Dissimilar effects of two El Niño types on PM2.5 concentrations in East Asia

Abstract

We investigate the effects of natural variability of meteorological fields on surface PM_2.5 concentration changes in East Asia during El Niño periods for the past three decades (1980-2014) through GEOS-Chem 3D global chemical transport model simulations. First, our evaluation of the model with anthropogenic emissions for 2006 and a comparison against observations show that the simulated results accurately reproduced the observed spatial distribution of annual mean aerosol concentrations for 2006-2007 including inorganic (sulfate, ammonium, and nitrate) and carbonaceous (organic and black carbon) aerosols in the surface air. Based on the Oceanic Niño Index, the assimilated meteorological data used in the model simulations indicate that 10 El Niño events occurred for the past three decades (1980-2014). We further classified the 10 El Niño events into 6 central Pacific El Niño (C-type) and 4 eastern Pacific El Niño (E-type) to examine the different roles of two El Niño types in determining seasonal surface PM_2.5 concentrations in East Asia. We find opposite impacts on the seasonal surface PM_2.5 concentrations depending on two El Niño types, such that the surface PM_2.5 concentrations during the E-type period are higher than the climatological mean value, especially in northern East Asia. The peak increase of as much as 20% occurs in winter and is sustained until the following spring. However, the C-type period shows a decrease in seasonal PM_2.5 concentrations in northern East Asia compare to the climatological mean, and the peak decrease of as much as 10% occurs in the following spring. The different of two El Niño types also have dissimilar impacts on surface PM_2.5 concentrations in southeastern China. Natural variation of aerosol concentrations driven by the different of two El Niño types appears to be significant and would be an important factor in determining the inter-annual variation of aerosol concentrations in East Asia.

Keywords: Aerosol; Chemical transport model; El Niño.