DOI: 10.1016/j.atmosres.2018.02.015
Scopus记录号: 2-s2.0-85044338380
论文题名: Integration of optical and chemical parameters to improve the particulate matter characterization
作者: Perrone M.R. ; Romano S. ; Genga A. ; Paladini F.
刊名: Atmospheric Research
ISSN: 1698095
出版年: 2018
卷: 205 起始页码: 93
结束页码: 106
语种: 英语
英文关键词: Mass scattering cross section
; Particle optical properties
; PM chemical speciation
; Primary and secondary OC
; Ångström coefficient
Scopus关键词: Aerosols
; Carbon
; Chlorine
; Copper
; Magnesium
; Manganese
; Nephelometers
; Optical properties
; Organic carbon
; Titanium
; Aerosol optical property
; Elemental and organic carbons
; Frequency distributions
; Mass scattering
; Particle optical properties
; Primary and secondary OC
; Scattering co-efficient
; Transformation mechanisms
; Chemical speciation
; aerosol composition
; aerosol property
; cross section
; elemental carbon
; optical property
; organic carbon
; particulate matter
; speciation (chemistry)
; Italy
英文摘要: Integrating nephelometer measurements have been combined with co-located in space and time PM10 and PM1 mass concentration measurements to highlight the benefits of integrating aerosol optical properties with the chemical speciation of PM1 and PM10 samples. Inorganic ions (SO4 2−, NO3 −, NH4 +, Cl−, Na+, K+, Mg2+, and Ca2+), metals (Fe, Al, Zn, Ti, Cu, V, Mn, and Cr), and the elemental and organic carbon (EC and OC, respectively) have been monitored to characterize the chemical composition of PM1 and PM10 samples, respectively. The scattering coefficient (σp) at 450 nm, the scattering Ångström coefficient (Å) calculated at the 450–635 nm wavelength pair, and the scattering Ångström coefficient difference (∆Å) retrieved from nephelometer measurements have been used to characterize the optical properties of the particles at the surface. The frequency distribution of the Å daily means during the one-year monitoring campaign, performed at a southeastern Italian site, has allowed identifying three main Å variability ranges: Å ≤ 0.8, 0.8 < Å ≤ 1.2, and Å > 1.2. We found that σp and ∆Å mean values and the mean chemical composition of the PM1 and PM10 samples varied with the Å variability range. σp and ∆Å reached the highest (149 Mm−1) and the smallest (0.16) mean value, respectively, on the days characterized by Å > 1.2. EC, SO4 2−, and NH4 + mean mass percentages also reached the highest mean value on the Å > 1.2 days, representing on average 8.4, 9.8, and 4.2%, respectively, of the sampled PM10 mass and 12.4, 10.6, and 7.7%, respectively, of the PM1 mass. Conversely, σp and ∆Å mean values were equal to 85 Mm−1 and 0.55, respectively, on the days characterized by Å ≤ 0.8 and the EC, SO4 2−, and NH4 + mean mass percentages reached smaller values on the Å ≤ 0.8 days, representing 4.5, 6.0, and 1.9% of the PM10 mass and 9.4, 7.3, and 5.8% of the PM1 mass, respectively. Primary and secondary OC (POC and SOC, respectively) contributions also varied with the Å variability range. POC and SOC mean mass percentages reached the highest and the smallest value, respectively, on the days characterized by Å > 1.2. Conversely, POC and SOC mean mass percentages reached the smallest and the highest value, respectively, on the days characterized by Å ≤ 0.8. It has also been shown that the PM, OC, OC + EC, POC, and SOC mass scattering cross sections varied significantly with the Å variability range, because of the Å dependence on aerosol sources and/or emission, transport, and transformation mechanisms. Therefore, it has been shown that Å daily mean values can represent a good tool to better differentiate the chemical speciation of size-fractioned PM samples. © 2018 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/108923
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: Dipartimento di Matematica e Fisica, Università del Salento, Lecce, 73100, Italy; Dipartimento di Scienze e Tecnologie Biologiche e Ambientali, Università del Salento, Lecce, 73100, Italy
Recommended Citation:
Perrone M.R.,Romano S.,Genga A.,et al. Integration of optical and chemical parameters to improve the particulate matter characterization[J]. Atmospheric Research,2018-01-01,205