2020年毕业于中国科学院大学环境经济与环境管理专业，获得理学博士学位；2011年毕业于法国奥弗涅第一大学可持续发展经济学专业，获得硕士学位；2008年毕业于巴黎第九大学可持续发展管理专业，获得硕士学位；2006年毕业于中国农业大学，获得学士学位。2012年至今在中国科学院城市环境研究所工作，2019-2021年期间于厦门市生态环境局挂职，2024-2025年期间于厦门市自然资源和规划局挂职。作为第二完成人，分别获得2016龙岩市科学技术进步一等奖、2017厦门市、2018福建省、2023宁波市、2024厦门市科学技术进步三等奖。第一发明人获得发明专利 3 项，软件著作权 2 项。近 五 年 以 第 一 作 者 或 通 讯 作 者 在 环 境 领域 顶 级 期 刊 Building and Environment, Journal of Environmental Management、Science of the Total Environment、Journal of Cleaner Production、Ecological Indicators 等发表的文章著作10余篇，出版著作《城市绿地生态服务功能提升的关键技术研》《城市受损生态空间修复保育及功能提升研究》《城市群生态安全保障关键技术研究与集成示范》。主持福建省引导性项目、人事局留学生择优资助项目、国家自然科学基金青年项目、厦门市自然科学基金，作为骨干参加社会科学基金重大项目、国家自然科学基金面上项目、十三五和十四五国家重点研发计划、中国科学院重点部署项目、院重点实验室跨组合作项目、福建省重大专项等项目。

城市可持续景观规划、城市绿色空间规划、城市空间结构管控技术、低碳城市规划、环境政策分析、森林生态修复与评估、森林碳汇技术

1. Abiot M, Ren Y*, Yilkal GM, Zuo* S, Zhu P. Spatial-temporal trends and driving mechanisms of land degradation sensitivity in the southern region of China[J]. Ecological Indicators, 2025, 175:113532.

2. Tian Y, Zuo* S, Ju J, Dai S, Ren Y, Dou P. Local carbon emission zone construction in the highly urbanized regions: Application of residential and transport CO2 emissions in Shanghai, China[J]. Building and Environment, 2023, 247: 111007.

3. Li M, Zuo* S, Su Y, et al. An Approach Integrating MultiSource Data with LandTrendr Algorithm for Refining Forest Recovery Detection[J]. Remote Sensing, 2023,15, 2667.

4. Shudi Zuo*, Shaoqing Dai, Jiaheng Ju, et al., The importance of the functional mixed entropy for the explanation of residential and transport CO2 emissions in the urban center of China[J]. Journal of Cleaner Production, 2022, 380: 134947

5. Abiot M, Zhang W, Zuo S*, Ren Y*, Han J*. A machine learning and geostatistical hybrid method to improve spatial prediction accuracy of soil potentially toxic elements [J]. Stochastic Environmental Research and Risk Assessment, 2022, https://doi.org/10.1007/s00477-022-02284-1.

6.  Abiot M, Zuo S*, Zhang W, Qiu Y, Ren Y*, Han J*. Optimal spatial sampling design for monitoring potentially toxic elements pollution on urban green space soil: A spatial simulated annealing and k-means integrated approach [J]. Science of the Total Environment, 2022, 802:149728.

7. Dou P, Zuo S*, Ren Y*, Rodriguez M, Dai S. Refined water security assessment for sustainable water management: A case study of 15 key cities in the Yangtze River Delta, China [J]. Journal of Environmental Management, 2021, 290:112588.

8. Qiu Y#, Zuo S*#, Yu Z, Zhan Y, Ren Y*. Discovering the effects of integrated green space air regulation on human health: a bibliometric and meta-analysis [J]. Ecological Indicators, 2021,132:108292.

9. Zuo S, Yang* L, Dou P, et al., The direct and interactive impacts of hydrological factors on bacillary dysentery across different geographical regions in central China, Science of The Total Environment[J]. 2021, 764: 144609. 

10. Duan C, Zuo S, Wu Z, et al., A review of research hotspots and trends in biogenic volatile organic compounds (BVOCs) emissions combining bibliometrics with evolution tree methods, Environmental Research Letters[J]. 2021,16:013003.

11. Zuo S*, Dai S, Ren Y*. More fragmentized urban form more CO2 emissions? A comprehensive relationship from the combination analysis across different scales [J]. Journal of Cleaner Production, 2019, https://doi.org/10.1016/j.jclepro.2019.118659

12. Zuo S, Dou P, Ren Y* . Mapping sources of atmospheric pollution: Integrating spatial and cluster bibliometrics [J]. Environmental Reviews, 2019, https://doi.org/10.1139/er-2018-0105

13. Zuo S, Dai S, Li Y, et al. Analysis of heavy metal sources in the soil of riverbanks across an urbanization gradient[J]. International journal of environmental research and public health, 2018, 15(10): 2175.

14. Zuo S, Dai S, Song X, et al. Determining the mechanisms that influence the surface temperature of urban forest canopies by combining remote sensing methods, ground observations, and spatial statistical models[J]. Remote Sensing, 2018, 10(11): 1814.

15. Dai S, Yin R, Zuo S*, et al. Investigating the uncertainties propagation analysis of CO2 emissions gridded maps at the urban scale: a case study of Jinjiang city, China[J]. Remote Sensing, 2020, doi: 10.3390/rs12233932.