Air quality expert group - Fine particulate matter (PM2.5) in ... - Defra

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Table A2.1.1: Evaluation of CMAQ forecast with hourly PM10 provisional AURN data, 12-26 April 2011. Rural and remote Urban background Number of sites 4 16 12 normal mean bias (%) 8 -14 -24 normal mean error (%) 44 37 41 % of pairs within a factor of two 68 73 68 Forecast the hourly PM10 exceeding 65 µg m -3 Annex 2: PM modelling in the UK Urban proportion correct 0.96 0.91 0.97 odds ratio skill score 0.98 0.90 0.64 3. The WRF-CMAQ air quality model has been used to investigate the sensitivity of PM to a reduction in precursor (sulphur dioxide (SO2), nitrogen oxides (NOx) and ammonia (NH3)) emissions. The simulations are based on 2006 using four months – January, April, July and October – as representatives of winter, spring, summer and autumn respectively, allowing evaluation over a range of different conditions. The response is not easy to predict due to the non-linearity of the relationship between the change in emissions and PM components. 4. The 12 km resolution WRF-CMAQ model run of the UK has been used. It uses the ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble model as the boundary conditions for the Weather Research and Forecasting model (WRF), and emissions from EMEP and the National Atmospheric Emissions Inventory (NAEI); biogenic emissions are calculated using the weather conditions from WRF and the Biogenic Potential Inventory (Dore et al., 2003). CMAQ is operated using the Carbon Bond 05 gas-phase chemistry mechanism, with additional aqueous and aerosol processing. Aerosol concentrations (hourly values in each grid point) and wet and dry deposition are output for 18 organic species, three natural organic species, nitrate (NO3 - ), sulphate (SO4 2- ), chloride (Cl - ), ammonium (NH4 + ), sodium (Na + ), soil, elemental carbon (EC), and additional fine and coarse mode PM. 5. The response to emissions reductions in particulate matter were in line with those reported for the PTM (A2.6). The reduction in SO2 emissions has the largest overall effect on PM, the largest individual effect being on sulphate. This is a non-linear response which also varies with season and location. The response of SO4 2- and NH4 + show a seasonal response which is lower in winter than summer. Reducing NOx emissions has the smallest effect. There is an overall increase in sulphate for January, April and October as reported for the PTM, with no effect in summer. The effects on both fine and coarse NO3 - show a less than linear response, with a large spatial variation. Again, reducing NH3 emissions shows a response very similar to the PTM studies. It results in a reduction in NH4 + and fine NO3 - by similar amounts, with a smaller reduction in SO4 2- . This is the only scenario where no PM component increases. 149
PM2.5 in the UK 150 6. The non-linearity of the model response to emission reduction is the result of complex interactions. It highlights the importance of introducing the emissions into the model using realistic temporal profiles. A2.2: WRF/CMAQ applications at the Centre for Atmospheric and Instrumentation Research (CAIR), University of Hertfordshire 7. CMAQ is not currently being used as a policy tool in the UK but is being considered for regulatory applications as part of the Comparison of Simple and Advanced Regional Models (CREMO) funded by the Environment Agency. Defra is commissioning work to assess the potential of CMAQ to meet its policy needs. The intention of this work will be to develop an operational version of the model for UK policy applications. This and the following section provide examples of applications for the years 2003, 2005 and 2006, which formed part of the AQMEII, MEGAPOLI (FP7), Defra model inter-comparison and CREMO projects. Further details on the model set-up and applications can be found in Yu et al. (2008) and Chemel et al. (2010). 8. The focus of research has been on PM2.5 and modelled results are compared with the observations from Harwell, London North Kensington and London Bloomsbury. Overall, CMAQ underestimates PM2.5 concentration at the selected sites but reproduces the temporal variations. There are important considerations when comparing modelled and measured data for the results presented here. First, the spatial grid resolution is 18 km x 18 km and is not optimum for simulating pollutants that are, at least partly, generated on smaller, local scales. This set-up has been used as a pragmatic approach to develop a regional configuration to model hourly concentrations over multiple years. Second, previous results (not shown here) have indicated sensitivity of PM2.5 concentrations to boundary conditions, for example, in the comparison conducted with boundary conditions from GEMS and from GEOS-Chem (global air pollution model). Third, the treatment of aerosols is part of ongoing model developmental work and significant changes will be introduced in the next version of CMAQ. The results shown in Figure A2.2.1 are annual PM2.5 modelled results for 2003 using CMAQ version 4.6 and annual PM2.5 modelled results for 2006 using CMAQ version 4.7.1. For 2003 the grid spacing was 15 km. The 2006 run conducted at 18 km grid spacing was part of the AQMEII model intercomparison for a domain which covered all of Europe. 9. The daily average PM2.5 concentrations were calculated for a rural background station Harwell (HAR) for 2003 and 2006, and for urban background stations London North Kensington (LNK) for 2006 and London Bloomsbury (LBB) for 2003. Modelled PM2.5 ground (first level) results are compared with measurements from the selected stations for the year 2006 and 2003 for the appropriate stations in Figure A2.2.1. This figure shows that overall CMAQ values reproduce the temporal variations for all three stations but show about a 30-40% underestimation especially for the urban stations. Further analysis is required to understand the model response during peak occurrences, where it correctly captures the timing but not necessarily the magnitude of the event. This will include examination of the local and regional nature of PM2.5 and its precursors, as well as the governing meteorological processes (simulated with WRF).
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AIR QUALITY EXPERT GROUP Fine Parti
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This is a report from the Air Quali
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II Membership Chair Professor Paul
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IV Acknowledgements The Air Quality
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VI 2.5 Summary 39 2.5.1 What does t
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VIII 5.4 Components of PM2.5 and so
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PM2.5 in the UK 2 Air Quality Direc
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PM2.5 in the UK 4 I.2.1 Concentrati
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PM2.5 in the UK 6 • PM2.5 emissio
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PM2.5 in the UK 8 I.4.1 Modelling r
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PM2.5 in the UK 10 4. In broad term
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PM2.5 in the UK Table 1.2: National
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PM2.5 in the UK 14 17. Dry depositi
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PM2.5 in the UK 16 in ozone in the
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PM2.5 in the UK 18
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PM2.5 in the UK 20 5. The exact for
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PM2.5 in the UK 22 12. These diffic
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PM2.5 in the UK 24 2.3 Methods used
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PM2.5 in the UK 26 (e) During the
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PM2.5 in the UK 28 2.3.3 The Partis
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PM2.5 in the UK 30 35. For non-auto
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PM2.5 in the UK 32 43. Ratification
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PM2.5 in the UK 34 49. Many of the
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PM2.5 in the UK 36 57. Black carbon
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PM2.5 in the UK 38 2.4.4 PM2.5 elem
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PM2.5 in the UK 40 average of 93.6%
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PM2.5 in the UK Annex 1 - PM2.5 mon
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PM2.5 in the UK 44
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PM2.5 in the UK 46 3.2.1 Diurnal va
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PM2.5 in the UK 48 PM2.5/µgm -3 20
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PM2.5 in the UK 50 3.2.4 Seasonal v
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PM2.5 in the UK 52 12. Results are
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PM2.5 in the UK 54 3.4.2 Relationsh
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PM2.5 in the UK 56 Correlation 0.8
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PM2.5 in the UK Figure 3.11: Polar
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PM2.5 in the UK 60 south. Further a
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PM2.5 in the UK 62 3.7 PM2.5 episod
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PM2.5 in the UK 64 secondary ammoni
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PM2.5 in the UK 66 3.8 PM2.5 concen
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PM2.5 in the UK 68 3.9 Composition
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PM2.5 in the UK 70 43. The UK has i
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PM2.5 in the UK 72 NO 3 6 4 2 2000
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PM2.5 in the UK 74 54. PM ammonium
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PM2.5 in the UK 76 58. Data from th
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PM2.5 in the UK 78 (k) Road traffic
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PM2.5 in the UK 80 provided by spec
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PM2.5 in the UK 82 14. The London L
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PM2.5 in the UK Table 4.1: UK emiss
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PM2.5 in the UK 86 24. National inv
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PM2.5 in the UK 88 Figure 4.5: Spat
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PM2.5 in the UK 90 either nanoparti
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PM2.5 in the UK 92 37. Further cons
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PM2.5 in the UK Emissions (ktonnes)
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PM2.5 in the UK 96 Figure 4.7: Spat
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Page 131 and 132: PM2.5 in the UK 120 105. Receptor m
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Page 159: PM2.5 in the UK 148 2. Figure A2.1.
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Page 165 and 166: PM2.5 in the UK 154 (a) (b) modPM 2
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Page 171 and 172: PM2.5 in the UK 160 SIA components
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Page 175 and 176: PM2.5 in the UK 164 A2.6: Photochem
Page 177 and 178: PM2.5 in the UK 166 PM2.5 Emission
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Page 187 and 188: PM2.5 in the UK 176 4. The delivery
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Page 199 and 200: PM2.5 in the UK Chapter 5 Modelling
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