MAX-DOAS observations and their application to validations of satellite and model data in Wuxi, China 1) Satellite group, Max Planck institute for Chemistry,

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MAX-DOAS observations and their application to validations of satellite and model data in Wuxi, China 1) Satellite group, Max Planck institute for Chemistry, Mainz, Germany 2) Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, China 3) Belgian Institute for Space Aeronomy – BIRA-IASB, Brussels, Belgium 4) Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Greece Yang Wang, Thomas Wagner, Pinhua Xie, Ang Li, Steffen Beirle, Nicolas Theys, Isabelle De Smedt, MariLiza Koukouli, Trissevgeni Stavrakou

th OMI Science Team Meeting, 2015, Yang Wang Overview:  Where is Wuxi city?  Motivation, satellite data and MAX-DOAS measurements in Wuxi  MAX-DOAS results, profiles of aerosols and trace gases  Effects of Aerosol and shape factor of trace gases on box AMF and AMF of satellite retrieval  Comparison of daily averaged OMI VCD with MAX-DOAS VCD  Annual variation of aerosol and trace gases from MAX-DOAS, OMI and CTM  Conclusion

- 3 - Where is Wuxi? Wuxi city (circle) is about 130 km north-west of Shanghai (triangle) and by the Yangtze river. The population in this city is about six millions. It is located at the boundary of the area with high pollution adjoined to Shanghai. NO2 DOMINO SO2 BIRA HCHO BIRA mean OMI

Motivation  NO2, SO2, HCHO are important for environment and climate science  Satellite is valuable way to obverse the global distribution.  Some challenges for the retrieval of the Trop. VCD for satellite: 1)SO2, HCHO SCD retrievals are influence by ozone and low absorption signal. 2)Tropospheric AMF calculations : Shape factor of trace gases from chemistry transfer model Not including aerosols cloud products sensitive to aerosols MAX-DOAS => aerosol and trace gases profiles and Trop. VCD => validate satellite products

Satellite data  Ozone monitor instrument: Resolution: 13 x 24 km, daily global coverage, overpass time 13:30  Data sets ( ): 1) NO2, DOMINO 2.0 product, trace gas shape factor from TM4 model (KNMI) 2) SO2, BIRA-IASB (N. Theys et al. JGRD., 2015), trace gas shape factor from IMAGESv2, horizontal resolution of 2° × 2.5° (Stavrakou, Atmos. Chem. Phys. 2013) NASA, Nickolay Krotkov, 3) HCHO, BIRA-IASB (I. De Smedt et al. ACPD., 2015), trace gas shape factor from IMAGESv2

Our measurements in Wuxi station Spectral range: 290 – 425 nm (NO2, SO2, HCHO and O4). Elevation angle: 5°, 10°, 20°, 30° and 90° Azimuth angle: Exact north MINI MAX-DOAS from 2011 to 2014: O4 and NO2, 350 nm – 391 nm; SO2, – 330; HCHO, nm – 359 nm Filters: shift < 1 pixel, offset correction < 1%, RMS < 0.01, SZA < 75 SCD retrieval: VCD and profile: Nonlinear optimal estimation method to retrieve profiles of aerosol extinction and trace gas VMR, then integrate profiles to acquire VCD. Filters: difference between measured and retrieved dSCD < a threshold; keep trace gas profiles with convincing aerosol profiles the sky conditions (cloud free, aerosol and clouds) identified by MAX-DOAS (Atmos. Meas. Tech. Discuss. 8, 4653–4709, 2015) help avoid the influence of clouds on aerosol and trace gases results of MAX-DOAS.

- 7 - Normalized profiles of aerosol extinction and trace gas VMR from MAX-DOAS  The profile shapes: Aerosol: Gaussian NO2: exponential SO2: exponential but higher layer HCHO: Largest value near surface, a box shape above 0.5km to 1km then fast decrease  Different seasons: Shapes similar In cloud free sky shape factor

- 8 - Discrepancy of shape factors from MAX-DOAS and CTM, and its effect on AMF Difference: HCHO>SO2>NO2 clear sky: SZA: 40 SAA:-140 VZA:30 VAA:40 Surface albedo: 0.05 including MAX-DOAS shape factor => decrease AMF (HCHO >SO2 > NO2) Totally mean 13:00 to 14:00

- 9 - Geometry: SZA: 40 SAA:-140 VZA:30 VAA:40 Effects of Aerosol on box AMF of satellite retrieval - compared with clear sky NO2 at 435nm HCHO at 337nmSO2 at 319nm  depended on wavelength, stronger at short wavelength (SO2)  Shading effect occurs below 1km, its magnitude up to 50%  Enhancing effect above 1km, up to 10% AOD: 0.83 SSA: 0.9 g: 0.72 mean aerosol profile from MAX-DOAS box AMF altitude / km

fake low clouds => CTP=1040 hPa (surface) fake high clouds => CTP=900 hPa (1km) Effects of Aerosol on box AMF of satellite retrieval - effect of fake clouds due to aerosols on box AMF Lambertian clouds CF=10% -> CRF=25% NO2 at 435nmHCHO at 337nm SO2 at 319nm 1.Treating aerosol as clouds, especially low clouds can overestimate the boxAMF strongly, up to 300% near the ground. 2.This overestimation is stronger at short wavelength (SO2) CF up to 15%, CTP >900 hPa for high anthropogenic aerosol load (AOD>0.4) Cloud and aerosol classification for 2 ½ years of MAX-DOAS observations in Wuxi (China) and comparison to independent data sets. Atmos. Meas. Tech. Discuss. 8, 4653–4709, 2015 CF up to 15%, CTP >900 hPa for high anthropogenic aerosol load (AOD>0.4) Cloud and aerosol classification for 2 ½ years of MAX-DOAS observations in Wuxi (China) and comparison to independent data sets. Atmos. Meas. Tech. Discuss. 8, 4653–4709, 2015 box AMF

Effects of Aerosol on AMF of satellite retrieval  AMF in clear sky is larger by 6%- 10% (SO2 > NO2 > HCHO)  Treating aerosol as low clouds increase AMF by up to 100%. As high clouds increase AMF by up to 30% (HCHO and SO2), but good for NO2 Mean shape factors from MAX-DOAS 4 types of boxAMFs 4 AMFs for NO2, SO2,HCHO Effect depended on CTP (large uncertainty in cloud products for aerosols) Suggest: calculate AMF in clear sky when CTP>900 hPa Poster: Evaluation of the effect of strong aerosol loads on satellite retrievals of tropospheric NO 2, SO 2 and HCHO using MAX-DOAS observations in Wuxi, China. => six cases with AOD from 0.6 to 1.7 in cloud free sky, combine MAX-DOAS, Aeronet, MODIS and OMI observations Poster: Evaluation of the effect of strong aerosol loads on satellite retrievals of tropospheric NO 2, SO 2 and HCHO using MAX-DOAS observations in Wuxi, China. => six cases with AOD from 0.6 to 1.7 in cloud free sky, combine MAX-DOAS, Aeronet, MODIS and OMI observations

Comparison of OMI VCD with MAX-DOAS VCD - NO  The high cloud shading effect underestimate NO2 VCD strongly, slopes improved by 15% by excluding high clouds  Aerosol effect underestimate NO2 VCD strongly, slopes improved by 17% by excluding high clouds, treating aerosol as clouds.  For clear sky, OMI VCD lower than MAX-DOAS VCD by 5% Cloud fractionCloud top height MAX-DOAS: minutes around overpass time OMI: distance from pixel center to station < 50 km Coincident criteria: High cloud shading effect: Using CTP, Improvement of linear regression by excluding the data with CTP<900 Aerosol effect: Using AOD, Improvement of linear regression by excluding the data for AOD>0.5 High cloud shading effect: Using CTP, Improvement of linear regression by excluding the data with CTP<900 Aerosol effect: Using AOD, Improvement of linear regression by excluding the data for AOD>0.5

Comparison of daily averaged OMI VCD with MAX-DOAS VCD - SO  High clouds shading effect: excluding high clouds, slope is improved by 10%.  Aerosol effect: excluding large aerosols, slope is improved by 11%.  In clear sky underestimation by 40%? Speculation: shape factor, residual aerosol and cloud effect, gradient smoothing effect and SCD retrieval. BIRA

Comparison of daily averaged OMI VCD with MAX-DOAS VCD -HCHO mean OMI VCD =11.2 mean OMI VCD random error=9.3 mean MAX-DOAS VCD=13.8  The random error from the DOAS fitting of SCD causes the large scattering points.  Excluding most cloud and aerosol effects improve the slope by 13%  In clear sky OMI underestimate HCHO by 8%. Cloud properties Random error

Annual variation of aerosol and trace gases - Bimonthly mean AOD from MAX-DOAS and AERONET MAX-DOAS AERONET 90% 75% mean Median 25% 10%  Well agreement  There is not regular variation AERONET level :00 to 14:00

Annual variation of aerosol and trace gases - Bimonthly mean VCD of trace gases Comparison: Variation trend agree well MAXDOAS>OMI> CTM Maximum: NO2 in winter; SO2 in winter HCHO in summer; NO2: SO2: HCHO: Trop. VCD [10^15 molecs/cm^2] 13:00 to 14:00

Conclusion: 1.Differences of the profile shapes from MAX-DOAS and CTM are larger for HCHO>SO2>NO2 => effect on AMF (HCHO > SO2 > NO2) in clear sky 2.Treating aerosol as clouds, especially low clouds cause the boxAMF overestimated by up to 300% and AMF by up to 100%. The effect is strongly depended on CTP. 3.We suggest to calculate AMF in clear sky when CTP>900 hPa to avoid the large error from treating aerosol as low clouds. 4.Cloud shading effect and aerosol effect (treating aerosol as clouds) make OMI underestimate NO2, SO2 and HCHO strongly. We can use CTP>900 hPa and AOD<0.5 to exclude high clouds and strong aerosol to improve validation.

Great thanks for your attention! EGU General Assembly 2014, Yang Wang

Comparison of daily averaged OMI VCD with MAX-DOAS VCD -HCHO mean OMI VCD =11.2 mean OMI VCD random error=9.3 mean MAX-DOAS VCD=13.8 The random error from the DOAS fitting of SCD causes the large scattering points. Aerosol effect underestimate VCD by 13%. In clear sky underestimation by 8%. Cloud properties Random error

Comparison with collocated independent techniques - Point to point, time difference <15 min, in cloud free sky Well agreement with sunphotometer (20km away), visibilitymeter and LP-DOAS (nearby). R ≈0.7 AOD Near surface aerosol extinction Near surface NO2 VMR Near surface SO2 VMR 2. Aerosol: Best agreement in summer => stronger wind cause homogeneous vertical and horizontal distribution in 0 to 200meters. worst in spring => dusk storm 3. Trace gases: MAX-DOAS larger in summer and spring due to lifted high concentration in 0 to 200 meters (Meng, et al, 2008, Tower measurements in Beijing )