A comparison of atmospheric transport models for traffic emissions

De in Nederland gebruikte rekenmodellen voor luchtkwaliteit langs snelwegen en stadswegen geven wisselende resultaten. Voor berekening van jaargemiddelde concentraties van stikstofdioxide en fijn stof zijn de verschillen tussen modellen beperkt. Bij de berekening van meer specifieke aspecten van luchtkwaliteit, bijvoorbeeld het aantal overschrijdingsdagen, kunnen de verschillen tussen modelresultaten aanzienlijk groter zijn. Atmosferische verspreidingsmodellen berekenen luchtkwaliteit als gevolg van emissies door het verkeer. In Nederland is een aantal van deze verspreidingsmodellen in gebruik bij overwegend commerciele bureaus. Zij voeren berekeningen uit in opdracht van overheid en bedrijfsleven. De rekenmodellen die deze bureaus gebruiken werken volgens uiteenlopende rekenmethoden. Om vast te stellen in hoeverre de resultaten van de verschillende modellen met elkaar overeenstemmen, zijn in dit onderzoek zes in Nederland gebruikte rekenmodellen met elkaar vergeleken. Bij de berekening van de jaargemiddelde concentratie van stikstofdioxide en fijn stof langs snel- en stadswegen, liggen de resultaten van de modellen binnen een marge van 10-15% rond het gemiddelde van de modellen. Bij de berekening van het aantal overschrijdingsdagen voor fijn stof langs snelwegen liggen de verschillende modelresultaten echter in een bandbreedte van 30% rond het gemiddelde. Voor een typische stadswegsituatie is die bandbreedte 50%.This report presents the results of an intercomparison study of six atmospheric transport models for traffic situations in the Netherlands. A number of test cases were defined in consultation with the model owners in which the input parameters to the models, such as emissions, meteorological conditions and road characteristics. Two base cases were defined: one for roadways and one for urban roads, along with a number of variants on these two base cases. The variants, for example, consisted of different meteorological conditions, different background concentrations and the presence of a noise barrier. The model owners calculated - for both base cases and variants - the annual concentration of NO2 and PM10 and the number of days in which the daily threshold of 50 ug/m3 of PM10 is exceeded. For the roadway test cases annual levels of NO2 and PM10 calculated by the different models are within about 10% of the average of all model results. The large difference found in the number of exceedence days was caused by the difference in the methods used to derive the exceedence days. When using one standard method, as in the Dutch regulations, this difference fell to within 30%. Because of technical reasons only the "street canyon" variant was considered for urban roads. In this variant the model results were between 10% and 15% for NO2 and PM10, respectively, of the average of all models. If the contribution of the road alone is considered (i.e. comparing the concentrations without the prescribed background concentration), the models differ by a factor of 2 to 3 and the number of exceedence days for PM10 by a factor of 2.VROM-DG

A comparison between concentrations calculated with CAR II 5.0 and concentrations measured via the air quality network

Lokale overheden gebruiken het model CAR II (Calculation of Air pollution from Road traffic) voor de berekening van de luchtkwaliteit in verkeersbelaste situaties. Uit onderzoek van het RIVM blijkt dat de berekende stikstofdioxide en fijn stof concentraties redelijk goed overeen komen met metingen. De berekende concentraties zijn gemiddeld enkele microgrammen per kubieke meter hoger respectievelijk lager dan de gemeten stikstofdioxide en fijn stof concentraties. Op basis van door gemeenten zelf aangeleverde verkeersgegevens zijn voor de jaren 2003, 2004 en 2005 berekeningen met CAR II, versie 5.0, uitgevoerd in de straten waar meetstations van het van het Landelijk Meetnet Luchtkwaliteit van het RIVM staan. De resultaten van de berekeningen voor stikstofdioxide en fijn stof zijn vervolgens vergeleken met metingen in de straten over dezelfde periode. De berekende stikstofdioxide concentraties zijn gemiddeld ruim twee microgram per kubieke meter hoger dan de gemeten concentraties. De berekende fijn stof concentraties zijn gemiddeld iets lager dan de gemeten concentraties. Er is voor fijn stof een grotere spreiding in de geconstateerde verschillen dan voor stikstofdioxide het geval is. De resultaten van CAR II voldoen voor de jaargemiddelde concentratie van zowel stikstofdioxide als fijn stof aan de in de wet gestelde eisen voor de nauwkeurigheid van de bepaling van jaargemiddelde concentraties. In hoeverre de resultaten van de uitgevoerde vergelijking een garantie zijn voor de betrouwbaarheid en/of de toepasbaarheid van CAR voor toekomstige jaren is moeilijk te zeggen. Het is niet onmogelijk dat verschillende bouwstenen in de huidige CAR onvolkomenheden bevatten die elkaar nu (deels) compenseren.Dutch municipalities use the model CAR II (Calculation of Air pollution from Road traffic) to estimate local air quality in streets with traffic. RIVM has shown that the concentrations of nitrogen dioxide and particulate matter, as calculated by CAR II, version 5.0, are in fairly good agreement with measurements. Calculated concentrations are, on average, a few micrograms per cubic metre higher (for nitrogen dioxide) or lower (for particulate matter) compared to measurements. Based on traffic information provided by municipalities, calculations were performed using CAR II, version 5.0, for the years 2003, 2004 and 2005 for those streets where a measuring station of the national air quality measuring network of the RIVM is located. The results of the calculations were compared with measurements during the same period. Calculated nitrogen dioxide concentrations are on average just over two micrograms per cubic metre higher than measured concentrations. For particulate matter the calculated concentrations are just below measured levels. Furthermore, the spread in differences between measured and calculated concentrations is larger for particulate matter. With respect to accuracy of the calculations, the yearly averaged concentrations calculated by CAR II comply with legal regulations. It will be difficult to determine to what extent the results of the present study can be used to indicate the reliability and applicability of the CAR model in future. It is also quite possible that several modules of CAR contain errors, which, at present, counteract each other.VROM-LM

Het 'VELD'-project, addendum. Uitwerking juli en augustus 2003

In een gebied van 3x3 km rond het dorp Vragender in de Achterhoek zijn uitgebreid metingen van ammoniakconcentraties (NH3) gedaan en emissies berekend aan de hand van in detail geregistreerde agrarische activiteiten. Op basis van deze emissies zijn modelberekeningen gedaan met het OPS-STe (korte termijn) verspreidingsmodel.VRO

Technical description of the RIVM/KNMI PUFF dispersion model. Version 4.0

This report provides a technical description of the RIVM/KNMI PUFF model. The model may be used to calculate, given wind and rain field data, the dispersion of components emitted following an accident, emergency or calamity; the model area may be freely chosen to match the area of concern. The report concentrates on model structure and on model inputs and output. The significance of input parameters is explained and first order estimate values for these are provided. The model's inputs and output are illustrated using examples.<br

Technische beschrijving van het RIVM/KNMI PUFF-verspreidingsmodel. Versie 4.0

This report provides a technical description of the RIVM/KNMI PUFF model. The model may be used to calculate, given wind and rain field data, the dispersion of components emitted following an accident, emergency or calamity; the model area may be freely chosen to match the area of concern. The report concentrates on model structure and on model inputs and output. The significance of input parameters is explained and first order estimate values for these are provided. The model's inputs and output are illustrated using examples.RIV

SLAM, een transportmodel voor de korte termijn en de korte afstand met als toepassing de beschrijving van de verspreiding van ammoniak

SLAM (Short-term Local scale Ammonia transport Model) has been developed to calculate the ammonia concentrations in a multiple source area on a short term (hour) and local scale (100 m up to 15 km). In SLAM the dispersion in the surface layer is modelled using a description given by Gryning et al. (1987). The model also takes into account dry deposition and chemical conversion of ammonia as well as a background concentration caused by remote sources outside the model area. The meteorological input parameters are hourly averaged values of wind speed, wind direction and its standard deviation, temperature and global radiation. The grid setting is limited to 75 x 75 grids within an area of 15 x 15 km. Also extra receptor points can be specified. Basically the number of sources is unlimited but will be restricted by computing time. A sensitivity analysis of several model parameters (except emission strength) showed that wind speed, standard deviation of the lateral wind global radiation, source height and height at which the concentration was calculated, were the most important factors influencing the calculated concentrations. Uncertainties in emissions are directly translated into to model results and are expected to be the largest uncertainty source. SLAM largely overestimated measured concentrations when the wind velocity was 1.5 m s-1 SLAM calculated a 10-15% higher yearly averaged concentration. Differences between measured and calculated diurnal concentration patterns were 10-30%. From the comparison with mobile measurements it was concluded that the spatial distribution of the ammonia concentration in time by SLAM was reasonable represented. Large deviations between the calculated and measured concentrations could be attributed to a strong variation in local emissions not represented in the inventory. SLAM can easily be adjusted or extended to describe the concentration of other gases and aerosols emitted from multiple source areas.<br

Lange termijn metingen van gamma-HCH in neerslag in Nederland

The results of 20 years of measuring gamma-HCH in precipitation in the Netherlands are presented here. Analysis has revealed a systematic seasonal behaviour, with enhanced levels of gamma-HCH in precipitation from April through June. Evidence was found for a statistically significant change in concentrations during the last 20 years. Measurement results from the last three years (1999-2001) showed a clear downward trend, suggesting a decline in lindane emissions. An evaluation of measurement results from north-west Europe confirms the large-scale distribution of gamma-HCH in precipitation in north-west Europe. Given the large uncertainties in emission estimates and in modelling of atmospheric transport and deposition, measurements are concluded to form a better tool for monitoring the changes in environmental quality and emissions.De resultaten van 20 jaar metingen gamma-HCH in neerslag in Nederland worden gepresenteerd. Analyse van de data toont aan dat er sprake is van een systematisch seizoensgedrag met verhoogde niveaus van gamma-HCH in neerslag in de periode van april tot en met juni. Er zijn aanwijzingen gevonden voor een statistisch significante verandering in de concentraties in de afgelopen 20 jaar. De meetresultaten van de afgelopen drie jaar (1999-2001) laten een duidelijke dalende trend zien. Dit suggereert een afname in de lindaan emissies. Een evaluatie van meetresultaten uit noordwest Europa bevestigt de grootschalige verspreiding van gamma-HCH in neerslag in noordwest Europa. Op basis van de grote onzekerheden in emissieschattingen en in het modelleren van het atmosferisch transport en depositie wordt geconcludeerd dat metingen een beter instrument zijn om veranderingen in de milieukwaliteit en in de emissies te monitoren

[SLAM, a Short-term and Local-scale Ammonia transport Model.]

SLAM (Short-term Local scale Ammonia transport Model) has been developed to calculate the ammonia concentrations in a multiple source area on a short term (hour) and local scale (100 m up to 15 km). In SLAM the dispersion in the surface layer is modelled using a description given by Gryning et al. (1987). The model also takes into account dry deposition and chemical conversion of ammonia as well as a background concentration caused by remote sources outside the model area. The meteorological input parameters are hourly averaged values of wind speed, wind direction and its standard deviation, temperature and global radiation. The grid setting is limited to 75 x 75 grids within an area of 15 x 15 km. Also extra receptor points can be specified. Basically the number of sources is unlimited but will be restricted by computing time. A sensitivity analysis of several model parameters (except emission strength) showed that wind speed, standard deviation of the lateral wind global radiation, source height and height at which the concentration was calculated, were the most important factors influencing the calculated concentrations. Uncertainties in emissions are directly translated into to model results and are expected to be the largest uncertainty source. SLAM largely overestimated measured concentrations when the wind velocity was 1.5 m s-1 SLAM calculated a 10-15% higher yearly averaged concentration. Differences between measured and calculated diurnal concentration patterns were 10-30%. From the comparison with mobile measurements it was concluded that the spatial distribution of the ammonia concentration in time by SLAM was reasonable represented. Large deviations between the calculated and measured concentrations could be attributed to a strong variation in local emissions not represented in the inventory. SLAM can easily be adjusted or extended to describe the concentration of other gases and aerosols emitted from multiple source areas.DGM/L

Lange-afstandstransport van Persistente Organische Verontreinigingen, I: Beschrijving van oppervlakte-atmosfeer uitwisselings modules en implementatie in EUROS

Beschrijving van een model voor de uitwisseling van gasvormige Persistent Organic Pollutants (POP) tussen het aardoppervlak en de atmosfeer, en de toepassing in het Euleriaanse verspreidingsmodel EUROS. Als voorbeeld is de netto depositie van lindaan over Europa berekend. Bij niet-emissiegebieden op land werd gevonden dat natte depositie verantwoordelijk is voor gemiddeld 75% van de totale toevoer van lindaan, terwijl gemiddeld ongeveer 30% re-emissie optrad. Op zee bleek droge depositie, de belangrijkste bron van lindaan, verantwoordelijk voor gemiddeld 72% van de totale toevoer, en bedroeg de fractie re-emissie gemiddeld 15%. De concentraties van lindaan in neerslagwater van een aantal stations rond de Noordzee worden door het model met een factor 3 overschat. Een model gevoeligheidsanalyse laat zien dat de emissiedata de grootste bron van onzekerheid zijn.Concerns a description of a model for the exchange of gaseous Persistent Organic Pollutants (POP) at land and sea surfaces and its application in the Eulerian air pollution transport model EUROS. Sample simulations of the net deposition of lindane over Europe are discussed. For non-emission areas over land, wet deposition was found to account for on average 75% of the total input of lindane, while on average 30% of this input re-volatilizes. Over sea, dry deposition accounts for on average 72% of the total input, the average re-volatilization fraction being 15%. The concentrations of lindane in rainwater for a number of stations around the North Sea are overestimated by the model by about a factor of 3. A model response analysis showed that the emission data are the main cause of uncertainty in the calculated concentrations.DGM/L