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Considering that the complexity and dynamicity of CO2 emissions, the spatiotemporal distribution pattern of atmospheric CO2 and its drivers remain unclear. In this study, we used the Geographically Weighted Regression (GWR) method to analyze the comprehensive distribution of CO2 concentration in mainland China from 2015 to 2019. We considered the relationship between nine factors, including natural and human activities, and CO2 concentration. To clarify the correlation between CO2 concentration and drivers, we utilized Pearson’s correlation coefficient. Then, the GWR analysis revealed the spatial heterogeneity across provinces, which reflects the extent to which impact factors influence CO2 concentrations. Finally, we analysed CO2 concentration spatiotemporal variation characteristics and predicted future trends of CO2 concentration in 31 provinces in China. According to our research, GDP has a major impact on CO2 growth, while natural factors have a minor influence on CO2 concentration. Our study found significant regional differences in the effects of combined variables on CO2 concentrations, with monthly rotational patterns temporally and clustering of high growth rates spatially and CO2 concentration in mainland China will continue to steadily increase. The findings of this research are crucial for China’s future energy low-carbon transition and policy-making.

As a radiant light source within the dynamic range of most spacecraft payloads, the Moon provides an excellent reference for on-orbit radiometric calibration. This research hinges on the precise simulation of lunar spectral irradiances and Earth-based Moon observation geometry. The paper leverages the Hapke model to simulate the temporal changes in lunar spectral irradiances, utilizing datasets obtained from the Lunar Reconnaissance Orbiter Camera (LROC). The research also details the transformation process from the lunar geographic coordinate system to the instantaneous projection coordinate system, thereby delineating the necessary observational geometry. The insights offered by this study have the potential to enhance future in-orbit spacecraft calibration procedures, thereby boosting the fidelity of data gathered from satellite observations. [ABSTRACT FROM AUTHOR]

The distribution of atmospheric CO2 is not homogenous, primarily due to variations in the CO2 budgets of regional terrestrial ecosystems. To formulate a comprehensive strategy to combat the increasing global CO2 levels and associated warming, it is crucial to consider both the distribution of atmospheric CO2 and the CO2 budgets of ecosystems. This study focused on analyzing the relationship between regional atmospheric CO2 and CO2 budgets in China from 2010 to 2017. Initially, a robust estimation model of net ecosystem CO2 exchange was developed to calculate CO2 budgets using collected emission data. Subsequently, Pearson correlation, redundancy analysis, and geographically weighted regression techniques were employed to examine the link between atmospheric CO2 levels, CO2 budgets, and other meteorological factors at various spatial and temporal scales. The findings from the redundancy analysis and geographically weighted regression indicated that the atmospheric CO2 content of each province could not be solely determined by the regional CO2 budgets. However, a significant and positive correlation between atmospheric CO2 levels and CO2 budgets was observed in non-coastal provinces for a period of six months (R2 ranging from 0.46 to 0.83). Consequently, it is essential to promote a balance between CO2 emissions and the CO2 uptake capacity of regional ecosystems. This balance would minimize positive CO2 budgets and effectively mitigate the increase in atmospheric CO2 levels. [ABSTRACT FROM AUTHOR]