Spatial distribution of BC sources from mobile measurements
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Presentation to the 2009 Australia-New Zealand Aerosol Workshop.
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Spatial distribution of BC sources from mobile measurements
- 1. Spatial distribution of BC sources from mobile measurements Gustavo Olivares (a.k.a. Guy Coulson) National Institute of Water and Atmosphere Research
- 2. Outline • Why? • Campaign description • Method • Results • Conclusion
- 3. Why? • Identify Traffic vs. Residential Wood Combustion (RWC) emission areas – Enable emission density estimates – Highlight target areas for campaigns, measures, etc
- 4. Campaign description • Woodburning Emission Dispersion in Glen Eden (WEDGE) … deja vu anyone? • MAQS2 based campaign – BC – CO2 – GPS
- 5. (simple) Method • Ratio for RWC emission factors is about 3 times larger than the same ratio for traffic • Ratio between BC and CO2
- 8. Results BC / CO2 12% 10% 8% ~ 3 times higher ratio for RWC Frequency 6% 4% 2% 0% 0 5 BC / CO2 10 15 20 25 30 35 40 45 50 55 60 65 70 75
- 10. Source mapping
- 11. Source mapping
- 12. Conclusions • BC / CO2 ratio is useful to discriminate between traffic and residential combustion sources • Mobile measurements of these pollutants can effectively map the emission areas • Could this be used for point measurements screening?
Editor's Notes
- The message is “this is only the beginning” in that this method will enable detailed emission density estimates (per source) and that it is a simple-ish way of getting validation of emission inventories (we’re only using a small part of the MAQS2)
- No need to go into details here … a campaign in west auckland focusing on drainage flow … but for this study, we expanded the aims to “source mapping”
- Very simple … EFtraffic(BC)/EFtraffic(CO2) is about 1/3 of the same ratio for wood combustion. Assuming both BC and CO2 as inert in the scale of minutes, one can say that the same 1:3 ratio must be observable in the ratio of ambient concentrations of BC and CO2
- Average of last years runs (“most” nights are included) The scale is PPM and the point is that there is a spatial pattern here
- Note that the scale is in NANOgrams/m3 negative values are product of high resolution sampling (5sec averaged to 10sec) and it is a trade-off between removing most of the negative numbers (that happen when concentration varies a lot … for example when going through a plume) and having enough detail to resolve ~100m There is a pattern that it is not the same as CO2
- This is the FREQUENCY plot of the ratios … the cool thing here is that the data does show a bimodal structure which points to 2 sources with a ratio for one of around 10 and the second one around 25 … pretty close to 1:3! So … the data does differentiate these 2 sources
- What does this ratio looks like on a map? The scale is BC/CO2 (nanograms/m3 per ppm) Key thing is the redish blob in the south-east But this plot can be misleading as we’re only aiming at IDENTIFICATION of the sources, not QUANTIFICATION so … next one
- A mask was put on the plot to highlight where the data shows predominance of RWC and traffic … and oh surprise … traffic is important in the roads and RWC in the residential areas ;-) Next for more detail
- This shows a detail of the dense residential area in Glen Eden Success! This method with this data has identified areas where traffic is more significant than RWC for a “typical winter’s night” in west Auckland
- The key thing is to prompt the last question … (the answer is yes and you can even get an estimate of total emissions from a ratio analysis on point measurements) My point is that CO2 is generally ignored in AQ measurement campaigns but we can get pretty good information if we include those kind of tracers into the study design.