Analysis of Nitrogen Dioxide Concentration at Highway Toll Stations Based on fsQCA—Data Sourced from Sentinel-5P

Abstract

The Fuzzy-Set Qualitative Comparative Analysis (fsQCA) method is employed in this study to investigate the combined effects of region area, the number of COVID-19 infections, and the number of family cars on NO2 concentration at key highway toll stations in Zhejiang Province, China. By selecting and comparing typical cases, the analysis reveals differentiated characteristics in how various factor combinations influence NO2 concentration. The main findings are as follows: Under COVID-19 lockdown measures, prolonged vehicle waiting times and a shift towards family car usage among the public have led to a significant increase in NO2 concentration at highway toll stations. Promoting the Electronic Toll Collection (ETC) system and encouraging public transportation are of great importance. The synergistic effects of COVID-19 lockdown policies and urban land area, resulting in the reduction in the number of family cars and the excellent air circulation conditions in large cities, have contributed to the decrease in NO2 concentration at highway toll stations. Increasing urban green spaces and promoting clean energy vehicles are crucial for advancing urban sustainable development. The combined analysis of the region area and the number of family cars indicates that a higher proportion of large vehicles contributes to improving transportation efficiency, but also results in elevated NO2 concentration at highway toll stations due to diesel emissions. Optimizing the transportation structure and reducing reliance on large vehicles are of significant importance.