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溶解态的锰和铁是海洋中重要的生物营养元素,也是探查海底热液活动及其演化的重要示踪剂。由于海底热液活动研究的迫切需求,以及AUV,ROV和HOV等水下运载支撑平台的迅速发展,20世纪80年代以来深海溶解态锰铁原位分析技术得到了快速发展。早期研发的Scanner和SUAVE,可对热液羽流中高含量的锰铁元素实现联合测定,但存在元素之间相互干扰等问题,因此针对锰、铁元素单独测量的原位分析仪应运而生。锰原位分析仪中,ZAPS虽然具有较低的检测限,但是无法在深海高压环境下进行原位校正;GAMOS系列具有原位校正功能,且能耗较低,可长期运行,但是检测限偏高,因此只能应用于热液环境中含量相对高的锰监测。铁原位分析仪中,改进的ALCHIMIST可实现热液喷口异常高含量铁和正常海域水体中低含量铁的检测,但由于能耗较高而难以应用于长期观测中;低能耗的Fe-Osmo-Analyzer和CHEMINI则在长期运行方面有着明显的优势。随着AUV/ROV/HOV等水下移动平台应用的日渐广泛以及海底观测网技术的迅速发展,发展原位分析仪进行长期的自主观测将成为一种必然趋势。
Dissolved manganese and iron are important biotrophic elements in the oceans and are also important tracers for the exploration of seafloor hydrothermal activity and its evolution. Due to the urgent need of seafloor hydrothermal activity research and the rapid development of underwater transport support platforms such as AUV, ROV and HOV, deep-sea dissolved manganese in situ analysis has developed rapidly since the 1980s. Early development of Scanner and SUAVE can measure the high content of ferromanganese in hydrothermal plume, but there are some problems such as mutual interference between elements. Therefore, the in-situ analyzer for the measurement of manganese and iron alone has come into being. In the manganese in-situ analyzer, although ZAPS has lower detection limit, it can not be calibrated in-situ in deep-sea high pressure environment. The GAMOS series has the function of in-situ calibration with low energy consumption and long-term operation. However, Therefore, it can only be applied to manganese monitoring with relatively high content in hydrothermal environment. In the iron in-situ analyzer, the improved ALCHIMIST can detect iron with abnormally high content of iron in hydrothermal vents and low levels of iron in normal seawater, but it is difficult to apply it to long-term observation due to high energy consumption. Low energy consumption of Fe-Osmo -Analyzer and CHEMINI have a clear advantage over the long run. With the increasing use of underwater mobile platforms such as AUV / ROV / HOV and the rapid development of underwater observational network technology, it will become an inevitable trend to develop an in situ analyzer for long-term autonomous observation.