In order to assess whole nations or economic sectors regarding their contribution to CC or CC mitigation goals, other approaches than LCA or those in Table 4.5 above have been developed. They were derived from the productivity concept that is a common approach in economics and relate GHG emissions to economic output. Such approaches can be applied to an economic sector or a whole nation, for example C Productivity or its reciprocal C Intensity (Table 4.6; published as Appendix file to Hansen et al. (2016b))(6.3).
Dissertation A. Hansen Background Information: State of the Art
Table 4.6: Overview of some productivity approaches dealing with carbon (reproduction of Appendix Table A1 in Hansen et al. (2016b); references in brackets are listed in section 6.3.6)
Name NPP/NEP Carbon Productivity Carbon
Intensity
CSF Carbon efficiency CUDe
C emissions Unit of cost of a technology Unit of biochar C after 100 years
Baseline Usually one year Arbitrary period length, often one year
Marginal cost and projected emissions of reference technology
100 years Not stated Adjustable
Description Rate at which energy is converted into cost of the last unit) of emission abatement for varying amounts
Science Policy Policy Science Pharmaceutical
industry x-axis and costs per ton on y-x-axis
1. Measure C content
Table 4.6 –continued–
Name NPP/NEP Carbon Productivity Carbon
Intensity
CSF Carbon efficiency CUDe
Benefits In combination with
CUDe—Carbon Utilization Degree, CSF—Carbon Stability Factor, GDP—Gross Domestic Product, GHG—Greenhouse Gases, MACC—Marginal Abatement Cost Curves, NPP/NEP—Net Primary Productivity/Net Ecosystem Productivity, S&P/IFCI—Standard & Poor’s International Finance Corporation Indexes;
Unless otherwise indicated by superscripts, information was taken from cited References in the last row.
Dissertation A. Hansen From Impact to Resource Short Overview of Approaches applied in the Articles of the Thesis
5 Short Overview of Approaches applied in the Articles of the Thesis
A bioenergy pathways was chosen that was about to leave the pilot scale state and was being introduced economically in 2011 (IEA Bioenergy). Its biomass feedstock (SRC) had been esteemed promising (3.1): Large energy providers pursued its cultivation (for example Vattenvall Europe AG, Ehm 2011), and intensively approached farmers at that time to grow SRC, and to close supply contracts. Furthermore, long-term GHG data were available from poplar SRC sites as well as from neighbouring reference plots, cultivated with the region’s common cash crop rye (Kern et al. 2010).
For each manuscript, a comprehensive literature research was conducted prior to final methodological decisions; details are given in the respective articles.
The bioenergy pathway was modeled using an LCA Tool (Umberto® 5.6) (ifu&ifeu 1994-2011) for which unit processes existed from previous work (Möhlmann et al. 2000; Hansen et al. 2001). The tool includes a function to analyse uncertainty in the material flow models by MC analyses (4.2.2).
According to the state-of-the-art of LCA studies (Table 4.4), a MC analysis was performed (see para-meters and probability distributions in 6.1.2). The fossil reference system was taken from Klobasa et al.
(2009). Their model presents the substitution effects of biomass in the German electricity mix (4.1). In Hansen et al. (2016a) (6.2), the results of the Umberto® model were merged in spreadsheets (MS Profes-sional Plus 2010) with additional data from unit processes to represent two strategies for the insula-tion of buildings. For these strategies, a scenario analysis was performed due to the complexity of sys-tems and resulting problems in safeguarding the independence of parameters for a MC analysis.
Additional data were taken from LCA data repositories, for example ecoinvent (Frischknecht et al.
2005), and GEMIS (Fritsche & et al. 2014)(see details in the articles chapters). Additionally, telephone interviews were conducted with stakeholders for missing information, for instance with energy crop consultants who advise farmers on SRC implementation, or with feed producers who rely on specific agricultural ingredients for their product formula. These interviews have been qualitative and limited, therefore they cannot be considered as significantly representative for the complete sector.
The analyses used a life-cycle-based approach (see 4.1) and included the relevant production processes of crop cultivation and its production factors (fertilizers, pesticides, fuels, seeds). Allocation was avoided by system expansion where possible. Otherwise, a mixed approach was followed as in Eady et al. (2012). Detailed information on system boundaries and functional units are available in the respective articles (Hansen et al. 2013; Hansen et al. 2016b; Hansen et al. 2016a) (6.1-6.3). For the CC impact assessment, the three GHG out of the complete IPCC list were assessed that are the most relevant in an agricultural context: N2O, CH4 and CO2. Further GHG from the Kyoto list (UNFCCC 1998) were included in a pre-study of the uncertainty assessment but were found to be irrelevant and omitted in Hansen et al. (2013). An extended LUC assessment as a variation of the usual LUC
balancing approach was performed in Hansen et al. (2013). On the one hand, absolute N2O emissions from unfertilized6 poplar SRC plots were considered in the balance. In additional step, these emissions where balanced against the N2O that would have been emitted from the reference crop rye. Common LUC assessments just consider stock changes in above and below-ground biomass as well as in soil organic carbon as land use change effects (see 4.1.5).
In distinction to these impact-oriented assessments of biomass utilization, a five-plus-one step approach was developed in Hansen et al. (2016b)(6.3). Following a process chain assessment (Figure 6.8), it identifies productive C for each transformation process. Productive C in an anthropocentric view was defined as C that yields a useful output, that is it is (i) transformed into marketable products or provides useful services (e.g. insulation material, or energy generation (direct benefit)), or (ii)
performs important ecological functions (e.g. improves soil fertility (indirect benefit)). The ratio of the total productive C to C that was originally available in the biomass was defined as Carbon Utilization Degree (CUDe). Generic data for example calculation of productive carbon share in biomass chains (biogas and hemp fiber insulation) were compiled in spreadsheets and visualized with e!Sankey® 3.2.