High-resolution solar absorption spectra, observed by ground-based Fourier Transform Infrared spectroscopy (FTIR), are used to retrieve vertical profiles and partial or total column concentrations of many trace gases. In this study, we present the tropospheric CO₂ columns retrieved by mid-infrared solar spectra over Hefei, China. To reduce the influence of stratospheric CO₂ cross-dependencies on tropospheric CO₂, an a posteriori optimization method based on a simple matrix multiplication is used to correct the tropospheric CO₂ profiles and columns. The corrected tropospheric CO₂ time series show an obvious annual increase and seasonal variation. The tropospheric CO₂ annual increase rate is 2.71 ± 0.36 ppm yr^-1, with the annual peak value in January, and CO₂ decreases to a minimum in August. Further, the corrected tropospheric CO₂ from GEOS-Chem simulations are in good agreement with the coincident FTIR data, with a correlation coefficient between GEOS-chem model and FTS of 0.89. The annual increase rate of XCO₂ observed from near-infrared solar absorption spectra is in good agreement with the tropospheric CO₂ but the annual seasonal amplitude of XCO₂ is only about 1/3 of dry-air averaged mole fractions (DMF) of tropospheric CO₂. This is mostly attributed to the seasonal variation of CO₂ being mainly dominated by sources near the surface.

High-resolution solar absorption spectra were continuously collected by a ground-based Fourier transform infrared (FTIR) spectrometer to retrieve the total column of carbon monoxide (CO), hydrogen cyanide (HCN), ethane (C₂H₆), acetylene (C₂H₂), and formaldehyde (H₂CO). The time series and variation characteristics of these gases were analyzed. The biomass combustion process is identified by using the correlations between the monthly mean deviations of HCN, C₂H₆, C₂H₂ and H₂CO versus CO and satellite fire point data. The months with high correlation coefficients (R > 0.8) and peaks of fire point number are considered to be with biomass combustion occurrence. The emissions of HCN, C₂H₆, C₂H₂ and H₂CO in Anhui were estimated using the enhancement ratios of gases to CO in these months when biomass combustion was the main driving factor of gas concentration change. The study proved the ability of FTIR system in inferring the period during biomass combustion and estimating emissions of the trace gases concerning biomass combustion.

As an important irritant trace gas in the atmosphere, ammonia (NH₃) significantly impacts human health and environment. Bottom-up emission inventories are widely used to estimate ammonia emissions and their geographical distributions over China. However, high uncertainties are still associated with emission inventories due to inaccurate emission factors used. The Differential Evolution (DE) algorithm is a population-based stochastic optimization algorithm used to solve complicated optimization problems. We quantify NH₃ emissions and lifetime from Infrared Atmospheric Sounding Interferometer (IASI) NH₃ observations together with MERRA-2 wind fields based on the DE algorithm. Two inland cities, Urumchi and Golmud in China, are chosen to study of the NH₃ emissions based on the distributions of NH₃ total columns and wind fields. The NH₃ emissions rate estimated is about 5.84 × 10⁻¹¹ and 4.19 × 10⁻¹¹ kg·m⁻²s⁻¹ in Urumchi and in the Golmud area from May to September from 2008 to 2023, respectively. The lifetime of NH₃ estimated in the two areas is 4.31 and 9.19 h, respectively. We compare the NH₃ emissions and lifetime estimated in this study with the values in other studies, and the results show the reliability of the method used. This work is one of few quantitative studies of NH₃ emissions from cities using satellite observations in China.

Vertical profiles and stratospheric HNO₃ and HCl columns are retrieved by ground-based high resolution Fourier transform infrared spectroscopy (FTIR) remote sensing measurements at the Hefei site in China. The time series of stratospheric HNO₃ and HCl columns from January 2017 to December 2019 showed similar annual variation trends, with an annually decreasing rate of (−9.45 ± 1.20)% yr⁻¹ and (−7.04 ± 0.81)% yr⁻¹ for stratospheric HNO₃ and HCl, respectively. The seasonal amplitudes of stratospheric HNO₃ and HCl are 2.67 × 10¹⁵ molec cm⁻² and 4.76 × 10¹⁴ molec cm⁻² respectively, both reaching their maximum in March and their minimum in September, due to the tropopause height variation. Further, HNO₃ and HCl data were used to compare with Microwave Limb Sounder (MLS) satellite data. MLS satellite data showed similar seasonal variations and annual rates with FTIR data, and the stratospheric HNO₃ and HCl columns of the two datasets have correlation coefficients (r) of 0.87 and 0.88, respectively. The mean bias between satellite and FTIR data of stratospheric HNO₃ and HCl columns are (−8.58 ± 12.22)% and (4.58 ± 13.09)%, respectively.

We utilize the tropospheric NO ₂ columns derived from the observations of Ozone Monitoring Instrument (OMI) onboard AURA to analyze the spatial distributions and temporal trends of NO ₂ in Wanjiang City Belt (WCB) of China from 2005 to 2016. The aim of this study is to assess the effect of industrial transfer policy on the air quality in WCB. Firstly, we used the surface in situ NO ₂ concentrations to compare with the OMI-retrieved tropospheric NO ₂ columns in order to verify the accuracy of the satellite data over the WCB area. Although it is difficult to compare the two datasets directly, the comparison results prove the accuracy of the OMI-retrieved tropospheric NO ₂ columns in cities of WCB. Then, the spatial distributions of the annual averaged tropospheric NO ₂ total columns over Anhui Province show that NO ₂ columns were considerably higher in WCB than those in other areas of Anhui. Also, we compared the spatial distributions of the total NO ₂ columns in 2005 through 2010 and in 2011 through 2016 and found that the total NO ₂ columns in WCB increased by 19.9%, while the corresponding value increased only 13.9% in other Anhui areas except the WCB area. Furthermore, the temporal variations of NO ₂ columns show that although the NO ₂ columns over WCB and Anhui increased significantly from 2005 to 2011, they decreased sharply from 2011 to 2016 due to the strict emission reduction measures in China. Finally, the HYSPLIT model was used to analyze the origins of NO ₂ and transport pathways of air masses in a typical city, Ma’anshan city.

Understanding the distribution of atmospheric water vapor (H₂O) is crucial for global warming studies and climate change mitigation. In this study, we retrieved the ground layer, tropospheric and total columns of H₂O using ground-based high-resolution Fourier transform infrared spectrometry (FTIR). The H₂O total columns are obtained from near-infrared (NIR) and mid-infrared (MIR) spectra, and the ground layer and tropospheric H₂O columns are retrieved from the MIR spectrum. The total columns of H₂O retrieved from NIR and MIR have a good consistency (R = 0.989). Additionally, the ground layer H₂O columns have a similar seasonal variation to total columns and tropospheric columns but have a higher seasonal amplitude. The ground layer H₂O columns are close to the total columns and tropospheric columns in winter; however, in summer, the average difference between the ground layer and total columns and the value between the ground layer and tropospheric columns are large. This is mostly due to temperature variation. The temperature has a linear response to H₂O, and the relationship between surface temperature and ln(XH₂O) values in the ground layer, the entire atmosphere and the troposphere show a significantly positive correlation, and the correlation coefficient R is 0.893, 0.882 and 0.683, respectively. Furthermore, we selected the HYSPLIT model to simulate the back trajectories of air parcels in the four seasons in Hefei and find that the air mass transport has a significant impact on the local H₂O change. These results demonstrate that ground-based high-resolution FTIR technology has high accuracy and precision in observing the vertical distribution and seasonal changes of H₂O in different atmospheres.