Abstract

Bioenergy use is expected to increase significantly to support energy strategies and to meet climate targets in a large number of countries. Agricultural residues as an energy resource have attracted a lot of interest, as the use of residue biomass is perceived as beneficial to mitigate greenhouse gas emission and to be less harmful to the environment than other biomass resources. Here we present a holistic sustainability assessment of the use of cereal straw for heat and electricity production in Denmark. The assessment applies a methodology and framework developed by the Global Bioenergy Partnership. Sixteen sustainability indicators within the three pillars of sustainability (environmental, social and economic) are quantified or assessed qualitatively together with their development over time from year 2000–2014/2015. The assessment points to a number of benefits of straw based bioenergy as reductions in GHG emissions, income generation and jobs for a rural population, reduced use of fossil fuels and increased diversity of the national energy supply. These benefits come at a risk of soil degradation and soil organic matter mining, of increased emissions of non-greenhouse gases. The assessment shows that land allocation to straw harvest for energy has increased over time together with land productivity. The diversity of the national energy supply has increased over time just as the infrastructure required to support straw to energy supply chains. Ecologically there is a potential for further use of agricultural residue biomass for energy. To realise the potential sustainably, attention should be put on developing guidelines or regulation on biomass harvest, on avoidance of environmental burden shifting, on logistics and efficient conversion to energy services, and on maintaining a suitable organisational and policy framework. The framework of the Global Bioenergy Partnership proved to be a versatile tool for the assessment of bioenergy sustainability, also in a developed country. It is, however, relying on specific data sources and formats, which in many cases are not readily available.

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