Improving our understanding of the AMS quantification uncertainty: Reanalysis of aircraft data sets

Transcription

1 Improving our understanding of the AMS quantification uncertainty: Reanalysis of aircraft data sets Presented By Hongyu Guo Pedro Campuzano-Jost, Benjamin A. Nault, Douglas A. Day, Jose L. Jimenez University of Colorado-Boulder AMS User Meeting St Louis, MO Sept 9 th,

2 Motivation Google Scholar search key word Aerosol mass spectrometer Aerodyne AMS deployed extensively for quantifying non-refractory submicron aerosols. What are our propagated accuracies? Much larger uncertainties (than the left)? C s = 1012 CE s MW NO3 RIE s IE NO3 QN A alli I s,i IE s = RIE s MW s IE NO3 MW NO3 Estimated input accuracies (2σ): IE NO3 ~ 10% RIE NH4 ~ 10%, RIE SO4 ~ 15% RIE OA 20% (means ) CE: 30% (after applying CDCE) Q: ~ 1% Results σ NO3 = σ NH4 ~ 33%; σ SO4 ~ 35% σ OA ~ 37% Note that precisions are often far better Papers often state 15-20% without justification Bahreini et al., 2009 Murphy, 2016(1) Jimenez et al., 2016 Murphy, 2016(2) Larger uncertainty in AMS OA (2x 3x). Such large errors not observed AMS consistent within the stated uncertainty Clarify that the large error not expected Goal: To do the most critical evaluation on AMS characterization and to improve AMS quantification 2

3 Rich aircraft data sets Previous 12 aircraft studies with AMS (from Jimenez group) Highlights: Large variabilities in sources, compositions, acidities, liquid water contents, mixing states, size distributions, and optical properties High care and attention to calibration and quality control. High-time-resolution data. 3

4 Work flow Instruments SAGA Filters SAGA MC-IC PILS-IC PALMS etc. Key Inter- Comparisions Aerosol Composition Data Treatment Time-degradation (IC) External Mixtures? Products RIE SO4 RIE NH4 CE Probed Dependencies Acidity UHSAS LAS SMPS etc. Physical (size) Transmission Correction Count Saturation CE*RIE OA RH/LWC NO 3 Fraction Nephelometer CRD etc. Optical OA Fraction Neph(dry&wet) U-UHSAS DASH-SP etc. Hygrosco picity f(rh) => κ Fresh BB? RIE OA OA Type 4

5 Discussion-Sulfate closure SAGA filter (PM 4 ) vs AMS (PM 1 ) Aerosol Composition Time-degradation (IC) External Mixtures? DC3 (all) WINTER (excluding RF13) RF13 5

6 Sulfate closure-mc smearing? Aerosol Composition Time-degradation (IC) External Mixtures? Atom-2 RF208 data SAGA-MC vs AMS Slope = 1.10, r 2 = 0.73 Slope = 1.00, r 2 =

7 Sulfate closure-mc smearing? Aerosol Composition Time-degradation (IC) External Mixtures? Atom-2 RF208 data MC-IC smearing effect (nonzero recovery time). SAGA-MC agrees with AMS (original) sulfate. Better agreements with simulated AMS data (based on ~ 60 min exponential decay). 7

8 Sulfate closure-dependencies? CE based on Middlebrook et al., 2012 ph from Nault et al., in prep Aerosol Composition Time-degradation (IC) External Mixtures? ATom-2 RF208 data No significant dependencies on CE, ph, and RH. (within uncertainty) 8

9 Sulfate closure-rie SO4 Nault et al., 2018 Entire KORUS-AQ data Aerosol Composition Time-degradation (IC) External Mixtures? Consistent RIE SO4 and RIE NH4 for a range of nitrate fraction. (by varying mixtures of NH 4 NO 3 and (NH 4 ) 2 SO 4 in lab) KORUS-AQ RIE SO4 uncertainty as low as 5%. 9

10 Sulfate closure-rie SO4 Aerosol Composition Time-degradation (IC) External Mixtures? Nault et al., 2018 Entire KORUS-AQ data 1:1 10

11 Work flow Key Inter- Comparisions Data Treatment Products Aerosol Composition Time-degradation (IC) External Mixtures? RIE SO4 RIE NH4 CE Physical (size) Transmission Correction Count Saturation CE*RIE OA Optical Hygrosco picity f(rh) => κ Fresh BB? RIE OA 11

12 Discussion-Volume closure Corrections: 1. AMS transmission 2. refractive index: PSL vs ambient aerosol Particle sizers range o UHSAS: 63 nm 1 µm Kupc et al., 2018 Physical (size) Knote et al., 2011 Transmission Correction Count Saturation ATOM3 RF304 data Good agreements on PM 1 volumes. 12

13 Discussion-Volume closure (ultrafine?) Physical (size) Particle sizers range o UHSAS: 63 nm 1 µm o NMASS: 3 60 nm Transmission Correction Count Saturation ATOM3 RF311 data Kupc et al., 2018 Williamson et al.,

14 Discussion-Volume closure Middlebrook et al., 2012 Physical (size) Transmission Correction Count Saturation ATOM2 RF208 data Good agreements between (AMS + BC) and UHSAS PM 1 volumes. No significant dependencies on CE and RH. 14

15 Discussion-Volume closure (Count saturation) Nault et al., 2018 KORUS-AQ data Physical (size) Transmission Correction Count Saturation (AMS + BC) generally agrees with LAS volumes Count saturation of LAS (at high particle number/mass concentrations) 15

16 Work flow Key Inter- Comparisions Data Treatment Products Aerosol Composition Time-degradation (IC) External Mixtures? RIE SO4 RIE NH4 CE Physical (size) Transmission Correction Count Saturation CE*RIE OA Optical Hygrosco picity f(rh) => κ Fresh BB? RIE OA 16

17 Discussion-Extinction closure In-situ dry submicron scattering/extinction measurements low uncertainty (5%) If refractive index and size distribution relatively constant, scattering mass Optical >PM1 present? Nault et al., 2018 Assuming a constant n of 1.55 Entire KORUS-AQ data Mass scattering/extinction efficiency Typically 4-8 Mm-1/(µg sm-3) at 532 nm ρ = 1.64 g cm-3 (AMS) 6.41 Mm-1/(µg sm-3) MSE 17 Mie Code available at

18 Work flow Key Inter- Comparisions Data Treatment Products Aerosol Composition Time-degradation (IC) External Mixtures? RIE SO4 RIE NH4 CE Physical (size) Transmission Correction Count Saturation CE*RIE OA Optical Hygrosco picity f(rh) => κ Fresh BB? RIE OA 18

19 Discussion-hygroscopicity closure Hygroscopicity of inorganic salts (AS, AN) are well characterized. κ OA ~ Cerully et al., 2015 Hygrosco picity f(rh) => κ Fresh BB? Closure: κ = ε OA κ OA + ε AS κ AS + ε AN κ AN + κ OA = κ ε ASκ AS ε AN κ AN ε OA Jimenez et al.,

20 Future work: Look into details of the 12 aircraft campaigns Questions? 20