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Research Report

Emission balances of first- and second-generation biofuels: Case studies from Africa, Mexico and Indonesia

Dorian Frieden
Naomi Pena
David Neil Bird
Hannes Schwaiger
Lorenza Canella
Copyright Date: Jan. 1, 2011
Pages: 76
OPEN ACCESS
https://www.jstor.org/stable/resrep02305
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Table of Contents

  1. (pp. 1-4)

    This chapter describes the background, goal and scope of the analysis.

    Greater production and use of biofuels are being promoted to support, amongst other goals, mitigation of climate change. Governments in both developed and developing nations are adopting mandates and incentives to drive greater use of biofuels for transport. In response to these new drivers, use of proven crops, conversion technologies and fuels (first-generation pathways) is increasing; at the same time, research into and testing of new crops, conversion technologies and fuels (second-generation elements) are accelerating.

    Biofuel pathways tend to be evaluated against a number of criteria, including: cost; technological...

  2. (pp. 5-9)

    The description of the methodology begins with an overview of biofuel GHG emissions. Following this is an explanation of how the systems are modelled using the BioGrace calculation tool, and then a review of the allocation approach and how LUC emissions are calculated.

    The study considers the following sources of GHG emissions, including emissions due to energy inputs and auxiliary materials:

    land use change (LUC);

    cultivation of feedstocks;

    transport of feedstocks to the bioethanol plant;

    production of the biofuel and its co-products;

    co-products exported from the system;

    transport of the biofuel, either to the first point of distribution in-country or...

  3. (pp. 10-21)

    This chapter provides the generic data used across all case studies, brief descriptions of the various biofuel pathways considered and biofuel-pathway-specific data. The first section provides generic data that are independent of feedstocks and processing technologies. Subsequent information is organised by biofuel pathway. Each biofuel pathway section includes technology-specific data such as biofuel yields per MJ feedstock and country-specific data such as feedstock productivity or fertiliser use. Where no country-specific data were available, default values were used; these are the same for the various cases.¹

    The biofuel pathway sections include very brief descriptions of the processes. A more detailed overview...

  4. (pp. 22-57)

    This chapter presents the results of the analysis for each biofuel pathway and country, in terms of GHG emissions per MJ biofuel produced. Due to necessary rounding, aggregation of subtotals may differ slightly from totals in the following tables.

    Results derived directly from the BioGrace tool are presented in overview tables. The overview tables also contain, where available, comparisons with standard values from the RED or from other sources where the biofuel pathway is not included in the RED. In particular, the RED does not include default values for jatropha. For comparison, values from the UK’s former Renewable Fuels Agency...

  5. (pp. 58-59)

    The calculation of emissions from the non-LUC component is based on regional information, whereas that for the LUC component is based on global modelling. As a result, the LUC component is not regionally differentiated, but rather depends only on the type and origin of the feedstock (e.g. LUC is the same for all regions in the ‘first generation only’ scenario). Further regional differentiation was not possible with the GLOBIOM model for the following reasons.

    1. The GLOBIOM model does not distinguish between direct and indirect LUC; it calculates the effects of the 2 together;

    2. The GLOBIOM model does not distinguish between...

  6. (pp. 60-60)

    The production of biodiesel from jatropha in Mexico and from palm oil in Indonesia, where CH4 emissions are not captured, have the highest GHG pathways amongst those examined. The 5 pathways with the lowest emissions all use wood as the feedstock. These low emissions result from the fact that low or negative emissions from LUC are attributed to these pathways. However, these pathways require second-generation conversion technologies. Bioethanol from sugarcane in Mexico and Indonesia have the lowest emissions from first-generation pathways.

    Where the ‘first generation only’ value for emissions from LUC is applied, emissions from LUC dominate pathway emissions. Where...