Measurements and characterization of particle size ... - Wiley

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, C08024, doi:10.1029/2009JC005930, 2010

Measurements and characterization of particle size distributions in coastal waters R. A. Reynolds,1 D. Stramski,1 V. M. Wright,1 and S. B. Woźniak2 Received 19 October 2009; revised 26 March 2010; accepted 16 April 2010; published 25 August 2010.

[1] The particle size distribution (PSD) plays a central role in understanding many facets of the aquatic ecosystem, yet it is rarely measured in field studies and no single method provides a complete description of the PSD. In this study, size distributions of diverse particle suspensions were measured using a laser diffractometer (LISST‐100X), an electrical impedance particle sizer (Coulter Counter), and a particle imaging system (FlowCAM). All three instruments provided similar estimates of average particle size for suspensions of known standards. For broad polydisperse assemblages of particles a generally good agreement was found between the LISST and Coulter over a large portion of the size spectrum (from ∼1–3 mm to 50 mm), with the exception of suspensions exhibiting narrow features which were not accurately resolved with the LISST measurement. For featureless PSDs, however, the LISST provides an adequate proxy and has the capability for in situ measurements with high spatial and temporal resolution. We examined LISST field measurements from coastal regions within the context of a commonly used parameterization of the PSD. Analysis of nearly 5500 size distributions suggest that the average slope of the power law distribution for particles larger than 3 mm is −3.5. However, in many coastal waters this model provides a poor description of the PSD owing to the presence of significant peaks in the distribution. The combination of these data with Mie scattering calculations suggest that such departures from the idealized PSD can significantly impact the prediction of seawater optical properties. Citation: Reynolds, R. A., D. Stramski, V. M. Wright, and S. B. Woźniak (2010), Measurements and characterization of particle size distributions in coastal waters, J. Geophys. Res., 115, C08024, doi:10.1029/2009JC005930.

1. Introduction [2] Suspended particles are an ubiquitous component of natural waters, and play an important role in the biogeochemical cycling of elements and compounds within the marine environment. The size distribution of these particles is important to the structure and functioning of aquatic ecosystems, as it influences trophic interactions within the planktonic community. Particle size has a strong role in determining the differential sinking rates of various particle types, and thus determines horizontal and vertical fluxes of materials within the water column. The propagation of light in water is also strongly influenced by the absorption and scattering of particles, whose optical properties are largely dependent upon both the particle size and refractive index. [3] The particle size distribution (PSD) can be defined as the average number of particles within a given size class of

1

Marine Physical Laboratory, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, USA. 2 Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland. Copyright 2010 by the American Geophysical Union. 0148‐0227/10/2009JC005930

width DD for a unit volume of suspension [e.g., Jonasz and Fournier, 2007] N ð DÞ ¼ N 0 ðDÞDD;

ð1Þ

where N(D) is the average number of particles per unit volume in the size interval D ± 0.5DD. In this formulation, D represents the midpoint diameter of each size class. The measure of particle size can be expressed in different ways, such as particle volume, projected‐area, or diameter. Because the particle shape is usually unknown, D is often represented as that of a volume‐equivalent sphere. N′(D) represents the differential distribution per unit size, also referred to as the density function of the PSD. [4] Efforts to model light scattering and absorption within the ocean, and to partition optical contributions among different constituents of seawater, rely implicitly on some parametrization of the particle size distribution [e.g., Stramski and Kiefer, 1991; Twardowski et al., 2001]. Modeling studies suggest that the optically significant size range of particles spans the range from submicron colloids and nanoparticles [Stramski and Woźniak, 2004] to large particles oraggregates on the order of millimeters [Carder and Costello, 1994]. Measurements of the PSD generally resolve only a limited portion of this size range, and no studies exist which have measured the PSD over the entire optically relevant size

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REYNOLDS ET AL.: COASTAL PARTICLE SIZE DISTRIBUTIONS

range. In particular, measurements of the PSD in the submicron range are rare [e.g., Peng and Effler, 2007] and often controversial due to limitations of current techniques, despite the potential importance such particles are postulated to have on optical properties such as the backscattering coefficient [Morel and Ahn, 1991; Stramski and Kiefer, 1991; Ulloa et al., 1994]. Similarly, measurements for particles exceeding a few hundred microns in diameter, typically acquired using camera‐based systems, are rarely coupled with measurements of smaller particles [Jackson et al., 1997; Stemmann et al., 2008]. [5] Numerous approximations to mathematically describe the shape of the PSD have been proposed in marine systems, including power law models [Bader, 1970], Gaussian or log‐ normal distributions [Jonasz, 1983, 1987], and the gamma function [Risovic, 1993]. Given the diverse physical and biological interactions which influence particle dynamics in aquatic ecosystems, a single function is unlikely to adequately encompass all cases. The power law model, also known as the Junge distribution, is perhaps the most frequently used representation, and several studies have offered theoretical justifications for its applicability to suspensions of aquatic particles [Sheldon et al., 1972; Platt and Denman, 1978; Kiefer and Berwald, 1992]. The general form of this approximation can be used to describe an entire size distribution or selected portions N 0 ð DÞ ¼ k

D Do

;

ð2Þ

where Do is a reference diameter, k is the differential number concentration at Do, and −g is the slope of the distribution. Values of −g reported for marine particle assemblages typically range between −3.5 and −4,but values outside of this range are not uncommon [see Jonasz and Fournier, 2007]. The slope value is also likely to be sensitive to the range of the size distribution over which it is determined, as changes in slope as a function of size have been reported for marine particle assemblages [Kitchen et al., 1982; Jonasz, 1983; Loisel et al., 2006]. [6] Historically, microscopic examination of water samples was the primary way to determine overall particle concentration, and to provide estimates of the distribution of particles within various size classes. This method is too labor‐intensive to routinely analyze significant numbers of samples, as a large number of individual particles within each sample need to be counted and accurately sized in order to generate a statistically valid particle size distribution. A further drawback of this approach is the necessity to remove water samples from the natural environment, which generally must be preserved with a chemical fixative for storage until analysis. The enclosure of sample and subsequent manipulation can modify the particle assemblage from the natural state. Because the influence of enclosure and preservation artifacts varies from sample to sample, it is difficult to quantify and correct for such biases. Recently, the marriage of microscopy with digital image capture and processing techniques have made counting and analyzing large numbers of particles more rapid and automated [Moore et al., 2009]. A major advantage of imaging techniques is the ability to characterize particle shapes, and to identify and quantify specific types of particles.

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[7] Electrical particle counting instrumentation, such as the Coulter and the Elzone counters, was first developed for medical applications and subsequently introduced into marine sciences in the 1960s [Sheldon and Parsons, 1967]. The basic principle of this technique involves aspirating particles suspended in a conducting solution through a small orifice (aperture), across which an electrical field is generated. As particles pass through the aperture, changes in electrical resistivity owing to the displacement of electrolyte can be readily recorded and quantified. The change in impedance is directly proportional to the volume of the particle, and thus both the number and the volumetric size distribution of particles is determined. The electrical impedance technique is generally accepted as a standard method of analysis for determining particle size distribution in aquatic systems. It is accurate, can be easily calibrated with known standards, and yields high‐resolution measurements of particle size. Several thousands of particles within a water sample can be rapidly measured, permitting good statistical power. However, similar to microscopic techniques, it is laborious and requires the use of discrete water samples removed from the natural environment. There is also concern that shear forces operating near the aperture entrance may break up some particle aggregates, resulting in further modification of the particle size distribution [McCave, 1984]. [8] Optical approaches for determining the PSD can potentially minimize some of these shortcomings. The basis of such techniques is that the light scattering properties of particles are highly size‐dependent. Light scattering measurements can be recorded from a single particle or from an ensemble of particles in suspension, and some methods are amenable to in situ use without need for sample manipulation. Examples of these techniques include estimating particle size from the magnitude of light scattering at a nominal angle (e.g., flow cytometry), time‐of‐transition scanning particle counters, holographic imaging techniques, and laser diffractometry. Most of these approaches are based on optical models which utilize a mathematical inversion to estimate size from the observed scattering signal, and thus rely on assumptions concerning certain particle properties, such as shape and refractive index. Significant limitations may result from these assumptions, especially for polydisperse assemblages of diverse aquatic particles. [9] The LISST‐100X (Laser In Situ Scattering and Transmissometry; Sequoia Scientific, Inc., hereafter referred to simply as LISST) is a commercially available instrument which measures light scattering of a particle suspension at small forward angles, and utilizes this information to estimate the PSD [Agrawal and Pottsmith, 2000]. The basis of the inversion is optical diffraction by spherical particles significantly larger than the light wavelength, which is considered equivalent to diffraction by an aperture of equal size (Fraunhofer diffraction). The instrument has been shown to provide reasonable estimates of the PSD for particle suspensions of marine sediments [Gartner et al., 2001], laboratory phytoplankton cultures [Karp‐Boss et al., 2007], and natural particle assemblages from lakes and marine coastal waters [Serra et al., 2001; Ahn and Grant, 2007]. [10] In this study, we compare in detail measurements of the PSD obtained concomitantly with three instruments which utilize different sizing principles; a LISST, a Coulter counter, and a portable Flow Cytometer And Microscope

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system (FlowCAM). Intercomparisons are made on well‐ defined suspensions created in the laboratory and field samples collected from the natural environment. In addition to identifying and counting distinct populations of known size, our interests lie in characterizing the size distribution of polydisperse particle populations over a broad size range. A second objective of our study is to examine variability in the magnitude and shape of the particle size distribution in marine coastal waters. In situ and laboratory measurements of the PSD from the LISST are analyzed within the context of the commonly used power law parameterization. Utilizing Mie scattering calculations, we examine how departures from these idealized approximations of the PSD potentially influence predictions of the optical properties of seawater.

2. Materials and Methods 2.1. Suspensions and Measurements [11] For direct comparisons, experiments were conducted on well‐defined particle suspensions prepared in the laboratory or with natural seawater samples collected from the marine environment. In all experiments, a well‐mixed, master solution was first prepared, then subsamples of this solution were apportioned for simultaneous analysis of particle size by the different instruments. 2.1.1. Microsphere Standards [12] Polystyrene latex microspheres of varying diameter were obtained from three commercial sources; Beckman‐ Coulter, Duke Scientific, and Polysciences. Microsphere sizes were certified by the manufacturer and are NIST‐ traceable. Experiments were conducted on nearly monodisperse suspensions (i.e. exhibiting a narrow, well‐defined peak in the size distribution) consisting of microspheres of varying nominal size (1, 2, 5, 10, 20, 50, and 100 mm), as well as suspensions created by mixing microspheres of different sizes. All stock solutions of microspheres were first sonicated to minimize aggregation, diluted in seawater filtered multiple times through a 0.2 mm Nuclepore membrane filter, and maintained in suspension by continuous stirring. 2.1.2. Plankton Cultures [13] Biological particles often deviate from ideal spheres, and generally have a lower refractive index than manufactured standards. Monospecific cultures of marine phytoplankton grown in enriched seawater media were also used as test suspensions for comparison. Cultures were harvested in late log phase of growth, and thus the suspensions contained cell debris and detritus in addition to live cells. Species included in these tests were Dunaliella tertiolecta (Chlorophyceae), Thalassiosira weissflogii (Baccilariophyceae), Emiliana huxleyii (Prymnesiophyceae), and Akashiwo sanguinea (Dinophyceae). 2.1.3. Field Samples [14] Natural seawater suspensions contain a diverse mixture of particle sizes, shapes, and composition. Surface seawater samples from near‐shore environments were collected at 1–2 m depth either at the Imperial Beach Pier (IBP) or Scripps Institution of Oceanography Pier (SIOP) in San Diego, California, over a period encompassing June 2005 to July 2007. The Imperial Beach Pier measurements were conducted approximately bi‐weekly over a 1.5 year period, and thus exhibit large seasonal variability in particle concentration and composition of the assemblage. Samples were

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transported back to the laboratory, and analyses of particle size distribution were conducted on unpreserved samples within two hours after collection. Additional field experiments comparing the LISST and Coulter counter were conducted within the coastal Pacific waters of Santa Barbara Channel in September 2008 as part of the ONR program entitled Radiance in a Dynamic Ocean (RaDyO). We note that although sample collection and manipulation may have altered the particle community from its natural state in situ, all PSD measurements on discrete water samples were done on the same sample at the same time and are thus directly comparable. [15] To examine possible artifacts arising from sample manipulation, we conducted additional experiments from the Scripps Pier in which LISST observations of the PSD were obtained in situ at the time of water collection. The instrument was suspended in water at a depth of 1–2 m, and measurements were recorded for a 10‐min. period. During this time, several carboys of water were filled for transport to the lab where 70L of collected water were used to fill a cylindrical tank with a depth of 1.25 meters. The tank was stirred continuously throughout the experiment to minimize settling. PSD measurements were repeated with the LISST by suspending the instrument within the tank and again averaging data over a 10 minute period. During this time, a subsample of water was removed from the tank for measurements with benchtop instrumentation. 2.2. Coulter Counter Measurements [16] The particle size distribution was measured with a Beckman‐Coulter Multisizer III analyzer using 0.2 mm filtered seawater as the diluent and blank. The range of size and its resolution with this instrument is determined by the size of the aperture used for measurement, with the measured size range approximately 2–60% of the aperture diameter. For particle assemblages with a limited size range, an aperture tube of appropriate size was chosen to provide the best resolution of the sample. For natural seawater samples, an aperture tube with a diameter of 100 mm was typically used. In some experiments, data were collected from multiple aperture sizes (e.g., both 30 mm and 200 mm apertures) and merged into a single size distribution. Each aperture of the instrument was calibrated using microsphere standards following the manufacturer’s procedure. [17] Each discrete PSD measurement consisted of a set of values representing the number of particles per unit volume within each size class, N(D), where D represents the diameter of a volume‐equivalent sphere for the midpoint of each individual class. Size classes consisted of 256 bins logarithmically spaced over the measured range, ensuring a very high size resolution of measurements. The width of individual size bins is dependent upon the aperture size and diameter of the size class; for example, DD ranges from as little as 0.01 mm for a 30 mm aperture (D = 0.8 mm) to as large as 1.6 mm for a 200 mm aperture (D = 119.2 mm). For each sample, a minimum of three replicate measurements of PSD were taken, each consisting of measurement on a subsample ranging in volume from 0.05 ml to 2 ml depending on the aperture used. For the analysis of natural seawater samples, larger volumes (several ml with a 20 mm aperture to 200 ml with a 200 mm aperture) were often examined by increasing the number of replicates and sum-

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ming the results. Blank measurements on 0.2 mm filtered sample were always taken at least in triplicate and averaged. Replicate measurements were blank‐corrected and averaged to yield the final estimate of N(D). [18] The distribution of particle volume, V(D), was calculated from the numerical size distribution by assuming the midpoint of each size class as representative of the particle volume‐equivalent diameter within each size class V ð DÞ ¼ N ð DÞ

D3 : 6

ð3Þ

2.3. LISST Measurements [19] The LISST estimates the size distribution of an ensemble of particles using forward scattering of a laser beam measured with a series of 32 annular detectors, spanning the approximate angular range 0.08–13.5° in water, over a pathlength of 5 cm. An additional photodiode detector at 0° (angle of acceptance equals 0.027°) records transmitted light, from which the beam attenuation coefficient of particles, cp, can be calculated. [20] The angular pattern of optical scattering is used to calculate the particle volume concentration, V(D), in 32 size classes through an inversion algorithm which utilizes a kernel matrix derived from the Mie solutions of scattering by homogeneous spheres [Agrawal and Pottsmith, 2000]. The midpoint and width of the size classes increase logarithmically with diameter. The instrument used in this study was customized to utilize a 532 nm laser, as opposed to the 670 nm laser normally provided with the instrument. This wavelength was chosen for consistency with other scattering instruments in our laboratory, and because it represents a spectral region of low particle and chromophoric dissolved organic matter (CDOM) absorption. The effective particle size range measured with this laser is 1.05–198.6 mm, with the width of individual size classes varying from 0.2 to 30.3 mm over this range. [21] The LISST was used for in situ measurements, in the experimental tank, and in benchtop mode for analyzing discrete water samples in the laboratory. For the latter, a sample chamber equipped with a magnetic stir bar was inserted into the optical head of the instrument. Following cleaning of optical surfaces, sample was gently introduced to the sample chamber to minimize bubble formation and the chamber was shaded with black cloth to minimize any influence from ambient light. Sample measurements consisted of 1000–1500 repeated scans collected at 1 Hz frequency. Blank determinations were made by measuring 0.2 mm filtered seawater in an identical manner as samples, and subsequently subtracted from the sample measurements. This procedure yields results representative of particles only, and also corrects for any contribution of CDOM absorption in the sample. [22] The particle volume concentration in a given size class, V(D), was calculated using manufacturer provided software and calibration. We observed significant fluctuations in the power output of the laser during the initial period of measurement, and thus the first 150 measured scans were rejected from analysis. The remaining data were averaged to produce the final volume distribution, and the particle number distribution was calculated from the relation described in equation (3).

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2.4. FlowCAM Measurements [23] For selected experiments, additional estimates of the PSD were obtained with a portable FlowCAM system (Fluid Imaging Inc.). The FlowCAM images particles in two dimensions through a standard microscope objective lens as they pass through a glass flow chamber [Sieracki et al., 1998]. In the present measurements, an objective lens of 20X magnification was utilized and sample was pumped through a 2.0 × 0.1 mm flow chamber at a rate of approximately 0.3 ml min−1, permitting measurement of particles in the approximate size range of 5–100 mm. Whereas FlowCAM is known to be a powerful technique for imaging and identification of relatively large particles (>15 mm [e.g., See et al., 2005]) in cultures or in natural samples, our interest was to determine whether this technique can provide a quantitative estimate of the PSD over the entire measured size range. [24] In our experiments, image acquisition was triggered by detecting forward scattering (5°) of a 532 nm laser beam from particles, digitized, and stored electronically. A typical sampling run imaged and recorded 1500–2000 particles, and image analysis software provided with the instrument was used to count and size each particle. Particles were identified by distinguishing them from the image background, and the size of each identified particle was estimated in two ways. One approach was based on determining the particle cross‐ sectional area from summation of the total number of pixels occupied by a particle, followed by conversion to equivalent spherical diameter. The second calculation was of the particle Feret diameter, which is the maximum chord length that can be drawn between any two points along the particle boundary. All data reported here represent the calculated Feret diameter. Measurements of individual particles were binned into size distributions at a size resolution of 1 mm. 2.5. Additional PSD Calculations [25] Because the width of each size class, DD, varies within and among instruments, differential functions of the PSD were computed to facilitate direct comparisons. These distributions were calculated by dividing the measured concentration in each size class by the width of the class, and are denoted by N′(D) and V′(D) for the number and volume distributions, respectively. [26] Percentile statistics are one way to characterize and compare size distributions, and can be calculated from the various measures of particle size (e.g., volume or projected‐ area). Here we report principally median particle diameters (50th percentile) of the volume distribution, D50 V . Total particle concentrations, in terms of both number and volume, within a given size interval were calculated by summing the appropriate quantity in each size class contained within the limits of the size range.

3. Results and Discussion 3.1. Laboratory Intercomparisons of Sizing Instruments 3.1.1. Microsphere Size Standards [27] The instruments employed in our experiments utilize different principles for determining particle size and have different resolution capabilities, thus some differences in the

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Table 1. Comparison of Particle Diameters Derived From Laboratory Measurements on Nearly Monodisperse Suspensions of Polystyrene Microspheres Obtained From Various Manufacturersa Coulter

LISST

FlowCAM

Manufacturer

Nominal Diameterb (mm)

Modal Range (mm)

D50 V (mm)

Modal Range (mm)

D50 V (mm)

Modal Range (mm)

D50 V (mm)

Polysciences Polysciences Beckman‐Coulter Beckman‐Coulter Beckman‐Coulter Duke Scientific Duke Scientific

0.97 ± 0.01 2.10 ± 0.03 5.07 ± 0.14 9.93 ± 0.26 20.18 ± 0.54 49.7 ± 0.7 99.5 ± 1.5

0.98–0.99 2.06–2.09 5.00–5.07 9.85–9.98 20.18–20.45 49.93–50.60 99.63–100.97

1.16 2.15 5.08 9.92 20.08 49.85 99.52

1.05–1.24 2.74–3.23 5.28–6.23 8.65–10.20 19.72–23.27 44.98–53.08 87.00–102.67

n.d. 2.18 3.70 8.71 18.82 46.02 92.15

5.5–6.5 8.5–9.5 18.5–19.5

5.68 8.39 18.68

a For all three instruments, the reported diameters represent the modal diameter (range of size bin) and the median particle diameter calculated from the measured particle volume distribution, D50 V . The abbreviation n.d. indicates that the median value could not be determined from the volume distribution. b For Beckman‐Coulter standards, the nominal diameter reported by the manufacturer represents the median number diameter. For Polysciences and Duke Scientific, this nominal diameter represents the mean number diameter.

PSD and derived statistical descriptors are expected. Measurements with particles of known size, shape, and composition permit a direct comparison of the different approaches. The range of microsphere standards examined in our experiments span a range in diameters from 1 to 100 mm (Table 1); Coulter and LISST measurements were obtained on all suspensions, while FlowCAM measurements were done on only a subset of these experiments. For solutions comprised of a single microsphere standard, all three instruments generally provided measures of average particle size (e.g., modal or median diameter) similar to each other and that agreed well with the reported size of the standard. The largest differences between the LISST and the Coulter were observed in the size range D < 10 mm, where particle size approaches the lower measurement range of the LISST. The peak of the 1 mm sample lies outside of the LISST measurement range and could not be resolved by the instrument. We note that in Table 1, the seemingly good value of the median diameter obtained by the LISST for the 2 mm bead suspension is spurious because of an artifactual sharp increase in the PSD for the smallest size classes, which skews the distribution and influences calculation of the median diameter. This behavior was often seen in measurements on suspensions of microspheres with diameters of 10 mm or less (Figure 1), and is discussed in more detail in a later section. [28] The corresponding volume distributions for these suspensions are depicted in Figure 1. The data in Figure 1 have been normalized to the concentration of the modal peak to facilitate comparison of the shape of the PSD. The Coulter counter results illustrate its accuracy and very high capability for resolving narrow peaks in the distribution. With the exception of the smaller particle sizes, the LISST also accurately identified individual peaks in each suspension. Both the FlowCAM and the LISST have lower size resolution of the individual size classes (i.e. larger DD) as compared to the Coulter, and the derived distributions are much broader. For example, the measured Coulter distribution for the 10 mm microsphere suspension exhibits a concentrated narrow peak representing the population. Smaller secondary modes corresponding to particle aggregates (doublets and triplets) are also discernible, although in terms of volume their concentration represents only ∼5% of the singlet peak. Such small scale features are not capable of being resolved with the LISST, and instead are represented by a single broader peak in the distribution which is five times

the width of the singlet peak determined with the Coulter. For experiments with microsphere D ≥ 10, the ratio of the computed full‐width‐half‐maximum (FWHM) length to the modal diameter is 2.0% and 34.3% for the Coulter and LISST, respectively. This coarser resolution implies a limited ability of the LISST to discriminate individual populations of similarly sized particles in a mixed suspension. [29] This limitation is illustrated by an experiment in which a polydisperse suspension was created by mixing microspheres of varying size. When measured individually, the populations are readily resolved with the LISST (Figure 2), but the identification and quantification of separate populations is difficult when measured as a mixture with the same individual concentrations. Instead, the resulting size distribution suggests the presence of a broad bimodal peak which spans the range of the three populations. This results as a consequence of a relatively coarse size resolution in combination with a smoothing effect of the inversion algorithm. 3.1.2. Plankton and Seawater Samples [30] Naturally occurring suspensions rarely consist of particles with uniform size, shape, or composition, and thus comparisons were also conducted on plankton cultures and natural seawater samples. Figures 3 and 4 provide examples of particle size distributions, depicted in terms of both particle number (Figures 3 (left) and 4 (left)) and volume (Figures 3 (right) and 4 (right)), measured for phytoplankton cultures and natural seawater samples. Unlike Figure 1, these data have not been normalized and depict quantitative particle concentrations per unit volume and per unit size. [31] As expected for biological particle populations, algal suspensions were characterized by a broader modal peak than typically observed for artificial standards, and the size distributions may exhibit secondary peaks and other features. Comparable estimates of particle size were observed among the three instruments for these suspensions; for example, modal diameters of the population usually agreed to within 20%. Although shapes of the PSD were generally similar, differences in resolution among the instruments were apparent in the results. For example, the presence of a multimodal population of particles was observed in the culture of A. sanguinea using the Coulter and FlowCAM, with the dominant peak occurring at about 30 mm and a smaller, secondary peak discernible at 45 mm (Figure 3). These populations are interpreted as a single broad peak by the LISST, with a maxima centered between the two populations at 41 mm.

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Figure 1. Particle volume distributions for suspensions of polystyrene microspheres measured with a Beckman‐Coulter Multisizer III, a LISST‐100X, and a Fluid Imaging FlowCAM. To facilitate comparison of shape, each distribution has been normalized to a value of 1 for the modal peak. Vertical dashed lines indicate the certified nominal diameter of each microsphere as reported by the manufacturer. FlowCAM measurements are illustrated for 5.07, 9.93, and 20.18 mm microspheres only. Both the LISST and Coulter size distributions also suggest sharp increases in concentration in the smaller size regions (∼3 mm), which likely indicates the presence of significant amounts of cellular debris and other detritus in this particular culture. [32] Measured size distributions from two surface seawater samples representing natural polydisperse suspensions of particles are depicted in Figure 4. One example was obtained from Scripps Pier in midsummer, while the other example is from a station in the Santa Barbara channel occupied in late summer. The size distributions in these samples display the characteristic shape of natural water samples, in which the overall trend is for particle number to rapidly decrease with

increasing particle diameter. Both samples, however, also exhibit the presence of multiple peaks in the data corresponding to local increases in particle populations. Analyses of the total dry mass concentration of suspended particles and concentration of particulate organic carbon suggest that the particle assemblages in both locations at these times were principally composed of organic particles, contributing more than 80% to total particle mass. Chlorophyll concentrations for these samples were typical of Southern California coastal waters during these time periods, between 1–2 mg m−3. [33] For the Scripps Pier sample, measurements of the PSD were obtained with all three instruments, with data from the LISST obtained both in situ and in benchtop mode

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Figure 2. Particle volume distributions measured by the LISST for three individual microsphere suspensions (open symbols). The mixed suspension (solid circles) was created by combining the three individual suspensions at the same concentrations as depicted for the individual size distributions. using discrete water samples. The measured PSDs indicate the presence of two major populations of particles, one in the diameter size range of 4–7 mm and another located near D = 30 mm, superimposed on the overall trend of decreasing particle concentration with size. Because of this wide separation in size, all three instruments could readily resolve the two populations.

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[34] A remarkably good agreement in both shape and magnitude of the measured PSD is observed between the Coulter and LISST laboratory measurements on the discrete water sample. When integrated over a similar size range, the calculated volume and number concentrations determined with the two instruments agree within 5%. However, the PSD determined from in situ LISST measurements exhibited an anomalous behavior in the smaller size classes as compared to the laboratory measurement, with a large trough in the distribution apparent at 2.2 mm. Subsequent experiments, described in the next section, identified the cause of this phenomenon as stray light contamination of the measured optical signals occurring at large scattering angles, leading to errors in the calculated PSD. [35] Throughout most of the size distribution, the FlowCAM yielded significantly lower particle concentrations than the LISST or the Coulter. This pattern was consistently observed in all experiments, including microsphere suspensions and plankton cultures (Figure 3). For particles of 25 mm diameter, particle counts obtained with the FlowCAM were generally 30–40% lower than those obtained with the Coulter, and this underestimation increased as particle diameter decreased. The FlowCAM measurements were routinely done using detection of light scattering or chlorophyll fluorescence as a trigger for image acquisition, and our findings suggest a low efficiency at detecting particles when operated in this mode. Other experiments (not shown) indicated that autotrigger mode, in which the sample is regularly imaged at several frames per second, provides concentration estimates more in agreement with the LISST

Figure 3. Particle size distributions of two phytoplankton cultures as measured with three different instruments. Differential distributions per unit size are depicted for both (left) particle number (N′(D)) and (right) particle volume (V′(D)) concentration. 7 of 19

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Figure 4. Example particle size distribution measurements of surface seawater samples collected from (top) Scripps Pier and (bottom) the Santa Barbara Channel. Differential distributions per unit size are depicted for both (left) particle number and (right) particle volume concentration. For the Santa Barbara data, the close agreement between in situ and laboratory LISST measurements make the two curves difficult to distinguish. and the Coulter. This latter mode works well for dense particle suspensions such as plankton cultures, but is impractical for dilute suspensions such as those typically encountered in seawater because of the length of time required to count a sufficient number of particles to ensure statistical accuracy. [36] Multiple peaks in the size distribution were also observed with the Coulter counter for the Santa Barbara Channel sample (Figure 4). In contrast to the Scripps Pier sample, however, these peaks are separated by diameters of only a few mm. A large, dominant peak in the PSD is evident at 2.9 mm, with smaller peaks appearing at 1.3 and 4 mm. In order to identify and resolve such features in the small particle range, the use of a small aperture (30 mm) covering a narrow size range was necessary to complement the broader size range data obtained with a larger aperture tube (in this example, 200 mm). Similar to the previous examples, these narrowly spaced peaks are not resolved by the LISST, and instead are represented by a single peak. In this experiment, the in situ LISST measurement was made with the optical end of the instrument enclosed within a dark rubber cylinder, which significantly reduced the effects of ambient light on the scattering signal and associated artifacts at the lower end of the examined size range. As a result, the in situ estimates of the PSD from the LISST do not show the artifactual feature for the small size classes and agree well with discrete laboratory estimates of the PSD from the LISST and the Coulter.

3.1.3. LISST Artifacts in the PSD [37] An apparent minimum in a few small size classes, preceded by a sharp increase in the particle concentration at the smallest end of the size spectrum, was often observed in the LISST‐derived size distributions (e.g., Figure 4 (top)). This behavior was not evident in the Coulter data, and represents an artifact in the LISST‐derived estimates of size. [38] We observed that these effects were most pronounced for in situ measurements of near‐surface waters. Figure 5 depicts results from five experiments in which particle size distributions were first measured in situ at a depth of 1– 1.5 m, then re‐measured back in the laboratory on water collected at the time of in situ measurement. In all of these experiments, a large decrease in the in situ PSD is apparent at ∼2 mm, generally coupled with a rapid increase at smaller diameters. These features are absent in the laboratory measurements where the illumination of the instrument with ambient light was eliminated. [39] Simple experiments were conducted in the field to examine potential sources of this behavior. In situ variability of detector dark currents was assessed by occluding the detector window during vertical profiles in the water column. The dark counts recorded on each ring detector were observed to be small ( 0.99), with a median difference of 13.5%. Similar results are observed for the integrated number distribution. [47] In addition to total concentration, we compared common descriptors of the PSD such as the median particle diameter calculated from the volume distribution (Figure 7b). For both monodisperse and polydisperse suspensions, a reasonably good correspondence was observed over the measured range of particle sizes. On average, the LISST underestimates the Coulter value by about 11%. This may partially result from the coarser resolution (larger size bins) of the LISST. [48] Despite utilizing different principles, our results suggest that the LISST and the Coulter counter generally provide consistent agreement in determinations of both particle

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Figure 8. Location of coastal sampling stations for two cruises: (top) Monterey Bay, California (MB06) and (bottom) Baltic and North Seas (OC07). size and concentration. In particular, measurements on polydisperse field samples were highly correlated in terms of particle size and concentration estimates. These results suggest that the LISST can provide reasonable estimates of the in situ particle size distribution within natural waters, particularly when the PSD is generally monotonic and featureless. Under such conditions, the high size resolution required to distinguish and separate any narrow population peaks is not critical. It should also be noted that in certain scenarios which violate the underlying assumptions of the optical inversion, for example situations in which highly nonspherical particles dominate the assemblage, the LISST may provide inaccurate data on particle size [Karp‐Boss et al., 2007]. 3.2. Characterization of the PSD With In Situ LISST Measurements [49] In addition to samples collected in southern California coastal waters, in situ LISST measurements of particle size distributions were obtained on two field expeditions (Figure 8). The first (MB06) was conducted in Monterey Bay, California during the period 04–15 September 2006 as part of a NOAA Coastal Ocean Applications and Science Team experiment [Davis et al., 2007]. Stations were located in the central and NE portion of the Bay, and strong algal blooms, with surface chlorophyll a concentrations exceeding 300 mg m−3, were observed at some locations. Particle assemblages sampled during this cruise were largely dominated by biogenic parti-

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cles, with organic material contributing on average 80% to the total particulate mass in the top 10 m of the water column. [50] A second expedition on the research vessel Oceania (OC07) sampled European coastal waters during the period 31 August to 13 September, 2007. The cruise track encompassed a series of stations from the SW portion of the Baltic Sea, through the Danish straits of Kattegat and Skaggerak, and into the eastern North Sea (Figure 8). In contrast to Monterey Bay, locations sampled encompassed a larger variety of particle assemblages. In the Baltic, biogenic particles dominated the particle assemblage on a mass basis. In portions of the N. Sea and the two Straits, however, this situation was reversed and inorganic particles contributed 60–80% of the particle mass. [51] On both cruises, in situ vertical profiles of the particle size distribution were obtained by lowering an instrument package containing the LISST through the water column at a vertical speed of 10–15 m min−1. A single profile was obtained at each station. LISST measurements of angular scattering intensity and beam transmission were median filtered and averaged into half‐meter depth bins (generally 4–5 measurements per bin). The depth‐averaged scattering signals were then processed with manufacturer’s software to calculate vertical profiles of the particle size distribution and the particle beam attenuation coefficient at 532 nm, cp(532). Metrics describing the size distribution at each depth were calculated from the data, such as integrated particle concentration and median particle diameter. [52] Because data from these two cruises were collected before identification of the issue involving stray light contamination of the scattering signal, the instrument was deployed unbaffled and thus the near‐surface data are subject to the previously described artifacts in the derived size distributions. Examination of this data indicated that the stray light effect on the PSD was usually confined to the first seven size bins (D < 3.2mm), and we therefore chose to remove this size range from consideration in the subsequent analyses of LISST field data for this study. This effectively reduces the range of the LISST‐measured PSD to 3.2–198.6 mm. 3.2.1. Spatial Variability [53] Figure 9 depicts a summary of measured size distributions collected in surface waters (5 m depth) for all locations. Particle number concentrations span a 33‐fold range for the combined data set, ranging from 0.265 to 8.709 × 1010 m−3. The concentration of particle volume exhibits an even greater variability, 0.67 to 168.4 ppm. The largest range was observed in Southern California waters collected from Imperial Beach and Scripps Pier, which contain both the minimum and maximum of our observations. [54] A diversity of shapes in the PSD is evident among surface waters in our data set. Some size distributions are relatively featureless, and these were generally associated with waters located furthest offshore, or samples containing little organic material (e.g., N. Sea or winter IBP samples). However, a large percentage of the distributions, particularly ones with a high contribution of organic material, exhibit the presence of one or more strong peaks in the distribution. These peaks are associated with the presence of distinct plankton populations, and thus the location of these peaks differs among samples dependent upon locale. [55] Vertical gradients in the PSD were also observed at most sampling sites. Figure 10 depicts measured vertical

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Figure 9. (left) Particle number and (right) volume concentrations measured at 5 m depth with the LISST for various coastal environments. structure at two locations, one from each of the expeditions. Station 017 is the northernmost location in Monterey Bay depicted in Figure 8, and had a water depth of approximately 20 m. Warming of surface waters resulted in a weakly stratified upper mixed layer of 12 m depth, in which the vertical distribution of chlorophyll a fluorescence exhibited a broad maximum. Measurements on discrete water samples confirmed the presence of high chlorophyll in this layer, with concentrations exceeding 46 mg m−3. Gravimetric and chemical analyses indicate that 80% of particulate material by mass was organic. The particle beam attenuation coefficient at 532 nm, cp(532), had a sharp maxima of 5 m−1 near the bottom of the mixed layer, then declined with increasing depth. [56] Particle size distributions at this station were characterized by a distinctive large peak centered at 49 mm (FWHM 35–75 mm), an interval consistent with the general size range of the dinoflagellate A. sanguinea, the species identified as the dominant contributor to red tide blooms

during the study period. A smaller population of 4–5 mm particles was also evident in the spectra, but contributed only a small (1%) amount to total particle volume. The vertical distribution of cp was closely mirrored by total particle concentration, VT, calculated as the integral of particle volume between Dmin = 3.2 mm and Dmax = 198.6 mm. In contrast to these two parameters, the median particle diameter D50 V exhibited a broader maximum which extended downward through the mixed layer, indicating a significant proportion of large cells on both sides of the density gradient. Such an observation is consistent with previously described behavior of dinoflagellates, which are known to migrate vertically within the water column. [57] Station 028 from the Oceania cruise was located in the southeastern part of the North Sea, near the outflow of the Elbe River. A strong gradient in both temperature and salinity was observed to separate a layer of cooler, fresher water in the upper 19 m from underlying waters. Chlorophyll a concentrations in the surface layer were 15 mg m−3,

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Figure 10. Vertical distributions at two locations of fluorescence from chlorophyll a, the particulate beam attenuation coefficient at 532 nm, integrated particle volume within the size range 3.2 to 198.6 mm, median particle diameter, and the average particle attenuation per unit particle volume. The two stations depicted are MB06 station 017 (Lat. 36° 56.81′N, Lon. 238° 03.26′E) and OC07 station 028 (Lat. 54° 08.38′N, Lon. 7° 59.42′E). about 70% lower than those observed in the depicted Monterey Bay station. Uniform attenuation was observed throughout the upper layer with a minimum occurring in the pycnocline, and increasing again with depth below this gradient. Total particle volume and median diameter were much smaller than observed in the station from Monterey Bay. [58] The observations at these stations are consistent with the generally accepted notion that, to first order, beam attenuation is largely dependent upon particle concentration. However, the observed attenuation per unit concentration is very different between these two stations. This can be examined by computing the mean attenuation per unit particle volume, cp(l)/VT. It should be noted that cp includes the contribution of all particles greater than 0.2 mm, while VT is calculated from the size range 3.2–198.6 mm, and thus the volume‐specific attenuation for this size range is to some extent overestimated. However, the contribution of particles in the size range 0.2–3.2 mm to total volume is expected to be small, leading to only a small error in this quantity. [59] The calculated values of cp(532)/VT for the Monterey Bay station average 0.2 m−1 ppm−1 in the surface, with a slight (15%) decrease observed at the particle maximum and below (Figure 10). Surface values from the N. Sea station,in contrast, are ∼50% higher than those calculated for Monterey Bay, and a distinct maximum is evident within the pycnocline. The contribution of organic matter to total particle mass was similar for both stations (∼75%), suggesting that large differences in average particle refractive index are unlikely. The observed differences in cp(532)/VT between the two stations likely reflect some combination of

changes in the relative contributions of small and large particles to beam attenuation, differences in particle shape, or package effects arising from particle aggregation [Boss et al., 2001, 2009]. 3.2.2. Performance of Power Law as a Model of the PSD Shape [60] Models for seawater optical properties frequently use a power law approximation of the PSD (equation (2)) [Stramski and Kiefer, 1991; Boss et al., 2001; Twardowski et al., 2001]. In situ measurements of the PSD obtained from the MB06 and OC07 cruises were examined within the context of this model. The combined data set, representing vertical profiles measured at all stations, results in 2408 and 3074 individual PSDs for each cruise, respectively. For each size distribution, particle number concentration, N′(D), as a function of diameter D over the range 3.2–198.6 mm was fit to the model described in equation (2). Calculations were done using least‐squares minimization on the log‐transformed data of each distribution. The coefficient of determination for the fitted regressions using the log‐transformed data was always high, generally ≥0.95. [61] Figure 11 illustrates the frequency distribution of the power law exponent −g obtained for each cruise. The mean values of the power law exponent are remarkably consistent for both MB06 and OC07, −3.46 and −3.47 respectively. The OC07 distribution is broader with a standard deviation nearly twice that of MB06. The larger variability observed in this data set may result from a greater diversity of station types sampled on this cruise, as the majority of stations sampled in Monterey Bay were dominated almost exclusively by populations of large plankton cells.

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Figure 11. Frequency distribution of the power law exponent −g (equation (2)) for particle size distributions measured on (a) MB06 and (b) OC07 cruises. The data include all depths of sampling, and the total number of observations n for each cruise is shown. [62] Previous studies in oceanic waters have reported a similar range in −g [e.g., Stemmann et al., 2008], with a central value of −4 typically used for modeling the PSD in oligotrophic waters. Values of −4 were measured in only a small subset of our data, and were primarily associated with stations located the furthest offshore and thus the most oceanic in nature. The majority of our data exhibit larger values of −g over the measured size range, suggesting that coastal waters on average have a shallower slope than offshore oligotrophic waters. This is consistent with the observation that larger particles are generally more prevalent in coastal particle assemblages, owing to the presence of larger planktonic species, particles of terrestrial origin, or resuspended bottom materials. [63] Despite the high values of the determination coefficients obtained when fitting the log‐transformed data to the linearized power law model, examination of the residuals indicates that for any given PSD, significant deviations can occur between the observed and fitted data. For each PSD in the data set, we calculated the normalized bias (NB) in percent for each size class, NB(D) = 100 × (P(D) − O(D))/O(D), where P(D) and O(D) represent the predicted and observed number concentration, respectively. Figure 12 illustrates the median values of the observed biases as a function of diameter for each of the two cruises. With the exception of the largest size class, the average biases are less than 25% and can be positive or negative. Certain regions of the size

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distribution are systematically under‐ or overestimated by the power law fit; for example, in Monterey Bay the power law often underestimates the concentration of particles in the 4 and 30 mm size range,while overestimating concentrations in the 10 mm size range. Finally, it should be noted that any given PSD can have much higher biases than indicated by Figure 12, in some cases concentrations within a given size class were observed to be in error by nearly three orders of magnitude. These situations were almost always associated with distinctive peaks in the PSD, resulting from local blooms of a given plankton population, which are not captured by a power law description. [64] An interesting application of these deviations from a power law model is the use of residuals to identify distinctive particle populations and to examine their distributions in the water column. As an example, Figure 13 illustrates the vertical distribution of the normalized bias in each size class for the Monterey Bay station depicted in Figure 10. Application of the power law model leads to a significant underestimation of particle concentration in the size range around 50 mm, and this bias is particularly strong near the base of the upper mixed layer coincident with high dinoflagellate concentrations. Such information can, in principle, be used to identify the vertical location of individual particle populations which create discernible peaks in the PSD. [65] Although the power law model with a single slope over a broad particle size range provides a convenient empirical descriptor of the PSD, we conclude that it often fails to capture the complexities of the PSD prevalent in dynamic particle populations such as those found in coastal and nearshore waters. These dynamics include processes such as local blooms of individual populations, which result in deviations from the general “background” trend of increasing particle number with decreasing size. Recent studies of minerogenic particles within freshwater lakes and rivers have also concluded that the power law model provides a poor descriptor of the size distribution for this

Figure 12. Median values of the normalized bias, in percent, as a function of particle diameter for the power law model. The normalized bias was calculated as NB = 100 [(P(D) − O(D))/O(D)], where O(D) represents the observed concentration for a given size class D and P(D) is the concentration predicted by the model. Shown are the results for the MB06 and OC07 cruises.

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Figure 13. Contours of the normalized bias (NB as defined in Figure 12) as a function of depth and particle diameter for the Monterey Bay station depicted in Figure 10. component of the particle assemblage, and that use of this model strongly influences estimates of particle optical scattering and optical variability in these environments [Peng et al., 2007, 2009]. 3.3. Implications for Optical Modeling [66] For a given light wavelength in vacuum l, the spectral absorption, a(l), scattering, b(l), and attenuation, c(l) = a(l) + b(l) coefficients of seawater strongly depend upon both the size distribution of suspended particles and their refractive index. Forward optical models attempt to predict seawater optical properties and radiative transfer within the ocean from detailed knowledge of the particle assemblage concentration and composition [e.g., Mobley and Stramski, 1997; Stramski et al., 2001; Babin et al., 2003]. Similarly, inversions of optical data and models can be used to derive information on the particle assemblage [Twardowski et al., 2001; Boss et al., 2001; Sullivan et al., 2005; Kostadinov et al., 2009]. Because the PSD is rarely measured in such studies, it is generally modeled using empirical formulations with varying degrees of complexity. Our measurements in coastal waters suggest that departures from these idealized models occur frequently. [67] The spectral beam attenuation coefficient of particles in a suspension, cp(l), can be considered as the product of particle number concentration, the mean particle projected area G, and the mean dimensionless efficiency factor for attenuation, Qc(l) cp ðÞ ¼ N ð DÞG Qc ðÞ ¼ N ð DÞc ðÞ:

ð4Þ

The bar above the symbols indicate that these quantities represent a hypothetical mean particle derived from a polydisperse population, and the product G Qc denotes the

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mean attenuation cross‐section, c. The efficiency of light attenuation is a function of both particle size and refractive index, and thus changes in the PSD influence c and cp in two ways; directly through G and indirectly through influencing Qc [e.g., Stramski and Reynolds, 1993]. Similar relatioqnships can be written for other inherent optical properties, including the spectral absorption, ap(l), and backscattering, bbp(l), coefficients of particles. [68] To examine the potential influence of the idealized single slope power law parameterization of the PSD on modeled optical properties, we have coupled our size distribution measurements with the Mie scattering model that assumes spherical and homogeneous particles [Bohren and Huffman, 1983]. These assumptions, although frequently violated by many types of natural particles, can be reasonably adopted for the purpose of identifying general trends in our analysis. Inputs to the Mie model include the particle size distribution and the complex refractive index, m = n + n′i. [69] Several particle size distributions of surface waters measured with the LISST were selected to represent different scenarios, for example stations in which the PSD was relatively featureless and well‐approximated by a power law function, as well as locations which exhibited significant departures from this behavior owing to the presence of one or more peaks in the distribution (Figure 14). Measured PSDs were fit to a power law model, and the derived coefficients were used to generate a modeled PSD over the same size range as the observations. The integrated concentration of particles within this size range and the mean cell projected area were computed for each size distribution. [70] Both measured and modeled PSDs were used as input for the Mie scattering computations using the code of Bohren and Huffman [1983] modified to include the effects of polydispersion. A light wavelength of 550 nm was used in these calculations,and a particle refractive index of 1.05 + 0i was assumed for all particles. For simplicity, we assumed no absorption at 550 nm as marine particles usually exhibit weak absorption in this spectral region. Outputs of these computations yielded the mean efficiency factor for attenuation, Qc(550), which is equivalent to scattering for non‐ absorbing particles. Additional calculations indicated that inclusion of a nonzero absorption term has only a minor influence on the results; for typical absorption values in this spectral band, the calculated efficiency factors differ by less than 0.5%. The predicted beam attenuation coefficient of particles was then calculated for both observed and modeled size distributions according to equation (4). [71] Table 2 summarizes the results of these computations for the PSDs depicted in Figure 14. Predicted values of cp vary as much as 40% between those calculated using the observed particle size distribution and those calculated using the modeled PSD. For the first three samples listed in Table 2 (IBP:22, MB06:11, and IBP:23), the modeled cp is significantly lower than that calculated using the actual observed size distribution. All three of these measurements represent stations sampled during the presence of a “red tide”, in which high concentrations of dinoflagellates strongly influenced the particle assemblage and the observed size distributions were characterized by a prominent peak in the size range of 40–50 mm which is not reproduced by a power law model. The presence of this peak influences the fit so that particle concentrations are overestimated at both smaller and larger

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Figure 14. Particle size distributions utilized in Mie scattering calculations to examine the influence of the PSD shape in the prediction of seawater optical properties (see Table 2). Note that these data represent the number of particles within discrete size bins N(D), and are not normalized to the finite width of each bin. For each station, measured (LISST, circles) and modeled (line) size distributions are shown. Modeled distributions were calculated by fitting a power law model (equation (2)) to the measured density function of size distribution, N′(D). The slope −g of the fit is displayed. size classes and leads to an overestimate of the total concentration for all three stations. The absence of the peak in the modeled distribution also leads to significant underestimate of the mean projected area of the population. Results of Mie computations indicate that the calculated mean efficiency factor Qc is overestimated, and that the mean cross‐ section as a whole is underestimated. The combined errors of overestimating particle number and underestimating the mean cross‐section compensate each other to some extent, but the calculated cp is still underestimated by a significant amount. [72] A relatively good agreement between cp values calculated from both observed and modeled size distributions are noted for some samples, represented in Table 2 by stations I2002, OC07:22, and MB06:10. The PSDs at these locations are reasonably well‐described by a power law model, and are associated with the farthest offshore of our stations and thus most representative of oceanic conditions.

[73] Two selected stations, OC07:40 and SIOP:7, exhibit the presence of small peaks in the PSD, but these peaks are much less pronounced than those observed in the first three examples. In both cases, overestimates of the particle concentration from the modeled size distribution are approximately compensated by underestimates of the mean cross‐ section, leading to a fortuitous reasonable agreement between the two calculated values of cp. [74] IBP41 was the only selected example in which a significant overestimate of cp was obtained through use of the modeled PSD. Similar to some other examples, there is a large overestimate of the total particle concentration; however, this bias was not compensated by a large enough underestimation of the cross‐section to obtain a correct value of the beam attenuation coefficient. [75] Similar analysis of the particle backscattering coefficient, bbp(550), led to qualitatively similar results. A major difference, however, was that the mean backscattering effi-

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19.74 5.40 3.61 0.37 1.27 0.90 1.22 0.31 4.42 ‐74.8 ‐40.6 ‐59.1 ‐5.7 ‐0.8 ‐22.2 ‐3.8 ‐3.2 ‐28.1 160.62 152.75 150.00 77.59 244.14 160.05 137.62 69.21 52.56 637.82 256.98 366.51 82.28 246.14 205.60 143.06 71.51 73.16 2.08 2.21 2.16 2.60 2.22 2.20 2.39 2.64 2.41 ‐78.5 ‐44.7 ‐64.3 ‐4.5 ‐0.7 ‐27.2 ‐5.1 ‐2.6 ‐30.3 66.09 64.39 60.64 30.28 109.95 68.03 56.83 26.34 21.15 307.34 116.33 169.92 31.70 110.74 93.42 59.90 27.05 30.35 130.7 15.3 90.7 5.1 0.1 29.2 7.9 9.8 65.0 71.419 24.228 18.795 4.7483 5.1614 5.6847 9.198 4.724 99.805 30.955 21.006 9.8535 4.5161 5.1583 4.4014 8.522 4.3039 60.482 IBP:22 MB06:11 IBP:23 I2002 OC07:22 OC07:40 MB06:10 SIOP:7 IBP:41

a For the example stations listed, two PSDs were used as input to Mie scattering calculations; the observed PSD and a modeled PSD derived from fitting the observed data to a power law function (see Figure 14). Values of the total particle number concentration NT, the mean projected area G, the mean efficiency factor for beam attenuation Qc, and the predicted particle beam attenuation coefficient cp calculated for both PSDs are given. The mean attenuation cross‐section, c = G Qc, is also shown. The Mie calculations assume a light wavelength of 550 nm, and a complex index of refraction for particles of m = 1.05 + 0i. The difference in percent of the modeled PSD from the observed PSD is given for each parameter.

‐41.9 ‐31.4 ‐21.9 ‐0.9 −0.8 0.5 3.8 6.2 18.6 17.1 7.4 14.7 −1.3 ‐0.1 6.9 1.4 ‐0.6 3.1 2.43 2.37 2.47 2.56 2.22 2.35 2.42 2.63 2.49

Observed Observed Percent Observed Station

Modeled

Percent

Observed

Modeled

Observed

Percent

11.47 3.70 2.82 0.37 1.26 0.91 1.27 0.33 5.25

Modeled Modeled Percent Modeled

Percent cp(550) (m−1) c(550) (mm2) Qc (550) (dimensionless) G (mm2) NT × 10−9 (m−3)

Table 2. Summarized Results of Modeling Exercises to Estimate the Potential Impact of Using Modeled Particle Size Distributions in Calculations of Suspension Optical Propertiesa


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ciency, Qbb(550), was insensitive to the differences between measured and modeled size distributions; thus observed differences in computed particle backscattering arose solely through changes in N(D) and G. It should be noted that because the lower limit of the size range used in this analysis (Dmin = 3.2 mm) is relatively large and does not encompass the smaller size range postulated to be an important contributor to bbp, these results should be interpreted with caution. [76] The modeling analysis was also used to investigate ramifications of having a coarser size resolution of the PSD. Figure 4 (bottom) illustrates the particle size distribution of a field sample measured in situ using the LISST with a baffle (and hence extending the LISST range to particles as small as ∼1 mm), and also on a discrete water sample with the Coulter counter. The high resolution of the Coulter data allows identification of several distinct peaks in the size distribution, some of which are separated by only 1–2 mm. These peaks were not resolvable with the LISST, which resulted in a PSD “smoothed” relative to the actual distribution as revealed by the Coulter. As described above, we compared calculations of inherent optical properties using the PSD obtained from either the Coulter or the LISST over a size range common to both instruments (1.045–44.9 and 1.051–45.01 mm, respectively). In this particular example, the computed value for cp(550) is 9% lower using the lower resolution PSD measured by LISST. Similarly, the computed bbp(550) is 12% lower.

4. Summary and Conclusions [77] Field and laboratory experiments utilizing a variety of particle types suggest that the LISST‐derived particle size distributions, in terms of both particle concentration and size, are generally comparable to Coulter counter measurements. As these instruments are based on very different principles for detecting and sizing particles, such agreement is encouraging and suggests that a combination of these two techniques can provide a good approach for characterizing the PSD in aquatic environments, especially in coastal waters with highly variable particle populations. [78] The Coulter technique provides a highly accurate measurement of particles down to D ∼ 0.6–0.8 mm, with sufficient resolution in size to resolve distinct populations within a mixed assemblage of particles, or to identify regions of changing slope in the PSD. To encompass a broad size range, however, measurements with multiple apertures are needed on a given water sample, and for typical seawater samples it is generally necessary to count large volumes in order to obtain sufficient counting statistics for particles larger than ∼10–20 mm. Because of the time and labor necessary to satisfy these requirements, the analysis of more than a few discrete water samples per day is difficult. [79] An attractive feature of the LISST is its capability to provide rapid in situ measurements of the PSD at high spatial and temporal resolution. Because relatively large volumes of water can be quickly measured without a need for sample manipulation, estimates of the PSD for rarer, larger particles are likely to be more accurate than with small‐volume discrete samples. The results of our measurements on natural water samples suggest that artifacts associated with sample withdrawal from the environment were minimal in our experiments, as comparisons of the in situ PSD with results 17 of 19

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obtained on discrete water samples in the laboratory (measured with either LISST or Coulter) failed to show any systematic discrepancies. However, this generalization will likely not hold in some environments, particularly where delicate particles (e.g., large flocs or aggregates, chain‐ forming plankton species) comprise a significant portion of the assemblage. In such cases, an in situ measurement is necessary to adequately represent such features. [80] Because of its coarser size resolution, the LISST has a limited ability to resolve narrow peaks in a distribution, or to discriminate populations of similarly sized particles when present in a mixed population. In such cases a high resolution measurement such as that provided by the Coulter counter will yield a more accurate estimate of the PSD. This limitation is less severe when PSDs are monotonic and featureless, or if local peaks in the population are broad and widely separated. These conditions are more frequently met in oligotrophic offshore waters than in coastal environments; however, in such clear waters with low particle abundances the 5 cm path length of the LISST is often insufficient to accurately measure the scattering signal. [81] Apparent artifacts in the LISST‐derived PSD were often observed within the smallest size classes of the distribution, and were most prominent for in situ measurements of near‐surface waters. The cause of these problems arises from stray light contamination of the measured scattering signal from solar irradiance. This contamination, which increased with increasing scattering angle, led to significant errors in the retrieval of particle sizes for D < 3.2 mm. Shading of the instrument’s optical path by an external baffle significantly reduced the contamination. The problem could also be addressed by appropriate gating of the scattering signal, a firmware upgrade to implement this feature is currently being explored by the manufacturer (Y. Agrawal, personal communication, 2009). [82] Previous studies have demonstrated a good correspondence in abundances of phytoplankton cells determined with a FlowCAM and traditional microscopic counts [See et al., 2005; Buskey and Hyatt, 2006]. These comparisons were conducted with a focus towards relatively large particles (D > 15 mm). Experiments by Sterling et al. [2004] also indicate that for spherical particles within the size range 5 to 90 mm, the FlowCAM yields estimates of particle diameter that are comparable to both Coulter counter and LISST‐100 determinations. The results of our experiments, however, suggest that quantitative estimates of the PSD are problematic when conducted over a broad size range which includes particles smaller than the microplanktonic community. With smaller particles, detection becomes more difficult, and higher concentrations increase the possibility of coincidence errors (i.e. multiple particles within the flow cell being counted as a single particle). Despite these limitations, the FlowCAM does provide valuable additional information such as the abundance of specific particle types, optical characteristics such as light scattering and pigment fluorescence, and information on particle morphology. [83] The in situ measurements of coastal waters obtained with the LISST demonstrate significant spatial and temporal variability in both the concentration and shape of the PSD. Although the use of simple models such as the power law formulation with a single slope can provide a reasonable description of the PSD in some environments, our mea-

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surements indicate that the slope of this distribution for particles larger than 3 mm is frequently less steep than the value of −4 commonly assumed in models of the PSD. Our observations also suggest that this type of model often provides a poor description of the PSD, and fails to capture all the complexity inherent in suspended particle dynamics. Compared to the open ocean, coastal regions represent a highly energetic environment in which particle dynamics may occur on short time and space scales owing to rapid growth and decline of plankton populations in response to environmental variability, episodic inputs of particles from land runoff and rivers,and sediment resuspension events. Such phenomena frequently lead to large departures from the monotonic shape of the PSD usually assumed by idealized descriptions. [84] The combination of our size distribution measurements with Mie scattering theory indicates that the assumption of a power law model for the PSD can lead to significant errors (40%) in the predictions of seawater bulk optical properties. These errors are caused by inaccuracies in both the magnitude of the predicted particle concentration, and in the shape of the PSD. Fortuitously, the overall magnitude of prediction error is often reduced to some extent through opposite trends in the prediction of particle number and the optical cross‐section. Because of the simplifying assumptions utilized in these simulations, it should be recognized that actual errors could be larger than reported here. The observed errors were most pronounced when the PSD deviates from a power law because of significant curvature, or the presence of significant peaks resulting from increases in an individual size range. Both of these features appear to be common in coastal waters, and a high resolution measurement of the PSD is then necessary for improved accuracy in calculations of radiative transfer. [85] The magnitude and variability of ocean optical properties is largely caused by suspended particles, and characterizing and predicting such variability continues to be a major challenge. Despite decades of observations on these properties from field measurements, studies which include parallel investigations of the fundamental causes which drive such variability (e.g., particle size and composition) are rare. With the continuing refinement of technology (e.g., laser‐ diffraction, particle imaging) to rapidly and conveniently estimate the PSD in situ, simplified formulations of the PSD will likely become replaced by the use of actual data. We anticipate that such developments will lead to improvements in the ability to simulate ecological interactions, particle dynamics, and radiative transfer within natural waters. [86] Acknowledgments. This work was supported by the U.S. Office of Naval Research Optics and Biology Program (award N00014‐05‐1‐ 0246). The data from the Santa Barbara Channel were collected during the ONR‐sponsored program Radiance in a Dynamic Ocean (award N00014‐ 06‐1‐0071). We are indebted to Marta Cichocka, Agnieszka Cieplak, and Su‐Jen Roberts for excellent technical assistance in the laboratory. We thank Yogi Agrawal for discussions regarding operation of the LISST. Mike Twardowski and Matthew Slivkoff drew our attention to stray light artifacts with LISST measurements and contributed useful discussions. We also thank the personnel aboard the research vessels John Martin, Oceania, and Kilo Moana for providing safe and enjoyable platforms in which to conduct our measurements at sea. Curt Davis and the NOAA Coastal Ocean Applications and Science Team program are acknowledged for providing partial support of our participation in the Monterey Bay experiment. Comments on the manuscript by two anonymous reviewers are appreciated.

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