Optimization of Charging Station Siting Based on Land Use and Atmospheric Pollution

Optimizing the charging station layout is crucial to promoting the adoption of electric vehicles (EVs) and combating urban air pollution. The EV market in China is booming, and how to develop a reasonable charging station layout with limited resources has become a hot topic. To explore the current charging station deployment characteristics, a geographically weighted regression (GWR) method is applied to simulate the spatial heterogeneity and visualize how land use, transportation facilities, and environmental pollution affect the distribution of existing charging stations. To further characterize this process, three types of data, pollutant emission data, point‐of‐interest (POI) data, and road network data, were obtained from Tongzhou District, Beijing, China. Finally, the suitability of future charging station layout is assessed by integrating the charging demand and air pollution level. The study area is divided into five types of areas, and gradual improvement of charging stations in different types of areas are recommended. The results of this study not only enhance the market share of EVs, but also effectively guide travelers to switch to new energy vehicles, thus reducing traffic exhaust emissions and improving air quality.