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High spatial resolution XCO2 data is key to investigating the mechanisms of carbon sources and sinks. However, current carbon satellites have a narrow swath and uneven observation points, making it difficult to obtain seamless and full-coverage data. We propose a novel method combining extreme gradient boosting (XGBoost) with particle swarm optimization (PSO) to construct the relationship between OCO-2 XCO2 data and auxiliary data (i.e., vegetation, meteorological, anthropogenic emissions, and LST data), and to map the seamless monthly XCO2 concentration in East Asia from 2015 to 2020. Validation results based on TCCON ground station data demonstrate the high accuracy of the model with an average R2 of 0.93, Root Mean Square Error (RMSE) of 1.33 and Mean Absolute Percentage Error (MAPE) of 0.24 % in five sites. The results show that the average atmospheric XCO2 concentration in East Asia shows a continuous increasing trend from 2015 to 2020, with an average annual growth rate of 2.21 ppm/yr. This trend is accompanied by clear seasonal variations, with the highest XCO2 concentration in winter and the lowest in summer. Additionally, anthropogenic activities contributed significantly to XCO2 concentrations, which were higher in urban areas. These findings highlight the dynamics of regional XCO2 concentrations over time and their association with human activities. This study provides a detailed examination of XCO2 distribution and trends in East Asia, enhancing our comprehension of atmospheric CO2 dynamics.

Guided by intergroup contact theory, this survey study investigates how White American adults' (N = 697 , Mage = 44.42, SD = 14.6, age range = 18 –67) social media intergroup expression frequency and valence, direct contact quality, and perceptions of institutional bias were associated with behavioral and affective attitudes toward ethnic Chinese during COVID-19. Structural Equation Modeling analyses indicate that social media intergroup expression valence and direct contact quality play a critical role in improving intergroup attitudes toward ethnic Chinese directly, and indirectly through building empathy and/or reducing anxiety. In addition, analyses demonstrate the negative role of social media intergroup expression frequency, which had: (1) a direct negative effect on behavioral attitudes and (2) an indirect negative effect on both attitudinal measures through increased anxiety and decreased empathy. Lastly, perceptions of institutional bias were negatively associated with affective attitudes through increased intergroup anxiety. Overall, findings reveal the dynamic interplay of the intergroup processes between social media intergroup expression, intergroup contact, and perceptions of institutional bias in shaping intergroup anxiety, empathy, and attitudes during COVID-19. [ABSTRACT FROM AUTHOR]

Mongolia’s substantial mineral resources have played a pivotal role in its economic progress, with mining activities significantly contributing to this development. However, these continuous mining operations, particularly at the Oyu Tolgoi copper and gold mine, have induced land subsidence that threatens both production activities and poses risks of geological and other natural disasters. This study employs the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to monitor and analyze time-series surface subsidence using 120 Sentinel-1A datasets from 2018 to 2022. The findings reveal that the SBAS-InSAR method successfully captures the subsidence and its spatial distribution at Oyu Tolgoi, with the maximum cumulative subsidence reaching −742.01 mm and the highest annual average subsidence rate at −158.11 mm/year. Key drivers identified for the subsidence include variations in groundwater levels, active mining operations, and changes in surface stress. This research underscores the ongoing subsidence issue at the Oyu Tolgoi mining area, providing crucial insights that could aid in enhancing mining safety and environmental conservation in the region.