increased all-cause, cardiovascular, ischemic heart disease and lung cancer mortality, as well as incident asthma and acute lower respiratory infections. Overall, the review reinforces evidence linking long-term air pollution exposure to multiple adverse health outcomes. Similarly, Yazdi et al. (2022) [24] found that long-term exposure to air pollutants, particularly PM_2.5 and O₃ is associated with increased cardiovascular and respiratory hospital admissions among older adults, while NO₂ show more mixed results. Likewise, Al Ahad et al. (2024) [25] observed that long-term exposure to ambient air pollution is associated with higher all-cause and cause-specific hospitalizations, including respiratory, cardiovascular, infectious and mental health conditions, with stronger effects for cumulative exposure over time. These reviews emphasize the substantial burden of long-term exposure and suggest that sustained air quality improvements can reduce healthcare use.

Short-term studies have also shown that temporary increases in pollution can trigger acute health issues as well. Liu et al. (2022) [9] reported that short-term increases in PM_2.5 and to a lesser extent, NO₂ and O₃ are associated with higher all-cause mortality in the United States, with detectable effects even at concentrations below current air quality guidelines. Rakshit et al. (2025) [26] in a systematic review of short- and long-term health effects of high Air Quality Index (AQI) exposure, summarized evidence that short-term increases in air pollution are linked to acute respiratory and other multisystem morbidities. Seihei et al. (2024) [27] highlighted that Andimeshk city experiences very high particulate matter levels, with PM where particles are less than 10 micrometres in diameter (PM₁₀) often exceeding legal limits due to dust storms and regional dust transport, thereby exposing the population to substantial short-term health risks. In line with these findings, Zhang et al. (2025) [28] reported that short-term exposure to PM_2.5, PM₁₀, SO₂, NO₂ and Carbon Monoxide (CO) during peak traffic hours is associated with increased hospitalizations for respiratory diseases, with particularly pronounced effects among children and older adults. However, only a small part of this literature has examined the acute health effects of short-term air pollution exposure during mega-events, where pollution levels may vary significantly due to traffic limitations, construction activities or temporary emission control policies.

Therefore, this study aims to systematically review the evidence on the effects of mega-events on air pollution and related health outcomes. Specifically, it examines changes in air pollutant concentrations and health indicators including hospitalizations, mortality and biological markers before, during and after mega-events, and compares these effects across different event types and contexts. By focusing on acute exposure windows, this review seeks to clarify the immediate health implications of mega-event-related air pollution and to inform future public health and urban planning strategies.

2. Materials and Methods

The present systematic review protocol is registered on PROSPERO database, last check made on 14 April 2025 and publish on the 9 April 2026, ID: CRD420251032553 Available from: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251032553 (accessed on 9 April 2026). And the systematic review is reported following the PRISMA 2020 statement guidelines.

2.1. Study Selection

Eligible articles were searched and identified in PubMed, Embase, Scopus and Web of Science (WoS) up to 7 April 2025. The search string aimed to identify original research articles assessing the impact of air pollution associated with mega-events on human health outcomes including the following terms: ‘Air Pollution’, ‘Air Pollutants’, ‘mega-events’, ‘Olympics’, ‘Festivals’, ‘Health’, ‘Respiratory Diseases’, ‘Cardiorespiratory Diseases’, ‘Hospitalisations’, ‘Mortality’. Full strings are reported in Appendix A.

2.2. Inclusion and Exclusion Criteria

Original observational or interventional studies conducted in urban or suburban areas during mega-events (sports, cultural, festival or political gatherings) assessing air pollution levels (e.g., PM_2.5, NO₂, O₃, CO, etc.) and their effects on human health outcomes were considered potentially eligible. The populations under investigation include general or specific subgroups, with outcomes such as respiratory, cardiovascular, mortality, hospitalization or early biological responses such as oxidative stress and inflammation. Comparative studies evaluating exposure before, during and after the events were also included. On the contrary, we excluded editorials, opinion papers, conference abstracts, protocols, dissertations, reviews, meta-analyses and studies that did not measure air pollution during a mega-event or that did not assess health outcomes. Two reviewers completed the article selection in a blind process, starting from the screening of titles and abstracts according to the inclusion and exclusion criteria declared. Included resources underwent a second screening phase based on full texts evaluation using Rayyan (http://rayyan.qcri.org). Disagreements on article selection were discussed and eventually submitted to a third reviewer.

2.3. Data Extraction

Data extraction was independently performed by two researchers using structured spreadsheets. For studies on mortality and hospitalizations, we collected information on author, year, title, country, study design, population characteristics, sample size, age, sex, type and measurement of air pollution, concentrations (before, during and after the mega-event), type and year of mega-event, observation period, outcomes assessed (mortality and hospitalizations) and outcomes quantification at each time point [counts, mean ± Standard Deviation (SD), median (Interquartile Range, IQR)] or mean with 95% Confidence Intervals, CIs) along with statistical analysis details and main results. For biomarker biomonitoring studies, extraction included similar variables with additional details on biomarker type, biological matrix, unit of measure and assessment methods. Outcomes were measured before, during and after the mega-event were extracted using the same metrics. The timing of the pre-event and post-event periods was recorded as defined by each original study, because these event windows differed across studies. Because of this methodological heterogeneity, we synthesized the findings narratively rather than applying a single uniform sampling window across all studies.

2.4. Quality Assessment

The quality assessment of the included articles was performed by two independent reviewers using the Effective Public Health Practice Project (EPHPP) Quality Assessment Tool for Quantitative studies available at https://www.ephpp.ca/quality-assessment-tool-for-quantitative-studies/ (accessed on 3 February 2026). This instrument evaluates risk of bias across eight methodological categories—selection bias, study design, confounders, blinding, data collection methods, withdrawals and dropouts, intervention integrity, and analysis—by integrating objective criteria with the judgments of experts who meet predefined qualifications. An overall quality score is then calculated by summing the domain ratings, yielding a numeric value that determines the final classification: scores ≤ 5 are designated weak, scores 6–7 are moderate, and scores ≥ 8 are considered strong. This systematic approach ensures that the risk of bias is transparently assessed across all included studies and any discrepancy between reviewers was discussed, and, if required, a third reviewer was consulted.

3. Results

3.1. Qualitative Synthesis

As described in Figure 1, among the 6207 items initially identified, 2903 duplicates were removed before screening. Titles and abstracts of the remaining 3304 were screened, 58 full texts were assessed and the exclusion criteria lead to the removal of 27 articles. A number of 31 research articles were finally included in the present systematic review. Among the excluded articles, three did not involve any mega-event, three did not assess air pollution, and four did not report relevant health outcomes (e.g., mortality, hospitalization and early biological responses). Additionally, nine review papers, two articles written in languages other than English and six studies with other methodological issues were excluded. The procedure is summarized by the PRISMA diagram reported in Figure 1.

3.2. Study Setting and Mega-Events Characteristics

As shown in Table 1, a total of 31 studies were included in this review, comprising mainly observational designs. The studies were published between 2010 and 2024 with the vast majority conducted in China (n = 28), followed by India (n = 2) and the USA (n = 1). Most studies assessed the total general population during mega-events and in a subset of studies where a specific sample was reported the number of participants ranged from 11 to 788 individuals. The included studies were mainly observational and varied substantially in sample population characteristics, observation period and mega-event context, which limits the direct comparison of outcome estimates across studies, as summarized in Table 1. The mega-events were mainly sport-related with the Beijing Olympics and Paralympic games 2008 being the most frequently studied event (n = 22), followed by the Asian Games (n = 4). Other sport events included the Nanjing Youth Olympics Games 2014 (n = 1), the World Military Games 2019 (n = 1) and the Atlanta Olympics Games 1996 (n = 1). Cultural and religious festivals were also represented including Diwali, Dusshera, Deepawali and Holi festivals in India (n = 2). The observation period varied across studies, with mega-event durations ranging from 2 to 51 days and an average duration of approximately 31 days (±10.2 days).

3.3. Mega-Event-Related Air Pollution, Mortality and Hospitalization

Table 2 provides an overview of the characteristics and main findings of the studies that investigated the relationship between changes in air pollution during mega-events and mortality and hospitalization outcomes. A total of 14 studies were included [30,32,33,34,35,36,39,41,44,45,48,56,57,59], all of which measured ambient air pollutant concentrations before, during, and after the mega-event using data obtained from official environmental monitoring networks. The pollutants most frequently examined were PM_2.5, SO₂, NO₂, O₃, SO₂, NO and particle number concentration (PNC) [32,45], measured through validated monitoring instruments such as tapered element oscillating microbalance (TEOM) systems [32,45], chemiluminescence analyzer [44], fluorescence-based monitors and particle mobility spectrometers [39,57]. Health outcomes were extracted from mortality registries and hospital admission databases and mainly comprised all-cause mortality (n = 2) ([35,41]), cardiovascular and respiratory mortality (n = 5) ([33,34,45,47,56]), hospitalization (n = 4) ([32,36,39,44]), health risks (n = 2) ([30,57]) and emergency department visits (n = 1) ([59]). Most studies used time-series designs and applied statistical models such as generalized additive models (GAM), quasi-Poisson regression or linear regression, with adjustments for meteorological variables, long-term temporal trends and day-of-week effects to estimate the short-term impact of pollutant fluctuations on health outcomes. Regarding the results, as shown in Table 2, among the 14 included studies [30,32,33,34,35,36,39,41,44,45,48,56,57,59], mortality outcomes were mainly examined in relation to short-term variations in PM_2.5, PM₁₀, NO₂ and O₃ during mega-events or pollution control periods. In most studies ([34,41,45,48]), reductions in particulate matter during intervention periods were associated with decreases in all-cause, cardiovascular and respiratory mortality. He et al. (2016) [41] reported that a 10 µg/m³ decrease in PM₁₀ was associated with an 8.4–9.6% reduction in all-cause mortality and an 8.8% reduction in cardiovascular mortality. Similarly, Lin et al. (2014) [48] reported reductions in daily mortality during the Asian Games period, with all-cause mortality, Mean(SD), decreasing from 32 (7) to 25 (5) per day, cardiovascular mortality from 11 (4) to 8 (3) per day, and respiratory mortality from 6 (3) to 5 (2) per day, coinciding with lower PM₁₀ concentrations. During the Beijing Olympic and Paralympic Games, Su et al. (2015) [45] reported that reductions in air pollution, particularly in PNC, were associated with a decrease in cardiovascular mortality risk during the period of strict emission control measures. Whereas, Zhang et al. (2019) [34] reported a reduction in stroke mortality during the 2010 Guangzhou Asian Games following the implementation of an air pollution control program. Daily stroke mortality decreased during the Asian Games (−18.26%). Reductions were also observed for ischemic stroke (−12%) and hemorrhagic stroke (−25.75%). PM_2.5, SO₂, and NO₂ were positively associated with stroke mortality counts, while PM₁₀ levels significantly decreased during the Asian Games period. By contrast, studies ([33,35,56]) conducted during periods of increased air pollution reported higher risks. Wu et al. (2019) [33] reported that a 10 µg/m³ increase in NO₂ was associated with a 1.89% increase in total mortality (95% CI 1.49–2.29), while a 10 µg/m³ increase in O₃ was associated with a 0.60% increase in total mortality (95% CI: 0.47–0.74). In addition, IQR increases in O₃ were associated with higher cardiorespiratory mortality and a 4.42% increase in cardiovascular mortality (95% CI: 3.16–5.69). Zhang et al. (2011) [56] reported stronger associations between PM₁₀ and cardiovascular mortality, whereas NO₂ showed stronger effects on respiratory mortality. Sinha et al. (2019) [35] similarly observed higher excess mortality with increased PM_2.5 levels. For hospitalizations and emergency department visits, Peel et al. (2010) [59] reported 2% to 4% increases in respiratory emergency visits associated with O₃, while particulate matter and gaseous pollutants were linked to cardiovascular visits. Gupta et al. (2019) [39] observed that respiratory hospital admissions during the Holi festival were approximately twice as high as before the event and 1.3 times higher than after Holi. PM₁₀ showed a stronger impact than PM_2.5, particularly for upper respiratory admissions. Daga et al. (2019) [36] also reported increases in total, respiratory, cardiac and stroke admissions following post-Diwali rises in PM_2.5 and PM₁₀. During the Olympic emission control period, Su et al. (2016) [44] reported higher cardiovascular emergency room visits during the non-Olympic period when air pollution levels were higher, while lower pollution levels during the Olympic period were associated with reduced cardiovascular Emergency Room Visits (ERV). PM_2.5 showed adverse effects on cardiovascular ERV, with an interquartile range increase (68 µg/m³) associated with a relative risk of 1.022 (95% CI: 0.990–1.057), particularly among females, although this association did not reach statistical significance because the confidence interval crossed 1.0. Breitner et al. (2021) [32] observed lower respiratory and pneumonia mortality during the Olympic intervention period enforced under strict emission control measures, the associations were mainly observed for particle number concentrations, with an increase of 7958 particles/cm³ in ultrafine particles associated with a 16.3% increase in respiratory mortality.

As illustrated in Figure 2, mega-events can temporarily alter air pollution exposure, with emission controls generally reducing particulate pollution and associated mortality and hospitalizations outcomes, whereas the absence of emission controls is linked to increases in pollutant levels and adverse health impacts.

Overall, the mortality and hospitalization studies showed a consistent pattern in both effect size and statistical significance across event types, pollutants and outcome definitions. Studies conducted before–during–after mega-events with stricter temporary emission controls generally showed cleaner reductions in PM_2.5, PM₁₀ and NO₂ and were more often associated with lower mortality or hospitalization risks, whereas festival-related studies without emission controls more often showed the opposite pattern. These differences likely reflect how strong the pollution controls were, how much air pollution changes, who was studied and how each study was designed.

3.4. Mega-Event-Related Air Pollution and Early Biological Responses

Table 3 presents the characteristics and main findings of studies observing early biological responses to variations in air pollution during mega-events, with a specific focus on inflammatory and oxidative stress biomarkers. Across 17 studies ([31,37,38,40,42,43,46,47,49,50,51,52,53,54,55,58,60]), ambient air pollutant concentrations were measured before, during and after mega-events using standardized environmental monitoring systems, and biological samples were collected in parallel to assess short-term physiological responses to exposure changes. The pollutants most frequently monitored included PM_2.5, PM₁₀, O₃, NO₂ and particle number concentration. Biological assessments were conducted using multiple matrices, including blood ([31,37,40,42,43,47,50]), urine ([43,46,47,50,52]), saliva and exhaled breath condensate ([49,50,52,53,54]). The biomarkers investigated mainly reflected systemic inflammation, oxidative stress and autonomic or cardiovascular responses, such as C-reactive protein (CRP), interleukins (IL-6, IL-8), tumor necrosis factor (TNF-α), malondialdehyde (MDA), 8-hydroxy-2′-deoxyguanosine (8-OHdG) and heart rate variability (HRV). Most studies adopted repeated measure or panel designs and applied linear mixed models, generalized linear models or time-series analyses to estimate short-term associations between pollutant variations and biomarker fluctuations, accounting for meteorological and temporal confounders.

Regarding the results, as shown in Table 3, among the 17 studies ([31,37,38,40,42,43,46,47,49,50,51,52,53,54,55,58,60]), reductions in air pollution during intervention periods were generally associated with decreases in inflammatory, oxidative stress and cardiovascular biomarkers. For example, Li et al. (2019) [37] reported lower levels of inflammatory chemokines, including Regulated on Activation, Normal T Cell Expressed and Secreted (RANTES), Monocyte Chemotactic Protein-2 (MCP-2) and Thymus and Activation-Regulated Chemokine (TARC) during the 2008 Beijing Olympic period with the strict emission control, while increases in air pollution after the Games were associated with higher levels of these biomarkers and positive associations with IL-8, Eotaxin-1 and Growth-Regulated Oncogene Alpha (GRO-α). Similarly, Li et al. (2017) [42] reported significant changes in inflammatory biomarkers across the before, during, and after periods of the 2014 Nanjing Youth Olympic Games, including soluble CD40 ligand (sCD40L), Interleukin-1 beta (IL-1β), CRP and Vascular Cell Adhesion Molecule (VCAM-1). Higher PM_2.5 and O₃ concentrations were associated with increased serum levels of sCD40L, Intercellular Adhesion Molecule 1 (ICAM-1), VCAM-1, P-selectin and IL-1β, while reductions in PM_2.5 and O₃ were associated with decreases in inflammatory biomarkers. Taken together, these two Olympics studies show a similar short-term biological response to air pollution changes but the specific biomarkers and exposure responses patterns were not identical, suggesting that the effect depends on the event setting, pollutant mixture and biomarker type.

Similar patterns were reported for pulmonary and systemic inflammation markers. For instance, Huang et al. (2012) [54] reported that reductions in air pollution during the 2008 Beijing Olympic control period were associated with decreases in FeNO and oxidative stress biomarkers, indicating reduced pulmonary inflammation. In contrast, higher air pollution levels in the 0–48 h were associated with increases in FeNO, Exhaled Breath Condensate (EBC) nitrite and nitrate and decreases in EBC pH, while pollution exposure 48–96 h before measurement was associated with increases in EBC 8-isoprostane and markers of DNA oxidative damage. Similarly, Zhang et al. (2013) [52] reported that during the 2008 Beijing Olympic period, when air pollution decreased, inflammatory, oxidative stress and hemostasis biomarkers were reduced, accompanied by improved cardiovascular physiology. After the Olympics, when pollution levels increased again, increases were observed in pulmonary inflammation markers (FeNO, EBC nitrite, nitrate, nitrite+nitrate, pH, 8-isoprostane), systemic inflammation and oxidative stress markers (fibrinogen, von Willebrand Factor (vWF), urinary 8-OHdG), as well as hemostasis and platelet activation markers (sCD40L, sCD62P, vWF), together with increases in cardiovascular measures such as heart rate and systolic blood pressure. Lin et al. (2015) [47] reported that higher levels of Black carbon (BC), PM_2.5, SO₂, NO₂ and CO were associated with increases in malondialdehyde and 8-oxodG, while Gong et al. (2013) [53] found that reductions in air pollution during Olympic control measures were associated with decreases in EBC MDA, with levels increasing again after the controls ended. Studies examining cardiovascular and hemostasis biomarkers also reported similar patterns. Rich et al. (2012) [55] observed decreases in fibrinogen, vWF, soluble P-selectin (sCD62P), sCD40L and heart rate during the Beijing Olympic Games when particulate and gaseous pollutants decreased by 13–60%, whereas these biomarkers increased again after pollutant concentrations returned to pre-Olympic levels. In addition, changes in air pollution were associated with physiological responses, including increases in blood pressure with higher PM_2.5 exposure, in the same study during the Seventh World Military Games, no significant response was observed for Glutathione Reductase (GR) despite changes in other oxidative stress and inflammatory biomarkers [31] and altered heart rate variability in individuals exposed to high traffic-related particulate matter levels [60]. Biomarkers of exposure also responded to pollution changes, for example, Gong et al. (2015) [46] reported decreases in urinary metabolites of traffic-related pollutants during the Olympic period, followed by increases after the Games.

Figure 2 shows that emission-control periods were linked to improved early biological responses, with lower levels of inflammation, oxidative stress, respiratory and cardiovascular biomarkers, whereas these markers worsened after the controls were lifted.

Overall, Table 3 shows that short-term reductions in air pollution during mega-events were often accompanied by improvements in early biological responses, particularly inflammatory, oxidative stress, hemostatic and cardio-respiratory biomarkers. Across studies, PM_2.5 and PM₁₀ were the pollutants most frequently associated with changes in biomarkers such as CRP, IL-1β, IL-6, IL8, VCAM-1, MDA, 8-isoprostane and 8-OHdG, while traffic and combustion- related pollutants including NO₂, SO₂, BC and CO showed similar but more variable associations. Several studies also reported that biomarker levels worsened again after pollution returned to pre-event levels indicating a consistent short-term biological response to changes in air quality.

3.5. Risk of Bias Assessment

All included studies were assessed with the EPHPP Quality Assessment Tool for Quantitative Studies according to their respective designs. Overall, 77.42% of the studies were rated as ‘weak’, 22.58% were rated as ‘Moderate ‘quality and no study received a strong rating. Most of the weak ratings reflected limitations in the study design and confounding control, and because the included studies used different designs and event windows, the relation between study quality and findings was examined qualitatively rather than through a pooled statistical comparison. Data extraction was performed systematically according to predefined criteria to ensure consistency across all studies. (Supplementary Materials: Table S1).

4. Discussion

This review shows that mega-events provide a unique opportunity to observe how rapid changes in air pollution are associated with short-term changes in mortality, hospitalizations and early biological responses. Mega-events can generate abrupt and large-scale shifts in urban emissions.

Preparatory construction activities and increased mobility may temporarily worsen air quality, whereas the implementation of traffic restrictions, industrial shutdowns, and other emission control measures can substantially reduce pollutant levels over short periods [61]. Mega-events are not homogeneous and their health effects vary according to the nature of the event and the associated emission profile. Evidence from several Olympic and Asian Games interventions showed marked reductions in pollutants such as PM_2.5, PM₁₀, NO₂, SO₂ and particle number concentrations, while festivals without emission controls, such as Diwali or Holi, were associated with sharp pollution increases. Sporting events are therefore more often linked to temporary emission-control measures and pollutant reductions, whereas festivals and religious gatherings may generate pollution increases because of fireworks, biomass burning, crowding and transport-related emissions. Accordingly, the direction and magnitude of health effects may differ across event types and this should be considered in the interpretation of the evidence.

In this review, several studies reported that strict emission controls during mega-events reduced ambient concentrations of PM_2.5, PM₁₀, NO₂, SO₂ and other pollutants which were followed by decreases in all-cause, cardiovascular and respiratory mortality. [32,34,41,45,48]. These findings are biologically plausible, given that inhaled particulate matter and traffic-related gases are known to trigger pulmonary oxidative stress and inflammation that rapidly propagate systemically, promoting endothelial dysfunction, autonomic imbalance and a pro-thrombotic state that can precipitate acute cardiovascular and respiratory outcomes [62,63,64].

4.1. Early Biological Responses: Oxidative Stress and Inflammation

Across the included early biological responses study, the pattern was not identical for all pollutants. PM_2.5 and PM₁₀ were the pollutants most consistently associated with changes in inflammatory, oxidative stress, hemostatic and cardio-respiratory biomarkers, whereas NO₂, SO₂, BC and CO showed similar but more variable associations.

Experimental and clinical studies show that PM and PM_2.5 deposit deeply in the lungs, enter cells and accumulate in mitochondria, where they disrupt the electron transport chain and produce ROS, leading to oxidative stress, mitochondrial DNA damage, cytochrome-c release and apoptosis [65,66]. This oxidative stress activates redox-sensitive signaling pathways (e.g.,Mitogen-Activated Protein Kinase (MAPK), Nuclear Factor kappa-light-chain-enhancer of activated B cells (NF-kβ), Activator Protein-1 (AP-1)), which up-regulate pro-inflammatory cytokines and adhesion molecules, promoting systemic inflammation, endothelial dysfunction, vasoconstriction and platelet activation [67]. These pathways provide a mechanistic potential explanation for the increases in mortality and hospital admissions observed during periods of higher pollution reported in this review. In addition, controlled exposure studies to urban PM and diesel exhaust have shown reduced vasodilatory responses and decreased heart-rate variability, effects that are attenuated when exposure is lowered, supporting the idea that short-term reductions in pollution can rapidly reduce cardiovascular strain and acute mortality risk [63,68]. A recent multi-omics systematic review confirms that PM exposure is consistently associated with higher oxidative stress markers, altered pro-oxidant metabolites (eicosanoids, ceramides), depletion of antioxidant pathways (glutathione, vitamins C and E), and disruptions in metabolic and inflammatory processes that favor a pro-inflammatory, pro-oxidative profile, which is consistent with the biomarker increase observed in this review during emission control periods [69]. Conversely, when mega-events are associated with increased emissions (e.g., traffic congestion, fireworks, biomass burning), higher short-term concentrations of PM_2.5, PM₁₀, NO₂ and SO₂ are expected to intensify oxidative stress and systemic inflammation, which aligns with the increases in mortality, hospitalizations and biological markers reported in our results during high-exposure periods, and is consistent with epidemiological evidence showing that even modest day-to-day increases in these pollutants are linked to higher risks of myocardial infarction, stroke, heart failure and cardiorespiratory mortality, with no clear safe threshold [70]. This interpretation is further supported by previous research supporting the notion that individuals with pre-existing respiratory disease are especially vulnerable to these acute pollutant spikes. In an Italian multicenter cohort, long-term exposure to traffic-related air pollution was associated with a markedly higher prevalence of chronic obstructive pulmonary disease (COPD) and more severe disease progression [71]. Moreover, a multipollutant analysis linking long-term exposure to a mixture of PM, NO₂ and O₃ with asthma and rhinitis demonstrated that patients with allergic airway conditions had amplified inflammatory responses and poorer symptom control [72]. Together, these results indicate that people with respiratory diseases or vulnerable groups suffer from the worst effects when pollution surges during mega-events.

Toxicological and in vitro studies support the evidence that intervention reducing air pollution can result in a decrease in inflammatory, oxidative stress and cardiovascular biomarkers, with a new increase in biomarker levels when pollution return to pre-event levels. Particulate matter with high oxidative potential induces ROS generation, lipid peroxidation and oxidative DNA damage disrupts endothelial tight junctions via ROS-dependent calcium influx and calpain-mediated degradation of the junctional protein ZO-1 and up-regulates adhesion molecules such as ICAM-1 and VCAM-1, particularly for particles derived from combustion and metal-rich sources, antioxidant treatment has been shown to prevent these effects, supporting a causal role of oxidative stress pathways [73,74]. These findings are consistent with broader evidence showing that airborne particulate matter induces oxidative stress and inflammation across multiple organ systems, which are central mechanisms linking air pollution to cardiovascular and respiratory disease [75]. They also align with epidemiological and biomarker data from Italian studies on vulnerable people and air pollution. In the GEIRD multi-case–control study, Squillacioti et al. (2024) [76] found that adults with asthma, COPD and other airway diseases who were exposed to higher urban air pollution levels had significantly increased systemic oxidative-stress biomarkers compared with less exposed subjects, reinforcing the central role of redox imbalance and systemic inflammation as pathways through which air pollution can exacerbate respiratory morbidity. In parallel, Schilirò et al. (2026) [77] demonstrated that PM₁₀ from the Po Valley has high oxidative and toxic potential in vitro, reinforcing the idea that changes in particle load and composition during mega-events can rapidly modulate oxidative stress and related biomarker profiles possibly also in exposed populations, as observed in our review.

4.2. Mortality and Hospitalisations Outcomes

Across the included mortality and hospitalization studies, the pattern was not identical for all pollutants. PM₁₀ appeared more consistently associated with cardiovascular mortality, NO₂ with respiratory mortality, and O₃ with total mortality or respiratory emergency visits, whereas PM_2.5 and PM₁₀ were the pollutants most frequently linked to biomarker changes.

Studies conducted during the Beijing 2008 Olympics showed that short-term reductions in air pollution were associated with changes in EBC markers, including pH, nitric oxide, nitrite and nitrate, demonstrating that short-term variability in PM and NO₂ directly modulates airway oxidative and inflammatory responses in healthy adults [65], which is in agreement with the decreases in FeNO, EBC nitrite/nitrate and 8-isoprostane reported in the Olympic panel studies included in this review. Consistent with the mortality and hospitalization findings, a nationwide case-crossover study in 292 Chinese cities evaluating the Air Pollution Prevention and Control Action Plan (APPCAP) found that between 2013 and 2017 mean PM_2.5 and CO concentrations fell by about 29% and 20%, respectively, and these declines were accompanied by a roughly 30% decrease in cause-specific hospital admissions [78], while a quasi-experimental study of Tokyo’s diesel emission control ordinance similarly showed that, compared with Osaka, larger decreases in PM_2.5 were paralleled by greater declines in age-standardized mortality, including a 22% reduction in pulmonary disease mortality and a 4.9% reduction in lung cancer mortality over a decade, consistent with a causal benefit of targeted emission reductions on respiratory deaths [79]. Moreover, in Makkah, monthly NO₂ and O₃ levels were more strongly associated with cardiovascular and respiratory mortality during the crowded Hajj seasons than in non-Hajj periods, suggesting that pollution peaks superimposed on vulnerable populations can amplify death rates. [80] The fact that, during the COVID-19 years when pilgrim numbers and emissions were sharply reduced, most pollutant mortality associations in Makkah became inverse or non-significant (with the partial exception of SO₂) further supports the interpretation that it is the concurrence of pollution peaks with a concentrated, high-risk population that drives the excess cardiorespiratory mortality observed during Hajj [80]. In addition, toxicological studies conducted during the Nanjing Youth Olympic Games demonstrated that air-quality interventions can reduce not only pollutant concentrations but also the oxidative and cytotoxic potential of particulate matter, supporting the reductions in oxidative stress biomarkers observed in this review [81]. These lines of evidence are complemented by previous research during the Torino 2006 Winter Olympic Games, where targeted emission-control measures around the competition venues were linked to measurable reductions in ambient benzene and formaldehyde concentrations [82] and to attenuated mutagenic activity of PM_2.5 in the Po Valley [83], showing that mega-event interventions can modify both gaseous carcinogens and the genotoxic fraction of PM in a way that is consistent with the biomarker improvements observed in our review. More recently, the integration of effect-based bioassays into routine PM₁₀ monitoring in the same region [77] has shown that periods with stricter air-quality measures are characterized by a lower oxidative and mutagenic potential of particulate samples, mirroring the pattern of reduced toxicological potency and improved biomarker profiles that we report during mega-events. Taken together, the studies in Turin (2006) and later monitoring in the Po Valley both support our findings, they show that when emission controls are put in place for big events, air-pollutant levels decrease, the remaining pollutants become potentially less detrimental, and we can see real improvements in health markers and actual health outcomes.

4.3. Methodological Consideration and Excluded Studies

There were two studies, Thakur et al.(2010) and Huang et al.(2017) [84,85] that were mainly based on simulated estimations rather than directly calculated exposure response analysis. Because they did not provide clearly quantified effect variations derived from observed data, they have not been included in the present systematic review. However, is worth mentioning their contribution to the scientific literature; the direction of their findings was aligned with studies that provided measured effect estimates, supporting the overall consistency of the observed evidence. In the case of Zhu et al. (2021) [86], the biomarker findings were primarily based on correlation analyses rather than fully quantified exposure response gradients, which limits the precision of interpretation. Nevertheless, the observed direction of change remained consistent with other biomarker studies that reported quantified reductions. Additionally, a further article by Ghada et al. (2021) [87], the only European paper we found on Oktoberfest in Munich, Germany, did not report results specifically for emergency-department visits during the Oktoberfest period but only for annual data without isolating the event period, for this reason, it could not be directly integrated into our before–during–after framework. Even though their paper still adds useful background on festival-related pollution.

4.4. Strength and Limitation

This review has several strengths. First, it provides a comprehensive synthesis of studies examining the relationship between air pollution changes during mega-events and health outcomes, highlighting how temporary emission control measures can influence both clinical outcomes (mortality and hospitalizations) and early biological responses. Another strength of this review is the inclusion of studies investigating not only clinical outcomes but also biomarkers related to inflammation, oxidative stress and cardiovascular function, which helps to better understand the potential biological mechanisms linking air pollution exposure to adverse health effects. However, several limitations should also be considered when interpreting the findings. The geographical distribution of the included studies was uneven. Most of the available evidence comes from Asian countries, particularly China, where several studies were conducted during the Beijing Olympic Games [32,35,37,38,40,41,43,44,45,46,47,49,50,51,56,57,58,60,85], while others examined events, such as the Asian Games [33,34,42,48] or large-scale festivals in India [36,39]. In contrast, no eligible studies were identified from Europe or Africa and only one study was conducted in North America [59]. This pattern reflects the current evidence base rather than a restriction in our search strategy and it may limit the generalizability of the findings to other regions with different environmental conditions, pollution levels and sources and population characteristics.

4.5. Public Health Implications and Future Perspectives

The findings of this review highlight several gaps in the current literature that might be a starting point to suggest directions for public health and future research. From a public health perspective, the consistent improvements observed during periods of strict emission control measures highlight the potential benefits of implementing similar strategies beyond mega-events such as the Olympic Games. In contrast, festivals and large public gatherings without emission controls, such as Diwali or Holi, were often associated with sharp increases in pollution and adverse health outcomes. This suggests that stricter regulation of emission sources during such events, including traffic restrictions, control of fireworks, and temporary industrial measures, could substantially reduce short-term health risks. Therefore, future mega-events planning should prioritize early targeted emission-control strategies tailored to the size and timing of the expected pollution peak.

From a research perspective, several gaps remain. First, there is a need for more studies conducted in underrepresented regions, particularly Europe, America, Australia and Africa, in order to improve the generalizability of the findings and account for differences in pollution sources and population characteristics. Second, future studies should aim to better characterize the impact of specific emission sources during mega-events, including traffic, biomass burning, and fireworks, as well as their contribution to pollutant mixtures and toxicity. There is also a need for more integrated study designs combining clinical outcomes and biological markers within the same populations, in order to strengthen the causal link between exposure, early biological responses, and health effects. Finally, longitudinal studies are needed to determine whether repeated short-term improvements in air quality can translate into sustained long-term health benefits. At the individual level, these findings suggest that personal preventive strategies may also play an important role, particularly during high-exposure events. Reducing outdoor activities during peak pollution periods and the use of personal protective equipment, such as face masks with an adequate filtering capacity, may help limit exposure, especially among vulnerable populations including older adults and individuals with pre-existing cardiovascular or respiratory conditions. Increasing public awareness of short-term pollution peaks during mega-events and promoting simple protective behaviors could further contribute to reducing health risks.

5. Conclusions

Air pollution, when altered abruptly during mega-events, produces immediate and measurable health effects. The studies assembled in this review demonstrate that emission control measures, such as traffic restrictions, industrial shutdowns and firework bans, implemented for events like the Olympic Games, Asian Games or large festivals consistently lowered concentrations of PM_2.5, PM₁₀, NO₂, SO₂ and related pollutants. These reductions were paralleled by declines in all-cause, cardiovascular and respiratory mortality, hospital admissions and early biological responses. For example, one included study reported that a 10 μg/m³ decrease in PM₁₀ was associated with an 8.4 to 9.6% reduction in all-cause mortality and an 8.8% reduction in cardiovascular mortality [41]. In contrast, events without strict emission controls causes sharp pollution increases that coincided with rises in mortality, hospitalizations and elevated biomarker levels. These findings support strict emission controls for mega-events, such as traffic restrictions, industrial shutdowns and firework bans, especially in settings with high baseline pollution and vulnerable populations. The review also highlights several methodological gaps and the dominance of evidence from Asian contexts (e.g., Beijing Olympic studies) with less data from Europe, Africa, the Americas and Oceania, limiting the generalizability of findings.

Acknowledgements

AcknowledgmentsWe thank the authors who published previous research articles on this topic allowing us to conduct a Systematic Review. For the preparation of the graphical abstract and Figure 2 presented in this manuscript, we used GenAI ChatGPT Pro version 5.5. The authors have reviewed and edited the output and take full responsibility for the content of this publication.

Competing interests

Conflicts of InterestThe authors declare no conflicts of interest.

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