Aerosol optical depth (AOD) serves as a significant parameter in aerosol research. With the increasing utilization of satellite data in AOD research, it is crucial to evaluate the satellite AOD data. Using Aerosol Robotic Network (AERONET) in situ measurements, this study investigates the accuracy and applicability of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) AOD data in Asia from June 2006 to June 2023. By matching the CALIPSO AOD data in a 1° × 1° area around the selected AERONET sites, various statistical metrics were used to create a comprehensive evaluation system. The results show that: (1) There is a high correlation between the AODs of CALIPSO and AERONET (R = 0.636), and the AOD values of CALIPSO are only 1.7% higher than those of AERONET on average. The MAE (0.215) and RMSE (0.358) suggest that the error level of CALIPSO AOD is relatively low; (2) In most of the 25 sites throughout Asia CALIPSO AOD have high matching accuracies with the AERONET AOD, and only in three sites has a validation accuracy of ‘Poor’; (3) The accuracy varies across the four seasons, ranked as follows: winter demonstrates the highest accuracy, followed by autumn, spring, and summer; (4) The accuracy varies with surface elevation, with better matching in lowest altitude (500 m) areas, but slightly worse matching in medium altitude (200–500 m) areas and low altitude (50–200 m). The uncertainty in the CALIPSO AOD retrievals varies in seasons, altitudes, and aerosol characteristics.

In this study, the spatial–temporal characteristics of AOD in the Yellow River Basin (YRB) and urban agglomerations within the basin were analyzed at a 1 km scale from 2011 to 2020 based on the MCD19A2 AOD dataset. This study shows the following: (1) From 2011 to 2020, the AOD value of the YRB showed a declining trend, with 96.011% of the zones experiencing a decrease in AOD. The spatial distribution of AOD displayed a pattern of high in the east, low in the west, high in the south, and low in the north. The rate of decline showed a distribution pattern of fast in the southeast and slow in the northwest. (2) The AOD in the YRB showed similar characteristics in different seasons: the south and east were consistently higher than the north and west. The seasonal AOD values in the YRB showed the following pattern: summer > spring > autumn > winter. The AOD values of urban agglomeration were basically larger in spring and summer. (3) The SDE and mean center of the yearly AOD were located in the southeast and Shanxi Province, with the movement from southeast to northwest. It can be divided into three stages based on the movement trajectory: northeast–southwest round-trip movement (2011–2014), one-way movement to the northwest (2014–2018), and southeast–northwest round-trip movement (2018–2020).

Identifying the types and vertical distribution of aerosols plays a significant role in evaluating the influence of aerosols on the climate system. Based on the aerosol optical properties obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), this study analyzed the long-term aerosol characteristics of seven cities in East Asia (Ulaanbaatar, Beijing, Lanzhou, Shanghai, Lhasa, Hong Kong, and Bangkok) from 2007 to 2021, including the spatiotemporal variations of aerosol optical depth (AOD), the vertical stratification characteristics of aerosols, and the main aerosol subtype. The results showed that, except for Lhasa, the AOD values of all cities exhibited a trend of initially increasing and then decreasing over the years. Except for Shanghai, the high values of AOD in the other cities occurred in the spring and summer seasons, while the low values occurred in the autumn and winter seasons. In all four seasons, the AOD contribution within the 1–3 km range accounted for more than 50% of the total. In the autumn and winter seasons, this proportion reached over 80%. The main types of aerosols and their contributions varied at different altitudes. Overall, dust, polluted continental/smoke, polluted dust, and elevated smoke dominated in all aerosol layers across each city. On the other hand, clean marine, clean continental, and dusty marine had very small proportions, accounting for less than 5% of all the cities’ aerosol layers.

Although satellite sensors provide global observations, factors such as cloud interference and narrow swath widths frequently result in partial data gaps which constrain the continuous spatiotemporal analysis of the column-averaged dry air mole fraction of CO₂ (XCO₂). To address this challenge, this study develops a novel multi-stage fusion framework that integrates GOSAT and OCO-2 data using inverse error variance weighting and a dynamic bias correction technique, generating a seamless monthly XCO₂ dataset for East Asia (2016–2024). Validation against TCCON measurements (RMSE = 1.22 ppm; R² = 0.96) and WDCGG data (RMSE = 2.85 ppm; R² = 0.76) demonstrates the high accuracy of the product. The results show that the growth rate consistently exceeds 2.2 ppm/year, with clear seasonal patterns characterized by spring maxima and summer minima. Spatially, the locus of rapid growth has shifted toward central and western China, reflecting patterns of regional economic development, while substantial concentrations still persist in the industrialized regions of eastern China, Japan, and South Korea. This study provides new insights into regional atmospheric CO₂ dynamics and emphasizes the efficacy of dynamic bias correction in data fusion.