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 (NOx), 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 NOx 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 NOx emitters in the world6. As a result, China is experiencing a series of severe air pollution problems7,8. 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.
figure 1

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

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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 regions14,15. 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 Vtropo and Vstrat denote tropospheric and stratospheric V, respectively. Mtropo and Mstrat 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, Vstrat, and Vtropo 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.
figure 2

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

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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
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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.
figure 3

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

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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.
figure 4

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

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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.
figure 5

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

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

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

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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 observations24,25. 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.
figure 7

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

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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.