Cyclist exposure to black carbon, ultrafine particles and heavy metals: An experimental study along two commuting routes near Antwerp, Belgium

Evaluation of a self-monitoring protocol for assessing soot and polycyclic aromatic hydrocarbon exposure among chimney sweeps

Traditional methods for measuring chemical exposure have challenges in terms of obtaining sufficient data; therefore, improved methods for better assessing occupational exposure are needed. One possible approach to mitigate these challenges is to use self-monitoring methods such as sensors, diaries, or biomarkers. In the present study, a self-monitored method for measuring soot exposure, which included real-time air monitoring, a work diary, and the collection of urine samples, was evaluated. To validate the method, exposure measurements during the workday and diary entries were compared with velocities calculated from GPS tracking and the expected polycyclic aromatic hydrocarbon (PAH) metabolite patterns in urine. The method was applied with chimney sweeps, an occupational group at a high risk of many severe health outcomes and for whom effective control measures for reducing exposure are needed. In the study, 20 chimney sweeps followed a self-monitoring protocol for 8 consecutive workdays. Personal exposure to soot was measured as black carbon (BC) using micro-aethalometers. A diary was used to record the work tasks performed, and urine samples were collected and analysed for PAH metabolites. From the expected 160 full day measurements, 146 (91%) BC measurements and 149 (93%) diaries were collected. From the expected 320 urine samples, 304 (95%) were collected. The tasks noted in the diaries overlapped with information obtained from the GPS tracking of the chimney sweeps, which covered 96% of the measurement time. The PAH metabolites in urine increased during the work week. Factors believed to have positively influenced the sample collection and task documentation were the highly motivated participants and the continuous presence of trained occupational hygiene professionals during the planning of the study and throughout the measurement stage, during which they were available to inform, instruct, and address questions. In conclusion, the self-monitored protocol used in this study with chimney sweeps is a valuable and valid method that can be used to collect larger numbers of samples. This is especially valuable for occupations in which the employees are working independently and the exposure is difficult to monitor with traditional occupational hygiene methods.

Portable Sensors for Dynamic Exposure Assessments in Urban Environments: State of the Science

This study presents a fit-for-purpose lab and field evaluation of commercially available portable sensor systems for PM, NO2, and/or BC. The main aim of the study is to identify portable sensor systems that are capable of reliably quantifying dynamic exposure gradients in urban environments. After an initial literature and market study resulting in 39 sensor systems, 10 sensor systems were ultimately purchased and benchmarked under laboratory and real-word conditions. We evaluated the comparability to reference analyzers, sensor precision, and sensitivity towards environmental confounders (temperature, humidity, and O3). Moreover, we evaluated if the sensor accuracy can be improved by applying a lab or field calibration. Because the targeted application of the sensor systems under evaluation is mobile monitoring, we conducted a mobile field test in an urban environment to evaluate the GPS accuracy and potential impacts from vibrations on the resulting sensor signals. Results of the considered sensor systems indicate that out-of-the-box performance is relatively good for PM (R2 = 0.68-0.9, Uexp = 16-66%, BSU = 0.1-0.7 µg/m3) and BC (R2 = 0.82-0.83), but maturity of the tested NO2 sensors is still low (R2 = 0.38-0.55, Uexp = 111-614%) and additional efforts are needed in terms of signal noise and calibration, as proven by the performance after multilinear calibration (R2 = 0.75-0.83, Uexp = 37-44%)). The horizontal accuracy of the built-in GPS was generally good, achieving <10 m accuracy for all sensor systems. More accurate and dynamic exposure assessments in contemporary urban environments are crucial to study real-world exposure of individuals and the resulting impacts on potential health endpoints. A greater availability of mobile monitoring systems capable of quantifying urban pollutant gradients will further boost this line of research.

Dynamic and stationary monitoring of air pollutant exposures and dose during marathons

Marathon running significantly increases breathing volumes and, consequently, air pollution inhalation doses. This is of special concern for elite athletes who ventilate at very high rates. However, race organizers and sport governing bodies have little guidance to support events scheduling to protect runners. A key limitation is the lack of hyper-local, high temporal resolution air quality data representative of exposure along the racecourse. This work aimed to understand the air pollution exposures and dose inhaled by athletes, by means of a dynamic monitoring methodology designed for road races. Air quality monitors were deployed during three marathons, monitoring nitrogen dioxide (NO2), ozone (O3), particulate matter (PMx), air temperature, and relative humidity. One fixed monitor was installed at the Start/Finish line and one mobile monitor followed the women elite runner pack. The data from the fixed monitors, deployed prior the race, described daily air pollution trends. Mobile monitors in combination with heatmap analysis facilitated the hyper-local characterization of athletes' exposures and helped identify local hotspots (e.g., areas prone to PM resuspension) which should be preferably bypassed. The estimation of inhaled doses disaggregated by gender and ventilation showed that doses inhaled by last finishers may be equal or higher than those inhaled by first finishers for O3 and PMx, due to longer exposures as well as the increase of these pollutants over time (e.g., 58.2 ± 9.6 and 72.1 ± 23.7 μg of PM2.5 for first and last man during Rome marathon). Similarly, men received significantly higher doses than women due to their higher ventilation rate, with differences of 31-114 μg for NO2, 79-232 μg for O3, and 6-41 μg for PMx. Finally, the aggregated data obtained during the 4 week- period prior the marathon can support better race scheduling by the organizers and provide actionable information to mitigate air pollution impacts on athletes' health and performance.

Exploring the triple burden of social disadvantage, mobility poverty, and exposure to traffic-related air pollution

Understanding the relationships between ultrafine particle (UFP) exposure, socioeconomic status (SES), and sustainable transportation accessibility in Toronto, Canada is crucial for promoting public health, addressing environmental justice, and ensuring transportation equity. We conducted a large-scale mobile measurement campaign and employed a gradient boost model to generate exposure surfaces using land use, built environment, and meteorological conditions. The Ontario Marginalization Index was used to quantify various indicators of social disadvantage for Toronto's neighborhoods. Our findings reveal that people in socioeconomically disadvantaged areas experience elevated UFP exposures. We highlight significant disparities in accessing sustainable transportation, particularly in areas with higher ethnic concentrations. When factoring in daily mobility, UFP exposure disparities in disadvantaged populations are further exacerbated. Furthermore, individuals who do not generate emissions themselves are consistently exposed to higher UFPs, with active transportation users experiencing the highest UFP exposures both at home and at activity locations. Finally, we proposed a novel index, the Community Prioritization Index (CPI), incorporating three indicators, including air quality, social disadvantage, and sustainable transportation. This index identifies neighborhoods experiencing a triple burden, often situated near major infrastructure hubs with high diesel truck activity and lacking greenspace, marking them as high-priority areas for policy action and targeted interventions.

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.

Whether cycling around the city is in fact healthy in the light of air quality - Results of black carbon

Studying the air quality and exposure of the inhabitants of urban agglomerations to pollution is the basis for the creation and development of more sustainable cities. Although research on black carbon (BC) has not yet reached the official acceptable levels and guidelines, the World Health Organization clearly indicates the need to measure and control the level of this pollutant. In Poland, monitoring of the level of BC concentration is not included in the air quality monitoring network. To estimate the extent of this pollutant to which pedestrians and cyclists are exposed, mobile measurements were carried out on over 26 km of bicycle paths in Wrocław. The obtained results indicate the influence of urban greenery next to the bicycle path (especially if the cyclist is separated from the street lane by hedges or other tall plants) and the 'breathability' (i.e., associated with surrounding infrastructure) of the area on the obtained concentrations; the average concentration of BC in such places ranged from 1.3 to 2.2 μg/m³, whereas a cyclist riding directly on bike paths adjacent to the main roads in the city center is exposed to concentrations in the range of 2.3-14 μg/m³. The results of the measurements, also related to stationary measurements made at a selected point of one of the routes, clearly indicate the importance of the infrastructure surrounding the bicycle paths, their location, and the impact of urban traffic on the obtained BC concentrations. The results presented in our study are based only on short-term-field campaigns preliminary studies. To determine the quantitative impact of the characteristics of the bicycle route on the concentration of pollutants, and thus the exposure of users, the systematized research should cover a greater part of the city and be representative in terms of various hours of the day.

Mobile measurements of black carbon: Comparison of normal traffic with reduced traffic conditions during COVID-19 lock-down

A mobile monitoring campaign was conducted (by bicycle) to assess the black carbon (BC) concentrations in Cluj-Napoca city, Romania, in 2020, before, during and after COVID-19 lock-down. Over the entire study period, the BC concentrations ranged between 1.0 and 25.9 μg/m³ (averaged per street section and period characterized by different traffic conditions). Marked spatial and temporal differences were observed. Observed differences in BC concentrations between locations are attributed to traffic intensities, with average BC concentrations, under normal circumstances, of 6.6-14.3 μg/m³ at roads with high to intense traffic, compared to 2.8-3.1 μg/m³ at areas with reduced traffic, such as residential areas, parks and pedestrian streets. The COVID-19 measures impacted traffic volumes, and hence average BC concentrations decreased from 5.9 μg/m³ to 3.0 μg/m³ during lock-down and in a lower extent to 3.4 μg/m³ and 4.4 μg/m³ in post-lockdown periods with reduced and more normalized traffic. Two approaches to account for variations in background concentrations when comparing different situations in time are assessed. Subtracting background concentrations that are measured at background sites along the monitoring route is an appropriate method to assess spatio-temporal differences in concentrations. A reduction of about 1-2 μg/m³ was observed for the streets with low to medium traffic, and up to 6 μg/m³ at high traffic locations under lockdown. The approach presented in this study, using mobile measurements, is useful to understand the personal exposure to BC along the roads in different seasons and the influence of traffic reduction on BC pollution during prolonged restrictions. All these will support policymakers to reduce pollution and achieve EU directives targets and WHO recommendations.

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.

Evaluating the Meteorological Effects on the Urban Form-Air Quality Relationship Using Mobile Monitoring

Predictive models based on mobile measurements have been increasingly used to understand the spatiotemporal variations of intraurban air quality. However, the effects of meteorological factors, which significantly affect the dispersion of air pollution, on the urban-form-air-quality relationship have not been understood on a granular level. We attempt to fill this gap by developing predictive models of particulate matter (PM) in the Bronx (New York City) using meteorological and urban form parameters. The granular PM data was collected by mobile low-cost sensors as the ground truth. To evaluate the effects of meteorological factors, we compared the performance of models using the urban form within fixed and wind-sensitive buffers, respectively. We find better predictive power in the wind-sensitive group (R = 0.85) for NC₁₀ (number concentration for particles with diameters of 1 μm-10 μm) than the control group (R = 0.01), and modest improvements for PM_2.5 (R = 0.84 for the wind sensitive group, R = 0.77 for the control group), indicating that incorporating meteorological factors improved the predictive power of our models. We also found that urban form factors account for 62.95% of feature importance for NC₁₀ and 14.90% for PM_2.5 (9.99% and 4.91% for 3-D and 2-D urban form factors, respectively) in our Random Forest models. It suggests the importance of incorporating urban form factors, especially for the uncommonly used 3-D characteristics, in estimating intraurban PM. Our method can be applied in other cities to better capture the influence of urban context on PM levels.

Fine-Grained Urban Air Quality Mapping from Sparse Mobile Air Pollution Measurements and Dense Traffic Density

Urban air quality mapping has been widely applied in urban planning, air pollution control and personal air pollution exposure assessment. Urban air quality maps are traditionally derived using measurements from fixed monitoring stations. Due to high cost, these stations are generally sparsely deployed in a few representative locations, leading to a highly generalized air quality map. In addition, urban air quality varies rapidly over short distances (<1 km) and is influenced by meteorological conditions, road network and traffic flow. These variations are not well represented in coarse-grained air quality maps generated by conventional fixed-site monitoring methods but have important implications for characterizing heterogeneous personal air pollution exposures and identifying localized air pollution hotspots. Therefore, fine-grained urban air quality mapping is indispensable. In this context, supplementary low-cost mobile sensors make mobile air quality monitoring a promising alternative. Using sparse air quality measurements collected by mobile sensors and various contextual factors, especially traffic flow, we propose a context-aware locally adapted deep forest (CLADF) model to infer the distribution of NO2 by 100 m and 1 h resolution for fine-grained air quality mapping. The CLADF model exploits deep forest to construct a local model for each cluster consisting of nearest neighbor measurements in contextual feature space, and considers traffic flow as an important contextual feature. Extensive validation experiments were conducted using mobile NO2 measurements collected by 17 postal vans equipped with low-cost sensors operating in Antwerp, Belgium. The experimental results demonstrate that the CLADF model achieves the lowest RMSE as well as advances in accuracy and correlation, compared with various benchmark models, including random forest, deep forest, extreme gradient boosting and support vector regression.

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.

Children's exposure to BC and PM pollution, and respiratory tract deposits during commuting trips to school

Although children have been identified as a vulnerable group highly susceptible to traffic-related air pollution, their exposure during school commutes to traffic-related pollutants and the relevant health impact is rarely studied. In this study, we measured black carbon (BC) and particulate matter (PM: PM₁, PM_2.5, and PM₁₀) concentrations that children are exposed to during their multi-modal (walking, private cars, and e-bikes) commuting trips to schools in Xi'an, China. A multi-parameter inhalation rate assessment model was developed in combination with the Multi-Path Particle Dosimetry (MPPD) model to quantify the deposition dose in different parts of children's respiratory system (head, tracheobronchial (TB), pulmonary (PUL)). Results show that walking to school exposed children to the lowest PM₁, PM_2.5, and BC concentrations, whereas riding an e-bike led to significantly elevated exposure to PM₁ and BC than the other two modes. This is due to children's closer proximity to vehicle tail pipe emissions when they bike to school on road or roadside. The PM and BC concentrations showed remarkable increases in comparison to background concentrations during children's school commutes. Urban background (UB) concentration, traffic volume (TV), time of day, and meteorological parameters could influence a child's personal exposure, and the impact of each factor vary across different transportation modes. Particle size of the pollutant affects its deposition site in the respiratory system. Deposition fractions (DFs) and deposition doses in the head region (DF > 50%) were the highest for PM and BC, for which fine particles (BC, PM₁, and PM_2.5) were then most easily deposited in the PUL region while coarse particles rarely reach PUL. Children inhaled higher doses of polluted air during active commuting (walking) than passive commuting (private cars, e-bikes), due to longer times of exposure coupled with more active breathing.

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.

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.

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.

Environmental exposure during travel: A research review and suggestions forward

Daily travel through the urban fabric exposes urban dwellers to a range of environmental conditions that may have an impact on their health and wellbeing. Knowledge about exposures during travel, their associations with travel behavior, and their social and health outcomes are still limited. In our review, we aim to explain how the current environmental exposure research addresses the interactions between human and environmental systems during travel through their spatial, temporal and contextual dimensions. Based on the 104 selected studies, we identify significant recent advances in addressing the spatiotemporal dynamics of exposure during travel. However, the conceptual and methodological framework for understanding the role of multiple environmental exposures in travel environments is still in an early phase, and the health and wellbeing impacts at individual or population level are not well known. Further research with greater geographical balance is needed to fill the gaps in the empirical evidence, and linking environmental exposures during travel with the causal health and wellbeing outcomes. These advancements can enable evidence-based urban and transport planning to take the next step in advancing urban livability.

Assessment of Home-Based and Mobility-Based Exposure to Black Carbon in an Urban Environment: A Pilot Study

The combustion of fossil fuels is a significant source of particulate-bound black carbon (BC) in urban environments. The personal exposure (PE) of urban dwellers to BC and subsequent health impacts remain poorly understood due to a lack of observational data. In this study, we assessed and quantified the levels of PE to BC under two exposure scenarios (home-based and mobility-based exposure) in the city of Trivandrum in India. In the home-based scenario, the PE to BC was assessed in a naturally ventilated building over 24 h each day during the study period while in the mobility-based scenario, the PE to BC was monitored across diverse microenvironments (MEs) during the day using the same study protocol for consistency. Elevated BC concentrations were observed during the transport by motorcycle (26.23 ± 2.33 µg/m³) and car (17.49 ± 2.37 µg/m³). The BC concentrations observed in the MEs decreased in the following order: 16.58 ± 1.38 µg/m³ (temple), 13.78 ± 2.07 µg/m³ (restaurant), 11.44 ± 1.37 µg/m³ (bus stop), and 8.27 ± 1.88 µg/m³ (home); the standard deviations represent the temporal and spatial variations of BC concentrations. Overall, a relatively larger inhaled dose of BC in the range of 148.98–163.87 µg/day was observed for the mobility-based scenario compared to the home-based one (118.10–137.03 µg/day). This work highlights the importance of reducing PE to fossil fuel-related particulate emissions in cities for which BC is a good indicator. The study outcome could be used to formulate effective strategies to improve the urban air quality as well as public health.

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.

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.

Modelling Cyclists’ Multi-Exposure to Air and Noise Pollution with Low-Cost Sensors—The Case of Paris

Cyclists are particularly exposed to air and noise pollution because of their higher ventilation rate and their proximity to traffic. However, few studies have investigated their multi-exposure and have taken into account its real complexity in building statistical models (nonlinearity, pseudo replication, autocorrelation, etc.). We propose here to model cyclists’ exposure to air and noise pollution simultaneously in Paris (France). Specifically, the purpose of this study is to develop a methodology based on an extensive mobile data collection using low-cost sensors to determine which factors of the urban micro-scale environment contribute to cyclists’ multi-exposure and to what extent. To this end, we developed a conceptual framework to define cyclists’ multi-exposure and applied it to a multivariate generalized additive model with mixed effects and temporal autocorrelation. The results show that it is possible to reduce cyclists’ multi-exposure by adapting the planning and development practices of cycling infrastructure, and that this reduction can be substantial for noise exposure.

Impact of urban street canyon architecture on local atmospheric pollutant levels and magneto-chemical PM10 composition: An experimental study in Antwerp, Belgium

As real-life experimental data on natural ventilation of atmospheric pollution levels in urban street canyons is still scarce and has proven to be complex, this study, experimentally evaluated the impact of an urban street canyon opening on local atmospheric pollution levels, during a 2-week field campaign in a typical urban street canyon in Antwerp, Belgium. Besides following up on atmospheric particulate matter (PM), ultrafine particles (UFPs) and black carbon (BC) levels, the magneto-chemical PM₁₀ composition was quantified to identify contributions of specific elements in enclosed versus open street canyon sections. Results indicated no higher overall PM, UFP and BC concentrations at the enclosed site compared to the open site, but significant day-to-day variability between both monitoring locations, depending on the experienced wind conditions. On days with oblique wind regimes (4 out of 14), natural ventilation was observed at the open location while higher element contributions of Ca, Fe, Co, Ni, Cu, Zn and Sr were exhibited at the enclosed location. Magnetic properties correlated with the PM₁₀ filter loading, and elemental content of Fe, Cr, Mn and Ti. Magnetic bivariate ratios identified finel-grained magnetite carriers with grain sizes below 0.1 μm, indicating similar magnetic source contributions at both monitoring locations. Our holistic approach, combining atmospheric monitoring with magneto-chemical PM characterization has shown the complex impact of real-life wind flow regimes, different source contributions and local traffic dynamics on the resulting pollutant concentrations and contribute to a better understanding on the urban ventilation processes of atmospheric pollution.

Development of a land use regression model for black carbon using mobile monitoring data and its application to pollution-avoiding routing

Black carbon is often used as an indicator for combustion-related air pollution. In urban environments, on-road black carbon concentrations have a large spatial variability, suggesting that the personal exposure of a cyclist to black carbon can heavily depend on the route that is chosen to reach a destination. In this paper, we describe the development of a cyclist routing procedure that minimizes personal exposure to black carbon. Firstly, a land use regression model for predicting black carbon concentrations in an urban environment is developed using mobile monitoring data, collected by cyclists. The optimal model is selected and validated using a spatially stratified cross-validation scheme. The resulting model is integrated in a dedicated routing procedure that minimizes personal exposure to black carbon during cycling. The best model obtains a coefficient of multiple correlation of R=0.520. Simulations with the black carbon exposure minimizing routing procedure indicate that the inhaled amount of black carbon is reduced by 1.58% on average as compared to the shortest-path route, with extreme cases where a reduction of up to 13.35% is obtained. Moreover, we observed that the average exposure to black carbon and the exposure to local peak concentrations on a route are competing objectives, and propose a parametrized cost function for the routing problem that allows for a gradual transition from routes that minimize average exposure to routes that minimize peak exposure.

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.

Personal exposure to black carbon in Stockholm, using different intra-urban transport modes

The traffic microenvironment has been shown to be a major contributor to the total personal exposure of black carbon (BC), and is key to local actions aiming at reducing health risks associated with such exposure. The main aim of the study was to get a better understanding of the determinants of traffic-related personal exposure to BC in an urban environment. Personal exposure to ambient levels of BC was monitored while walking, cycling and traveling by bus or car along four streets and while cycling alternative routes simultaneously. Monitoring was performed during morning and afternoon peak hours and at midday, with a portable aethalometer recording one-minute mean values. In all, >4000 unique travel passages were performed. Stepwise Linear Regression was used to assess predictors to personal exposure levels of BC. The personal BC concentration ranged 0.03-37 μg/m³. The average concentrations were lowest while walking (1.7 μg/m³) and highest traveling by bus (2.7 μg/m³). However, only 22% of the variability could be explained by travel mode, urban background BC and wind speed. BC concentrations measured inside a car were on average 33% lower than measured simultaneously outside the car. Choosing an alternative bicycle route with less traffic resulted in up to 1.4 μg/m³ lower personal exposure concentrations. In conclusion, traveling by bus rendered the highest personal BC concentrations. But when taking travel time and inhalation rate into account, the travel-related exposure dose was predicted to be highest during walking and cycling. It is however probable that the benefits from physical activity outweigh health risks associated with this higher exposure dose. It is clear that road traffic makes an important contribution to personal exposure to BC regardless of mode of intra-urban transport. Our data suggest that commuting along routes with lower BC levels would substantially decrease commuter's exposure.

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

With the promotion of bicycle sharing, cycling as an active transportation mode is a matter of public interest. However, cyclists' recurrent exposure to traffic-related air pollution is associated with the potential health risks. Quantification of the health risks associated with daily exposure of commuting cyclists to atmospheric pollutants is vital, but barely reported. In this study, real-time mobile measurement campaigns were performed with high time-resolution portable instruments, along two commuting routes in Xi'an, China. We investigated personal exposure and inhaled dose of particulate matter and ultrafine particle (UFP) for cyclists. The results showed cyclists' exposure to average pollutants concentrations: fine particulate matter (PM_2.5, 38.6 ± 17.1 μg m^-3) and UFP (18,172 ± 11,282 particles cm^-3). The exposure "hotspots" of cyclists were identified: intersections, diesel engines, etc. Cyclists' exposure to the highest PM_2.5 (46.9  μg m^-3) concentrations were observed in morning periods; these were ∼36%/42% higher compared to the afternoon or evening, while the latter periods corresponded to higher UFP concentrations (18,342/18,502 particles cm^-3). The measurements of PM_2.5 and UFP were clearly higher during autumn months, when compared to summer months. In multivariate models, wind speed was not significant, temperature and local urban background concentrations explained 70.9% the variation of PM_2.5, the 67.8% of UFP was explained by temperature, traffic and relative humidity, and each 100 increase in on-road vehicles were associated with increase of 1328 particles cm^-3 for UFP exposure in cyclists. Cycling in bike boulevards decreased exposure concentrations by 31.5% for PM and 36.6% for UFP compared to traffic roadsides, moving vehicles were identified as key contributors to PM_0.25-0.3 and PM_2.0-10 of cyclists' exposure. The potential health risks deserve attention under the mobility and air pollution challenges faced by many metropolitan areas in emerging economies. Our findings could serve to promote better design for low-exposure network of separated bike boulevards.