The inherent optical properties (IOPs) of suspended particulate matter and their
relations with the main biogeochemical characteristics of particles have been
examined in the surface waters of the southern Baltic Sea. The empirical data
were gathered at over 300 stations in open Baltic Sea waters as well as in the
coastal waters of the Gulf of Gdańsk. The measurements included IOPs such
as the absorption coefficient of particles, absorption coefficient of phytoplankton,
scattering and backscattering coefficients of particles, as well as biogeochemical
characteristics of suspended matter such as concentrations of suspended particulate matter (SPM), particulate organic matter (POM), particulate organic carbon
(POC) and chlorophyll a (Chl a). Our data documented the very extensive
variability in the study area of particle concentration measures and IOPs (up to
two orders of magnitude). Although most of the particle populations encoun-
tered were composed primarily of organic matter (av. POM/SPM=ca 0.8), the
different particle concentration ratios suggest that the particle composition varied
significantly. The relations between the optical properties and biogeochemical
parameters of suspended matter were examined. We found significant variability in
the constituent-specific IOPs (coefficients of variation (CVs) of at least 30% to 40%,
usually more than 50%). Simple best-fit relations between any given IOP versus
any constituent concentration parameter also highlighted the significant statistical
errors involved. As a result, we conclude that for southern Baltic samples an easy
yet precise quantification of particle IOPs in terms of the concentration of only
one of the following parameters – SPM, POM, POC or Chl a – is not achievable.
Nevertheless, we present a set of best statistical formulas for a rough estimate of
certain seawater constituent concentrations based on relatively easily measurable
values of seawater IOPs. These equations can be implemented in practice, but
their application will inevitably entail effective statistical errors of estimation of
the order of 50% or more.
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