In recent years, large-area heavy haze pollution cases occur frequently in eastern China, especially evident in Beijing-Tianjin-Hebei and the surrounding regions. In order to operationally monitor the process of larger regional heavy haze events, a type of quantitative method based on satellite remote sensing and numerical simulations was first established and applied in multiple heavy haze processes in the research area. First, this study proposed the operational haze aerosol optical depth (HOD) method by combining Terra, Aqua satellite and WRF-NAQPM numerical simulation in haze days. Second, based on the coupled HOD data, we proposed the quantitative method for obtaining the process and severity degree for larger regional heavy haze events. Finally, this study used the method applying it to several typical heavy pollution events which occurred in Beijing-Tianjin-Hebei and its three surrounding provinces in the winter season from 1 November 2015 to 4 January 2016. The validation for HOD retrieval results showed that the couple HOD from this study have good accuracy, the linear correlation coefficient between retrieval HOD and the AERONET Beijing station data reached over 0.8, and the linear correlation coefficient between the retrieval HOD and the regional ground monitoring station PM_2.5 data reached over 0.7. The applied results showed that the method in this study is feasible to reflect the whole process of heavy haze events. Analysis of the typical heavy haze pollution events showed that the set of quantitative haze judging method in this study was consistent with the meteorological conditions in haze days also verifying that the method for haze inversion and the process analysis is reliable.

The Wide-Swath Imaging (WSI) sensor is a Chinese satellite launched in 2022, capable of providing data at resolutions ranging from 75 to 600 m for monitoring aerosols, fire points, and dust, among other uses. In this study, we developed a Dark Dense Vegetation method to retrieve the Aerosol Optical Depth (AOD) quickly from WSI 600 m data. First, after splitting into three types according to the Normalized Difference Vegetation Index (NDVI), we calculated the empirical parameters of land reflectance between the red (0.65 μm) and blue (0.47 μm) channels using Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance products over the Beijing area. Second, the decrease in the NDVI was simulated and analyzed under different AODs and solar zenith angles, and we introduced an iterative inversion approach to account for it. The simulation retrievals demonstrated that the iterative inversion produced accurate results after less than four iterations. Thirdly, we utilized the atmospherically corrected NDVI for dark target identification and output the AOD result. Finally, retrieval experiments were conducted using WSI 600 m data collected over Beijing in 2023. The retrieved AOD images highlighted two air pollution events occurring during 3–8 March and 27–31 October 2023. The inversion results in 2023 showed a strong correlation with Aerosol Robotic Network station data (the correlation coefficient was greater than 0.9). Our method exhibited greater accuracy than the MODIS aerosol product, though it was less accurate than the Multi-Angle Implementation of Atmospheric Correction product.

Relevant studies have shown that methane gas has a close relationship with seismic activity. The concentration of methane released within a tectonic zone can reflect the intensity status of tectonic activities, which is important for seismic monitoring. In this study, the January 2020 Xinjiang Jiashi earthquake was taken as the research object, and the mature Robust Satellite Technique (RST) algorithm was used to characterize the L3-level methane product data from the hyperspectral sensor, Atmospheric Infrared Sounder (AIRS), installed on the Earth Observing System (EOS) AQUA satellite at the monthly scale, 8-day scale and daily scale. An analysis of the spatial and temporal distribution of methane was carried out for before and after the earthquake based on the 3D structural condition of the gas, and the 3D structural conditions of the 8-day scale were introduced. An 8-day scale 3D structural condition was introduced and migration validation was performed, and the results showed that (1) the seismic methane anomaly-extraction process proposed in this study is feasible; (2) the 3D contour features indicated that the methane anomalies that occurred before the Jiashi earthquake were caused by geogenic emissions; (3) the anomaly-extraction algorithm from this study did not extract the corresponding anomalies in the non-seismic year, which indicated that the anomaly-extraction algorithm of this study has some degree of feasibility; and (4) the migrated validation of the Wenchuan earthquake of May 2008 further suggested that methane anomalies at the time of the Wenchuan earthquake were caused by the earthquake.

With the acceleration of global climate change and urbanization, air pollution, particularly ozone pollution, has become a critical environmental issue, especially in the Beijing–Tianjin–Hebei region of China. This study investigates the spatiotemporal distribution of ozone pollution and its precursors, focusing on formaldehyde as a key indicator of volatile organic compounds. Utilizing high-resolution remote sensing data from the China High-Resolution Air Pollutants dataset and TROPOMI HCHO observations from 2013 to 2022, we employed advanced techniques such as the Kolmogorov–Zurbenko filter and high-value area identification to analyze ozone pollution trends, meteorological influences, and the spatial distribution of HCHO concentrations. Our findings reveal a significant increase in ozone concentrations across BTH, with an annual growth rate of 2.51 μg/m³, peaking during the summer months. The KZ filter decomposition highlighted that short-term and seasonal variations dominate ozone fluctuations, driven by meteorological factors such as solar radiation and temperature. Furthermore, the identification of HCHO HVAs demonstrated that urban agglomeration and expansion zones exhibit higher HCHO concentrations, with VOCs-limited zones showing the most pronounced HCHO levels. The study also introduced the PHV (Percentage Higher than Vicinity) index to quantify anomalous HCHO emissions, providing a robust tool for pinpointing pollution hotspots. Based on these insights, we propose targeted emission control strategies for key regions, including urban expansion zones in Zhangjiakou and non-urban zones in Qinhuangdao, to mitigate ozone pollution effectively. This research offers valuable scientific support for regional air quality management and the formulation of precise pollution control measures in the Beijing–Tianjin–Hebei region.