Exposure assessment of cyclists to UFP and PM on urban routes in Xi'an, China

Air pollution exposure in active versus passive travel modes across five continents: A Bayesian random-effects meta-analysis

Epidemiological studies on health effects of air pollution usually estimate exposure at the residential address. However, ignoring daily mobility patterns may lead to biased exposure estimates, as documented in previous exposure studies. To improve the reliable integration of exposure related to mobility patterns into epidemiological studies, we conducted a systematic review of studies across all continents that measured air pollution concentrations in various modes of transport using portable sensors. To compare personal exposure across different transport modes, specifically active versus motorized modes, we estimated pairwise exposure ratios using a Bayesian random-effects meta-analysis. Overall, we included measurements of six air pollutants (black carbon (BC), carbon monoxide (CO), nitrogen dioxide (NO2), particulate matter (PM10, PM2.5) and ultrafine particles (UFP)) for seven modes of transport (i.e., walking, cycling, bus, car, motorcycle, overground, underground) from 52 published studies. Compared to active modes, users of motorized modes were consistently the most exposed to gaseous pollutants (CO and NO2). Cycling and walking were the most exposed to UFP compared to other modes. Active vs passive mode contrasts were mostly inconsistent for other particle metrics. Compared to active modes, bus users were consistently more exposed to PM10 and PM2.5, while car users, on average, were less exposed than pedestrians. Rail modes experienced both some lower exposures (compared to cyclists for PM10 and pedestrians for UFP) and higher exposures (compared to cyclist for PM2.5 and BC). Ratios calculated for motorcycles should be considered carefully due to the small number of studies, mostly conducted in Asia. Computing exposure ratios overcomes the heterogeneity in pollutant levels that may exist between continents and countries. However, formulating ratios on a global scale remains challenging owing to the disparities in available data between countries.

Seasonal variation of particle number concentration in a busy urban street with exposure assessment and deposition in human respiratory tract

Ultrafine particles (UFP) associated with air quality and health impacts are a major concern in growing urban regions. Concentrations of UFP (particles of size between 10 and 100 nm) and accumulation mode (Nacc) (particles of size >100 and up to 1000 nm), are analyzed over a highly polluted megacity, Delhi, in conjunction with vehicular flow density, during peak (morning, and evening) and non-peak hours. UFP contributes ≥60% to total particle concentration during autumn and monsoon. UFP concentrations are about 50,000 particles per cm3 in winter which reduces to about 25,000 particles during monsoon. Nacc are about 20,000 (winter) and 10,000 (monsoon) particles per cm3. UFP concentration and Nacc during peak hours are at least twice higher than those obtained in non-peak hours, confirming the dominant influence of emissions from vehicular exhaust in the study region. Seasonal analysis of UFP size distribution reveals that direct emissions dominate the particle concentrations during winter and autumn, whereas new particle formation mechanism contributes the highest in spring and summer. Assessment of inhalable particle number concentration and particle deposition in the human respiratory tract using Multiple Path Particle Dosimetry (MPPD) model, performed for the first time, shows that the order in which these particles deposit in the human respiratory tract is alveoli > bronchiole > bronchus. The deposition ranges between 10 and 18 million nanoparticles during different hours of the day, whereas the estimated inhalable particle concentration (IPN) varies between 0.5 and 1 billion. Results on the IPN during activities classified from light (walking), medium, heavy, very heavy to severe (long-distance running) provide insights into health effects on vulnerable populations. These quantitative results obtained over a megacity on hourly and seasonal variations of nanoparticles along with IPN and deposition rates for different activities are important, and are invaluable inputs for developing mitigation policies aimed to improve air quality and public health, both of which are major concerns in South Asia.

Concentration-dependent effects of reductive pulmonary inhalants on ultrafine particle-induced oxidative stress: Insights for health risk assessment

The impact of reductive pulmonary inhalants on ultrafine particles (UFPs)-induced pulmonary oxidative stress remains a crucial consideration, yet the concentration-dependent effects of these inhalants have remained unexplored. Here we synthesized composite UFPs simulating atmospheric UFPs, primarily composed of metals and quinones. We subjected these UFPs to varying concentrations (0-7000 μM) of two reductive pulmonary inhalants, N-acetylcysteine and salbutamol, to assess their influence on oxidative potential, measured through the dithiothreitol assay (OPDTT). Simultaneously, we analysed the soluble metal content of UFPs to uncover potential relationships between oxidative potential and metal solubility. Our results unveil a dual role played by these inhalants in shaping the OPDTT of composite UFPs. Specifically, OPDTT generally increased as inhalant concentrations rose from 0 to 300 μM. However, an intriguing reversal occurred when concentrations exceeded 500 μM, resulting in a decline in OPDTT. Relative to untreated UFPs, these inhalants induced promotion and inhibition effects within concentration ranges of 100-500 and >1000 μM, respectively. While no significant correlation emerged between OPDTT and soluble metal content as inhalant concentrations ranged from 0 to 7000 μM, noteworthy positive correlations emerged at lower inhalant concentrations (e.g., N-acetylcysteine at 0-300 μM). These findings provide insights into the potential influence of reductive pulmonary inhalants on health risks associated with UFP exposure, further underscoring the need for continued research in this critical area.

Quantifying the contributions of road and air traffic to ambient ultrafine particles in two urban communities

Traffic-related activities are widely acknowledged as a primary source of urban ambient ultrafine particles (UFPs). However, a notable gap exists in quantifying the contributions of road and air traffic to size-resolved and total UFPs in urban areas. This study aims to delineate and quantify the traffic's contributions to size-resolved and total UFPs in two urban communities. To achieve this, stationary sampling was conducted at near-road and near-airport communities in Seattle, Washington State, to monitor UFP number concentrations during 2018-2020. Comprehensive correlation analyses among all variables were performed. Furthermore, a fully adjusted generalized additive model, incorporating meteorological factors, was developed to quantify the contributions of road and air traffic to size-resolved and total UFPs. The study found that vehicle emissions accounted for 29% of total UFPs at the near-road site and 13% at the near-airport site. Aircraft emissions contributed 14% of total UFPs at the near-airport site. Notably, aircraft predominantly emitted UFP sizes below 20 nm, while vehicles mainly emitted UFP sizes below 50 nm. These findings reveal the variability in road and air traffic contributions to UFPs in distinct areas. Our study emphasizes the pivotal role of traffic layout in shaping urban UFP exposure.

Fine particulate matter (PM2.5) exposure assessment among active daily commuters to induce behaviour change to reduce air pollution

Fine particulate matter (PM2.5), a detrimental urban air pollutant primarily emitted by traffic and biomass burning, poses disproportionately significant health risks at relatively limited exposure during commuting. Previous studies have mainly focused on fixed locations when assessing PM2.5 exposure, while neglecting pedestrians and cyclists, who often experience higher pollution levels. In response, this research aimed to independently validate the effectiveness of bicycle-mounted low-cost sensors (LCS) adopted by citizens, evaluate temporal and spatial PM2.5 exposure, and assess associated health risks in Ljubljana, Slovenia. The LCS quality assurance results, verified by co-location field tests by air quality monitoring stations (AQMS), showed comparable outcomes with an average percentage difference of 21.29 %, attributed to humidity-induced nucleation effects. The colder months exhibited the highest air pollution levels (μ = 32.31 μg/m3) due to frequent thermal inversions and weak wind circulation, hindering vertical air mixing and the adequate dispersion of pollutants. Additionally, PM2.5 levels in all sampling periods were lowest in the afternoon (μ = 12.09 μg/m3) and highest during the night (μ = 61.00 μg/m3) when the planetary boundary layer thins, leading to the trapping of pollutants near the surface, thus significantly affecting diurnal and seasonal patterns. Analysis of exposure factors revealed that cyclists were approximately three times more exposed than pedestrians. However, the toxicological risk assessment indicated a minimal potential risk of PM2.5 exposure. The collaborative integration of data from official AQMS and LCS can enhance evidence-based policy-making processes and facilitates the realignment of effective regulatory frameworks to reduce urban air pollution.

Intermodal comparison of commuters' exposure to VOCs between public, private, and active transportation

Urban populations are exposed to a multitude of traffic-related air pollutants during daily commutes. This study assessed commuters' exposure to volatile organic compounds (VOCs) during bus, motorcycle, and bicycle commuting, and estimated the VOC inhalation dose. Benzene, toluene, ethylbenzene, and xylene (BTEX) were the main compounds detected, contributing 58 - 68% to ΣVOC (sum of the concentrations of all detected VOCs) in different travel modes. The mean ΣVOC exposure concentration was higher for motorcyclists than for cyclists and bus commuters. However, due to cyclists' higher minute ventilation rates and longer exposure time, they had the highest ΣVOC inhalation dose based on both travel time (7.09 ± 2.36 μg min-1) and distance (32.9 ± 10.8 μg km-1). Among the three travel modes, bus commuters had the lowest ΣVOC inhalation dose based on travel time (2.33 ± 1.18 μg min-1) and distance (8.91 ± 4.91 μg km-1), while motorcyclists had a moderate ΣVOC inhalation dose based on travel time (5.08 ± 1.46 μg min-1) and distance (13.4 ± 5.5 μg km-1). Health impact assessment of VOCs showed that cyclists faced the highest carcinogenic and non-carcinogenic risks, while bus commuters experienced the lowest health risk associated with VOC exposure. Our findings underscore the need to consider air quality in transportation infrastructure design and prioritize interventions to safeguard urban commuters' health, particularly cyclists, who are the most vulnerable to the adverse effects of traffic-related air pollutants.

The impact of low emission zones on personal exposure to ultrafine particles in the commuter environment

Auckland is a city with limited industrial activity, road traffic being the dominant source of air pollution. Thus, the time periods when social contact and movement in Auckland were severely curtailed due to COVID-19 restrictions presented a unique opportunity to observe impacts on pedestrian exposure to air pollution under a range of different traffic flow scenarios, providing insights into the impacts of potential future traffic calming measures. Pedestrian exposure to ultrafine particles (UFPs), was measured using personal monitoring along a customised route through Central Auckland during different COVID-19-affected traffic flow conditions. Results showed that reduced traffic flows led to statistically significant reductions in average exposure to UFP under all traffic reduction scenarios (TRS). However, the size of the reduction was variable in both time and place. Under the most stringent TRS (traffic reduction of 82 %), median ultrafine particle (UFP) concentrations reduced by 73 %. Under the less stringent scenario, the extent of reduction varied in time and space; a traffic reduction of 62 % resulted in a 23 % reduction in median UFP concentrations in 2020 but in 2021 similar traffic reductions led to a decrease in median UFP concentrations of 71 %. Under all scenarios, the magnitude of the impact of traffic reductions on UFP exposure varied along the route, with areas dominated by emissions from construction and ferry/port activities showing little correlation between traffic flow and exposure. Shared traffic spaces, previously pedestrianised, also recorded consistently high concentrations with little variability observed. This study provided a unique opportunity to assess the potential benefits and risks of such zones and to help decision-makers evaluate future traffic management interventions (such as low emissions zones). The results suggest that controlled traffic flow interventions can result in a significant reduction in pedestrian exposure to UFPs, but that the magnitude of reductions is sensitive to local-scale variations in meteorology, urban land use and traffic flow patterns.

A systematic review of transportation carbon emissions based on CiteSpace

Transportation sector has become a major contributor to the escalation of carbon emissions and subsequent climate change. In this study, a bibliometric analysis was conducted using CiteSpace on published papers (1991-2022). Then a theoretical framework was proposed through traditional content analysis from three aspects: measurement, mechanism analysis, and low-carbon pathways analysis. The clustering results show that the research topics have involved mainly factor analysis, evaluation, system analysis, control measurement and pollutants. A further summary of the content of the relevant literature shows that there are five main accounting methods for measuring transportation carbon emissions (TCEs), which can be applied to different scenarios. Studies involving the spatio-temporal distribution of TCEs is limited and mainly focus on macroperspectives. The mechanism of TCEs involves three main aspects: system assessment, efficiency measurement, and driver analysis, which serve to identify the internal patterns of TCEs. Finally, the outlook regarding TCEs is presented.

Die Feinstaubbelastung Radfahrender im innerstädtischen Straßenverkehr

Fahrradfahren als Form der aktiven Fortbewegung bietet viele gesundheitliche Vorteile durch eine gesteigerte körperliche Aktivität. In städtischer Umgebung können diese Vorteile aufgrund der intensivierten Respiration beim Radfahren und der Nähe zum Fahrzeugverkehr mit einer assoziierten Exposition von verkehrsbedingter partikulärer Luftverschmutzung durch Feinstaub beeinträchtigt werden. Das Ziel dieser Übersichtsarbeit ist, eine Darstellung der aktuellen Literatur mit mobil erhobenen Daten zur Feinstaubbelastung Radfahrender im urbanen Raum zu geben sowie die darin beschriebenen Einflussfaktoren der Feinstaubkonzentrationen aus Meteorologie, Verkehr, Architektur und zeitlichen Bedingungen zu beschreiben. Fahrradfahren repräsentiert diesbezüglich eine effiziente Vorgehensweise zur Charakterisierung individueller Feinstaubbelastungen mit der Möglichkeit einer hohen räumlich-zeitlichen Auflösung. Unter Beachtung der Hintergrundkonzentration können Aussagen zur relativen Schadstoffexposition und des einhergehenden Gesundheitsrisikos mit Erkenntnissen zugunsten einer umweltverträglichen innerstädtischen Verkehrsplanung getroffen werden.

Characterizing the source apportionment of black carbon and ultrafine particles near urban roads in Xi'an, China

Better knowledge of the sources of black carbon (BC) and ultrafine particles (UFPs) in urban roadway region will provide helpful information for improving road air pollution caused by vehicle emissions. For this purpose, we conducted daily observation of BC and UFPs at two trafficked sites (intersection and roadside), and a background site in Xi'an, China. The concentration data of BC and UFPs measured were combined with Aethalometer model and UFPs source apportion model, to determine and analyze the sources of BC in an urban road region. Further, the source and variation characteristics of primary and secondary UFPs at the roadside sites were clarified. The results showed that average BC concentrations at the intersection, roadside, and background were respectively 3577 ± 2771, 3078 ± 2343, and 1914 ± 1229 ng/m³. The BC source apportionment results revealed contribution rates of on-board fossil fuel combustion (BC_ff) at the intersection and near the road of ca. 78.7% and 73.6%, respectively. Moreover, the proportion of particles number concentrations directly emitted from vehicles and nucleated upon emission (47%) was lower than that of particles formed during the dilution and cooling of vehicle emissions and by in-situ new particle formation (53%) at the roadside site. At 49%, the proportion of primary particles number was slightly higher at the intersection. The impacts of new particle-formation events on the diurnal variation of secondary particles were explored. Generally, the majority of BC originated from traffic exhausts, while the secondary particles from non-traffic sources are dominant at the road intersections. By providing a better understanding of near-road pollution issues, this study's findings can be useful for taking effective regulatory efforts to improve air quality and reduce people's exposure to traffic-pollutants in an urban environment.

Assessment of Individual-Level Exposure to Airborne Particulate Matter during Periods of Atmospheric Thermal Inversion

Air pollution exposure is harmful to human health and reducing it at the level of an individual requires measurements and assessments that capture the spatiotemporal variability of different microenvironments and the influence of specific activities. In this paper, activity-specific and general indoor and outdoor exposure during and after a period of high concentrations of particulate matter (PM), e.g., an atmospheric thermal inversion (ATI) in the Ljubljana subalpine basin, Slovenia, was assessed. To this end, personal particulate matter monitors (PPM) were used, worn by participants of the H2020 ICARUS sampling campaigns in spring 2019 who also recorded their hourly activities. ATI period(s) were determined based on data collected from two meteorological stations managed by the Slovenian Environmental Agency (SEA). Results showed that indoor and outdoor exposure to PM was significantly higher during the ATI period, and that the difference between mean indoor and outdoor exposure to PM was much higher during the ATI period (23.0 µg/m3) than after (6.5 µg/m3). Indoor activities generally were associated with smaller differences, with cooking and cleaning even having higher values in the post-ATI period. On the other hand, all outdoor activities had higher PM values during the ATI than after, with larger differences, mostly >30.0 µg/m3. Overall, this work demonstrated that an individual-level approach can provide better spatiotemporal resolution and evaluate the relative importance of specific high-exposure events, and in this way provide an ancillary tool for exposure assessments.

Prediction of Short-Term Ultrafine Particle Exposures Using Real-Time Street-Level Images Paired with Air Quality Measurements

Within-city ultrafine particle (UFP) concentrations vary sharply since they are influenced by various factors. We developed prediction models for short-term UFP exposures using street-level images collected by a camera installed on a vehicle rooftop, paired with air quality measurements conducted during a large-scale mobile monitoring campaign in Toronto, Canada. Convolutional neural network models were trained to extract traffic and built environment features from images. These features, along with regional air quality and meteorology data were used to predict short-term UFP concentration as a continuous and categorical variable. A gradient boost model for UFP as a continuous variable achieved R² = 0.66 and RMSE = 9391.8#/cm³ (mean values for 10-fold cross-validation). The model predicting categorical UFP achieved accuracies for "Low" and "High" UFP of 77 and 70%, respectively. The presence of trucks and other traffic parameters were associated with higher UFPs, and the spatial distribution of elevated short-term UFP followed the distribution of single-unit trucks. This study demonstrates that pictures captured on urban streets, associated with regional air quality and meteorology, can adequately predict short-term UFP exposure. Capturing the spatial distribution of high-frequency short-term UFP spikes in urban areas provides crucial information for the management of near-road air pollution hot spots.

Air Quality Sensor Networks for Evidence-Based Policy Making: Best Practices for Actionable Insights

(1) Background: This work evaluated the usability of commercial “low-cost” air quality sensor systems to substantiate evidence-based policy making. (2) Methods: Two commercially available sensor systems (Airly, Kunak) were benchmarked at a regulatory air quality monitoring station (AQMS) and subsequently deployed in Kampenhout and Sint-Niklaas (Belgium) to address real-world policy concerns: (a) what is the pollution contribution from road traffic near a school and at a central city square and (b) do local traffic interventions result in quantifiable air quality impacts? (3) Results: The considered sensor systems performed well in terms of data capture, correlation and intra-sensor uncertainty. Their accuracy was improved via local re-calibration, up to data quality levels for indicative measurements as set in the Air Quality Directive (Uexp < 50% for PM and <25% for NO2). A methodological setup was proposed using local background and source locations, allowing for quantification of the (3.1) maximum potential impact of local policy interventions and (3.2) air quality impacts from different traffic interventions with local contribution reductions of up to 89% for NO2 and 60% for NO throughout the considered 3 month monitoring period; (4) Conclusions: Our results indicate that commercial air quality sensor systems are able to accurately quantify air quality impacts from (even short-lived) local traffic measures and contribute to evidence-based policy making under the condition of a proper methodological setup (background normalization) and data quality (recurrent calibration) procedure. The applied methodology and learnings were distilled in a blueprint for air quality sensor networks for replication actions in other cities.

Lung cell toxicity of co-exposure to airborne particulate matter and extremely low-frequency magnetic field

Although the toxic effects of urban airborne particulate matter (PM) have been known on lung cells, there is less attention to co-exposure to PM and extremely low frequency magnetic (ELF-MF) in occupational settings. The present study investigated the influences of PM and ELF-MF co-exposure on toxicity in human lung cells (A549).In this case, total PM (TPM) was evaluated according to NIOSH-0500. The TPM SiO₂ and metal contents were determined based on NIOSH-7602 and 7302, respectively. Besides, 900 mG ELF-MF exposure was simulated based on field measurements. The toxicity mechanisms were assessed by examining malondialdehyde, glutathione ratio, gene expression, and DNA strand breaks. Also, the toxicity indicators of the TPM samples were MDA generation, glutathione depletion, and DNA damage, and their impacts were analysed at doses below the LD₅₀ (4 µg).In addition, gene expression of OGG1 and MTH1 was upregulated after TPM exposure at the lowest dose (2 µg). But ITPA was upregulated in the presence of ELF-MF. The co-exposure to TPM and ELF-MF decreased oxidative stress and DNA damage levels compared to a single exposure to TPM.Although the ELF-MF reduced toxicity in response to TPM, this reduction was not lower than the unexposed cells.

Air Quality Sensors Systems as Tools to Support Guidance in Athletics Stadia for Elite and Recreational Athletes

While athletes have high exposures to air pollutants due to their increased breathing rates, sport governing bodies have little guidance to support events scheduling or protect stadium users. A key limitation for this is the lack of hyper-local, high time-resolved air quality data representative of exposures in stadia. This work aimed to evaluate whether air quality sensors can describe ambient air quality in Athletics stadia. Sensing nodes were deployed in 6 stadia in major cities around the globe, monitoring NO2, O3, NO, PM10, PM2.5, PM1, CO, ambient temperature, and relative humidity. Results demonstrated that the interpretation of hourly pollutant patterns, in combination with self-organising maps (SOMs), enabled the interpretation of probable emission sources (e.g., vehicular traffic) and of atmospheric processes (e.g., local vs. regional O formation). The ratios between PM size fractions provided insights into potential emission sources (e.g., local dust re-suspension) which may help design mitigation strategies. The high resolution of the data facilitated identifying optimal periods of the day and year for scheduling athletic trainings and/or competitions. Provided that the necessary data quality checks are applied, sensors can support stadium operators in providing athlete communities with recommendations to minimise exposure and provide guidance for event scheduling.

Ultrafine particle exposure for bicycle commutes in rush and non-rush hour traffic: A repeated measures study in Copenhagen, Denmark

Ultrafine particles (UFP), harmful to human health, are emitted at high levels from motorized traffic. Bicycle commuting is increasingly encouraged to reduce traffic emissions and increase physical activity, but higher breathing rates increase inhaled UFP concentrations while in traffic. We assessed exposure to UFP while cycling along a fixed 8.5 km inner-city route in Copenhagen, on weekdays over six weeks (from September to October 2020), during morning and afternoon rush-hour, as well as morning non-rush-hour, traffic time periods starting from 07:45, 15:45, and 09:45 h, respectively. Continuous measurements were made (each second) of particle number concentration (PNC) and location. PNC levels were summarized and compared across time periods. We used generalized additive models to adjust for meteorological factors, weekdays and trends. A total of 61 laps were completed, during 28 days (∼20 per time period). Overall mean PNC was 18,149 pt/cm³ (range 256-999,560 pt/cm³) with no significant difference between morning rush-hour (18003 pt/cm³), afternoon rush-hour (17560 pt/cm³) and late morning commute (17560 pt/cm³) [p = 0.85]. There was substantial spatial variation of UFP exposure along the route with highest PNC levels measured at traffic intersections (∼38,000-42000 pt/cm³), multiple lane roads (∼38,000-40000 pt/cm³) and construction sites (∼44,000-51000 pt/cm³), while lowest levels were measured at smaller streets, areas with open built environment (∼12,000 pt/cm³), as well as at a bus-only zone (∼15,000 pt/cm³). UFP exposure in inner-city Copenhagen did not differ substantially when bicycling in either rush-hour or non-rush-hour, or morning or afternoon, traffic time periods. UFP exposure varied substantially spatially, with highest concentrations around intersections, multiple lane roads, and construction sites. This suggests that exposure to UFP is not necessarily reduced by avoiding rush-hours, but by avoiding sources of pollution along the bicycling route.

Studies of the effectiveness of transport sector interventions in low- and middle-income countries: An evidence and gap map

Background

There are great disparities in the quantity and quality of infrastructure. European countries such as Denmark, Germany, Switzerland, and the UK have close to 200 km of road per 100 km2, and the Netherlands over 300 km per 100 km2. By contrast, Kenya and Indonesia have <30, Laos and Morocco <20, Tanzania and Bolivia <10, and Mauritania only 1 km per 100 km2. As these figures show, there is a significant backlog of transport infrastructure investment in both rural and urban areas, especially in sub-Saharan Africa. This situation is often exacerbated by weak governance and an inadequate regulatory framework with poor enforcement which lead to high costs and defective construction.The wellbeing of many poor people is constrained by lack of transport, which is called "transport poverty". Lucas et al. suggest that up to 90% of the world's population are transport poor when defined as meeting at least one of the following criteria: (1) lack of available suitable transport, (2) lack of transport to necessary destinations, (3) cost of necessary transport puts household below the income poverty line, (4) excessive travel time, or (5) unsafe or unhealthy travel conditions.

Objectives

The aim of this evidence and gap map (EGM) is to identify, map, and describe existing evidence from studies reporting the quantitative effects of transport sector interventions related to all means of transport (roads, rail, trams and monorail, ports, shipping, and inland waterways, and air transport).

Methods

The intervention framework of this EGM reframes Berg et al's three categories (infrastructure, prices, and regulations) broadly as infrastructure, incentives, and institutions as subcategories for each intervention category which are each mode of transport (road, rail trams and monorail, ports, shipping, and inlands waterways, and air transport). This EGM identifies the area where intervention studies have been conducted as well as the current gaps in the evidence base.This EGM includes ongoing and completed impact evaluations and systematic reviews (SRs) of the effectiveness of transport sector interventions. This is a map of effectiveness studies (impact evaluations). The impact evaluations include experimental designs, nonexperimental designs, and regression designs. We have not included the before versus after studies and qualitative studies in this map. The search strategies included both academic and grey literature search on organisational websites, bibliographic searches and hand search of journals.An EGM is a table or matrix which provides a visual presentation of the evidence in a particular sector or a subsector. The map is presented as a matrix in which rows are intervention categories (e.g., roads) and subcategories (e.g., infrastructure) and the column outcome domains (e.g., environment) and subcategories as (e.g., air quality). Each cell contains studies of the corresponding intervention for the relevant outcome, with links to the available studies. Included studies were coded according to the intervention and outcomes assessed and additional filters as region, population, and study design. Critical appraisal of included SR was done using A Measurement Tool to Assess Systematic Reviews (AMSTAR -2) rating scale.

Selection Criteria

The search included both academic and grey literature available online. We included impact evaluations and SRs that assessed the effectiveness of transport sector interventions in low- and middle-income countries.

Results

This EGM on the transport sector includes 466 studies from low- and middle-income countries, of which 34 are SRs and 432 impact evaluations. There are many studies of the effects of roads intervention in all three subcategories-infrastructure, incentives, and institutions, with the most studies in the infrastructure subcategories. There are no or fewer studies on the interventions category ports, shipping, and waterways and for civil aviation (Air Transport).In the outcomes, the evidence is most concentrated on transport infrastructure, services, and use, with the greatest concentration of evidence on transport time and cost (193 studies) and transport modality (160 studies). There is also a concentration of evidence on economic development and health and education outcomes. There are 139 studies on economic development, 90 studies on household income and poverty, and 101 studies on health outcomes.The major gaps in evidence are from all sectors except roads in the intervention. And there is a lack of evidence on outcome categories such as cultural heritage and cultural diversity and very little evidence on displacement (three studies), noise pollution (four studies), and transport equity (2). There is a moderate amount of evidence on infrastructure quantity (32 studies), location, land use and prices (49 studies), market access (29 studies), access to education facilities (23 studies), air quality (50 studies), and cost analysis including ex post CBA (21 studies).The evidence is mostly from East Asia and the Pacific Region (223 studies (40%), then the evidence is from the sub-Saharan Africa (108 studies), South Asia (96 studies), Latin America & Caribbean (79 studies). The least evidence is from Middle East & North Africa (30 studies) and Europe & Central Asia (20 studies). The most used study design is other regression design in all regions, with largest number from East Asia and Pacific (274). There is total 33 completed SRs identified and one ongoing, around 85% of the SR are rated low confidence, and 12% rated as medium confidence. Only one review was rated as high confidence. This EGM contains the available evidence in English.

Conclusion

This map shows the available evidence and gaps on the effectiveness of transport sector intervention in low- and middle-income countries. The evidence is highly concentrated on the outcome of transport infrastructure (especially roads), service, and use (351 studies). It is also concentrated in a specific region-East Asia and Pacific (223 studies)-and more urban populations (261 studies). Sectors with great development potential, such as waterways, are under-examined reflecting also under-investment.The available evidence can guide the policymakers, and government-related to transport sector intervention and its effects on many outcomes across sectors. There is a need to conduct experimental studies and quality SRs in this area. Environment, gender equity, culture, and education in low- and middle-income countries are under-researched areas in the transport sector.

Exposure to ultrafine particles while walking or bicycling during COVID-19 closures: A repeated measures study in Copenhagen, Denmark

Ultrafine particles (UFP; particulate matter <0.1 μm diameter) emitted from motorized traffic may be highly detrimental to health. Active mobility (walking, bicycling) is increasingly encouraged as a way to reduce traffic congestion and increase physical activity levels. However, it has raised concerns of increased exposure to UFP, due to increased breathing rates in traffic microenvironments, immediately close to their source. The recent Coronavirus Disease 2019 (COVID-19) societal closures reduced commuting needs, allowing a natural experiment to estimate contributions from motorized traffic to UFP exposure while walking or bicycling. From late-March to mid-July 2020, UFP was repeatedly measured while walking or bicycling, capturing local COVID-19 closure ('Phase 0') and subsequent phased re-opening ('Phase 1', '2', '2.1' & '3'). A DiSCmini continuously measured particle number concentration (PNC) in the walker/bicyclist's breathing zone. PNC while walking or bicycling was compared across phased re-openings, and the effect of ambient temperature, wind speed and direction was determined using regression models. Approximately 40 repeated 20-minute walking and bicycling laps were made over 4 months during societal re-opening phases related to the COVID-19 pandemic (late-March to mid-July 2020) in Copenhagen. Highest median PNC exposure of both walking (13,170 pt/cm³, standard deviation (SD): 3560 pt/cm³) and bicycling (21,477 pt/cm³, SD: 8964) was seen during societal closures (Phase 0) and decreased to 5367 pt/cm³ (SD: 2949) and 8714 pt/cm³ (SD: 4309) in Phase 3 of re-opening. These reductions in PNC were mainly explained by meteorological conditions, with most of the deviation explained by wind speed (14-22%) and temperature (10-13%). Highest PNC was observed along major roads and intersections. In conclusion, we observed decreases in UFP exposure while walking and bicycling during societal re-opening phases related to the COVID-19 pandemic, due largely to meteorological factors (e.g., wind speed and temperature) and seasonal variations in UFP levels.

Mobile monitoring and spatial prediction of black carbon in Cairo, Egypt

This study harnesses the power of mobile data in developing a spatial model for predicting black carbon (BC) concentrations within one of the most heavily populated regions in the Middle East and North Africa MENA region, Greater Cairo Region (GCR) in Egypt. A mobile data collection campaign was conducted in GCR to collect BC measurements along specific travel routes. In total, 3,300 km were travelled across a widespread 525 km of routes. Reported average BC values were around 20 µg/m³, announcing an alarming order of magnitude value when compared to the maximum reported values in similar studies. A bi-directional stepwise land use regression (LUR) model was developed to select the best combination of explanatory variables and generate an exposure surface for BC, in addition to a number of machine learning models (random forest gradient boost, light gradient boost model (LightGBM), Keras neural network (NN)). Data from 7 air quality (AQ) stations were compared-in terms of mean square error (MSE) and mean absolute error (MAE)-with predictions from the LUR and the NN model. The NN model estimated higher BC concentrations in the downtown areas, while lower concentrations are estimated for the peripheral area at the east side of the city. Such results shed light on the credibility of the LUR models in generating a general spatial trend of BC concentrations while the superiority of NN in BC accuracy estimation (0.023 vs 0.241 in terms of MSE and 0.12 vs 0.389 in terms of MAE; of NN vs LUR respectively).

The Effect of Route Choice in Children's Exposure to Ultrafine Particles Whilst Walking to School

Children walking to school are at a high risk of exposure to air pollution compared with other modes because of the time they spend in close proximity to traffic during their commute. The aim of this study is to investigate the effect of a walker's route choice on their exposure to ultrafine particles (UFP) on the walk to school. During morning commutes over a period of three weeks, exposure to UFP was measured along three routes: two routes were alongside both sides of a busy arterial road with significantly higher levels of traffic on one side compared to the other, and the third route passed through quiet streets (the background route). The results indicate that the mean exposure for the pedestrian walking along the background route was half the exposure experienced on the other two routes. Walkers on the trafficked side were exposed to elevated concentrations (>100,000 pt/cc) 2.5 times longer than the low-trafficked side. However, the duration of the elevated exposure for the background route was close to zero. Public health officials and urban planners may use the results of this study to promote healthier walking routes to schools, especially those planned as part of organized commutes.

Estimation of the Inhaled Dose of Pollutants in Different Micro-Environments: A Systematic Review of the Literature

Recently, the need to assess personal exposure in different micro-environments has been highlighted. Further, estimating the inhaled dose of pollutants is considerably one of the most interesting parameters to be explored to complete the fundamental information obtained through exposure assessment, especially if associated with a dose-response approach. To analyze the main results obtained from the studies related to the estimation of the inhaled dose of pollutants in different micro-environments (environments in which an individual spends a part of his day), and to identify the influence of different parameters on it, a systematic review of the literature was performed. The principal outcomes from the considered studies outlined that (i) exposure concentration and residence time are among the most important parameters to be evaluated in the estimation of the inhaled dose, especially in transport environments. Further, (ii) the pulmonary ventilation rate can be of particular interest during active commuting because of its increase, which increases the inhalation of pollutants. From a methodological point of view, the advent of increasingly miniaturized, portable and low-cost technologies could favor these kinds of studies, both for the measurement of atmospheric pollutants and the real-time evaluation of physiological parameters used for estimation of the inhaled dose. The main results of this review also show some knowledge gaps. In particular, numerous studies have been conducted for the evaluation (in terms of personal exposure and estimation of the inhaled dose) of different PM fractions: other airborne pollutants, although harmful to human health, are less represented in studies of this type: for this reason, future studies should be conducted, also considering other air pollutants, not neglecting the assessment of exposure to PM. Moreover, many studies have been conducted indoors, where the population spends most of their daily time. However, it has been highlighted how particular environments, even if characterized by a shorter residence time, can contribute significantly to the dose of inhaled pollutants. These environments are, therefore, of particular importance and should be better evaluated in future studies, as well as occupational environments, where the work results in a high pulmonary ventilation rate. The attention of future studies should also be focused on these categories of subjects and occupational studies.

Commuter PM exposure and estimated life-expectancy loss across multiple transportation modes in Xi'an, China

Commuters are reportedly exposed to severe traffic-related air pollution (TRAP) during their commuting trips. This study was designed and implemented to (1) compare particulate matter (PM) exposure across four common transportation modes; (2) examine and analyze various determining factors; and (3) estimate public health effects caused by commuting exposure to PM. All analyses and calculations were based on the experimental data collected from 13 volunteers, including heart-rate data on 336 commuting trips in four travel modes in Xi'an China. The results indicate highest PM exposure associated with cycling (average PM₁₀, PM_2.5 and PM_1.0 of 114.35, 72.37 and 56.51 μg/m³, respectively), followed by riding transit buses (116.29, 67.60 and 51.12 μg/m³ for the same pollutants, respectively), then taking a taxi (97.61, 58.87 and 45.11 μg/m³), and the lowest exposure onboard subways (55.86, 46.20 and 40.20 μg/m³). A multivariable linear regression model was used to examine major influences on PM concentration variations, with results corroborating significant PM variance across commuting modes, which is also affected by background pollution concentration and relative humidity. Further, years of life expectancy (YLE) loss were estimated using an inhalation dose model together with the life table method: cycling commuters experienced the greatest YLE loss (5.51-6.43 months per capita for the studied age group). During severe pollution periods, substituting other modes (like subway) for cycling could effectively avoid acute exposure. PM_2.5 levels in taxi cabins powered by CNG or methanol were comparatively lower, indicating that implementing alternative energy strategies could effectively lower traffic emissions and population exposure.

Particulate matter exposure at a densely populated urban traffic intersection and crosswalk

Exposure to elevated particulate matter (PM) pollution is of great concern to both the general public and air quality management agencies. At urban traffic intersections, for example, pedestrians are often at a higher risk of exposure to near-source PM pollution from traffic while waiting on the roadside or while walking in the crosswalk. This study offers an in-depth investigation of pedestrian exposure to PM pollution at an urban traffic intersection. Fixed-site measurements near an urban intersection were conducted to examine the variations in particles of various sizes through traffic signal cycles. This process aids in the identification of major PM dispersion patterns on the roadside. In addition, mobile measurements of pedestrian exposure to PM were conducted across six time intervals that correspond to different segments of a pedestrian's journey when passing through the intersection. Measurement results are used to estimate and compare the cumulative deposited doses of PM by size categories and journey segments for pedestrians at an intersection. Furthermore, comparisons of pedestrian exposure to PM on a sunny day and a cloudy day were analyzed. The results indicate the importance of reducing PM pollution at intersections and provide policymakers with a foundation for possible measures to reduce pedestrian PM exposure at urban traffic intersections.

Individual- and Household-Level Interventions to Reduce Air Pollution Exposures and Health Risks: a Review of the Recent Literature

PURPOSE OF REVIEW

We reviewed recent peer-reviewed literature on three categories of individual- and household-level interventions against air pollution: air purifiers, facemasks, and behavior change.

RECENT FINDINGS

High-efficiency particulate air/arresting (HEPA) filter air purifier use over days to weeks can substantially reduce fine particulate matter (PM2.5) concentrations indoors and improve subclinical cardiopulmonary health. Modeling studies suggest that the population-level benefits of HEPA filter air purification would often exceed costs. Well-fitting N95 and equivalent respirators can reduce PM2.5 exposure, with several randomized crossover studies also reporting improvements in subclinical cardiovascular health. The health benefits of other types of face coverings have not been tested and their effectiveness in reducing exposure is highly variable, depends largely on fit, and is unrelated to cost. Behavior modifications may reduce exposure, but there has been little research on health impacts. There is now substantial evidence that HEPA filter air purifiers reduce indoor PM2.5 concentrations and improve subclinical health indicators. As a result, their use is being recommended by a growing number of government and public health organizations. Several studies have also reported subclinical cardiovascular health benefits from well-fitting respirators, while evidence of health benefits from other types of facemasks and behavior changes remains very limited. In situations when emissions cannot be controlled at the source, such as during forest fires, individual- or household-level interventions may be the primary option. In most cases, however, such interventions should be supplemental to emission reduction efforts that benefit entire communities.

Influence of methodology on the estimation of the particle surface area dose received by a population in all-day activities

In everyday life, people are exposed to different concentrations of airborne particles depending on the microenvironment where they perform their different activities. Such exposure can lead to high sub-micron particle doses. The received dose depends on particle concentration to which people are exposed (typically expressed in terms of number or surface area), time spent in each activity or microenvironment (time activity pattern) and amount of air inhaled (inhalation rate). To estimate an actual value of the received dose, all these parameters should be measured under real-life conditions; in fact, the concentrations should be measured on a personal scale (i.e. through a direct exposure assessment), whereas time activity patterns and inhalation rates specific to the activity performed should be considered. The difficulties in obtaining direct measurements of these parameters usually lead to adopt time activity patterns and inhalation rates already available in scientific literature for typical populations, and local outdoor particle concentrations measured with fixed monitoring stations and extrapolated for all the other microenvironments. To overcome these limitations, we propose a full-field method for estimating the received dose of a population sample, in which all the parameters (concentration levels, time activity patterns and inhalation rates) are measured under real-life conditions (also including the inhalation rates, that were evaluated on the basis of the measured heart rates). Specifically, 34 volunteers were continuously monitored for seven days and the data of sub-micron particle concentrations, activities performed, and inhalation rates were recorded. The received dose was calculated with the proposed method and compared with those obtained from different simplified methodologies that consider typical data of particle concentrations, time activity patterns and inhalation rates obtained from literature. The results show that, depending on the methodology used, the differences in the received daily dose can be significant, with a general underestimation of the most simplified method.

The relationship between personal exposure and ambient PM2.5 and black carbon in Beijing

This study is part of the "Air Polluion Impacts on Cardiopulmonary disease in Beijing: an integrated study of Exposure Science, Toxicologenomics & Environmental Epidemiology (APIC-ESTEE)" project under the UK-China joint research programme "Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China)". The aim is to capture the spatio-temporal variability in people's exposure to fine particles (PM_2.5) and black carbon (BC) air pollution in Beijing, China. A total of 120 students were recruited for a panel study from ten universities in Haidian District in northwestern Beijing from December 2017 to June 2018. Real-time personal concentrations of PM_2.5 and BC were measured over a 24-h period with two research-grade portable personal exposure monitors. Personal microenvironments (MEs) were determined by applying an algorithm to the handheld GPS unit data. On average, the participants spent the most time indoors (79% in Residence and 16% in Workplace), and much less time travelling by Walking, Cycling, Bus and Metro. Similar patterns were observed across participant gender and body-mass index classifications. The participants were exposed to 33.8 ± 27.8 μg m^-3 PM_2.5 and to 1.9 ± 1.2 μg m^-3 BC over the 24-h monitoring period, on average 24.3 μg m^-3 (42%) and 0.8 μg m^-3 (28%) lower, respectively, than the concurrent fixed-site ambient measurements. Relative differences between personal and ambient BC concentrations showed greater variability across the MEs, highlighting significant contributions from Dining and travelling by Bus, which involve potential combustion of fuels. This study demonstrates the potential value of personal exposure monitoring in investigating air pollution related health effects, and in evaluating the effectiveness of pollution control and intervention measures.

A gradient boost approach for predicting near-road ultrafine particle concentrations using detailed traffic characterization

This study investigates the influence of meteorology, land use, built environment, and traffic characteristics on near-road ultrafine particle (UFP) concentrations. To achieve this objective, minute-level UFP concentrations were measured at various locations along a major arterial road in the Greater Toronto Area (GTA) between February and May 2019. Each location was visited five times, at least once in the morning, mid-day, and afternoon. Each visit lasted for 30 min, resulting in 2.5 h of minute-level data collected at each location. Local traffic information, including vehicle class and turning movements, were processed using computer vision techniques. The number of fast-food restaurants, cafes, trees, traffic signals, and building footprint, were found to have positive impacts on the mean UFP, while distance to the closest major road was negatively associated with UFP. We employed the Extreme Gradient Boosting (XGBoost) method to develop prediction models for UFP concentrations. The Shapley additive explanation (SHAP) measures were used to capture the influence of each feature on model output. The model results demonstrated that minute-level counts of local traffic from different directions had significant impacts on near-road UFP concentrations, model performance was robust under random cross-validation as coefficients of determination (R²) ranged from 0.63 to 0.69, but it revealed weaknesses when data at specific locations were eliminated from the training dataset. This result indicates that proper cross-validation techniques should be developed to better evaluate machine learning models for air quality predictions.

Athletes' exposure to air pollution during World Athletics Relays: A pilot study

Potential adverse consequences of exposure to air pollutants during exercise include decreased lung function, and exacerbation of asthma and exercise-induced bronchoconstriction. These effects are especially relevant for athletes and during international competitions, as they may impact athletic performance. Thus, assessing and mitigating exposure to air pollutants during exercising should be encouraged in sports venues. A comprehensive air quality assessment was carried out during the World Relays Yokohama 2019, in the stadium and the warm-up track. The pilot included on-line and off-line instrumentation for gaseous and particulate pollutants and meteorological parameters, and the comparison with local reference data. Air quality perception and exacerbation of symptoms of already-diagnosed diseases (mainly respiratory and cardiovascular) were assessed by athletes by means of questionnaires during training sessions. Median NO₂ concentrations inside the stadium (25.6-31.9 μgm^-3) were in the range of the Yokohama urban background, evidencing the impact of urban sources (e.g., traffic) on athletes' exposure during training and competition. The assessment of hourly air pollutant trends was identified as a valuable tool to provide guidance to reduce atheletes' exposure, by identifying the periods of the day with lowest ambient concentrations. This strategy could be adopted to define training and competition schedules, and would have special added value for athletes with respiratory conditions. Personal exposure to polycyclic aromatic hydrocarbons was quantified through wearable silicone wristbands, and showed highly variability across volunteers. The wristbands are a simple approach to assess personal exposure to potentially toxic organic compounds. Further research would be necessary with regard to specific air pollutants that may trigger or exacerbate respiratory conditions typical of the athlete community. The availability of high time-resolved exposure data in the stadiums opens up the possibility to calculate doses of specific pollutants for individual athletes in future athletics events, to understand the impact of environmental factors on athletic performance.

Ultrafine particles: Levels in ambient air during outdoor sport activities

Conducting aerobic activity on regular basis is recognised as one of the steps to maintain healthier lifestyle. The positive outcomes though can be outweighed if conducted in polluted atmosphere. Furthermore, the specific inhalation during exercising, which results in bypass of nasal filtration systems and deeper penetration into the respiratory system, might result in higher risks especially to pollutants such as ultrafine particles (UFP), which aerodynamic particle diameter are <100 nm. Thus, this work aims to evaluate UFP levels at sites used for conducting physical sport activities outdoors and to estimate the respective inhalation doses considering various scenarios and different physical activities. Monitoring of UFP was conducted during three weeks (May-June 2015) at four different sites (S1-S4) regularly used to conduct physical exercising. The results showed that UFP highly varied (medians 5.1-20.0 × 10³ # cm^-3) across the four sites, with the highest UFP obtained when exercising next to trafficked streets whereas S3 and S4 (a garden and city park) exhibited 2-4 times lower UFP. In view of the obtained UFP concentrations, the estimated inhalation doses ranged 1.73 × 10⁸-3.81 × 10⁸ # kg^-1 when conducting moderately intense sport activities and 1.93 × 10⁸-5.95 × 10⁸ # kg^-1 for highly intense ones. Highly intense activities (i.e. running) led to twice higher UFP exposure; children and youths (5-17 yrs old) experienced 203-267% higher doses. Considering the age- and gender- differences, estimated UFP doses of males were 1.1-2.8 times higher than of females. Finally, UFP inhalation doses estimated for walking (commuting to work and/or schools) were 1.6-7.5 times lower than when conducting sport activities. Thus to protect public health and to promote healthy and physically active lifestyle, strategies to minimize the negative impacts of air pollution should be developed and implemented.

Short-Term Impact of Traffic-Related Particulate Matter and Noise Exposure on Cardiac Function

Exposure to traffic-related air pollution and noise exposure contributes to detrimental effects on cardiac function, but the underlying short-term effects related to their simultaneous personal exposure remain uncertain. The aim is to assess the impact of total inhaled dose of particulate matter and total noise exposure on the variations of electrocardiogram (ECG) parameters between pre-cycling and post-cycling periods. Mid-June 2019, we collected four participants' personal exposure data related to traffic-related noise and particulate matter (PM_2.5 and PM₁₀) as well as ECG parameters. Several Bayesian linear models were built to examine a potential association between air pollutants and noise exposure and ECG parameters: heart rate (HR), standard deviation of the normal-to-normal intervals (SDNN), percentage of successive RR intervals that differ by more than 50 ms (pNN50), root mean square of successive RR interval differences (rMSSD), low-frequency power (LF), high-frequency power (HF), and ratio of low- to high-frequency power (LF/HF). We analyzed in total 255 5-min segments of RR intervals. We observed that per 1 µg increase in cumulative inhaled dose of PM_2.5 was associated with 0.48 (95% CI: 0.22; 15.61) increase in variation of the heart rate, while one percent of total noise dose was associated with 0.49 (95% CI: 0.17; 0.83) increase in variation of heart rate between corresponding periods. Personal noise exposure was no longer significant once the PM_2.5 was introduced in the whole model, whilst coefficients of the latter that were significant previously remained unchanged. Short-term exposure to traffic-related air and noise pollution did not, however, have an impact on heart rate variability.