摘要
选取2011—2021年陕西省10个城市的面板数据,运用“压力-状态-响应”(pressure-state-response, PSR)模型、耦合协调度模型、空间关联特征来探讨影响城市化与大气环境安全的主要制约因素,并为陕西省城市化与生态环境共同发展提供科学建议。研究表明,陕西省各地级市城市化发展水平整体呈现上升趋势,大气环境质量综合指数波动较大,总体上有下降的趋势。陕西省近10年间城市化与大气环境发展协调程度总体上处于上升趋势。其中,西安市在城市化与大气环境水平的发展上协调度较高,商洛市、汉中市等耦合协调度较低。并且发现各城市大气环境质量与城市化发展耦合协调度都具有正向的空间依赖性。因此,陕西省在制定城市发展策略的过程中应考虑优化产业结构、节能发展、发挥西安市的空间溢出性等手段,实现陕西省各城市之间的和谐、可持续发展。
Based on the panel data of 10 cities in Shaanxi Province from 2011 to 2021,PSR model,coupling coordination model,and spatial correlation characteristics were used to explore the main constraints affecting urbanization and atmospheric environment security and provide scientific suggestions for the common development of urbanization and ecological environment in Shaanxi Province.The result shows that the overall level of urbanization development in various cities in Shaanxi Province is on the rise,and the comprehensive index of atmospheric environmental quality fluctuates greatly,showing a downward trend overall.The overall coordination between urbanization and atmospheric environment development in Shaanxi Province has been on the rise in the past decade.Among them,Xi’an has a high level of coordination in the development of urbanization and atmospheric environment,while coupled coordination in cities such as Shangluo and Hanzhong is relatively low.And it is found that the coupling and coordination between atmospheric environmental quality and urbanization development in various cities have a positive spatial dependence.Therefore,in the process of formulating urban development strategies,Shaanxi Province should consider optimizing industrial structure,energy-saving development,and leveraging the spatial spillover of Xi’an City to achieve harmonious and sustainable development among cities in Shaanxi Province.
作者
仙岚岚
XIAN Lanlan(School of Statistics,Xi’an University of Finance and Economics,Xi’an 710100,China)
出处
《科技和产业》
2024年第18期70-75,共6页
Science Technology and Industry
关键词
城市化
大气环境
PSR模型
耦合协调度模型
空间相关性
urbanization
atmospheric environment
psr model
coupling coordination model
spatial correlation