Analysis of hotspots of urban eco-environmental problems: A case study of Shenzhen City

Abstract

Urban eco-environmental management is a key focus in the modernization of national governance systems and governance capacity. Advanced information technology should be used to identify ecological problems in urban areas accurately while enhancing the environmental management capacity to promote the sustainable development of cities. This study centers on statistical data from PM_2.5 air monitoring stations in Shenzhen, China, and supplemental data, such as population distribution data from China Unicom’s mobile phone signaling. Data cleaning and fusion are used to construct a spatial dataset of an eco-environmental problem: PM_2.5 concentrations. The geostatistical analysis tool ArcGIS is used to identify the most suitable interpolation method for reflecting this eco-environmental problem based on multiple parameter adjustments and repeated testing. A hotspot distribution map of PM_2.5 concentrations is generated, and correlation analysis is conducted on the population density and distribution patterns in these hotspot areas. This enables the quantitative analysis and exploration of the spatial characteristics and coupling relationships of PM_2.5 concentrations. The results show a positive correlation between the PM_2.5 concentration distribution and the points of interest, road network density, number of dead-end roads, and average building height in Shenzhen. No correlation is found between population and building densities and the PM_2.5 concentration distribution, possibly due to the city’s effective environmental management and pollution control measures. These findings help advance the development of precise, scientific, legally compliant pollution control strategies and decision-making processes. Furthermore, they provide technical support for urban eco-environmental planning, management, and sustainable development.