title: Estimation of aerosol mass scattering efficiencies under high mass loading: case study for the megacity of Shanghai, China.
abstract: Aerosol mass scattering efficiency (MSE), used for the scattering coefficient apportionment of aerosol species, is often studied under the condition of low aerosol mass loading in developed countries. Severe pollution episodes with high particle concentration frequently happened in eastern urban China in recent years. Based on synchronous measurement of aerosol physical, chemical, and optical properties at the megacity of Shanghai for two months during autumn 2012, we studied MSE characteristics at high aerosol mass loading. Their relationships with mass concentrations and size distributions were examined. It was found that MSE values from the original US IMPROVE algorithm could not represent the actual aerosol characteristics in eastern China. It results in an underestimation of the measured ambient scattering coefficient by 36%. MSE values in Shanghai were estimated to be 3.5 ± 0.55 m(2)/g for ammonia sulfate, 4.3 ± 0.63 m(2)/g for ammonia nitrate, and 4.5 ± 0.73 m(2)/g for organic matter, respectively. MSEs for three components increased rapidly with increasing mass concentration in low aerosol mass loading, then kept at a stable level after a threshold mass concentration of 12–24 μg/m(3). During severe pollution episodes, particle growth from an initial peak diameter of 200–300 nm to a peak diameter of 500–600 nm accounts for the rapid increase in MSEs at high aerosol mass loading, that is, particle diameter becomes closer to the wavelength of visible lights. This study provides insights of aerosol scattering properties at high aerosol concentrations and implies the necessity of MSE localization for extinction apportionment, especially for the polluted regions.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Cheng
authors.forename: Jingkun
authors.initials: J
authors.lastname: Jiang
authors.forename: Changhong
authors.initials: C
authors.lastname: Chen
authors.forename: Jian
authors.initials: J
authors.lastname: Gao
authors.forename: Shuxiao
authors.initials: S
authors.lastname: Wang
authors.forename: John G
authors.initials: JG
authors.lastname: Watson
authors.forename: Hongli
authors.initials: H
authors.lastname: Wang
authors.forename: Jianguo
authors.initials: J
authors.lastname: Deng
authors.forename: Buying
authors.initials: B
authors.lastname: Wang
authors.forename: Min
authors.initials: M
authors.lastname: Zhou
authors.forename: Judith C
authors.initials: JC
authors.lastname: Chow
authors.forename: Marc L
authors.initials: ML
authors.lastname: Pitchford
authors.forename: Jiming
authors.initials: J
authors.lastname: Hao
mesh_terms: D000336:Aerosols / Q000032:analysis*; D000393:Air Pollutants / Q000032:analysis*; D000465:Algorithms; D002681:China; D002947:Cities; D004784:Environmental Monitoring / Q000379:methods*; D009566:Nitrates / Q000032:analysis; D010316:Particle Size; D012044:Regression Analysis; D012621:Seasons
chemical_list: D000336:Aerosols; D000393:Air Pollutants; D009566:Nitrates