Analyzing the Impact of Nuclear Power on CO2 Emissions

Sanglim Lee, Minkyung Kim, Jiwoong Lee
2017 Sustainability  
This study investigates the relationship between the nuclear power proportion and CO 2 emissions per capita using the panel dynamic ordinary least square method. The panel datasets consist of 18 countries covering 95% of the global nuclear reactors. The results indicate that a long-term 1% increase in nuclear power led to a 0.26-0.32% decrease in CO 2 emissions per capita. Additionally, in France, Germany, and Switzerland they demonstrate the existence of the environmental Kuznets curve-an
more » ... znets curve-an inverted U-shaped relationship between environmental pollution and income per capita. substitute for dirtier ones in the production of goods. Understandably, the EKC hypothesis can be accounted for with some mixture of scale, composition, and technique effects. The empirical evidence for this hypothesis is mixed at best, according to the estimation method, the data time periods and types, and the characteristics of countries [10] . There are mainly three research groups to examine the relationship between economic growth and environmental quality (we refer the reader to References [8, [11] [12] [13] [14] for a comprehensive survey). The first group investigates the relationship between economic development and environmental degradation in the framework of the EKC hypothesis. Recent studies include References [11, [15] [16] [17] . The second group examines the relationship between economic development and energy consumption and tests the causal relationship between these variables. Payne [18] delivers an extensive review on this issue. The third group combines the two research groups by investigating the relationship among environmental degradation, economic growth, and energy consumption. Many recent studies focus on the impact of renewable energy on CO 2 emissions in the EKC framework [12, 13, [19] [20] [21] [22] [23] . Consistent with the third research group focusing on nuclear power, Iwata et al. [5] estimated the EKC with the additional variable of nuclear power, and provided statistical evidence of the important role of nuclear power in reducing CO 2 emissions. Similarly, Iwata et al. [6] investigated the EKC for CO 2 emissions in 11 OECD countries by considering the role of nuclear power. These studies employ the autoregressive distributed lag (ARDL) model by Pesaran et al. [24] to consider the co-integration relation among their set of variables and analyze the role of nuclear power in reducing CO 2 emissions on an individual country basis. The ARDL has econometric advantages, in that it can be used with a mixture of I(0) and I(1) variables, and estimate the short-run and long-run parameters simultaneously (a time-series is said to be I(d) variable if its d'th difference is stationary), as a single co-integration approach. Iwata et al. [7] also analyzed the impacts of nuclear energy on CO 2 emissions using the pooled mean group (PMG) estimation method by Pesaran et al. [25] . Regarding nonstationary heterogeneous panels, the PMG approach allows the short-run coefficients to be heterogeneous but constrains the long-run coefficients to be identical across groups. Although these studies convincingly argue the relationship between nuclear power and CO 2 emissions, there are some limitations, in that the ARDL approach is based on individual countries and the PMG approach imposes that the long-run coefficient be homogenous across groups with nonstationary heterogeneous panels. To overcome such limitations, this study uses the panel dynamic ordinary least squares (PDOLS) method by Pedroni [26] , which has the advantage of combining cross-sectional and time-series data to secure sufficient data points, and allows for the heterogeneity of coefficients across groups with nonstationary heterogeneous panels. This study aims to examine the relationship between the nuclear power proportion (the ratio of electricity produced from nuclear power to total electricity) and CO 2 emissions per capita using the PDOLS method with nonstationary heterogeneous panels. The panel datasets in this study consist of 18 countries with more than four nuclear power plants each as of 2016, which operate 420 reactors, or approximately 95% of the 444 reactors worldwide. The results indicate that a long-term 1% increase in the nuclear power proportion leads to decreases of 0.26-0.32% in CO 2 emissions per capita. The main contribution of this study is, with the PDOLS approach, it provides statistical results as to how much nuclear power reduces CO 2 emissions per capita for both the group mean and individual countries currently operating most of the nuclear reactors in the world. Additionally, this study compares nuclear power with renewable energy in terms of mitigating CO 2 emissions. The remainder of this paper is structured as follows. Section 2 briefly reviews the econometric methodology used to analyze the relationship between nuclear power and CO 2 emissions. Section 3 features the data utilized. The results are presented in Section 4. Section 5 concludes the study. Estimation Methodology A three-stage procedure with nonstationary heterogeneous panels to analyze the relationship between the nuclear power proportion and CO 2 emissions per capita is employed in this study. First,
doi:10.3390/su9081428 fatcat:t4flj7x7ebasfb7h6wh73p7hsm