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Carbon dioxide (CO2) is the most important long-lived greenhouse gas and can be retrieved using solar absorption spectra recorded by a ground-based Fourier-transform infrared spectrometer (FTIR). In this study, we investigate the CO2 retrieval strategy using the Network for the Detection of Atmospheric Composition Change–Infrared Working Group (NDACC–IRWG) type spectra between August 2018 and April 2022 (~4 years) at Xianghe, China, aiming to find the optimal observed spectra, retrieval window, and spectroscopy. Two spectral regions, near 2600 and 4800 cm−1, are analyzed. The differences in column-averaged dry-air mole fraction of CO2 (XCO2) derived from spectroscopies (ATM18, ATM20, HITRAN2016, and HITRAN2020) can be up to 1.65 ± 0.95 ppm and 7.96 ± 2.02 ppm for NDACC-type 2600 cm−1 and 4800 cm−1 retrievals, respectively, which is mainly due to the CO2 differences in air-broadened Lorentzian HWHM coefficient (γair) and line intensity (S). HITRAN2020 provides the best fitting, and the retrieved CO2 columns and profiles from both 2600 and 4800 cm−1 are compared to the co-located Total Column Carbon Observing Network (TCCON) measurements and the greenhouse gas reanalysis dataset from the Copernicus Atmosphere Monitoring Service (CAMS). The amplitude of XCO2 seasonal variation derived from the NDACC-type (4800 cm−1) is closer to the TCCON measurements than that from the NDACC-type (2600 cm−1). Moreover, the NDACC-type (2600 cm−1) retrievals are strongly affected by the a priori profile. For tropospheric XCO2, the correlation coefficient between NDACC-type (4800 cm−1) and CAMS model is 0.73, which is higher than that between NDACC-type (2600 cm−1) and CAMS model (R = 0.56). [ABSTRACT FROM AUTHOR]

Nitrous oxide (N2O) and methane (CH4) are two important greenhouse gases in the atmosphere. In 2019, mid-infrared (MIR) solar absorption spectra were recorded by a Bruker VERTEX 70 spectrometer and a Bruker IFS 125HR spectrometer at Sodankylä, Finland, at spectral resolutions of 0.2 and 0.005 cm-1 , respectively. The N2O and the CH4 retrievals from high-resolution MIR spectra have been well investigated within the Network for the Detection of Atmospheric Composition Change (NDACC) but not for MIR spectra gathered with instruments operating at low spectral resolution. In this study, N2O and CH4 retrieval strategies and retrieval uncertainties from the VERTEX 70 MIR low-resolution spectra are discussed and presented. The accuracy and precision of the VERTEX 70 N2O and CH4 retrievals are assessed by comparing them with the coincident 125HR retrievals and AirCore measurements. The relative differences between the N2O total columns retrieved from 125HR and VERTEX 70 spectra are - 0.3 ± 0.7 (1 σ) % with a correlation coefficient (R) of 0.93. Regarding the CH4 total column, we first used the same retrieval microwindows for 125HR and VERTEX 70 spectra, but there is an underestimation in the VERTEX 70 retrievals, especially in summer. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX 70 spectra are -1.3±1.1 (1 σ) % with a R value of 0.77. To improve the VERTEX 70 CH4 retrievals, we propose alternative retrieval microwindows. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX 70 spectra in these new windows become 0.0±0.8 (1 σ) %, along with an increase in the R value to 0.87. The coincident AirCore measurements confirm that the VERTEX 70 CH4 retrievals using the latter window choice are better, with relative mean differences between the VERTEX 70 CH4 retrievals and AirCore measurements of - 1.9 % for the standard NDACC microwindows and of 0.13 % for the alternative microwindows. This study provides insight into the N2O and CH4 retrievals from the low-resolution (0.2 cm-1) MIR spectra observed with a VERTEX 70 spectrometer, and it demonstrates the suitability of this kind of instrument for contributing to satellite validation, model verification, and other scientific campaigns with the advantage of its transportability and lower cost compared to standard NDACC-type Fourier-transform infrared (FTIR) instruments. [ABSTRACT FROM AUTHOR]

In this study, we present O3 retrievals from ground-based Fourier transform infrared (FTIR) solar absorption measurements between June 2018 and December 2019 at Xianghe, China (39.75 ∘ N, 116.96 ∘ E). The FTIR spectrometer at Xianghe is operated with indium gallium arsenide (InGaAs) and indium antimonide (InSb) detectors, recording the spectra between 1800 and 11 000 cm -1. As the harmonized FTIR O3 retrieval strategy within the Network for the Detection of Atmospheric Composition Change (NDACC) uses the 1000 cm -1 spectral range, we apply the O3 retrieval in the 3040 cm -1 spectral range at Xianghe. The retrieved O3 profile is mainly sensitive to the vertical range between 10 and 40 km, and the degrees of freedom for signal is 2.4±0.3 (1σ), indicating that there are two individual pieces of information in partial columns between the surface and 20 km and between 20 and 40 km. According to the optimal estimation method, the systematic and random uncertainties of the FTIR O3 total columns are about 13.6 % and 1.4 %, respectively. The random uncertainty is consistent with the observed daily standard deviation of the FTIR retrievals. To validate the FTIR O3 total and partial columns, we apply the same O3 retrieval strategy at Maïdo, Réunion (a.k.a. Reunion Island; 21.08 ∘ N, 55.38 ∘ E). The FTIR O3 (3040 cm -1) measurements at Xianghe and Maïdo are then compared with the nearby ozonesondes at Beijing (39.81 ∘ N, 116.47 ∘ E) and at Gillot (20.89 ∘ S, 55.53 ∘ E), respectively, as well as with co-located TROPOspheric Monitoring Instrument (TROPOMI) satellite measurements at both sites. In addition at Maïdo, we compare the FTIR O3 (3040 cm -1) retrievals with the standard NDACC FTIR O3 measurements using the 1000 cm -1 spectral range. It was found that the total columns retrieved from the FTIR O3 3040 cm -1 measurements are underestimated by 5.5 %–9.0 %, which is mainly due to the systematic uncertainty in the partial column between 20 and 40 km (about -10.4 %). The systematic uncertainty in the partial column between surface and 20 km is relatively small (within 2.4 %). By comparison with other measurements, it was found that the FTIR O3 (3040 cm -1) retrievals capture the seasonal and synoptic variations of the O3 total and two partial columns very well. Therefore, the ongoing FTIR measurements at Xianghe can provide useful information on the O3 variations and (in the future) long-term trends. [ABSTRACT FROM AUTHOR]

Methane (CH4) is one of the most important greenhouse gases in the atmosphere, making it worthwhile to study its temporal and vertical distributions in source areas, e.g., North China. For this purpose, a ground-based high-resolution Fourier transform infrared spectrometer (FTIR), the Bruker IFS 125HR, along with an in-situ instrument, the Picarro G2301, were deployed in Xianghe County (39.8°N,117.0°E), Hebei Province, China. Data have been recorded since June 2018. For the FTIR measurements, we used two observation modes to retrieve the mole fraction of CH4: the Total Carbon Column Observing Network (TCCON) method (retrieval algorithm: GGG2014), and the Network for the Detection of Atmospheric Composition Change (NDACC) method (retrieval algorithm: SFIT4). Combining FTIR with in-situ measurements, we found the temporal and vertical distributions of atmospheric CH4 within three vertical layers (near the ground, in the troposphere, and in the stratosphere), and throughout the whole atmosphere. Regarding the diurnal variation of CH4 near the ground, the concentration at night was higher than during the daytime. Regarding the seasonal variation, CH4 was low in spring and high in summer, for all three vertical layers. In addition, there was a peak of CH4 in winter near the ground, both in the troposphere and the whole atmosphere. We found that variation of CH4 in the tropospheric column was close to that of the in-situ measurements near the ground. Furthermore, the variations of CH4 in the stratospheric column could be influenced by vertical motions, since it was higher in summer and lower in winter. [ABSTRACT FROM AUTHOR]

Column-averaged dry-air mole fraction of CO (X CO) measurements are obtained from two ground-based Fourier transform infrared (FTIR) spectrometer networks: the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC). In this study, the differences between the TCCON and NDACC X CO measurements are investigated and discussed based on six NDACC–TCCON sites using data over the period 2007–2017. A direct comparison shows that the NDACC X CO measurements are about 5.5 % larger than the TCCON data at Ny-Ålesund, Bremen, and Izaña (Northern Hemisphere), and the absolute bias between the NDACC and TCCON data is within 2 % at Saint-Denis, Wollongong and Lauder (Southern Hemisphere). The hemispheric dependence of the bias is mainly attributed to their smoothing errors. The systematic smoothing error of the TCCON X CO data varies in the range between 0.2 % (Bremen) and 7.9 % (Lauder), and the random smoothing error varies in the range between 2.0 % and 3.6 %. The systematic smoothing error of NDACC data is between 0.1 % and 0.8 %, and the random smoothing error of NDACC data is about 0.3 %. For TCCON data, the smoothing error is significant because it is higher than the reported uncertainty, particularly at Southern Hemisphere sites. To reduce the influence from the a priori profiles and different vertical sensitivities, the scaled NDACC a priori profiles are used as the common a priori profiles for comparing TCCON and NDACC retrievals. As a result, the biases between TCCON and NDACC X CO measurements become more consistent (5.6 %–8.5 %) with a mean value of 6.8 % at these sites. To determine the sources of the remaining bias, regular AirCore measurements at Orléans and Sodankylä are compared to co-located TCCON measurements. It is found that TCCON X CO measurements are 6.1 ± 1.6 % and 8.0 ± 3.2 % smaller than the AirCore measurements at Orléans and Sodankylä, respectively, indicating that the scaling factor of TCCON X CO data should be around 1.0000 instead of 1.0672. Further investigations should be carried out in the TCCON community to determine the correct scaling factor to be applied to the TCCON X CO data. This paper also demonstrates that the smoothing error must be taken into account when comparing FTIR X CO data, and especially TCCON X CO data, with model or satellite data. [ABSTRACT FROM AUTHOR]