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.

Fire in China, driven by both natural and anthropogenic factors, significantly influences ecological stability. This study provides a comprehensive spatiotemporal analysis of active fires across China from 2003 to 2024 using MODIS Collection 6.1 active fire and land cover products. Our results reveal a significant national decline in fire counts since 2016, accompanied by with a marked geographical shift in hotspots from East China to Northeast China. It clarifies that croplands and savannas are the main fire-prone land covers, yet they have also experienced the most substantial decline in fire counts. East China (46.8%) and Central China (27.1%) were the largest contributors to the reduction in cropland fire counts. Temporal displacement toward nighttime straw burning was observed in East China. The decline in average fire radiative power (FRP) of daytime agricultural fires indicates that straw burning bans effectively reduced both the frequency and intensity of fires. Persistent savanna and forest fires are highly clustered in Southern China, while new emerging grassland fires are concentrated in Western China. Persistent cropland fires overlap with emerging zones in Northeast and Central China. Our study can assist in optimizing targeted fire policies and supporting better fire risk management.

Open burning of crop residue is a major source of air pollutants in China. While a nationwide straw burning ban implemented in 2016 has proven effective in reducing primary emissions, its impact on ozone (O₃), a key pollutant detrimental to human health, remain poorly quantified. This study aims to assess the impact of straw burning on downwind urban O₃ pollution and to investigate the complex mechanisms governing O₃ changes resulting from transported agricultural fire plumes. Here, using multi-satellite data and ground observations from 2013 to 2020, this study developed a method to identify smoke-affected days and estimate plume transport time over northern China. The results show that the straw burning ban effectively reduced peak concentrations of particulate matter (PM_2.5) during harvest seasons. However, O₃ responses on smoke-affected days were heterogeneous, showing both increases and decreases. The random forest model revealed the meteorological and chemical drivers of O₃ variability. Elevated formaldehyde (HCHO) and temperatures promote O₃ production, while higher NO₂ and relative humidity enhance its titration. Trajectory analysis further decoupled the mechanisms that O₃ and HCHO enhancements were primarily driven by local photochemistry, whereas NO₂ increases were attributable to regional transport and mixing with anthropogenic pollution. This study underscores the necessity for integrated air quality management strategies that account for the complex trade-offs between PM_2.5 and O₃ to fully realize the public health benefits of emission control policies.

This work presents a comprehensive investigation of tropospheric NO₂ measurements using a portable ground-based Pandora spectrometer, incorporating an independently designed and implemented calibration and retrieval process (P-CAR v1.0). We designed and optimized a region-specific algorithm for retrieving tropospheric NO₂ column densities in China. The measurement process began with establishing a spectral calibration system for processing the Pandora’s raw observations, followed by enhancing the differential optical absorption spectroscopy (DOAS) algorithm to retrieve both the slant column densities (SCDs) and tropospheric vertical column densities (VCDs) of NO₂. To validate our retrieval products, comparative analyses were conducted against co-located MAX-DOAS measurements. The results demonstrate excellent agreement between Pandora-retrieved tropospheric NO₂ and MAX-DOAS observations, with correlation coefficients exceeding 0.96 for both hourly and daily mean VCDs and fitting slopes greater than 0.90. Furthermore, the validation extended to multi-satellite observations from the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI), exhibiting pronounced consistency, as evidenced by the correlation coefficients all surpassing 0.90 for the hourly mean values. These findings confirm the high accuracy and reliability of NO₂ retrievals from the portable Pandora instrument, significantly boosting its potential for atmospheric monitoring and application.