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A Global-Scale Mineral Dust Equation
Xuan Liu1, Jay R Turner1, Jenny L Hand2
1Department of Energy, Environmental and Chemical Engineering Washington University in St. Louis St. Louis MO USA.
Abstract:
A robust method to estimate mineral dust mass in ambient particulate matter (PM) is essential, as the dust fraction cannot be directly measured but is needed to understand dust impacts on the environment and human health. In this study, a global-scale dust equation is developed that builds on the widely used Interagency Monitoring of Protected Visual Environments (IMPROVE) network's "soil" formula that is based on five measured elements (Al, Si, Ca, Fe, and Ti). We incorporate K, Mg, and Na into the equation using the mineral-to-aluminum (MAL) mass ratio of (K2O + MgO + Na2O)/Al2O3 and apply a correction factor (CF) to account for other missing compounds. We obtain region-specific MAL ratios and CFs by investigating the variation in dust composition across desert regions. To calculate reference dust mass for equation evaluation, we use total-mineral-mass (summing all oxides of crustal elements) and residual-mass (subtracting non-dust species from total PM) approaches. For desert dust in source regions, the normalized mean bias (NMB) of the global equation (within ±1%) is significantly smaller than the NMB of the IMPROVE equation (-6% to 10%). For PM2.5 with high dust content measured by the IMPROVE network, the global equation estimates dust mass well (NMB within ±5%) at most sites. For desert dust transported to non-source regions, the global equation still performs well (NMB within ±2%). The global equation can also represent paved road, unpaved road, and agricultural soil dust (NMB within ±5%). This global equation provides a promising approach for calculating dust mass based on elemental analysis of dust.
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