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A new automated shipboard analytical method for determining iron(III) in seawater has been developed. The method is based on a combination of selective column extraction using chelating resin and improved chemiluminescence (CL) detection in a closed flowthrough system. In this method, Fe(III) in an acidified sample solution is selectively collected on 8-quinolinol immobilized chelating resin and then eluted with dilute hydrochloric acid. The resulting eluent is mixed with luminol solution, aqueous ammonia, and hydrogen peroxide solution successively, and then the mixture is introduced into the CL cell. The iron concentration is obtained from the CL intensity. The detection limit of iron(III) is 0.05 nmol L1 234when using an 18-mL seawater sample. The method was applied to ordinary oceanic waters and hydrothermal waters collected in the North and South Pacific Oceans. Worldwide marine chemists and marine biologists have focused on the behavior of iron in seawater, since Martin et al.1"5 pointed out that the phytoplankton growth in oceanic water was limited by the deficiency of iron derived from the atmosphere rather than the lack of nutrients in some oceanic regions, such as the equatorial Pacific, Gulf of Alaska, and Antarctic Ocean. This attractive hypothesis created a heated argument in various journals6 78"9 and spurred the geochemical study of iron. For example, Zhuang et al.10 reported recently that more than half of the iron in aeolian mineral dust existed in the form of Fe (II), resulting in the enhancement of solubility (1) Martin,

In nearly a dozen open‐ocean fertilization experiments conducted by more than 100 researchers from nearly 20 countries, adding iron at the sea surface has led to distinct increases in photosynthesis rates and biomass. These experiments confirmed the hypothesis proposed by the late John Martin [Martin, 1990] that dissolved iron concentration is a key variable that controls phytoplankton processes in ocean surface waters However, the measurement of dissolved iron concentration in seawater remains a difficult task [Bruland and Rue, 2001] with significant interlaboratory differences apparent at times. The availability of a seawater reference solution with well‐known dissolved iron (Fe) concentrations similar to open‐ocean values, which could be used for the calibration of equipment or other tasks, would greatly alleviate these problems [National Research Council (NRC), 2002[.

Geochemical characteristics of hydrothermal fluids in the Iheya North hydrothermal field, mid-Okinawa Trough, was investigated. Twelve-years observation reveals temporal variation of vent fluid chemistry potentially controlled by temporally varying pattern of the phase-separation and -segregation, while the constant Element/Cl ratios among the periods and chimneys indicate the stable chemical composition of the source hydrothermal fluid prior to undergoing phaseseparation. The high K contents in the estimated source fluid are typical in the arc-backarc hydrothermal systems due to the hydrothermal reaction with the K-enriched felsic rocks. The high I, B and NH 4 contents and alkalinity are derived from decomposition of the sedimentary organic matters.Compositional and isotopic properties of gas species, CH 4 , H 2 , CO 2 , and C 2 H 6 , strongly suggest a dominance of biogenic CH 4 associated with the sedimentary organic matter. Based on the carbon mass balance calculation and the multidisciplinary investigations of the Iheya North hydrothermal system since the discovery, we hypothesized that the microbial methanogenesis occurs not only within the Central Valley where hydrothermal vents exist, but also in the spatially abundant and widespread basin-filling sediments surrounding the Iheya North Knoll, and that the microbially produced CH 4 is recharged together with the source fluid into the deep hydrothermal reaction zone. This "Microbial Methanogenesis at Recharge area in hydrothermal circulation" (MMR) model would be an implication for the generation and incorporation of hydrothermal fluid CH 4 in the deep-sea hydrothermal systems but also for those of cold seep CH 4 and for the presently uncertain hydrothermal fluid paths in the subseafloor environments. In the near future, the IODP drilling will be conducted in the Iheya North hydrothermal system, and give an excellent opportunity to testify our MMR model.

The GEOTRACES Intermediate Data Product 2014 (IDP2014) is the first publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2013. It consists of two parts: (1) a compilation of digital data for more than 200 trace elements and isotopes (TEls) as well as classical hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing a strongly inter-linked on-line atlas including more than 300 section plots and 90 animated 3D scenes. The IDP2014 covers the Atlantic, Arctic, and Indian oceans, exhibiting highest data density in the Atlantic. The TEI data in the IDP2014 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at cross-over stations. The digital data are provided in several formats, including ASCII spreadsheet, Excel spreadsheet, netCDF, and Ocean Data View collection. In addition to the actual data values the IDP2014 also contains data quality flags and 1-sigma data error values where available. Quality flags and error values are useful for data filtering. Metadata about data originators, analytical methods and original publications related to the data are linked to the data in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2014 data providing section plots and a new kind of animated 3D scenes. The basin-wide 3D scenes allow for viewing of data from many cruises at the same time, thereby providing quick overviews of large-scale tracer distributions. In addition, the 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of observed tracer plumes, as well as for making inferences about controlling processes. (C) 2015 The Authors. Published by Elsevier B.V