Commonly defined as the potential for implementing a mitigation or adaptation option, climate actions’ feasibility encompasses much more than a simple “can-do” attitude. The implementation of climate action has been particularly studied after the Paris Agreement and has sky-rocketed since its inclusion in the latest IPCC Reports. The feasibility of adaptation options in Africa, the water sector in urban and rural landscapes, or mitigation actions in developing countries are just a few examples of a term whose definition is still ongoing. However, a huge gap exists between what is planned and what is currently being implemented to make sure we reach climate goals effectively..
The evaluation of feasibility is complex, and based on the evaluation of barriers (those that constrain climate action) and enablers (those that enhance climate action). Thus, analysing case studies provides empirical evidence on an action’s planning, implementation, and monitoring processes. While recent comprehensive conceptual frameworks offer a more holistic, strong and structured visual approach, iterations between testing theoretical frameworks with empirical data might lead to adequate solutions.
Some international repositories work on compiling empirical data on climate action. For example, the Global Covenant of Mayors – A complete collection of action plans and monitoring reports from the MyCovenant reporting platform, 4th Release is a comprehensive database where signatories worldwide report on their sustainable energy climate action plans (SECAPs). Analysing such data has proved to serve the purpose, as recent studies are already using it to delve into feasibility extensively and even identify key predictors of greenhouse gas emissions for cities committing to mitigate. The following sections will delve into such data and provide an overview of some observations that can be useful in identifying barriers and enablers for empirical implementation.
What can be feasible?
The features of climate actions can define their feasibility. For instance, the lack of detailed information in climate action planning is an acknowledged barrier to action implementation. Different types of actions might also have different constraints. While developing synthetic alternatives to fossil fuels, such as hydrogen or others, might face technological maturity constraints, other mitigation strategies like solar fields or wind farms require huge land extensions. Understanding the type of climate action and its requirements facilitates identifying barriers.
Figure 1 depicts the number of mitigation actions per sector compiled in the GCoM Database and their implementation status. Local heat and cold production seems to be the most successful sector, with a percentage of completed action above 10%. Nevertheless, it is also the sector with fewer actions available. In contrast, the residential sector has substantially greater actions but shows a much lower completed percentage. Hypotheses can be made: while local heat and cold production barriers might be more tied to technological aspects, which might be surpassed by economic means, tenure can strongly limit the capacity to operate in residential buildings.
Figure 1 Stacked bar chart showing the number of mitigation actions per mitigation sector and the percentage of total Completed actions. The left Y-axis represents the number of total actions, while the right Y-axis depicts the percentage of total actions Completed. Source: Authors. Data: Global Covenant of Mayors – A complete collection of action plans and monitoring reports from the MyCovenant reporting platform, 4th Release
When can something be feasible?
Temporal aspects are critical in feasibility analysis due to two reasons. Firstly, context varies through time. A climate action might be feasible in a specific context, but its feasibility might be compromised if the situation changes. For instance, Figure 2 shows the distribution of mitigation actions through time. While the bars show the number of actions per year in different implementation statuses, the black line draws the percentage of completed actions. While it is a hypothetical thought, a decreasing percentage of completed actions is identified when external global events such as the financial crisis of 2008 or the COVID-19 pandemic. Similarly, Figure 3 shows how minimising the time between approval of mitigation plans and actions relates to higher implementation rates.
Figure 2 Temporal distribution of mitigation actions, based on the GCoM Database. The left Y-axis shows the count of total mitigation actions, while the right Y-axis shows the percentage of completed mitigation actions. Source: Authors. Data: Global Covenant of Mayors – A complete collection of action plans and monitoring reports from the MyCovenant reporting platform, 4th Release
Figure 3 Distribution of actions according to the years that passed between the approval year of the plan where the action was included and the actual implementation start. An analysis of the time between the plan’s approval and the implementation start of mitigation actions shows that the most completed actions tend to start even before the approval. However, some values appear extremely negative, potentially pointing towards a tendency to include already completed actions in plans developed afterwards. Thus, the data shall be interpreted cautiously. When looking only at actions implemented the same year as the plan approval, we see an increase in the percentage of completed actions, while six years after approval, the share of completed actions decreases substantially. Source: Authors. Data: Global Covenant of Mayors – A complete collection of action plans and monitoring reports from the MyCovenant reporting platform, 4th Release
Who is involved in defining feasibility?
The interactions between agencies can significantly influence feasibility. The lack of clearly defined responsibilities or a failure to consider the needs of vulnerable groups can decrease the likelihood of a successful outcome. Mitigation can improve while accounting for vulnerable groups and just procedural planning. To empirically identify that, it has been analysed whether mitigation actions account for vulnerable groups. First, it can be seen that the vast majority of mitigation actions claim to consider “All” vulnerable groups. However, when targeting specific groups that are not shaped by economic issues – low-income, unemployed, and persons living in sub-standard housing – the completed rate appears higher.
Figure 4 Number of mitigation actions targeting vulnerable populations (bar) and share of completed actions (line). Source: Authors. Data: Global Covenant of Mayors – A complete collection of action plans and monitoring reports from the MyCovenant reporting platform, 4th Release
Understanding Feasibility Barriers and Enablers
The results of the empirical analysis of the Covenant of Mayors data showed some factors that might constrain or enhance the implementation of mitigation in Europe. Figure 5 presents a graphical interpretation of the identification of potential barriers and enablers. It offers a comprehensive and integrated approach that might increase the understandability of barriers and enablers data, aiming to help climate planners and implementors to better understand feasibility. While specific barriers are usually attached to a specific dimension, they can happen in different phases of the implementation. For example, a lack of information on the measure can happen during the planning stage, while the social acceptance can translate into protests that typically appear from the implementation phase.
Figure 5 Integrated graphical summary for the identification of barriers. The different barriers and enablers identified in the analysis are listed on the left: (1) the role of planning information on short-implementation-times measures; (2) the relevance of the timeframe between the plan approval and the start of the implementation; (3) the importance of targeting vulnerable groups. The different planning stages have also been listed on its right, as each of the mentioned factors occurs at a different point of the measure timeline. For a better understanding, the example of social acceptance as a barrier has been placed as a phenomenon that typically impacts the implementation and operationalisation stage of the action, reducing its effectiveness. Finally, each factor has been categorised according to the dimensions used by multidimensional approaches.
