As members of the PACE Science Team we propose to pursue analytical and theoretical studies as part of the measurement suite area "Inherent Optical Properties (IOPs) of the Ocean". Our goal is to improve field measurements of particulate absorption coefficients and remote sensing estimates of absorption coefficients of phytoplankton and non-phytoplankton components and particulate carbon pools associated with these components. The main objectives are to: (1) Develop a protocol and quantify the uncertainties of a new filter-pad approach and the existing filter-pad methods to measuring the particulate absorption coefficient; (2) Develop a model to partition the absorption coefficient of seawater into phytoplankton, non-algal particulate (NAP), and colored dissolved organic matter (CDOM) components with a key novel aspect of separating NAP from CDOM; and (3) Conduct a pilot study of the relationship between NAP absorption and NAP organic carbon to enable a capability for remote sensing of carbon pools associated with separate phytoplankton and non-phytoplankton components. The overall approach to address these objectives will be based primarily on the analysis of existing laboratory and field data, but will also encompass a combination of limited number of laboratory and field measurements to collect new data, and the application of remote sensing data from high spectral resolution sensor HICO. With regard to Objective 1 we will examine the filter-pad methods for determining the absorption coefficient of particles with high spectral resolution(~ 1 nm) over a broad spectral range from UV through NIR; specifically the traditional transmittance (T) and transmittance-reflectance (T-R) methods as well as the inside-sphere (IS) method which is the most recent refinement with the filter placed inside an integrating sphere. The IS method offers several advantages over the T and T-R methods, leading to improved accuracy and precision of absorption measurements. We will determine complete protocols including new optimal correction algorithms for pathlength amplification factor (which is the main source of uncertainty) and will quantify uncertainties for all three methods, benefiting the interpretation of historical data and acquisition of future data of particulate absorption. We anticipate that the IS approach will serve as the new recommended (preferable) method for measurements of particle absorption. With regard to Objective 2 we will develop a model to provide for the first time a capability for estimating the three major absorption components separately (phytoplankton, NAP, and CDOM) from the total absorption coefficient of seawater, which is derivable from remote sensing. In this development, we will use the existing quality-verified field data of absorption coefficients from various regions of the world's ocean and will expand the approach that has been successful for partitioning the absorption coefficient into phytoplankton and non-phytoplankton (NAP+CDOM combined) components (Zheng and Stramski 2013). The significance of the proposed partitioning model is associated with relationships between the component absorption coefficients and biogeochemical stocks, such as DOC, particulate non-algal and phytoplankton carbon, chlorophyll-a, as well as phytoplankton community structure and primary productivity. As a prototyping activity (Objective 3) we will examine one such unexplored link, specifically the relationship between the NAP absorption and NAP organic carbon, which will provide a basis for estimating separate pools of phytoplankton and non-algal organic carbon from remote sensing. This project will create new and advance existing algorithms for deriving ocean color data products, in particular IOPs and carbon stocks associated with separate phytoplankton and non-phytoplankton components, which will contribute to scientific goals of PACE mission to understand ocean carbon cycling and ecology.