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During the last two decades CO2 emissions increased rapidly along with the growth of production and energy use in the industrial sector in Thailand. We use the Logarithmic Mean Divisia Index (LMDI) method to decompose the source of changes of CO2 emission level and CO2 emission intensity of the sector for the period 2005–2017. The results show that during this period, on average the amount of CO2 emissions and the CO2 emission intensity increased annually. The structural change effect helped reduce both the amount of CO2 emissions and the emission intensity. However, the increased energy intensity of individual industries led to an increase in the amount of CO2 emission and CO2 emission intensity. The study thus calls for policies to reduce energy intensity of firms in the manufacturing sectors in order for Thailand to benefit from industrial growth without having to incur greater polluting emissions. Keywords: CO2 emissions, LMDI decomposition, Manufacturing industries, Thailand

Since the 1990s, CO2 emissions have increased steadily in line with the growth of production and the use of energy in the manufacturing sector in Thailand. The Logarithmic Mean Divisia Index Method is used for analysing the sources of changes in CO2 emissions as well as the CO2 emission intensity of the sector in 2000−2018. On average throughout the period, both the amount of CO2 emissions and the CO2 emission intensity increased each year relative to the baseline. The structural change effect (effect of changes of manufacturing production composition) reduced, but the intensity effect (effect of changes of CO2 emissions of individual industries) increased the amount of CO2 emissions and the CO2 emission intensity. The unfavourable CO2 emission intensity change came from the increased energy intensity of individual industries. The increased use of coal and electricity raised the CO2 emissions, whereas the insignificant change in emission factors showed little impact. Therefore, the study calls for policies that decrease the energy intensity of each industry by limiting the use of coal and reducing the electricity used by the manufacturing sector so that Thailand can make a positive contribution to the international community’s effort to achieve the goal of CO2 emissions reduction.

The study computes and analyses the sources of the change of energy intensity of the manufacturing industries in Thailand during the period (1991–2011) using the decomposition method. The Logarithmic Mean Divisia Index is computed and the results show that the energy intensity in the period (1991–2000) increased greatly from the increased energy intensity of each industry. In the more recent period (2000–2011) the energy intensity declined a little. However the decline was mainly from the structural change effect with negligible contribution from decreased energy intensity of each industry. The findings imply the need to balance industrial restructuring policies with efforts to reduce energy intensity for a sustainable economic development. Besides, there is much room for individual industries to improve their energy efficiency. Policies on restructuring energy prices and other non-price related measures should be devised to induce individual industries, particularly the highly energy intensive ones, to reduce their energy intensity.

The study aims at finding the energy intensity and the sources of the changes of the energy intensity of the steel and steel products industry in Thailand using the firm level data collected from the surveys and interviews of steel firms in 2005 and 2012. The study finds that the energy intensity of the industry during the decade of domestic and global economic turbulent time in the 2000s fluctuated. The intensity declined immediately after recovering from the 1997 financial and currency crises but moved in an inverted U-shaped curve when the industry went through the various changes of production structure during 2003 to 2010. The decomposition analysis based on the logarithmic mean Divisia index method finds that the source of the changes of the energy intensity of the industry was dominated by the structural change effect. The fluctuation of the energy intensity was found despite a persistent decline, albeit relatively small, in the energy intensity of individual subsectors. This calls for the need to strengthen the effect of subsector energy intensity changes to help reduce the energy intensity of the industry in the long term. The study results imply four policy measures the government should use to induce steel firms to reduce their energy intensity and thus use the energy in the most efficient way.