孔亚文
性别：女
职称：助理研究员
邮箱：kongyw@aircas.ac.cn
地址：北京朝阳区大屯路甲20号北
孔亚文，中国科学院空天信息创新研究院助理研究员。主要从事大气环境数值模拟、大气成分遥感数据同化，多尺度碳源汇反演核算等领域的研究。研发了四维集合卡尔曼滤波与多个大气化学传输模式耦合的数据同化系统，应用于大气污染物源反演及碳源汇反演研究。研发的全球碳源汇反演产品被全球碳收支计划（Global Carbon Budget）评估认证和采纳。以第一作者在Atmospheric Chemistry and Physics、Atmospheric Research等期刊发表论文6篇。目前已担任过JGR: Atmospheres、Atmospheric Research、Geoscientific Model Development等期刊审稿人。
学习经历：
2016—2020 中国科学院大学 地图学与地理信息系统 博士
2013—2016 中国海洋大学 气象学 硕士
2009—2013 中国海洋大学 大气科学 学士
工作经历：
2024—至今 中国科学院空天信息创新研究院 助理研究员
2021—2024 清华大学地球系统科学系 博士后
大气成分遥感数据同化
（1）全球-中国区域碳通量自上而下反演研究，国家自然科学基金青年科学基金，项目负责人，2023.01—2025.12；
（2）东北亚异常反气旋影响下京津冀冬季PM2.5和O3复合污染关键因子研究，国家自然科学基金面上项目，合作单位负责人，2023.01—2026.12；
（3）碳中和与清洁空气协同治理路径及综合效应研究，国家自然科学基金重点项目，参与，2022.01—2026.12；
（4）大气污染源全组分谱库建立及排放清单编制，国家重点研发计划，参与，2022.10—2026.03。
1. Kong, Y., Zheng, B., and Liu, Y.: Tracking daily NOx emissions from an urban agglomeration based on TROPOMI NO2 and a local ensemble transform Kalman filter, Atmos. Chem. Phys., 2025.
2. Kong, Y., Zheng, B., Zhang, Q., and He, K.: Global and regional carbon budget for 2015–2020 inferred from OCO-2 based on an ensemble Kalman filter coupled with GEOS-Chem, Atmos. Chem. Phys., 22, 10769–10788
3. Kong Y., Sheng L., Li Y., et al. Improving PM2.5 forecast during haze episodes over China based on a coupled 4D-LETKF and WRF-Chem system. Atmospheric Research. 2020, 249: 105366.
4. Kong Y., Chen B., Measho S. Spatio-Temporal Consistency Evaluation of XCO2 Retrievals from GOSAT and OCO-2 Based on TCCON and Model Data for Joint Utilization in Carbon Cycle Research. Atmosphere. 2019, 10(7): 354.
5. Kong Y., Zhang X., Sheng L., et al. Validation and application of multi-source altimeter wave data in China’s offshore areas. Acta Oceanologica Sinica, 2016, 35(11): 86-96.
6. Lin, J., Dai, T., Sheng, L., Zhang, W., Hai, S., and Kong, Y.: Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy, Geosci. Model Dev.,2024.
7. Zheng, B., Ciais, P., Chevallier, F., Yang, H., Canadell, J. G., Chen, Y., van der Velde, I. R., Aben, I., Chuvieco, E., Davis, S. J., Deeter, M., Hong, C., Kong, Y., Li, H., Li, H., Lin, X., He, K., and Zhang, Q.: Record-high CO2 emissions from boreal fires in 2021, Science, 379,912-917, 2023.
8. Li. H., Zheng, B., Ciais, P., Boersma, K. F., Riess, T. C. V. W., Martin, R. V., Broquet, G., van der A, R., Li, H., Hong, C., Lei, Y., Kong, Y., Zhang, Q., and He, K.: Satellite reveals a steep decline in China’s CO2 emissions in early 2022, Science Advances, 9, eadg7429, 2023.
9. Lin, X.; Chen, B.; Zhang, H.; Wang, F.; Chen, J.; Guo, L.; Kong, Y. Effects of the Temporal Aggregation and Meteorological Conditions on the Parameter Robustness of OCO-2 SIF-Based and LUE-Based GPP Models for Croplands. Remote Sens. 2019, 11, 1328.
10. Guo, L.; Chen, B.; Zhang, H.; Xu, G.; Lu, L.; Lin, X.; Kong, Y.; Wang, F.; Li, Y. Improving PM2.5 Forecasting and Emission Estimation Based on the Bayesian Optimization Method and the Coupled FLEXPART-WRF Model. Atmosphere 2018, 9, 428.
11. Chu, Y., Sheng, L., Liu, Q., Zhao, D., Jia, N., & Kong, Y. Size distributions and source function of sea spray aerosol over the South China Sea. Journal of Ocean University of China, 2016, 15(4), 569-576.
