Land-use change (LUC)-related greenhouse gas (GHG) emissions determine largely whether bioenergy is a suitable option for climate change mitigation. This study assesses how LUC emissions influence demand for bioenergy to mitigate GHG emissions, and how this affects the energy mix, using Brazil as a case study. A methodological framework is applied linking bioenergy supply curves, with associated costs and spatially explicit LUC emissions, to a bottom-up energy system model. Furthermore, the influence of four key determining parameters is assessed: agricultural productivity, time horizon, natural succession (NS), and the use of dynamic emission factors (EFs).
Demand for new bioenergy plantations range from 0.5 to 6.7 EJ in 2050, and is avoided when its EF reaches above 15 kg CO2/GJbiomass. Dynamic EFs result in earlier and larger use of bioenergy. Static EFs attenuate all emissions evenly over time, resulting in relative high emissions around 2050 when the carbon budget is most stringent. This in contrast to dynamic EFs, having early high peaks because of clearance of natural vegetation, but relatively small long-term emissions when the carbon budget is most stringent. Exclusion of NS, in combination with spared agricultural land, results in a demand of 6.7 EJ, because of its low carbon penalty. Assuming that land is spared due to continuous yield increase (which is the reason to include NS as and EF component), bypasses the fact that yield improvements (that make those lands available) take place because of demand for bioenergy.
When low-carbon biomass is in limited availability, increasing electrification is observed, leading to electric capacity increase of 62% (mainly wind and solar energy), and a 12% energy system costs increase. Inclusion of spatiotemporal explicit supply potential and LUC emissions leads to improved bioenergy deployment pathways that come closer to the real situation as the dynamic nature of LUC emissions is included.