Understanding the drivers and climate sensitivity of open ocean methane emissions to the atmosphere

了解公海甲烷排放到大气中的驱动因素和气候敏感性

• 批准号: 2241744
• 负责人: Thomas Weber
• 金额: $ 29.41万
• 依托单位: University of Rochester
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2241744&HistoricalAwards=false
• 关键词: Understanding; drivers; climate; sensitivity; open

Methane is a potent greenhouse gas with a global warming potential thirty times larger than carbon dioxide. In addition to human emissions methane has many natural sources to the atmosphere, which could be amplified by future climate warming. Methane emissions from the vast open ocean are relatively small but their sensitivity to climate change is highly uncertain. This is because the processes that supply methane to surface ocean waters are not well understood. To improve our understanding of the open ocean methane cycle, this project will use a computer model to interpret a large database of methane concentration measurements. First, the model will be used to determine the dominant biological source of methane within surface waters. Candidates include production during algae growth, production in the guts of small animals, and bacterial decay of organic matter. Each of these processes would produce a different surface methane pattern, allowing the model to distinguish between them. Second, the model will quantify the supply of methane from the seafloor in low oxygen zones of the ocean, and determine whether this methane is consumed by bacteria before escaping to the atmosphere. This is important because low oxygen zones will likely grow as the climate warms. Leakage of methane from these regions could therefore act as a feedback on climate change. The global model developed in this project will simulate the open ocean sources and sinks of methane, including in situ aerobic methanogenesis in surface waters, diffusion from anoxic sediments, oxidation in the water column, and exchange with the atmosphere. Data will be assimilated to optimize model parameters, and ultimately determine the balance of sources and sinks that is most consistent with the observed ocean methane distribution. Aerobic methane production will be formulated as function of phytoplankton growth, zooplankton abundance, and organic matter recycling, to determine which mechanisms best explains the pattern of surface methane supersaturation. The oxygen dependence of sedimentary methane sources and bacterial methane oxidation will be optimized to best match the observed plumes that spread laterally from suboxic waters and upwell towards the surface. The resulting optimized model will then be used to predict future perturbation of the open ocean methane source in response to ecosystem changes and ocean oxygen loss.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

甲烷是一种强有力的温室气体，其全球变暖潜力是二氧化碳的30倍。除了人类排放的甲烷外，甲烷还有许多自然来源，未来的气候变暖可能会加剧甲烷的排放。来自广阔公海的甲烷排放量相对较小，但其对气候变化的敏感性高度不确定。这是因为人们对向海洋表面沃茨提供甲烷的过程还没有很好的了解。为了提高我们对开阔海洋甲烷循环的理解，该项目将使用计算机模型来解释甲烷浓度测量的大型数据库。首先，该模型将用于确定地表沃茨内甲烷的主要生物来源。候选者包括藻类生长过程中的生产，小动物肠道中的生产，以及有机物质的细菌腐烂。这些过程中的每一个都会产生不同的地表甲烷模式，使模型能够区分它们。其次，该模型将量化海洋低氧区海底甲烷的供应，并确定这些甲烷在逃逸到大气中之前是否被细菌消耗。这很重要，因为低氧区可能会随着气候变暖而增长。因此，这些地区的甲烷泄漏可能是对气候变化的反馈。本项目开发的全球模式将模拟开放海洋甲烷的源和汇，包括表层沃茨中的原地有氧甲烷生成、缺氧沉积物的扩散、水柱中的氧化以及与大气的交换。将对数据进行同化，以优化模型参数，并最终确定与观测到的海洋甲烷分布最一致的源和汇的平衡。好氧甲烷产量将被制定为浮游植物生长、浮游动物丰度和有机物回收的函数，以确定哪些机制最能解释表面甲烷过饱和的模式。沉积甲烷源和细菌甲烷氧化的氧依赖性将被优化，以最好地匹配所观察到的羽流，从亚氧沃茨横向蔓延，并上升到表面。由此产生的优化模型将被用来预测未来扰动的开放海洋甲烷源，以应对生态系统的变化和海洋氧气loss.This奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。