Can we simplify air quality mapping? This research introduces a statistical model that estimates daily nitrogen dioxide concentrations over large areas at a fine spatial scale. Designed to be easily adaptable to different regions, this model offers a simpler alternative to complex dispersion models, which require regular updating and significant computation time. This study examines the relationship between daily and annual nitrogen dioxide values, revealing a dependence on the range of daily values. The model’s performance is compared with standard geostatistical methods such as external drift kriging using cross-validation over one year. The reduced computation time means that daily maps can be produced for use by French air quality observatories. The model’s reduced computation time and adaptability make it a practical tool for air quality observatories, enabling the timely creation of daily maps. This facilitates informed decision-making and effective strategies for managing and improving air quality in urban and rural environments.
This paper in Air Quality, Atmosphere & Health fits perfectly with the journal’s emphasis on environmental science and technology related to air quality. The spatial model provides a valuable tool for estimating daily nitrogen dioxide concentrations. Its comparison with standard methods underscores the journal’s commitment to advancing methodologies for monitoring and managing air pollution and its associated health impacts.