Dispersion modelling work at King’s College London

David Carslaw

Environmental Research Group

King’s College London

London Air Quality Network-LAQN

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Insight from measurements– Secondary

pollutants from UK/Europe

– Natural particle episodes e.g. Saharan dust in March 2000

– Very localised conditions e.g. congested traffic and the specific configuration of buildings 0

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Particle episode, February 2003

Model development

• Data from LAQN has been used in the development of practical models for London– NO2 and PM10 regression and receptor models

(Carslaw et al., 2001; Fuller et al., 2002)– Techniques used in tandem with ADMS to

predict concentrations London-wide

Carslaw, D.C., Beevers, S.D., Fuller, G., 2001. An Empirical Approach for the Prediction of Annual Mean Nitrogen Dioxide Concentrations in London. Atmospheric Environment, Vol. 35, 1505-1515.

Fuller, G.W., Carslaw, D.C., Lodge, H.W., 2002. An Empirical Approach for the Prediction of Daily Mean PM10 Concentrations. Atmospheric Environment, Vol. 36, 1431-1441.

Met pre-processors• Some account has been

taken of urban meteorology based on parameterisations in the literature– Addition of anthropogenic

heat flux

– Approach is too simplistic

– Need for more appropriate met data for urban modelling (heat fluxes, energy balances)

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Application of dispersion models in London

• Projections of future base case concentrations of NO2 and PM10

• Analysis of the efficacy of different potential policies in London e.g. a low emission zone and the use of new vehicle technologies

Congestion charging (CCS)

• ERG will be working with Transport for London to monitor the CCS scheme (AQ measurement, emissions, prediction)

• It will provide an unprecedented level of traffic activity information– Continuous traffic counters– Manual counts – specific

vehicle types– Automatic number plate

recognition (ANPR)

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Congestion charging

• Many interesting research questions:• CCS is a large natural experiment i.e. the effect of a

perturbation

• How atmospheric composition responds to a specific policy in a large urban area

• Potential effects of displacing emissions to hours of the day where dispersion is less efficient

• How secondary pollutants respond to emissions changes over a comparatively small area

• Re-suspended particulate matter from vehicle-induced turbulence

Research priorities

• Urban meteorology– Significantly more information is required

• Connecting the different scales– No one model works at all scales

• Developments in dispersion modelling needs to be matched with developments in emissions inventories– Emission factors, spatial and temporal scales, species

considered– A wider context: urban morphology, heat release etc.– Data management e.g. expertise with GIS