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  • Editor: Christian Seassal
  • Vol. 22, Iss. S3 — May. 5, 2014
  • pp: A1009–A1022
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UV polarization lidar for remote sensing new particles formation in the atmosphere

Grégory David, Benjamin Thomas, Yoan Dupart, Barbara D’Anna, Christian George, Alain Miffre, and Patrick Rairoux  »View Author Affiliations


Optics Express, Vol. 22, Issue S3, pp. A1009-A1022 (2014)
http://dx.doi.org/10.1364/OE.22.0A1009


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Abstract

Understanding new particles formation in the free troposphere is key for air quality and climate change, but requires accurate observation tools. Here, we discuss on the optical requirements ensuring a backscattering device, such as a lidar, to remotely observe nucleation events promoted by nonspherical desert dust or volcanic ash particles. By applying the Mie theory and the T-matrix code, we numerically simulated the backscattering coefficient of spherical freshly nucleated particles and nonspherical particles. We hence showed that, to remotely observe such nucleation events with an elastic lidar device, it should operate in the UV spectral range and be polarization-resolved. Two atmospheric case studies are proposed, on nucleation events promoted by desert dust, or volcanic ash particles. This optical pathway might be useful for climate, geophysical and fundamental purposes, by providing a range-resolved remote observation of nucleation events.

© 2014 Optical Society of America

1. Introduction

Among all light scattering directions, the backward direction is one of the most sensitive to the particles size and shape, as underlined by numerical simulations [1

1. M. I. Mishchenko, L. D. Travis, and A. A. Lacis, Scattering, Absorption and Emission of Light by Small Particles, 3rd ed. (Cambridge University, 2002).

,2

2. T. Nousiainen, E. Zubko, H. Lindqvist, M. Kahnert, and J. Tyynelä, “Comparison of scattering by different nonspherical, wavelength-scale particles,” J. Quant. Spectrosc. Radiat. Transfer 113(18), 2391–2405 (2012). [CrossRef]

], laboratory experiments [3

3. G. David, B. Thomas, E. Coillet, A. Miffre, and P. Rairoux, “Polarization-resolved exact light backscattering by an ensemble of particles in air,” Opt. Express 21(16), 18624–18639 (2013). [CrossRef] [PubMed]

] as well as field experiments, dedicated to passive [4

4. O. Dubovik, A. Sinyuk, T. Lapyonok, B. N. Holben, M. I. Mishchenko, P. Yang, T. F. Eck, H. Volten, O. Muñoz, B. Veihelmann, W. J. van der Zande, J.-F. Leon, M. Sorokin, and I. Slutsker, “Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust,” J. Geophys. Res. 111(D11), D11208 (2006). [CrossRef]

] or active [5

5. G. David, B. Thomas, T. Nousiainen, A. Miffre, and P. Rairoux, “Retrieving simulated volcanic, desert dust, and sea-salt particle properties from two / three-component particle mixtures using UV-VIS polarization Lidar and T-matrix,” Atmos. Chem. Phys. 13(14), 6757–6776 (2013). [CrossRef]

9

9. I. Veselovskii, O. Dubovik, A. Kolgotin, T. Lapyonok, P. Di Girolamo, D. Summa, D. N. Whiteman, M. I. Mishchenko, and D. Tanré, “Application of randomly oriented spheroids for retrieval of dust particle parameters from multiwavelength lidar measurements,” J. Geophys. Res. 115(D21), D21203 (2010). [CrossRef]

] remote sensing. Such backscattering devices have become a standard in observation and monitoring of atmospheric aerosol, as underlined in a variety of field campaigns or missions, such as CALIPSO [6

6. D. M. Winker, M. A. Vaughan, A. Omar, Y. Hu, K. A. Powell, Z. Liu, W. H. Hunt, and S. A. Young, “Overview of the CALIPSO mission and CALIOP data processing algorithms,” J. Atmos. Oceanic Technol. 26(11), 2310–2323 (2009). [CrossRef]

], ACE [7

7. A. Shimizu, N. Sugimoto, I. Matsui, K. Arao, I. Uno, T. Murayama, N. Kagawa, K. Aoki, A. Uchiyama, and A. Yamazaki, “Continuous observations of Asian dust and other aerosols by polarization lidars in China and Japan during ACE-Asia,” J. Geophys. Res. 109(D19), D19S17 (2004). [CrossRef]

], or SAMUM [8

8. A. Ansmann, A. Petzold, K. Kandler, I. Tegen, M. Wendisch, D. Muller, B. Weinzierl, T. Muller, and J. Heintzenberg, “Saharan Mineral Dust Experiments SAMUM–1 and SAMUM–2: what have we learned?” Tellus, Ser. B 63(4), 403–429 (2011). [CrossRef]

], which provided vertical profiles of particles backscattering coefficients in the low and in the free troposphere, under in situ conditions of temperature and humidity. To interpret lidar observations, numerical simulations have been developed in complement [9

9. I. Veselovskii, O. Dubovik, A. Kolgotin, T. Lapyonok, P. Di Girolamo, D. Summa, D. N. Whiteman, M. I. Mishchenko, and D. Tanré, “Application of randomly oriented spheroids for retrieval of dust particle parameters from multiwavelength lidar measurements,” J. Geophys. Res. 115(D21), D21203 (2010). [CrossRef]

,10

10. J. Gasteiger, S. Groß, V. Freudenthaler, and M. Wiegner, “Volcanic ash from Iceland over Munich: mass concentration retrieved from ground-based remote sensing measurements,” Atmos. Chem. Phys. 11(5), 2209–2223 (2011). [CrossRef]

] to retrieve the particles mean diameter as well as the particles mass concentration from lidar observations. In such studies, a numerical limit of approximately 100 nanometers has been drawn for the lowest particles mean diameter observable with a 355 nm-wavelength backscattering device. Consequently, it has been generally considered that particles for sizes below 100 nanometers could not be observed with an optical backscattering instrument. Nonetheless, as underlined by the definition of the lidar backscattering coefficient, such small-sized particles may strongly contribute to the optical backscattering coefficient, when present in high concentrations, as implied by the detection of molecular backscattering with a lidar device.

2. Particles backscattering coefficient during a NPF-event

In this section, we numerically evaluate the backscattering coefficient corresponding to a dust NPF-event, where nonspherical and spherical particles coexist at different sizes and number concentrations. Accordingly, these numerical simulations were made as a function of particle size and radiation wavelength. The particles backscattering coefficient βp quantitatively describes the amount of light scattered in the backward direction by the particles ensemble:
βp(λ)=0Dp,max(dσdΩ)p(Dp,λ)×np(Dp)dDp
(1)
where (dσ/dΩ)p is the differential backscattering cross-section of the particles (m2sr−1) at wavelength λ and for a particle diameter Dp (for non-spherical particles, a volume equivalent diameter can be defined for the Dp-definition). The integration is performed over the particles size distribution (PSD), np = dNp/dDp representing the particles number density corresponding to the particles number concentration Np (m−3). The starting point of our numerical simulation is the observation of a typical dust NPF-event [18

18. Y. Dupart, S. M. King, B. Nekat, A. Nowak, A. Wiedensohler, H. Herrmann, G. David, B. Thomas, A. Miffre, P. Rairoux, B. D’Anna, and C. George, “Mineral dust photochemistry induces nucleation events in the presence of SO2.,” Proc. Natl. Acad. Sci. U.S.A. 109(51), 20842–20847 (2012). [CrossRef] [PubMed]

], as displayed in Fig. 1(a), where the time evolution of np is plotted as a function of Dp. This plot is representative of particle concentrations observed during NPF-events [12

12. M. Kulmala, T. Petäjä, T. Nieminen, M. Sipilä, H. E. Manninen, K. Lehtipalo, M. Dal Maso, P. P. Aalto, H. Junninen, P. Paasonen, I. Riipinen, K. E. J. Lehtinen, A. Laaksonen, and V. M. Kerminen, “Measurement of the nucleation of atmospheric aerosol particles,” Nat. Protoc. 7(9), 1651–1667 (2012). [CrossRef] [PubMed]

]. As underlined by Kulmala et al. [12

12. M. Kulmala, T. Petäjä, T. Nieminen, M. Sipilä, H. E. Manninen, K. Lehtipalo, M. Dal Maso, P. P. Aalto, H. Junninen, P. Paasonen, I. Riipinen, K. E. J. Lehtinen, A. Laaksonen, and V. M. Kerminen, “Measurement of the nucleation of atmospheric aerosol particles,” Nat. Protoc. 7(9), 1651–1667 (2012). [CrossRef] [PubMed]

], the appearance of the “banana-shaped” plot in the lower part of Fig. 1(a) is a clear signature of a NPF-event: such a modification of the PSD cannot be explained by any other physical or chemical process. The dust origin of the observed air masses can be checked from air mass back-trajectories [18

18. Y. Dupart, S. M. King, B. Nekat, A. Nowak, A. Wiedensohler, H. Herrmann, G. David, B. Thomas, A. Miffre, P. Rairoux, B. D’Anna, and C. George, “Mineral dust photochemistry induces nucleation events in the presence of SO2.,” Proc. Natl. Acad. Sci. U.S.A. 109(51), 20842–20847 (2012). [CrossRef] [PubMed]

,26

26. A. Stohl, C. Forster, A. Frank, P. Seibert, and G. Wotawa, “Technical note: the Lagrangian particle dispersion model, FLEXPART version 6,” Atmos. Chem. Phys. 5, 2462–2474 (2005).

]. Freshly nucleated particles have diameters as low as a few nanometers (lowest size range of so-called ultrafine particles), and subsequently growth to sizes in the range of several tens of nanometers. Nucleation events, to be seen in between 09:00-12:00, then 18:00-19:00, only occur in the presence of weak concentrations of coarser particles (diameters above 800 nanometers). These coarser particles were identified as nonspherical dust particles [18

18. Y. Dupart, S. M. King, B. Nekat, A. Nowak, A. Wiedensohler, H. Herrmann, G. David, B. Thomas, A. Miffre, P. Rairoux, B. D’Anna, and C. George, “Mineral dust photochemistry induces nucleation events in the presence of SO2.,” Proc. Natl. Acad. Sci. U.S.A. 109(51), 20842–20847 (2012). [CrossRef] [PubMed]

, 27

27. W. Wang, J. Ma, S. Hatakeyama, X. Liu, Y. Chen, A. Takami, L. Ren, and C. Geng, “Aircraft measurements of vertical ultrafine particles profiles over northern China coastal areas during dust storms in 2006,” Atmos. Environ. 42(22), 5715–5720 (2008). [CrossRef]

].
Fig. 1 Panel (a): Observation of the size and time evolution of the particles number concentration during a typical dust-NPF event, taken from a field campaign [18] on 2009 March 13th. Local time is used (UTC + 8h, Asian field campaign). The observed behavior between 9:00 and 12:00, then 18:00 to 19:00, is a clear signature of a NPF-event, while in the meantime, coarser dust particles, for diameters above 800 nm, are in low number concentrations. Panel (b): Numerical simulation of the backscattering coefficient βNPF obtained by applying the Mie theory at λ = 355 nm (blue), 532 nm (green), 1064 nm (red). The dust particles backscattering coefficient βdust, derived from T-matrix numerical simulation, is plotted at λ = 355 nm in light blue.

2.1 Mie numerical simulation of the nucleated particles backscattering coefficient βNPF

Freshly nucleated particles, despite their very low backscattering cross-section, may significantly contribute to βp, if they are numerous. These particles can be considered as spherical particles, which mainly contain sulfuric acid, as shown by the state-of-the-art literature [14

14. J. Kirkby, J. Curtius, J. Almeida, E. Dunne, J. Duplissy, S. Ehrhart, A. Franchin, S. Gagné, L. Ickes, A. Kürten, A. Kupc, A. Metzger, F. Riccobono, L. Rondo, S. Schobesberger, G. Tsagkogeorgas, D. Wimmer, A. Amorim, F. Bianchi, M. Breitenlechner, A. David, J. Dommen, A. Downard, M. Ehn, R. C. Flagan, S. Haider, A. Hansel, D. Hauser, W. Jud, H. Junninen, F. Kreissl, A. Kvashin, A. Laaksonen, K. Lehtipalo, J. Lima, E. R. Lovejoy, V. Makhmutov, S. Mathot, J. Mikkilä, P. Minginette, S. Mogo, T. Nieminen, A. Onnela, P. Pereira, T. Petäjä, R. Schnitzhofer, J. H. Seinfeld, M. Sipilä, Y. Stozhkov, F. Stratmann, A. Tomé, J. Vanhanen, Y. Viisanen, A. Vrtala, P. E. Wagner, H. Walther, E. Weingartner, H. Wex, P. M. Winkler, K. S. Carslaw, D. R. Worsnop, U. Baltensperger, and M. Kulmala, “Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation,” Nature 476(7361), 429–433 (2011). [CrossRef] [PubMed]

, 24

24. M. Ehn, J. A. Thornton, E. Kleist, M. Sipilä, H. Junninen, I. Pullinen, M. Springer, F. Rubach, R. Tillmann, B. Lee, F. Lopez-Hilfiker, S. Andres, I. H. Acir, M. Rissanen, T. Jokinen, S. Schobesberger, J. Kangasluoma, J. Kontkanen, T. Nieminen, T. Kurtén, L. B. Nielsen, S. Jørgensen, H. G. Kjaergaard, M. Canagaratna, M. D. Maso, T. Berndt, T. Petäjä, A. Wahner, V. M. Kerminen, M. Kulmala, D. R. Worsnop, J. Wildt, and T. F. Mentel, “A large source of low-volatility secondary organic aerosol,” Nature 506(7489), 476–479 (2014). [CrossRef] [PubMed]

].

To be quantitative, we hence numerically simulated the backscattering coefficient βNPF of nucleated particles during the NPF-event depicted in Fig. 1(a), by applying the Mie theory. We computed their differential backscattering cross-section (dσ/dΩ)NPF as a function of the particle diameter Dp and radiation wavelength λ, using a wavelength-dependent sulfuric acid refractive index [28

28. J. R. Hummel, E. P. Shettle, and D. R. Longtin, “A new background stratospheric aerosol model for use in atmospheric radiation models,” AFGL-TR-88–0166, Air Force Geophysics Laboratory, Hanscom Air Force Base, MA (1988).

]. We then retrieved βNPF from Eq. (1), using the particles number density nNPF displayed in Fig. 1(a), corresponding to particles diameters between 3 and 800 nanometers, coarser particles being nonspherical [18

18. Y. Dupart, S. M. King, B. Nekat, A. Nowak, A. Wiedensohler, H. Herrmann, G. David, B. Thomas, A. Miffre, P. Rairoux, B. D’Anna, and C. George, “Mineral dust photochemistry induces nucleation events in the presence of SO2.,” Proc. Natl. Acad. Sci. U.S.A. 109(51), 20842–20847 (2012). [CrossRef] [PubMed]

, 27

27. W. Wang, J. Ma, S. Hatakeyama, X. Liu, Y. Chen, A. Takami, L. Ren, and C. Geng, “Aircraft measurements of vertical ultrafine particles profiles over northern China coastal areas during dust storms in 2006,” Atmos. Environ. 42(22), 5715–5720 (2008). [CrossRef]

]. The time evolution of βNPF is displayed in Fig. 1(b) at the three most commonly used lidar wavelengths, namely λUV = 355 nm (UV), λVIS = 532 nm (VIS) and λIR = 1 064 nm (IR).

As expected, βNPF increases between 09:00 and 12:00 as the NPF-event appears while freshly nucleated particles growth. Interestingly, this increase is stronger at the UV-wavelength ( + 0.65 Mm−1sr−1) than at the VIS wavelength ( + 0.35 Mm−1sr−1) or at the IR one ( + 0.13 Mm−1sr−1). Hence, the highest βNPF-values are observed in the UV spectral range. The numerical simulation provides quantitative values for βNPF: it varies between 8 and 17 × 10−7 m−1sr−1 for λ = 355 nm and, at the onset of the nucleation process, βNPF is equal to 7 × 10−7 m−1sr−1. As discussed in Section 3, this value is detectable with the state-of-the art lidar devices. The same conclusions can be drawn between 18:00 and 19:00, where particles growth after a dust outbreak. In the late afternoon, particles below 10 nm are not actually seen due to the interplay between nucleation and condensation on pre-existing particles. The corresponding back-trajectory shows that the same dust-loaded air mass is followed all day long.

2.2 Size and wavelength dependence of βNPF

The observed large variations, with repetitive patterns, mainly originates from the differential backscattering cross-section (dσ/dΩ)NPF of nucleated particles, which is size and wavelength dependent, and not monotonically increasing with increasing diameter. When decreasing the wavelength from the IR down to the UV spectral range, more significant integrand-values are observed at lower particles sizes, as a consequence of the size parameter increase (for λ = 355 nm, particles with diameter in the range of 100 nm correspond to size parameter xp = πDp/λ ≈1). Consequently, the lowest particle size contributing to βNPF is observed at λ = 240 nm and corresponds to Dp,min = 50 nm, while for λ = 1 064 nm, Dp,min is around 250 nm. Hence, the nucleation of clusters leading to the formation of ultrafine particles in the range of a few nanometers cannot be addressed with a lidar, even in the UV spectral range, at least for such number concentrations. Nonetheless, the subsequent particles growth to sizes in the range of a few tens of nanometers is more significantly contributing to βNPF in the UV spectral range, where the highest (dσ/dΩ)NPF × nNPF(r)-values are observed. In this spectral range, almost all particles for diameters between Dp,min and 800 nm contribute to βNPF, which is hence increased. As a comparison, in the IR spectral range, the main contribution to βNPF originates from particles with diameter around Dp,min = 300 nm. Therefore, for lidar observation of a NPF-event, the UV spectral range should be preferably used, as confirmed in Fig. 2(b) where βNPF (i.e. the integral of Fig. 2(a) over the PSD) is plotted as a function of the wavelength λ. Hence, for a given backscattering device, the sensitivity of light backscattering to βNPF is increased by four times when operated at λ = 355 nm (UV) rather than for λ = 1064 nm (IR).

2.3 T-matrix numerical simulation of the dust particles backscattering coefficient βdust

As depicted in Fig. 1(a), NPF-events only appear in the presence of low dust particles number concentrations, in agreement with Wang et al.’s field measurements [27

27. W. Wang, J. Ma, S. Hatakeyama, X. Liu, Y. Chen, A. Takami, L. Ren, and C. Geng, “Aircraft measurements of vertical ultrafine particles profiles over northern China coastal areas during dust storms in 2006,” Atmos. Environ. 42(22), 5715–5720 (2008). [CrossRef]

] and Dupart et al.’s laboratory findings [18

18. Y. Dupart, S. M. King, B. Nekat, A. Nowak, A. Wiedensohler, H. Herrmann, G. David, B. Thomas, A. Miffre, P. Rairoux, B. D’Anna, and C. George, “Mineral dust photochemistry induces nucleation events in the presence of SO2.,” Proc. Natl. Acad. Sci. U.S.A. 109(51), 20842–20847 (2012). [CrossRef] [PubMed]

]. The latter authors showed that dust particles act as a condensation and coagulation sink for gases and other particles. To account for the key role played by nonspherical dust particles (see Section 2.1 and 2.4), we numerically evaluated the dust particles backscattering coefficient βdust corresponding to the Fig. 1(a) dust NPF-event.

Dust particles being highly irregularly-shaped, their backscattering coefficient cannot be computed by applying the Mie theory. However, the backscattering property of size-shape distributions of atmospheric dust particles can be well-mimicked by a size-shape distribution of spheroids, used as a proxy for the dust particles ensemble [4

4. O. Dubovik, A. Sinyuk, T. Lapyonok, B. N. Holben, M. I. Mishchenko, P. Yang, T. F. Eck, H. Volten, O. Muñoz, B. Veihelmann, W. J. van der Zande, J.-F. Leon, M. Sorokin, and I. Slutsker, “Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust,” J. Geophys. Res. 111(D11), D11208 (2006). [CrossRef]

,5

5. G. David, B. Thomas, T. Nousiainen, A. Miffre, and P. Rairoux, “Retrieving simulated volcanic, desert dust, and sea-salt particle properties from two / three-component particle mixtures using UV-VIS polarization Lidar and T-matrix,” Atmos. Chem. Phys. 13(14), 6757–6776 (2013). [CrossRef]

,9

9. I. Veselovskii, O. Dubovik, A. Kolgotin, T. Lapyonok, P. Di Girolamo, D. Summa, D. N. Whiteman, M. I. Mishchenko, and D. Tanré, “Application of randomly oriented spheroids for retrieval of dust particle parameters from multiwavelength lidar measurements,” J. Geophys. Res. 115(D21), D21203 (2010). [CrossRef]

]. Hence, to compute βdust, we applied the T-matrix numerical code [25

25. M. I. Mishchenko and L. D. Travis, “Capabilities and limitations of a current Fortran implementation of the T-matrix method for randomly oriented rotationally symmetric scatterers,” J. Quant. Spectrosc. Radiat. Transfer 60(3), 309–324 (1998). [CrossRef]

], choosing size parameters corresponding to coarse dust particles (diameters above 800 nm) at λ = 355 nm. For the shape distribution of spheroids, we assumed equal numbers of prolate (ε < 1) and oblate (ε ≥ 1) spheroids, ε = b/a representing the aspect ratio of a spheroid having a and b for major / minor axis. We also accounted for polarization effects (to be used in Section 2.4), by choosing ε-values that are distributed through a power-law n = 3 shape distribution, ranging from 1.2 up to 2.6 with a 0.2 step, that well mimics atmospheric dust particles [5

5. G. David, B. Thomas, T. Nousiainen, A. Miffre, and P. Rairoux, “Retrieving simulated volcanic, desert dust, and sea-salt particle properties from two / three-component particle mixtures using UV-VIS polarization Lidar and T-matrix,” Atmos. Chem. Phys. 13(14), 6757–6776 (2013). [CrossRef]

,25

25. M. I. Mishchenko and L. D. Travis, “Capabilities and limitations of a current Fortran implementation of the T-matrix method for randomly oriented rotationally symmetric scatterers,” J. Quant. Spectrosc. Radiat. Transfer 60(3), 309–324 (1998). [CrossRef]

]. Using m = 1.57 – 0.007 × i for the dust particles refractive index at λ = 355 nm [29

29. K. Kandler, K. Lieke, N. Benker, C. Emmel, M. Küpper, D. Müller-Ebert, M. Ebert, D. Scheuvens, A. Schladitz, L. Schütz, and S. Weinbruch, “Electron microscopy of particles collected at Praia, Cape Verde, during the Saharan Mineral Dust Experiment: particle chemistry, shape, mixing state and complex refractive index,” Tellus, Ser. B 63(4), 475–496 (2011). [CrossRef]

] and the coarse PSD depicted in the upper graph of Fig. 1(a), corresponding to nonspherical particles, we retrieved the dust particles backscattering coefficient βdust at λ = 355 nm, as displayed in light blue color in Fig. 1(b). Our numerical simulation shows that βdust reaches a minimum value of 3 × 10−7 m−1sr−1 at the onset of the nucleation process, at 09:00.

2.4 Methodology for remotely sensing a NPF-event with a backscattering device

The above Mie and T-matrix numerical simulations show that, when βdust is sufficiently high, as around 12:00 (see Fig. 1(b)), the dust particles loading is so high that the βNPF-coefficient starts to decrease, in agreement with Dupart et al.’s laboratory measurements [18

18. Y. Dupart, S. M. King, B. Nekat, A. Nowak, A. Wiedensohler, H. Herrmann, G. David, B. Thomas, A. Miffre, P. Rairoux, B. D’Anna, and C. George, “Mineral dust photochemistry induces nucleation events in the presence of SO2.,” Proc. Natl. Acad. Sci. U.S.A. 109(51), 20842–20847 (2012). [CrossRef] [PubMed]

], showing that NPF-events only appear at low dust concentrations. Such a correlative behavior between βNPF and βdust is not observed before the NPF-event (i.e. during nighttime) where both backscattering coefficients decrease. As a result, under the condition that the atmosphere is stable [18

18. Y. Dupart, S. M. King, B. Nekat, A. Nowak, A. Wiedensohler, H. Herrmann, G. David, B. Thomas, A. Miffre, P. Rairoux, B. D’Anna, and C. George, “Mineral dust photochemistry induces nucleation events in the presence of SO2.,” Proc. Natl. Acad. Sci. U.S.A. 109(51), 20842–20847 (2012). [CrossRef] [PubMed]

], the βNPF and βdust backscattering coefficients may be used as optical tracers for the NPF-event.

The presence of nonspherical particles, such as dust particles, is key for observing the NPF-event. As implied by Eq. (1), atmospheric particles, whatever their size or shape, either spherical (s) or nonspherical (ns), contribute to the particles backscattering coefficient βp. As detailed in [5

5. G. David, B. Thomas, T. Nousiainen, A. Miffre, and P. Rairoux, “Retrieving simulated volcanic, desert dust, and sea-salt particle properties from two / three-component particle mixtures using UV-VIS polarization Lidar and T-matrix,” Atmos. Chem. Phys. 13(14), 6757–6776 (2013). [CrossRef]

], the s-particles backscattering coefficient βs can then be separately determined from its equivalent for nonspherical particles βns by carefully analyzing the polarization π of the backscattered radiation (π = {//, ⊥} is defined with respect to the incident laser linear polarization). In this way, βs and βns can be separately retrieved as follows [5

5. G. David, B. Thomas, T. Nousiainen, A. Miffre, and P. Rairoux, “Retrieving simulated volcanic, desert dust, and sea-salt particle properties from two / three-component particle mixtures using UV-VIS polarization Lidar and T-matrix,” Atmos. Chem. Phys. 13(14), 6757–6776 (2013). [CrossRef]

, 30

30. A. Miffre, G. David, B. Thomas, and P. Rairoux, “Atmospheric non-spherical particles optical properties from UV-polarization lidar and scattering matrix,” Geophys. Res. Lett. 38(16), L16804 (2011). [CrossRef]

]:
βs=βs,//=βp,//βns,//=βp,//βp,/δns
(2a)
βns=βns,//+βns,=βp,(1+1/δns)
(2b)
since only ns-particles depolarize laser light, at a rate characterized by the ns-particles depolarization δns = βns,⊥ns,// (s-particles do not contribute to βp,⊥). In this way, backscattering from all ns-particles − whatever their size − can be separately addressed from that of s-particles, including those that participate to the NPF-event, which can then be more easily addressed. In addition, following Fig. 2(a) (i.e. Mie theory), it is only when the backscattering device is operated in the UV spectral range that particles for diameters between Dp,min = 50 and 800 nm contribute to βs. We hence become sensitive to the nucleated particles and to the subsequent particles growth to larger sizes, the latter particles also originating from the NPF-event. Furthermore, particles for sizes larger than Dp,max = 800 nm cannot be considered as spherical [18

18. Y. Dupart, S. M. King, B. Nekat, A. Nowak, A. Wiedensohler, H. Herrmann, G. David, B. Thomas, A. Miffre, P. Rairoux, B. D’Anna, and C. George, “Mineral dust photochemistry induces nucleation events in the presence of SO2.,” Proc. Natl. Acad. Sci. U.S.A. 109(51), 20842–20847 (2012). [CrossRef] [PubMed]

, 27

27. W. Wang, J. Ma, S. Hatakeyama, X. Liu, Y. Chen, A. Takami, L. Ren, and C. Geng, “Aircraft measurements of vertical ultrafine particles profiles over northern China coastal areas during dust storms in 2006,” Atmos. Environ. 42(22), 5715–5720 (2008). [CrossRef]

]. As a result, the backscattering coefficient βNPF from spherical nucleated particles can be addressed by using a UV polarization-resolved backscattering device. In short, the polarization acts as a particle shape discriminator, allowing the backscattering separation of spherical particles from any other nonspherical particle, whatever its size. The more accurate the polarization analysis is, the more sensitive to βs the lidar remote sensing device is. Besides, the wavelength acts as a particle size discriminator, since, as discussed in Section 2.2, the shorter the wavelength is, the more sensitive to fine and ultrafine particles light backscattering is. In this way, backscattering from newly formed particles can be addressed by detecting their subsequent particles growth.

3. Lidar remote sensing observation of NPF-events

The numerical simulation shows that, at the onset of the nucleation process, βNPF is as low as 7 × 10−7 m−1sr−1NPF-increase of 6.5 × 10−7 m−1sr−1 during the NPF-event). In this section, we focus on our ability to perform such low backscattering measurements by discussing on the sensitivity and accuracy on βs in the UV. UV-polarization lidar experiments are then proposed as atmospheric case studies, in the presence of desert dust or volcanic ash particles.

3.1 A sensitive and accurate UV-polarization lidar device for detecting dust NPF-events

Following Eq. (2) the ability to detect a NPF-event is determined by the achieved sensitivity and accuracy on the remote optical tracers βs and βns in the UV spectral range. As discussed in G. David et al. [31

31. G. David, A. Miffre, B. Thomas, and P. Rairoux, “Sensitive and accurate dual-wavelength UV-VIS polarization detector for optical remote sensing of tropospheric aerosols,” Appl. Phys. B 108(1), 197–216 (2012). [CrossRef]

], two main features may hence limit the sensitivity of the lidar βNPF-measurement:

  • in the UV spectral range, molecular backscattering may overcome particles backscattering and hence limit the achieved sensitivity on βp.
  • sky background contribution, as well as polarization leakages, may limit the sensitivity on βs.

Fig. 3 Spectral dependence of molecular backscattering cross-section at λ = 355 nm numerically simulated for a standard atmosphere, for co-(black) and cross- (grey) polarized polarization components. Ro-vibrational molecular spectra appears spectrally smoothed due to the finite spectral linewidth of the laser emission (1 GHz), whose Doppler broadening is also included.
Figure 3 recalls the spectral dependence of the molecular (m) backscattering cross-section at λ = 355 nm. The particles backscattering being elastic, to increase our sensitivity to βp compared with βm, we used very narrow interference filters to spectrally bound Rayleigh molecular backscattering down to Cabannes backscattering. Practically, we chose Δλ = 0.3 nm (the filter central wavelength is defined with a 0.1 nm accuracy), which set the molecular depolarization δm = 0.37%, derived from optical molecular backscattering computation. This narrow filter also enabled to minimize the sky background contribution. To further increase our sensitivity to βp, during daytime, we matched the low (and hence difficult to measure) cross-polarized lidar signal with the lowest polarization component of the sky background intensity [31

31. G. David, A. Miffre, B. Thomas, and P. Rairoux, “Sensitive and accurate dual-wavelength UV-VIS polarization detector for optical remote sensing of tropospheric aerosols,” Appl. Phys. B 108(1), 197–216 (2012). [CrossRef]

]. Finally, polarization leakages were minimized by inserting two successive polarizing beamsplitter cubes in each polarization detector channel. As specified on a laboratory dedicated test bench, polarization cross-talks were found fully negligible, with better than 10−7 accuracy [31

31. G. David, A. Miffre, B. Thomas, and P. Rairoux, “Sensitive and accurate dual-wavelength UV-VIS polarization detector for optical remote sensing of tropospheric aerosols,” Appl. Phys. B 108(1), 197–216 (2012). [CrossRef]

].

3.2 Remote sensing of a desert dust NPF-event with a UV-polarization lidar

Fig. 4 Time-altitude maps of the lidar-retrieved backscattering coefficients {βp,//, βp,⊥}-coefficients, then {βs, βns}-backscattering coefficients measured at Lyon at λ = 355 nm in July 2010 during a Saharan dust outbreak. To put light on the achieved sensitivity, a different color code has been used for each map.
As a first case study, we evaluated the βs and βns lidar backscattering coefficients corresponding to a Saharan dust outbreak that occurred at Lyon in July 2010. During this event, ns-particles were identified as desert dust particles, as confirmed by air mass back-trajectories [30

30. A. Miffre, G. David, B. Thomas, and P. Rairoux, “Atmospheric non-spherical particles optical properties from UV-polarization lidar and scattering matrix,” Geophys. Res. Lett. 38(16), L16804 (2011). [CrossRef]

]. By applying Eqs. (2) and (3), we determined the Fig. 4 time-altitude maps for βp,// and βp,⊥, then βs and βns, using a lidar ratio Sp = (68 ± 5) sr and δdust = (22.5 ± 2.5) % [9

9. I. Veselovskii, O. Dubovik, A. Kolgotin, T. Lapyonok, P. Di Girolamo, D. Summa, D. N. Whiteman, M. I. Mishchenko, and D. Tanré, “Application of randomly oriented spheroids for retrieval of dust particle parameters from multiwavelength lidar measurements,” J. Geophys. Res. 115(D21), D21203 (2010). [CrossRef]

]. Dust particles, for which βp,⊥ is non-null, are mainly located above 3 km altitude while a βp,//-enhancement is observable in the free troposphere between 2 and 3 km altitude.

Fig. 5 Spherical (grey) and nonspherical (brown, dust) particles backscattering coefficient βs and βns as a function of altitude during a Saharan dust outbreak (Lyon, July 2010, 5h), together with the corresponding βp,// and βp,⊥-profiles. To ease the reading, the graph is limited to altitudes above the PBL where the dust cloud is present.
These features are best seen on the {βs, βns} time-altitude maps: s-particles are only observed at the border of the dust ns-layer, i.e. the βs-enhancement only occurs at low dust particles backscattering, in agreement with our numerical simulation (Section 2). To put error bars, we plotted in Fig. 5 vertical profiles of βs and βns at 05:00, for altitudes above the PBL (i.e. above 1.5 km). Within our error bars, βs is larger than βns for altitudes below 2.7 km: the s-particles backscattering is higher when the dust loading is low. Above 2.7 km altitude, the dust particles backscattering is so high that the s-particles backscattering is lowered. These observations agree with laboratory and field experiments [18

18. Y. Dupart, S. M. King, B. Nekat, A. Nowak, A. Wiedensohler, H. Herrmann, G. David, B. Thomas, A. Miffre, P. Rairoux, B. D’Anna, and C. George, “Mineral dust photochemistry induces nucleation events in the presence of SO2.,” Proc. Natl. Acad. Sci. U.S.A. 109(51), 20842–20847 (2012). [CrossRef] [PubMed]

, 27

27. W. Wang, J. Ma, S. Hatakeyama, X. Liu, Y. Chen, A. Takami, L. Ren, and C. Geng, “Aircraft measurements of vertical ultrafine particles profiles over northern China coastal areas during dust storms in 2006,” Atmos. Environ. 42(22), 5715–5720 (2008). [CrossRef]

]. A particles backscattering threshold of 7.5 × 10−7 m−1sr−1 is hence observed around 2.7 km altitude for this dust event. Interestingly, it is in the same range as that derived from our numerical simulation. As discussed in Section 4, it may hence correspond to the backscattering threshold at which dust particles start to promote NPF-events.

3.3 Remote sensing of a volcanic ash NPF-event with a UV-polarization lidar

As a second case study, we analyzed the s and ns-particles backscattering coefficients during the Eyjafjallajökull volcanic eruption that occurred at Lyon on April 17th 2010. During this event, above 3.5 km altitude, ns-particles were identified as volcanic ash particles, as confirmed by air mass back-trajectories [33

33. A. Miffre, G. David, B. Thomas, P. Rairoux, A. M. Fjaeraa, N. I. Kristiansen, and A. Stohl, “Volcanic aerosol optical properties and phase partitioning behavior after long-range advection characterized by UV-Lidar measurements,” Atmos. Environ. 48, 76–84 (2012). [CrossRef]

]. Using the lidar ratio and the ash depolarization ratio published in [33

33. A. Miffre, G. David, B. Thomas, P. Rairoux, A. M. Fjaeraa, N. I. Kristiansen, and A. Stohl, “Volcanic aerosol optical properties and phase partitioning behavior after long-range advection characterized by UV-Lidar measurements,” Atmos. Environ. 48, 76–84 (2012). [CrossRef]

], we retrieved the vertical profiles of βp,//, βp,⊥, βs and βns displayed in Fig. 6.
Fig. 6 Spherical (grey) and nonspherical (brown, ash) particles backscattering coefficient βs and βns as a function of altitude during a volcanic ash episode (Lyon, April 17th 2010, 12h), together with the corresponding βp,// and βp,⊥-profiles. To ease the reading, the graph is limited to altitudes above the PBL.
Above 3.5 km altitude, both s- and ns-particles contribute to the βp,//-profile while only ash particles contribute to the βp,⊥-profile. As for desert dust particles, within Fig. 6 error bars, the s-particles backscattering is increasing only when the ash backscattering is sufficiently low (the s-particles backscattering tends to decrease at high βash-values). Hence, and as for desert dust particles, a backscattering threshold of approximately 7 × 10−7 m−1sr−1 can be defined for this volcanic ash event.

4. Discussion

In this section, the lidar observations performed in Section 3 are analyzed and discussed, in agreement with the state-of-the-art literature on desert dust particles [18

18. Y. Dupart, S. M. King, B. Nekat, A. Nowak, A. Wiedensohler, H. Herrmann, G. David, B. Thomas, A. Miffre, P. Rairoux, B. D’Anna, and C. George, “Mineral dust photochemistry induces nucleation events in the presence of SO2.,” Proc. Natl. Acad. Sci. U.S.A. 109(51), 20842–20847 (2012). [CrossRef] [PubMed]

, 27

27. W. Wang, J. Ma, S. Hatakeyama, X. Liu, Y. Chen, A. Takami, L. Ren, and C. Geng, “Aircraft measurements of vertical ultrafine particles profiles over northern China coastal areas during dust storms in 2006,” Atmos. Environ. 42(22), 5715–5720 (2008). [CrossRef]

] and volcanic ash particles [19

19. J. Boulon, K. Sellegri, M. Hervo, and P. Laj, “Observations of nucleation of new particles in a volcanic plume,” Proc. Natl. Acad. Sci. U.S.A. 108(30), 12223–12226 (2011). [CrossRef] [PubMed]

]. In both case studies, it is only when the dust (resp. ash) backscattering coefficient is sufficiently low that, within our error bars, an s-particles backscattering enhancement has been observed.

As a preliminary remark, this feature cannot be attributed to a systematic bias originating from our {βs, βns}-retrieval procedure since the βs-increase and its subsequent βns-decrease were already observable on the unprocessed lidar co- and cross-polarized lidar signals, prior to our retrieval methodology. In addition, though βs = βp – βns, βs evolves independently from βns, since βp varies with altitude.

5. Conclusion and outlook

Acknowledgments

The authors thank Dr. H. Hermann and Dr. B. Nekat from IFT-Leipzig for making their banana-shaped plot available, as well as Dr. I. Veselovskii and M.I. Mishchenko for making their T-matrix numerical code available. Région Rhône-Alpes and CNRS are thanked for partly funding this work (thèse de Grégory David soutenue par la Région Rhône-Alpes à hauteur de 32 116 euros). Support by the French-German atmospheric research program (CNRS-INSU/DFG), by the Agence Nationale de la Recherche (ANR, Grant PHOTODUST), by the DFG-LEFE, is gratefully acknowledged.

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J. D. Klett, “Lidar inversion with variable backscatter/extinction ratios,” Appl. Opt. 24(11), 1638–1643 (1985). [CrossRef] [PubMed]

33.

A. Miffre, G. David, B. Thomas, P. Rairoux, A. M. Fjaeraa, N. I. Kristiansen, and A. Stohl, “Volcanic aerosol optical properties and phase partitioning behavior after long-range advection characterized by UV-Lidar measurements,” Atmos. Environ. 48, 76–84 (2012). [CrossRef]

34.

D. N. Whiteman, D. Venable, and E. Landulfo, Comments on “Accuracy of Raman lidar water vapor calibration and its applicability to long-term measurements,” Appl. Opt. 50(15), 2170–2176, author reply 2177–2178 (2011). [CrossRef] [PubMed]

35.

B. Thomas, A. Miffre, G. David, J.-P. Cariou, and P. Rairoux, “Remote sensing of trace gases with optical correlation spectroscopy and lidar: theoretical and numerical approach,” Appl. Phys. B 108(3), 689–702 (2012). [CrossRef]

OCIS Codes
(010.1110) Atmospheric and oceanic optics : Aerosols
(010.1290) Atmospheric and oceanic optics : Atmospheric optics
(010.3640) Atmospheric and oceanic optics : Lidar
(290.1310) Scattering : Atmospheric scattering
(290.1350) Scattering : Backscattering
(290.5855) Scattering : Scattering, polarization

ToC Category:
Remote Sensing and Sensors

History
Original Manuscript: March 14, 2014
Revised Manuscript: April 18, 2014
Manuscript Accepted: April 18, 2014
Published: April 30, 2014

Virtual Issues
June 11, 2014 Spotlight on Optics

Citation
Grégory David, Benjamin Thomas, Yoan Dupart, Barbara D’Anna, Christian George, Alain Miffre, and Patrick Rairoux, "UV polarization lidar for remote sensing new particles formation in the atmosphere," Opt. Express 22, A1009-A1022 (2014)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-22-S3-A1009


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