MAX-DOAS measurements of tropospheric NO2 and HCHO in Nanjing and the comparison to OMI observations

Nanjing and the comparison to OMI observations Ka Lok Chan1, Zhuoru Wang1, Aijun Ding2, Klaus-Peter Heue1, Yicheng Shen2, Jing Wang3, Feng Zhang4, Yining Shi4, Nan Hao5, and Mark Wenig6 1Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Oberpfaffenhofen, Germany 2School of Atmospheric Sciences, Nanjing University, Nanjing, China 3Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China 4Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China 5European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Darmstadt, Germany 6Meteorological Institute, Ludwig-Maximilians-Universität München, München, Germany Correspondence: Ka Lok Chan (ka.chan@dlr.de)


Introduction
Nitrogen dioxide (NO 2 ) and formaldehyde (HCHO) are major atmospheric pollutants playing crucial roles in atmospheric chemistry.NO 2 is a catalyst for ozone (O 3 ) formation in the troposphere, while also participating in the catalytic destruction of stratospheric O 3 (Crutzen, 1970).Major NO 2 sources include fossil fuel combustion, biomass burning, lightning and oxidation of ammonia (Bond et al., 2001;Zhang et al., 2003).The emissions of NO 2 show a significant increasing trend in China due to the rapid industrialization and economy development in the last two decades (Zhang et al., 2007;van der A et al., 2008;Zhao et al., 2013), making it one of the most severe air pollution problems.HCHO is an intermediate product of the oxidation of almost all volatile organic compounds (VOCs).Therefore, it is widely used as an indicator of non methane volatile organic compounds (NMVOCs) (Fried et al., 2011).VOCs also have significant impacts on the abundance of hydroxyl (OH) radicals in the atmosphere, which is the major oxidant in the tropospheric.Major HCHO sources over the continents include the oxidation of VOCs emitted from plants, biomass burning, traffic and industrial emissions.Oxidation of methane (CH 4 ) emitted from the ocean is the main source of HCHO over water.Both NO 2 and HCHO contribute to the formation of secondary aerosols (Jang and Kamens, 2001) and they are toxic to human in high concentration.The spatial distribution of NO 2 and HCHO is strongly related to their emissions due to their short atmospheric lifetime.Consequently, it is important to understand the spatial and temporal variations of atmospheric NO 2 and HCHO for better air pollution management and control.
Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) is a powerful remote sensing measurement technique which provides valuable vertical distribution information of atmospheric aerosols and trace gases (Platt and Stutz, 2008).
Information of tropospheric aerosols and traces gases are obtained from the molecular absorption in the ultraviolet and visible spectral bands by applying the differential optical absorption spectroscopy (DOAS) technique to the observations of scattered sun light spectrum in several different viewing directions.As the experimental setup of MAX-DOAS is rather simple and inexpensive, it has been widely used for the observation of atmospheric aerosols and trace gases in the past decade (Hönninger and Platt, 2002;Hönninger et al., 2004;Wittrock et al., 2004;Frieß et al., 2006;Irie et al., 2008;Li et al., 2010;Clémer et al., 2010;Halla et al., 2011;Li et al., 2013;Ma et al., 2013;Chan et al., 2015;Jin et al., 2016;Wang et al., 2016;Chan et al., 2018).MAX-DOAS measurements are highly sensitive to aerosols and trace gases in the lower troposphere and provide valuable information of the vertical distribution of aerosol extinction and trace gases.The information of the aerosol and trace gas vertical profiles are particularly important for the study of the physical and chemical processes in the atmosphere.
Satellite based remote sensing measurements provide indispensable spatial information of air pollutants (Burrows et al., 1999;Bovensmann et al., 1999;Callies et al., 2000;Levelt et al., 2006).Trace gas columns are derived from the satellite observations of Earth's reflected solar spectrum for the investigation of atmospheric dynamics and emissions from both anthropogenic and natural sources (Beirle et al., 2003;Wenig et al., 2003;Beirle et al., 2004;Richter et al., 2005;Zhang et al., 2007;van der A et al., 2008).Satellite measurements can also be used to determine the effectiveness of emission control measures (Mijling et al., 2009;Witte et al., 2009;Wu et al., 2013;Chan et al., 2015).However, the uncertainties of satellite trace gas column retrieval are strongly dependent on the accuracy of the assumptions of trace gas vertical distributions.In addition, the temporal resolution of satellite measurements is often limited to single observation per day.Therefore, it is useful to compare and integrate ground based and satellite observations for the interpretation of the spatial and temporal variation of NO 2 and HCHO.
Nanjing is the second largest city in the Yangtze River Delta and Eastern China.It is also the provincial capital of Jiangsu province.The population of Nanjing is about 8 million.Yangtze River is running through the city of Nanjing making it the largest inland port in China.Industrial, water and road transportation are the major anthropogenic sources of air pollutions in Nanjing.Due to its rapid development as well as its surrounding cities in the Yangtze River Delta, Nanjing is facing a series of air pollution problems in recent years.In addition, Nanjing has also hosted several important international events including the summer Youth Olympic Games in 2014.Therefore, it is important to have a better understanding of the air pollution sources in order to support the design of air quality related environmental policies in the future.
In this paper, we present long term MAX-DOAS observations of NO 2 and HCHO in Nanjing.Ground based MAX-DOAS measurements were performed from April 2013 to February 2017.Details of the MAX-DOAS experimental setup, the spectral analysis as well as the retrieval of the aerosol extinction, NO 2 and HCHO profiles are presented in section 2. Section 3.1 shows the validation of MAX-DOAS aerosol observations by comparing the reported aerosol optical depths (AODs) to sun photometer measurements.The comparison of NO 2 and HCHO VCDs measured by the MAX-DOAS and OMI satellite is presented in Section 3.2.An analysis of regional transport of pollutants over Yangtze River Delta is shown in section 3.4.In section 3.5, we presented an evaluation of the pollution reduction observed during the Youth Olympic Games in 2014.

Experimental setup
A MAX-DOAS instrument was set up at a meteorological station of Nanjing University (32.12 • N, 118.95 • E) which is located on a small hill in the University campus at about 45 m above sea level.The meteorological station is located about 17 km northeast of the Nanjing city center and about 5 km south of the Yangtze River.The MAX-DOAS instrument for scattered sunlight measurements consists of a scanning telescope, a stepping motor controlling the viewing zenith angle of the telescope and a spectrometer.Scattered sun-light collected by the telescope is redirected by a quartz fiber to the spectrometer for spectral analysis.The field of view of the telescope is about 0.6 • .An Ocean Optic USB2000 spectrometer equipped with a Sony ILX511 charge-coupled device (CCD) detector is used to cover the wavelength range from 288 nn to 434 nm.The full width half maximum (FWHM) spectral resolution of the spectrometer is 0.6 nm (at 360 nm).
A complete measurement cycle consists of scattered sun-light observations at elevation angle (α) of 1      , 30 • and the zenith (90 • ).The viewing azimuth angle is adjusted to 320 • (northwest).The exposure time and the number of scan of each measurement is adjusted automatically depending on the received intensity of the scattered sun-light spectrum in order to achieve a similar intensity level for all the measurements.A full measurement sequence takes about 5 -10 minutes.All the measurement spectra were first corrected for offset and dark current and then analyzed using the spectral analyzing software QDOAS version 3.2 (http://uv-vis.aeronomie.be/software/QDOAS/).The MAX-DOAS spectral fit was performed at 2 different wavelength ranges of 338 -370 nm for NO 2 retrieval and 324.5 -359 nm for HCHO retrieval.In this study, the zenith spectrum (α = 90 • ) taken in the same measurement cycle is used as reference spectrum in the spectral analysis to retrieve the differential slant column densities (DSCDs).The differential slant column density (DSCD) is defined as the difference between the slant column density (SCD) of the measured spectrum and the corresponding zenith reference spectrum.The broad band spectral structures caused by Rayleigh and Mie scattering are removed by including a low order polynomial in the DOAS fit.Absorption cross section of several trace gases were included in the DOAS fit at different fitting ranges, details of the DOAS retrieval settings for each wavelength range are listed in Table 1.The DOAS fit settings follow the one used in the Quality Assurance for Essential Climate Variables (QA4ECV) project (http://www.qa4ecv.eu/).These settings have also been adopted for the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) campaign (http://www.tropomi.eu/data-products/cindi-2).Small shift and squeeze of the wavelengths are allowed in the wavelength mapping process in order to compensate small uncertainties caused by the instability of the spectrograph.Figure 1 shows an example of the spectral fit retrieval of NO 2 and HCHO DSCDs from a MAX-DOAS spectrum taken on 12 th May 2013 at 08:48 (local time) with viewing elevation angle of 1  (a) I0 correction is applied with SCD of 10 17 molec/cm 2 (Aliwell et al., 2002).
As clouds are not included in the radiative transfer calculation of the aerosol and trace gas profile retrieval, the retrieval result can be significantly influenced by the present of cloud in the atmosphere.Therefore, the retrieved DSCDs were first filtered by removing cloudy scenes before proceeding to the aerosol and trace gas profile retrieval.The vertical profile of the oxygen collision complex O 4 only varies in a small range with atmospheric pressure and temperature, the retrieved O 4 DSCDs and Therefore, we applied a locally weighted regression smoothing filter (LOWESS) (Cleveland, 1981) et al., 2009;Clémer et al., 2010;Wagner et al., 2011;Chan et al., 2015;Wang et al., 2016;Chan et al., 2018;Zhang et al., 2018).
A scaling correction factor has to be applied to the measured O 4 DSCDs in order to bring measurement and model results into agreement.However, the physical meaning of this observation is still not well understood (Ortega et al., 2016;Wagner et al., 2019).Theoretically, the optical path should be the longest under aerosol free condition for off zenith measurement.The conversion of the MAX-DOAS observations to aerosol extinction and trace gas profile requires inversion of the underlying radiative transfer equations.These equations cannot be linearized, therefore, it is suggested to fit the measurement quantities to the forward calculation of radiation transfer (Wagner et al., 2004;Hönninger et al., 2004;Sinreich et al., 2005;Frieß et al., 2006;Hartl and Wenig, 2013;Chan et al., 2018).As the vertical distribution profile of O 4 is very stable and it has several absorption bands in the ultraviolet and visible spectral range, it is commonly used as fitting quantity for the aerosols retrieval.
In this study, aerosol vertical profiles are retrieved at the 360 nm O 4 absorption band using the Munich Multiple wavelength MAX-DOAS retrieval algorithm (M 3 ) (Chan et al., 2018).The algorithm is developed based on the optimal estimation method (Rodgers, 2000) and utilizes the Library for Radiative Transfer (LibRadTran) model (Emde et al., 2016) as the forward model.
In this study, the U.S. standard mid-latitude atmosphere profiles for winter (January) and summer (July) are temporally interpolated to each month of the year for the radiative transfer simulations.A brief description of the aerosol and trace gases vertical profile retrieval algorithm and the parameterization used in this study are presented in the following.A more detailed description of the 3M retrieval algorithm can be found in Chan et al. (2018).
In this study, all valid MAX-DOAS observations within a single measurement cycle are grouped together for the aerosol vertical profile retrieval.Assuming the set of measurement can be reproduced by the forward model and the forward model results are dependent on the aerosol extinction profile, we can then retrieve the aerosol extinction profile by fitting the forward model results to the MAX-DOAS O 4 observations using the iterative Newton-Gauss method.As the information contained in the MAX-DOAS observations are most likely not enough to retrieve an unique aerosol extinction profile, we have to supply the necessary information to the aerosol inversion in a form of a priori aerosol profile.As the aerosol load in Nanjing varies in a wide range, using a fix a priori could result in over regularizing the retrieval under higher aerosol load conditions.Therefore, we have implemented an iterative approach to avoid over regularizing the retrieval.We first use a fixed initial a priori to retrieve the aerosol extinction profile.The fixed a priori profile is then scaled to have the same aerosol optical depth retrieved from the previous run.Then the new a priori is used in the next run to retrieve the aerosol extinction profile.This procedure is repeated until the difference between the retrieved and a priori aerosol optical depth is less than 10 % or the number of iteration reaches the limit.
As aerosols are typically emitted and formed close to the surface in urban areas, we assume the a priori aerosol extinction profile follows an exponentially decreasing function with a scale height of 1.0 km.The aerosol optical depth (AOD) of the a priori aerosol profile is set to 0.5 for the retrieval at 360 nm.The uncertainties of the a priori aerosol profile are set to 100 % and the correlation length of the aerosol inversion is assumed to be 0.5 km.As MAX-DOAS measurements are more sensitive to the aerosol and trace gases close to the instrument, therefore, we divided the lowest 3.0 km of the troposphere into 15 layers with thickness of each layer of 200 m.A fix set of single scattering albedo of 0.92, asymmetry parameter of 0.68 and ground albedo of 0.04 is assumed in the radiative transfer calculations.An example of aerosol extinction profile retrieval is indicated in Figure 2a-c.
The aerosol information obtained from the procedure described above were used for the differential box air mass factor (∆DAMF) calculation for the trace gas profile inversion.The ∆DAMFs were calculated at a single wavelength for the retrieval of trace gas profile using the radiative transfer model LibRadTran with the Monte Carlo simulation module MYSTIC (Emde et al., 2016).The ∆DAMF was assumed to be constant within the DOAS spectral fitting windows.In this study, vertical distribution profiles of NO 2 are retrieved at 360 nm.An example of NO 2 profile retrieval is indicated in Figure 2d-f.For HCHO vertical distribution profile retrieval, aerosol extinction profiles obtained at the 360 nm O 4 band are converted to 340 nm assuming a fixed Ångström coefficient (Ångström, 1929) of 1.The Ångström coefficient can varies significantly with time.
Sun photometer measurements in Nanjing (see Section 2.2) show that the Ångström coefficient mostly varies between 0.7 (10 th percentile) and 1.4 (90 th percentile).Based on the sun photometer observations, we estimated the error caused by fixed Ångström coefficient on aerosol extinction is less than 2 %.The ∆DAMFs are subsequently calculated at 340 nm for the HCHO profile retrieval.An example of HCHO profile retrieval is indicated in Figure 2g-i.
The atmosphere layer settings of the trace gas profile retrieval are the same as the one used in the aerosol profile retrieval.
NO 2 and HCHO concentrations above the retrieval height (3 km) are assumed to follow the U.S. standard atmosphere.As the trace gas profile cannot be fully reconstructed by the small number of measurements, therefore, we use the optimal estimation method (Rodgers, 2000) with iterative approach to regularize the inversion (Chan et al., 2015(Chan et al., , 2018)).The first step uses a fixed initial a priori to retrieve the trace gas distribution.The fixed a priori profile is then scaled to have the vertical column retrieved from the first run.The scaled a priori is used in the next run to retrieve the trace gas profile.The process repeats until the difference between the retrieved and a priori trace gas vertical column is less than 10 % or the number of iteration reaches the limit.In this study, the a priori is assumed to follow an exponential decrease function with a scale height of 1.0 km.The uncertainty of the a priori profile is set to 100 % of the a priori and correlation length is set to 0.5 km in the trace gas profile inversion.The NO 2 vertical column density (VCD) of the a priori is set to 2 × 10 16 molec/cm 2 while the a priori HCHO VCD is set to 1 × 10 16 molec/cm 2 .

Sun photometer measurements
A sun photometer was installed on the roof of a building of Nanjing University of Information Science and Technology In this study, AODs measured by the sun photometer were used for the inter-comparison study to validate the MAX-DOAS aerosol retrieval.Cloud screened data were used.The data consist of AOD measurements at 7 different wavelength channels from 340 nm to 1020 nm.AOD measurements at 340 nm and 380 nm are interpolated to 360 nm for comparison.

Meteorological data
Meteorological parameters such as temperature, wind speed and wind direction are taken from a weather station in Nanjing which is located about 20 km south of the MAX-DOAS measurement site.The weather station is operated by the National Meteorological Center of China Meteorological Administration.These data are available on the webpage of China Meteorological Administration (https://data.cma.cn/site/index.html).The meteorological data are mainly used for the analysis of meteorological effects on air quality in Nanjing during the Youth Olympic Games in 2014.

OMI satellite observations
The Ozone Monitoring Instrument (OMI) is a passive nadir-viewing satellite borne imaging spectrometer (Levelt et al., 2006) on board the Earth Observing System's (EOS) Aura satellite.The EOS Aura satellite orbit at an altitude of ∼710 km with a local equator overpass time of 13:45 LT (local time).The instrument consists of two charge-coupled devices (CCDs) covering a wavelength range from 264 nm to 504 nm.A scan provides measurements at 60 positions across the orbital track covering a swath of approximately 2600 km.The spatial resolution of OMI varies from ∼320 km 2 (at nadir) to ∼6400 km 2 (at both edges of the swath).The instrument scans along 14.5 sun-synchronous polar orbits per day providing daily global coverage.
The NASA's OMI NO 2 and HCHO standard product version 3 (Krotkov et al., 2017;González Abad et al., 2015) are used in this study.In the NO 2 product, the slant column densities (SCDs) of NO 2 are derived from Earth's reflected spectra in the visible range (402 -465 nm) using an iterative sequential algorithm (Marchenko et al., 2015).Previous studies show the updated SCDs are on average 10 -40 % lower compared to the previous version of retrieval (Marchenko et al., 2015).The OMI NO 2 SCDs are converted to VCDs by using the concept of air mass factor (AMF) (Solomon et al., 1987).The AMFs are calculated using NO 2 profile simulated by the Global Modeling Initiative (GMI) chemistry transport model.The horizontal resolution of GMI is 1 • (latitude) × 1.25 • (longitude) (Rotman et al., 2001).Separation of stratospheric and tropospheric columns is achieved by the local analysis of the stratospheric field over unpolluted areas (Bucsela et al., 2013).
The OMI HCHO retrieval algorithm uses the direct fit of radiances in the spectral range from 328.5 nm to 356.5 nm for the SCD retrieval.In the current version of HCHO product, OMI radiance measurement over the remote Pacific is used as reference in the fitting process.This approach is reported to reduce the interferences from unresolved spectral structures in the retrieval of weak absorbers like HCHO (De Smedt et al., 2018).The retrieved SCDs are then converted to VCDs using the AMF approach.The AMFs are calculated based on climatological HCHO profiles.

Back trajectory modeling
The The sun photometer is sensitive to the entire column while the MAX-DOAS is mostly sensitive to aerosol at the lowest few kilometers of the troposphere.Therefore, the MAX-DOAS is likely to underestimate the AOD when there is an elevated aerosol layer in the upper troposphere.This explanation matches with the observations that the MAX-DOAS agrees better with the sun photometer under low aerosol conditions (AOD < 1) and underestimate the AOD during high AOD conditions.Another source of error is the assumption of aerosol optical properties in the MAX-DOAS retrieval.In order to quantify the error caused by the fixed asymmetry parameter and single scatter albedo used in the aerosol retrieval, we have performed a sensitivity analysis by retrieving the aerosol profile with different asymmetry parameter and single scattering albedo.As the sun photometer in Nanjing does not provide full inversion of aerosol optical properties, aerosol optical properties are taken from the Taihu AERONET station which is about 150 km southeast of Nanjing.The 10 th and 90 th percentile of asymmetry parameter and single scatter albedo are used for the sensitivity study.The result shows that the error caused by the fixed asymmetry parameter 5 on AOD retrieval can be up to 4 %, which the single scattering albedo shows a smaller impact of up to 1.5 %.In addition, the MAX-DOAS and sun photometer are separated by a distance of ∼25 km and the sun photometer site is very close to an industrial park, where the heavy polluted industries are located, i.e., steel and cement plants.Therefore, the sun photometer measurements are expect to be higher than the MAX-DOAS observations.Accounting for these effects, the MAX-DOAS and sun photometer observation agrees well with each other and the MAX-DOAS derived aerosol profiles are reliable for the 10 retrieval of NO 2 and HCHO profiles.

Comparison of MAX-DOAS and OMI observations
Vertical column densities of NO 2 and HCHO retrieved from the ground based MAX-DOAS measurements are compared to OMI satellite observations.MAX-DOAS data are temporally averaged around the OMI overpass time from 12:00 to 14:00  NO 2 VCDs measured by the MAX-DOAS and the OMI satellite shows a similar seasonal pattern with higher NO 2 columns during winter and lower NO 2 values over summer.Higher NO 2 levels are due longer atmospheric lifetime of NO 2 during winter and higher emissions in winter, e.g., higher power consumption and emissions from individual domestic heating.MAX-DOAS and OMI observations show good temporal consistency with each other with Pearson correlation coefficient (R) of 0.91.Despite the strong correlation between the two datasets, the OMI observations is systematically underestimating the NO 2 columns.The slope and offset of the total least squares regression between the two datasets is 0.50 and -1.89 × 10 15 molec/cm 2 , respectively.Averaged OMI NO 2 column over Nanjing is 5.67 × 10 15 molec/cm 2 which is about 60 % lower than the MAX-DOAS averaged VCD of 14.96 × 10 15 molec/cm 2 (see Figure 4).The underestimation of NO 2 VCDs from OMI measurements agree with previous studies in the Yangtze Delta (Chan et al., 2015).The discrepancies can be related to the differences in spatial coverage between the ground based and satellite observations and the uncertainties related to the NO 2 vertical distribution profile shape used in the air mass factor calculation.We quantified the influence of NO 2 vertical distribution profile on the air mass factor calculation by recomputed the OMI tropospheric NO 2 air mass factor using the MAX-DOAS NO 2 profile as a priori information.OMI NO 2 VCDs retrieved with MAX-DOAS NO 2 profiles are also indicated in Figure 4. Using the MAX-DOAS profile as a priori information in the OMI NO 2 VCDs retrieval on average increased the OMI NO 2 VCDs by ∼30 % with correlation nearly unchanged.The averaged OMI NO 2 column over Nanjing increased to 7.29 × 10 15 molec/cm 2 .In addition, the slope of the regression line increases from 0.50 to 0.57 while the offset reduces from -1.89 to -1.35 × 10 15 molec/cm 2 .The result indicates that a better estimation of NO 2 vertical distribution in the satellite VCD retrieval reduces the discrepancies.Our findings agree with previous studies that using better estimated NO 2 vertical profile in the satellite air mass factor calculation enhanced the OMI NO 2 columns and reduced discrepancies between OMI and ground based observations (Chan et al., 2012;Lin et al., 2014;Chan et al., 2015;Wang et al., 2017).However, the improved OMI NO 2 VCDs are still about 50 % lower than the MAX-DOAS observations indicating that there are still remaining issues.Previous study shows that the OMI NO 2 tropospheric vertical columns processed by the Royal Netherlands Meteorological Institute (KNMI) (DOMINO version 2.0) (Boersma et al., 2011) only underestimated the tropospheric NO 2 VCDs by ∼20 % compared to ground based MAX-DOAS observations in Wuxi (another city in Yangtze River Delta) (Wang et al., 2017).In order to investigate the differences between different OMI NO 2 products, we have also plotted the KNMI OMI NO 2 product in Figure 4.The average NO 2 column reported from the KMI product is 10.10 × 10 15 molec/cm 2 , which is about a factor of 2 higher than the NASA product.The result shows the KNMI product only underestimate the NO 2 columns in Nanjing by ∼30 % which is consistent with previous study in Yangtze River Delta (Wang et al., 2017).The difference between the two OMI products can be related to different spectral analysis techniques, stratospheric tropospheric separation algorithms as well as a priori profiles used in the retrievals.
Investigation of the differences between the two algorithms is however beyond the scope of this study.Another source of discrepancy is related to the difference in spatial coverage of OMI and MAX-DOAS observations.The spatial coverage of the OMI measurement footprint is ranging from 330 km 2 up to 4600 km 2 with an average of 920 km 2 .Measurements with such large spatial coverage are probably difficult to capture the spatial gradient of NO 2 and resulted in an underestimation over pollution hot spots due to the averaging of large OMI footprint.This effect is especially significant over Nanjing, as it is a local pollution hot spot surrounded by rather clean areas.The underestimation of NO 2 columns is coherent with previous measurements over urban pollution hot spots, i.e., Washington DC and Shanghai (Wenig et al., 2008;Chan et al., 2015).In addition, previous measurements over suburban area in Shanghai show better agreement with OMI observations compared to the measurements in the city (Chan et al., 2015) indicating the effect of spatial inhomogeneity of NO 2 on the satellite data comparison.However, the impact of this effect is difficult to quantify due to lack of high spatial resolution data.Cloud contamination could be an important source of error in the satellite retrieval.Previous study show that the cloud effect on OMI NO 2 VCD retrieval is only significant for cloud radiance fraction > 0.4 (Wang et al., 2017).The OMI NO 2 data used in this study are filtered for cloud radiance fraction smaller than 0.4.Therefore, cloud contamination should only show a negligible effect in the comparison.
We have also compared the MAX-DOAS and OMI observations of HCHO and both datasets show a similar seasonal variation pattern.The seasonal variation pattern of HCHO is opposite to NO 2 with higher HCHO columns during summer and lower in winter.Higher HCHO levels in summer are related to the increases of biogenic emission of precursor VOCs from plants and higher oxidation rate of VOCs.The MAX-DOAS measurements of HCHO VCDs agree well with the OMI observations with Pearson correlation coefficient (R) of 0.75.In addition, the absolute value of the columns show a perfect agreement.
The average HCHO VCD measured by the MAX-DOAS is 8.04 × 10 15 molec/cm 2 while the averaged OMI HCHO VCD is 7.89 × 10 15 molec/cm 2 .The slope of the total least squares regression between the two datasets is 0.99 with an offset of 0.31 × 10 15 molec/cm 2 (see Figure 4b).In order to quantified the influence of HCHO vertical distribution profile on the air mass factor calculation, we have recomputed the OMI HCHO VCDs using the MAX-DOAS HCHO profiles as a priori information.OMI HCHO VCDs retrieved with MAX-DOAS HCHO profiles are also indicated in Figure 4. Using the MAX-DOAS profile as a priori information in the OMI HCHO VCDs retrieval on average increased the OMI HCHO VCDs by ∼25 % with correlation nearly unchanged.The averaged OMI HCHO column over Nanjing increased to 9.95 × 10 15 molec/cm 2 .The slope of the regression line also increases from 0.99 to 1.39 while the offset reduces from 0.31 to -0.72 × 10 15 molec/cm 2 .Higher HCHO VCDs retrieved from OMI using MAX-DOAS profiles as a priori is mainly due to the MAX-DOAS measurements are not sensitive to HCHO at higher altitudes.Sources of HCHO in the troposphere include the oxidation of varies of VOCs, including methane.Some of these VOCs have relatively long atmospheric lifetime, e.g., methane, therefore, they are rather well mixed in the atmospheric and resulting in a larger portion of HCHO in the upper troposphere.The MAX-DOAS could not capture HCHO at higher altitudes.Therefore, using the MAX-DOAS profiles for OMI HCHO retrieval is likely underestimated the air mass factors and overestimated the HCHO total columns.

Seasonal variation of aerosol, NO 2 and HCHO vertical profiles
The seasonal variations of pollutant are closely related to meteorological conditions as well as the characteristics of different on the emission source characteristic as well as the atmospheric processes.Figure 6 shows the vertical profiles of NO 2 and HCHO for all four seasons.Significant seasonal patterns are observed from the NO 2 and HCHO data.The NO 2 vertical profiles show higher NO 2 maxing ratios in autumn and winter and lower in spring and summer.NO 2 profiles from all seasons show that the NO 2 mixing ratios decrease with increasing altitude.The result indicates most of the measured NO 2 is produced close to the surface which agrees with the fact that traffic emission is one of the largest source of atmospheric NO 2 in Nanjing.HCHO measurements show a different seasonal variation pattern with lower values during winter and higher mixing ratios in summer.
The seasonal pattern of HCHO indicates the significant contribution from biogenic emissions from vegetation.Although HCHO profiles for all seasons also show decreasing mixing ratio with height, the decreasing rate is in general much lower than that of NO 2 .Larger fraction of HCHO is located at higher altitudes.This is probably related to the source characteristic of HCHO.
Majority of the tropospheric HCHO is secondary produced from the oxidation of VOCs and resulting in a larger portion of HCHO in the upper altitudes.

Regional pollution transport
Air pollutants released to the atmosphere do not only cause local impacts, but also can influence regions far from the source through regional transport.In order to investigate the influences from regional transportation of air pollutants, we use the backward trajectories calculated by the HYSPLIT model to back correlate the possible source regions of the MAX-DOAS measured NO 2 .Similar approaches have also been applied for other source appointment studies (Stohl et al., 2009(Stohl et al., , 2011 Brunner et al., 2012Brunner et al., , 2017;;Wang et al., 2019).Backward trajectories are calculated at the center point of each MAX-DOAS retrieval layer below 2 km.The MAX-DOAS measurement of NO 2 partial columns are then assigned to the grid points along the backward trajectories.We assume the partial columns represent a 200 m thick layer of the assigned grid point and the vertical distribution of NO 2 in the assigned grid point is assumed to be homogeneous from the surface to 2 km above ground.
In this study, the backward propagated NO 2 data are binned in a resolution of 0.2       and t represents the time for the air mass to travel to the measurement site.This weighting scheme is useful when multiple trajectories overlapping with each other within a single grid point.
As the lifetime of NO 2 has a strong seasonal variability, we separate the measurements into summer (June, July and August) and winter (December, January and February) in our analysis.We assume the NO 2 lifetime in summer and winter is 3 h and ity of the reconstructed pollution maps, these numbers are used in this study.NO 2 fields reconstructed from the MAX-DOAS measurements in summer and winter using backward trajectories calculated by the HYSPLIT model are shown in Figure 7a&b.
Figure 7c&d shows the averaged OMI satellite observations of NO 2 during summer (June, July and August) and winter (December, January and February) from June 2013 to February 2017.The OMI measurements show that Nanjing has serious NO 2 pollution problem in winter.
The reconstructed NO 2 fields show a good spatial agreement with OMI satellite observations.However, the reconstructed NO 2 fields are on average 3 times higher than the OMI observations.As the MAX-DOAS NO 2 VCDs are on average 3 times higher than the OMI data, the large discrepancies of the absolute values between the reconstructed data and OMI observations are expected.Elevated NO 2 levels are observed during winter when air mass coming from the east, e.g., Shanghai, Suzhou and Nantong, where OMI observations also show high NO 2 levels.The summer time NO 2 levels are in general lower.However, elevated values can still be observed along the Yangtze River and over some cities, e.g., Nantong and Wuhu.
We have also applied the same approach to the MAX-DOAS HCHO measurements with HCHO lifetime of 1 h and 2 h for summer and winter measurements, respectively.HCHO fields reconstructed from the MAX-DOAS measurements are shown in Figure 8a&b.OMI observations of HCHO are also shown in Figure 8c&d for reference.Summer time HCHO data are in general higher than the observations during winter.However, the spatial distribution of the back propagated HCHO data does not show a strong correlation with the OMI satellite observations as the NO 2 data.This is probably due to HCHO is mostly secondary produced in the atmosphere.In addition, the atmospheric lifetime of HCHO is much shorter compared to NO 2 and therefore more dependent on the local productions.The result suggests that the MAX-DOAS measurements are sensitive to the regional transport of air pollutants.Despite the strong local contributions, the air quality of Nanjing can also be significantly influenced by the air pollution transportation, especially during winter.

Assessments of emission reduction during Youth Olympic
The summer Youth Olympic Games was held from 16 to 28 August 2014 in Nanjing, China.During the event, the government implemented a series of air pollution control measures.Heavy emission vehicles were strictly prohibited.Local heavy industries, e.g., petrochemical and steel industries were required to limit their production during the Youth Olympic Games.
These air pollution control measures were often implemented when such an international events held in China (Wu et al., 2013;Wang et al., 2014;Chan et al., 2015;Liu et al., 2016;Sun et al., 2016).In order to study the influences of the emission control measures implemented during the Youth Olympic Games on the local air quality, we compare the MAX-DOAS observations of aerosol, NO 2 and HCHO taken before, during and after the Youth Olympic Games.We define the pre-Olympic period from a month before the Youth Olympic Games for periods before, during and after the Youth Olympic Games, respectively.Similar reduction pattern is also observed from the NO 2 surface mixing ratios.Averaged NO 2 surface mixing ratios are 7.5, 4.7 and 9.0 ppbv for periods before, during and after the Youth Olympic Games, respectively.The HCHO columns measured during the Youth Olympic Games also decreased by more than ∼50 % from 17 × 10 15 molec/cm 2 before the Olympic down to 8 × 10 15 molec/cm 2 during the Youth Olympic Games.Surface HCHO mixing ratios also show similar reduction.The surface HCHO mixing ratios measured also reduced from 7.0 ppbv before the Youth Olympic to 3.3 ppbv during the Youth Olympic.As the meteorological conditions are very similar during the three periods, the decrease of pollutant concentrations are mainly attributed to the reduction of emissions during the Youth Olympic Games.

Summary and conclusions
In this paper, we present long term observations of atmospheric NO 2 and HCHO in Nanjing using a MAX-DOAS instrument.Using the MAX-DOAS NO 2 profile as a priori information in the OMI retrieval on average increased the OMI NO 2 VCDs by ∼30 % with correlation nearly unchanged.However, the improved OMI NO 2 VCDs are still about 50 % lower than the

Figure 1 .
Figure 1.An example of the DOAS retrieval of NO2 and HCHO DSCDs from a a MAX-DOAS spectrum taken on 12 th May 2013 at 08:48 (local time) with viewing elevation angle of 1 • .The left panels show the DOAS fit in the wavelength range of 338 -370 nm, while the right panels show DOAS fit in the wavelength range of 324.5 -359 nm.

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relative) intensities are assumed to vary smoothly with time with the solar and viewing geometry.Rapid change of O 4 DSCDs and intensities indicates a sudden change in the radiative transport condition which is likely due to the present of clouds.

Figure 2 .
Figure 2.An example of vertical profile retrieval of aerosol extinction, NO2 and HCHO from MAX-DOAS measurements taken on 4 th July 2013 at around 8:47 (local time).The left panels show the (a) aerosol extinction, (d) NO2 and (g) HCHO profiles.Panels in the middle column indicate the average kernel of (b) aerosol extinction, (e) NO2 and (h) HCHO profile retrieval.The measured (blue curves) and modeled (green curves) DSCDs of (c) O4, (f) NO2 and (i) HCHO are shown in the right column.

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32.20 • N, 118.70 • E), which is located at the north bank of the Yangtze River.The sun photometer site is ∼25 km northwest of the MAX-DOAS measurement site.The two instruments are separated by the Yangtze River.An industrial park is about 3 km east of the sun photometer site.Heavy industry factories, i.e., steel and cement plants are located in the industrial park.
photometer and MAX-DOAS.Both datasets are cloud filtered.AODs measured by both MAX-DOAS and sun photometer are in general in good agreement.The Pearson correlation coefficient (R) of daily averaged data is 0.73.The slope of the total least squares regression between the two datasets is 0.56 with an offset of 0.13.The discrepancies between the two datasets can be explain by the difference of measurement technique and measurement location.The sun photometer derives AOD from direct sun measurements, while the MAX-DOAS retrieves AOD using the O 4 absorption information from scattered sun light.

Figure 3 .
Figure 3.Comparison of AOD measured by the MAX-DOAS and sunphotometer.The total least squares regression line is calculated based on the daily data.

Figure 4 .Figure 5 .
Figure 4. (a) Time series of the MAX-DOAS (red markers) and NASA's OMI (blue markers) tropospheric NO2 VCDs over Nanjing from 2013 to 2017.MAX-DOAS data are temporally averaged around the OMI overpass time.OMI measurements are spatially averaged for pixels within 20 km of the MAX-DOAS measurement site.OMI NO2 VCDs retrieved using MAX-DOAS profile as a priori information are indicated as green markers.Tropospheric NO2 VCDs taken from KNMI product are also shown as gray marker for reference.(b) Comparison of tropospheric NO2 VCDs between the MAX-DOAS and OMI satellite observations.The total least squares regression line is calculated based on the monthly average data.

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local time), while OMI VCDs are spatially averaged for pixels within 20 km of the MAX-DOAS measurement site.Time series of MAX-DOAS and OMI observations of NO 2 and HCHO VCDs are shown in Figure 4 and Figure 5, respectively.Both OMI NO 2 and HCHO datasets are filtered for cloud radiance fraction smaller than 0.4.Daily and monthly averaged data are shown.Missing data for some months are due to cloud filtering or instrumental issues of the MAX-DOAS.

Figure 7 .
Figure 7.The upper panels show spatial distribution of NO2 in (a) summer and (b) winter reconstructed from the MAX-DOAS measurements using backward trajectories calculated by the HYSPLIT model.Backward trajectories are calculated over 6 h for summer measurements and 12 h for winter measurements.The lower panels indicates the average OMI NO2 vertical column densities over the Yangtze River Delta during (c) summer and (d) winter.

Figure 8 .
Figure 8.The upper panels show spatial distribution of HCHO in (a) summer and (b) winter reconstructed from the MAX-DOAS measurements using backward trajectories calculated by the HYSPLIT model.Backward trajectories are calculated over 6 h for summer measurements and 12 h for winter measurements.The lower panels indicates the average OMI HCHO vertical column densities over the Yangtze River Delta during (c) summer and (d) winter.

Figure 9 .Figure 10 .
Figure 9.Time series of (a) aerosol optical depths, (b) HCHO and NO2 VCDs and (c) HCHO and NO2 surface mixing ratios measured by the MAX-DOAS around the Youth Olympic Games.Hourly and daily averaged values are shown.The gray shadowed area indicates the Youth Olympic Games period (16 to 28 August 2014).

Figure 11 .
Figure 11.Boxplots of (a) aerosol optical depths, (b) NO2 and (c) HCHO VCDs before, during and after the Youth Olympic Games.
Ground based MAX-DOAS measurements were performed from April 2013 to February 2017.Differential slant columns of O 4 , NO 2 and HCHO were retrieved by applying the differential optical absorption technique to the scattered sun light spectra at the UV band.The results are served as inputs for the retrieval of aerosol extinction, NO 2 and HCHO profiles in the lower troposphere.Aerosol results derived from the MAX-DOAS observations are validated by comparing the AODs to sun photometer observations.The MAX-DOAS and sun photometer measurements show a good agreement with each other with Pearson correlation coefficient (R) of 0.73.Considering the differences in measurement technique and measurement location, we concluded that the MAX-DOAS aerosol measurements are reliable for the NO 2 and HCHO profile retrieval.Tropospheric vertical column densities (VCDs) of NO 2 derived from MAX-DOAS measurements are used to validate OMI observations.The comparison shows that the OMI observations correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91.However, OMI observations are on average 60 % lower than the MAX-DOAS measurements.

Table 1 .
The DOAS retrieval settings for different wavelength bands.
with a regression window of 3 hours to the O 4 DSCDs and intensities time series at each elevation angle to filter data influenced by inhomogeneous and/or rapid changes of radiation transport conditions.Data with fast varying O 4 DSCDs and intensities were filter out.Only data with slow varying O 4 DSCDs and intensities were used in the aerosol and trace gas retrieval.The limitation of this cloud screening algorithm is that the algorithm is not able to distinguish continuous and homogeneous cloud condition.However, it is rare that the cloud does not change for a long time (within an hour) and the cloud layer is homogeneous for all viewing Thus, the MAX-DOAS measurement of O 4 DSCDs should be smaller than the one simulated with pure Rayleigh atmosphere.In this study, we compared the forward simulation of O 4 DSCDs under aerosol free condition to the O 4 DSCDs retrieved from the MAX-DOAS observations to examine the necessity of O 4 correction.Our result shows that the measured O 4 DSCDs occasionally exceeded the forward simulation results which implies that correction of O 4 DSCDs is necessary.The ratio between simulated and measured O 4 DSCD varies from 0.75 to 1.0 for cases where the measured O 4 DSCDs exceeded the forward simulation results.Our finding agrees with previous reported scaling correction factors of O 4 DSCDs which is ranging