Hunan Institute of Economic Geography, Hunan University of Finance and Economics, Changsha, 410205, China; Hunan Key Laboratory of Land Resources Evaluation and Utilization, Changsha, 410007, China; School of Engineering Management, Hunan University of Finance and Economics, Changsha, 410205, China.
Hunan Institute of Economic Geography, Hunan University of Finance and Economics, Changsha, 410205, China.
J Environ Manage. 2021 Apr 1;283:112000. doi: 10.1016/j.jenvman.2021.112000. Epub 2021 Jan 25.
Accurate understanding of the relationship between urban land morphology and the concentration of PM is essential for achieving high-quality development of urban agglomerations. Based on a mechanism framework of "Internal-External driving force", 19 Chinese urban agglomerations at different development levels were analysed using the geographically weighted regression model to evaluate the impacts of urban land morphology on PM concentrations in years 2000-2017. The results show: (1) The PM average concentrations of all 19 urban agglomerations continue to increase from 30 μg/m in 2000 to 52 μg/m in 2007 but decreased to 34 μg/m in 2017. The changes in PM concentrations vary for urban agglomerations at different development levels. Spatial differences in PM concentrations are significant, forming a pattern that decreases from the centre to the periphery regions; (2) The urban land morphology of the entire urban agglomeration areas has undergone significant changes. The fractal dimension index (from 4.150 to 2.731) and the compactness (from 0.647 to 0.635) showed a downward trend, while the shape indices (from 1.421 to 1.606) demonstrated an increasing trend. National-level urban agglomerations are more compact and more complex in shape, while more fragmented are regional and local urban agglomerations; (3) Different parameters of urban land morphology have varying effects on PM concentration varies and at different development levels of urban agglomerations. The combination of urban land morphology, socio-economic factors, and natural elements has a complex effect on PM concentrations. It can contribute to understanding the linkage between urban land morphology and PM, providing references for future studies.
准确理解城市土地形态与 PM 浓度之间的关系，对于实现城市群的高质量发展至关重要。基于“内外部驱动力”的机制框架，利用地理加权回归模型分析了 19 个处于不同发展水平的中国城市群，以评估城市土地形态对 2000-2017 年 PM 浓度的影响。结果表明：（1）19 个城市群的 PM 平均浓度均呈先增后降的趋势，从 2000 年的 30μg/m 增加到 2007 年的 52μg/m，2017 年又降低至 34μg/m。不同发展水平城市群的 PM 浓度变化不同，空间差异显著，呈现出由中心向边缘递减的格局；（2）城市群整体土地形态发生显著变化，分形维数指数（4.150 至 2.731）和紧凑度（0.647 至 0.635）呈下降趋势，形状指数（1.421 至 1.606）呈上升趋势，国家级城市群更为紧凑，形状更为复杂，而区域和地方城市群则更为破碎；（3）不同的城市土地形态参数对 PM 浓度的影响因城市群发展水平的不同而有所不同，城市土地形态、社会经济因素和自然要素的组合对 PM 浓度有复杂的影响。该研究有助于理解城市土地形态与 PM 之间的联系，为未来的研究提供参考。
