Investigation of NR-PM1 Species and Effect on Visibility in Xi’an, China

• 作 者: Yichen Wang Junji Cao
• 机 构: State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academ
• 出 处: 第十一届全国气溶胶会议暨第十届海峡两岸气溶胶技术研讨会
• 发表日期: 2013年5期
• 关键词: ACSM NR_PM1 stable atmospheric condition formation visibility HOA OOA

　　With an Aerodyne Aerosol Chemical Speciation Monitor,we mainly focused on the variation of NR_PM1 species,its inorganic species formation and its effect on visibility impairment under a stable atmospheric condition (low wind speed period,from 1 September to 6 September,from 26 September to 1 October respectively).The NR_PM1 took up ~60% of PM2.5.Organic contributes the most (58% on average) to the NR_PM1 mass loading,other species make ~40% contributions.Through Principle component analysis,we found NH4 +,SO4 2- and NO3 - played a stably significant role on visibility impairment within different period of the day.With the IMPROVE equation,Light scattering from NR_PM1 was ~ 80% of that from PM2.5,illustrating the dominance of NR_PM1 in the light scattering process.Organics contributed the most to light scattering during this period whereas (NH4)2SO4 and NH4NO3 played more important role on the visibility variation than Org did.Overall,it is the combination of organics,(NH4)2SO4 and NH4NO3,not a single species that are responsible for the variation of visibility variation.Sulfate formation was dominated with gas phase reactions during daytime and droplet phase reactions at night.Nitrate particles,however,were not formed immediately after gas phase reactions in the afternoon.Two types of OA (HOA and OOA) were found in this study.The oxygenation level of organics was relatively high and photochemical reaction proceeded rapidly in the afternoon.BBOA(biomass burning organic aerosol) cannot be resolved though tracers of BBOA(m/z 60 and 73) have a prominent signal,illustrating the similar variation of time series between these two factors,which maybe resulted from the traditional energy consumption pattern in villages.