Addressing Key Drivers of Regional C[O.sub.2] Emissions of the Manufacturing Industry in Japan.

• Author: Matsumoto, Ken'ichi

1. INTRODUCTION

   As a member country of the United Nations Framework Convention on Climate Change and as a signatory of the Kyoto Protocol, Japan has made eforts to reduce its greenhouse gas (GHG) emissions, particularly C[O.sub.2] emissions. Although Japan has not provided emissions reduction targets for the second commitment period of the Kyoto Protocol, it has continued its eforts toward emissions reduction. Japan ratified the Paris Agreement on November 8, 2016, and it has stated its aim of reducing its emissions by 2030 by 26.0% compared with 2013 levels.

   Japan's C[O.sub.2] emissions trajectories by sector are shown in Figure 1. Total C[O.sub.2] emissions in Japan increased until the reduction caused by the global financial crisis of 2007-2008. Emissions in 2007 were 16.2% greater than in 1990. Emissions increased again after recovery from the economic crisis, but they decreased following the Great East Japan Earthquake in 2011. Nevertheless, emissions in 2015 were still 7.7% greater than 1990 levels. In 2015, emissions from Japan's manufacturing industry accounted for approximately one quarter (24.4%) of the total. In addition, if emissions derived from the energy conversion sector were allocated to energy (i.e., electricity and heat) consumers, emissions from the manufacturing industry would have accounted for approximately 40% of the total. Thus, this industry constitutes the major source of emissions in Japan, making the reduction of its emissions extremely important. Emissions from this industry increased from 1990 to 2007 by 7.1%, but they decreased after both the financial crisis and the Great East Japan Earthquake. Overall, emissions from the manufacturing industry have changed little during the previous 25 years; emissions in 2015 were 3.1% lower than the 1990 levels.

   Various decomposition techniques have been used in numerous studies to investigate the factors behind the increases or decreases in the trends of time series of C[O.sub.2] emissions (Ang et al., 1998; Liaskas et al., 2000; Ang and Choi, 1997, 2002; Ang, 2005; Diakoulaki and Mandaraka, 2007; Shrestha et al., 2009; Bhattacharyya and Matsumura, 2010; Kumbaroglu, 2011; O' Mahony et al., 2012; Xu and Ang, 2013, 2014; Jeong and Kim, 2013; Ren et al., 2014; Xu et al., 2014; Fernandez Gonzalez et al., 2014a, 2014b; Ouyang and Lin, 2015; Zhang and Da, 2015; Ang et al., 2015; Roinioti and Koroneos, 2017; Shigetomi et al., 2018). (1) Most such decomposition studies have been conducted at the national scale. For example, Xu and Ang (2013) undertook a comprehensive literature review on index decomposition analysis (IDA) and found that such studies have been conducted in developed to developing countries at national scales (and for various sectors including national total emissions). Xu et al. (2014) applied the logarithmic mean Divisia index (LMDI) method to carbon emissions from 1995 to 2011 in China. They decomposed the emissions into five factors (energy structure, energy intensity, industry structure, economic output, and population scale effects). They found that the major driver of carbon emissions was the economic output effect, followed by population scale and energy structure effects. There have also been previous studies that have focused on Asian countries (Shrestha and Timilsina, 1996; Paul and Bhattacharya, 2004; Shrestha et al., 2009; Jeong and Kim, 2013; Ren, Yin and Chen, 2014; Ouyang and Lin, 2015; Zhang and Da, 2015), although few have considered Japan. One example of a decomposition study that did consider Japan was conducted by Henriques and Borowiecki (2017). They applied the extended Kaya decomposition technique to identify the drivers of long-term C[O.sub.2] emissions since 1800 for 12 developed countries, including Japan. Okamoto (2013) used the Shapley-Sun decomposition method to decompose the C[O.sub.2] emissions from domestic industries into five factors (changes in economic scale, industrial composition, energy intensity, import composition, and import scale), focusing on the impact of the growth of the service economy in Japan on changes to C[O.sub.2] emissions. Yabe (2004) performed decomposition analysis of Japanese industrial sectors from 1985 to 1995 using an input-output table. In their respective decomposition analyses, Greening (2004) and Lu et al. (2007) focused on the transportation sector in Japan (and other countries), while Malla (2009) focused on electricity generation.

   The work by Luo et al. (2017) represents one of the few examples of an application of decomposition analysis at local scale (city level). They focused on the two cities of Shanghai and Tokyo and they compared their respective factors. Wang et al. (2018) is another example; they decomposed provincial C[O.sub.2] emissions in China into eight factors, highlighting the breakdown of the total emissions of each province. However, neither of these two studies undertook detailed analysis of the decomposed factors.

   In Japan, the Act on Promotion of Global Warming Countermeasures constitutes the basic regulation to combat climate change. It stipulates the responsibilities of the national government, local government, and business operators are as follows. (1) The national government shall support the programs of local governments for the control of GHGs and endeavor to provide technical advice and other measures to promote activities by private entities. (2) Local governments shall endeavor to provide information and take other measures to promote activities by local businesses concerning the control of GHGs. (3) Business operators shall strive to develop measures for the control of GHGs regarding their business activities and cooperate with programs of the national government and local governments for controlling GHGs. (2) Based on the act, local governments (prefectures and cities) have established ordinances for global warming countermeasures. However, few of the ordinances propose regulations on the GHG emissions of the various industrial sectors, although some do include numerical targets (Chiba Prefecture 2015b). One example of a mandatory measure by local government on the business sector is the emissions trading scheme of Tokyo, which was launched in April 2010. It obliges large-scale business establishments, which consumed energy of 1500 kl of oil equivalent in the previous year, to reduce their C[O.sub.2] emissions and to participate in emissions trading (i.e., cap and trade). However, the main actions directed toward the mitigation of climate change by business entities in Japan have been based on the voluntary approach (Voluntary Action Plan on the Environment from 1997 and Commitment to a Low Carbon Society from 2013) by Keidanren (Japan Business Federation). These comprise voluntarily determined action plans for GHG emissions reductions by business associations (including 31 industry associations), and each association sets its own emissions reduction targets followed by reviews through the plan-docheck-act cycle. Therefore, the interactions between local governments and industrial sectors in relation to measures adopted to mitigate climate change are limited.

   The Paris Agreement refers to the roles of non-state actors and therefore eforts at the local level are essential to the reduction of C[O.sub.2] emissions nationally. Prefectures in Japan are obliged to set their own targets and action plans for GHG emissions reductions. Because prefectures set ambitious targets, the combined target of all 47 prefectures is to reduce emissions by 2030 by 25.6%-28.0% compared with 2012 levels, which is greater than the national target (E-konzal and Kiko Network, 2016). To achieve this target and to set targets beyond 2030, it is crucial to identify those factors that drive prefecture-level C[O.sub.2] emissions. In particular, considering the emissions situation outlined above, the identification of such factors and their changes in relation to the manufacturing industry of each prefecture is essential. The studies by Yabe (2004) (Japan), Diakoulaki and Mandaraka (2007) (European Union), Jeong and Kim (2013) (Korea), Ren et al. (2014) (China), and Ouyang and Lin (2015) (China) are examples of the application of C[O.sub.2] emissions decomposition in the manufacturing industry; however, they only considered the national level.

   The purpose of the present study was to adopt a decomposition approach (i.e., IDA) to investigate those factors behind the changes in C[O.sub.2] emissions between 1990 and 2013 in relation to the Japanese manufacturing industry. We implemented IDA at the prefectural rather than the national level. If we analyzed the factors at a national level, the effects would be averaged. By performing prefectural-level analysis, we could identify the factors behind the emissions increases/decreases in detail.

2. METHODS

   2.1 Decomposition Approach

   We conducted IDA to investigate those factors behind the changes in C[O.sub.2] emissions in the manufacturing industry of the 47 prefectures in Japan (Figure A1 in Appendix A). Four factors were considered in the decomposition: C[O.sub.2] emissions per energy use in sector i (carbon intensity effect), energy use per gross prefectural product (GPP) in sector i (energy intensity effect), share of GPP in sector i (structure effect), and total GPP in the manufacturing industry (activity effect).

   There are several types of IDA method, e.g., the LMDI and Laspeyres index (Ang, 2004; Roinioti and Koroneos, 2017). We used the LMDI approach (Ang, 2005, 2015) because it has been used often in similar decomposition studies (Shrestha et al., 2009). Ang (2005, 2015) proposed two types of LMDI decomposition formula: multiplicative and additive decomposition and we chose to adopt the latter. (3)

   The equations used for the decomposition analysis are shown in Eqs. [1]-[6]. Equation [1] represents the breakdown into the four factors of the total annual C[O.sub.2] emissions of the sectors of the...