Air quality modelling in London LAEI2013

Transcription

1 Air quality modelling in London LAEI2013 David Dajnak Environmental Research Group, King s College London MRC-HPA Centre for Environment and Health Imperial College London

2 Main Objectives 1. What is King s recipe for mapping London s Air pollution? 2. Model evaluation 3. Air quality apportionment 4. Mapping 2013 using LAEI Can we predict future air quality? (And How will London look like?)

3 What is King s recipe for mapping London s Air pollutio Emission sources in London (we use LAEI2013) Dispersion Model (we use King s LAQT)

4 King s London Air Quality Toolkit (LAQT) descript Modelling-measurement Approach A kernel modelling technique, based on ADMS, describe the initial dispersion Kernels are created using hourly meteorological measurements The contribution from each emission source is calculated by applying each kernel summed onto a fixed grid The LAQT provides annual mean NO X, NO 2, O 3, PM 10 and PM 2.5

5 Treatment of sources A single receptor point is located in the centre of each (1km X 1 km) squares, covered by LAEI.

6 Treatment of sources The model sums together three source categories: First, sources outside the model domain (background concentration) For NO X, we use rural measurements For PM, we use rural and regional sources (secondary PM and natural) Second, within the model domain, but greater than 500m from a receptor location (London background) All London sources represented as volumes sources Third, for those sources within 500m of a receptor location Detailed treatment of local road/gas/rail/aircraft sources

7 Treatment of sources Predictions in London are based upon the LAEI sources and include: Road transport Passenger and freight rail Aviation sources Passenger and commercial shipping Gas heating (domestic and industrial-commercial) Oil and coal combustion sources (domestic and commercial) Large regulated industrial processes (Part A) Small regulated industrial processes (Part B) Construction source (NRMM) Others (agricultural, waster transfer, accidental and outdoor fires, construction/demolition and garden emissions)

8 Cooking emissions sources PM measurement at KC1 estimated between 0.42 and 0.84 g m -3 Cooking emissions sources estimated to produce 692 tonnes of PM Spatially distributed using OS mastermap commercial premises, registered as preparing food in a kitchen, as take away or restaurant Predicted concentration: 0.67 g m -3 at KC1 and 0.34 g m -3 LAEI area

9 Biomass sources Wood burning is poorly represented in the UK Digest of Energy Statistics (DUKES) Difficult to track fuel use, with much wood coming from scavenged sources or small suppliers Much wood burning is for decorative or secondary heating, making it hard to estimate activity from surrogates (such as gas use) It is difficult to represent wood burning PM in the LAEI Biomass emissions, mostly from wood burning, were measured in London Taking an average of all the years available between 2009 and 2014 for both NK3 (North Kensington) and GR3 (Woolwich) sites Annual mean biomass estimated to be 1.07 g m -3

10 Representing road sources King s London Emission Toolkit (LET) provides detailed and flexible traffic emissions required to run LAQT Road emissions are modelled as a series of road links 10 m long Based on geographically accurate Ordnance Survey road map data Six road categories (and associated kernels): Open roads (motorway) Typical roads Street canyon (by orientation) LAQT covers over 2 million 10m road sources Representing railway sources ð Bloomsbury Central London Site Treated in the same way as for roads but using rail network

11 Representing gas sources Height of release Spatial distribution Assumed building heights Commercial gas combustion low-yellow med green high grey very high -navy)

12 Representing Heathrow Airport Aircraft sources were represented using the same method as roads Account was taken of The effect of accelerating aircraft The rapidly reducing effect of aircraft emissions to ground level concentrations at different aircraft heights

13 Model Evaluation Of course many factors cannot be adequately described and modelling deficiencies exist. BUT The LAQT provides a compromise between detailed input data availability and model flexibility.

14 Model Evaluation NO X and NO 2 MRC-HPA Centre for Environment and Health Imperial College London

15 Model Evaluation PM 10 and PM 25 MRC-HPA Centre for Environment and Health Imperial College London

16 Air Quality Apportionment in 2020 (LAEI2013) At first it seems that high concentration blowing from outside of London or continent could be largely responsible for London s problem BUT

17 Cross sectional concentrations PM NO X concentration ( g m -3 ) NO X Central London 0 Transect (North-South) across London In Fact air quality problems are mostly caused by local emission sources

18 Present and Future Predictions

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21 Can we predict future Air quality? The emission inventory is not perfect Emission factor need to be improved in present and future (for new technology such as hybrid or old/new Euro Engine classification) Calibrating can affect Future modelling performance How the LAEI will change in future years is uncertain Future changes from outside of London source is uncertain Air quality is very sensitive to Meteorology MRC-HPA Centre for Environment and Health Imperial College London

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28 Take Away Message 1. What is the recipe for mapping London Air quality? LAEI dispersion + measurement 2. Are others responsible? No, Peak of pollution always near local sources 3. What is main cause of pollution? Road traffic 4. LAEI2013 mapping High concentration around road network NRMM blobs have disappeared 5. Future Predictions Predicting future is always a risk (meteorology uncertainty) Improve the emission inventory (remove calibration) By 2030, NO 2 is dropping but remain a problem And PM is not changing very much because non-exhaust stable 6. Developments Improved UK PM modelling by incorporating biomass and cooking emissions in King s UK CMAQ urban model

29 Thanks for your attention Thanks to all colleagues at King s: Gregor Stewart, Sean Beevers, James Smith, Nutthida Kitwiroon, Gary Fuller and David Green Acknowledgement to The Greater London Authority and Transport for London, who fund, develop and maintain the London Atmospheric Emissions Inventory. For more information please visit data.london.gov.uk MRC-HPA Centre for Environment and Health Imperial College London