The column-averaged dry-air mole fractions of CO₂ (XCO₂), CH₄ (XCH₄) and CO (XCO) have been measured with a Bruker IFS 125HR Fourier-transform infrared (FTIR) spectrometer at Xianghe (39.75^∘ N, 116.96^∘ E, north China) since June 2018. This paper presents the site, the characteristics of the FTIR system and the measurements. The instrumental setup follows the guidelines of the Total Carbon Column Observing Network (TCCON): the near-infrared spectra are recorded by an InGaAs detector together with a CaF₂ beam splitter, and the HCl cell measurements are recorded regularly to derive the instrument line shape (ILS) showing that the instrument is correctly aligned. The TCCON standard retrieval code (GGG2014) is applied to retrieve XCO₂, XCH₄ and XCO. The resulting time series between June 2018 and July 2019 are presented, and the observed seasonal cycles and day-to-day variations in XCO₂, XCH₄ and XCO at Xianghe are discussed. In addition, the paper shows comparisons between the data products retrieved from the FTIR measurements at Xianghe and co-located Orbiting Carbon Observatory-2 (OCO-2) and Tropospheric Monitoring Instrument (TROPOMI) satellite observations. The comparison results appear consistent with validation results obtained at TCCON sites for XCO₂ and XCH₄, while for XCO they highlight the occurrence of frequent high-pollution events. As Xianghe lies in a polluted area in north China where there are currently no TCCON sites, this site can fill the TCCON gap in this region and expand the global coverage of the TCCON measurements. The Xianghe FTIR XCO₂, XCH₄ and XCO data can be obtained at https://doi.org/10.18758/71021049 (Yang et al., 2019).

The new-generation sensor TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel 5 precursor (S5P) satellite is promising for monitoring air pollutants with greater spatial resolution, especially for China, which suffers from severe pollution. As tropospheric NO₂ vertical column densities (VCDs) from TROPOMI have become available since February 2018, this study presents the comparisons of NO₂ data measured by TROPOMI and its predecessor Ozone Monitoring Instrument (OMI) over China, together with validation against ground Multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements. At the nationwide scale, we used two different filters performed for the TROPOMI data (named TROPOMI50 and TROPOMI75), and the TROPOMI50 yielded larger values than TROPOMI75. The TROPOMI NO₂ datasets from different filters show consistent spatial patterns with OMI, and the correlation coefficient values were both above 0.93. However, linear regression indicates that NO₂ loadings in TROPOMI is about 2/3 to 4/5 of those in OMI, which is presumably due to a different cloud mask and uncertainties of air mass factors. The absolute difference is prominent over the high pollution areas such as Jing-Jin-Ji region and during winter and autumn, exceeding 0.6 × 10¹⁶ molecules cm⁻² (molec cm⁻²). However, the NO₂ concentrations retrieved from TROPOMI50 in the southern China may be somewhat higher than OMI. When it comes to the local-scale Jing-Jin-Ji hotspot, the analysis focuses on a comparison to TROPOMI75. TROPOMI manifests high quality and exhibits a significantly better performance of representing spatial variability. In contrast, OMI shows fewer effective pixels and does a poor job of capturing local details due to its row anomaly and low resolution. The absolute difference between two datasets shows the same seasonal behavior with NO₂ variation, which is most striking in the winter (0.31 × 10¹⁶ molec cm⁻²) and is lowest in the summer (0.05 × 10¹⁶ molec cm⁻²). Furthermore, the ground MAX-DOAS instrument in Xianghe station, the representative site in Jing-Jin-Ji, is used to assess the skill of satellite retrievals. It turns out that both OMI and TROPOMI underestimate the observations, ranging from 30% to 50%, with OMI being less biased. In spite of the negative drift, the temporal structures of changes derived from OMI and TROPOMI closely match the ground-based records, since the correlation coefficients are above 0.8 and 0.95 for daily and monthly scales, respectively. Overall, TROPOMI NO₂ retrievals are better suited for applications in China as well as the Jing-Jin-Ji hotspot due to its higher spatial resolution, although some improvements are also needed in the near future.

In recent years, new and strict air quality regulations have been implemented in China. Therefore, it is of great significance to evaluate the current air pollution situation and effectiveness of actions. In this study, Ozone Monitoring Instrument (OMI) satellite data were used to detect the spatiotemporal characteristics of tropospheric NO₂ columns over China from 2005 to 2018, including spatial distribution, seasonal cycles and long-term trends. The averaged NO₂ pollution is higher in southeastern China and lower in the northwest, which are well delineated by the Heihe–Tengchong line. Furthermore, the NO₂ loadings are highest in the North China Plain, with vertical column density (VCD) exceeding 13 × 10¹⁵ molec cm⁻². Regarding the seasonal cycle, the NO₂ loadings in eastern China is highest in winter and lowest in summer, while the western region shows the opposite feature. The amplitude of annual range increase gradually from the south to the north. If the entire period of 2005–2018 is taken into account, China has experienced little change in NO₂. In fact, however, there appears to be significant trends of an increase followed by a downward tendency, with the turning point in the year 2012. In the former episode of 2005–2012, increasing trends overwhelm nearly the whole nation, especially in the Jing–Jin–Tang region, Shandong Province, and Northern Henan and Southern Hebei combined regions, where the rising rates were as high as 1.0–1.8 × 10¹⁵ molec cm⁻² year⁻¹. In contrast, the latter episode of 2013–2018 features remarkable declines in NO₂ columns over China. Particularly, the regions where the decreased degree was remarkable in 2013–2018 were consistent with the regions where the upward trend was obvious in 2005–2012. Overall, this upward–downward pattern is true for most parts of China. However, some of the largest metropolises, such as Beijing, Shanghai and Guangzhou, witnessed a continuous decrease in the NO₂ amounts, indicating earlier and more stringent measures adopted in these areas. Finally, it can be concluded that China’s recent efforts to cut NO₂ pollution are successful, especially in mega cities.

The TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite has been used to detect the atmospheric environment since 2017, and it is of great significance to investigate the accuracy of its products. In this work, we present comparisons between TROPOMI tropospheric NO₂ and total SO₂ products against ground-based MAX-DOAS at a single site (Xianghe) and OMI products over a seriously polluted region (North China Plain, NCP) in China. The results show that both NO₂ and SO₂ data from three datasets exhibit a similar tendency and seasonality. In addition, TROPOMI tropospheric NO₂ columns are generally underestimated compared with collocated MAX-DOAS and OMI data by about 30–60%. In contrast to NO₂, the monthly average SO₂ retrieved from TROPOMI is larger than MAX-DOAS and OMI, with a mean bias of 2.41 (153.8%) and 2.17 × 10¹⁶ molec cm⁻² (120.7%), respectively. All the results demonstrated that the TROPOMI NO₂ as well as the SO₂ algorithms need to be further improved. Thus, to ensure reliable analysis in NCP area, a correction method has been proposed and applied to TROPOMI Level 3 data. The revised datasets agree reasonably well with OMI observations (R > 0.95 for NO₂, and R > 0.85 for SO₂) over the NCP region and have smaller mean biases with MAX-DOAS. In the application during COVID-19 pandemic, it showed that the NO₂ column in January-April 2020 decreased by almost 25–45% compared to the same period in 2019 due to the lockdown for COVID-19, and there was an apparent rebound of nearly 15–50% during 2021. In contrast, a marginal change of the corresponding SO₂ is revealed in the NCP region. It signifies that short-term control measures are expected to have more effects on NO₂ reduction than SO₂; conversely, we need to recognize that although the COVID-19 lockdown measures improved air quality in the short term, the pollution status will rebound to its previous level once industrial and human activities return to normal.

Monitoring the atmospheric CO${}_2$ columns inside and around a city is of great importance to understand the temporal–spatial variation of XCO${}_2$ near strong anthropogenic emissions. In this study, we use two FTIR CO${}_2$ column measurements in Beijing (Bruker EM27/SUN) and Xianghe (Bruker IFS 125HR) between 2019 and 2021 to investigate the differences of XCO${}_2$ between Beijing (urban) and Xianghe (suburb) in North China and to validate the OCO-2 and OCO-3 satellite XCO${}_2$ retrievals. The mean and standard deviation (std) of the $\Delta$XCO${}_2$ between Beijing and Xianghe (Beijing–Xianghe) observed by two FTIR instruments are 0.206 ± 1.736 ppm, which has a seasonal variation and varies with meteorological conditions (wind speed and wind direction). The mean and std of the XCO${}_2$ differences between co-located satellite and FTIR measurements are −0.216 ± 1.578 ppm in Beijing and −0.343 ± 1.438 ppm in Xianghe for OCO-2 and 0.637 ± 1.594 ppm in Beijing and 1.206 ± 1.420 ppm in Xianghe for OCO-3. It is found that the OCO-3 snapshot area mode (SAM) measurements can capture the spatial gradient of XCO${}_2$ between urban and suburbs well. However, the FTIR measurements indicate that the OCO-3 SAM measurements are about 0.9–1.4 ppm overestimated in Beijing and Xianghe.