Full-coverage atmospheric CO2 reconstruction data in China from 2010 to 2019

This monthly atmospheric CO2 dataset was reconstructed from GOSAT XCO2 retrievals using a spatiotemporal kriging method. We employed this dataset to investiage the spatiotemporal variation in atmospheric CO2 and its influencing factors. Please the publication as below: --Chen, X., He, Q., Ye, T., Liang, Y., & Li, Y. (2023). Decoding spatiotemporal dynamics in atmospheric CO2 in Chinese cities: Insights from satellite remote sensing and geographically and temporally weighted regression analysis. Science of The Total Environment, 167917. We also share other atmopsheric reconstruction datasets: For full-coverage, 1-km, AOD data in China, please go to harvard dataverse. This dataset was imputed based on MODIS MAIAC 1-km AOD retrievals. For full-coverage, 1-km, CO2 data in China, please go to 10.5281/zenodo.10022904. This dataset was reconstructed based on OCO-2 XCO2 retrievals and machine learning algorithm. For full-covereage, 1-km, PM2.5 data in China, please go to 10.5281/zenodo.8437234 or 10.5281/zenodo.8347128.本月度大气CO₂数据集基于GOSAT XCO2反演产品，采用时空克里金（spatiotemporal kriging）方法重构得到。本数据集用于探究大气CO₂的时空变化特征及其影响因素。相关引用文献如下： --Chen, X., He, Q., Ye, T., Liang, Y. & Li, Y. (2023). 解码中国城市大气CO₂的时空动态：基于卫星遥感与地理时空加权回归分析的研究洞察. 《Science of The Total Environment》, 167917. 本团队同时共享其他大气重构数据集： 1. 中国全域1公里分辨率气溶胶光学厚度（AOD, Aerosol Optical Depth）数据：请访问哈佛数据文库（Harvard Dataverse）。该数据集基于MODIS MAIAC 1公里AOD反演产品插补得到。 2. 中国全域1公里分辨率CO₂数据：请访问10.5281/zenodo.10022904。该数据集基于OCO-2 XCO2反演产品与机器学习算法重构得到。 3. 中国全域1公里分辨率PM2.5数据：请访问10.5281/zenodo.8437234 或 10.5281/zenodo.8347128。