1.多维数据驱动的城市级碳排放反演与能源协同发展情景推演方法研究，国网四川省电力公司，2024-2026，主持

2.四川盆地多介质跨圈层大气污染与气候变化协同控制技术与应用示范，国家重点研发项目子课题，2024-2027，主持

3.成都市大气环境卫星遥感数据治理与融合项目，广州华慧智联科技有限公司，2024-2025，主持

4.大气污染防治科技工作(温室气体和大气污染物时空分布及协同分析)，四川省生态环境科学研究院，2024，主持

5.基于卫星遥感及机器学习融合算法的区域清单空间分配优化，院士工作站开放课题，2023，主持

6.碳卫星监测分析与展示-技术服务项目，国网四川省电力公司，2022，主持

7. 农田土壤属性数字化制图方法研究技术服务，浙江省农业科学院数字农业研究所，2022，主持

8.机器学习重构PM_2.5时空分布中的特征空间优化机制研究，国家自然科学基金面上项目，2021-2024，主持

9.碳数据汇集与数据治理-实施项目，国网四川省电力公司，2021，主持

10.基于多源城市大数据的空气质量全面域时空计算推断技术应用示范，四川省科技厅重点研发项目，2020-2021，主持

11.基于机器学习的预报结果订正研究工作，成都市重大科技应用示范项目课题，2020-2022，主持

12.基于大数据的宜宾市空气质量精细化管理，四川大学-宜宾市人民政府市校战略合作项目，2020，主持

13.空气污染物高分辨率时空分布模型与网格化监测数据特征识别研究，河北先河环保科技股份有限公司技术开发(合作)项目，2020，主持

14.生态环境大数据及遥感数据分析，成都大数据产业技术研究院有限公司合作项目，2020，主持

15.高新区重点区域“一区一策”精细化管控对策研究服务项目，成都高新技术产业开发区环境保护与城市综合管理执法局，2019，主持

16.基于大气传输背景的广安市颗粒物精准化预测项目，四川省生态环境科学研究院，2019，主持

17.灾区恢复力综合评价技术，国家重点研发计划子课题，2018-2021，主持

18.网格化空气质量管理研究，四川省青年人才项目，2018-2020，主持

19.大气污染数值模拟及防控对策研究，四川大学人才引进启动经费，2018-2020，主持

20.城市尺度的邻苯二甲酸酯环境过程模拟，国家自然科学基金青年项目，2017-2019，主持

【代表性论著】

1. Li, T.^#; Zheng, X.^#; Liu, X.; Zhang, H.; Grieneisen, M. L.; He, C.; Ji, M.; Zhan, Y.^*; Yang, F. Enhancing space-based tracking of fossil fuel CO₂ emissions via synergistic integration of OCO-2, OCO-3, and TROPOMI measurements. Environmental Science & Technology. 2025.

2. Zheng, X.^#; Meng, H.^#; Zhao, Z.; Liu, X.; Zhou, L.; Grieneisen, M. L.; Zhang, H.; Zhan, Y.^*; Yang, F. Deep transfer learning for spatiotemporal mapping of PM_2.5 nitrate across China: Addressing small data challenges in environmental machine learning. Journal of Hazardous Materials. 2025.

3. Tang, D.; Mi, T.; Zheng, X.; Yang, M.; Grieneisen, M. L.; Zhan, Y.^*; Yang, F. Harmonizing low-cost and regulatory air quality monitoring networks with interpretable semi-supervised learning: Reducing exposure misclassification in underrepresented communities. Journal of Hazardous Materials. 2025.

4. Tang, D.; Zhan, Y.^*; Yang, F. A review of machine learning for modeling air quality: Overlooked but important issues. Atmospheric Research. 2024.

5. Liu, X.; Pu, X.; Lu, C.; Zhang, H.; Li, T.; Grieneisen, M. L.; Li, J.; Ma, N.; Yan, C.; Zhan, Y.^* Yang, F., Interpretable regional meteorological feature extraction enhances deep learning for extended 120-h PM_2.5 forecasting. Journal of Cleaner Production. 2024.

6. Mi, T.; Tang, D.; Fu, J.; Zeng, W.; Grieneisen, M. L.; Zhou, Z.; Jia, F.; Yang, F.; Zhan, Y.^* Data augmentation for bias correction in mapping PM_2.5 based on satellite retrievals and ground observations. Geoscience Frontiers. 2024.

7. Meng, X.; Pang, K.; Zhan, Y.^*; Wang, M.^*; Li, W.; Wang, Y.; Zhang, J.; Xu, Y. Light-duty gasoline vehicle emission deterioration insights from large-scale inspection/maintenance data: The synergistic impact of usage characteristics. Environment International. 2024.

8. Li, W.^#; Li, Y.^#; Xu, W.; Chen, Z.; Gao, Y.; Liu, Z.; Li, Q.; Jiang, M.; Liu, H.; Luo, B.^*; Zhan, Y.^*; Dai, L.^* Maternal PM_2.5 exposure and hypospadias risk in Chinese offspring: Insights from a nationwide surveillance-based study. Journal of Hazardous Materials. 2024.

9. Zhao, Z.; Lu, Y.; Zhan, Y.^*; Cheng,Y.; Yang, F.; Brook, J. R.; He, K. Long-term spatiotemporal variations in surface NO₂ for Beijing reconstructed from surface data and satellite retrievals. Science of the Total Environment. 2023.

10. Fu, J.; Tang, D.; Grieneisen, M. L.; Yang, F.; Yang, J.; Wu, G.; Wang, C.; Zhan, Y.^* A machine learning-based approach for fusing measurements from standard sites, low-cost sensors, and satellite retrievals: Application to NO₂ pollution hotspot identification. Atmospheric Environment. 2023.

11. 陈玉敏; 魏阳; 常政威; 张凌浩; 刘洪利; 刘雪原; 曾文; 赵子翔; 李春圆; 米潭; 詹宇. ^*基于遥感数据和XGBoost算法的31个城市NO2、CO2浓度比率变化特征. 地球科学与环境学报. 2023.

12. He, C.^#; Ji, M.^#; Li, T.; Liu, X.; Tang, D.; Zhang, S.; Luo, Y.; Grieneisen, M. L.; Zhou, Z.; Zhan, Y.^* Deriving full-coverage and fine-scale XCO₂ across China based on OCO-2 satellite retrievals and CarbonTracker output. Geophysical Research Letters. 2022.

13. Wu, Y.; Di, B.; Luo, Y.; Grieneisen, M. L.; Zeng, W.; Zhang, S.; Deng, X.; Tang, Y.; Shi, G.; Yang, F.; Zhan, Y.^* A robust approach to deriving long-term daily surface NO₂ levels across China: Correction to substantial estimation bias in back-extrapolation. Environment International. 2021.

14. Zeng, W.^#; Zhao, H.^#; Liu, R.; Yan, W.; Qiu, Y.; Yang, F.; Shu, C.^*; Zhan, Y.^* Association between NO₂ cumulative exposure and influenza prevalence in mountainous regions: A case study from southwest China. Environmental Research. 2020.

15. Liu, D.; Di, B.; Luo, Y.; Deng, X.; Zhang, H.; Yang, F.; Grieneisen, M. L.; Zhan, Y.^* Estimating ground-level CO concentrations across China based on national monitoring network and MOPITT: Potentially overlooked CO hotspots in the Tibetan Plateau. Atmospheric Chemistry and Physics. 2019.

16. 汤宇磊; 杨复沫; 詹宇.^* 四川盆地PM_2.5与PM₁₀高分辨率时空分布与关联分析. 中国环境科学. 2019.

17. Zhan, Y.; Luo, Y.; Deng, X.; Zhang, K.; Zhang, M.; Grieneisen, M. L.; Di, B.^* Satellite-based estimates of daily NO₂ exposure in China using hybrid random forest and spatiotemporal kriging model. Environmental Science & Technology. 2018.

18. Zhan, Y.; Luo, Y.; Deng, X.; Grieneisen, M. L.; Zhang, M.; Di, B.^* Spatiotemporal prediction of daily ambient ozone levels across China using random forest for human exposure assessment. Environmental Pollution. 2018.

19. Zhan, Y.; Luo, Y.; Deng, X.; Chen, H.; Grieneisen, M. L.; Shen, X.; Zhu, L.^*; Zhang, M.^* Spatiotemporal prediction of continuous daily PM_2.5 concentrations across China using a spatially explicit machine learning algorithm. Atmospheric Environment. 2017.

20. Zhan, Y.; Sun, J.; Luo, Y.; Pan, L.; Deng, X.; Wei, Z.; Zhu, L.^* Estimating emissions and environmental fate of di-(2-ethylhexyl) phthalate in Yangtze River Delta, China: Application of inverse modeling. Environmental Science & Technology. 2016.