1.空气污染暴露对生育健康的影响（研究领域：流行病学）；

2.环境政策的健康效应推断（研究领域：因果推断统计）；

3.基于多源数据的不良环境暴露及健康风险评估（研究领域：空间统计、机器学习、疾病负担评估）。

1.国家自然科学基金青年项目，41701591，基于风险评价识别我国空气污染健康损伤的高危人群，2018/01-2018/12，8万元，主持

2.公司百度基金，2020BD031，多源数据深度学习驱动的高分辨疾病负担空间分布研究，2021.1-2022.12, 30万，主持，在研

3.国家自然科学基金面上项目，4217050142，基于多源数据融合，评估我国细颗粒物、臭氧和温度的相关关系及其协同健康风险，2022.1-2025.12，55万，主持，在研

1.  Li J#, Guan T#, Guo Q#, Geng G, Wang H, Guo F, Li J, Xue T*. Exposure to landscape fire smoke reduced birthweight in low-and middle-income countries: findings from a siblings-matched case-control study. eLife. 2021 Sep 29;10:e69298.

2. Xue T*,#, Geng G#, Han Y, Wang H, Li J, Li H, Zhou Y, Zhu T*. Open fire exposure increases the risk of pregnancy loss in South Asia. Nature Communications 2021; 20: 37676. 10.1038/s41467-021-23529-7.

3. Xue T#,*, Geng G#, Li J#, et al, Zhu T*. Associations Between Exposure to Landscape Fire Smoke and Child Mortality in Low- and Middle-Income Countries: a matched case-control study. The Lancet Planetary Health, 5(9), e588-e598.

4. Xue, T., Guan, T., Geng, G., Zhang, Q., Zhao, Y. and Zhu, T.*, 2021. Estimation of pregnancy losses attributable to exposure to ambient fine particles in south Asia: an epidemiological case-control study. The Lancet Planetary Health, 5(1), pp.e15-e24.

5. Xue, T., Zhu, T.*, Geng, G. and Zhang, Q., 2019. Association between pregnancy loss and ambient PM2· 5 using survey data in Africa: a longitudinal case-control study, 1998–2016. The Lancet Planetary Health, 3(5), pp.e219-ee225.

6. Xue T*, Guan T, Zheng Y, Geng G, Zhang Q, Yao Y and Zhu T*. Long-term PM2.5 exposure and depressive symptoms in China: a quasi-experimental study. The Lancet Regional Health - Western Pacific 2021, 6: 100079.

7. Xue T*, Zhu T*, Peng W, Guan T, Zhang S, Zheng Y, Geng G, Zhang Q. Clean air actions in China, PM2.5 exposure and household medical expenditures: A quasi-experimental study. PLoS Medicine 2021, 18(1), p.e1003480.

8. Xue T, Zhu T*, Zheng Y, Zhang Q. Declines in mental health associated with air pollution and temperature variability in China. Nature Communications 2019; 10, 2165.

9. Xue T, Zheng Y, Tong D, Zheng B, Li X, Zhu T, Zhang Q*. Spatiotemporal continuous estimates of PM2.5 concentrations in China, 2000-2016: a machine learning method with inputs from satellites, chemical transport model, and ground observations. Environment International 2019; 123: 345–357. (ESI高被引)

10. Xue T, Liu J, Zhang Q*, Geng G, Zheng Y, Dan T, Liu Z, Guan D, Bo Y, Zhu T, He K, Hao J, Rapid improvement of PM2.5 pollution and associated health benefits in China during 2013–2017. SCIENCE CHINA Earth Sciences 2019. 62(12), 1847-1856. (ESI高被引)