Abstract
Meteorological normalization is a key concept in studying anthropogenic effects on air pollutant concentrations and its temporal trends. While apparently successful in revealing anthropogenic effects and often used, there are downsides to the methods and limitations which should be taken into account when using it. This study examines the concept of meteorological normalization in the context of predicting air pollutant concentrations, particularly focusing on the method's theoretical background and implicit assumptions. We provide a rigorous analysis that outlines the conditions under which meteorological normalization can effectively estimate expected values of response variables, which are commonly time series of air pollutant concentrations such as PM$_{10}$ . Through our analysis, we identify critical assumptions, such as the independence of meteorological and non-meteorological variables, which can significantly impact the validity of the method's outcomes. We also explore potential failure modes of meteorological normalization when these assumptions are violated, offering practical examples and visualizations that highlight the limitations of this technique. Our findings suggest that while meteorological normalization can be a useful tool, careful consideration of its applicability is necessary to avoid misleading conclusions in air quality assessments.