Monitoring air quality in an urban area using remote sensing techniques and in situ measurements.

1. Monitoring air quality in an urban area using remote sensing techniques and in situ measurements. Space Research Centre L. Kramer, R. Leigh, J. Remedios & P. Monks. Leicester City Council

2. Satellites In situ Ground based remote sensing

3. In Situ Monitors Run by Leicester City Council - Hourly averaged NO2 concentrations (ppb)  molybdenum converters.

4. CMAX-DOAS Coated Glass Plano -convex lens Fibre-optic to Spectrometer 15o 10o 90o 5o 2o

5. DOAS fitting window of 428-510nm includes NO2, O3, H2O and the oxygen dimer O4. • Tropospheric DSCDs are produced from the subtraction of the concurrent zenith differential slant column for each measurement in the off axis views, removing the stratospheric signal. • A box model is used to derive air mass factors (AMF) for NO2 for each of the viewing angles. Data from the 5 deg view is used in all analyses here.

6. CMAX-DOAS – in situ comparisons • Daily averaged NO2 concentrations for December 2005 to March 2006 during DOAS measurement period. • Group 1, defined as “urban background”, show no positive bias in the in situ measurements

7. OMI • The Ozone Monitoring Instrument (OMI) was launched onboard the NASA EOS Aura satellite in July 2004. • OMI is a Nadir viewing spectrometer that measures in the spectral range between 270 and 500 nm. • Has a spectral resolution of 0.52 and 0.45 nm in the UV-1 and UV-2 channels and 0.63 nm in the visible channel. • OMI has a large swath width of 2600 km, to obtain this viewing swath the viewing angle is 114° • In the normal operation mode, the OMI pixel size is 13 x 24 km2 making it suitable for comparisons with measurements on an urban scale.

8. OMI-DOAS comparison • Black circles - all “inner swath” pixels • Red crosses - cloud cleared (Cldfr<0.2). • Blue triangles - those measurements where OMI covers at least 90% of the area surrounding Leicester. • This ensures that the sampling area of CMAX-DOAS is also sampled by the OMI pixel. The correlation is then greatly improved (R=0.64).

9. OMI- in situ comparison The mean NO2 concentration and variability were calculated for the “urban background” monitoring stations and compared to OMI tropospheric NO2 columns for 2005 and 2006. Cloud cleared and inner swath pixels only.

10. Near-surface measurements, particularly in urban areas are subject to variation due to spatial and temporal inhomogeneity of boundary layer NO2. • The two different observation techniques also yield different samplings of the atmosphere on a spatial scale, which can introduce biases. • A positive bias is observed in the near-surface concentrations due to the fact that OMI is measuring a larger area than what the in situ monitor’s measure.

11. To correct for the bias, background near-surface NO2 measurements were included in the analyses. The background near-surface NO2 data was obtained from an in situ chemiluminescence monitor in Market Harborough (52.55 N, 0.77 W). 1-α α

12. Spring – red Summer – blue Autumn black Winter - green

13. Seasonal and Weekly cycles Monthly averages of NO2 for cloud free days for OMI (blue) and mean FOV-weightedNO2 from “urban background” monitors (black) in 2005 and 2006. The near-surface measurements demonstrate the expected seasonal cycle of NO2 - low concentrations in summer with an increase in the winter months.

14. Seasonal and Weekly cycles Urban background stations Rural background stations • For each day of the week the mean is calculated and normalised to the median weekly value (Beirle et al. 2003). • Weekly cycles are similar for measurements from all instruments, with a noticeable decrease in NO2 at the weekend compared to the weekday levels • A peak in NO2 levels on Monday is observed which may be due to an increase in traffic from commuters FOV-weighted OMI

15. CMAX- and in situ weekly cycles for Dec 2005 to Mar 2006. Much clearer cycle, with almost constant weekly levels and a large reduction in NO2 on a Sunday. This may show that the large OMI pixel is dominated by background sources of NO2, which do not display such a strong an anthropogenic cycle.

16. Summary • Different observation techniques yield different samplings of the atmosphere on a spatial and temporal scale → can introduce biases. • The bias can be corrected for my introducing the background in situ NO2 in the correlation. • The agreement now is very good for the spring and summer months with correlation coefficients of 0.83 and 0.64 respectively. The correlation for autumn is also good (R=0.60), however, during the winter OMI generally observes much higher concentrations of NO2 than what is represented by the near surface NO2 over the pixel This is also observed in the seasonal cycles. • Weekly cycles reflects the ability of all three instruments to measure the anthropogenic cycles of air quality around Leicester.

17. Further work OMI - in situ comparisons for other cities around the UK Manchester Birmingham

18. LAMP Leicester Air Quality Measurement Project • Monitoring techniques for NOx • NOxy – York • BBCEAS – Leic • Mobile Monitor (Chemiluminescence) – Council • Chemiluminescence Monitors – Council • CMAX-DOAS – Leic • OMI

20. Airviro • Airviro: An Integrated System for Air Quality Management → Developed by Swedish Meteorological and Hydrological Institute (SMHI) • A geographical Emissions Database into which data can be entered from point sources • 4 Different Models • A street canyon model for investigating air pollution at a fine scale • Gaussian plume and Eulerian grid models for investigating regional and local scale air pollution • A Heavy Gas model for investigating accidental releases