Abstract

Dust heterogeneous chemistry plays an important role in the atmosphere and has significant effects on climate and the environment. However, the traditional modelling method treats heterogeneous chemistry as pseudo-first-order reactions, which retains significant uncertainties, hindering the accurate prediction of secondary inorganic aerosols. In contrast, the actual dust heterogeneous chemistry involves complex multiphase reactions, including partition between gas- and dust-phase, and reactions on the dust surface. In this study, we implement a photocatalytic mechanism into the GEOS-Chem model and apply it to investigate the impact on atmospheric chemistry during a dust storm over East Asia during April 9–14th, 2018.With the photocatalytic heterogeneous chemistry (PHO), model simulation better reproduces observed sulfate and nitrate concentrations than those with the traditional pseudo-first-order mechanism (TDT) or without any dust heterogeneous chemistry at all (BASE). As validated against observations, normalized mean bias (NMB) in PHO reduces substantially compared to TDT, from −61.65% and 103.38% to −2.19% and 6.83% at Nanjing and Shanghai, respectively. The model also accurately simulates gaseous precursors such as SO2 and NO2, as evidenced by a decline in NMB from 103.38% to 81.80%–6.83% and 6.64% at the two sites, respectively. Furthermore, our analysis indicates that the larger dry deposition velocity of dust-phase sulfate and higher sulfate concentrations simulated by PHO jointly lead to a significant increase in SO4 dry deposition flux, demonstrating that the dust heterogeneous chemical process facilitates the removal of aerosol pollutants during dust events. These findings reinforce the need for enhancing the representation of dust heterogeneous chemistry in atmospheric models, underlining the criticality of this factor in accurate predictive modelling and environmental impact studies.

Full Text
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