Bart Degraeuwe

Subclinical responses in healthy cyclists briefly exposed to traffic-related air pollution: an intervention study

BackgroundNumerous epidemiological studies have demonstrated adverse health effects of a sedentary life style, on the one hand, and of acute and chronic exposure to traffic-related air pollution, on the other. Because physical exercise augments the amount of inhaled pollutants, it is not clear whether cycling to work in a polluted urban environment should be encouraged or not. To address this conundrum we investigated if a bicycle journey along a busy commuting road would induce changes in biomarkers of pulmonary and systematic inflammation in a group of healthy subjects.Methods38 volunteers (mean age: 43 ± 8.6 years, 26% women) cycled for about 20 minutes in real traffic near a major bypass road (road test; mean UFP exposure: 28,867 particles per cm3) in Antwerp and in a laboratory with filtered air (clean room; mean UFP exposure: 496 particles per cm3). The exercise intensity (heart rate) and duration of cycling were similar for each volunteer in both experiments. Exhaled nitric oxide (NO), plasma interleukin-6 (IL-6), platelet function, Clara cell protein in serum and blood cell counts were measured before and 30 minutes after exercise.ResultsPercentage of blood neutrophils increased significantly more (p = 0.004) after exercise in the road test (3.9%; 95% CI: 1.5 to 6.2%; p = 0.003) than after exercise in the clean room (0.2%; 95% CI: -1.8 to 2.2%, p = 0.83). The pre/post-cycling changes in exhaled NO, plasma IL-6, platelet function, serum levels of Clara cell protein and number of total blood leukocytes did not differ significantly between the two scenarios.ConclusionsTraffic-related exposure to particles during exercise caused a small increase in the distribution of inflammatory blood cells in healthy subjects. The health significance of this isolated change is unclear.

No exercise-induced increase in serum BDNF after cycling near a major traffic road.

Commuting by bike has a clear health enhancing effect. Moreover, regular exercise is known to improve brain plasticity, which results in enhanced cognition and memory performance. Animal research has clearly shown that exercise upregulates brain-derived neurotrophic factor (BDNF - a neurotrophine) enhancing brain plasticity. Studies in humans found an increase in serum BDNF concentration in response to an acute exercise bout. Recently, more evidence is emerging suggesting that exposure to air pollution (such as particulate matter (PM)) is higher in commuter cyclists compared to car drivers. Furthermore, exposure to PM is linked to negative neurological effects, such as neuroinflammation and cognitive decline. We carried-out a cross-over experiment to examine the acute effect of exercise on serum BDNF, and the potential effect-modification by exposure to traffic-related air pollution. Thirty eight physically fit, non-asthmatic volunteers (mean age: 43, 26% women) performed two cycling trials, one near a major traffic road (Antwerp Ring, R1, up to 260,000 vehicles per day) and one in an air-filtered room. The air-filtered room was created by reducing fine particles as well as ultrafine particles (UFP). PM10, PM2.5 and UFP were measured. The duration (∼20min) and intensity of cycling were kept the same for each volunteer for both cycling trials. Serum BDNF concentrations were measured before and 30min after each cycling trial. Average concentrations of PM10 and PM2.5 were 64.9μg/m(3) and 24.6μg/m(3) in cycling near a major ring way, in contrast to 7.7μg/m(3) and 2.0μg/m(3) in the air-filtered room. Average concentrations of UFP were 28,180 particles/cm(3) along the road in contrast to 496 particles/cm(3) in the air-filtered room. As expected, exercise significantly increased serum BDNF concentration after cycling in the air-filtered room (+14.4%; p=0.02). In contrast, serum BDNF concentrations did not increase after cycling near the major traffic route (+0.5%; p=0.42). Although active commuting is considered to be beneficial for health, this health enhancing effect could be negatively influenced by exercising in an environment with high concentrations of PM. Whether this effect is also present with chronic exercise and chronic exposure must be further elucidated.

Effects of traffic signal coordination on noise and air pollutant emissions

Traffic management solutions are increasingly called for to address problems of transport and mobility. In particular, coordinated traffic lights that create green waves along major arterials are an increasingly used strategy to reduce travel times. Although it is usually assumed that an improved traffic flow will result in lower vehicle emissions, little scientific research has been spent on the effects of synchronized traffic lights on emissions. Moreover, because changes in traffic flow do not necessarily influence travel times, noise and air quality in the same way, there is a clear need for a combined approach. This paper reports on a computational study in which a microscopic traffic simulation model (Paramics) is combined with submodels for the emission of noise (Imagine) and air pollutants (VERSIT+). Through the simulation of a range of scenarios, the model is used to investigate the influence of traffic intensity, signal coordination schemes and signal parameters on the noise, carbon dioxide, nitrogen oxides and particulate matter emissions along an arterial road equiped with a series of traffic lights. It was found that the introduction of a green wave could potentially lower the emissions of the considered air pollutants by 10%-40% in the most favorable conditions, depending on traffic flow and signal timing settings. Sound pressure levels were found to decrease by up to 1?dB(A) near the traffic signals, but to increase by up to 1.5?dB(A) in between intersections. Traffic intensity and green split were found to have the largest influence on emissions, while the cycle time did not have a significant influence on emissions.

Integrated health impact assessment of travel behaviour: model exploration and application to a fuel price increase.

Transportation policy measures often aim to change travel behaviour towards more efficient transport. While these policy measures do not necessarily target health, these could have an indirect health effect. We evaluate the health impact of a policy resulting in an increase of car fuel prices by 20% on active travel, outdoor air pollution and risk of road traffic injury. An integrated modelling chain is proposed to evaluate the health impact of this policy measure. An activity-based transport model estimated movements of people, providing whereabouts and travelled kilometres. An emission- and dispersion model provided air quality levels (elemental carbon) and a road safety model provided the number of fatal and non-fatal traffic victims. We used kilometres travelled while walking or cycling to estimate the time in active travel. Differences in health effects between the current and fuel price scenario were expressed in Disability Adjusted Life Years (DALY). A 20% fuel price increase leads to an overall gain of 1650 (1010-2330) DALY. Prevented deaths lead to a total of 1450 (890-2040) Years Life Gained (YLG), with better air quality accounting for 530 (180-880) YLG, fewer road traffic injuries for 750 (590-910) YLG and active travel for 170 (120-250) YLG. Concerning morbidity, mostly road safety led to 200 (120-290) fewer Years Lived with Disability (YLD), while air quality improvement only had a minor effect on cardiovascular hospital admissions. Air quality improvement and increased active travel mainly had an impact at older age, while traffic safety mainly affected younger and middle-aged people. This modelling approach illustrates the feasibility of a comprehensive health impact assessment of changes in travel behaviour. Our results suggest that more is needed than a policy rising car fuel prices by 20% to achieve substantial health gains. While the activity-based model gives an answer on what the effect of a proposed policy is, the focus on health may make policy integration more tangible. The model can therefore add to identifying win-win situations for both transport and health.

Does the New European Driving Cycle (NEDC) really fail to capture the NOX emissions of diesel cars in Europe

Tests with Portable Emissions Measurement Systems (PEMS) have demonstrated that diesel cars emit several times more NOX on the road than during certification on the New European Driving Cycle (NEDC). Policy makers and scientists have attributed the discrepancy to the unrealistically low dynamics and the narrow temperature range of NEDC testing. Although widely accepted, this assumption was never been put under scientific scrutiny. Here, we demonstrate that the narrow NEDC test conditions explain only a small part of the elevated on-road NOX emissions of diesel cars. For seven Euro 4–6 diesel cars, we filter from on-road driving those events that match the NEDC conditions in instantaneous speed, acceleration, CO2 emissions, and ambient temperature. The resulting on-road NOX emissions exceed by 206% (median) those measured on the NEDC, whereas the NOX emissions of all unfiltered on-road measurements exceed the NEDC emissions by 266% (median). Moreover, when applying the same filtering of on-road data to two other driving cycles (WLTP and CADC), the resulting on-road NOX emissions exceed by only 13% (median) those measured over the respective cycles. This result demonstrates that our filtering method is accurate and robust. If neither the low dynamics nor the limited temperature range of NEDC testing can explain the elevated NOX emissions of diesel cars, emissions control strategies used during NEDC testing must be inactive or modulated on the road, even if vehicles are driven under certification-like conditions. This points to defeat strategies that warrant further investigations by type-approval authorities and, in turn, limitations in the enforcement of the European vehicle emissions legislation by EU Member States. We suggest applying our method as a simple yet effective tool to screen and select vehicles for in-depth analysis by the competent certification authorities.

A novel approach to screen and compare emission inventories.

A methodology is proposed to support the evaluation and comparison of different types of emission inventories. The strengths and weaknesses of the methodology are presented and discussed based on an example. The approach results in a “diamond” diagram useful to flag out anomalous behaviors in the emission inventories and to get insight in possible explanations. In particular, the “diamond” diagram is shown to provide meaningful information in terms of: discrepancies between the total emissions reported by macro-sector and pollutant, contribution of each macro-sector to the total amount of emissions released by pollutant, and the identification and quantification of the different factors causing the discrepancies between total emissions. A practical example in Barcelona is used for testing and to provide relevant information for the analyzed emission datasets. The tests show the capability of the proposed methodology to flag inconsistencies in the existing inventories. The proposed methodology system may be useful for regional and urban inventory developers as an initial evaluation of the consistency of their inventories.

Adding spatial flexibility to source-receptor relationships for air quality modeling

To cope with computing power limitations, air quality models that are used in integrated assessment applications are generally approximated by simpler expressions referred to as “source-receptor relationships (SRR)”. In addition to speed, it is desirable for the SRR also to be spatially flexible (application over a wide range of situations) and to require a “light setup” (based on a limited number of full Air Quality Models - AQM simulations). But “speed”, “flexibility” and “light setup” do not naturally come together and a good compromise must be ensured that preserves “accuracy”, i.e. a good comparability between SRR results and AQM. In this work we further develop a SRR methodology to better capture spatial flexibility. The updated methodology is based on a cell-to-cell relationship, in which a bell-shape function links emissions to concentrations. Maintaining a cell-to-cell relationship is shown to be the key element needed to ensure spatial flexibility, while at the same time the proposed approach to link emissions and concentrations guarantees a “light set-up” phase. Validation has been repeated on different areas and domain sizes (countries, regions, province throughout Europe) for precursors reduced independently or contemporarily. All runs showed a bias around 10% between the full AQM and the SRR. This methodology allows assessing the impact on air quality of emission scenarios applied over any given area in Europe (regions, set of regions, countries), provided that a limited number of AQM simulations are performed for training.

The Influence of the Changing NOx-Split for Compliance to the European Limit Values in Urban Areas

In this paper, we investigate the influence of the changing NOx-split in traffic emissions on the ambient NO2-concentrations. First of all, we show that the NOx-split is indeed changing, by looking at measurements in tunnels and at urban locations. Secondly, we analyze on a local scale the effect of this changing split. It is shown that the a large influence can be found. Finally, we discuss some of the consequences of these changes, for instance, on the effectiveness of the EU-legislation.

Lung deposited dose of UFP and PM for cyclists and car passengers in Belgium

Commuter cyclists experience short episodes of high exposure to traffic born air pollution that have potential adverse health effects. We have compared respiratory parameters and exposure to Ultrafine Particles, PM2.5 and PM10 for persons who cycled and drove identical trajectories in three Belgian locations in a pair-wise design. Differences in lung deposited doses are large and consistent across locations. Physical activity significantly increases exposure of cyclists to traffic exhaust. Additional analyses of physiological parameters reveal changes in exhaled NO, serum BDNF and % blood neutrophile cells, but we hypothesize that these effects do not offset the overall health benefits of cycling.

Is Driving 1 km to Work Worse for the Environment Than Driving 1 km for Shopping

One of the measures that is promoted in order to improve the air quality is the decrease of vehicle mileage. However, there are different reasons to assume that not every kilometer driven by car yields the same impact on air pollution nor on the exposure of people. For instance, some trips are driven at high speeds on highways, while others are driven at relatively low speeds in urban environments. This will have an impact on the resulting emissions. Furthermore, emissions exhausted during the night will have a larger impact on the ground-level concentrations than emissions exhausted during the day, due to the higher atmospheric stability. And another aspect is that emissions produced in cities will affect a larger population than emissions in sparsely populated areas. These and other aspects are examined in this chapter. Analysis of the results per trip purpose shows that driving 1 km to work increases the pollutant concentrations about 1.3–1.4 times more than driving 1 km to go shopping, mainly due, but not confined to, the time of the day at which the activity is performed.