4.2. Decomposition Analysis Results
Measures to save carbon dioxide emissions in the manufacturing industry are particularly challenging, as the sector faces a constant struggle between economic growth drivers and sustainability issues [
3]. Decomposition analysis have been constructed for Latvian manufacturing industry to monitor changes in total industrial CO
2 emissions over the period from 1995 to 2019 determined by five main factors—the industrial activity effect, structure effect, energy intensity effect, fuel mix effect, and emission intensity effect. The study period was divided in five groups, each accounting for a 5-year time interval, except for the last group, which represents the time period from 2015 to 2019 and, thus, includes a 4-year time interval. Since there were no data on 2020 yet available, year 2019 values were the latest available data that were included in the study.
Figure 6 shows the results of the decomposition analysis in combination with the CO
2 growth rates during the representative period.
The overall CO2 growth rate in the Latvian manufacturing industry have been fluctuating over the study period. Steady decreases were observed for the periods from 1995 to 2000 and from 2010 to 2015, when the CO2 growth rates were −22% and −26%, respectively. However, in the intervals from 2000 to 2005 (+1%) and from 2005 to 2010 (+3%), the CO2 growth rate indicated an upward trend, while in the interval from 2015 to 2019, the CO2 growth rate was equal to −1%. It can be concluded that CO2 reduction in the manufacturing industry has stagnated in recent years, and there has been little improvement in the last 5 years. Furthermore, the fluctuations in the results show that the changes in CO2 emissions are unsteady, so a more detailed study of the influencing factors should be conducted.
Table 3 summarizes the main decomposition results in total absolute values. Significant differences are observed between periods. In the first period (1995–2000), the main driver of changes in industrial CO
2 emissions was a decrease in energy intensity. This can be explained by the significant changes in the general economic restructuring and structure of the economy, when, after the restoration of independence in Latvia, the existing enterprises were forced to reorganize their original production methods and numerous new manufacturing companies entered the market. Therefore, significant investments were made and modernization measures were carried out in the manufacturing companies, which led to an increase in efficiency. In addition, the consumption of coal and petroleum products was significantly reduced during this period, which contributed to the overall reduction of CO
2 emissions.
In the second period (2000–2005), an increase in CO2 emissions from manufacturing industries was observed. In the first period, the main driver of changes in CO2 emissions was the effect of industrial activity. Increasing demand in both local and export markets led to a significant increase in production volumes, which increased production capacity and drove the overall development of the industry. Improvements in energy and emissions intensity could not compensate for the effect of increasing industrial activity, so CO2 emissions increased during this period.
In the third period (2005–2010), similar to what was observed in the second period, total CO2 emissions increased by 33.8 thousand tons in absolute values and showed a 3% CO2 growth rate. The period is characterized as the period before the global financial crisis, when a general decrease in industrial activity was observed in all manufacturing subsectors. During this period, a significant shift to more energy-intensive sectors was observed.
The fourth period (2010–2015) shows a large decrease in CO2 emissions. The period is characterized by a large significant restructuring that occurred due to the existence of the largest metal producer in the market. As the metal production sector accounted for 25% of the total CO2 emissions of the manufacturing sector in the past, the bankruptcy of the largest player in the market subsequently affected the overall reduction of industrial CO2 emissions. During this period, a large effect was also observed in the factor of energy intensity, which can be explained by the inefficiency of the production processes of the respective metal production company.
The fifth period (2015–2019), or the period representing the latest trends in the industry, showed a modest reduction in CO
2 emissions, where the total decreased in absolute terms by 10.7 thousand tons of CO
2 emissions and a negative growth rate of −1%. Although a significant improvement in energy efficiency and decarbonization measures can be observed, the effect from the improvements was largely offset by the increasing industrial activity. This suggests that the current pace of improvements may not be sufficient to achieve greater CO
2 emission reductions in industry in the future.
Table 4 summarizes the main events during the analyzed time intervals that influenced the change in CO
2 emissions.
Figure 7 illustrates year-to-year changes in the contribution of each decomposition factor to the changes in CO
2 emissions and the overall growth rate of CO
2 emissions with all subsectors included and
Table 5 summarizes the results in absolute values. The growth rate of CO
2 emissions is negative and shows a fluctuation pattern. However, two significant peaks are observed in the periods from 2009 to 2010 and from 2017 to 2018. The first one is explained by the recovery of the manufacturing industry after the financial crisis. However, a more detailed investigation is carried out to explain the reasons for the second peak observed in recent years.
Over the period of ten years, the manufacturing industry experienced a shift from one energy intensive sector (metal manufacturing) to other no less energy intensive sector (wood processing). However, the competitive advantage of the wood products manufacturing sector is the high share of RES utilization where wood residues and chips are used in thermal processes, which is a CO2-neutral fuel. If the aggregate values of the period are analyzed excluding 2013, which distorted the entire industry, the energy intensity effect played the most important role in reducing CO2 emissions.
The overall decomposition results show a positive trend towards the implementation of decarbonization measures, which in aggregate contributed to a reduction in overall emissions intensity in the industry. However, energy efficiency measures had a more than six times larger overall effect on CO
2 reduction compared to RES measures. The results prove that energy efficiency improvements are the most important strategy for the long-term development of companies to achieve energy and emission savings. The main reason for the increase in industrial CO
2 emissions is the effect of industrial activity, explained by the gradual annual increase in the volume of industrial production, which subsequently also led to an increase in total energy consumption to compensate for the increase in demand [
6].
These findings are consistent with the decomposition results of the Odysee-Mure energy efficiency decomposition model for Latvian industry [
41]. The Odysee-Mure energy consumption decomposition of industry for the period from 2000 to 2018 showed that the total energy consumption of industry increased by 2.5% annually in the studied period, which is mainly due to the increase in industrial activity in two important subsectors of Latvian industry—wood processing and non-metallic mineral production. The Odysee-Mure decomposition of energy efficiency in industry concludes that the improvements in energy efficiency, which enabled significant energy savings in industry and reduced the overall energy intensity of industry, contributed to the fact that total energy consumption did not increase even more [
41].
In total, in the time period from 2015 to 2019, a larger decrease in energy intensity in the manufacturing industry was observed compared with the first half of the decade. Part of the explanation in energy efficiency activity in past five years can be explained by autonomous developments in the companies, where in order to increase company competitiveness, there is a constant need to look for ways to decrease energy costs. However, another part of the explanation lies in the effect from policies that might have stimulated larger energy savings and the achievement of more ambitious energy efficiency targets [
34].
The results of the decomposition analysis showed that improvements in energy intensity have contributed most to reducing CO
2 emissions in the manufacturing sector in the past. Therefore, in order to observe how recent energy efficiency measures might have affected the green transformation in industry, a more detailed analysis is conducted for a period from 2015 to 2019.
Figure 8 illustrates the contribution of each effect on changes in CO
2 emissions and overall change in generated CO
2 emissions in each sub-sector in the time period from 2015 to 2019.
In total, in 2019, almost all manufacturing industry sub-sectors indicated a reduction in CO2 emissions compared to the levels of year 2015. However, three sectors reported the opposite. In 2019, CO2 emissions increased by 6% in transport equipment production sector, by 26% in wood processing sector, and by 9% in other sub-sectors compared to 2015.
The energy intensity effect was the main driver that contributed to the reduction of CO2 emissions in most of the sectors, except for not elsewhere specified sectors (plastics, rubber, furniture, and other manufacturing) in the period of the last five years. The wood processing sector and chemical and petrochemical production sector were the only sectors that indicated a negative tendency towards increasing the share of RES. Both sectors showed the opposite trend in their fuel mixes, indicating a decrease of RES in the total energy mix. The results show that despite significant energy efficiency improvements in these sub-sectors, total rise in industrial activity, structural effect, and fuel mix effect counteracted the energy intensity effect. Therefore, the current energy efficiency improvements could not compensate these effects, which drove up the overall CO2 emissions at a much higher pace than the implemented energy efficiency measures.
The structural effect shows the overall change in the contribution of a particular sector to the total industrial activity. That is, if the structural effect is positive, then the total industrial activity in the sector has increased as has the total contribution to the total industrial value added. On the other hand, a negative value means that the sector’s contribution to the total value added generated has decreased. The results show that the share of metals production sector, food processing sector, and textile production sector in the total industrial generated value added has decreased. This structural effect also contributed to the achievement of higher CO2 reductions in the sector. On the contrary, the chemicals production sector, non-metallic mineral production sector, and transport equipment production sector has raised their contribution to the overall generated industrial added value over the period from 2015 to 2019.
Year-to-year changes in CO
2 emissions were examined in more detail for the largest manufacturing sector in Latvia—wood processing, which alone consumes almost two-thirds of all industrial energy use in Latvia.
Figure 9 illustrates the results of the CO
2 emission decomposition for the wood processing sector.
Industrial activity was the main reason for the sharp increase in the total energy consumption of the wood processing sector during the studied period. The increasing demand for wood chips, wood pellets, and other wood products in the largest global export markets made the wood processing sector the fastest growing sector of Latvian industry and led to a significant annual increase in production volume over the last decade [
6]. The influence of export demand on industrial manufacturing activity and its embodied carbon emissions was demonstrated in the study of [
21], where a decomposition analysis of manufacturing CO
2 emissions in China showed that the growth of international exports of produced goods had the greatest influence on the increase in industrial CO
2 emissions [
21]. Similarly, Latvia’s wood processing sector has seen exports increase by 82% in the last decade (over the period 2010–2019) [
42] and 60% of the total wood products produced in Latvia were exported in 2019. Thus, the development of the sector is strongly influenced by the demand on international export markets [
33].
According to the decomposition analysis results, the fuel mix effect in the wood processing sector has been the main driver of the increase in CO2 emissions over the last five years. It shows that the sector has reduced its overall share of RES the total fuel mix, signaling a negative trend. An increase in fossil energy consumption in the wood sector was observed during the periods from 2014 to 2018. In part, this could be explained by the fact that overall demand for wood products, particularly wood pellets and chips, has increased across the global trade market, which has also pushed factories to increase their capacity. As a result, deficiencies in wood residues and wood chips, which are mostly used for combustion processes, have been compensated by natural gas or fossil energy. This also increased the total CO2 emissions generated in the industry.
Figure 10 illustrates the changes in the total distribution of energy products consumed in the wood-processing sector during the last five years. The change index shows the amplitude of how the consumption of certain products has changed compared to the values of 2015, which is taken as the base year. In general, it can be observed that the demand for heat has more than doubled; additionally, the consumption of oil products, natural gas, and electricity has gradually increased. However, the consumption of wood products has decreased. Therefore, the results indicate that there is an overall negative trend towards higher consumption of fossil energy resources.
Subsequently, this trend affects both the overall share of RES in the total fuel mix and the emission intensity of the sector, as shown in
Figure 11. It can be observed that the total share of wood products in the total fuel mix gradually decreased except in 2019. As a result, the emission intensity indicator fluctuates in the representative years. A significant peak in emission intensity is observed in 2018, when the share of RES in the total fuel mix reached the lowest value.
In addition, a correlation analysis was performed to investigate the relationship between the volumes of wood products produced and the RES share in the energy balance of the wood processing sector, as shown in
Figure 12. The results for the period from 2013 to 2019 show a strong correlation (R
2 = 0.9059), with a downward slope between the two variables. The correlation analysis confirms that the increase in industrial activity in the wood processing sector caused the share of RES to decrease. The exception of 2019 can be explained by the fact that in 2019 in Latvia was observed a winter with mild temperatures; therefore, there was also a lower demand for wood products, including pellets.