Optical Properties of Atmospheric Aerosols Russell Philbrick a,b and Hans Hallen a a Physics Department, b Marine Earth and Atmospheric Sciences Department NC State University, Raleigh NC 27695-8202 36th Review of Atmospheric Transmission Models (ATM) Conference 9-11 June 2015 at the Hotel Hyatt Dulles in Herndon, VA 1
Physical Processes Governing Transmission Through Aerosols (1) Aerosol Size Compared with Wavelength As size increases, the cross-section σ ~ r 6 for λ < r, and σ ~ r 2 for λ > r, where r is a spherical particle 500 nm 10 radius. The relative scattering cross-section at σ ∼ a 6 10 6 two wavelengths depends on (frequency ratio) 4 , i.e. ( ν 2 / ν 1 ) 4 , or ( λ 1 / λ 2 ) 4 . Scattering cross section of dielectric sphere: σ = 4 π [( ε - ε o )/ ε + 2 ε o )] 2 k 4 a 6 sin 2 θ Backscatter cross section: ARD σ back ∼ a 6 (2) Aerosol Shape Complicates Transmission Road/Agriculture/Desert Dust Scattering from water vapor and other liquid aerosols can be easily described and scattering phase functions are useful in describing the size distribution. Irregular shape aerosols require more complex analysis and some knowledge of 20 μm the typical size and composition to analyze. 2
Physical Processes Governing Transmission Through Aerosols (3) Aerosol Complex Index of Refraction Arizona Road Dust The chemical makeup of an aerosol strongly influences the transmission. The real k Unground component of the index governs the k Ground scattering and the imaginary component describes the absorption. An additional factor that can complicate the transmission calculation is the thickness of the material, which can hide part of the aerosol’s effect if the material is optically thick at a wavelength of interest. (4)The Spatial Distribution of Aerosols Describes Transmission The many ways that aerosols are generated results in complex patterns and residence time are influenced by wind, diffusion, 3 settling time, and chemical processes.
Raman Lidar Provides an Important Tool for Extinction Profiles Log Cross Section Rayleigh Scatter 532 nm 2ndH Nd:YAG Excited Electronic States Nitrogen 607 nm Water Vapor Rotational Raman , ∆ J Virtual Energy Levels 660 nm states, are distributed by the thermal energy and describe the local temperature. 500 550 600 650 Rotational Levels Wavelength (nm) J V=2 10 -30 λ = 532 nm J V=1 Vibration Energy Levels ∆ E Backscatter Cross-section (m 2 ) Elastic J V=0 10 -32 N 2 and O 2 Vibrational Raman transitions to Virtual Energy Rotation Lines level relaxes to a unique vibrational level of the Anti-Stokes Stokes molecule. Concentrations the major molecules 10 -34 in the atmosphere, N 2 , O 2 , H 2 O, O 3 , CO 2 , … , can be determined relative to N 2 using their Raman signal and laboratory measured cross-section. 10 -36 524 528 532 536 540 4 Wavelength (nm)
LAMP at Point Mugu CA Raman Lidar for Water Vapor and Temperature Envelopes of the Balloon Anti-Stokes 528.8 nm Sonde Rotational Lines 530.5 nm
Raman Lidar Optical Extinction Signal intensity (corrected for 1/z 2 ) will follow hydrostatic I = I 0 e - α z profile in a pure molecular atmosphere without scattering loss – the difference from that molecular profile gradient is extinction. α tot = α mol scat + α aer scat + α mol abs + α aer abs d N (z) α = − α − α − α aer mol mol aer R ln (z) (z) (z) R scat abs abs ⋅ 2 dz P (z) z R = d 1 N(z) α aer α mol ln - (z) . 532 ⋅ 532 2 dz 2 (z) z P 530 O - outgoing – 532, 355, or 266 nm R - return - 530 (rot), 607 (N 2 ), 285 (N 2 ) or 276 (O 2 ) nm 6
Extinction Profiles 09/17/97 04:00-04:59 PDT Hesperia, CA 6 Extinction at 284 nm 5.5 Extinction at 530 nm 5 Extinction at 607 nm 4.5 Altitude [km] 4 3.5 3 2.5 2 1.5 1 0.01 0.1 1 10 Extinction [1/km] The multi-wavelength lidar profiles show a larger number of smaller aerosol particles present over most of the height, but when a cloud is encountered near 4 km, all of the 7 wavelengths indicate the same extinction due to multiple scattering.
Extinction Profiles 09/17/97 04:00-04:59 PDT Hesperia, CA Time sequence and 6 Extinction at 284 nm integrated profiles of optical 5.5 Extinction at 530 nm 5 Extinction at 607 nm extinction – SCOS 97 4.5 Altitude [km] 4 3.5 3 The lidar data is typically gathered in 1-min 2.5 integrated profiles that are stacked side- 2 by-side and then a 5-min smoothing filter is 1.5 applied. 1 0.01 0.1 1 10 Extinction [1/km] 8
The Raman Lidar thus allows us to study the troposphere in the same way that we could by releasing an instrumented weather balloon every few minutes each day. A quick view of the next few slides show some of the important ways that Raman Lidar now contributes to our knowledge of the atmosphere. These examples include the following cases: (1-2) The night before a major air pollution event, we see a moist layer moving into the area and then being rapidly transported to the ground by encounter with the rising morning convective boundary layer. A back-trajectory calculation shows that it came from the Ohio Valley, and EPA measurements at the site show it contains the chemical, PAN, which is a power plant emission. The PAN quickly dissociates and forms smog aerosols as shown in the extinction plot. (3) The relation of PM2.5 and PM10 (EPA surface sensors) correlated to lidar extinction at 800 m (lidar measurement in the mixed PBL 24 hr). (4) A surface measurement shows the strong correlation of extinction with water vapor. (5-6) Opportunities to use Raman Lidar to study cloud micro-physics are shown. 9
8PM 2AM 8AM 8AM 8PM 8AM NARSTO-NE-OPS 1998 NARSTO-NE-OPS 1998 Transport Initiated Pollution Event - Transport Initiated Ozone and PM Event PAN from Ohio Valley Power Plants Revealed by Water Vapor Tracer 10
8 AM 8 PM 8 AM 8 PM 8 AM 8 AM NARSTO-NEOPS – Philadelphia Air Pollution Event 21-22 Aug 1998 11
Lidar Optical Extinction Compared to PM 10 and PM 2.5 PM Mass – George Allen – Harvard SPH 12
Humidity control of extinction >80% relative humidity causes striking increase in small particle extinction (primarily due to drop in nighttime temperature) 13
Scattering from Cloud Cloud scattering at visible and ultraviolet wavelengths - - multi- λ to infer size variation - SH in region around cloud indicates growth or dissipation UV VIS H 2 O 14
The time sequence shows the evolution of a cloud in terms of the local water vapor content and small particle extinction. 15
Using the N 2 , O 2 and the rotational signals from Raman Lidar, we are able to measure the path optical extinction at UV, VIS, NIR wavelengths near the laser wavelength we choose, but we must avoid wavelengths where chemical absorption occurs (high values of k ). Most of the visible and near ultraviolet region has sufficiently low absorption, due to peaks in the imaginary index of refraction, that the Raman lidar technique provides excellent profiles of optical extinction. However, we often need to better understand the optical path in the presence of aerosols composed of various absorbing chemicals, and those particles that are in condensed and irregular forms, such as airborne dusts. In solid materials, the optical scatter process is complicated by internal electric fields from nearby charge distributions. Effective medium theory is used to better describe these more complicated environments and extend measurements into the infrared region, where absorption features dominate. The use of ellipsometry, infrared absorption measurements, and electron microscopy, together with development of sample preparation techniques, now provide an opportunity to characterize these complex optical environments. 16
Wavelength ( µ m) 20 10 5 3.3 2.5 2 1.67 µ m ARD Index of Refraction (Uncorrected for Bulk Media Effects) Real Index Imaginary Index 17
Wavelength ( µ m) 25 16.7 12.5 10 8.3 µ m Arizona Road Dust Ellipsometer – Woollam IR-VASE Real Index Run 3 14-16 Oct 2011 200-1400 cm -1 (7.0-40 µ m) (Scattering) at 4 cm -1 resolution Imaginary Index (Absorption) 18
Ellipsometry Measurements of the Real and Imaginary Index Arizona Road Dust (ARD) 4 Real Index of Refraction Four Different 3 Real Index, n Samples of ARD 2 1 0 Imaginary Index of Refraction Four Different 2 Samples of ARD Imaginary Index, k 1 0 7 9 11 13 15 17 19 21 23 25 27 29 Wavelength ( µ m) 19
A warning about geometry • Limiting cases are Correction of the Index – No screening ε = f a ε a + f b ε b • The index is obviously wrong – Maximum screening for something mostly silica. − 1 ε = f a ε a + f b ε b • Mix silica (~1.5) and air (~1) and get something in between. • Solution depends upon the • Capacitance works when << geometry. wavelength. Use the dielectric constant ε = • • The spheres case is in between. (n - ik) 2 E ε a No screening ε b Maximum screening ε a ε b 20
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