Drivers of CO2 emissions in the former Soviet Union: A country level IPAT analysis from 1990 to 2010
Introduction
Climate change has become one of the most urgent global environmental problems. Despite numerous policy initiatives to limit global warming to a 2 °C increase, one could observe an unprecedented growth in material wealth and an associated 44% increase in CO2 emissions over the last two decades [1]. There are only a small number of countries that have managed to decrease their emissions during this period – and most of them come from the FSU (former Soviet Union ) [1].
Little research has been done on these countries and their changes in energy use and CO2 emissions. This study closes this gap by investigating the drivers of change of CO2 emissions over the last 20 years in 15 post-Soviet republics: Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russian Federation, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. With a combined population of over 286 million inhabitants, or 4.2% of the world population, the region, in 2010, generated a GDP (gross domestic product ) of 1.26 trillion USD (measured in constant 2005 US dollars), representing approximately 2% of global GDP [2].
In the early 1990s, newly established Former Soviet republics experienced significant decreases in wealth and associated GHG (greenhouse gas ) emissions as a result of decreasing economic outputs and structural economic changes. Both CO2 emissions and per capita GDP decreased by 35%; GHG emissions in 1990 was 3.66 billion tons of CO2, representing 17% of global emissions, but by 2010 falling to 7.9% of global emissions [1], [2].
These countries have always been very diverse economically, environmentally and culturally despite being part of the USSR. After gaining independence in the early 1990s, their economic, political and social transition processes went on even more diverse paths: while the three Baltic States, who became EU (European Union) member-states in 2004, are praised as champions in liberalization and stabilization, other post-Soviet republics were slower in economic reforms and democratization processes, with Uzbekistan being the worst procrastinator [3].
There are several studies looking at socio-economic changes in former Soviet republics after the collapse of the Soviet Union [4], [5], [6], [7], [8], [9] as well as studies analyzing changes in energy consumption and intensity, GHG emissions and environmental pressures [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20]; only some of which used decomposition analysis. But these studies are more than 10 years old now and are only looking at either one country [21] or at the FSU as a block [22], [23], [24], [25], [26], [27]. Another shortcoming is that in global CO2 studies, the FSU is usually analyzed as one block [22], [23], [24], [25], [26], [27]. These studies conclude that the income effect explains the lower GHG emission level in the FSU compared to OECD (Organization of Economic Cooperation and Development) countries, but much of this effect is canceled out by higher aggregate energy intensity in the FSU. However, they are missing important details due to the disparate trajectories and profiles of individual countries; moreover, their results are dominated by Russia as the biggest country in the region.
This study is the first providing detailed country by country analyses aiming to identify the determining factors for change in CO2 emissions in 15 post-Soviet republics from 1990 to 2010 by applying a more disaggregated version of the commonly used IPAT index decomposition analysis.
Section snippets
Description of the case study region
The region is very diverse, and differences among countries in the region are both large (see Table 1) and persistent over time. Within that group, Russia is the biggest country accounting of half of the population and two thirds of primary energy consumption and CO2 emissions. Other big countries in the region are Ukraine, Kazakhstan and Uzbekistan.
There are also significant and widening differences in income, with per capita GDP ranging from 463 USD in Tajikistan to 10,371 USD in Estonia in
Materials and methods
There are two dominant methods used for time-series decomposition, namely SDA (structural decomposition analysis ) and IDA (index decomposition analysis ). A comparison between the two can be found in Hoekstra and van den Bergh [29]. SDA is based on input–output analysis. Rose and Casler [30] provided a review on its theoretical basis and main features. IDA uses index number theory in decomposition and its advantage is that it can be uses to study any available data at any level of aggregation
Change in CO2 emissions of the FSU
Results from additive decomposition analysis in Fig. 1 show that CO2 emissions in the FSU increased by 392 million tons or 20%, from 1970 to 2010; the main driving forces for this increase were affluence (per capita GDP) and population. Until 1998 changes in CO2 emissions were closely following affluence but since emissions have decoupled from changes in affluence. This was possible as other factors stimulated emissions savings.
Table 2 shows that during the 1970s increasing carbon intensity of
Discussion and conclusions
Global studies suggest that changes in affluence and carbon intensity of GDP can explain most of the changes in CO2 emissions [26], [27]. In our study we use these and other factors for a detailed look at the changes in CO2 emissions in the FSU.
Ang and Zhang [22] compared energy-related CO2 emissions in different world regions and concluded that lower income and population could explain the lower aggregate carbon emission level in the FSU compared to OECD countries, but much of this effect is
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