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.

The spatial and temporal changes in SO₂ regimes over China during 2005 to 2016 and their associated driving mechanism are investigated based on a state-of-the-art retrieval dataset. Climatological SO₂ exhibits pronounced seasonal and regional variations, with higher loadings in wintertime and two prominent maxima centered in the North China Plain and the Cheng-Yu District. In the last decade, overall SO₂ decreasing trends have been reported nationwide, with spatially varying downward rates according to a general rule – the higher the SO₂ loading, the more significant the decrease. However, such decline is in fact not monotonic, but instead four distinct temporal regimes can be identified by empirical orthogonal function analysis. After an initial rise at the beginning, SO₂ in China undergoes two sharp drops in the periods 2007–2008 and 2014–2016, amid which 5-year moderate rebounding is sustained. Despite spatially coherent behaviors, different mechanisms are tied to North China and South China. In North China, the same four regimes are detected in the time series of emission that is expected to drive the regime of atmospheric SO₂, with a percentage of explained variance amounting to 81 %. Out of total emission, those from the industrial sector dominate SO₂ variation throughout the whole period, while the role of household emission remains uncertain. In contrast to North China, SO₂ emissions in South China exhibit a continuous descending tendency, due to the coordinated cuts of industrial and household emissions. As a result, the role of emissions only makes up about 45 % of the SO₂ variation, primarily owing to the decoupled pathways of emission and atmospheric content during 2009 to 2013 when the emissions continue to decline but atmospheric content witnesses a rebound. Unfavorable meteorological conditions, including deficient precipitation, weaker wind speed and increased static stability, outweigh the effect of decreasing emissions and thus give rise to the rebound of SO₂ during 2009 to 2013.

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.

Atmospheric CO₂ mole fractions are observed at Beijing (BJ), Xianghe (XH), and Xinglong (XL) in North China using Picarro G2301 cavity ring-down spectroscopy instruments. The measurement system is described comprehensively for the first time. The geographical distances among these three sites are within 200 km, but they have very different surrounding environments: BJ is inside the megacity; XH is in the suburban area; XL is in the countryside on a mountain. The mean and standard deviation of CO₂ mole fractions at BJ, XH, and XL between October 2018 and September 2019 are 448.4±12.8, 436.0±9.2, and 420.6±8.2 ppm, respectively. The seasonal variations of CO₂ at these three sites are similar, with a maximum in winter and a minimum in summer, which is dominated by the terrestrial ecosystem. However, the seasonal variations of CO₂ at BJ and XH are more affected by human activities as compared to XL. Using CO₂ at XL as the background, CO₂ enhancements are observed simultaneously at BJ and XH. The diurnal variations of CO₂ are driven by the boundary layer height, photosynthesis, and human activities at BJ, XH, and XL. We also compare the CO₂ measurements at BJ, XH, and XL with five urban sites in the USA, and it is found that the CO₂ mean concentration at BJ is the largest. Moreover, we address the impact of the wind on the CO₂ mole fractions at BJ and XL. This study provides an insight into the spatial and temporal variations of CO₂ mole fractions in North China.

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.