부산대학교 도서관

Climate change objectives of mitigation and adaptation are being mainstreamed into many policies and strategies around the world. In Europe, this has included the Rural Development Programme, which aims to tackle multiple social, economic and environmental objectives in rural areas, and the integration of climate change objectives adds another strand of complexity to the decision making process. When formulating policies determining the likely effectiveness of any particular measure can be challenging, especially with respect to the spatial and temporal variability of greenhouse gas emissions. This is a challenge faced by all countries and regions around the world. This study uses Europe as an example to explore this issue. It highlights the variability in emissions from land use operations that may be encountered under different conditions and time horizons and considers this in the context of policy formulation. The Optimal Strategies for Climate change Action in Rural Areas software has been adapted to derive net greenhouse gas emissions for rural development operations for all regions in Europe. Operations have been classified into five categories based on their benefit/burden over different time horizons. The analysis shows that it is important to understand the time period over which benefits or burdens are realised and determine how this fits with policy instruments, such as land management agreements and the permanency of actions. It also shows that in some regions an operation can have benefits, but in other regions it has burdens; thus, location can be critical. Finally, in the context of developing operations to meet multiple social, economic and environmental objectives, it is important to acknowledge that seeking options that only reduce emissions may not always be practical or possible. In some instances, we may have to accept an increase in emissions in order to meet other objectives. It is important that we evaluate the net greenhouse gas emissions of all operations, not just those aimed at climate change mitigation. We can then select those with the least burden in the process of developing optimal solutions to meet multiple objectives.