SHERPA-city: A web application to assess the impact of traffic measures on NO2 pollution in cities

This paper presents SHERPA-City, a web application to assess the potential of traffic measures to abate NO₂ air pollution in cities. The application is developed by the Joint Research Centre. It is freely available (https://integrated-assessment.jrc.ec.europa.eu) and allows the user to perform a fast screening of possible NO₂ abatement measures addressing traffic in European cities. SHERPA-City results depend on the quality of the default input data. It is therefore important to stress that the SHERPA-City default traffic flows, emission factors, fleet composition, road network topology, NO₂ pollution from other sources and meteorological data are based on EU-wide datasets that may not always represent perfectly a particular local situation. This is why the SHERPA-City allows the default data to be substituted by local data, to better reflect local features. This tool must be considered as a first step in exploring options to abate NO₂ air pollution through transport measures. The final decisions should be based, wherever possible, on full-scale modelling studies incorporating local knowledge.

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.

On the design and assessment of regional air quality plans: The SHERPA approach

Although significant progress has been made in Europe regarding air quality, problems still remain acute for some pollutants, notably NO₂ and Particulate Matter (fine and coarse fractions) in specific regions/cities. One issue regarding air quality management is governance, i.e. the selection of appropriate and cost effective strategies over the area controlled by policy makers. In this work we present a new approach to integrated assessment modelling focusing on regional and urban aspects. One of the key added values is spatial flexibility, namely the possibility to assess the contributions from different regions to air quality at any given location. The SHERPA tool is shown to be particularly helpful in addressing the following tasks: source allocation, governance and the assessment of scenario impacts. Application of the methodology over the London area for yearly averaged PM_2.5 concentrations demonstrates these features. Given that it is possible to use the SHERPA interface with other types of data, SHERPA can also be seen as a means to foster harmonization in the field of model evaluation.

Analyzing the efficiency of short-term air quality plans in European cities, using the CHIMERE air quality model

Regional and local authorities have the obligation to design air quality plans and assess their impacts when concentration levels exceed the limit values. Because these limit values cover both short- (day) and long-term (year) effects, air quality plans also follow these two formats. In this work, we propose a methodology to analyze modeled air quality forecast results, looking at emission reduction for different sectors (residential, transport, agriculture, etc.) with the aim of supporting policy makers in assessing the impact of short-term action plans. Regarding PM₁₀, results highlight the diversity of responses across European cities, in terms of magnitude and type that raises the necessity of designing area-specific air quality plans. Action plans extended from 1 to 3 days (i.e., emissions reductions applied for 24 and 72 h, respectively) point to the added value of trans-city coordinated actions. The largest benefits are seen in central Europe (Vienna, Prague) while major cities (e.g., Paris) already solve a large part of the problem on their own. Eastern Europe would particularly benefit from plans based on emission reduction in the residential sectors; while in northern cities, agriculture seems to be the key sector on which to focus attention. Transport is playing a key role in most cities whereas the impact of industry is limited to a few cities in south-eastern Europe. For NO₂, short-term action plans focusing on traffic emission reductions are efficient in all cities. This is due to the local character of this type of pollution. It is important, however, to stress that these results remain dependent on the selected months available for this study.

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.

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.