While the approach often shows reasonable results, there is also criticism towards the method. argue that, despite the extensive use of various meteorology correction methods in numerous studies, there remains significant uncertainty about their effectiveness in accounting for meteorological variability to accurately estimate counterfactual air quality and 40 identify the true effects of changes in anthropogenic emissions. They also point out that while many studies lean heavily on the predictive accuracy of their statistical models, their predictive performance does not necessarily equate to accurate estimations of counterfactual scenarios and causal impacts. They also argue that emission-driven trends without influence from meteorological variability cannot be derived from data, especially for geographical locations where meteorologically influenced environmental processes are the main drivers of, e.g., dust emissions. Further criticism is oriented towards the inability to use 45 the "corrected" model for extrapolation to scenarios that are not covered in the data , such as a new wind direction at the measurement station.