Stijn Janssen

Improving local air quality in cities: To tree or not to tree?

Vegetation is often quoted as an effective measure to mitigate urban air quality problems. In this work we demonstrate by the use of computer models that the air quality effect of urban vegetation is more complex than implied by such general assumptions. By modelling a variety of real-life examples we show that roadside urban vegetation rather leads to increased pollutant concentrations than it improves the air quality, at least locally. This can be explained by the fact that trees and other types of vegetation reduce the ventilation that is responsible for diluting the traffic emitted pollutants. This aerodynamic effect is shown to be much stronger than the pollutant removal capacity of vegetation. Although the modelling results may be subject to a certain level of uncertainty, our results strongly indicate that the use of urban vegetation for alleviating a local air pollution hotspot is not expected to be a viable solution.

Impact of trees on pollutant dispersion in street canyons: A numerical study of the annual average effects in Antwerp, Belgium

Effects of vegetation on pollutant dispersion receive increased attention in attempts to reduce air pollutant concentration levels in the urban environment. In this study, we examine the influence of vegetation on the concentrations of traffic pollutants in urban street canyons using numerical simulations with the CFD code OpenFOAM. This CFD approach is validated against literature wind tunnel data of traffic pollutant dispersion in street canyons. The impact of trees is simulated for a variety of vegetation types and the full range of approaching wind directions at 15° interval. All these results are combined using meteo statistics, including effects of seasonal leaf loss, to determine the annual average effect of trees in street canyons. This analysis is performed for two pollutants, elemental carbon (EC) and PM10, using background concentrations and emission strengths for the city of Antwerp, Belgium. The results show that due to the presence of trees the annual average pollutant concentrations increase with about 8% (range of 1% to 13%) for EC and with about 1.4% (range of 0.2 to 2.6%) for PM10. The study indicates that this annual effect is considerably smaller than earlier estimates which are generally based on a specific set of governing conditions (1 wind direction, full leafed trees and peak hour traffic emissions).

Dispersion modelling of traffic induced ultrafine particles in a street canyon in Antwerp, Belgium and comparison with observations

The aim of this study is to investigate the dispersion of ultrafine particles and its spatial distribution in a street canyon and its neighbourhood with the 3D CFD model ENVI-met®. The performance of the model at street scale is evaluated and the importance of the boundary conditions like wind field and traffic emissions on the UFP concentration is demonstrated. To support and validate the modelled results, a short-term measurement campaign was conducted in a street canyon in Antwerp, Belgium. The UFP concentration was measured simultaneously with P-TRACK (TSI Model 8525) at four different locations in the canyon. The modelled UFP concentrations compare well with the measured data (correlation coefficient R from 0.44 to 0.93) within the standard deviation of the measurements. Despite the moderate traffic flow in the street canyon, UFP concentrations in the canyon are in general double of the background concentrations, indicating the high local contribution for this particle number concentration. Some of the observed concentration profiles are not resembled by the model simulations. For these specific anomalies, further analysis is performed and plausible explanations are put forward. The role of wind direction and traffic emissions is investigated. The performance evaluation of ENVI-met® shows that in general the model qualitatively and quantitatively describes the dispersion of UFP in the street canyon study.

Size resolved ultrafine particles emission model--a continues size distribution approach.

A new parameterization for size resolved ultrafine particles (UFP) traffic emissions is proposed based on the results of PARTICULATES project (Samaras et al., 2005). It includes the emission factors from the Emission Inventory Guidebook (2006) (total number of particles, #/km/veh), the shape of the corresponding particle size distribution given in PARTICULATES and data for the traffic activity. The output of the model UFPEM (UltraFine Particle Emission Model) is a sum of continuous distributions of ultrafine particles emissions per vehicle type (passenger cars and heavy duty vehicles), fuel (petrol and diesel) and average speed representative for urban, rural and highway driving. The results from the parameterization are compared with measured total number of ultrafine particles and size distributions in a tunnel in Antwerp (Belgium). The measured UFP concentration over the entire campaign shows a close relation to the traffic activity. The modelled concentration is found to be lower than the measured in the campaign. The average emission factor from the measurement is 4.29E+14 #/km/veh whereas the calculated is around 30% lower. A comparison of emission factors with literature is done as well and in overall a good agreement is found. For the size distributions it is found that the measured distributions consist of three modes--Nucleation, Aitken and accumulation and most of the ultrafine particles belong to the Nucleation and the Aitken modes. The modelled Aitken mode (peak around 0.04-0.05 μm) is found in a good agreement both as amplitude of the peak and the number of particles whereas the modelled Nucleation mode is shifted to smaller diameters and the peak is much lower that the observed. Time scale analysis shows that at 300 m in the tunnel coagulation and deposition are slow and therefore neglected. The UFPEM emission model can be used as a source term in dispersion models.

Fine Atmospheric Particles from Agricultural Practices in Flanders: From Emissions to Health Effects and Limit Values

Agriculture can influence air quality via emissions of ammonia, soil dust and soot. These can be emitted into the atmosphere during farming practices, and contribute in different amounts to the total emissions and concentrations of air particulate matter (PM). The exact contribution of Flemish agricultural emissions to total air PM concentrations and to negative health effects are not well known. In this paper, agricultural emissions in Flanders and the processes leading to secondary PM are reviewed, together with their associated health effects. Agricultural ammonia emissions are a major contributor to local formation of secondary PM, and can increase above normal levels during some smog episodes. From a health perspective, secondary PM formed by ammonia is considered less important. Epidemiological studies suggest that combustion-related particles are the cause of negative health effects, although a reduction in ammonia emissions would reduce acidification and eutrophication of ecosystems. The World Health Organization currently considers PM2.5 as the best indicator for assessing human health effects. Setting an additional limit value for combustion-related particles would target potentially more harmful particles.

Simulating Building Downwash of Heavy Metals by Using Virtual Sources: Methodology and Results

There is a discrepancy in data quality between the highly detailed concentration measurements in the surroundings of industrial plants emitting heavy metals and the registered emission data at these sites. When simulating the concentration fields in the direct vicinity of the emitting plants by using the bi-gaussian model IFDM and the reported emissions, the simulated concentrations were much lower than the measured concentrations. Originally, this was thought to be due to diffuse, wind-fugitive emissions not reported in the official inventories. Therefore, inverse modeling was performed to get the emission data and wind dependency of these emissions. It was expected that the emissions coming out of the inverse modeling would follow a power law of the wind speed except for very low and very high wind speeds. In the latter case, a constant emission was expected, while in the former case, no emissions were expected to be found. However, this lower threshold did not seem to exist in the modeled emissions. Furthermore, these emissions seemed to have their source in spots not used for storage of heavy metals such as parking lots. Detailed analysis of these results showed that another effect, known as building downwash, is responsible for this behavior. Thereafter, it was shown that it is possible for a bi-gaussian model that lacks a building downwash module, to simulate correct concentration levels by putting in virtual sources just behind the buildings causing the building downwash phenomenon. By using half of the available concentration data for the inverse modeling and half for the validation, it was shown that this technique can be used to produce detailed and validated concentration maps of the surroundings of the industrial site. Finally, it was shown that in this case study building downwash has an important effect on local concentrations and that a better representation of building downwash is needed in bi-gaussian models to describe the complex dispersion patterns in the wake of industrial sites.

Making High Resolution Air Quality Maps for Flanders, Belgium

Using a combination of models, high resolution air quality maps for Flanders (Belgium) have been made. First of all, the Eulerian air quality model AURORA has simulated for a complete year the air pollutant concentrations over the region on a 3 × 3 km² resolution. These results are calibrated using the RIO-interpolation model on air quality station data. Thereafter, an extra simulation using the bi-Gaussian IFDM model is made on a resolution of 1 × 1 km², with a finer resolution (up to 25 m) close to the major roads. The nesting methodology of IFDM in AURORA is designed to avoid double counting of the roads. The results are highly detailed PM10, PM2.5, NO2 and EC maps for Flanders. Using station data and data from several measurement campaigns, the maps have been validated and it has been shown that the maps show indeed a highly detailed picture of the air quality in Flanders. These data will be used in assessing the air quality and human exposure to it in Flanders, and in assessing policy scenarios designed to improve the air quality.

A Statistical Approach for the Spatial Representativeness of Air Quality Monitoring Stations and the Relevance for Model Validation

A methodology is presented for the assessment of the spatial represent- tativeness of air pollution monitoring data. The methodology relies on a statistical approach that links air quality expectation values with land use characteristics. The relevance of this issue for model validation is addressed and the technique is illu- strated for the validation of BelEUROS model results.

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.

The Role of Vegetation in Local and Urban Air Quality

We present the outcome of the international conference ‘Local Air Quality and its Interactions with Vegetation’, which took place in Antwerp, Belgium on January 21-22, 2010. Results of international CFD studies, measurement campaigns and experimental studies show that vegetation can have an important effect on dispersion patterns determining local air quality. However, there are many parameters involved (vegetation structure, local meteorology, urban canopy characteristics, mechanical turbulence properties) and the results show that the complexity of the mechanisms of vegetation affecting local air quality are often underestimated.