Analysis of the particle size distribution and optical properties in the Korean seas

Transcription

1 Analysis of the particle size distribution and optical properties in the Korean seas Boram Lee 1,2, Young-Je Park 1, Wonkook Kim 1, Jae-Hyun Ahn 1, Kwangseok Kim 1, Jeong-Eon Moon 1 and Sang-Wan Kim 2 1 Korea Ocean Satellite Center (KOSC), Korea Institude of Ocean Science and Technology(KIOST) 2 Geoinformation Engineering, Sejong University Corresponding youngjepark@kiost.ac.kr 1 / 27

2 INDEX Introduction Data / Method Preliminary results Discussion and Conclusion 2 / 27

3 Introduction 3 / 27

4 background Particle Size Distribution (PSD) the mathematical function that defines the number of particles according to size can be used to characterize marine particles phytoplankton community dynamics, sediment transport (Slade and Boss, 2015) Inherent Optical Properties (IOP) When a photon interacts with matter, photon can disappear : absorption coefficient (a) photon can change its direction and/or energy : scattering coefficient (b) a(λ) + b(λ)= c(λ) (attenuation coefficient) independent on the ambient light field ptical_properties The link between the PSD and the IOP in Mie theory, IOP can calculated by using PSD and index of refraction 4 / 27

5 Mathematical descriptions of the PSD ξ power law or Junge type distribution N(D) = KD -ξ most widely used for optical and ecological purposes (Jonasz, 1983; Briucaud et al., 1981; Stramski and Kiefer, 1991; Boss et al., 2001; Twardowski et al., 2001) Else sum of lognormal functions, Weibull distribution, gamma function are used 5 / 27

6 Mathematical descriptions of the particulate attenuation coefficient, c p c p is summation of c ph and c d particulate attenuation coefficient, c p (λ) is well described by a hyperbolic relation to γ the wavelength (c p λ -γ ) (Diehl and Haardt, 1980; Boss et al. 2001b) 6 / 27

7 The link between PSD and c p The exponent of PSD (ξ) is linearly related with c p (γ) (Diehl and Haardt, 1980) γ = ξ 3 Boss et al., 2001 <Assumption> 1. nonabsorbing particle (imaginary index of refraction is zero) 2. spherical particles 3. PSD is described by Junge-type distribution 7 / 27

8 objective In this study (initial study) : using field data collected in 2015 near East/Japan sea, Conduct measurements and post processing for PSD and c p (λ) compare the spectral shape of the c p (λ) and PSD Ultimate objective : 1) evaluate a theoretical model between the spectral shape of the c p (λ) and PSD 2) Understanding the relationship between PSD and IOP 8 / 27

9 Data and Method 9 / 27

10 In-situ data East/Japan Sea (EJS) (m) Clear oceanic water Carried out in May 2015 Number of sample :9 (PSD, AC-S) Mokpo coastal zone (MP) Turbid water Carried out in March 2015 MP EJS Number of sample : 17 (PSD) MP EJS 10/ 27

11 PSD measurement Use the Coulter counter Multisizer 3 Principal: As each particles passes through the aperture, momentarily increasing the impedance of the aperture suspended particles are counted and sized 11 / 27

12 PSD measurement 100um aperture tube was used (2~60um particle size measurable) SPM, mainly Nano/Micro phytoplankton etc. can be detected MP EJS measured PSD lacks large particles made statistics pool Eliminate large particles MP: D max : 15um / EJS : D max : 9um 12/ 27

13 PSD exponent (ξ) < EJS> < MP> Using Least mean square, PSD data is fitted to power law function, and obtained exponent (ξ) 13/ 27

14 Attenuation coefficient (c ) measurement : Wetlabs AC-S Wetlabs AC-S has two sensors : absorption, a(λ) and attenuation, c(λ) sensors Provides an 80+ wavelength output from nm Technical report on WetLabs AC-S absorption and beam attenuation meter (Shungu Garaba) 14/ 27

15 Time duration Post processing for AC-S raw data NASA Protocol instrument report ( 1) merging the CTD with the ac-s 2) outliers were removed (subtracts surface data) Red: temperature Blue: depth 3) Temperature and salinity corrections 4) Scattering correction 15/ 27

16 Temperature and Salinity Correction ψ T, ψ S : dependency factor (Sullivan et al., 2006) The T and S influence to Red and NIR wavelength mainly 16/ 27

17 Temperature and Salinity Correction a, c: Raw data a-t, c-t: Temperature correction a-t-s, c-t-s: Salinity correction over 600 nm, correction applied suitably 17/ 27

18 Scattering Correction (Referred from NASA protocol ver 4 vol IV) Equation TS corrected a ε TS corrected b Based on the field measurements, laboratory experiments and theoretical calculations (Kirk 1992), the ε varies from 0.14 for Case 1 water and increases to 0.18 in waters were scattering is dominated by suspended sediments (Case 2 waters) Shows the systematic scattering offsets between true absorption and measured 18/ 27

19 Scattering Correction (Reference : NASA protocol ver 4 vol IV) λ NIR =730 (refer to 2015 Univ. Maine ocean optics) 19/ 27

20 Scattering Correction (Reference : NASA protocol ver 4 vol IV) Approximately 550nm has minimal absorption by particulate matter b p (554) is selected for examination of the relationship scattering and particle mass concentration Scattering corrected b p (554) shows better relationship Reference (Babin et al., 2003) 20/ 27

21 Preliminary results 21/ 27

22 PSD exponent Date year month 2015 Location Number of stations * ξ : PSD exponent Statio n ξ averaged ξ B B B B B B C C MP 17 C C C E F I J K TS E E EJS 9 E E E E E E E EJS Shows weak peak at 6~7um possibility of the particles of nano phytoplankton MP Data is slightly biased to fit the log-log data to the linearized Junge distribution due to dynamic populations in coastal water 22/ 27

23 C p exponent (γ) Date year month 2015 Location Number of stations 5 EJS 9 * γ : c exponent Station name γ E E E E E E E E E c p (λ) = c measured (λ) - a cdom (λ) a cdom (λ) derived from spectrophotometer γ shows 0.9~1.3 Normalized spectra by c p (554) show similar slope 23/ 27

24 Relationship between ξ and γ of EJS data Data shows non linear relationship Possibilities of difference with linear model Limitation of small dataset influence of min/max Wavelength # if specific groups of algae occupy a narrow range of sizes in bloom conditions, judicious choice of wavelengths with weak absorption to measure attenuation may improve the performance (Boss et al., 2001b) assumption of spherical particle assumption of non absorbing particle 24/ 27

25 Possibility of non linearity : absorbing particle Twardowski et al. (2001) Result of Mie calc. square : m p =1.02-0i Cross : m p =1.20-0i Circle : m p = i The only region where the ξ-3 relationship was maintained for ξ values between 3.5 and 4 (regardless n ) Boss et al. (2001b) we found absorption to affect mostly results in populations with large ξ (more small particles) 25/ 27

26 Discussion and Conclusion It is known that PSD can be described as Junge-type distribution The exponent of Junge distribution of MP and EJS data shows 4.17 and 4.29 (average value) It is known that the exponent of PSD (ξ) is linearly related with c p (γ) (Diehl and Haardt, 1980) We evaluate a theoretical model using EJS data shows nonlinear relationship possibilities of nonlinearity : choice of D min /D max, non spherical particle, absorbing particle Future works Through the Mie calculation, investigate the influence of shape and absorption property of particles Obtain more in-situ PSD and c p data of various particle composition samples 26/ 27

27 Thank you very much 27/ 27

28 Scientific Background: The Junge Distribution Christian Junge performed the first measurements of the size distribution and chemical composition of atmospheric aerosols (Junge, 1953; 1955; 1957; 1958; 1961; 1963) Characteristic of Junge distribution: 1) they follow a power law function over a wide range from 0.1 um to over 20 mm in particle radius. 2) The inverse power law exponent of the number distribution function ranged between 3 and 5 with a typical value of 4. Junge distribution. 28/ 27