Dust Emission Modeling Using a New High‐Resolution Dust Source Function in WRF‐Chem With Implications for Air Quality

Abstract

Air-borne dust affects all aspects of human life. The sources of dust have high spatial variation and a better quantification of dust emission helps to identify remediation measures. Orographic and statistical source functions allow a better estimation of dust emission fluxes in coarse-scale modeling, but a high-resolution source function is necessary to represent the highly heterogeneous nature of dust sources at the finer scale. Here we use a newly developed high-resolution (~500 m) source function in Weather Research and Forecasting model, coupled with chemistry (WRF-Chem) to simulate dust emission over the Middle East and North Africa and evaluate our simulated results against observations. Using a 4-km grid spacing, we also simulate the emission and transport of dust originating from the Tigris-Euphrates basin, one of the most important regional dust sources, and quantify the effects of this source on the air quality of the entire Arabian Peninsula. Results show that the use of new source function effectively represents the key dust sources and provides reasonable estimates of dust optical depth and concentrations. We find that the atmospheric dust originating from the Tigris-Euphrates basin alone exceeds the particulate matter 10 air quality standards in several downwind cities. Our results have broader environmental implications and indicate that the mobilization of depleted uranium deposited in Kuwait and Southern Iraq during the Gulf War (1991) could potentially affect the urban centers over the peninsula, albeit in low concentrations. Our results suggest that an integrated and coordinated management of the Tigris-Euphrates basin is necessary to maintain good air quality across the Arabian Peninsula.

Modelling mineral dust emissions and atmospheric dispersion with MADE3 in EMAC v2.54

“…A similar modal aerosol (MESSy-)submodel which is comparable to MADE3 is GMXe (Global Modal-aerosol eXtension; Pringle et al, 2010). A major difference between the two aerosol models is that MADE3 distinguishes between purely soluble particles and particles containing insoluble material, with the intention to enable a more straightforward quantification of the number concentrations of ice-nucleating particles (Righi et al, 2020).…”

“…We use the Ångstrom exponent (AE; 870-440 nm) from AERONET measurements to select dust-dominated stations. An AE criterion is commonly used to extract the coarse-mode component from AOD data, which represents soil dust as the dominant coarse aerosol in desert regions (Ginoux et al, 2012;Eck et al, 1999;Parajuli et al, 2019). Stations with an AE of less than 0.75 (multiannual mean) and with more than 50 observation days are selected.…”

Mineral dust modelling with MADE3 in EMAC v2.54

“…We use the Ångstrom exponent (AE, 870-440 nm) from AERONET measurements to select dust-dominated stations. An AE criterion is commonly used to extract the coarse-mode component from AOD data, which represents soil dust as the dominant coarse aerosol in desert regions (Ginoux et al, 2012;Eck et al, 1999;Parajuli et al, 2019). Stations with AE less than 0.75 (multi-annual mean) and…”

“…This skill score is commonly used for model comparisons with observations (e.g. Klingmüller et al, 2018;Parajuli et al, 2019). For simplicity, we use R 0 = 1, as we are mainly interested in the relative changes of the skill score for different model simulations.…”

Study of SO Pollution in the Middle East Using MERRA‐2, CAMS Data Assimilation Products, and High‐Resolution WRF‐Chem Simulations

“…In this study we focus on the ME, which is one of the most polluted areas in the world. Because of extremely high levels of natural particulate pollution driven by dust aerosols (Jish Prakash et al, 2016;Kalenderski & Stenchikov, 2016;Parajuli et al, 2019;Tsiouri et al, 2015), the region experiences extreme pollution episodes, compounded by a strong contribution of anthropogenic aerosols and gases (Ahmed, 1990;Barkley et al, 2017;Karagulian et al, 2015;Lelieveld, Beirle, et al, 2015;Lelieveld et al, 2009;Ukhov et al, 2020). ME emits CAMS-OA uses anthropogenic emissions from the MACCity inventory (Granier et al, 2011) on a 0.5 • × 0.5 • grid built over the period 1960-2010 (see Figure 1a).…”