|Title: ||Spatial and temporal dimensions of Life Cycle Assessment: application togreenhouse gas emissions of bioenergy|
|Other Titles: ||Spatiale en temporele dimensies van levenscyclusanalyse: toepassing opbroeikasgasemissies van bio-energie|
|Authors: ||Gomes Dias Almeida, Joana|
|Issue Date: ||5-May-2015 |
|Abstract: ||Bioenergy was put forward as a way to reduce greenhouse gas (GHG) emissions of energy provision. In order to ascertain that this goal is met it is necessary to compare the cumulative emissions of bioenergy and fossil-based energy supply chains. One well-accepted method to do so is life cycle assessment (LCA), which records all the material and energy flows in and out of a supply chain and estimates their impact on climate through the global warmingnbsp;(GWP) indicator. Land use change (LUC) emissions are claimed to potentially invert the emission reduction potential of bioenergy feedstocks, but arenbsp;left out of LCAs due to methodological difficulties and a lack of data. In fact, GHG emissions fromnbsp;are distributed in time and space, in contrast to the static and spatially-abstract nature of LCA. Bioenergy has motivated anbsp;deal of efforts in making life cycle inventories (LCIs) more complete in terms of LUC emissions and also in making LCA more receptive to their spatial and temporal variations. Thenbsp;goal is to accurately estimatenbsp;emissions and their impact on climate, and to better value emissions occurring at different moments in a life cycle. This thesis aims at estimating and integrating LUC emissions in LCA of bioenergy, gauging the importance of time considerations in GWP and thenbsp;of spatially explicit LCIs.|
Here, we focus on the case of Jatropha initiatives in Mali. Jatropha is an oil-yielding bioenergy crop that was promoted as an accessible, decentralized energy source for rural populations in developing countries. Previously published Jatropha LCAs reported it to have lower emissions than fossil fuels. Such LCAs, however, did notnbsp;into account the full scope of GHGnbsp;as LUC emissions were left out andnbsp;lacked reliable yield information. Their magnitude for Jatropha is highly site specific and therefore largely unknown. We started by making a generic LCA, with literature data collected during early Jatropha investments, and a site specific onenbsp;field data, including on yields. Next, we measured LUC emissions based on field data and estimatedrsquo;s carbon debt. The field datanbsp;of measurements of carbon content in soil and biomass in Jatropha plantations and proxies of previous land uses: cropland and fallow land. We concludenbsp;yield and previous land use are key factors in the environmental performance ofnbsp;production system. Improving productivity in degraded lands seems to be the priority, starting with an engagement of growers in tending and harvesting Jatropha plants.
Based on the data collected in the first part of the thesis, we built an LCI in annual time steps for a whole rotation span of Jatropha. We used RothC model to determine how the soil organic carbon (SOC) content evolves under Jatropha throughout the years, revealing that Jatropha plantations lose SOC rapidly after LUC and a new equilibrium isnbsp;after 9-10 rotations (180-200 years). We analyzed this LCI with the GWP metrics currently adopted by the IPCC and also with a novel dynamic LCA approach that addresses the effects of emission timing and time horizon choice in the GWP of the life cycle. Our results were, however, inconclusive regarding its advantages relative to the classic GWP of IPCC. The timenbsp;of carbon sequestration and release in the Jatropha system is too short to have different signals innbsp;two approaches, which was expected. In addition, dynamic LCA yields a wide range of results depending on the time of analysis, maintaining the subjectivity of this choice.
Further on, we explored new spatial applications of LCA in a spatially explicit supply chain optimization exercise. We used a pre-existing optimization model and parameterized it with life cycle impact assessment datanbsp;the production of electricity from Jatropha oil in Mali. The goal was to obtain the spatial outline and input requirements of the optimal supply chains to fulfil a certain electricity demand in Mali. We included a spatially-explicit inventory ofnbsp;emissions in function of harvestable Jatropha seednbsp;the Southern part of Mali, based on estimated yields of Trabucco et al. (2010). This approach successfully modeled supply chains optimized for minimal GWP. This mainly linkednbsp;finding the parts of the country where the best LUC emission to seed yield ratio is obtainable, as these are the factors most decisive on the final GHG emission balance. These optimal cultivation areas are located not on degraded lands, but on more productivenbsp;and conflict with cropland.
This thesis showed how life cycle thinking can serve the betterment and sustainable design of land-based production systems and how their spatial and temporal dimensions challenge the LCA methodology. While a small contribution is done here to the time issues in LCA, we demonstrated the usefulness of extensive, time-specific LCIs to appreciate the sustainability of a bioenergy initiative. On the one hand, we showed that including LUC in the LCI can compromise Jatropha’s low GHG emission premise. On the other hand, such comprehensive LCIs add value to life cycle thinking as a framework to conjecture prospective, more efficient Jatropha and other crop-based bioenergy supply chains. Future research should include improving LCIs through better, more specific data on the emissions from land conversion and land occupation with bioenergy, namely extending them with approachable indirect land use change estimates.
|Publication status: ||published|
|KU Leuven publication type: ||TH|
|Appears in Collections:||Division Forest, Nature and Landscape Research|