Abstract
Abstract. Mass-specific absorption (ai∗(λ)) and scattering (bi∗(λ)) coefficients were derived for four size fractions (i = 0.2–0.4, 0.4–0.7, 0.7–10, and > 10 µm, λ = wavelength in nm) of suspended particulate matter (SPM) and with samples obtained from surface waters (i.e., 0–2 m depth) of the Saint Lawrence Estuary and Saguenay Fjord (SLE-SF) during June of 2013. For the visible–near-infrared spectral range (i.e., λ = 400–710 nm), mass-specific absorption coefficients of total SPM (i.e., particulates > 0.2 µm) (hereafter aSPM∗) had low values (e.g., < 0.01 m2 g−1 at λ = 440 nm) in areas of the lower estuary dominated by particle assemblages with relatively large mean grain size and high particulate organic carbon and chlorophyll a per unit of mass of SPM. Conversely, largest aSPM∗ values (i.e., > 0.05 m2 g−1 at λ = 440 nm) corresponded with locations of the upper estuary and SF where particulates were mineral-rich and/or their mean diameter was relatively small. The variability of two optical proxies (the spectral slope of particulate beam attenuation coefficient and the mass-specific particulate absorption coefficient, hereafter γ and Svis, respectively) with respect to changes in particle size distribution (PSD) and chemical composition was also examined. The slope of the PSD was correlated with bi∗(550) (Spearman rank correlation coefficient ρs up to 0.37) and ai∗(440) estimates (ρs up to 0.32) in a comparable way. Conversely, the contribution of particulate inorganic matter to total mass of SPM (FSPMPIM) had a stronger correlation with ai∗ coefficients at a wavelength of 440 nm (ρs up to 0.50). The magnitude of γ was positively related to FSPMi or the contribution of size fraction i to the total mass of SPM (ρs up to 0.53 for i = 0.2–0.4 µm). Also, the relation between γ and FSPMPIM variability was secondary (ρs = −0.34, P > 0.05). Lastly, the magnitude of Svis was inversely correlated with aSPM∗(440) (ρs = −0.55, P = 0.04) and FSPMPIM (ρs = −0.62, P = 0.018) in sampling locations with a larger marine influence (i.e., lower estuary).
Highlights
IntroductionThe distribution of suspended particulate matter (SPM) (Table 1) in coastal and estuarine environments has a major influence on biogeochemical processes (e.g., phytoplankton blooms) (Guinder et al, 2009), ecosystem structure (e.g., food web) (Dalu et al, 2016) and dispersion of pollutants (e.g., copper, mercury, polycyclic aromatic hydrocarbons) (Ma et al, 2002; Ramalhosa et al, 2005)
The distribution of suspended particulate matter (SPM) (Table 1) in coastal and estuarine environments has a major influence on biogeochemical processes (Guinder et al, 2009), ecosystem structure (Dalu et al, 2016) and dispersion of pollutants (Ma et al, 2002; Ramalhosa et al, 2005)
Unlike particle size distribution (PSD), the mineral content of SPM was less variable between individual samples (FSPMPIM range = 20 to 87 %)
Summary
The distribution of suspended particulate matter (SPM) (Table 1) in coastal and estuarine environments has a major influence on biogeochemical processes (e.g., phytoplankton blooms) (Guinder et al, 2009), ecosystem structure (e.g., food web) (Dalu et al, 2016) and dispersion of pollutants (e.g., copper, mercury, polycyclic aromatic hydrocarbons) (Ma et al, 2002; Ramalhosa et al, 2005). The spatial and temporal variability of suspended particulates is relatively high (i.e., > 100-fold) in littoral environments (Doxaran et al, 2002; Montes-Hugo and Mohammadpour, 2012) This represents a challenge for traditional methods of measuring SPM based on gravimetry (Strickland and Parson, 1972) as the analysis of a large number of samples is time-consuming and costly. These studies are commonly based on a relatively small dataset that may partially represent the in situ distributions of SPM.
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