A Mie-based flow cytometric size and real refractive index determination method for natural marine particle populations

  • Jacopo Agagliate

Student thesis: Doctoral Thesis


Following the path of combining Mie theory and flow cytometry to assign size and refractive index to suspended particles in the steps of Ackleson & Spinrad (1988) and, more recently, Green et al. (2003a, 2003b), a Mie-based flow cytometry (FC) method was developed to retrieve particle size distributions (PSDs) and real refractive index (rRI) information in natural waters. The need for a technique capable of directly assessing both size and real refractive index of the particles was first established by carrying out a sensitivity analysis of the effect a spectrally complex refractive index and log-normal variations to commonly employed PSD models have on the optical behaviour of the particle population. The Mie-based FC method proper was then developed and tested, initially against standard particles of known diameter and rRI and secondly on two datasets, one of algal culture samples (AC dataset) and one of natural seawater samples collected in UK coastal waters (UKCW dataset).The method retrieved PSDs and real refractive index distributions (PRIDs) for both datasets. FC PSDs were validated against known algal sizes for AC samples and against independent PSDs measured via laser diffractometry for UKCW samples. PRIDs were then combined with FC PSDs and fed into Mie-based forward optical modelling to reconstruct bulk IOPs. These achieved broad agreement with independent IOP measurements, lending further support to the results of the FC method and to the employment of Mie theory within the context of optical modelling of natural particle populations. Furthermore, the unique insight offered by the FC method in terms of PSD and PRID determination allowed for the assessment of the individual contribution of particle subpopulations to the bulk IOPs, both by size (small/large particle fractions) and by particle type (inorganic/organic/fluorescent fractions). Lastly, PSDs and PRIDs were combined with literature-derived models of particle density, cell organic carbon and chlorophyll-A content, in an effort to explore the biogeochemical properties of the particle populations within the UKCW dataset. The models successfully estimated independent measurements of particulate suspended matter and (after an optimisation procedure) of organic carbon and chlorophyll-A content.
Date of Award28 Sept 2017
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SponsorsUniversity of Strathclyde
SupervisorDavid McKee (Supervisor) & Neil Hunt (Supervisor)

Cite this