Customizing CO2 allocation using a new non-iterative method to reflect operational constraints in complex EU refineries
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Developing a robust method for CO2 allocation in oil refineries is an ongoing debate within the life cycle assessment (LCA) community. Several methodologies reported in the literature, mostly performing sequential and iterative calculations, tend to be biased toward diesel at the expense of gasoline, failing to properly consider the role played by hydrogen. This paper develops a new non-iterative refinery CO2 allocation method to explore the concept of customized allocation to overcome the inherent bias in standard methods.
The allocation methodology is based on a system of linear equations built around the material and energy balances of a refinery. After describing the process of building such system, it is shown that the carbon allocation values of all final products and intermediate streams are directly obtained by solving it. A numerical example of CO2 emission allocation to major refinery products is provided from an optimized refinery linear programming (LP) case for the European refining industry, based on literature projections for 2020.
Results and discussion
The paper presents the key emission sources in the European refinery sector, and by using a standard mass-based allocation technique, we show that the carbon intensities of refined petroleum products derived using the non-iterative method are consistent with other studies. We confirm the findings that the standard allocation typically used in attributional refinery LCA tends to reward diesel to the detriment of gasoline. We attempted reconciling this by applying a reallocation factor to customize the CO2 allocation to represent the “real” economic purposes of process units reflecting the constraints European refineries face today. This moderated the octane production effects given the important role the reformer plays in hydrogen co-production, where the emission burden of highly knock-resistant reformate is redistributed to hydrogen and carried through to diesel.
By customizing the allocation of CO2, we demonstrated that the differences between a consequential and an attributional approach in refinery LCA can partly be reconciled. We now run into the risk of increasing the subjectivity of the attributional method by using “judgment calls” to decide on the choice of weightage to be applied. We invite the wider LCA practitioners to further investigate the use of this new non-iterative method for allocating CO2 and explore the concept of reallocation factors as means to customize emission allocation.
KeywordsAttributional CO2 allocation Fuel GHG Joint production Linear programming Non-iterative methodology Oil refinery
- ANL (2013) Greenhouse gases, regulated emissions and energy use in transportation model. Argonne National Laboratory, ArgonneGoogle Scholar
- Bouvart F, Saint-Antonin V, Gruson J-F (2013) “Well-to-tank” carbon impact of fossil fuels. French Environment and Energy Management Agency (ADEME)Google Scholar
- CARB (2009) Proposed regulation to implement the low carbon fuel standard. Volume I. Staff Report: Initial Statement of Reasons. California Air Resources BoardGoogle Scholar
- CONCAWE (2013) Oil refining in the EU in 2020, with perspectives to 2030. CONCAWE, BrusselsGoogle Scholar
- CONCAWE (2017) Estimating the marginal CO2 intensities of EU refinery products. CONCAWE, BrusselsGoogle Scholar
- Dale BE, Kim S (2014) Can the predictions of consequential life cycle assessment be tested in the real world? Comment on “Using attributional life cycle assessment to estimate climate-change mitigation…”. J Ind Ecol 18(3):466–467Google Scholar
- EC. (2009) Directive 2009/28/EC of the European parliament and of the council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing directives 2001/77/EC and 2003/30/EC. Off J Eur Union:16–62Google Scholar
- El-Houjeiri HM, Vafi K, Duffy J, McNally S, Brandt AR (2015) Oil production greenhouse gas emissions estimator OPGEE v1.1 draft EGoogle Scholar
- EPA (2010) Part II Environmental Protection Agency. 40 CFR Part 80 Regulation of fuels and fuel additives: changes to Renewable Fuels Standard Program; Final Rule. Washington: National Archives and Records AdministrationGoogle Scholar
- European Commission (2015) Reference document on best available techniques for mineral oil and gas refineries. Seville, Integrated Pollution Prevention and Control (IPPC)Google Scholar
- European Union (2016) BioGrace. (The Intelligent Energy Europe Programme) Retrieved from http://www.biograce.net/
- ICCT (2014) Upstream emissions of fossil fuel feedstocks for transport fuels consumed in the European Union. The International Council on Clean Transportation, Washington DCGoogle Scholar
- JEC (2014a) Well-to-Wheels analysis of future automotive fuels and powertrains in the European conext, version 4.a. Joint Research Centre-EUCAR-CONCAWE collaborationGoogle Scholar
- JEC (2014b) Well-to-tank appendix 2—version 4a. Joint Research Centre-EUCAR-CONCAWE collaboration. Ispra, European CommissionGoogle Scholar
- thinkstep (2012) GaBi 6 Professional database Retrieved from http://www.gabi-software.com/support/gabi/gabi-6-lci-documentation/