There is a body of evidence on the risk to human health posed by the exposure to desert dust. However, results from epidemiological studies from different regions are inconsistent. Among possible causes of inconsistency is the scarcity of daily desert dust contributions to PM10 and PM2.5 levels recorded in populated areas in order to conduct rigorous epidemiological studies, but also the lack of robust and harmonized methodologies to deliver airborne desert-dust concentrations. This study evaluated the performance of the main statistical methods currently used by European countries to estimate the net load of desert dust on PM10 and PM2.5 levels during the occurrence of desert dust outbreaks. To this end, long-term data series (2010-2023) on PM10 and PM2.5 levels and composition obtained in a regional background (Montseny) and an urban background (Barcelona) monitoring site, in Northeast Spain, were used. The results identify the most appropriate method for determining the regional daily PM10 background concentration, excluding dust-days. This involves applying a moving 50th percentile with a 30-day time window to data from nearby regional background environments. Such PM10 background is essential for calculating the daily net dust contribution (PM10 net-dust). However, applying this procedure to data from urban or industrial environments causes an overestimation of PM10 net-dust values, which intensifies with higher local PM10 levels. On the other hand, in the case of low PM10 (net-dust) values(<3 mu g m(-3)) the relative errors are so high that it is not advisable to use these estimates of natural PM contributions to assess compliance with air quality standards. For PM2.5, however, the mineral dust content is much lower than for PM10. Consequently, applying the same methodology results in significantly greater relative errors in the PM2.5 net-dust estimates. In this case, it is also advisable to use PM2.5 data series obtained in regional background environments. However, if nearby regional background data is not available, the method can be applied directly to the evaluated urban or industrial datasets, but excluding traffic and industrial hotspots for the calculation of the PMnet-dust. In conclusion, accurately quantifying PMnet-dust is a complex issue, and it is necessary to continue improving current methods and developing new methods that allow for the most accurate estimation possible of daily desert dust contributions, especially for the low concentration ranges and for finer PM size fractions. The methodologies reported here are applicable to all regions affected by desert dust.