Eglinton, TI
1991
Analysis of Peru Margin Surface Sediments by PY-MS
Eglinton, T.I.; McCaffrey, M.A.; Huai, H. and Meuzelaar, H.L.C.
ACS Preprints, Division of Fuel Chemistry, 36(2):781-789 (201st ACS National Meeting, Atlanta, GA, April 1991).
In offshore Peru high sedimentary organic carbon contents are a direct consequence of the extremely high primary productivity (ca. 1000g Carbon m²/yr) which, in turn, is supported by the upwelling of nutrient-rich waters near the coast. Diatoms represent the major phytoplankton type and give rise to sediments dominated by biogenic silica and planktonic organic matter. The remineralization of this large flux of organic matter to the bottom waters and sediments results in oxygen depletion over large areas of the shelf that, in turn, promotes organic carbon preservation in the underlying sediments. Sulfide from sulfate reduction is prevalent in the bottom waters and with a limited availability of iron (due to the dominant biogenic input coupled with a very low influx of detrital sediments) the excess sulfide is available for reaction with the organic matter. As a result high organic sulfur concentrations are found in the sediments.
The coastal Peru upwelling region is believed to be a modern analogue to the depositional environments of petroleum source rocks such as the Miocene Monterey Formation of the California Borderland. Because organic matter alteration pathways in surface sediments ultimately influence kerogen type and eventual petroleum yield, there has been interest in characterizing surface sediments such as those offshore Peru. Lipid, carotenoid and amino acid constituents as well as general biogeochemistry have been studied previously. However, studies of the macromolecular components of the sediments have been less extensive. This paper describes results from Py-MS analyses of sediment samples obtained from discrete intervals in a 1-meter core obtained from the upper continental shelf of the Peru Upwelling region. Factor and discriminant analysis of the Py-MS data revealed several distinct changes within this 1-meter section.
Eglinton, TI
1991
Analysis of Peru Margin Surface Sediments by PY-MS
Eglinton, T.I.; McCaffrey, M.A.; Huai, H. and Meuzelaar, H.L.C.
ACS Preprints, Division of Fuel Chemistry, 36(2):781-789 (201st ACS National Meeting, Atlanta, GA, April 1991).
In offshore Peru high sedimentary organic carbon contents are a direct consequence of the extremely high primary productivity (ca. 1000g Carbon m²/yr) which, in turn, is supported by the upwelling of nutrient-rich waters near the coast. Diatoms represent the major phytoplankton type and give rise to sediments dominated by biogenic silica and planktonic organic matter. The remineralization of this large flux of organic matter to the bottom waters and sediments results in oxygen depletion over large areas of the shelf that, in turn, promotes organic carbon preservation in the underlying sediments. Sulfide from sulfate reduction is prevalent in the bottom waters and with a limited availability of iron (due to the dominant biogenic input coupled with a very low influx of detrital sediments) the excess sulfide is available for reaction with the organic matter. As a result high organic sulfur concentrations are found in the sediments.
The coastal Peru upwelling region is believed to be a modern analogue to the depositional environments of petroleum source rocks such as the Miocene Monterey Formation of the California Borderland. Because organic matter alteration pathways in surface sediments ultimately influence kerogen type and eventual petroleum yield, there has been interest in characterizing surface sediments such as those offshore Peru. Lipid, carotenoid and amino acid constituents as well as general biogeochemistry have been studied previously. However, studies of the macromolecular components of the sediments have been less extensive. This paper describes results from Py-MS analyses of sediment samples obtained from discrete intervals in a 1-meter core obtained from the upper continental shelf of the Peru Upwelling region. Factor and discriminant analysis of the Py-MS data revealed several distinct changes within this 1-meter section.