We have over 12,000 students, from over 100 countries, within one of the safest campuses in the UK


93% of Lancaster students go into work or further study within six months of graduating

Home > Research > Publications & Outputs > Regional Scale Modelling of Particulate Matter ...
View graph of relations

« Back

Regional Scale Modelling of Particulate Matter in the UK: Source Attribution and Assessment of Uncertainties.

Research output: Contribution to journalJournal article


<mark>Journal publication date</mark>05/2007
<mark>Journal</mark>Atmospheric Environment
Number of pages13
<mark>Original language</mark>English


The models HARM and ELMO are used to investigate the importance of different source categories contributing to total PM10 (SIA, SOA and primary particulate matter) across the UK and the impact of uncertainties on both present day and future concentration estimates. Modelled concentrations of SIA (secondary inorganic aerosol) are compared against data from the UK's Nitric Acid and Aerosol Network and SOA (secondary organic aerosol) against measurements made at the Bush Estate, Edinburgh. These data indicate that the HARM/ELMO modelling approach comes close to achieving mass closure. Comparison with national maps of total PM10 indicate that the models underestimate particulate matter concentrations around large conurbations, probably due to the localised nature of emissions of primary particulates in these areas and model scale. The models are used to attribute particulate matter to different source and size categories, assessing the relative importance of primaries, SIA and SOA; the contributions of anthropogenic and biogenic precursors of SOA; the relative importance of PMcoarse (PM10–PM2.5) and PMfine (PM2.5) and UK vs. other EMEP area sources. The implications of these attributions for emissions control policies are discussed. The impact of uncertainties in emissions of the sources of primaries, SIA and SOA are explored. For primary PM10 and SOA this has been achieved through emissions scaling and for SIA using the GLUE (Generalised Likelihood Uncertainty Estimation) approach. The selection of acceptable model parameter sets has been based on the need to retain the capability to model deposition of S and N species. The impact of uncertainty on estimates of present day SIA concentrations is illustrated for sites in the Nitric Acid and Aerosol Network. A more limited assessment for 2010 has been carried out at the national scale, illustrating that inclusion of uncertainty can change modelled concentrations from no exceedance of current air quality objectives, to one of exceedance over large areas of south and east England.