Polarization Measurements and Evaluation Based on Multidimensional Polarization Indices Applied in Analyzing Atmospheric Particulates
Abstract
:1. Introduction
2. Experimental Setup and Methods
2.1. Sample Preparation
2.2. Experimental Setup
2.3. Signal Processing and System Calibration
3. Results and Discussion
3.1. Polarization Characteristics of Particle Size
3.2. Polarization Characteristics of Particle Composition
3.3. Polarization Characteristics of Absorption Effects
3.4. Polarization Characteristics of Particle Shape
3.5. Optimal Combination of Polarization Indicators
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Block, M.L.; Calderon-Garciduenas, L. Air pollution: Mechanisms of neuroinflammation and CNS disease. Trends Neurosci. 2009, 32, 506–516. [Google Scholar] [CrossRef] [Green Version]
- Maher, B.A.; Ahmed, I.A.; Karloukovski, V.; MacLaren, D.A.; Foulds, P.G.; Allsop, D.; Mann, D.M.; Torres-Jardon, R.; Calderon-Garciduenas, L. Magnetite pollution nanoparticles in the human brain. Proc. Natl. Acad. Sci. USA 2016, 113, 10797–10801. [Google Scholar] [CrossRef] [Green Version]
- Han, L.; Zhou, W.; Li, W.; Li, L. Impact of urbanization level on urban air quality: A case of fine particles (PM(2.5)) in Chinese cities. Environ. Pollut. 2014, 194, 163–170. [Google Scholar] [CrossRef]
- Huang, R.J.; Zhang, Y.; Bozzetti, C.; Ho, K.F.; Cao, J.J.; Han, Y.; Daellenbach, K.R.; Slowik, J.G.; Platt, S.M.; Canonaco, F.; et al. High secondary aerosol contribution to particulate pollution during haze events in China. Nature 2014, 514, 218–222. [Google Scholar] [CrossRef] [Green Version]
- Schmeisser, L.; Andrews, E.; Ogren, J.A.; Sheridan, P.; Jefferson, A.; Sharma, S.; Kim, J.E.; Sherman, J.P.; Sorribas, M.; Kalapov, I.; et al. Classifying aerosol type using in situ surface spectral aerosol optical properties. Atmos. Chem. Phys. 2017, 17, 12097–12120. [Google Scholar] [CrossRef] [Green Version]
- Aiken, A.C.; Decarlo, P.F.; Kroll, J.H.; Worsnop, D.R.; Huffman, J.A.; Docherty, K.S.; Ulbrich, I.M.; Mohr, C.; Kimmel, J.R.; Sueper, D.; et al. O/C and OM/OC ratios of primary, secondary, and ambient organic aerosols with high-resolution time-of-flight aerosol mass spectrometry. Environ. Sci. Technol. 2008, 42, 4478–4485. [Google Scholar] [CrossRef]
- Ajtai, T.; Filep, Á.; Schnaiter, M.; Linke, C.; Vragel, M.; Bozóki, Z.; Szabó, G.; Leisner, T. A novel multi−wavelength photoacoustic spectrometer for the measurement of the UV–vis-NIR spectral absorption coefficient of atmospheric aerosols. J. Aerosol Sci. 2010, 41, 1020–1029. [Google Scholar] [CrossRef]
- Groß, S.; Freudenthaler, V.; Wirth, M.; Weinzierl, B. Towards an aerosol classification scheme for future EarthCARE lidar observations and implications for research needs. Atmos. Sci. Lett. 2015, 16, 77–82. [Google Scholar] [CrossRef] [Green Version]
- Sousa, G.; Gaulier, G.; Bonacina, L.; Wolf, J.P. Discriminating Bio-aerosols from Non-Bio-aerosols in Real-Time by Pump-Probe Spectroscopy. Sci. Rep. 2016, 6, 33157. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ansmann, A.; Wandinger, U.; Riebesell, M.; Weitkamp, C.; Michaelis, W. Independent measurement of extinction and backscatter profiles in cirrus clouds by using a combined Raman elastic-backscatter lidar. Appl. Opt. 1992, 31, 7113. [Google Scholar] [CrossRef]
- Costabile, F.; Barnaba, F.; Angelini, F.; Gobbi, G.P. Identification of key aerosol populations through their size and composition resolved spectral scattering and absorption. Atmos. Chem. Phys. 2013, 13, 2455–2470. [Google Scholar] [CrossRef] [Green Version]
- Groß, S.; Tesche, M.; Freudenthaler, V.; Toledano, C.; Wiegner, M.; Ansmann, A.; Althausen, D.; Seefeldner, M. Characterization of Saharan dust, marine aerosols and mixtures of biomass-burning aerosols and dust by means of multi-wavelength depolarization and Raman lidar measurements during SAMUM 2. Tellus B 2017, 63, 706–724. [Google Scholar] [CrossRef]
- Okamoto, H.; Sato, K.; Nishizawa, T.; Sugimoto, N.; Makino, T.; Jin, Y.; Shimizu, A.; Takano, T.; Fujikawa, M. Development of a multiple-field-of-view multiple-scattering polarization lidar: Comparison with cloud radar. Opt. Express 2016, 24, 30053–30067. [Google Scholar] [CrossRef]
- Jurányi, Z.; Burtscher, H.; Loepfe, M.; Nenkov, M.; Weingartner, E. Dual-wavelength light-scattering technique for selective detection of volcanic ash particles in the presence of water droplets. Atmos. Meas. Tech. 2015, 8, 5213–5222. [Google Scholar] [CrossRef] [Green Version]
- Muñoz, O.; Hovenier, J.W. Laboratory measurements of single light scattering by ensembles of randomly oriented small irregular particles in air. A review. J. Quant. Spectrosc. Radiat. Transf. 2011, 112, 1646–1657. [Google Scholar] [CrossRef]
- Renard, J.B.; Thaury, C.; Mineau, J.L.; Gaubicher, B. Small-angle light scattering by airborne particulates: Environnement S.A. continuous particulate monitor. Meas. Sci. Technol. 2010, 21, 085901. [Google Scholar] [CrossRef]
- Iwasaka, Y.; Shi, G.Y.; Shen, Z.; Kim, Y.S.; Trochkine, D.; Matsuki, A.; Zhang, D.; Shibata, T.; Nagatani, M.; Nakata, H. Nature of Atmospheric Aerosols over the Desert Areas in the Asian Continent: Chemical State and Number Concentration of Particles Measured at Dunhuang, China. Water Air Soil Pollut. Focus 2003, 3, 129–145. [Google Scholar] [CrossRef]
- Renard, J.-B.; Dulac, F.; Berthet, G.; Lurton, T.; Vignelles, D.; Jégou, F.; Tonnelier, T.; Jeannot, M.; Couté, B.; Akiki, R.; et al. LOAC: A small aerosol optical counter/sizer for ground-based and balloon measurements of the size distribution and nature of atmospheric particles—Part 1: Principle of measurements and instrument evaluation. Atmos. Meas. Tech. 2016, 9, 1721–1742. [Google Scholar] [CrossRef] [Green Version]
- Kobayashi, H.; Hayashi, M.; Shiraishi, K.; Nakura, Y.; Enomoto, T.; Miura, K.; Takahashi, H.; Igarashi, Y.; Naoe, H.; Kaneyasu, N.; et al. Development of a polarization optical particle counter capable of aerosol type classification. Atmos. Environ. 2014, 97, 486–492. [Google Scholar] [CrossRef]
- Li, D.; Zeng, N.; Zhan, D.; Chen, Y.; Zeng, M.; Ma, H. Differentiation of soot particulates in air using polarized light scattering method. Appl. Opt. 2017, 56, 4123–4129. [Google Scholar] [CrossRef] [PubMed]
- Weinzierl, B.; Sauer, D.; Esselborn, M.; Petzold, A.; Veira, A.; Rose, M.; Mund, S.; Wirth, M.; Ansmann, A.; Tesche, M.; et al. Microphysical and optical properties of dust and tropical biomass burning aerosol layers in the Cape Verde region—An overview of the airborne in situ and lidar measurements during SAMUM-2. Tellus B 2017, 63, 589–618. [Google Scholar] [CrossRef] [Green Version]
- Omar, A.H. Development of global aerosol models using cluster analysis of Aerosol Robotic Network (AERONET) measurements. J. Geophys. Res. 2005, 110. [Google Scholar] [CrossRef]
- Badieyan, S.; Dilmaghani-Marand, A.; Hajipour, M.J.; Ameri, A.; Razzaghi, M.R.; Rafii-Tabar, H.; Mahmoudi, M.; Sasanpour, P. Detection and Discrimination of Bacterial Colonies with Mueller Matrix Imaging. Sci. Rep. 2018, 8, 10815. [Google Scholar] [CrossRef] [Green Version]
- Li, X.; Liao, R.; Zhou, J.; Leung, P.T.Y.; Yan, M.; Ma, H. Classification of morphologically similar algae and cyanobacteria using Mueller matrix imaging and convolutional neural networks. Appl. Opt. 2017, 56, 6520–6530. [Google Scholar] [CrossRef]
- Li, X.; Liao, R.; Ma, H.; Leung, P.T.Y.; Yan, M. Polarimetric learning: A Siamese approach to learning distance metrics of algal Mueller matrix images. Appl. Opt. 2018, 57, 3829–3837. [Google Scholar] [CrossRef] [PubMed]
- Tang, I.N. Chemical and size effects of hygroscopic aerosols on light scattering coefficients. J. Geophys. Res. Atmos. 1996, 101, 19245–19250. [Google Scholar] [CrossRef]
- Wyatt, P.J. Some chemical, physical, and optical properties of fly ash particles. Appl. Opt. 1980, 19, 975–983. [Google Scholar] [CrossRef] [PubMed]
- Alexander, D.T.; Crozier, P.A.; Anderson, J.R. Brown carbon spheres in East Asian outflow and their optical properties. Science 2008, 321, 833–836. [Google Scholar] [CrossRef] [PubMed]
- Jiang, R.T.; Acevedo-Bolton, V.; Cheng, K.C.; Klepeis, N.E.; Ott, W.R.; Hildemann, L.M. Determination of response of real-time SidePak AM510 monitor to secondhand smoke, other common indoor aerosols, and outdoor aerosol. J. Environ. Monit. 2011, 13, 1695–1702. [Google Scholar] [CrossRef] [PubMed]
- Kandler, K.; Benker, N.; Bundke, U.; Cuevas, E.; Ebert, M.; Knippertz, P.; Rodriguez, S.; Schuetz, L.; Weinbruch, S.J.A.E. Chemical composition and complex refractive index of Saharan Mineral Dust at Izaa, Tenerife (Spain) derived by electron microscopy. Atmos. Environ. 2007, 41, 8058–8074. [Google Scholar] [CrossRef]
- Miffre, A.; Mehri, T.; Francis, M.; Rairoux, P. UV-VIS depolarization from Arizona Test Dust particles at exact backscattering angle. J. Quant. Spectrosc. Radiat. Transf. 2016, 169, 79–90. [Google Scholar] [CrossRef]
- Liao, R.; Zeng, N.; Zeng, M.; He, Y.; Ma, H. Estimation and extraction of the aerosol complex refractive index based on Stokes vector measurements. Opt. Lett. 2019, 44, 4877. [Google Scholar] [CrossRef] [PubMed]
- Chen, Y.; Zeng, N.; Chen, S.; Zhan, D.; He, Y.; Ma, H. Study on morphological analysis of suspended particles using single angle polarization scattering measurements. J. Quant. Spectrosc. Radiat. Transf. 2019, 224, 556–565. [Google Scholar] [CrossRef]
Shape | Aerosol Type | Manufacturer | Complex Refractive Index | Generator |
---|---|---|---|---|
Sphere | PSL (1, 2, 2.5 μm) | Sigma-Aldrich | 1.590–0.000i | Met-one 255 |
Quasi-spherical | Na2SO4 | Hong-Meng Beijing | 1.480–0.001i [26] | Met-one 255 |
NaCl | Hong-Meng Beijing | 1.540–0.001i [26] | Met-one 255 | |
NaNO3 | Hong-Meng Beijing | 1.587–0.001i [26] | Met-one 255 | |
Fly ash | AIOFM | 1.570–0.010i [27] | TSI-3400A | |
Carbon sphere | Nano-Micro Tech | 1.670–0.270i [28] | TSI-3400A | |
Highly irregular shape | Arizona dust | Power Technology | 1.540–0.020i [29] | TSI-3400A |
Carbon nanochip | Sigma-Aldrich | 1.670–0.270i [28] | TSI-3400A | |
Mesoporous carbon | XFNANO | 1.670–0.270i [28] | TSI-3400A | |
Hollow carbon sphere | XFNANO | 1.670–0.270i [28] | TSI-3400A |
Number | Index | Number | Index | Number | Index |
---|---|---|---|---|---|
1 | H-Hdop (30°) | 9 | P-Hdop (30°) | 17 | R-Hdop (30°) |
2 | H-Pdop (30°) | 10 | P-Pdop (30°) | 18 | R-Pdop (30°) |
3 | H-Hdop (60°) | 11 | P-Hdop (60°) | 19 | R-Hdop (60°) |
4 | H-Pdop (60°) | 12 | P-Pdop (60°) | 20 | R-Pdop (60°) |
5 | H-Hdop (85°) | 13 | P-Hdop (85°) | 21 | R-Hdop (85°) |
6 | H-Pdop (85°) | 14 | P-Pdop (85°) | 22 | R-Pdop (85°) |
7 | H-Hdop (115°) | 15 | P-Hdop (115°) | 23 | R-Hdop (115°) |
8 | H-Pdop (115°) | 16 | P-Pdop (115°) | 24 | R-Pdop (115°) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Liao, R.; Guo, W.; Zeng, N.; Guo, J.; He, Y.; Di, H.; Hua, D.; Ma, H. Polarization Measurements and Evaluation Based on Multidimensional Polarization Indices Applied in Analyzing Atmospheric Particulates. Appl. Sci. 2021, 11, 5992. https://doi.org/10.3390/app11135992
Liao R, Guo W, Zeng N, Guo J, He Y, Di H, Hua D, Ma H. Polarization Measurements and Evaluation Based on Multidimensional Polarization Indices Applied in Analyzing Atmospheric Particulates. Applied Sciences. 2021; 11(13):5992. https://doi.org/10.3390/app11135992
Chicago/Turabian StyleLiao, Riwei, Wei Guo, Nan Zeng, Jun Guo, Yonghong He, Huige Di, Dengxin Hua, and Hui Ma. 2021. "Polarization Measurements and Evaluation Based on Multidimensional Polarization Indices Applied in Analyzing Atmospheric Particulates" Applied Sciences 11, no. 13: 5992. https://doi.org/10.3390/app11135992
APA StyleLiao, R., Guo, W., Zeng, N., Guo, J., He, Y., Di, H., Hua, D., & Ma, H. (2021). Polarization Measurements and Evaluation Based on Multidimensional Polarization Indices Applied in Analyzing Atmospheric Particulates. Applied Sciences, 11(13), 5992. https://doi.org/10.3390/app11135992