1. 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.
2. 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.
3. 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.
4. 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.
5. 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
6. 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
7. 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.
8. 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.
9. 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.
10. 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[J]. Science of the Total Environment, 2021, 144609.