Climate change mitigation scenarios and policies and measures: the case of Kazakhstan

Abstract

This article illustrates the main difficulties encountered in the preparation of GHG emission projections and climate change mitigation policies and measures (P&M) for Kazakhstan. Difficulties in representing the system with an economic model have been overcome by representing the energy system with a technical-economic growth model (MARKAL-TIMES) based on the stock of existing plants, transformation processes, and end-use devices. GHG emission scenarios depend mainly on the pace of transition in Kazakhstan from a planned economy to a market economy. Three scenarios are portrayed: an incomplete transition, a fast and successful one, and even more advanced participation in global climate change mitigation, including participation in some emission trading schemes. If the transition to a market economy is completed by 2020, P&M already adopted may reduce emissions of CO₂ from combustion by about 85 MtCO₂ by 2030 – 17% of the emissions in the baseline (WOM) scenario. One-third of these reductions are likely to be obtained from the demand sectors, and two-thirds from the supply sectors. If every tonne of CO₂ not emitted is valued up to US$10 in 2020 and $20 in 2030, additional P&M may further reduce emissions by 110 MtCO₂ by 2030.

Policy relevance

This article analyses Kazakhstan's climate change and energy efficiency policies by making use of a modelling platform that provides a consistent framework for testing dynamic hypotheses. The effects of different P&M have been evaluated as the differences between two scenarios according to the United Nations Framework Convention on Climate Change (UNFCCC) reporting guidelines. It concludes that domestic climate mitigation objectives are synergistic with energy efficiency goals, and the set of policies adopted to achieve both objectives should be planned, implemented, and enforced jointly. It also quantifies the GHG emissions reduction if the transition to a market economy proceeds quickly and successfully (∼ −100 MtCO₂e in 2030), and if a mitigation-specific policy is implemented (∼ −200 MtCO₂e in 2030) compared to a baseline projection, and it highlights the need to prepare more robust and detailed energy balances and inventory of emissions in order to develop and monitor the progress of the policies.

Keywords:

• bottom-up approaches
• climate change policies
• emission projections
• emissions scenarios
• energy models
• optimal emissions path

Notes

1. Labelled as the Third–Sixth National Communication (NC3–6) and marking the transition to becoming an Annex I country.

2. According to earlier inventories, net emissions in 1990 were 378 MtCO₂e.

3. In this article, $ means US dollars (constant of the year 2000). The local currency, Kazakh Tenge, is converted into current US$ using purchase power parity (ppp). Current US$ are converted into constant using the GDP deflator of the US.

4. The efficiency of coal used in power plants is in the 20–27% range.

5. Totals calculated via the two approaches may differ. Such differences can be reduced to zero (or almost zero) if appropriate. Lower heating values and emission coefficients are chosen for coal and oil products, so that material, energy, and carbon balances are assured in refineries and coal transformation processes.

6. As reported at http://unfccc.int/national_reports/items/1408.php, the UNFCCC secretariat has instructed the preparation of National Communications. The most recent documents (Diaz-Bone, 2009; Simeonova, 2009) refer to NC5.

7. These measures and policies include the following: (1) the Decree of the Government of the Republic of Kazakhstan No. 97, from 6 February 2013, which states that, from 1 July 2013, all imported cars must meet the Euro-4 standard; (2) the State programme of forced industrial-innovative development, 2014; (3) the Decree of the Government of the Republic of Kazakhstan No. 1181, September 2012, which sets requirements for the energy efficiency of buildings and their components.

8. The characteristics of MARKAL-TIMES models are illustrated in dozens of publications. A list of projects and applications is reported on the ETSAP website.

9. Weighted sum of CO₂, CH₄, and N₂O, in terms of CO₂e.

10. A more disaggregated approach/comparison by subsector/technology was carried out in NC3–6 to identify more detailed P&M. For instance, TFC was split by final consumption sector (transport, buildings, industry, agriculture) and TPES by sector (plants, refineries, coal processing, transmission, distribution). However, in the analysis of model results, a trade-off has to be reached between accuracy and detail.

11. ADES is equal to TDES in the WOM and WM scenarios, but is lower in the WAM scenario due to price increases.

12. CO₂ emissions in the WOM scenario are also shown: their growth index has the same profile as TDES.

Additional information

Funding

This work was supported by the Ministry of Education and Science under the Program ‘Research and development in energy efficiency, energy saving, renewable energy sources, environmental protection for 2014–2016' and the Joint Project of the United Nations Development Programme in Kazakhstan, the Ministry of Energy of the Republic of Kazakhstan, a Global Environment Facility entitled ‘Third National Communication of United Nations Framework Convention on Climate Change'.