Alison Redington* and Derrick Ryall* Dick Derwent** MODELLING PARTICULATE SULPHATE AND NITRATE IN NORTH WEST EUROPE WITH A LAGRANGIAN DISPERSION MODEL Alison Redington* and Derrick Ryall* Dick Derwent** * Met Office, Exeter, United Kingdom ** rdscientific, Newbury, United Kingdom EMEP Workshop on PM Measurement and Modelling New Orleans, April 2004
PM10 TRENDS IN THE UNITED KINGDOM IN URBAN CENTRES
UK POLICY-MAKERS CONCERNS What are the levels, sources and characteristics of PM10 and PM2.5 in the UK ? What are the trends in PM10 and PM2.5 ? What are the extent of exceedances of air quality targets currently and in the future ? Some form of modelling is required to answer these questions.
MODELLING SUSPENDED PARTICULATES IN THE UNITED K INGDOM Primary vs secondary and inorganic vs organic particulate matter Particulate sulphate and nitrate is main focus of this study Role of long range transboundary transport and local formation Application of the UK Met Office NAME Lagrangian dispersion model Aim is to give source attribution to particulate sulphate and nitrate at 15 minutes time resolution and 15 km spatial resolution
UK Met Office’s operational dispersion model (1-1000’s kms) NAME MODEL UK Met Office’s operational dispersion model (1-1000’s kms) Lagrangian - pollutant modelled by large numbers of ‘parcels’ released into the ‘model’ atmosphere Model driven by meteorological fields from the Met Office’s operational forecast model Particles are transported by local mean wind in 3-dimensions Diffusion by turbulence is represented by random walk techniques, displacing particles in both the horizontal and vertical Before talking about the modelling work I’ll briefly introduce the NAME model. NAME is the UK met offices atmospheric dispersion model which can be applied from local to regional scale. It is used widely for emergency response purposes and indeed was developed following the Chernobyl accident. It is a Lagrangian model where the pollutant is modelled by releasing large numbers of particles into the model atmosphere. The dispersion model is driven by 3D meteorological fields from the Met Offices numerical weather prediction model - the Unified Model. The local mean wind transports the particles and diffusion by turbulence is represented by random walk techniques. The particle mass can be changed by deposition processes, both wet and dry, and by chemical transformation.
LAGRANGIAN DISPERSION MODEL Receptor Source 65°N 20°E emissions grid 43°N 15°W Long-range transport and dispersion of an inert tracer
max O3 125 ppb 11/08/03
FORMATION OF SECONDARY INORGANIC AEROSOLS SO2 + OH = HOSO2 HOSO2 + O2 = HO2 + SO3 SO3 + H2O = H2SO4 = sulphate aerosol SO2aq + H2O2 = H2SO4 = sulphate aerosol SO2aq + O3 = H2SO4 = sulphate aerosol NO2 + OH = HNO3 = nitrate aerosol NO2 + O3 = NO3 + O2 NO2 + NO3 = N2O5 = nitrate aerosol NH3aq + HNO3aq = NH4NO3aq = nitrate aerosol
OPERATIONS IN A LAGRANGIAN DISPERSION MODEL Emit some new air parcels, each loaded up with SO2 and NOx Move air parcels to new locations with 3-d turbulent wind fields Locate air parcels in Eulerian grid Calculate air concentrations in Eulerian grid Allow for chemical transformations and deposition Recalculate air parcel masses This is the main time-stepping algorithm in a source-oriented Lagrangian dispersion model.
ANNUAL AVERAGE SO2 CONCENTRATIONS - 1996 Compares well with EMEP observations for 1996
ANNUAL AVERAGE PARTICULATE SULPHATE CONCENTRATIONS - 1996 Compares well with observations for 1996
ANNUAL AVERAGE NO2 CONCENTRATIONS - 1996 Compares well with rural observations for 1996
ANNUAL AVERAGE HNO3 CONCENTRATIONS - 1996 No observations for direct comparison
ANNAUL AVERAGE PARTICULATE NITRATE CONCENTRATIONS - 1996 No observations for direct comparison
ANNUAL AVERAGE SECONDARY INORGANIC AEROSOL - 1996 Tendency to overestimate rural PM10 observations
EMEP MONITORING SITE NETWORK
STATISTICS FOR EVALUATION OF DAILY MEASURED AND MODELLED PARTICULATE SULPHATE FOR 1996 agreement is somewhat disappointing, over-prediction during wintertime, lack of background sulphate from North Atlantic
STATISTICS FOR EVALUATION OF MONTHLY MEASURED AND MODELLED HNO3 AND NO3 FOR 1999-2000 nitrate aerosol is slightly over-predicted, nitric acid is under-predicted and shows poorer performance, however the data are inadequate
EMEP MONITORING SITE NETWORK
WINTERTIME AND SUMMERTIME MODEL PERFORMANCE timing of peaks is excellent, but overestimation during winter
SOURCE ATTRIBUTION Each air parcel emitted into the NAME model keeps a record of the location where it was emitted It is straightforward to construct a map showing the origins of the particulate sulphate and nitrate found at any location in the model The source allocation given for secondary pollutants refers to the origins of the primary pollutant precursors
MEAN DIURNAL VARIATIONS IN PARTICULATE NITRATE DURING 10 DAYS IN MAY 2003 AT A RURAL EMEP SITE AT HARWELL OXFORDSHIRE UK Preliminary data kindly provided by Steve Moorcroft, Casella Stanger
CONCLUSIONS Model development is severely hampered by lack of good observations of the individual components of PM10 and PM2.5 These need to be of hourly time resolution and co-located with other air quality measurements Artefact-free nitrate observations are particularly sparse in Europe and must distinguish ammonium nitrate from sodium and calcium nitrates Cloud liquid water content, low cloud amount, precipitation amounts and boundary layer depths are difficult quantities to obtain from meteorological models with sufficient accuracy for secondary particle modelling
ACKNOWLEDGEMENTS To the United Kingdom Department for Environment Food and Rural Affairs for their support through contract CPEA 7 To Alison Redington and Derrick Ryall United Kingdom Met Office for their patient work with the NAME model To Steve Moorcroft, Casella Stanger for contributing his preliminary continuous observations of particulate nitrate To members of the United Kingdom Air Quality Expert Group for their helpful discussions To Environment Canada for their generous offer of help with travel costs