Using advanced dispersion models and mobile monitoring to characterize spatial patterns of ultrafine particles in an urban area

Zwack, Leonard M.; Hanna, Steven R.; Spengler, John D.; Levy, Jonathan I.

doi:10.1016/j.atmosenv.2011.06.019

Cited by 36 publications

(26 citation statements)

References 21 publications

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“…They showed that the shape of street level particle number distributions was similar for the selected heights (due to the slow transformation processes) with consistent decrease in the number concentration per size mode. Wang et al (2008) and Zwack et al (2011) modelled the dispersion of traffic emitted UFP (total number of particles) in a neighbourhood scale, showing that the concentration decays exponentially with distance. This is also confirmed by the measurements by Zhu et al (2009), showing that the UFP concentration decayed exponentially with increasing distances with sharp concentration gradients observed within 100-150 m from the roadway.…”

Section: Resultsmentioning

confidence: 99%

Modelling the Mixing of Size Resolved Traffic Induced and Background Ultrafine Particles from an Urban Street Canyon to Adjacent Backyards

Nikolova

Janssen

Vos

et al. 2014

Aerosol Air Qual. Res.

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By means of numerical simulations the aims of this study are as follows: (1) to investigate the dispersion and mixing of ultrafine particles (UFP) with pre-existing size resolved UFP in a street canyon and its vicinity with the ENVI-met 3D microscale model; (2) to show the effects of boundary conditions, like wind direction and traffic emissions, on the UFP concentration in the near vicinity; and (3) to evaluate the importance of deposition and coagulation at the street scale. The decrease in UFP concentration in nucleation mode particles (diameter < 30 nm) and Aitken mode particles (diameter between 30-100 nm) downwind of the street canyon is caused by the large differences in the size distributions of the emissions and the background. Based on the wind direction and traffic emissions, the UFP concentration over the rooftop increases by 23% for the South-West wind up to 165% for the Northern wind. The background distribution for the South-West wind direction remains mono-modal, with a peak in the Aitken mode as a result of the relatively low contribution of advected particles from the street canyon. For the Northern wind the background size distribution transforms to a bi-modal distribution, with peaks in the nucleation and the Aitken modes as a result of the high UFP concentration advected from the boulevard. The overall effect of deposition and coagulation on the UFP is negligible for the cases considered in this study. Overall, deposition is more efficient and faster than coagulation in removing particles, and especially those in the nucleation mode.

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Section: Resultsmentioning

confidence: 99%

Modelling the Mixing of Size Resolved Traffic Induced and Background Ultrafine Particles from an Urban Street Canyon to Adjacent Backyards

Nikolova

Janssen

Vos

et al. 2014

Aerosol Air Qual. Res.

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show abstract

“…Evidently, the spatial variability of UFP concentrations depends on the spatial proximity to sources (Zhu et al, 2002) but also the dispersion conditions governed by topography, current wind speed and direction, and temperature inversions (Birmili et al, 2009a;Zwack et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Estimating the contribution of photochemical particle formation to ultrafine particle number averages in an urban atmosphere

Birmili

2015

Science of The Total Environment

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Ultrafine particles (UFPs, diameter<100 nm) have gained major attention in the environmental health discussion due to a number of suspected health effects. Observations of UFPs in urban air reveal the presence of several, time-dependent particle sources. In order to attribute measured UFP number concentrations to different source type contributions, we analyzed observations collected at a triplet of observation sites (roadside, urban background, rural) in the city of Leipzig, Germany. Photochemical new particle formation (NPF) events can be the overwhelming source of UFP particles on particular days, and were identified on the basis of characteristic patterns in the particle number size distribution data. A subsequent segmentation of the diurnal cycles of UFP concentration yielded a quantitative contribution of NPF events to daily, monthly, and annual mean values. At roadside, we obtained source contributions to the annual mean UFP number concentration (diameter range 5-100 nm) for photochemical NPF events (7%), local traffic (52%), diffuse urban sources (20%), and regional background (21%). The relative contribution of NPF events rises when moving away from roadside to the urban background and rural sites (14 and 30%, respectively). Their contribution also increases when considering only fresh UFPs (5-20 nm) (21% at the urban background site), and conversely decreases when considering UFPs at bigger sizes (20-100 nm) (8%). A seasonal analysis showed that NPF events have their greatest importance on UFP number concentration in the months May-August, accounting for roughly half of the fresh UFPs (5-20 nm) at the urban background location. The simplistic source apportionment presented here might serve to better characterize exposure to ambient UFPs in future epidemiological studies.

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“…Mobile measurements are performed with different platforms, e.g. pedestrians (Zwack et al, 2011a), bicycles (Berghmans et al, 2009;Boogaard et al, 2009;Peters et al, 2013;Sullivan and Pryor, 2014), trams (Hagemann et al, 2014;Hasenfratz et al, 2014) and cars (Westerdahl et al, 2005;Hu et al, 2012;Hudda et al, 2014). Mobile measurements are used for a range of different purposes, e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Mobile measurements are used for a range of different purposes, e.g. to assess personal exposure by equipping the study object with a portable monitor (Berghmans et al, 2009;Boogaard et al, 2009;Dons et al, 2011;SpiraCohen et al, 2010), to assess the exposure in different modes of transport (Kaur et al, 2005;Int Panis et al, 2010;Kingham et al, 2013), to study spatial variation in air pollution (Weijers et al, 2004;Zwack et al, 2011c;MacNaughton et al, 2014), to investigate seasonal and regional variation (Bukowiecki et al, 2003), to study spatio-temporal correlation with noise (Weber, 2009), or to develop and validate air quality models (Zwack et al, 2011a;Merbitz et al, 2012). Other studies address the potential of using mobile measurements to construct air pollution maps at a high spatial resolution (e.g.…”

Section: Introductionmentioning

confidence: 99%

Mobile monitoring for mapping spatial variation in urban air quality: Development and validation of a methodology based on an extensive dataset

Bossche

Peters

Verwaeren

et al. 2015

Atmospheric Environment

191

132

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Mobile monitoring is increasingly used as an additional tool to acquire air quality data at a high spatial resolution. However, given the high temporal variability of urban air quality, a limited number of mobile measurements may only represent a snapshot and not be representative. In this study, the impact of this temporal variability on the representativeness is investigated and a methodology to map urban air quality using mobile monitoring is developed and evaluated.A large set of black carbon (BC) measurements was collected in Antwerp, Belgium, using a bicycle equipped with a portable BC monitor (micro-aethalometer). The campaign consisted of 256 and 96 runs along two fixed routes (2 and 5 km long). Large gradients over short distances and differences up to a factor of 10 in mean BC concentrations aggregated at a resolution of 20 m are observed. Mapping at such a high resolution is possible, but a lot of repeated measurements are required. After computing a trimmed mean and applying background normalisation, depending on the location 24 to 94 repeated measurement runs (median of 41) are required to map the BC concentrations at a 50 m resolution with an uncertainty of 25 %. When relaxing the uncertainty to 50 %, these numbers reduce to 5 to 11 (median of 8) runs. We conclude that mobile monitoring is a suitable approach for mapping the urban air quality at a high spatial resolution, and can provide insight into the spatial variability that would not be possible with stationary monitors. A careful set-up is needed with a sufficient number of repetitions in relation to the desired reliability and spatial resolution. Specific data processing methods such as background normalisation and event detection have to be applied.

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Using advanced dispersion models and mobile monitoring to characterize spatial patterns of ultrafine particles in an urban area

Cited by 36 publications

References 21 publications

Modelling the Mixing of Size Resolved Traffic Induced and Background Ultrafine Particles from an Urban Street Canyon to Adjacent Backyards

Modelling the Mixing of Size Resolved Traffic Induced and Background Ultrafine Particles from an Urban Street Canyon to Adjacent Backyards

Estimating the contribution of photochemical particle formation to ultrafine particle number averages in an urban atmosphere

Mobile monitoring for mapping spatial variation in urban air quality: Development and validation of a methodology based on an extensive dataset

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