OSPM — A Parameterised Street Pollution Model

Berkowicz, Ruwim

doi:10.1007/978-94-010-0932-4_35

Cited by 123 publications

(108 citation statements)

References 4 publications

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“…The modelling approach has been described previously 16,24 . Briefly, the NO x contribution for roadways within a 500m buffer around 31 monitoring locations was modelled using ADMS Roads 25 and OSPM 26 and the contribution from the urban background was modelled using ADMS3. Concentrations from these emission-dispersion models were calibrated by fitting regression models to NO x measurements from the 31 monitoring sites.…”

Section: Modelled Exposure To Air Pollutionmentioning

confidence: 99%

Characterising socio-economic inequalities in exposure to air pollution: A comparison of socio-economic markers and scales of measurement

Goodman

Wilkinson

Stafford³

et al. 2011

Health & Place

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Section: Modelled Exposure To Air Pollutionmentioning

confidence: 99%

Characterising socio-economic inequalities in exposure to air pollution: A comparison of socio-economic markers and scales of measurement

Goodman

Wilkinson

Stafford³

et al. 2011

Health & Place

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“…The local scale dispersion modelling is based on a combined application of the road network dispersion model CAR-FMI (e.g., Härkönen, 2002), the Operational Street pollution model OSPM (e.g., Berkowicz, 2000;Kukkonen et al, 2003) and the Urban Dispersion Model UDM-FMI (Karppinen et al, 2000a, b), regarding dispersion from streets and roads, dispersion in a street canyon, and dispersion from various point, area and volume sources, respectively.…”

Section: Helsinki Uaqifsmentioning

confidence: 99%

Integrated systems for forecasting urban meteorology, air pollution and population exposure

Hänninen²,

et al. 2007

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Abstract. Urban air pollution is associated with significant adverse health effects. Model-based abatement strategies are required and developed for the growing urban populations. In the initial development stage, these are focussed on exceedances of air quality standards caused by high short-term pollutant concentrations. Prediction of health effects and implementation of urban air quality information and abatement systems require accurate forecasting of air pollution episodes and population exposure, including modelling of emissions, meteorology, atmospheric dispersion and chemical reaction of pollutants, population mobility, and indoor-outdoor relationship of the pollutants. In the past, these different areas have been treated separately by different models and even institutions. Progress in computer resources and ensuing improvements in numerical weather prediction, air chemistry, and exposure modelling recently allow a unification and integration of the disjunctive models and approaches. The current work presents a novel approach that integrates the latest developments in meteorological, air quality, and population exposure modelling into Urban Air Quality Information and Forecasting Systems (UAQIFS) in the context of the European Union FUMAPEX project. The suggested integrated strategy is demonstrated for examples of the systems in three Nordic cities: Helsinki and Oslo for assessment and forecasting of urban air pollution and Copenhagen for urban emergency preparedness.

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“…The OSPM model is a parameterized model for flow and dispersion conditions in street canyons (Berkowicz 2000;Berkowicz et al 2008). Concentrations of exhaust gases are calculated as the sum of the direct contribution from traffic and the recirculation part of the pollutants in the street.…”

Section: Building-based Air Quality Model Systemmentioning

confidence: 99%

“…In particular, a deterministic building-based air quality model system for Macao has been developed by the authors (Tang and Wang 2007;Sheng and Tang 2011a, b). The system integrates the operational street pollution model (OSPM) (Berkowicz 2000), digital maps of the road network, building layout and topographic information, an urban landscape model, and the GIS. The building-based model system has the feature that the street configuration and traffic data can be automatically extracted building by building and therefore, the complex spatial variation of traffic emission, urban geometry, and air pollution can be captured.…”

Section: Introductionmentioning

confidence: 99%

Risk assessment of traffic-related air pollution in a world heritage city

Sheng

Tang

2012

Int. J. Environ. Sci. Technol.

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To support environmental risk management in a world heritage city, this paper presents high spatial-resolution maps of air pollutants for the Macao Peninsula. In particular, the risk of exposure to traffic-related nitrogen dioxide pollution for the 22 world heritage monuments in the Historic Center of Macao was assessed. The air-pollution mapping was performed by a building-based air quality model system, in which the traffic-related air pollutions at 5,965 receptor points in the Macao Peninsula were modeled and the average spatial resolution was 727 receptors/km 2 . The results indicate that under the conditions of the evening peak hour and the north wind direction sector 0-20°, air quality in the Macao Peninsula is the worst. About 14.1% of the modeled nitrogen dioxide concentrations at the 5,965 receptor points exceed the national ambient air quality standard for scenic spot of 120 lg/m 3 in China. Two world heritage monuments, i.e., the ''Leal Senado'' Building and the Cathedral, are exposed to excessively high nitrogen dioxide concentrations of 135.9 and 121.1 lg/m 3 , respectively. The results in this paper could help decision makers to develop effective strategies to protect the world cultural heritages in Macao for future human generations to appreciate and enjoy.

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OSPM — A Parameterised Street Pollution Model

Cited by 123 publications

References 4 publications

Characterising socio-economic inequalities in exposure to air pollution: A comparison of socio-economic markers and scales of measurement

Characterising socio-economic inequalities in exposure to air pollution: A comparison of socio-economic markers and scales of measurement

Integrated systems for forecasting urban meteorology, air pollution and population exposure

Risk assessment of traffic-related air pollution in a world heritage city

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