First observation of tropospheric nitrogen dioxide from the Environmental Trace Gases Monitoring Instrument onboard the GaoFen-5 satellite

Abstract

The Environmental Trace Gases Monitoring Instrument (EMI) is the first Chinese satellite-borne UV–Vis spectrometer aiming to measure the distribution of atmospheric trace gases on a global scale. The EMI instrument onboard the GaoFen-5 satellite was launched on 9 May 2018. In this paper, we present the tropospheric nitrogen dioxide (NO₂) vertical column density (VCD) retrieval algorithm dedicated to EMI measurement. We report the first successful retrieval of tropospheric NO₂ VCD from the EMI instrument. Our retrieval improved the original EMI NO₂ prototype algorithm by modifying the settings of the spectral fit and air mass factor calculations to account for the on-orbit instrumental performance changes. The retrieved EMI NO₂ VCDs generally show good spatiotemporal agreement with the satellite-borne Ozone Monitoring Instrument and TROPOspheric Monitoring Instrument (correlation coefficient R of ~0.9, bias < 50%). A comparison with ground-based MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) observations also shows good correlation with an R of 0.82. The results indicate that the EMI NO₂ retrieval algorithm derives reliable and precise results, and this algorithm can feasibly produce stable operational products that can contribute to global air pollution monitoring.

Remote sensing: Tuned-up satellite identifies pollutant hot spots

Improvements to a high-resolution spectrometer onboard China’s recently-launched GaoFen-5 (GF-5) satellite can give researchers a new tool to assess atmospheric trace gases. Cheng Liu from the University of Science and Technology of China and his colleagues reported the first successful retrieval of nitrogen dioxide from the GF-5 orbiter thanks to crucial adjustments to calibration algorithms. The satellite’s payload Environmental Trace Gases Monitoring Instrument (EMI) uses visible spectroscopic measurements to detect nitrogen dioxide in the atmosphere, which can be used to identify the spatial distribution of pollution emissions on the Earth. To overcome on-orbit issues including detector saturation, the team has optimized the spectral retrieval settings by spectral precalibration, fitting wavelength adjustment, reference spectrum selection, etc. Comparisons to other satellite and ground measurements revealed the optimization effort yielded reliable results for monitoring pollution levels.

Introduction

The Environmental Trace Gases Monitoring Instrument (EMI)¹ is the first Chinese satellite-borne spectrometer with the aim to measure atmospheric pollutants from space. The EMI payload onboard the GaoFen-5 satellite was successfully launched on 9 May 2018. The GaoFen-5 satellite has a polar orbit at an altitude of 706 km. The Chinese EMI instrument is expected to contribute to the understanding of global air quality and atmospheric chemistry, similar to predecessor European and American satellite missions, e.g., the Ozone Monitoring Instrument (OMI)² and TROPOspheric Monitoring Instrument (TROPOMI)³. EMI has instrumental characteristics that are similar to OMI and TROPOMI, e.g., the local overpass time at ~13:30, spectral coverage, push-broom imaging technique, and daily global coverage. Both EMI and TROPOMI (launched in 2017) are new-generation satellite-borne air pollutant sensors compared to the OMI that was launched in 2004. TROPOMI follows the heritage of OMI in both instrument design and trace gas retrievals, but with higher spatial resolution and signal-to-noise ratio. A prototype EMI nitrogen dioxide (NO₂) retrieval algorithm was developed before launch based on the OMI NO₂ retrieval. However, optimization of the NO₂ retrieval algorithm was necessary to adapt the unexpected issues of EMI after launch, especially spectral calibration.

Nitrogen oxides (NO_x), defined as the sum of nitrogen oxide and NO₂, are the major pollutants contributing to ozone and secondary aerosol formation in the troposphere through photochemical reactions⁴. Sources of NO_x include fossil fuel combustion, vehicle emissions, biomass burning, and lightning⁵. Due to rapid industrialization and urbanization in the past few decades, China has become one of the largest NO_x emitters in the world⁶. As a result, China is experiencing a series of severe air pollution problems^7,8. In addition to measuring NO₂ distribution directly from space, applications of satellite remote sensing may include estimations of pollutant emissions⁹, air quality trend detection¹⁰, model validation, and assimilation of satellite data¹¹.

Figure 1a illustrates the optical design of the EMI satellite instrument. The EMI instrument covers the ultraviolet (UV) and visible (Vis) spectral ranges from 240 to 710 nm with a spectral resolution of 0.3–0.5 nm. Light received by the telescope is depolarized by a scrambler and subsequently split into four spectral channels, the UV1 (240–315 nm), UV2 (311–403 nm), VIS1 (401–550 nm), and VIS2 (545–710 nm) channels. Each spectrometer is equipped with a two-dimensional charge-coupled device (CCD) detector, with one dimension used for spectral coverage and the other dimension used for spatial coverage. The EMI instrument scans in the nadir direction toward the earth’s surface with an opening angle of 114° corresponding to a swath width of 2600 km, enabling daily global coverage with a nadir resolution of 12 × 13 km² and a local overpass time of 13:30 (Fig. 1b). The direct sun solar irradiance spectrum, typically used as a reference spectrum in the spectral analysis of the nadir radiance measurement, is introduced to the EMI telescope once a day using the quartz volume diffuser¹². By using the unique absorption features of different trace gases in the UV–Vis range, the abundances of atmospheric pollutants can be retrieved from the difference between atmospheric and solar spectra.

Fig. 1. Illustration of the operating principle of the EMI instrument.

a Schematic diagram of the EMI optical system. b The on-orbit operation of the EMI instrument onboard the GaoFen-5 satellite

In this paper, we present a new tropospheric NO₂ vertical column density (VCD, i.e., the vertical integral of NO₂ concentration from the earth’s surface to the top of the atmosphere) retrieval algorithm dedicated to the EMI instrument. Details of the spectral retrieval, stratospheric–tropospheric separation of the NO₂ column and slant to vertical column conversion are presented. The first EMI retrieval of tropospheric NO₂ columns is compared to datasets from modern state-of-the-art European and American satellite sensors.

Results

NO₂ retrieval overview

The retrieval of tropospheric NO₂ VCDs from satellite UV–Vis observations typically follows a state-of-the-art three-step approach. First, the total NO₂ slant column density (SCD) are retrieved from nadir radiance spectra normalized by the solar irradiance, using the differential optical absorption spectroscopy (DOAS) technique¹³. Subsequently, the stratospheric NO₂ columns are separated from the total NO₂ SCDs by assuming longitudinal homogeneity of stratospheric NO₂, while neglecting the minor contribution of tropospheric NO₂ (usually on the order of 10¹⁴ molecules cm⁻²) over remote clean regions^14,15. Last, tropospheric NO₂ SCDs are converted to VCDs using air mass factors (AMFs)¹⁶. The AMF is defined as the ratio between SCD and VCD. It is a measure of the effective optical path length from the top of the atmosphere to the earth’s surface and reflected to the satellite through the atmosphere:

$$M=\frac{S}{V}$$ 1

where M is the AMF, S denotes the SCD, and V represents the VCD. The AMF can be calculated with a radiative transfer model (RTM). The final tropospheric NO₂ VCD can be derived after subtracting the stratospheric contribution and AMF conversion:

$$V_{\mathrm{tropo}}=\frac{S-V_{\mathrm{strat}}\times M_{\mathrm{strat}}}{M_{\mathrm{tropo}}}=\left(\frac{S}{M_{\mathrm{strat}}}-V_{\mathrm{strat}}\right)\times \frac{M_{\mathrm{strat}}}{M_{\mathrm{tropo}}}$$ 2

where V_tropo and V_strat denote tropospheric and stratospheric V, respectively. M_tropo and M_strat represent tropospheric and stratospheric M, respectively. Details of the stratospheric estimation and AMF calculation are provided in the “Materials and methods” section.

Figure 2 shows an example of EMI NO₂ retrieval of S, V_strat, and V_tropo on 1 January 2019. Enhanced NO₂ levels are observed in Eastern China, India, and the Middle East.

Fig. 2. An example of EMI NO₂ retrieval on 1 January 2019.

The total SCDs (S), stratospheric VCDs (V_strat), and tropospheric VCDs (V_tropo) retrieval of NO₂ are shown in a, b, and c, respectively. Note that satellite ground pixels affected by clouds are indicated in white

Algorithm improvements

A prototype EMI NO₂ retrieval is developed before launch. The prototype algorithm is very similar to the operational OMI NO₂ retrieval¹⁷. However, due to unexpected issues, i.e., low signal-to-noise ratio at the edges of the spectral channels, bad irradiance measurement due to a diffuser calibration issue, and spectral saturation issue, the NO₂ retrieval setting must be further optimized to address these issues. A series of sensitivity tests, including cloud correction, fitting wavelength range, reference selection, and spectral precalibration, have been performed to optimize the settings for tropospheric NO₂ VCD retrieval. Table 1 lists the updated retrieval settings of the EMI NO₂ retrieval. Parameters used in the OMI QA4ECV NO₂ retrieval¹⁷ are also listed for reference.

Table 1.

NO₂ retrieval settings used in the EMI and OMI NO₂ algorithms

Configurations and parameters	OMI NO2 product (Boersma et al.17)	EMI NO2 product (in this study)
NO2 SCDs fitting
Wavelength range	405–465 nm	420–470 nm
Radiometric calibration	Using calibrated (ir)radiance30	Recalibrated the earth radiance measurements
Reference spectrum	Solar irradiance averaged between 2005−2009 (ref. 30)	Daily earth radiance over the remote Pacific
Instrument slit function	Preflight measured31	Calibrated online by using solar atlas22, Gaussian shape assumed.
NO2 AMF calculations
Radiative transfer model (RTM)	Doubling-Adding KNMI (DAK) model17	Vector Linearized Discrete Ordinate Radiative Transfer (VLIDORT) model14
Calculation method	Lookup table interpolation	Lookup table interpolation
A priori NO2 profile	The global chemistry Transport Model version 5 (TM5)32 simulations at 1 × 1°	The GEOS-Chem v10-01 at 2 × 2.5° for the global domain33, and WRF-Chem v3.7 at ~20 km for the China domain34
Stratospheric–tropospheric separation	Data assimilation17	Reference sector method14

The EMI NO₂ fitting range is shifted slightly from 405–465 nm (OMI operational NO₂ setting¹⁷) to 420–470 nm to avoid the lower signal-to-noise ratio region at the edges of the VIS1 channel¹². Figure 3 illustrates an example of the retrieval of NO₂ SCD, i.e., the NO₂ amount integrated along the optical path in the atmosphere, by applying the DOAS fit to the EMI-measured spectrum.

Fig. 3. An example of NO₂ SCD retrieval from the EMI measurement spectra over Beijing on 15 May 2019.

The top panel shows the fitted spectra and reference. The middle panel shows the measured and fitted NO₂ optical depth. The spectral fit residual is shown in the bottom panel

The spectral saturation issue (i.e., the analogue photon signal reaches the maximum digital value of the CCD detector) is critical for EMI observations over bright clouds due to its high surface reflectance. Supplementary Figure 1 shows the global spatial pattern of the root mean square (RMS) of the spectral fitting residual, cloud radiance fraction from TROPOMI observations, and the true color image from the MODIS-Aqua instrument on 1 January 2019. The spatial pattern of the fitting residual RMS is correlated to the cloud pattern. Therefore, we filtered pixels with relatively large spectral fitting residuals, i.e., the RMS values >0.004.

The key calibration data measured during the on-ground calibration¹² seem unsuitable for EMI on-orbit measurements due to the degradation and stability of the instrument in the complex space environment (e.g., cosmic radiation exposure¹⁸ and possible instrument changes since launch¹⁹). Therefore, we recalibrated the EMI earth radiance measurements by comparing the EMI radiance to TROPOMI measurements and RTM simulations. An advantage of DOAS is that it does not rely on precisely calibrated radiance and is less sensitive to the variability in radiometric calibration than other methods based on discrete radiance (e.g., SBUV and TOMS ozone retrieval algorithms²⁰).

Figure 4 shows the comparisons of NO₂ SCDs for one orbit on 4 January 2019 retrieved using these spectral fitting scenarios: (a) current settings of the EMI NO₂ retrieval listed in Table 1; (b) using the measured irradiance spectrum as a reference; and (c) same as in (a) but without spectral precalibration. Irradiance spectra measured by EMI are currently accounting for some calibration issues, and these issues are probably related to the interference of the space environment on the hemispheric reflectance of solar diffusers¹⁸. NO₂ SCDs retrieved with irradiance as a reference show large biases and errors, particularly the central part of the measurement swath (Fig. 4b). Therefore, it is not optimal to use the direct sun irradiance spectra as a reference. To avoid the influence of abnormal irradiance spectra, we use cloud-free earth radiance measurements over the Pacific Ocean as a reference²¹. Compared to using solar irradiance as a reference, using earth radiance as a reference greatly reduced the spectral noise in the fit residual (Fig. 4a, b), which is likely related to the differences between spectra measured with the solar and earth-viewing modes²¹. The mean RMS of fitting residual by using earth radiance as a reference over cloud-free regions is 30% smaller than that with irradiance as a reference, as shown in Fig. 4a, b.

Fig. 4. Comparisons of NO₂ spectral retrieval results from orbit 03241 on 17 December 2018.

a The current EMI NO₂ retrieval in Table 1. b same as in a but using solar reference. c same as in a, but without spectral precalibration. The resulting NO₂ SCD, relative uncertainty, and RMS of the fitting residual are shown in the upper, middle, and bottom panels, respectively. The fitted NO₂ SCD and its uncertainty are masked in the white color when RMS > 0.004

Although using radiance as a reference improved the spectral retrieval, the radiance reference also contains a NO₂ absorption signal. Therefore, we must calculate the SCD offset to compensate for the residual NO₂ signal in the reference spectrum. The SCD offset is calculated using the NO₂ AMFs multiplied by the a priori NO₂ profile taken from the GEOS-Chem model simulations (Supplementary Fig. 2). The NO₂ simulation over clean remote regions is generally consistent with independent satellite observations, with a monthly mean bias of <0.26 × 10¹⁵ molecules cm⁻² (Supplementary Fig. 3). Then, the SCD offset is added back to the NO₂ SCDs. Note that the reference spectra are selected for each cross-track row to minimize the cross-track bias due to instrument artifacts. The systematic cross-track bias in EMI NO₂ SCDs (the so-called “stripes”, see Supplementary Fig. 4) is also observed for the OMI and TROPOMI products, and this bias can also be mitigated by using earth radiance as the reference spectrum²¹.

To account for the small variation in the spectral alignment due to the thermal variation in space¹², we calibrated the additional spectral shift or squeeze and instrument slit function through cross-correlation with a high-resolution solar spectrum atlas²² prior to the NO₂ DOAS fitting. The precalibrated measurement spectra lead to an ~30% smaller SCD fitting uncertainty than using initial calibration parameters (Fig. 4c), as well as a fit residual, and the SCD is nearly unchanged (within ~3.3%).

Discussion

The tropospheric NO₂ VCDs retrieved from EMI spectra are first validated against the OMI QA4ECV NO₂ products and the operational TROPOMI NO₂ products²³. EMI measurements are compared to the OMI and TROPOMI products due to their similar instrument characteristics, i.e., the push-broom design, spectral bands, and near-noon overpass time at ~13:30. Note that the TROPOMI NO₂ product generally followed the OMI QA4ECV NO₂ retrieval algorithm, but TROPOMI has a higher signal-to-noise ratio and spatial resolution²³. Figure 5 shows the monthly averaged NO₂ VCDs measured by EMI, OMI, and TROPOMI in January 2019. EMI NO₂ VCDs generally show similar spatial patterns and amplitudes of NO₂ VCDs compared to OMI and TROPOMI, while finer-scale details of NO₂ are captured by the satellite instrument with a higher spatial resolution. The EMI dataset overestimates NO₂ VCDs by up to 50% over polluted regions, such as the North China Plain (NCP) and India (Fig. 5d) compared to the TROPOMI observations. The spatiotemporal correlations between EMI NO₂ and TROPOMI NO₂ were also evaluated. For data taken from January to August 2019, the correlation coefficient (R) of daily mean NO₂ VCD time series over NCP between EMI and TROPOMI is 0.90, while the spatial correlation coefficient (R) of mean NO₂ VCDs over the NCP is 0.92 (Fig. 6). The remaining discrepancies between EMI and TROPOMI are mainly due to the NO₂ vertical profile used in the tropospheric AMF calculation, while the spectral fitting method (<3%) and stratospheric estimation method (<10%) only show a minor contribution (Supplementary Fig. 5).

Fig. 5. Validations of EMI tropospheric NO₂ VCDs against OMI and TROPOMI observations.

The global distribution of tropospheric NO₂ VCD in January 2019 is shown for a EMI, b TROPOMI, and c OMI. d shows the difference between EMI NO₂ in a and TROPOMI NO₂ in b

Fig. 6. Comparisons between tropospheric NO₂ VCDs from EMI and TROPOMI.

a Shows the daily mean time series of tropospheric NO₂ VCD over the North China Plain (NCP) from EMI and TROPOMI. Error bars indicate the 1σ standard deviation. b The density scatter plot of NO₂ VCDs over the NCP. Data are regridded to a resolution of 0.2° and averaged for the period of January–August 2019

The EMI tropospheric NO₂ VCDs are also compared to the ground-based NO₂ measurements from the Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments over northern China. A good agreement with a Pearson correlation coefficient (R) of 0.82 is found between the two datasets during January–August 2019 (Fig. 7, Supplementary Fig. 6). However, EMI generally underestimates tropospheric NO₂ VCDs by 30% compared to MAX-DOAS. The biases can be explained by the difference in spatial coverage between the ground-based and satellite observations^24,25. In general, both satellite and ground-based validations of EMI NO₂ measurements show good agreement with correlation coefficients (R) of 0.8–0.9, indicating that a new EMI tropospheric NO₂ retrieval provides reliable results for the investigation of air pollution distribution.

Fig. 7. Scatter plot of EMI tropospheric NO₂ VCD against ground-based MAX-DOAS observations in northern China.

Measurements from six different measurement sites are used in the comparison: the Gucheng site (GC, 39.149°N, 115.734°E) in the Hebei Province, the Guokeda site (GKD, 40.408°N, 116.675°E) in Beijing, the Qikeyuan (QKY, 39.9472°N, 116.3206°E) site in Beijing, the Nancheng (NC, 39.781°N, 116.127°E) site in Beijing, the Xianghe site (XH, 39.750°N, 116.095°E) in the Hebei Province, and the Shengyang site (SY, 41.812°N, 123.401°E) in the Liaoning Province

Materials and methods

The stratosphere–troposphere separation

The stratospheric contribution of NO₂ must be subtracted from the total NO₂ column to derive the tropospheric NO₂ column. In the EMI NO₂ retrieval, we used the STRatospheric Estimation Algorithm from Mainz¹⁴ to estimate the stratospheric contribution, which is based on the assumption that there is negligible contribution of tropospheric NO₂ columns over the remote Pacific and cloudy pixels in the middle latitudes. The weighting factors based on cloud and polluted regions, which determines their impacts on the stratospheric estimate, are assigned to each satellite pixel. Subsequently, spatial smoothing based on weighted convolution is used to estimate the global stratospheric column.

NO₂ AMF calculations

The EMI NO₂ AMFs of each atmospheric layer (i.e., Box-AMFs) are calculated at 445 nm by the linearized pseudospherical vector model VLIDORT²⁶ version 2.7. In addition to the solar and satellite-viewing geometries provided in the level 1 data, additional atmospheric and surface information are needed in the AMF calculations. Surface albedo at 442 nm is taken from the OMI minimum earth’s surface Lambertian equivalent reflectance²⁷ and interpolated to the EMI footprints. Considering the same local overpass time between EMI and TROPOMI, cloud top pressure and cloud fraction from TROPOMI²⁸ are used for the calculations of EMI NO₂ AMFs. A priori NO₂ profiles are taken from the high-resolution (~20 km) WRF-Chem simulations for the China domain and from GEOS-Chem simulations at the resolution of 2 × 2.5° for the global domain (Supplementary Fig. 7). The spatial resolution of the NO₂ a priori profile is reportedly one of the dominant uncertainty sources during the NO₂ AMF calculations²⁹. To expedite the calculation, these box-AMFs are precalculated and stored in the six-dimensional lookup table. Then, the box-AMF for each EMI observation can be derived by interpolating within the lookup table.

Author contributions

C.Z. performed the data analysis and wrote the manuscript. C.L. supervised this research and conceived the idea. K.L.C. contributed to the data interpretation and manuscript revisions. H.L., B.L., C.X., and W.T. processed the MAX-DOAS data. H.Z., F.S., and J.L. built the EMI instrument. C.Z. prepared the paper with inputs from all co-authors.

Data availability

The EMI level 1 and NO₂ datasets are available from Cheng Liu (chliu81@ustc.edu.cn) upon reasonable request. The OMI QA4ECV NO₂ and TROPOMI NO₂ datasets are available from http://www.temis.nl/airpollution/no2.html.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary information

Supplementary information is available for this paper at 10.1038/s41377-020-0306-z.