The large-scale oceanic distribution of trace elements: disentangling preformed contributions, regenerative processes, subsurface sources and sinks

微量元素的大规模海洋分布：解开预先形成的贡献、再生过程、地下源和汇

• 批准号: NE/M017826/2
• 负责人: Yves Plancherel
• 金额: $ 25.09万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FM017826%2F2
• 关键词: large; scale; oceanic; distribution; trace

Elements present in seawater in quantities so small that they do not affect salinity are called "trace elements". In spite of their low abundances, trace metals can play disproportionally large roles in controlling the dynamics of marine ecosystems. This is because some are necessary for the proper functioning of important enzymes and proteins and must thus be supplied in sufficient quantities to maintain phytoplankton populations. There are regions in the ocean where key metals, particularly iron (Fe), are lacking in proportion to the other nutrients, what limits biological productivity. Why some micronutrients are lacking in some region and not others is not fully understood; the processes that govern the natural cycles of these metals are not well known. This gap in understanding is partly due to the difficulty of measuring trace metals in the ocean: trace metals are present in very small quantities and water samples are taken from metallic research ships, making measurements prone to contamination. Reliable techniques to routinely measure trace metals in seawater have only been recently developed. Thanks to them, the accuracy of the data and data coverage over the oceans have improved dramatically over the last few years. With this project, I aim to improve the general understanding of the cycling of trace metals, particularly the micronutrients, by analyzing the newest and most complete trace metal databases available.The difficulty when trying to interpret measurements of dissolved trace metal concentrations, or other nutrients, in the deep sea is that one cannot easily distinguish between the amount that is present because it has been transported to the point of sampling from somewhere else and the amount that has been added or removed due to local, internal processes. Yet, one must be able to isolate that later component to quantify and interpret the influence of subsurface biogeochemical processes on trace metal cycles. Without this ability, one's interpretation of the measured concentration field could be wrong, mistaking transport phenomena for internal cycling mechanisms. This work will directly address this issue by applying statistical deconvolution techniques to explicitly quantify the amount that is transported. By taking the difference between the measured concentrations and the calculated transported component, it is possible to quantify the fraction that is due to biogeochemical processes and map these residual quantities.One of the most important processes influencing the distribution of trace metals in the sea is "scavenging"; that is the propensity for dissolved metals to stick to particles and sink along with them. Scavenging affects metals more than other nutrients. It is an important process because it is omnipresent (particles are everywhere) and can redistribute the metals within the ocean interior. It is hypothesized that if scavenging is strong, or operating for a long time, the scavenging process can fractionate metals relative to the other nutrients. When layers that are affected strongly by this process are transported back to the surface, they will bring with them waters that are depleted in the metal relative to the other nutrients. If the metal abundance is too low, this will limit surface productivity. Preliminary modeling experiments support the view that scavenging exerts a first order control on the distribution of some metals, such as thorium, beryllium, the rare earth elements and aluminium. It is, however, not clear how much micronutrient metals scavenge and if this effect is able to explain the distribution and characteristics of micronutrient-limited regions. This project will test this hypothesis. First, the statistical deconvolution results from the data will inform on the degree of fractionation imposed by scavenging on each metal. Secondly, models will be used to simulate scavenging and the fractionation process and quantify the influence on surface ecosystems.

在海水中存在的元素，其数量如此之小，以至于它们不会影响盐度，被称为“微量元素”。微量金属尽管丰度低，但在控制海洋生态系统动态方面可发挥巨大作用。这是因为有些是重要的酶和蛋白质正常运作所必需的，因此必须提供足够的数量来维持浮游植物的数量。在海洋中的某些区域，关键金属，特别是铁（Fe），与其他营养物质相比缺乏，这限制了生物生产力。为什么某些微量营养素在某些地区缺乏，而在其他地区却没有，目前还没有完全弄清楚;控制这些金属自然循环的过程也不为人所知。这种认识上的差距部分是由于难以测量海洋中的微量金属：微量金属的数量非常少，而且水样是从金属研究船上采集的，因此测量容易受到污染。可靠的技术，定期测量微量金属在海水中只是最近才开发出来。多亏了他们，数据的准确性和海洋数据的覆盖范围在过去几年中有了显着改善。通过这个项目，我的目标是通过分析最新和最完整的痕量金属数据库来提高对痕量金属循环的一般理解，特别是微量营养素。当试图解释溶解的痕量金属浓度或其他营养素的测量时，在深海中，最大的问题是，人们不能轻易区分从其他地方运到取样点的数量和由于本地内部流程而增加或删除的金额。然而，人们必须能够隔离后一种成分，以量化和解释地下地球化学过程对痕量金属循环的影响。如果没有这种能力，人们对测量浓度场的解释可能是错误的，将传输现象误认为内部循环机制。这项工作将直接解决这个问题，通过应用统计反卷积技术，明确量化的数量是运输。通过测量浓度和计算的迁移成分之间的差异，可以量化由于海洋地球化学过程产生的部分，并绘制这些残留量，影响海洋中痕量金属分布的最重要过程之一是“清除”;即溶解金属附着在颗粒上并随颗粒沿着下沉的倾向。清除影响金属比其他营养素。这是一个重要的过程，因为它是无所不在的（颗粒无处不在），可以重新分配海洋内部的金属。据推测，如果清除是强的，或操作了很长一段时间，清除过程可以相对于其他营养素破碎金属。当受到这一过程强烈影响的地层被输送回地表时，它们将带来相对于其他营养物质而言金属耗尽的沃茨。如果金属丰度太低，这将限制表面生产力。初步模拟实验支持这样的观点，即清除对某些金属，如钍、铍、稀土元素和铝的分布施加一级控制。然而，目前尚不清楚有多少微量营养素金属，以及这种影响是否能够解释微量营养素有限地区的分布和特征。本项目将检验这一假设。首先，来自数据的统计去卷积结果将告知通过清除对每种金属施加的分馏程度。其次，将利用模型模拟清除和分馏过程，并量化对地表生态系统的影响。

项目成果

Particle-Seawater Interaction of Neodymium in the North Atlantic

北大西洋钕的粒子与海水相互作用

• DOI: 10.1021/acsearthspacechem.0c00034
• 发表时间: 2020
• 期刊: ACS Earth and Space Chemistry
• 影响因子: 3.4
• 作者: Stichel T

Tropical Pacific climate variability under solar geoengineering: impacts on ENSO extremes

• DOI: 10.5194/acp-20-15461-2020
• 发表时间: 2019-01
• 期刊: Atmospheric Chemistry and Physics
• 影响因子: 6.3
• 作者: Abdul Malik;P. Nowack;J. Haigh;Long Cao;Luqman Atique;Y. Plancherel

Reemergence of Anthropogenic Carbon Into the Ocean's Mixed Layer Strongly Amplifies Transient Climate Sensitivity

人为碳重新进入海洋混合层强烈放大了瞬态气候敏感性

• DOI: 10.1029/2020gl089275
• 发表时间: 2020
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Rodgers K