A Global-Scale Mineral Dust Equation

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 PM_2.5 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.

Keywords: desert dust; dust; dust equation; dust mass; mineral dust; mineral elements.

Figure 1

The mineral‐to‐aluminum (MAL) ratio of (K₂O + MgO + Na₂O)/Al₂O₃ in six dust source regions and the average global continental crust shown on a log scale. The dashed line indicates the median MAL ratio (0.62) in continental crust of four data sources. Each symbol represents a data record in Table 2.

Figure 2

Particle size effect on the mineral‐to‐aluminum ratio and CO₂ content of dust using a data set of surface soil from arid regions (Engelbrecht et al., 2016). Inset P‐values are the results of the paired‐sample Wilcoxon test.

Figure 3

The mineral‐to‐aluminum ratio of (K₂O + MgO + Na₂O)/Al₂O₃ at Interagency Monitoring of Protected Visual Environments (IMPROVE) sites using daily‐integrated dust‐dominated (SOIL > 50% of reconstructed fine mass) PM_2.5 speciation data in 2011–2018 from the U.S. IMPROVE network. Only the sites with ≥5 data points were used to ensure representativeness. The number of selected IMPROVE sites is 95. The dashed line indicates the dividing line (103.2°W) through the Big Bend National Park site.

Figure 4

The ratio of the dust mass calculated by the global equation and the Interagency Monitoring of Protected Visual Environments (IMPROVE) equation to the “total mineral mass” for desert dust in source regions and for the average global continental crust.

Figure 5

Comparison of the dust mass calculated by the global equation and the Interagency Monitoring of Protected Visual Environments (IMPROVE) equation with the “total mineral mass” using dust‐dominated (SOIL > 50% reconstructed fine mass) PM_2.5 data in 2011–2018 from the U.S. IMPROVE network. Inset statistics are the normalized mean bias (NMB), mean fractional bias (MFB), and normalized root mean square error (NRMSE) of using the two equations for the entire data set. N is the number of speciation profiles.

Figure 6

Normalized mean bias (NMB) for the dust mass calculated by (a and b) the global equation and (c and d) the Interagency Monitoring of Protected Visual Environments (IMPROVE) equation compared to (a and c) the “total mineral mass” and (b and d) the “residual mass” at IMPROVE sites using daily‐integrated dust‐dominated (SOIL > 50% of reconstructed fine mass) PM_2.5 speciation data in 2011–2018 from the U.S. IMPROVE network. Only the sites with ≥5 data points were used to ensure representativeness. The number of selected IMPROVE sites is 95.

Figure 7

Comparison of dust mass calculated by the global equation and the Interagency Monitoring of Protected Visual Environments (IMPROVE) equation with the “total mineral mass” (left) and the “residual mass” (right) for dust‐dominated PM₁₀ data (SOIL > 50% of reconstructed fine mass) measured at Montelibretti, Italy during an African dust event (20–30 June 2006). Data with Na/Al > 0.45 or K/Al > 0.5 are excluded to reduce the influence of non‐dust sources. Inset statistics are the normalized mean bias and mean fractional bias of using the two equations.

Figure 8

The ratio of the dust mass calculated by the global equation and the Interagency Monitoring of Protected Visual Environments (IMPROVE) equation to the “total mineral mass” (left) and the “residual mass” (right) for paved road, unpaved road, and agricultural soil dust using PM_2.5 and PM₁₀ data from the U.S. Environmental Protection Agency's SPECIATE database and collected literature data (Amato et al., ; Zhao et al., 2006). Ratios are presented on a log scale. Data points are jittered to avoid overlap. The number of asterisks indicates the significance level (**P < 0.01, ****P < 0.0001) of the difference between two groups using the paired‐sample Wilcoxon test.