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Frontiers in Future Transportation ·

Volume 7 - 2026 | https://doi.org/10.3389/ffutr.2026.1857164

Car-free days as sustainable urban transport emission reduction strategies: evidence from Kigali city, Rwanda

  • Emily Airhart1,2
  • Egide Kalisa3*corresponding author
  1. 1Department of Pathology and Laboratory Medicine, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
  2. 2Department of Physical and Environmental Science, University of Toronto, Scarborough, ON, Canada
  3. 3Department of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
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Abstract

Car-Free Days (CFDs) in Kigali, Rwanda, are held twice monthly on Sundays, when motorized vehicle traffic is restricted on major roads from 7:00 AM–11:00 AM to promote physical activity and reduce air pollution. Previous studies assessing the effectiveness of CFDs in reducing air pollution in Kigali have relied solely on short-term, low-cost fine particulate matter (PM2.5) measurements during the intervention period at a single site and have provided no post-intervention rebound assessment. The present study provides the first record of variations in PM2.5 and ozone (O3) to evaluate the effectiveness of CFDs as a sustainable transport emission-reduction strategy. We examine whether reductions in air pollution persist beyond implementation hours and contribute to overall daily improvements in air quality in Rwanda. Continuous air quality data collected between 2022 and 2024 from two sites were analyzed. Pollutant concentrations during CFD Sundays were compared to normal Sundays across morning intervention (7:00 AM–11:00 AM) and post-intervention (11:00 AM–9:00 PM) periods. Results show that PM2.5 concentrations significantly decreased during CFD hours (−14.8%, P < 0.0001) and remained lower in the post-intervention period (−34.7%; P < 0.0001), with no evidence of rebound. Diurnal profiles showed continued declines after 11:00 a.m. and a suppressed evening peak, indicating a sustained reduction in daily exposure. In contrast, O3 showed no significant differences during CFD hours and increased in the afternoon, consistent with photochemical formation rather than direct traffic emissions. This study highlights that CFDs may serve as an effective, low-cost, and sustainable strategy to reduce transport emissions in Africa, where expensive interventions to reduce air pollution are lacking. These findings also highlight the potential of community-based interventions to enhance urban environmental sustainability and resilience, especially in rapidly urbanizing cities.

Keywords

1 Introduction

Poor air quality is an increasingly pressing environmental health issue, especially in urban areas where emission sources are concentrated. A primary contributor is the combustion of fossil fuels, which releases pollutants such as nitrogen oxides (NOX), volatile organic compounds (VOCs), and particulate matter (PM) (World Health Organization, 2024). Traffic-related air pollution (TRAP) contributes to increased atmospheric greenhouse gases, leading to rising global temperatures (Slimi et al., 2026). Additionally, VOCs and NOX undergo chemical reactions which form smog and ground-level ozone (O3), a harmful air pollutant (Atkinson, 2000). Fine particulate matter (PM2.5) can penetrate deep into the lungs and enter the bloodstream, resulting in adverse effects on cardiovascular, cerebrovascular, and respiratory health in humans (World Health Organization, 2024). Globally, air pollution is associated with approximately 6.7 million premature deaths each year (World Health Organization, 2024).

Reducing the emission of harmful air pollutants is critical to minimizing the health burden posed by air pollution. Among the strategies implemented in urban environments, car-free initiatives have emerged as a widely adopted approach to reduce TRAP while promoting more active and sustainable forms of transportation. Car-free initiatives are urban programs aimed at reducing motorized vehicle traffic to promote sustainable mobility, improve public health, and mitigate environmental pollution. These programs manifest in various forms, including car-free days (CFDs), pedestrian-only zones, and permanent street closures that prioritize non-motorized transportation. By discouraging private vehicle use, these initiatives encourage walking, cycling, and reliance on public transit, contributing to reduced greenhouse gas emissions, improved air quality, and more livable cities (Glazener et al., 2022).

One of the earliest and most influential examples is “Ciclovía Recreativa” in Bogotá, Colombia. Established in 1974, it has evolved into a citywide event in which more than 121 km of roads are closed from 7:00 a.m. to 2:00 p.m. every Sunday, attracting over two million participants (Sarmiento et al., 2010). Its success has inspired similar programs worldwide, demonstrating the transformative potential of car-free initiatives in urban settings. Today, cities worldwide have integrated car-free programs to promote physical activity and decrease TRAP. Examples include annual car-free events in Brussels, “Green Sundays” and low-emission traffic zones in Milan, “Ecological Sundays” in Turin, and CycloBia events in Texas (Bulan, 2024; Casale et al., 2009; Salazar-Collier et al., 2018; Vanderstraeten et al., 2010; Vanderstraeten et al., 2011). In Kigali, Rwanda, the CFD was introduced in 2016 as a monthly event and, due to its success, became a biweekly occurrence in 2018 (Kalisa et al., 2018; Kalisa et al., 2021). Between 7:00 a.m. and 11:00 a.m. on the first and third Sunday of each month, motorized vehicles are restricted on certain roads in the city to reduce TRAP, incorporating community health initiatives, outdoor fitness activities, and environmental awareness campaigns (Kalisa et al., 2021).

Previous research has investigated changes in ambient PM2.5 concentrations on CFDs in Kigali during the intervention period (between 7:00 a.m. and 11:00 a.m.). A study conducted by Subramanian et al. (2020) found that PM2.5 levels during CFDs decreased the most between 7:00 a.m. and 9:00 a.m., with average PM2.5 concentrations reduced by 10–12 μg/m3, a 20% decrease compared to normal Sundays. The study also observed similar PM2.5 reductions before 7:00 a.m., prior to the intervention period, suggesting that the reductions in PM2.5 may not be entirely attributable to the CFD policy itself. However, data were collected using a low-cost sensor from a single monitoring station on the roof of a building adjacent to the closed road and did not capture street-level air quality conditions. Additionally, the study did not assess air quality in the hours following the intervention period, a consideration important for understanding the full effect of CFD programs.

This study aims to assess the effectiveness of CFDs in reducing TRAP by examining ambient PM2.5 and O3 concentrations in Kigali using long-term, high-quality data from a reference air quality station. The study compares average PM2.5 and O3 concentrations during the intervention period (7:00 AM–11:00 AM) on CFDs to the same hours on normal Sundays (Sundays on which traffic was not restricted) and to post-intervention hours (from 11:00 AM–9:00 PM) on CFDs. It is hypothesized that CFDs will reduce PM2.5 concentrations, while O3 concentrations may vary due to photochemical processes.

2 Materials and methods

2.1 Data collection

Ambient PM2.5 and O3 concentration data were collected between February 2022 and September 2024. Measurements were recorded hourly in micrograms per cubic metre (µg/m3) for PM2.5 and in parts per billion (ppb) for O3. Data were collected from two fixed-location air quality monitoring stations located in Kigali, Rwanda: the Gasabo station and the United States Embassy (“US Embassy”) station. Both sites are located at street level within 10–20 m of roads affected by CFD restrictions (Figure 1).

Map of Africa showing Rwanda, with the sampling site in Kigali and the air quality monitoring station near the car-free day road.
Figure 1. Map of Africa showing Rwanda, with the sampling site in Kigali and the air quality monitoring station near the car-free day road.

The US Embassy station is part of a regional air quality monitoring network and is equipped with a Federal Equivalent Method (FEM)-designated Beta Attenuation Mass Monitor (BAM), which provides continuous, reference-grade measurements of PM (Omodieke et al., 2026). The BAM determines PM2.5 mass concentrations by measuring the attenuation of beta radiation as particles accumulate on a filter tape, allowing for accurate hourly quantification of ambient particulate levels. Data from this site have been used in previous studies to validate lower-cost sensor networks deployed across Kigali and have shown strong agreement between reference-grade and real-time monitoring systems (Omodieke et al., 2026). Data from the Gasabo station were collected using a real-time, affordable multi-pollutant monitor (RAMP) (Subramanian et al., 2020). Our previous studies showed that data from both BAM and RAMP monitors are strongly correlated (r = 0.96, p < 0.001) from a similar air quality station in Kigali and the US Embassy in Rwanda (Omodieke et al., 2026). A detailed description of RAMP monitors is provided in our previous study (Kalisa and Sudmant, 2025).

2.2 Data processing and analysis

All data processing and analysis were conducted in R (version 4.2.1). Data were cleaned by removing missing values, verifying timestamps, and filtering for Sundays. The dataset included 73 Sundays for the Gasabo station, comprising 17 CFDs and 56 normal Sundays, and 88 Sundays for the US Embassy station, including 24 CFDs and 64 normal Sundays. The amount of data available on Sundays differed between sites due to missing data on certain dates.

Observations were categorized as CFDs or normal Sundays based on a schedule of CFD events between 2022 and 2024. Analyses focused on two time periods: morning intervention hours (7:00 AM–11:00 AM) and afternoon post-intervention hours (11:00 AM–9:00 PM). These comparisons evaluated both the immediate impact of traffic restrictions and the potential rebound effects in pollutant concentrations following the resumption of motorized vehicle traffic.

Mean pollutant concentrations and standard deviations were calculated for each time period. Data analysis included independent t-tests to compare pollutant concentrations between the morning intervention hours (7:00 AM–11:00 AM) on CFDs and the same hours on normal Sundays. Independent t-tests also compared pollutant concentrations during morning intervention hours (7:00 AM–11:00 AM) and afternoon post-intervention hours (11:00 AM–9:00 PM) on CFDs. To further characterize temporal dynamics, diurnal patterns were analyzed by computing hourly mean concentrations across all CFDs and normal Sundays. These trends were visualized using line plots to evaluate temporal trends and potential rebound effects following traffic resumption.

3 Results

The mean ambient PM2.5 concentration during car-free hours (7:00 AM–11:00 AM) on CFDs was significantly lower (M = 41.03 μg/m3, SD = 15.72) than during the same hours on normal Sundays (M = 48.15 μg/m3, SD = 20.05), t(549.77) = −6.40, p < 0.001, 95% CI [–9.31, −4.94] (Figure 2). This represents a reduction of 7.12 μg/m3, or 14.8%, during the intervention period. Within CFDs, PM2.5 concentrations during the afternoon period (11:00 AM–9:00 PM; M = 26.81 μg/m3, SD = 13.70) were significantly lower than during the morning car-free hours, t(1406) = 15.16, p < 0.001, 95% CI [12.38, 16.06], corresponding to a decrease of 14.22 μg/m3 (34.7%) relative to morning concentrations (Figure 3). Comparisons with normal Sundays showed that afternoon PM2.5 concentrations remained lower on CFDs (26.81 μg/m3) than on normal Sundays (33.28 μg/m3), indicating that reductions in PM2.5 persisted beyond the traffic restriction period (Figure 3; Table 1).

Box plot comparing particulate matter air pollution (PM<sub>2.5</sub>) **(A)** and **(B)** Ozone (O<sub>3</sub>) average concentrations on a car-free day (CFD) with a non-car-free day (non-CFD) in Kigali city, Rwanda.
Figure 2. Box plot comparing particulate matter air pollution (PM2.5) (A) and (B) Ozone (O3) average concentrations on a car-free day (CFD) with a non-car-free day (non-CFD) in Kigali city, Rwanda.
Box plot comparing particulate matter air pollution (PM<sub>2.5</sub>) **(A)** and average ozone (O<sub>3</sub>). **(B)** concentrations on a car-free day (CFD) in effect (7 a.m.–11 a.m.) and on the same day during hours when CFD is not in effect (11 a.m. - 9 p.m.), when activities resumed in Kigali City.
Figure 3. Box plot comparing particulate matter air pollution (PM2.5) (A) and average ozone (O3). (B) concentrations on a car-free day (CFD) in effect (7 a.m.–11 a.m.) and on the same day during hours when CFD is not in effect (11 a.m. - 9 p.m.), when activities resumed in Kigali City.

TABLE 1. Summary of results showing comparisons of the mean ± standard deviation (M±SD) PM2.5 and O3 across time periods of car-free day (CFD) events.

PollutantComparisonCFD morning (M ± SD)Comparison Group (M ± SD)t-test result% difference
PM2.5 [μg/m3]Car-free hours vs. Normal Sunday (7–11 AM)41.03 ± 15.72Normal Sunday: 48.15 ± 20.05t (549.77) = −6.40p < 0.00114.8% lower on CFDs
Car-free hours vs. Afternoon (same day)41.03 ± 15.72Afternoon: 26.81 ± 13.70t (1406) = 15.16p < 0.00134.7% lower in the afternoon
O3 [ppb]Car-free hours vs. Normal Sunday (7–11 AM)19.07 ± 9.02Normal Sunday: 18.19 ± 8.19t (88.78) = 0.77p = 0.44394.6% higher on CFDs
Car-free hours vs. Afternoon (same day)19.07 ± 9.02Afternoon: 21.09 ± 8.16t (82.12) = −1.79p = 0.0771810.6% higher in the afternoon

Monthly and hourly trends showed distinct diurnal patterns between CFDs and normal Sundays (Figure 4). PM2.5 concentrations declined following the end of the car-free period and remained consistently lower throughout the afternoon and evening, whereas normal Sundays exhibited higher concentrations and a more pronounced evening peak. These patterns indicate that reductions in PM2.5 were sustained beyond the intervention window, with no evidence of a rebound following the resumption of traffic after 11:00 a.m. The results of the monthly variation show that the average concentrations of PM2.5 and O3 were generally higher during the dry seasons (December - February and June - August) than during the wet seasons (March-May and September-November) (Figure 4).

Temporal variation in the monthly mean concentrations of PM<sub>2.5</sub> **(A)** and O<sub>3</sub> **(C)**, and hourly variations showing car-free days (CFD) hours (green) and non-car-free (non-CFD) hours (orange) of PM<sub>2.5</sub> **(B)** and O<sub>3</sub> **(D)** for data collected from 2022 to 2024 at all air quality stations in Kigali, Rwanda.
Figure 4. Temporal variation in the monthly mean concentrations of PM2.5 (A) and O3 (C), and hourly variations showing car-free days (CFD) hours (green) and non-car-free (non-CFD) hours (orange) of PM2.5 (B) and O3 (D) for data collected from 2022 to 2024 at all air quality stations in Kigali, Rwanda.

In contrast, mean ambient O3 concentrations during car-free hours (7:00 AM–11:00 AM) were slightly higher on CFDs (M = 19.07 ppb, SD = 9.02) than on normal Sundays (M = 18.19 ppb, SD = 8.19), although this difference was not statistically significant, t(88.78) = 0.77, p = 0.4439. Within CFDs, O3 concentrations increased in the afternoon (M = 21.09 ppb, SD = 8.16), representing a 10.6% rise compared to morning levels, although not statistically significant (p = 0.077). Median O3 levels were comparable between CFDs and normal Sundays, with O3 concentrations slightly higher in the afternoon on both types of Sundays (Figure 3; Table 1).

Diurnal profiles showed the highest levels of O3 in the afternoon, with concentrations rising sharply after 8:00 a.m. before steadily decreasing in the evening (Figure 4). This pattern was observed for both CFDs and normal Sundays, however, O3 levels were generally slightly lower on CFDs. The divergence between the two curves was the most pronounced during the afternoon, after which the concentrations converged again in the evening.

4 Discussion

The present study evaluated the effectiveness of CFDs in reducing ambient PM2.5 and O3 concentrations in Kigali, Rwanda. The results show that CFDs are associated with significant reductions in PM2.5 during the morning intervention period, reinforcing the contribution of vehicular emissions to urban PM2.5 pollution (Kalisa et al., 2025). This study also provides evidence that reductions persist beyond intervention hours, with no rebound effect observed following the resumption of traffic. This challenges the assumption that short-term traffic interventions simply shift emissions to later in the day. Instead, CFDs may reduce overall daily PM2.5 emissions by discouraging individuals from using motorized vehicles beyond traffic restriction hours. This indicates that even short-term interventions can influence transport behaviour, thereby supporting broader goals of emission reduction and urban environmental resilience. Kalisa and Adams (2022) used a natural experiment during COVID-19 and found that air pollution decreased by 59% during the evening of the COVID-19 curfew, when traffic restrictions were in effect.

In contrast, O3 concentrations did not decrease during CFD hours and generally increased in the afternoon, reflecting the secondary nature of O3 formation which depends on photochemical reactions involving NOX and VOCs in the presence of sunlight (Atkinson, 2000). Increasing solar radiation throughout the day enhances photochemical activity, leading to higher O3 concentrations in the afternoon. Reduced traffic may also limit nitric oxide (NO) emissions, decreasing O3 titration and resulting in higher O3 levels despite lower emissions of its precursors (Jhun et al., 2015). The absence of reductions in O3 concentrations highlights that temporary traffic restrictions alone may not be sufficient to lower O3 levels. Instead, O3 concentrations are controlled predominantly by photochemical processes, with no clear effect from CFDs. Reducing O3 therefore requires broader emission control strategies targeting precursor emissions across multiple sectors.

The sustained reduction in PM2.5 observed beyond the CFD intervention period reflects the broader socio-environmental context in which these initiatives operate. In Kigali, CFDs function as coordinated, multi-sectoral interventions that involve government agencies, public health institutions, community members, transport operators, and local businesses that collectively shape urban mobility patterns and behaviours. Government agencies, such as the City of Kigali, implement and regulate CFDs, while public health institutions lead disease screening and health promotion activities. Community participation in mass sport activities and health screening may influence mobility behaviour even after the intervention hours, contributing to reduced cumulative emissions and explaining the absence of a rebound in PM2.5 concentrations after traffic resumes. In addition, transport operators and local businesses adapt to these periodic changes, influencing overall urban activity patterns (Kalisa and Adams, 2022). This multi-sectoral system aligns with a One Health approach, where environmental, human, and social systems are interconnected and collectively contribute to improved urban air quality. As such, CFDs are not just a transport policy, but a coordinated One Health system involving government, health, and community actors that contribute to air quality improvements.

Despite these benefits, CFDs alone are insufficient to achieve sustained, long-term reductions in urban air pollution. In Kigali, major contributors to PM2.5 pollution include biomass burning, charcoal use for household energy, and thermal energy generation (Rwanda Environment Management Authority, 2018; Kalisa, 2026) and pollution varies by different land-use types in Rwanda (Faye et al., 2025; Kalisa et al., 2026; Omodieke et al., 2026). While the findings demonstrate that CFDs can reduce daily PM2.5 levels, long-term interventions targeting all dominant sources of PM2.5 emissions are required to sustain reductions in urban ambient PM2.5 concentrations and improve air quality. Although CFD has been shown to reduce urban air pollution, the average level measured under CFD is still above the WHO annual air quality standard of 5 μg/m3 (WHO, 2024). A combined effort with CFD is required to reduce air traffic pollution in Kigali. Recently, the government of Rwanda has launched the 2050 master plan to invest in electric mobility (Mininfra, 2021). We recently demonstrated that scaling up electric mobility will have economic, environmental, and health benefits, but barriers such as charging access and costs need to be addressed to enhance adoption (Bursey and Kalisa, 2025; Kalisa et al., 2025; Sudmant et al., 2020).

5 Limitations of the study

This study has several limitations that should be considered when interpreting the results. First, while the study provides important findings, particularly for cities exploring low-cost traffic management measures such as car-free days to improve urban air quality, the analysis is based on a limited number of pollutants and monitoring locations. Our study has focused only on PM2.5 and O3 as important indicators of urban air quality; however, they do not capture the full spectrum of traffic-related emissions, such as Nitrogen dioxide (NO2), Black carbon (BC), and carbon monoxide (CO). Therefore, the study may not fully reflect the overall impact of Car-Free Days on urban air pollution.

Second, the spatial coverage of monitoring data is limited to a small number of fixed monitoring stations. PM2.5 and O3 concentrations were only measured at two fixed air quality monitoring stations located near the CFD events, limiting the ability to assess spatial variability in air quality and potential traffic displacement effects in other areas of the city. These stations may not be representative of the entire city, particularly given spatial variability in traffic patterns, land-use types, and emission sources. Since the CFD restrictions occur only on certain major roads in the city, emissions may be redistributed rather than reduced at a city-wide scale. Consequently, these findings should be interpreted as indicative of localized conditions rather than comprehensive city-wide effects.

Third, air pollution can vary by minutes, days, and weeks, and this study has not explored confounding factors such as wind speed, precipitation, temperature, and atmospheric stability, which may influence the results. Although we made every effort to ensure comparability, residual confounding remains. Our previous study demonstrated that Rwanda experiences a tropical climate, and these meteorological factors have minimal influence throughout the year (Kalisa et al., 2025), despite changes observed in winter and summer in the global North.

Fourth, a limitation of this study is that meteorological parameters were not directly measured during the sampling periods. Although meteorological factors can influence air pollutant concentrations, Rwanda’s tropical climate and relatively stable atmospheric conditions suggest that short-term meteorological factors during CFD and non-CFD periods were likely minimal to non-existent (Kalisa et al., 2025). Nevertheless, future studies incorporating detailed meteorological modelling and measurements would provide a more comprehensive analysis of their influence on air pollutant variability in Kigali and, more generally, in Rwanda.

Finally, the study has focused on the immediate changes in pollutant concentrations during car-free day events and does not assess long-term behaviour at the city-wide level due to data availability constraints. Given these limitations, the findings should be interpreted with caution. Although our study showed reductions during car-free events compared to non-car-free day events, future studies are requested, using high-resolution spatiotemporal datasets and expanded monitoring stations, additional pollutants, and analysis of confounding factors to better assess the broader and long-term impacts of car-free days on urban air quality during and after car-free days and to investigate sustained reductions or shifts in mobility patterns. Future studies should incorporate mobility and traffic proxy datasets, where available, to better characterize post-CFD traffic dynamics.

6 Conclusion

This study demonstrates that CFDs in Kigali are associated with reductions in PM2.5 concentrations during and after intervention periods, suggesting they may be effective, low-cost interventions to improve urban air quality. However, their limited impact on O3 highlights the need for comprehensive emission control strategies that address multiple emission sources and pollutants simultaneously. While CFDs are insufficient on their own to resolve urban air pollution, they represent a valuable component of broader sustainable transport and public health strategies, particularly in rapidly urbanizing cities.

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Footnotes

Edited by: Yamila Grassi, Instituto de Matemática de Bahía Blanca (INMABB), Argentina

Reviewed by: Yassine Charabi, Kuwait University, Kuwait

Porush Kumar, Rajasthan Technical University, India

Statements

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author EK declared that they were an editorial board member of Frontiers at the time of submission. This had no impact on the peer review process and the final decision.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Data availability

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

EA: Writing – review and editing, Visualization, Conceptualization, Validation, Formal Analysis, Methodology, Writing – original draft, Data curation. EK: Supervision, Conceptualization, Methodology, Writing – review and editing.

Acknowledgements

We acknowledge the air quality data obtained from the US Embassy Air Quality Monitoring Station in Kigali and from the Rwanda Environmental Management Authority’s air quality monitoring station.

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Citation

Airhart, E. & Kalisa, E. (2026). Car-free days as sustainable urban transport emission reduction strategies: evidence from Kigali city, Rwanda. Frontiers in Future Transportation, Volume 7. https://doi.org/
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7 - 2026

Copyright

Copyright © 2026 Airhart and Kalisa.

License: https://creativecommons.org/licenses/by/4.0/

*Correspondence: Egide Kalisa

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