Reconstructed algorithm for scattering coefficient of ambient submicron particles.

Ambient submicron particles (PM1) exert significant impacts on visibility degradation during severe pollution episodes of urban China. The U.S. IMPROVE algorithms are widely used for assessing the extinction effect of atmospheric aerosols, but only suitable for fine particulate matter. A proper algorithm for PM1 extinction estimation is lacking and becomes urgent, especially after the online measurement of PM1 species is routine by aerosol mass spectrometers. Here we conducted three-month in-situ measurements to explore mass scattering efficiencies (MSE) of PM1 major species at a supersite of eastern China. Results indicated that MSEs of ammonium sulfate and nitrate increase quickly and then keep stable with the mass accumulation, while those of organic matter keep at ∼5.5 m2/g but with a large vibration in the whole mass range. The algorithm for reconstructing PM1 dry scattering coefficient was derived from the integral of the variation patterns for the three PM1 species. The algorithm was then validated and compared with other empirical algorithms through separate field measurements. Good correlations between the reconstructed and measured dry scattering coefficient were observed with R square higher than 0.9 and slope of 1.01-1.05, indicating that the reconstructed algorithm can predict the dry scattering coefficient well based on PM1 chemical composition measurements in urban China. Our study is expected to provide observed insights on the variation of MSE in the wide mass range especially in the high region, as well as accurate formulas for ambient PM1 dry scattering apportionment.