Impact of bicycle route type on exposure to traffic-related air pollution

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.

Quantifying the contribution of environmental variables to cyclists' exposure to PM2.5 using machine learning techniques

Cyclists are particularly vulnerable to travel-related exposure to air pollution. Understanding the factors that increase exposure is crucial for promoting healthier urban environments. Machine learning models have successfully predicted air pollutant concentrations, but they tend to be less interpretable than classical statistical ones, such as linear models. This study aimed to develop a predictive model to assess cyclists' exposure to fine particulate matter (PM2.5) in urban environments. The model was generated using geo-temporally referenced data and machine learning techniques. We explored several models and found that the gradient boosting machine learning model best fitted the PM2.5 predictions, with a minimum root mean square error value of 5.62 μg m-3. The variables with greatest influence on cyclist exposure were the temporal ones (month, day of the week, and time of the day), followed by meteorological variables, such as temperature, relative humidity, wind speed, wind direction, and atmospheric pressure. Additionally, we considered relevant attributes, which are partially linked to spatial characteristics. These attributes encompass street typology, vegetation density, and the flow of vehicles on a particular street, which quantifies the number of vehicles passing a given point per minute. Mean PM2.5 concentration was lower in bicycle paths away from vehicular traffic than in bike lanes along streets. These outcomes underscore the need to thoughtfully design public transportation routes, including bus routes, concerning the network of bicycle pathways. Such strategic planning attempts to improve the air quality in urban landscapes.

Air pollution perception bias: Mismatch between air pollution exposure and perception of air quality in real-time contexts

Air pollution perception biases hinder the public's awareness of actual air quality. Past studies that examined the association and mismatch between actual and perceived air quality neglected individuals' dynamic exposure and their activity, travel, spatial, temporal, and social contexts. Using data collected with real-time air pollutant sensors and ecological momentary assessment (EMA), this study investigated the association and mismatch between momentary air pollution exposure and perceived air quality. It also examined how activity type, travel mode, spatial and temporal contexts, and social factors contribute to this disparity. The results show that exposure to air pollution is significantly higher in residential areas (1.777 μg/m3) and transportation land-use areas (2.863 μg/m3) compared to commercial areas. Exposure in the evening is 1.308 μg/m3 higher than in the afternoon. Working or studying activities are associated with 2.863 μg/m3 lower exposure, and individuals perceive air quality as good when working or studying and in residential areas. Conversely, individuals assess air quality as poor in railway travel contexts and being accompanied by friends. This study also reveals the nonstationary association between air pollution exposure and perceived air quality. The odds of underestimating air pollution are 1.8-2.7 times as high as that in residential areas and 2.1 to 2.6 times that in transportation land-use areas when compared to commercial areas. Implementing targeted mitigation measures in these contexts can enhance public awareness of 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.

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.

Prioritizing Street Tree Planting Locations to Increase Benefits for All Citizens: Experience From Joliette, Canada

As the climate continues to warm and the world becomes more urbanized, our reliance on trees and the benefits they provide is rapidly increasing. Many cities worldwide are planting trees to offset rising temperatures, trap pollutants, and enhance environmental and human health and well-being. To maximize the benefits of planting trees and avoid further increasing social inequities, a city needs to prioritize where to establish trees by first identifying those areas of greatest need. This work aims to demonstrate a spatially explicit approach for cities to determine these priority locations to achieve the greatest returns on specific benefits. Criteria for prioritization were developed in tandem with the City of Joliette, Canada, and based on nine indicators: surface temperature, tree density, vegetation cover, resilience, tree size and age, presence of species at risk, land use type, socioeconomic deprivation, and potential for active transportation. The City’s preferences were taken into account when assigning different weights to each indicator. The resulting tree planting priority maps can be used to target street tree plantings to locations where trees are needed most. This approach can be readily applied to other cities as these criteria can be adjusted to accommodate specific tree canopy goals and planning constraints. As cities are looking to expand tree canopy, we hope this work will assist in sustaining and growing their urban forest, enabling it to be more resilient and to keep providing multiple and sustained benefits where they are needed the most.

Integrating health indicators into urban and transport planning: A narrative literature review and participatory process

Today, urban and transport planners face considerable challenges in designing and retrofitting cities that are prepared for increasing urban populations, and their service and mobility needs. When it comes to health-promoting urban and transport developments, there is also a lack of standardized, quantitative indicators to guide the integration of health components right from the outset, i.e. in the formal planning or zoning phase. We narratively reviewed the literature and organized stakeholder workshops to identify and tailor planning principles and indicators that can be linked to health outcomes. We defined four core planning objectives that previous authoritative studies have suggested to result in positive health outcomes among city dwellers, which are: I) development of compact cities, II) reduction of private motorized transport, III) promotion of active (i.e. walking and cycling) and public transport, IV) development of green and public open space. Built on the review and stakeholder consensus, we identified 10 urban and transport planning principles that work towards achieving the four core objectives thought to provide health benefits for European city dwellers. These 10 planning principles are: 1) land use mix, 2) street connectivity, 3) density, 4) motorized transport reductions, 5) walking, 6) cycling, 7) public transport, 8) multi-modality, 9) green and public open space, and 10) integration of all planning principles. A set of indicators was developed and tailored for each planning principle. The final output of this work is a checklist ready to be applied by urban and transport professionals to integrate health into urban and transport developments in urban environments right from the outset.

Air pollution, physical activity and health: A mapping review of the evidence

BACKGROUND

Exposure to air pollution and physical inactivity are both significant risk factors for non-communicable diseases (NCDs). These risk factors are also linked so that the change in exposure in one will impact risks and benefits of the other. These links are well captured in the active transport (walking, cycling) health impact models, in which the increases in active transport leading to increased inhaled dose of air pollution. However, these links are more complex and go beyond the active transport research field. Hence, in this study, we aimed to summarize the empirical evidence on the links between air pollution and physical activity, and their combined effect on individual and population health.

OBJECTIVES AND METHODS

We conducted a non-systematic mapping review of empirical and modelling evidence of the possible links between exposure to air pollution and physical activity published until Autumn 2019. We reviewed empirical evidence for the (i) impact of exposure to air pollution on physical activity behaviour, (ii) exposure to air pollution while engaged in physical activity and (iii) the short-term and (iv) long-term health effects of air pollution exposure on people engaged in physical activity. In addition, we reviewed (v) public health modelling studies that have quantified the combined effect of air pollution and physical activity. These broad research areas were identified through expert discussions, including two public events performed in health-related conferences.

RESULTS AND DISCUSSION

The current literature suggests that air pollution may decrease physical activity levels during high air pollution episodes or may prevent people from engaging in physical activity overall in highly polluted environments. Several studies have estimated fine particulate matter (PM2.5) exposure in active transport environment in Europe and North-America, but the concentration in other regions, places for physical activity and for other air pollutants are poorly understood. Observational epidemiological studies provide some evidence for a possible interaction between air pollution and physical activity for acute health outcomes, while results for long-term effects are mixed with several studies suggesting small diminishing health gains from physical activity due to exposure to air pollution for long-term outcomes. Public health modelling studies have estimated that in most situations benefits of physical activity outweigh the risks of air pollution, at least in the active transport environment. However, overall evidence on all examined links is weak for low- and middle-income countries, for sensitive subpopulations (children, elderly, pregnant women, people with pre-existing conditions), and for indoor air pollution.

CONCLUSIONS

Physical activity and air pollution are linked through multiple mechanisms, and these relations could have important implications for public health, especially in locations with high air pollution concentrations. Overall, this review calls for international collaboration between air pollution and physical activity research fields to strengthen the evidence base on the links between both and on how policy options could potentially reduce risks and maximise health benefits.

[Evaluation of cyclists exposure to air pollution: a literature review]

OBJECTIVES

To describe and interpret the methodologies and results of the main studies related to the monitoring of exposure of cyclists to air pollution.

METHODS

Research and analysis of national and international research of the last ten years in the Cochrane, Scopus, Embase, Science Direct and Pubmed databases. The search was conducted in August and September 2017 using the following search descriptors for MeSH: air pollution, bicycle riding, environmental exposure, environmental health, exposure by inhalation, environmental pollutants, transportation, public health and toxicology. For DeCS: air Pollution, cycling, exposure to environmental risks, environmental pollutants, inhalation, transportation, public health and toxicology.

RESULTS

Nineteen eligible published articles were identified. Most studies were conducted in Europe and the United States. Four studies have been reported in South America. Other studies seek comparisons on different bicycle routes, compare exposure during variations of the same route, and others determine the distance-exposure relationship. In the same way, variables such as vehicular traffic, distance to the emission sources and the type of bike path, play a fundamental role in the exposure to pollutants in cyclists.

CONCLUSIONS

Several variables were found that influence, directly or indirectly, the cyclists exposure to air pollution, as well as some factors that can reduce this exposure.

Monitoring Excess Exposure to Air Pollution for Professional Drivers in London Using Low-Cost Sensors

In this pilot study, low-cost air pollution sensor nodes were fitted in waste removal trucks, hospital vans and taxis to record drivers’ exposure to air pollution in Central London. Particulate matter (PM 2.5 and PM 10 ), CO 2 , NO 2 , temperature and humidity were recorded in real-time with nodes containing low-cost sensors, an electrochemical gas sensor for NO 2 , an optical particle counter for PM 2.5 and PM 10 and a non-dispersive infrared (NDIR) sensor for CO 2 , temperature and relative humidity. An intervention using a pollution filter to trap PM and NO 2 was also evaluated. The measurements were compared with urban background and roadside monitoring stations at Honor Oak Park and Marylebone Road, respectively. The vehicle records show PM and NO 2 concentrations similar to Marylebone Road and a higher NO 2 -to-PM ratio than at Honor Oak Park. Drivers are exposed to elevated pollution levels relative to Honor Oak Park: 1.72 μ g m − 3 , 1.92 μ g m − 3 and 58.38 ppb for PM 2.5 , PM 10 , and NO 2 , respectively. The CO 2 levels ranged from 410 to over 4000 ppm. There is a significant difference in average concentrations of PM 2.5 and PM 10 between the vehicle types and a non-significant difference in the average concentrations measured with and without the pollution filter within the sectors. In conclusion, drivers face elevated air pollution exposure as part of their jobs.

Cyclists' exposure to air pollution: in situ evaluation with a cargo bike platform

Cyclists' exposure to air pollutants near roadways has been associated with numerous health effects. While the adverse health effects concerning aerosols have traditionally been assessed with data of particle mass concentrations, it appears that the number concentration is also another important indicator of toxicity. Thus, to holistically evaluate one's exposure to aerosol particles, assessments should be based on mass concentrations and number concentrations. In order to assess individual cyclists' exposure as they move through space and time, spatiotemporal high-resolution approaches are needed. Therefore, a mobile, fast-response monitoring platform was developed that uses a cargo bicycle as a base. Data of particle mass concentrations (PM₁, PM_2.5, PM₁₀) and particle number concentrations (PN₁₀) were collected along two different routes, one characterized by high-intensity vehicle traffic and one by low-intensity vehicle traffic. While high spatiotemporal heterogeneity was observed for all measured quantities, the PN₁₀ concentrations fluctuated the most. High concentrations of PN₁₀ could be clearly associated with vehicle traffic. For PM_2.5, this relation was less pronounced. Mean particle concentrations of all measures were significantly higher along the high-traffic route. Comparing route exposures, the inhalation of PM_2.5 was similar between both routes, whereas along the high-traffic route, cyclists were exposed to twice the particle number. We conclude that the cargo bike, featuring high-frequency mobile measurements, was useful to characterize the spatial distribution of mass concentrations and number concentrations across an urban environment. Overall, our results suggest that the choice of route is a key factor in reducing cyclists' exposure to air pollution.

Cyclists' exposure to air pollution under different traffic management strategies

We characterized the air pollution exposure of cyclists in the city center of Curitiba (Brazil) and then systematically analyzed the influence of several traffic management strategies (bus lanes, bicycle lanes, traffic calming area, traffic lights, and cleaner vehicle technologies) on the exposure. We focused on concentrations of particulates monitored on-board bicycles: PM_2.5, black carbon mass (BC) and particle number concentration (PNC), and also reported on total volatile organic compound concentrations (TVOC). Overall, mean (± standard deviation) exposure was moderate compared to other cities around the world (BC: 6.98 ± 11.53 μg m^--3, PM_2.5: 33.22 ± 25.64 μg m^-3, PNC: 3.93 × 10⁴ ± 4.17 × 10⁴ cm^-3, TVOC: 361 ± 99 ppb). Concentrations were higher in the morning rush hour than in the afternoon traffic peak, and exhibited a large spatial variability. Bus stops and signalized traffic intersections emerged as hotspots when compared to the rest of the journey, increasing all particulate concentrations. Lower exposure was found on streets with low traffic (particularly, small number of heavy-duty vehicles) and within shallow canyon structures. The impact of traffic calming areas on cyclists' exposure is still inconclusive and further experimental and modelling studies are needed. Simple emission calculations based on traffic activity and real-world emission factors suggested that replacing the diesel bus fleet with hybrid electric buses might largely decrease (64%) the exposure to BC in the city center. Urban planners could use this valuable information to project new cycleways, which would lead to healthier active transportation. Synchronizing traffic signals might further reduce exposure at intersections.

Seasonal Impacts of Particulate Matter Levels on Bike Sharing in Seoul, South Korea

Bike sharing is increasingly attracting more riders in cities around the world for its benefits regarding the urban environment and public health. The public bike sharing program of Seoul, South Korea, first launched in October 2015, is now widely spread around the city and serves more than 27,000 riders daily. However, concerns are being raised as rising air pollution levels in Seoul, represented by particulate matter (PM) levels, in recent years may negatively discourage citizens from using bike sharing. This study investigates the impact of PM10 and PM2.5 levels on bike sharing use in Seoul and seeks to identify any seasonal differences. A series of negative binomial regression models, which take into account control variables like weather conditions and calendar events, are adopted to empirically measure the impacts. Results show that the PM levels yield statistically significant negative impacts (p < 0.01) on bike sharing use throughout the year. The impacts are particularly stronger in winter and spring, when the PM levels are higher. Findings suggest that PM levels may operate as driving factors for bike sharing use in addition to meteorological conditions like temperature, humidity, and precipitation.

Personal strategies to minimise effects of air pollution on respiratory health: advice for providers, patients and the public

As global awareness of air pollution rises, so does the imperative to provide evidence-based recommendations for strategies to mitigate its impact. While public policy has a central role in reducing air pollution, exposure can also be reduced by personal choices. Qualified evidence supports limiting physical exertion outdoors on high air pollution days and near air pollution sources, reducing near-roadway exposure while commuting, utilising air quality alert systems to plan activities, and wearing facemasks in prescribed circumstances. Other strategies include avoiding cooking with solid fuels, ventilating and isolating cooking areas, and using portable air cleaners fitted with high-efficiency particulate air filters. We detail recommendations to assist providers and public health officials when advising patients and the public regarding personal-level strategies to mitigate risk imposed by air pollution, while recognising that well-designed prospective studies are urgently needed to better establish and validate interventions that benefit respiratory health in this context.

Trade-off between environmental benefits and time costs for public bicycles: An empirical analysis using streaming data in China

In recent years, bicycle sharing has become more popular in cities and towns around the world. Public bicycles are one of the important forms of bicycle sharing. The use of public bicycles instead of motor vehicles has brought about changes in environmental benefits for the society, and at the same time, it has also changed the travel time of residents. Because these changes are potential and cannot be measured directly, we put forward the calculation methods of environmental benefits and time costs of public bicycles according to the concept of opportunity cost. Taking Hohhot, the capital city of Inner Mongolia, as an example, according to the streaming data of 9.76×10⁶ valid orders of public bicycle trips in 2016, we found that the use of public bicycles could reduce consumption of standard coal by as much as 5,796.11 tons (accounting 0.16‱ of the total coal consumption in Inner Mongolia) and carbon emissions were reduced by 4,381.28 tons (accounting 0.30‱ of the total carbon emissions in Inner Mongolia). However, the promotion of public bicycles is not without disadvantages. The use of public bicycles has increased the average travel time of residents by 0.06 hours, which is neglected in previous studies. The contribution of public bicycles to saving 1kg standard coal corresponds to 0.10 hours of travel time waste. Thus, reducing 1kg of carbon emissions is corresponding to a waste of 0.14 hours of travel time. The use of public bicycles varies among different income groups, which is caused by the value of travel time. Low-income groups use more frequently than high-income groups. Generally speaking, low-income groups bring more environmental benefits to society through the use of public bicycles, but bear more time costs. Therefore, we propose a carbon tax on high-carbon transportation modes to encourage green travel and balance the environmental benefits and time costs of public bicycles.

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.

Health economic assessment of a shift to active transport

Active transportation (walking or cycling) as a substitute for car trips still represents a small percentage of all daily travels in many European cities. This study aimed to estimate the health and economic co-benefits for the adult population of modal shift from driving to active travel in urban environments. Three scenarios were modelled for the case study, the city of Porto, Portugal, by comparing travel patterns of 2013 to hypothetical scenarios of modal shifts from driving to active transport, namely: i) SC1 - conservative scenario, with a change of 5% from driving to cycling and 10% from driving to walking; ii) SC2 - moderate scenario, with a shift of 10% and 15%, respectively; and iii) SC3 - optimistic scenario, with a shift of 15% and 20%, respectively. The mortality risk reduction for five health outcomes (colon and breast cancers, diabetes, ischemic heart disease, cerebrovascular disease) was assessed, including an estimation of traffic injury and air pollution exposure risks. Results were presented in Disability-Adjusted Life Years (DALYs) avoided. Economic valuation for each scenario was performed using a Willingness-to-Pay approach for morbimortality and a Cost of Illness approach for 2013 hospitalizations and work absenteeism. Significant health benefits were found in all modelled scenarios, ranging from 1657 (16%) to 2881 (28%) DALYs avoided. Total costs averted ranged from €3894 to €6769 million through the scenarios. Cardio and cerebrovascular diseases mortality presented the largest benefit, accounting for about 3/4 of all avoidable DALYs in all scenarios. Reductions in CO₂ and PM₁₀ emissions were calculated, showing a decrease from 31.6 to 73.7 kt of CO₂ and 7 to 16 t for PM₁₀, respectively. A modal shift towards active transportation could lead to significant health and economic benefits, indicating that the evaluation of health impacts should be included in the analysis of active transport interventions.

Cyclists′ Exposure to Road Traffic Noise: A Comparison of Three North American and European Cities

According to the World Health Organization, high levels of exposure to road traffic noise are associated with adverse health effects. Earlier studies suggest that cyclists are exposed to higher noise levels than motorists. Other studies have demonstrated that cyclists’ exposure to noise could vary significantly according to their routes. The aim of this study is to compare cyclists’ exposure to noise and their determinants in three cities. Three participants cycled equipped with noise dosimeters and GPS watches: 1823, 967, and 1362 km in Copenhagen, Paris, and Montreal, respectively. We fitted three generalized additive mixed model with an autoregressive term models to predict the cyclists’ exposure to noise according to the type of route and bicycle infrastructure after controlling for the day of the week, as well as spatial and temporal trends. The overall noise means were 73.4, 70.7, and 68.4 dB(A) in Paris, Montreal, and Copenhagen, respectively. The exposure to road traffic noise is strongly associated with the type of bicycle infrastructure taken by the cyclist; riding on a cycleway significantly decreases it, while riding in a shared lane has no impact. Our findings demonstrate that it is possible to achieve a substantial reduction in cyclists′ exposure by adopting new practices that include noise exposure in the planning of future cycling infrastructure.

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.

Vertical monitoring of traffic-related air pollution (TRAP) in urban street canyons of Hong Kong

Rapid urbanization has significantly increased air pollution especially in urban regions with high traffic volumes. Existing methods for estimating traffic-related air pollution (TRAP) and TRAP-related health impacts are based on two-dimensional modelling. This paper describes a point-based methodology to monitor vertical pollutant concentrations in typical street canyons of Hong Kong. It explains the conceptual design, monitoring strategy and selection criteria for a limited number of receptor locations in street canyons to undertake field measurements for both outdoor exposure and indoor infiltration. It also expounds on the limitations and complications associated with field instrumentation and retention of participating home units. The empirical results were applied on the building infiltration efficiencies assessment. It is concluded that the cost-effective field methodology developed in this paper expects to strike a balance between exposure error and limited data locations. These findings will have important implications in future monitoring design of vertical TRAP exposure to support health studies.

Black Carbon and Particulate Matter Concentrations in Eastern Mediterranean Urban Conditions: An Assessment Based on Integrated Stationary and Mobile Observations

There is a paucity of comprehensive air quality data from urban areas in the Middle East. In this study, portable instrumentation was used to measure size-fractioned aerosol number, mass, and black carbon concentrations in Amman and Zarqa, Jordan. Submicron particle number concentrations at stationary urban background sites in Amman and Zarqa exhibited a characteristic diurnal pattern, with the highest concentrations during traffic rush hours (2–5 × 104 cm−3 in Amman and 2–7 × 104 cm−3 in Zarqa). Super-micron particle number concentrations varied considerably in Amman (1–10 cm−3). Mobile measurements identified spatial variations and local hotspots in aerosol levels within both cities. Walking paths around the University of Jordan campus showed increasing concentrations with proximity to main roads with mean values of 8 × 104 cm−3, 87 µg/m3, 62 µg/m3, and 7.7 µg/m3 for submicron, PM10, PM2.5, and black carbon (BC), respectively. Walking paths in the Amman city center showed moderately high concentrations (mean 105 cm−3, 120 µg/m3, 85 µg/m3, and 8.1 µg/m3 for submicron aerosols, PM10, PM2.5, and black carbon, respectively). Similar levels were found along walking paths in the Zarqa city center. On-road measurements showed high submicron concentrations (>105 cm−3). The lowest submicron concentration (<104 cm−3) was observed near a remote site outside of the cities.

Transforming Our Cities: Best Practices Towards Clean Air and Active Transportation

PURPOSE OF REVIEW

By 2050, 70% of the global population will live in urban areas, exposing a greater number of people to specific city-related health risks that will only be exacerbated by climate change. Two prominent health risks are poor air quality and physical inactivity. We aim to review the literature and state the best practices for clean air and active transportation in urban areas.

RECENT FINDINGS

Cities have been targeting reductions in air pollution and physical inactivity to improve population health. Oslo, Paris, and Madrid plan on banning cars from their city centers to mitigate climate change, reduce vehicle emissions, and increase walking and cycling. Urban streets are being redesigned to accommodate and integrate various modes of transportation to ensure individuals can become actively mobile and healthy. Investments in pedestrian, cycling, and public transport infrastructure and services can both improve air quality and support active transportation. Emerging technologies like electric and autonomous vehicles are being developed and may reduce air pollution but have limited impact on physical activity. Green spaces too can mitigate air pollution and encourage physical activity. Clean air and active transportation overlap considerably as they are both functions of mobility. The best practices of clean air and active transportation have produced impressive results, which are improved when enacted simultaneously in integrated policy packages. Further research is needed in middle- and low-income countries, using measurements from real-world interventions, tracing air pollution back to the sources responsible, and holistically addressing the entire spectrum of exposures and health outcomes related to transportation.

Understanding Potential Exposure of Bicyclists on Roadways to Traffic-Related Air Pollution: Findings from El Paso, Texas, Using Strava Metro Data

As bicycling on roadways can cause adverse health effects, there is an urgent need to understand how bicycle routes expose bicyclists to traffic emissions. Limited resources for monitoring reveal that bicycle travel patterns may constrain such understanding at the network level. This study examined the potential exposure of bicyclists to traffic-related air pollution in El Paso, Texas, using Strava Metro data that revealed bicycle patterns across the city networks. An initial spatial mapping analysis was conducted to explore the spatial patterns of bicycling and traffic pollutant emission, followed by exploratory descriptive statistics. A spatial bicycle model was then developed to explore factors influencing bicycling activity in El Paso. Analysis results indicated significant associations between greater bicycle volume and both higher levels of particulate matter (PM2.5) emissions and more frequent bus services, implying adverse health concerns related to traffic-related air pollution. The results also indicated significant effects of various environmental characteristics (e.g., roadway, bicycle infrastructure, topography, and demographics) on bicycling. The findings encourage extending this study to provide guidance to bicyclists whose regular trips take place on heavily trafficked roads and during rush hours in this region and to evaluate the net health impacts of on-road bicycling for the general population.

Particulate matter exposure and health impacts of urban cyclists: a randomized crossover study

BACKGROUND

Cycling and other forms of active transportation provide health benefits via increased physical activity. However, direct evidence of the extent to which these benefits may be offset by exposure and intake of traffic-related air pollution is limited. The purpose of this study is to measure changes in endothelial function, measures of oxidative stress and inflammation, and lung function in healthy participants before and after cycling along a high- and low- traffic route.

METHODS

Participants (n = 38) bicycled for 1 h along a Downtown and a Residential designated bicycle route in a randomized crossover trial. Heart rate, power output, particulate matter air pollution (PM₁₀, PM_2.5, and PM₁) and particle number concentration (PNC) were measured. Lung function, endothelial function (reactive hyperemia index, RHI), C-reactive protein, interleukin-6, and 8-hydroxy-2'-deoxyguanosine were assessed within one hour pre- and post-trial.

RESULTS

Geometric mean PNC exposures and intakes were higher along the Downtown (exposure = 16,226 particles/cm³; intake = 4.54 × 10¹⁰ particles) compared to the Residential route (exposure = 9367 particles/cm³; intake = 3.13 × 10¹⁰ particles). RHI decreased following cycling along the Downtown route and increased on the Residential route; in mixed linear regression models, the (post-pre) change in RHI was 21% lower following cycling on the Downtown versus the Residential route (-0.43, 95% CI: -0.79, -0.079) but RHI decreases were not associated with measured exposure or intake of air pollutants. The differences in RHI by route were larger amongst females and older participants. No consistent associations were observed for any of the other outcome measures.

CONCLUSIONS

Although PNC exposures and intakes were higher along the Downtown route, the lack of association between air pollutant exposure or intake with RHI and other measures suggests other exposures related to cycling on the Downtown route may have been influential in the observed differences between routes in RHI.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT01708356 . Registered 16 October 2012.

Errors associated with the use of roadside monitoring in the estimation of acute traffic pollutant-related health effects

Near-road monitoring creates opportunities to provide direct measurement on traffic-related air pollutants and to better understand the changing near-road environment. However, how such observations represent traffic-related air pollution exposures for estimating adverse health effect in epidemiologic studies remains unknown. A better understanding of potential exposure measurement error when utilizing near-road measurement is needed for the design and interpretation of the many observational studies linking traffic pollution and adverse health. The Dorm Room Inhalation to Vehicle Emission (DRIVE) study conducted near-road measurements of several single traffic indicators at six indoor and outdoor sites ranging from 0.01 to 2.3 km away from a heavily-trafficked (average annual daily traffic over 350,000) highway artery between September 2014 to January 2015. We examined spatiotemporal variability trends and assessed the potential for bias and errors when using a roadside monitor as a primary traffic pollution exposure surrogate, in lieu of more spatially-refined, proximal exposure indicators. Pollutant levels measured during DRIVE showed a low impact of this highway hotspot source. Primary pollutant species, including NO, CO, and BC declined to near background levels by 20-30 m from the highway source. Patterns of correlation among the sites also varied by pollutant and time of day. NO₂, specifically, exhibited spatial trends that differed from other single-pollutant primary traffic indicators. This finding provides some indication of limitations in the use of NO₂ as a primary traffic exposure indicator in panel-based health effect studies. Interestingly, roadside monitoring of NO, CO, and BC tended to be more strongly correlated with sites, both near and far from the road, during morning rush hour periods, and more weakly correlated during other periods of the day. We found pronounced attenuation of observed changes in health effects when using measured pollutant from the near-road monitor as a surrogate for true exposure, and the magnitude varied substantially over the course of the day. Caution should be taken when using near-road monitoring network observations, alone, to investigate health effects of traffic pollutants.

Local action on outdoor air pollution to improve public health

OBJECTIVES

The National Institute for Health and Care Excellence, jointly with Public Health England, have developed a guideline on outdoor air pollution and its links to health. The guideline makes recommendations on local interventions that can help improve air quality and prevent a range of adverse health outcomes associated with road-traffic-related air pollution.

METHODS

The guideline was based on a rigorous assessment of the scientific evidence by an independent advisory committee, with input from public health professionals and other professional groups. The process included systematics reviews of the literature, expert testimonies and stakeholder consultation.

RESULTS

The guideline includes recommendations for local planning, clean air zones, measures to reduce emissions from public sector transport services, smooth driving and speed reduction, active travel, and awareness raising.

CONCLUSIONS

The guideline recommends taking a number of actions in combination, because multiple interventions, each producing a small benefit, are likely to act cumulatively to produce significant change. These actions are likely to bring multiple public health benefits, in addition to air quality improvements.

A task-based analysis of black carbon exposure in Iowa farmers during harvest

Diesel exhaust has been associated with adverse human health effects. Farmers are often exposed to diesel exhaust; however, their diesel exposure has not been well characterized. In this descriptive study, we measured black carbon concentrations as a proxy for diesel exhaust exposure in 16 farmers over 20 sampling days during harvest in southeast Iowa. Farmers wore a personal aethalometer which measured real-time black carbon levels throughout the working day, and their activities were recorded by a field researcher. Black carbon concentrations were characterized for each farmer, and by activity, vehicle fuel type, and microenvironment. Overall, 574 discrete tasks were monitored with a median task duration of 5.5 min. Of these tasks, 39% involved the presence of a diesel vehicle. Farmers' daily black carbon geometric mean exposures ranged from 0.1-2.3 µg/m³, with a median daily geometric mean of 0.3 µg/m³. The highest black carbon concentrations were measured on farmers who used or worked near diesel vehicles (geometric mean ranged from 0.5 µg/m³ while harvesting to 4.9 µg/m³ during animal work). Higher geometric means were found for near vs. far proximity to diesel-fueled vehicles and equipment (2.9 vs. 0.3 µg/m³). Indoor, bystander proximity to diesel-operated vehicles resulted in the highest geometric mean black carbon concentrations (18 µg/m³). Use of vehicles with open cabs had higher mean black carbon concentrations than closed cabs (2.1-3.2 vs. 0.4-0.9 µg/m³). In summary, our study provided evidence that farmers were frequently exposed to black carbon associated with diesel-related activities at levels above urban ambient concentrations in their daily work during harvest.

Developing Multipollutant Exposure Indicators of Traffic Pollution: The Dorm Room Inhalation to Vehicle Emissions (DRIVE) Study

Introduction

The Dorm Room Inhalation to Vehicle Emissions (DRIVE2) study was conducted to measure traditional single-pollutant and novel multipollutant traffic indicators along a complete emission-to-exposure pathway. The overarching goal of the study was to evaluate the suitability of these indicators for use as primary traffic exposure metrics in panel-based and small-cohort epidemiological studies.

Methods

Intensive field sampling was conducted on the campus of the Georgia Institute of Technology (GIT) between September 2014 and January 2015 at 8 monitoring sites (2 indoors and 6 outdoors) ranging from 5 m to 2.3 km from the busiest and most congested highway artery in Atlanta. In addition, 54 GIT students living in one of two dormitories either near (20 m) or far (1.4 km) from the highway were recruited to conduct personal exposure sampling and weekly biomonitoring. The pollutants measured were selected to provide information about the heterogeneous particulate and gaseous composition of primary traffic emissions, including the traditional traffic-related species (e.g., carbon monoxide [CO], nitrogen dioxide [NO2], nitric oxide [NO], fine particulate matter [PM2.5], and black carbon [BC]), and of secondary species (e.g., ozone [O3] and sulfate as well as organic carbon [OC], which is both primary and secondary) from traffic and other sources. Along with these pollutants, we also measured two multipollutant traffic indicators: integrated mobile source indicators (IMSIs) and fine particulate matter oxidative potential (FPMOP). IMSIs are derived from elemental carbon (EC), CO, and nitrogen oxide (NOx) concentrations, along with the fractions of these species emitted by gasoline and diesel vehicles, to construct integrated estimates of gasoline and diesel vehicle impacts. Our FPMOP indicator was based on an acellular assay involving the depletion of dithiothreitol (DTT), considering both water-soluble and insoluble components (referred to as FPMOPtotal-DTT). In addition, a limited assessment of 18 low-cost sensors was added to the study to supplement the four original aims.

Results

Pollutant levels measured during the study showed a low impact by this highway hotspot source on its surrounding vicinity. These findings are broadly consistent with results from other studies throughout North America showing decreased relative contributions to urban air pollution from primary traffic emissions. We view these reductions as an indication of a changing near-road environment, facilitated by the effectiveness of mobile source emission controls. Many of the primary pollutant species, including NO, CO, and BC, decreased to near background levels by 20 to 30 m from the highway source. Patterns of correlation among the sites also varied by pollutant and time of day. NO2 exhibited spatial trends that differed from those of the other single-pollutant primary traffic indicators. We believe this was caused by kinetic limitations in the photochemical chemistry, associated with primary emission reductions, required to convert the NO-dominant primary NOx, emitted from automobiles, to NO2. This finding provides some indication of limitations in the use of NO2 as a primary traffic exposure indicator in panel-based health effect studies. Roadside monitoring of NO, CO, and BC tended to be more strongly correlated with sites, both near and far from the road, during morning rush hour periods and often weakly to moderately correlated during other time periods of the day. This pattern was likely associated with diurnal changes in mixing and chemistry and their impact on spatial heterogeneity across the campus. Among our candidate multipollutant primary traffic indicators, we report several key findings related to the use of oxidative potential (OP)-based indicators. Although earlier studies have reported elevated levels of FPMOP in direct exhaust emissions, we found that atmospheric processing further enhanced FPMOPtotal-DTT, likely associated with the oxidation of primary polycyclic aromatic hydrocarbons (PAHs) to quinones and hydroxyquinones and with the oxidization and water solubility of metals. This has important implications in terms both of the utility of FPMOPtotal-DTT as a marker for exhaust emissions and of the importance of atmospheric processing of particulate matter (PM) being tied to potential health outcomes. The results from the personal exposure monitoring also point to the complexity and diversity of the spatiotemporal variability patterns among the study monitoring sites and the importance of accounting for location and spatial mobility when estimating exposures in panel-based and small-cohort studies. This was most clearly demonstrated with the personal BC measurements, where ambient roadside monitoring was shown to be a poor surrogate for exposures to BC. Alternative surrogates, including ambient and indoor BC at the participants' respective dorms, were more strongly associated with personal BC, and knowledge of the participants' mean proximity to the highway was also shown to explain a substantial level of the variability in corresponding personal exposures to both BC and NO2. In addition, untargeted metabolomic indicators measured in plasma and saliva, which represent emerging methods for measuring exposure, were used to extract approximately 20,000 and 30,000 features from plasma and saliva, respectively. Using hydrophilic interaction liquid chromatography (HILIC) in the positive ion mode, we identified 221 plasma features that differed significantly between the two dorm cohorts. The bimodal distribution of these features in the HILIC column was highly idiosyncratic; one peak consisted of features with elevated intensities for participants living in the near dorm; the other consisted of features with elevated intensities for participants in the far dorm. Both peaks were characterized by relatively short retention times, indicative of the hydrophobicity of the identified features. The results from the metabolomics analyses provide a strong basis for continuing this work toward specific chemical validation of putative biomarkers of traffic-related pollution. Finally, the study had a supplemental aim of examining the performance of 18 low-cost CO, NO, NO2, O3, and PM2.5 pollutant sensors. These were colocated alongside the other study monitors and assessed for their ability to capture temporal trends observed by the reference monitoring instrumentation. Generally, we found the performance of the low-cost gas-phase sensors to be promising after extensive calibration; the uncalibrated measurements alone, however, would likely not have led to reliable results. The low-cost PM sensors we evaluated had poor accuracy, although PM sensor technology is evolving quickly and warrants future attention.

Conclusions

An immediate implication of the changing near-road environment is that future studies aimed at characterizing hotspots related to mobile sources and their impacts on health will need to consider multiple approaches for characterizing spatial gradients and exposures. Specifically and most directly, the mobile source contributions to ambient concentrations of single-pollutant indicators of traffic exposure are not as distinguishable to the degree that they have been in the past. Collectively, the study suggests that characterizing exposures to traffic-related pollutants, which is already difficult, will become more difficult because of the reduction in traffic-related emissions. Additional multi-tiered approaches should be considered along with traditional measurements, including the use of alternative OP measures beyond those based on DTT assays, metabolomics, low-cost sensors, and air quality modeling.

An accurate filter loading correction is essential for assessing personal exposure to black carbon using an Aethalometer

The AE51 micro-Aethalometer (microAeth) is a popular and useful tool for assessing personal exposure to particulate black carbon (BC). However, few users of the AE51 are aware that its measurements are biased low (by up to 70%) due to the accumulation of BC on the filter substrate over time; previous studies of personal black carbon exposure are likely to have suffered from this bias. Although methods to correct for bias in micro-Aethalometer measurements of particulate black carbon have been proposed, these methods have not been verified in the context of personal exposure assessment. Here, five Aethalometer loading correction equations based on published methods were evaluated. Laboratory-generated aerosols of varying black carbon content (ammonium sulfate, Aquadag and NIST diesel particulate matter) were used to assess the performance of these methods. Filters from a personal exposure assessment study were also analyzed to determine how the correction methods performed for real-world samples. Standard correction equations produced correction factors with root mean square errors of 0.10 to 0.13 and mean bias within ±0.10. An optimized correction equation is also presented, along with sampling recommendations for minimizing bias when assessing personal exposure to BC using the AE51 micro-Aethalometer.

Characteristics and applications of small, portable gaseous air pollution monitors

BACKGROUND

Traditional approaches for measuring air quality based on fixed measurements are inadequate for personal exposure monitoring. To combat this issue, the use of small, portable gas-sensing air pollution monitoring technologies is increasing, with researchers and individuals employing portable and mobile methods to obtain more spatially and temporally representative air pollution data. However, many commercially available options are built for various applications and based on different technologies, assumptions, and limitations. A review of the monitor characteristics of small, gaseous monitors is missing from current scientific literature.

PURPOSE

A state-of-the-art review of small, portable monitors that measure ambient gaseous outdoor pollutants was developed to address broad trends during the last 5-10 years, and to help future experimenters interested in studying gaseous air pollutants choose monitors appropriate for their application and sampling needs.

METHODS

Trends in small, portable gaseous air pollution monitor uses and technologies were first identified and discussed in a review of literature. Next, searches of online databases were performed for articles containing specific information related to performance, characteristics, and use of such monitors that measure one or more of three criteria gaseous air pollutants: ozone, nitrogen dioxide, and carbon monoxide. All data were summarized into reference tables for comparison between applications, physical features, sensing capabilities, and costs of the devices.

RESULTS

Recent portable monitoring trends are strongly related to associated applications and audiences. Fundamental research requires monitors with the best individual performance, and thus the highest cost technology. Monitor networking favors real-time capabilities and moderate cost for greater reproduction. Citizen science and crowdsourcing applications allow for lower-cost components; however important strengths and limitations for each application must be addressed or acknowledged for the given use.

Comparison of air pollution exposures in active vs. passive travel modes in European cities: A quantitative review

BACKGROUND

Transport microenvironments tend to have higher air pollutant concentrations than other settings most people encounter in their daily lives. The choice of travel modes may affect significantly individuals' exposures; however such considerations are typically not accounted for in exposure assessment used in environmental health studies. In particular, with increasing interest in the promotion of active travel, health impact studies that attempt to estimate potential adverse consequences of potential increased pollutant inhalation during walking or cycling have emerged. Such studies require a quantification of relative exposures in travel modes.

METHODS

The literature on air pollution exposures in travel microenvironments in Europe was reviewed. Studies which measured various travel modes including at least walking or cycling in a simultaneous or quasi-simultaneous design were selected. Data from these studies were harmonized to allow for a quantitative synthesis of the estimates. Ranges of ratios and 95% confidence interval (CI) of air pollution exposure between modes and between background and transportation modes were estimated.

RESULTS

Ten studies measuring fine particulate matter (PM_2.5), black carbon (BC), ultrafine particles (UFP), and/or carbon monoxide (CO) in the walk, bicycle, car and/or bus modes were included in the analysis. Only three reported on CO and BC and results should be interpreted with caution. Pedestrians were shown to be the most consistently least exposed of all across studies, with the bus, bicycle and car modes on average 1.3 to 1.5 times higher for PM_2.5; 1.1 to 1.7 times higher for UFP; and 1.3 to 2.9 times higher for CO; however the 95% CI included 1 for the UFP walk to bus ratio. Only for BC were pedestrians more exposed than bus users on average (bus to walk ratio 0.8), but remained less exposed than those on bicycles or in cars. Car users tended to be the most exposed (from 2.9 times higher than pedestrians for BC down to similar exposures to cyclists for UFP on average). Bus exposures tended to be similar to that of cyclists (95% CI including 1 for PM_2.5, CO and BC), except for UFP where they were lower (ratio 0.7).

CONCLUSION

A quantitative method that synthesizes the literature on air pollution exposure in travel microenvironments for use in health impact assessments or potentially for epidemiology was conducted. Results relevant for the European context are presented, showing generally greatest exposures in car riders and lowest exposure in pedestrians.

Health impact assessment of active transportation: A systematic review

OBJECTIVE

Walking and cycling for transportation (i.e. active transportation, AT), provide substantial health benefits from increased physical activity (PA). However, risks of injury from exposure to motorized traffic and their emissions (i.e. air pollution) exist. The objective was to systematically review studies conducting health impact assessment (HIA) of a mode shift to AT on grounds of associated health benefits and risks.

METHODS

Systematic database searches of MEDLINE, Web of Science and Transportation Research International Documentation were performed by two independent researchers, augmented by bibliographic review, internet searches and expert consultation to identify peer-reviewed studies from inception to December 2014.

RESULTS

Thirty studies were included, originating predominantly from Europe, but also the United States, Australia and New Zealand. They compromised of mostly HIA approaches of comparative risk assessment and cost-benefit analysis. Estimated health benefit-risk or benefit-cost ratios of a mode shift to AT ranged between -2 and 360 (median=9). Effects of increased PA contributed the most to estimated health benefits, which strongly outweighed detrimental effects of traffic incidents and air pollution exposure on health.

CONCLUSION

Despite different HIA methodologies being applied with distinctive assumptions on key parameters, AT can provide substantial net health benefits, irrespective of geographical context.