Risks and opportunities related to environmental transition are usually evaluated through the use of scenarios, produced and maintained by international bodies such as the International Energy Agency. This approach assumes perfect knowledge of the scenario by the agent, but in reality, scenario uncertainty is an important obstacle for making optimal investment or divestment decisions. In this paper, we develop a real-options approach to evaluate assets and potential investment projects under dynamic climate transition scenario uncertainty. We use off-the-shelf Integrated Assessment Model (IAM) scenarios and assume that the economic agent acquires the information about the scenario progressively by observing a signal, such as the carbon price or the greenhouse gas emissions. The problem of valuing an investment is formulated as an American option pricing problem, where the optimal exercise time corresponds to the time of entering a potential investment project or the time of selling a potentially stranded asset. To illustrate our approach, we employ representative scenarios from the scenario database of the Network for Greening the Financial System in two energy-related examples: the divestment decision from a coal-fired power plant without Carbon Capture and Storage (CCS) technology and the potential investment into a green coal-fired power plant with CCS. In both cases, we find that the real option value is very sensitive to scenario uncertainty: the value of the coal-fired power plant is reduced by 25% and that of the green coal investment project is reduced by 7% when the agent deduces the scenario by observing carbon emissions, compared to the setting when the true scenario is known. We also find that scenario uncertainty can lead to considerable delays in the implementation of green investment projects, emphasizing the importance of timely and precise climate policy information.

与环境转型相关的风险和机遇通常通过使用由国际能源机构等国际机构制作和维护的场景进行评估。这种方法假设代理完全了解场景，但实际上，场景的不确定性是做出最佳投资或撤资决策的重要障碍。在本文中，我们开发了一种实物期权方法来评估动态气候转型情景不确定性下的资产和潜在投资项目。我们使用现成的综合评估模型（IAM）情景，并假设经济主体通过观察信号（例如碳价或温室气体排放）逐步获取有关情景的信息. 投资估值问题被表述为美式期权定价问题，其中最佳执行时间对应于进入潜在投资项目的时间或出售潜在搁浅资产的时间。为了说明我们的方法，我们在两个与能源相关的示例中采用了绿色金融系统网络场景数据库中的代表性场景：没有碳捕集与封存 (CCS) 技术的燃煤电厂的撤资决策和潜在的投资一座采用 CCS 技术的绿色燃煤电厂。在这两种情况下，我们发现实物期权价值对情景不确定性非常敏感：与真实情景已知时的设置相比，当智能体通过观察碳排放量来推导情景时，燃煤电厂的价值降低了 25%，绿色煤炭投资项目的价值降低了 7%。我们还发现情景的不确定性会导致绿色投资项目的实施出现相当大的延误，这凸显了及时准确的气候政策信息的重要性。