Low-carbon scenarios for Russia’s energy system: A participative backcasting approach
Maria Sharmina
Tyndall Centre for Climate Change Research, University of Manchester
Suggested citation: Sharmina, M. (2017) Low-carbon scenarios for Russia’s energy system: A participative backcasting approach. Energy Policy, 104, p.303-315. doi:10.1016/j.enpol.2017.02.009.
Abstract:
Despite the high profile of climate change in scientific and policy discourse, the Russian government has thus far failed to commit to an emission reduction target based on the latest science. Given Russia is a key supplier of fossil fuels, a major greenhouse gas emitter, and climate impacts on its vast territory likely to have far-reaching consequences, this contextual research shows that the country’s current policies fall woefully short of what is required to implement the Paris Agreement. To support Russia in developing informed, internally consistent and scientifically literate energy policies, this paper presents low-carbon emission trajectories commensurate with the 2°C goal, using stakeholder-informed backcasting. The results illustrate that even if Russia’s CO2 emissions peak in 2017, a reduction rate of at least 9% per year between 2020 and 2030 is required to meet a 2°C budget constraint. These sustained rates are in excess of anything achieved globally or, indeed, deemed possible within most studies. Such emission reductions would involve unprecedented material changes to Russia’s energy system, including both rapidly cutting energy demand and building extensive low-carbon infrastructures. Nevertheless, failure to transform Russia’s existing policies will likely have global repercussions for achieving the Paris Agreement’s goals.
Keywords: emission scenarios; backcasting; Russia; climate change targets; cumulative emissions
1Introduction
In 2013 and 2014 the Intergovernmental Panel on Climate Change (IPCC) published its fifth report confirming a range of carbon budgets associated with the 2°C characterisation of dangerous climate change. More than 150 nations, including Russia, have recognised the 2°C target and committed to hold “the increase in the global average temperature to well below 2°C above pre-industrial levels”(UNFCCC, 2015). However, the countries’ current domestic pledges do not add up to this global commitment. There is a gap of 8–10GtCO2e (or 18–23%) per year by 2020 between their collective pledges and a 2°C pathway(UNEP, 2014).
Russia is an example of this disconnect between national climate mitigation measures and explicit international commitments. One the one hand, Russia is a signatory to 2°C. On the other hand, it is one of the countries whose national emission reduction target of 25% by 2020/2030 compared to 1990(Russian Government, 2015a) does not amount to a fair and science-based contribution to climate change mitigation (Kokorin and Korppoo, 2014; Sharmina et al., 2015). The low level of commitment to 2°C is further evident in the government’s attempt to sideline this target. For example, one of Russia’s communications to the UN Framework Convention on Climate Change specifies that 2°C “should not become the point of departure for a ‘top-down’ delineation of who pledges what” (Russian Government, 2014).
Continued global inaction and the accompanying climate change will have profound repercussions for Russia’s energy system and the wider prosperity of society. Some early climatic impacts will be beneficial, but over time most are likely to be negative. For example, increasing sleet load will lead to more breaks on overhead power transmission lines (RosHydromet, 2008b). As climate change intensifies river runoff, riverbed erosion may damage underwater parts of the national pipeline network. In the Russian Far North, substructures and foundations of both pipelines and hydrocarbon production sites are expected to become less stable due to thawing permafrost (RosHydromet, 2008b). With Russia being among the top three contributors to an observed global temperature increase (Matthews et al., 2014) and a key supplier of fossil fuels, climate impacts on its vast territory are likely to have worldwide implications.
To bridge the policy gap between global and domestic mitigation commitments, evidence-informed policy is essential. In policy-relevant research, there are two key gaps in this area. Firstly, to date, noin-depth Russia-focused scenarios for the county’senergy system have been developed constrained by carbon budgets, i.e., meaningfully linked to globaltemperature rises. Secondly, Russia-focused emission studies tend to cluster around highly aggregated top-down models and forecasting(e.g. Fiodorov et al., 2009; Malakhov, 2010; Novikova et al., 2009; Tchouprov, 2010). The dearth of exploratory, rather than predictive, and stakeholder-informed bottom-up tools implies that aspects of the country’s energy system remain overlooked. This paper develops scenario storylines and quantitative snapshots of Russia‘s energy system that serve as a starting point for a transition to a 2°C pathway, informed by expert interviews.
2A review of Russia-focused emission scenario publications
The articles and reports were selected for this section based on one criterion: they should produce and discuss detailed emission pathways for the future energy system of Russia. Most of the studies were in Russian. Table1 shows that the reviewed studies have several common features. For instance, forecasting dominates the modelling exercises, with elements of backcasting incorporated in a few studies. Climate change impacts, cumulative emissions and the economic crisis are rarely considered. Input-output tables appear to prevail as a basis of top-down models; however, the studies fail to acknowledge weaknesses of the input-output approach in the context of Russian economy. In particular, the volatility of prices and major economic restructuring in the 1990s may render the results of input-output modelling inadequate.Although Table1 may not be exhaustive, it is evident that many studies have drawbacks sufficient to make them unsuitable for advising policy-makers. Therefore, there is a strong need for novel approaches, such as backcasting, to explore Russian emission pathways and targets in detail.
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Table 1. A review of Russia-focused emission scenario publications (Note: where possible the last column describes the most ambitious scenarios within each set)
Model and source / Top-down (TD) or bottom-up (BU) / End year / Modelled emissions / Forecasting (F) or backcasting (BC) / Recent economic crisis considered / Cumulative emissions considered / Main mechanisms/incentives of changes in carbon and energy intensityENERGYBAL-GEM – simple simulation model (Bashmakov, 2009) / TD / 2050 / CO2 / F / In 2 out of 6 scenarios / No / Energy efficiency, CCS, bio, nuclear, hydro and heavy reliance on renewables – the only scenario with slightly decreasing emissions (starting from ~2043). C price: €30-50tCO2e.
MESAP/PlaNet –simulation model (Tchouprov, 2010; Teske and Tchouprov, 2009) / TD + BU / 2050 / Energy-related CO2 / F with elements of BC / No / No / Phasing out nuclear energy; realising full energy efficiency potential; emphasis on renewables (incl. sustainable biofuels). Global carbon trading system assumed; $50/tCO2 in 2050. CCS not included.
TIMES –optimisation model (Fiodorov et al., 2009) / BU / 2025 and 2030 / Electricity and heat-related CO2 / F / In several scenarios / No / Proportions of CCS, renewable and nuclear energy are unclear. C price increases from $15 to 25/tCO2 in 2013-25.
Dynamic linear optimisation model (Nekrasov and Siniak, 2007) / TD (+ BU?) / 2030 / CO2 / F / No / No / Nuclear power increases from 21.7 in 2000 to 68 GW in 2030 (~40-45% of power stations). RES generate 12.5% of energy in 2030, if nuclear is not capped, and ~80% (calculated based on the text) if nuclear is capped.
MENEK-EKO –optimisation model (Malakhov, 2010; Malakhov and Dubynina, 2010) / TD + BU / 2030 / CO2, CH4, N2O, other GHGs / F in two scenarios and BC in one / No / No / Carbon ‘charge’ is used in the third scenario, but magnitude unclear.
CCS, renewables and nuclear not discussed.
Prices are used instead of physical units (i.e., a ‘classic’ input-output model).
Simple simulation model(Novikova et al., 2009) / TD / 2020 / CO2 / F / No / Yes, in all scenarios / The largest share of renewable energy sources is 6.6% of generated energy.
GDP energy intensity is the main factor driving emissions down in the scenarios.
SRES-based scenarios (RosHydromet, 2008a) / TD + BU / 2100 / CO2, CH4, N2O, other GHGs / F / No / No details provided / No details provided.
World Bank’s model (Safonov, 2000) / TD / 2012 / CO2 / F / No / No / No details provided.
WEM – World Energy Model (IEA, 2007) / TD + BU / 2030 / Energy-related CO2 emissions / F and BC / No / No / No details provided.
IIASA’s GAINS optimisation models (Cofala et al., 2008) / TD + BU / 2030 / CO2, CH4, N2O, SO2, NOx, PM / F / No / No / “…both through structural changes in the energy system (fuel substitution, energy
efficiency improvements) and through end-of-pipe measures (e.g., carbon capture).”
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3Methods
3.1The backcasting approach
The backcasting approach has evolved as an alternative to forecasting, with a twofold purpose (Lovins, 1976; Robinson, 1982). First, backcasting aims to break away from past and current trends, assuming they are incompatible with desirable future states. Second, it avoids relying on predictions of economic variables, for example, future costs of energy and technologies (i.e., monetised variables commonly used in optimisation and input-output models). The preference for backcasting narrows down the range of available modelling tools and offers scope for applying “explanatory models” (Börjeson et al., 2006) more suitable for generating explorative scenarios rather than predictions.
To generate low-carbon scenarios for Russia’s energy system, this paper adopts a stakeholder-informed backcasting approach. Figure1 provides an outline of the backcasting process; its iterative nature helps to verify feasibility of a desirable objective and devise appropriate transition paths. In participative backcasting, the iteration process is aided by stakeholder engagement.
Figure 1. Stages of the backcasting approach: solid lines – the sequence of steps at first iteration, dotted lines – subsequent iterations (based on Anderson, 2001; Bows et al., 2009; Robinson, 1990)
The importance of cumulative emissions for climate change (IPCC, 2014a) suggests that they should be integrated as a pivotal constraint in low-carbon scenarios. The backcasting approach is well placed to facilitate such integration, as the first stageof backcasting requires an overarching objective placing a constraint on results of a scenario exercise. In addition to 2°C cumulative emission budgets (or ‘carbon budgets’) there are two more types of constraint placed on scenarios in this paper: the inertia in both the energy system and in the socio-economic environment, and the feasibility of implementing the scenarios. Section4.2 expands on the second and touches on the third type of constraint, by describing and analysing past and current trends in Russia’s energy system and related aspects of the re-developing economy. This section corresponds to thesecond stage of backcasting. The third and fourth stages are covered in sections4.3 and 4.4 exploring ‘desirable’ future states of Russia’s energy system in 2050 and pathways towards them. An energy system is developed iteratively to fit the pre-set carbon budget constraint. The consistency, feasibility and implications of the scenarios (the fifth and sixth stages of backcasting) have been tested through iterations, internal peer review and stakeholder input and are presented in sections4.5 and 5.
3.2Stakeholder engagement
Stakeholder engagement is essential when researching societal issues that are complex, unstructured and long-term (Eames et al., 2013; van Asselt Marjolein and Rijkens-Klomp, 2002), such as climate change mitigation. Such issues are multi-disciplinary, multi-scale and multi-actor (Dendler et al., 2012; van Asselt Marjolein and Rijkens-Klomp, 2002) and hence difficult to tackle by a single group of actors such as researchers. To address this concern, the study has engaged expert stakeholders in the scenario development process. While all applications of the ASK model thus far have invited stakeholder input, it is the first time a participative scenario study has been done in respect to energy scenario in Russia.Stakeholders in this study helped to ground scenario assumptions and narrow the ranges of input variables, in addition to providing a reality check for the scenarios developed(see Supplementary Information for the pilot topic guide, sample interview questions and sample scenario summaries used in the expert interviews). The author then transcribed the interviews and used a simplified version of thematic analysis to interpret the findings.
Five pilot semi-structured interviews were undertaken over the telephone between March and June 2012, as Table2 details. The interviewees’ professional background varied widely and included buildings-sector researchers, an aviation-sector entrepreneur and policy experts. Predictably, policy experts offered general and overarching insights, suitable for the contextual framing of the paper, while industry experts gave more specific interviews. The pilot interviews have informed the content and structure of the research design in this paper.
Table2. A summary of pilot interviews with respondents from the industry and policy backgrounds
Respondent / Professional background / Respondent’s residence at the time of the interview / Interview date1 / Buildings-sector researcher / Western Europe / 09/03/2012
2 / Aviation-sector entrepreneur / Russia / 26/03/2012
3 / Buildings-sector researcher / Eastern/Central Europe / 17/04/2012
4 / Policy expert (research/NGO) / Northern Europe / 29/05/2012
5 / Policy expert (consulting/business) / Russia / 27/06/2012
The second stage of the stakeholder engagement process consisted of four face-to-face interviews and involved policy experts rather than industry representatives and governmental officials. The potential interviewees identified for the second stage recruitment focused on Russia’s fossil fuel industry and the EU-Russia energy security issues. With their expertise spanning from economic geography to technology and innovation to ‘Weak State’ environments, the breadth of the expertise was deemed sufficient for providing valuable insights to this paper, as politico-economic and governance issues cover much of the relevant context. As Table3 shows, two experts were part of the ‘younger’ generation socialised in their discipline during Russia’s modern history, i.e., in the past 10–20 years. The other two interviewees belonged to a more ‘senior’ generation with much of their expertise developed during the existence of the Soviet Union. It was hoped that this difference would further diversify the interviewees’ responses.
Table3. A summary of in-person interviews with policy experts
Expert / Expertise / Expertise developed during… / Interview date1 / Technology and innovation / …Russia’s modern history / 23/04/2013
2 / Political economy / …Russia’s modern history / 09/05/2013
3 / Economic geography / …the Soviet times / 21/05/2013
4 / Natural-gas markets / …the Soviet times / 13/06/2013
Reflecting the research objective of this paper, two interview topics of different scope were identified to be discussed during in-person interviews. The first topic had a narrow focus on presentation and framing, consistency and feasibility of the scenarios. The second topic had a broad focus on both existing and potential decarbonisation triggers and Russia’s socio-political context. Although each interview started with the first topic (in particular, the presentation of scenarios), the two groups were not discussed sequentially or in a linear fashion. For example, questions about consistency and feasibility of the scenarios led to the discussion of more complex issues related to the Russian context and potential policies for decarbonisation.
3.3The ASK-Russia scenario tool
The original scenario generator, ASK, was developed by the Tyndall Centre for Climate Change Research for constructing UK decarbonisation scenarios (Agnolucci et al., 2009; Bows et al., 2010). The approach was subsequently modified to explore emissions from China (Wang and Watson, 2008, 2009) and to develop emission pathways for the shipping sector (Bows-Larkin et al., 2014). For the purposes of this paper, the original, UK-focused, ASK tool was modified to accommodate geopolitical and national circumstances of Russia. The main peculiarities of Russia’s energy system, analysed in section4.2 and reflected in the ASK-Russia tool (Figure2), include Russia’s historic and current sectoral energy use and emissions, transmission and distribution losses, energy efficiency potential, and renewable energy potential.
Figure 2. A schematic representation of the ASK-Russia tool based on the original ASK
This modelling method differs from the reviewed AR5 pathways (see section4.7) in two principal ways: (a) the ASK tool’s simplicity and (b) stringent assumptions on emission peak years (only in the future, never in the past, in order to take historical emissions into account) and on the deployment of negative emission technologies (only in one scenario out of four). The latter assumption is due to ASK’s relying on proven technologies such as biomass, nuclear, solar and wind energy, and energy efficiency, in contrast to the AR5 pathways assuming a large quantity of negative emissions(Anderson, 2015; UNEP, 2014).
4Results and discussion
4.1Deriving the carbon budget constraint (backcasting stage 1)
The first stage of backcasting defines the overarching objective that the backcast scenarios will aim to fulfil. In this case, such an objective is a cumulative emission constraint, also known as a ‘carbon budget’, corresponding to a low probability of exceeding the 2°C target. Despite uncertainties associated with a 2°C target (Guivarch and Hallegatte, 2013; Shaw, 2013), it is adopted in this paper as “the least unattractive course of action” (Jordan et al., 2013). This study takes a range of carbon budgets for Russia from Sharmina et al. (2015), following the method developed by Anderson and Bows (2011). The overarching objective of the backcast scenarios developed in this paper is to characterise an evolving energy system for Russia in 2011–2050 within the 5.5–7.1GtC (20.2–26.1GtCO2) cumulative emission budget range. It lies within the range of budgets from the AR5 emission scenario database (IPCC, 2014b).
4.2Russia’s energy system: past and present (backcasting stage 2)
Scenario exercises attempt to understand the relationship between stability and change, which makes the analysis of major developments and trends essential. This section sets out a rationale for an urgent transition to a low-carbon future and highlights the decarbonisation potential of Russia’s energy system, corresponding to the second stage of backcasting.
4.2.1Energy infrastructure
Specific characteristics of Russia’s energy supply chain and physical geography suggest a number of potential threats to maintaining the current, conventional energy supply system. The main risks include the high depreciation and low renewal rate of capital stock, extensive power transmission lines, and climate change impacts on pipelines and other energy infrastructure.
One of the most significant problems facing Russia’s economy in general and its energy system in particular is the large proportion of ‘used up’ capital stock and equipment. Nureev(2010) estimates that, while in 1970 and 1980 about 70% and 64% of all equipment respectively was less than 10 years old, in 2000 almost 60% was older than 16 years. Although more recent data are unavailable, the trend suggests that the situation is unlikely to have improved, which may have consequences for the nation’s energy security.The age of plants and equipment determines, to a large extent, their energy efficiency. For example, the average energy efficiency of coal-fired power plants in Russia was 23.9%, as opposed to 34.7% in Canada, a country of a comparable climate and size (World Energy Council, 2016). Rezinskikh and Grin’ (2010)blame this situation on the slow-down both in commissioning new plants and in developing energy-efficient technologies in the 1990s, arising from broader socio-economic and political problems, including the lack of a business-friendly environment and limited democratic institutions (Nureev, 2010).