Urban landscape forms can be effective in reducing increasing PM_(2.5) concentrations due to urbanization in China,making it crucially important to accurately quantify the spatiotemporal impact of urban landscape form...Urban landscape forms can be effective in reducing increasing PM_(2.5) concentrations due to urbanization in China,making it crucially important to accurately quantify the spatiotemporal impact of urban landscape forms on PM_(2.5) variations.Three landscape indices and six control variables were selected to assess these impacts in 362 Chinese cities during different time scales from 2001 to 2020,using a spatiotemporal geographically weighted regression model,random forest models and partial dependence plots.The results show that there are spatiotemporal differences in the impacts of landscape indices on PM_(2.5).the proportion of urban green infrastructure(PLAND-UGI)and the fractal dimension of urban green infrastructure(FRACT-UGI)exacerbate PM_(2.5) concentrations in the northwest,the proportion of impervious surfaces(PLAND-Impervious)mitigates air pollution in northwest and southwest China,and shannon’s diversity index(SHDI)has seasonal differences in the northwest.PLAND-UGI is the landscape index with the largest contribution(30%)and interpretable range.The relationship between FRACT and PM_(2.5) was more complex than for other landscape indices.The results of this study contribute to a deeper understanding of the spatial and temporal differences in the impact of urban landscape patterns on PM_(2.5),contributing to clean urban development and sustainable development.展开更多
基金funded by the Natural Science Foundation of Hunan Province,China(2023JJ40443)the Outstanding Youth Project of Hunan Provincial Education Department(22B0088 and 22B0055)+1 种基金the Joint Fund for Regional Innovation and Development of the National Natural Science Foundation(U22A20570)the Science and Technology Innovation Program of Hunan Province(2022RC4027),China.
文摘Urban landscape forms can be effective in reducing increasing PM_(2.5) concentrations due to urbanization in China,making it crucially important to accurately quantify the spatiotemporal impact of urban landscape forms on PM_(2.5) variations.Three landscape indices and six control variables were selected to assess these impacts in 362 Chinese cities during different time scales from 2001 to 2020,using a spatiotemporal geographically weighted regression model,random forest models and partial dependence plots.The results show that there are spatiotemporal differences in the impacts of landscape indices on PM_(2.5).the proportion of urban green infrastructure(PLAND-UGI)and the fractal dimension of urban green infrastructure(FRACT-UGI)exacerbate PM_(2.5) concentrations in the northwest,the proportion of impervious surfaces(PLAND-Impervious)mitigates air pollution in northwest and southwest China,and shannon’s diversity index(SHDI)has seasonal differences in the northwest.PLAND-UGI is the landscape index with the largest contribution(30%)and interpretable range.The relationship between FRACT and PM_(2.5) was more complex than for other landscape indices.The results of this study contribute to a deeper understanding of the spatial and temporal differences in the impact of urban landscape patterns on PM_(2.5),contributing to clean urban development and sustainable development.
