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代表性论著 1.Gao, B, Yang, J., Chen, Z*. et al. 2023. Geographical Convergent Cross Mapping (GCCM): Inferring causal associations from cross-sectional Earth System data. Nature Communications. 14, 5875.
2.Gao, B., Li, M., Wang, J., Chen, Z*. 2022. Temporally or spatially? Causation inference in Earth System Sciences. Science Bulletin 67, 232-235.
3.Chen,J., Lv, Q., Wu, S., Zeng, Y., Li, M., Chen,Z*., et al. 2023. An adapted hourly Himawari-8 fire product for China:principle, methodology and verification. Earth System Science Data. 15(5):1911-1931
4.Wang, Z., Li, R., Chen, Z*. et al. 2022. The estimation of hourly PM2.5 concentrations across China based on a Spatial and Temporal Weighted Continuous Deep Neural Network (STWC-DNN). ISPRS Journal of Photogrammetry and Remote Sensing 190(2):38-55
5.Chen, J., Yao, Q., Chen, Z*. et al. 2022. The Fengyun-3D (FY-3D) global active fire product: principle, methodology and validation. Earth System Science Data 14(8):3489-3508.
6.Chen, Z., Chen, D., Zhao, C., Kwan, M., Cai, J., Zhuang, Y., Zhao, B., Wang, X., Chen, B., Yang, J., Li, R., He, B., Gao, B., Wang, K., Xu, B. Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism. Environment International, 2020, 139: 105558.
7.Li, R., Xu, M., Li, M., Chen, Z.*, Zhao, N., Gao,B., Yao,Q.2021. Identifying the spatiotemporal variations in ozone formation regimes across China from 2005 to 2019 based on polynomial simulation and causality analysis. Atmospheric Chemistry and Physics. 21(20):15631-15646
8.Chen, Z., Chen, D., Kwan, M., Chen, B., Gao, B., Zhuang, Y., Li, R., Xu, B. 2019. The control of anthropogenic emissions contributed to 80% of the decrease in PM2.5 concentrations in Beijing from 2013 to 2017. Atmospheric Chemistry and Physics. 19，13519-13533.
9.Chen, Z. Chen, D., Wen, W., Zhuang, Y., Kwan, M., Chen, B, Zhao, B., Yang, L., Gao, B., Li, R., Xu, B. 2019. Evaluating the “2+26” Regional Strategy for Air Quality Improvement During Two Air Pollution Alerts in Beijing: variations of PM2.5 concentrations, source apportionment, and the relative contribution of local emission and regional transport. Atmospheric Chemistry and Physics. 19(10):6879-6891.
10.Chen, Z., Zhuang, Y., Xie, X.M., Chen, D.L., Cheng, N.L., Yang, L., Li, R. 2019. Understanding long-term variations of meteorological influences on ground ozone concentrations in Beijing During 2006–2016. Environmental Pollution. 245, 29-37.
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