Pathways and Emissions of climate-relevant TRace gases in a changing Arctic Ocean (PETRA)

北冰洋特别容易受到气候变化的影响。最近的研究表明，地表海水变暖的速度比其他海洋要快。此外，大气中CO2在海水中的溶解正在引起海洋酸化（OA）。有记录的海冰退缩将增加光的穿透，包括紫外线。这些环境参数（温度、OA和UV）极有可能成为压力源，改变北冰洋生态系统的结构和功能，反过来又会反馈给气候。其中一个反馈是气候活跃的微量气体的循环及其向大气的排放（这里：CH4， N2O， DMS， CO）。这些微量气体通过许多物理和生物过程迅速产生和消耗。例如，表层海水中CO的最大来源是通过紫外线诱导的光化学反应。然而，微量气体循环对气候变化的可能反应在很大程度上仍未被探索。这阻碍了我们预测这一重要气候反馈未来方向的能力。我们建议通过以下方式来调查这种反馈：a)发展将支持预测工具的基本理解；b)发展预测工具本身（计算机模型）。我们将利用三种互补的工具来实现这一目标：首先，对微量气体（包括深度和水平）进行新颖的高科技空间观测，这将使我们能够确定其周期的主要控制因素，并估计其目前进入大气的通量。其次，直接实验，其中三个压力源将被操纵，同时监测微量气体循环途径。我们的方法的新颖之处在于使用单独和联合的压力源操作（例如OA单独与高温和OA一起）。这将使我们能够探索压力源之间潜在的协同或拮抗作用。我们将使用最先进的化学和生物观察来跟踪微量气体循环的变化。例如，我们将监测参与微量气体循环的关键基因的丰度和活性。这些实验将使我们对与压力源有关的痕量气体循环有明确而精细的了解。第三，我们将采用计算机建模，将这种理解转化为预测工具，用于预测未来气候变化的影响。最后，为了将我们的相关发现迅速转化为政策，我们将通过我们的综合影响计划与公众、政策制定者、国际科学项目和政府间气候变化专门委员会（IPCC）进行接触。

The Arctic Ocean is exceptionally susceptible to climate change. Recent studies have shown that surface seawater is warming faster than in other oceans. In addition, atmospheric CO2 dissolution in seawater is causing Ocean Acidification (OA). The documented retreat of sea-ice will increase light penetration, including UV. These environmental parameters (temperature, OA and UV) are highly likely to act as stressors and alter the Arctic Ocean ecosystem structure and function which in turn will feed back on climate. One such feedback is the cycling of climatically active trace gases and their emission to the atmosphere (here: CH4, N2O, DMS, CO). These trace gases are rapidly produced and consumed by a number of physical and biological processes. For example, the biggest source of CO in surface seawater is via UV-induced photochemical reactions. Yet, the likely response of trace gas cycling to climate change remains largely unexplored. This hinders our ability to predict the future direction of this important climate-feedback. We propose to investigate this feedback by a) developing the basic understanding which will underpin a predictive tool and b) developing the predictive tool itself (computer model). We will achieve this using three complimentary tools: Firstly, novel, high-tech spatial observations of trace gases (with depth as well as horizontal) which will allow us to identify major controls on their cycles and estimate their present flux to the atmosphere. Secondly, direct experiments where the three stressors will be manipulated while trace gas cycling pathways are monitored. The novelty of our approach here, lies in the use of individual and combined stressor manipulation (e.g. OA alone versus high temperature and OA together). This will allow us to explore potential synergistic or antagonistic effects between stressors. We will use state-of-the-art chemical and biological observations to track changes in trace gas cycling. For example, we will monitor the abundance and activity of key genes involved in trace gas cycling. These experiments will give us explicit and refined understanding of trace gas cycling in relation to the stressors. Thirdly, we will employ computer modelling which will translate this understanding into a predictive tool that will be used to predict the impact of future climate change. Finally, and in order to rapidly translate our relevant findings to policy, we will engage with the public, policymakers, international science programmes and Intergovernmental Panel on Climate Change (IPCC) through our comprehensive impact plan.