Although agriculture could contribute substantially to European emission reductions, its mitigation potential lies untapped and dormant. Market-based instruments could be pivotal in incentivizing cost-effective abatement. However, sector specificities in transaction costs, leakage risks and distributional impacts impede its implementation. The significance of such barriers critically hinges on the dimensions of policy design. This article synthesizes the work on emissions pricing in agriculture together with the literature on the design of market-based instruments. To structure the discussion, an options space is suggested to map policy options, focusing on three key dimensions of policy design. More specifically, it examines the role of policy coverage, instruments and transfers to farmers in overcoming the barriers. First, the results show that a significant proportion of agricultural emissions and mitigation potential could be covered by a policy targeting large farms and few emission sources, thereby reducing transaction costs. Second, whether an instrument is voluntary or mandatory influences distributional outcomes and leakage. Voluntary instruments can mitigate distributional concerns and leakage risks but can lead to subsidy lock-in and carbon price distortion. Third, the impact on transfers resulting from the interaction of the Common Agricultural Policy (CAP) with emissions pricing will play a key role in shaping political feasibility and has so far been underappreciated.
POLICY RELEVANCE
Following the 2015 Paris Agreement, European climate policy is at a crossroads. Achieving cost-effectively the 2030 and 2050 European targets requires all sectors to reduce their emissions. Yet, the cornerstone of European climate policy, the European Union Emissions Trading System (EU ETS), covers only about half of European emissions. Major sectors have been so far largely exempted from carbon pricing, in particular transport and agriculture. While transport has been increasingly under the spotlight as a possible candidate for an EU ETS sectoral expansion, policy discussions on pricing agricultural emissions have been virtually absent. This article attempts to fill this gap by investigating options for market-based instruments to reduce agricultural emissions while taking barriers to implementation into account. 相似文献
Forest commons in Slovenia are a poorly known indigenous institution for common resource management. They are a functional entity linked to a specific community that establishes interpersonal and intergenerational ties, as well as a link to the resource. We refer to shared ownership of resource, once made of pastures; today forests prevail. Collective property management remained despite community changes and legislation development. Today registered forest commons represent approximately one-third of those that existed before 1945. We highlight seven developmental turns to explain their revival. Six indicators are used in the analysis of current conditions. Forest commons are a potentially effective response to forest management challenges in Slovenia but also a potential model of social cohesion, rational resource use, and a balance between forest use and conservation. However, they are plagued by state ignorance, which hinders statistically sound analyses. 相似文献
Saliency detection is an effective approach to extract regions of interest (ROIs) for remote sensing images. However, existing saliency detection models mainly focus on ROI extraction from a single image and usually are not able to produce satisfactory results because of complex background interference in remote sensing images. The employment of mutual information in a set of remote sensing images can provide an effective solution to this issue. In this paper, we propose a novel saliency detection model for multiple remote sensing images to simultaneously extract ROIs and identify images without ROIs. First, common salient feature analysis based on synthesized feature clustering and global contrast is implemented to exploit global correspondence in the synthesis feature domain, thereby highlighting preliminary ROIs against background interference and assigning lower saliency values to images without ROIs. Then, we design an exclusion criterion based on saliency value judgment to remove images without ROIs, and the remaining saliency maps are refined by an enhancement strategy. Finally, the enhanced maps serve as a feedback to yield a homogenous synthesized feature space in which integral ROIs with subtle borders are extracted by the reused cluster-based saliency calculation. Experiments reveal that our model outperforms seven state-of-the-art models by achieving the best ROC curve (AUC = 0.945) and maximal F-measure at 0.729. 相似文献