(695b) Life Cycle Carbon Footprint of Renewable Electricity Generation from Aspen Forest Harvest in Wisconsin, USA

The Renewable Portfolio Standard which mandates increased production of electricity from renewable sources in conjunction with shut down of pulp and paper mills in the Great Lakes region raises the question of “how to most sustainably utilize lands previously used by the pulp and paper mills?” The timber wood from these forest lands can be a promising feedstock for energy production in the form of electricity. In this study, we aim to use life cycle assessment (LCA) to investigate the more sustainable way of utilizing these lands, by comparing an afforestation scenario where the forest is allowed to grow back undisturbed while continuing to use electricity from the electric grid and a bioenergy scenario where the forest is utilized for electricity using life cycle assessment (LCA). The bioenergy scenario also investigated various intensive harvest rotation of the forest in 20, 40, and 80 yr cycles. This study is an attributional LCA where the same amount of electricity displaced in the bioenergy scenario will be modeled to be obtained from the grid in the afforestation scenario.

The study investigates aspen forest harvest in Wisconsin as a case study. A life cycle assessment model is used to quantify the cradle-to-grave GHG emission of renewable electricity, including soil and landscape C change, wood harvest, and combustion in fluidized bed boiler. The soil and landscape C changes in the LCA model is simulated using the DAYCENT ecosystem model parameterized for the site for both the afforestation and bioenergy scenarios using site-specific data such as weather, soil texture and carbon, etc while the LCA software, SimaPro is used to model the generation of electricity from timber. This study also investigates the potential effect of climate change in future years will have on the scenarios modeled. We assume moderate (2.1 °C/century) and severe climate warming (4.2 °C/century) scenarios with 10% increase in annual precitation as inputs to the DAYCENT model to project effects on forest carbon pools.