Distributions etc models

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Scope
Distributions etc models describes

Description

EEA Topic report No 19/1996 Ambient air quality, pollutant dispersion and transport models Appendix 3 Regional/continental scale models

Model name	Institution	Application	Type of model	Domain	Simulation period	Plume rise	Stability classification	Meteorology	Reference
IFDM	VITO Mol, Belgium	Stack emissions	Gaussian	Local	Yearly averages, hourly and daily percentiles	Briggs	Bultynk-Malet	Hourly time series	R. Cosemans, J. Kretzschmar and G. Maes, 1992
PLUIMPLUS	Staatsvitgeverij, ‘s Gravenhage, Nederland	Stack emissions	Gaussian in vertical Uniform in 30° -sector horizontal	Local	Yearly averages, empirical hourly and daily percentiles	Briggs	KNMI-system, surface roughness	Joint frequency matrix	Kleine Commissie Modellen, 1976
ISCST 2	Environmental Protection Agency, USA	Stack emissions	Gaussian	Local	1 hour to yearly average, n largest concentrations time series	Briggs	Pasquill Gifford classes, urban and rural modes	Hourly time series	EPA, Trinity Consultants 1992
AUSTAL 86	TA-LUFT, Germany	Stack emissions	Gaussian	Local	Yearly average, 98-percentiles	Briggs	TA-LUFT classes (4)	Joint frequency matrix	TA-LUFT, 1986
OML	National Environmental Research Institute, Denmark	Stack emissions	Gaussian	Local	Yearly averages, n largest hourly average, 99-percentiles	Briggs	Boundary layer scaling parameterisation	Hourly pre-processed time series	P. Løfstrøm and H.R. Olesen, 1988
UK-ADMS	CERC and UK Meteorological Office, United Kingdom	Stack emissions	Gaussian Non-Gaussian in vertical in convective situations	Local	1 hour to yearly averages, percentiles	Equations based on fluxes of mass and heat	Boundary layer parameterisation	Hourly pre-processed time series	Carruthers et al., 1992
HPDM	Sigma Research Corporation, USA	Stack emissions	Gaussian	Local	1 hour to yearly averages, n largest hourly average, 99-percentiles	Briggs	Boundary layer parameterisation	Hourly pre-processed series or on site measurements	Hanna and Paine, 1989
INPUFF	Environmental Protection Agency, USA	Stack emissions	Gaussian, puff trajectory	Local	1 hour to yearly averages, percentiles	Briggs	Pasquill-Gifford	Hourly pre-processed time series	Petersen and Lavdas, 1986
CTDMPLUS	Environmental Protection Agency, USA	Stack emissions	Gaussian	Local	1 hour to yearly average,	Briggs	Boundary Layer scaling parameterisation	Hourly pre-processed time series	EPA, Perry et al. 1989
SCALTURB	Norwegian Institute for Air Research (NILU), Norway	Stack emissions	Dispersion regions, Semi-Gaussian	Local	1 hour to yearly averages, percentiles	Briggs	Boundary layer parameterisation	Hourly pre-processed time series	Gryning, Holtslag, Irwin and Sivertsen, 1987
CAR	RIVM, TNO (The Netherlands)	road pollution	semi-empirical relation based on wind tunnel experiments and field campaigns	various street types (open lanes <==> street canyons)	yearly averaged; 98 percentiles	NO2 according to photostationary equilibrium		yearly averaged	Eerens et al, 1993
CARSMOG	RIVM, TNO (The Netherlands)	real time modelling of road pollution	semi-empirical relations (see CAR) combined with actual measurements	various street types (open lanes <==> street canyons)	hourly averaged	NO2 according to photostationary equilibrium		actual hourly values	den Tonkelaar W.A.M. 1995
CAR-FMI	Finland Meteorological Institute, Finland	Road pollution	Finite line source, partly analytical Gaussian	Local	1 hour	Boundary layer scaling	Discrete parcel method NOx, O2, O3	Hourly time series	Härkönen et al., 1994
ROADAIR	Norwegian Institute for Air Research (NILU), Norway	Road pollution	Finite line source, Gaussian Emission model based on traffic composition and driving conditions	Local	1 hour	Pasquill-Gifford stability classes	Conversion of NO to NO2 by O3.	Worst case 1 hour	Larssen and Torp, 1993
CONTILINK	Norwegian institute for Air Research (NILU), Norway	Road pollution	Finite line source Gaussian, semi-stationary	Local	Hourly concentrations	-	Pasquill Gifford	Wind direction, wind speed, stability	Larssen et al., 1993

References

• Air Quality Impact Assessment: Cairo International Airport, Terminal 3 with New Runway (NILU)
• The use of air pollution models (NILU)
• Ambient air quality, pollutant dispersion and transport models (EEA)

• AirView (allows you to query AirBase and visualise air quality data)

Definition

Causality

List of parents:

• item 1

Formula

Analytica_id:

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