Decomposition of energy consumption and CO2 emissions in Mexican manufacturing industries: Trends between 1990 and 2008

Energy for Sustainable Development 16 (2012) 57–67

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Energy for Sustainable Development

Decomposition of energy consumption and CO2 emissions in Mexican manufacturing industries: Trends between 1990 and 2008 Claudia Sheinbaum-Pardo ⁎, Sergio Mora-Pérez, Guillermo Robles-Morales Instituto de Ingenieria, UNAM. Apdo. Postal. 70–472, Coyoacan 04510, México D.F., Mexico

a r t i c l e

i n f o

Article history: Received 10 February 2011 Revised 8 August 2011 Accepted 9 August 2011 Available online 3 December 2011 Keywords: Manufacturing CO2 emissions Decomposition Mexico

a b s t r a c t From 1990 to 2008 the share of the manufacturing sector in the Mexican CO2 emissions related to energy consumption decreased from 20% to 14%. This was due to increased emissions of the transport sector (32 to 40%), but also to an important decrease in energy intensity of the manufacturing industries. The objective of this paper is to explain the changes in CO2 emissions related to energy consumption of the manufacturing industries in Mexico. To this end, a decomposition analysis based on an additive Log Mean Divisia Index was developed, in order to estimate relative contributions of activity, structure, real intensity, and fuel switching changes in different industrial subsectors. The results show that structure and real intensity changes played an important role in the moderate increase of CO2 emissions of the Mexican manufacturing industries. However, real intensity changes do not always reflect energy efficiency derived from technological changes, they might also reflect changes in the structure of product production. © 2011 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

Introduction Mexico represents around 1.6% of the world's population, 1.9% of the world's GDP and 1.5% of CO2 emissions related to energy use (IEA, 2011). The Kyoto Protocol does not have binding commitments for Mexico to reduce their greenhouse gas (GHG) emissions, but there is an increasing pressure for some developing countries, such as Mexico, to adopt some kind of target, specially under the current climate negotiations towards a post Kyoto agreement. Under this framework, it is important to evaluate the performance of Mexican energy consumption and related GHG emissions in the last decades. Especially, in the manufacturing sector, since it appeared to have important achievements in reduction of CO2 emissions. From 1990 to 2008, the final energy consumption in Mexico increased at an annual average rate of growth of 2.4% (from 3167 PJ to 4814 PJ). Of all the sectors, transport had the most increase, while manufacturing industries had a relatively small increment (Fig. 1). The CO2 emissions related to final energy consumption (including emissions from electricity generation related to electricity use) also increased at an average rate of growth of 2.4% per year (from 225.4 to 346.7 Tg of CO2), where increase in emission from transport sector was 3.6% per year, and manufacturing 1.3% per year. In 2008, manufacturing industries represented 17.4% of the National GDP, 26% of final energy use, and 29% of energy related CO2 emissions (INEGI, 2010; SE, 2009). However, between 1990 and 2008, Mexican ⁎ Corresponding author at: Instituto de Ingenieria, UNAM. Ciudad Universitaria, 04510; Mexico DF, Mexico. Tel.: + 52 556233693. E-mail address: [email protected] (C. Sheinbaum-Pardo).

manufacturing GDP grew at an annual average rate of growth of 2.4%, while final energy consumption for the same sector increased only at 1% per year; this difference implied a decrease in manufacturing energy intensity of 26% in the analyzed period (Fig. 2). The objective of this paper is to explain the changes in energy consumption and related CO2 emissions of the manufacturing industries in Mexico. To this end, a decomposition analysis based on Log Mean Divisia Index (LMDI) was developed in order to estimate the relative contributions of activity, structure, real intensity, and fuel switching changes. The results show that structure and real intensity changes played an important role in the moderate increase of manufacturing energy use. However, we highlight the matter that real intensity changes using value added as the activity variable, do not always reflect energy efficiency derived from technological changes, they might also reflect changes in the structure of product production. To put this study in context, it is important to mention other studies on energy and emission decomposition analysis of the manufacturing sector conducted in recent years. For example, Akbostanc et al. (2011) developed an aggregate decomposition analysis for the Turkish manufacturing industries using LMDI. They found that the activity and energy intensity were the primary factors determining the changes in CO2 emissions during the study period. They do not present disaggregated results for different manufacturing industrial subsectors. Cahill and Gallacho (2010) discuss different decomposition methods to explain energy efficiency trends in European industry. They developed the VALDEX index in order to explain changes in energy efficiency. Wang et al. (2010) developed a disaggregate analysis for different manufacturing industrial subsectors using LMDI, on the changes in industrial electricity consumption in china from 1998 to

0973-0826/$ – see front matter © 2011 International Energy Initiative. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.esd.2011.08.003

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C. Sheinbaum-Pardo et al. / Energy for Sustainable Development 16 (2012) 57–67

Transport

Manufacturing

National

Residential

Commercial and public

Manufacturing

15%

Agriculture

Mining and construction 10%

3000

5%

2500

0% 2000

PJ

19 -5%

91

19

93

19

95

19

97

19

99

20

01

20

03

20

05

20

07

20

09

1500 -10% 1000 -15% 500

Fig. 3. Annual GDP growth in Mexico, 1991–2009. Total national and manufacturing sector.

0 90

19

92

19

94

19

96

19

98

19

00

20

02

20

04

08

06

20

20

20

Fig. 1. Final energy use in Mexico.

2007. Similar studies for China are presented by Liu et al. (2009) and Cai (2009). Also Reddy and Ray (2010) presented a decomposition analysis for the Indian manufacturing industries. Salta et al. (2009) present a combined methodology using MDI and specific energy consumption. In most of these studies, the reduction in energy intensity (energy consumption per GDP) isolated from structural and activity changes is conceived as an increase in energy efficiency due to either technological changes or use of recycled materials. In this study we show that in the Mexican case, changes in manufacturing energy intensity for several industrial subsectors, not always reflect energy efficiency measures, but might reveal changes in the mix of products in total production. These changes can be explained by market demand modifications or simply by the increment of product imports due to the North American Free Trade Agreement, and therefore a reduction in Mexican production. This is important in the analysis of trends in energy and emissions, because when changes in product mix do not represent important modifications in the production process, changes in energy intensity

GDP

Energy use

Carbon dioxide emissions

Carbon dioxide intensity

Carbon dioxide emission index 1.8 1.6 1.4

can be reversible, depending on product demand and market conditions (imports, exports of production of certain products). To understand the reasons for energy intensity changes in each industrial subsector it is important to undertake a more detailed analysis based on unit energy consumption (energy use per physical units of production). The analysis in this paper is carried out in stages. First, a general picture of the Mexican manufacturing industry is explained. Second, the methodology used to analyze trends in energy consumption and carbon dioxide emissions is introduced. Finally, results of the industrial subsector and conclusions of the study are presented. The data employed for energy use was obtained from the National Energy Balances (SE, 1997, 2007, 2009); the data used for value added 1 and production was obtained from the Economic Information System of the National Statistics Agency (INEGI, 2010). Mexican manufacturing industry Disaggregate analysis of manufacturing industries is often presented for classifications of manufacturing activities such as the International Standard Industrial Classification (ISIC). The energy data provided by the Mexican Ministry of Energy was disaggregated by subsector industries that were classified by the ISIC revision 4, under three and four digit sectors (UNSD, 2010). These subsector industries were iron and steel (ISIC 2410), petrochemicals and basic chemicals (ISIC 2011), paper and pulp (ISIC 170), sugar (ISIC 1072), cement (ISIC 2394), glass (ISIC 231), beer and malt (ISIC 1103), fertilizers (ISIC 2012), tobacco (ISIC 120), soft drinks; mineral waters and other bottled waters (ISIC, 1104), motor vehicles, trailers and semitrailers (ISIC, 290), rubber (ISIC, 221), aluminum (part of ISIC, 2420) and others. Activity and structure

1.2 1.0 0.8 0.6 0.4 0.2

08

20

06 07 20

20

04 05 20

20

02 03 20

20

00 01 20

20

98 99 19

19

96 97 19

19

94 95 19

19

92 93 19

19

19

19

90 91

0.0

Fig. 2. Changes in different indicators of Mexican manufacturing industries (1990 = 1). Note: Carbon dioxide emission index (energy use/CO2 emissions); carbon dioxide intensity (CO2 emissions/GDP).

At the beginning of the 1990s a process of economic liberalization took place in Mexico. State-owned companies were privatized, energy price subsidies were decreased, de-regulation affected several sectors of the economy, and trade liberalization was reflected in the North American Free Trade Agreement (NAFTA) that started in 1994. Although these structural changes were supposed to promote significant economic growth, especially in the manufacturing industries, the real picture showed a slight increase in the Mexican economy from 1990 to 2008. The average rate of growth was 2.92%, and the manufacturing industries increased by 2.87% (INEGI, 2010). Fig. 3 1 In the case of value added for the different industrial subgroups absolute value added in 1993 pesos is available from 1988 to 2004. From 2004 to 2007 value added is calculated with index production. For 2008 it is estimated for aggregate groups.

C. Sheinbaum-Pardo et al. / Energy for Sustainable Development 16 (2012) 57–67

illustrates the trends in National and manufacturing GDP. As shown, two economic falls hit the Mexican economy in 1995 and 2001 (besides 2009), and from 2004 to 2008, economy has grown less each year, even less in the manufacturing sector. Table 1 presents the manufacturing GDP structure by industrial subsector for 1990 and 2008, as well as the annual rate of growth of manufacturing value added in constant 1993 pesos. In 1993 the exchange rate was 3.1 pesos/US dollar (Banxico, 2011). As shown, the absolute value added for petrochemical, fertilizers, and tobacco was lower in 2008 than in 1990. This represents an important decrease in the production of these industrial subsectors. In the case of basic chemicals, cement, glass, rubber, and other manufacturing industries, the actual value added increased, but its participation in the manufacturing value added decreased. Sugar, paper and pulp, and aluminum industries almost maintained their share in the manufacturing value added and, iron and steel, malt and beer, bottled waters and automotive industries augmented their share. Energy and CO2 emissions In 2008, the iron and steel industrial subsector represented the largest final energy use (21.8%), followed by cement (12%), sugar (8.3%) and basic chemicals (8.2%). As shown in Fig. 4, the picture was quite different in 1990. The main modification was the reduction of the petrochemical industry. This changed its participation in the manufacturing final energy consumption from 16.4% in 1990 to 2.2% in 2008 (from 170.5 PJ to 27.7 PJ). Other industries also reduced not only their share in manufacturing energy consumption, but their absolute energy consumption as well. This is the case of basic chemicals (from 104.3 PJ to 102.4 PJ), sugar (from 118.6 PJ to 103.7 PJ), paper and pulp (55.4 to 51.8), fertilizers (from 13.8 PJ to 4.1 PJ), and aluminum (from 6.4 PJ to 4.3 PJ). On the other hand, the final energy matrix for manufacturing energy also had important changes during the analyzed period (Fig. 5). In 1990 fuel oil represented 24.1% of final energy use and it decreased to 6.2% in 2008. Fuel oil was replaced by petcoke (0% in 1990 to 10.8%); LPG (1.4% to 3%). In 1990, NG represented 41.2% of the manufacturing final energy consumption; it decreased to 28.3% in 2001, and then rose to 32.1% in 2008. Electricity had a constant increase during the period, from 16.8% to 28.6%. Table 2 presents the final energy consumption matrix by manufacturing industrial subsector for 1990 and 2008. Fuel oil use decreased in all industrial subsectors, and NG use increased in all subsectors with the exception of cement, tobacco, automotive, rubber and others. Petcoke grew in cement and basic chemicals and, the Table 1 Structure of manufacturing GDP.

Aluminum Fertilizers Sugar Rubber Tobacco Petrochemical Glass Basic chemicals Malt and beer Paper and pulp Cement Bottled waters Iron and steel Automotive Others Total Source: INEGI (2010).

Percentage of total manufacturing GDP

Value added average annual rate of growth

1990 0.3% 0.3% 0.8% 1.0% 1.1% 1.2% 1.6% 1.7% 1.9% 2.1% 2.4% 2.9% 3.2% 10.1% 69.4% 100.0%

1990/2008 2.8% − 6.5% 2.5% 1.2% − 1.2% − 3.0% 2.3% 1.5% 5.1% 2.9% 2.5% 3.7% 3.6% 5.7% 2.2% 2.7%

2008 0.3% 0.1% 0.8% 0.8% 0.6% 0.4% 1.5% 1.4% 2.8% 2.2% 2.3% 3.5% 3.7% 16.9% 62.9% 100.0%

59

share of electricity use in final energy consumption decreased in iron and steel, and glass. This reduction in electricity consumption in certain industrial subsectors reflects an increase in cogeneration. By 2008, the installed capacity of industrial cogeneration reached 2689 MW. Generation alone reached 15,679 GWh, which represented around 17% of total electricity consumption in that year (CRE, 2011). 2 CO2 emissions related to energy consumption can be estimated using the IPCC methodology and emission factors (IPCC, 2006): CO2 E ¼ ∑CEFj Fj þ ∑CEFe e

ð1Þ

Where CEFj is the CO2 emission factor for fuel j, F is fuel consumption of fuel j, CEFe is the CO2 emission factor for electricity supply, and e the electricity consumption. The electricity emission factor varied over time, depending on the mix of primary energy sources and the power generation. Between 1990 and 2008, the electricity emission factor given in tCO2/TJ changed from 187.1 to 144.0 (673.7 to 518.4 kg/MWh). This decrease was mainly due to a rise in the use of natural gas in combined cycled plants to the detriment of thermal power plants using fuel oil. CO2 emissions related to energy use in manufacturing industries increased from 85.3 Tg in 1990 to 109.7 Tg in 2008 (Fig.6). Cement industries were the manufacturing industrial subsector that presented the highest increase of all (from 8.2 to 14.5 Tg of CO2). Total CO2 emissions decreased in the same six industrial subsectors where energy presented reductions: basic chemicals (−5.3%), sugar (− 85.2%), petrochemical (− 84.0%) paper and pulp (− 19.2%), fertilizers (−74.2%) and aluminum (−44.0%). 2.3. Energy intensity Table 3 presents the energy intensity in MJ/1993 pesos for each manufacturing industrial subsector for 1990 and 2008. As shown, energy intensity increased for cement, glass, bottled waters, tobacco, and other industries, while it decreased for the other industrial subsectors. Fig. 7 to Fig. 9 show the trends in energy intensity for the whole period by industrial subsector. Clearly, trends are neither continuous nor smooth for certain manufacturing industrial subsectors. That is the case of the petrochemical industry that has an abrupt decrease in 1993, and fertilizers whose energy intensity increased and decreased for different years (Fig. 7). Energy intensity of the cement and glass industries had several changes (Fig. 7). 2. Methodology Decomposition analysis is one of the most effective and widely applied tools for determining factors influencing energy consumption and its environmental side effects. The decomposition method consists of separating or decomposing energy and emissions; or intensities, in explanatory variables from aggregate data. These can be conducted utilizing several methodologies, by isolating the importance of the chosen explanatory variables. In this case, explanatory variables for final energy consumption are activity (manufacturing GDP), structure (the share of GDP generated by manufacturing subsubsector) and energy intensity (final energy consumption by GDP of manufacturing subsector); and for CO2 emissions, a carbon index is included; this represents the CO2 emissions divided by the final energy use for each subsector. Economic energy intensity i.e. energy use per unit of constant monetary value of output, is preferred in the analysis of the entire manufacturing sector. This is because it allows a comparison across subsectors in contrast to physical energy intensity i.e. energy use 2 Fuel consumption for cogeneration is accounted for in the fuel consumption reported by the National Energy Balances for each industrial group.

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C. Sheinbaum-Pardo et al. / Energy for Sustainable Development 16 (2012) 57–67

1400

Others Aluminum

1200

Rubber Automotive

1000

Bottled waters Tobacco

800

PJ

Fertilizers Malt and beer

600

Glass Paper and pulp

400

Cement Petrochemical

200

Sugar Basic chemicals

0 1990

Iron and steel

2008

Fig. 4. Final energy use by manufacturing industrial group (grayscale is defined as shown in the stack on the right.).

per unit of physical output, that is better for the analysis of energy efficiency, and international comparisons of a certain manufacturing subsector (Sudhakara Reddy and Kumar, 2011; Schipper and Meyers, 1992, Worrell et al. 1997, Ang and Zhang, 2000). To examine the changes we use the Log Mean Divisia additive index. Ang and Zhang (2000) presented Laspeyres and Divisia indexes multiplicative and additive methods for two decomposition variables (structure and energy intensity) to explain energy intensity. For more than two variables, Diakoulaki et al. (2006), Shyamal and Rabindra (2004) and Lise (2006), described the Log Mean Divisia decomposition methodology. This decomposition method possesses such a property as one that gives perfect decomposition, i.e. no residual term. Based on this methodology and in the knowledge that L(x,y) is the logarithmic mean of two positive numbers L(x,y) = (y− x)/ln(y/x); final energy consumption in the manufacturing industries can be decomposed by: E ¼ A∑i I S

ð2Þ

Where:

ð3Þ

Where:    At ΔEA ¼ ∑i LðEt; EoÞ ln Ao

ð4Þ

   St ΔES ¼ ∑i LðEt; EoÞ ln So

ð5Þ

   EIt ΔEI ¼ ∑i LðEt; EoÞ ln EIo

ð6Þ

And L(Et, Eo) is the logarithmic mean of manufacturing energy consumption in year t (2008) and year 0 (1990).

500 NG Electricity

400

Petcoke Bagasse 300

Coke Fuel oil

200

Diesel LPG Coal

100

Kerosene

20 08

20 06

20 04

20 02

20 00

19 98

19 96

19 94

19 92

0 19 90

Si

Activity: Total manufacturing GDP Energy intensity: Ei/GDPi energy intensity of manufacturing subsector i Structure: GDPi/GDP the share of

ΔE ¼ ΔEA þ ΔES þ ΔEI

PJ

A Ii

Energy changes between year t (2008) and year 0 (1990) can be expressed as the sum of changes of energy due to an activity effect (ΔEA), changes in energy due to a structural effect (ΔES) and changes in energy due to an energy intensity effect (ΔEI):

Fig. 5. Final energy use in Mexican manufacturing industries.

C. Sheinbaum-Pardo et al. / Energy for Sustainable Development 16 (2012) 57–67

61

Table 2 Energy mix by manufacturing industrial subsector (%).

Iron and steel Cement Sugar Basic chemicals Glass Paper and pulp Petrochemical Malt and beer Bottled waters Automotive Rubber Aluminum Fertilizers Tobacco Others

Coal and coke

Oil coke

1990

2008

1990

29.0

31.5 5.0

3.2

LPG 2008

1990

2.5 60.1

0.6

0.0

13.6 0.0

0.2 0.1 0.4

0.8 0.3 0.9

0.9 9.7 18.7 0.1 0.5

3.6 9.1 3.9

7.8

4.9

2008

Kerosene

Diesel

1990

1990

2008

1990

2008

1990

2008

0.4 1.0 7.1 1.4 1.9 0.9

0.5 0.2

13.6 78.3 31.2 33.9 19.8 56.1 6.6 57.7 21.2 0.9 13.7

3.2 18.7 5.8 9.2 7.7 21.8 0.8 36.3 11.9

41.2 10.9

51.2 5.1

49.1 65.7 25.8 93.4 31.4 23.1 28.5 61.7 25.2 69.0 60.9 35.7

52.8 84.0 55.0 97.5 42.9 24.8 21.8 51.7 27.0 82.7 51.2 16.6

2008

0.9

8.2

1.1

Fuel oil

3.5 21.4 4.2 4.7 7.7 1.0

5.2 0.3 2.7 1.7 0.7 30.6 5.8 20.9 0.2 3.7

7.6

6.2

NG

16.2 7.7 11.3

7.1

2.3 0.1

Bagasse 1990

61.5

Electricity 2008

93.8

0.5

1990

2008

15.1 9.8 0.3 15.4 9.3 16.7

11.1 10.9 0.3 18.3 7.8 19.1

6.5 24.6 47.7 19.8 66.6 13.8 31.4 39.3

16.5 23.6 68.5 20.2 71.8 13.6 46.5 61.1

Source: SE (1997, 2009).

CO2 emission changes between year t (2008) and year 0 (1990) can be expressed by: ΔCO2 ¼ ΔA þ ΔCO2 S þ ΔCO2 I þ ΔCI

ð7Þ

Where: CI ¼ CO2 =E

ð8Þ

And CO2 emission changes between year t (2008) and year 0 (1990) can be expressed as the sum of changes of CO2 emissions due to an activity effect (ΔCO2A), changes in CO2 emissions due to a structural effect (ΔCO2S), changes in CO2 emissions due to an energy intensity effect (ΔCO2EI) and, changes in CO2 emissions due to a carbon index effect (ΔCO2CI).    At ΔCO2A ¼ ∑i LðCO2t; CO2oÞ ln Ao

ð9Þ

   St ΔCO2S ¼ ∑i LðCO2t; CO2oÞ ln So

ð10Þ

3. Results Table 4 presents the results for the decomposition analysis of CO2 emissions in Tg of CO2 and Table 5 in percentages. Because of the methodology of the decomposition analysis, activity changes reflect changes in aggregate GDP of the manufacturing industries, and structure the share of each industrial subsector in aggregate manufacturing GDP. For the total sector, results show that CO2 emissions increased by 29% from 1990 to 2008. The activity effect (ΔCO2A) shows that CO2 emissions would have grown by 53% if other effects (structure, energy intensity and fuel mix i.e. carbon index) would have been constant at its 1990 value. In contrast to activity, all other factors have negative values. Structure effect (ΔCO2S) drove down manufacturing CO2 emissions by 9%, which represents less participation of certain intensive industries in the manufacturing GDP. Energy intensity effect (ΔCO2EI) drove down emissions by 10% and carbon index effect (carbon content in energy use; ΔCO2CI) pushed down CO2 emissions by 6%. The analysis of these changes by industrial subsector provides a wider vision. Iron and steel

   EIt ΔCO2EI ¼ ∑i LðCO2t; CO2oÞ ln EIo

ð11Þ

   CIt ΔCO2CI ¼ ∑i LðCO2t; CO2oÞ ln CIo

ð12Þ

Iron and steel is the largest energy consuming industrial subsector. It consumed 273.3 PJ in 2008, 21.8% of the final manufacturing energy use, which emitted 22.9 Tg of CO2. Natural gas is the main source of final energy consumption to this subsector, accounting for

25

Iron and steel Basic chemicals Sugar

20

Petrochemical

TgCO2

Cement Paper and pulp

15

Glass Malt and beer 10

Fertilizers Tobacco Bottled waters

5

Automotive Rubber Aluminum

0 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 19 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20

Fig. 6. CO2 emissions related to energy use in Mexican manufacturing industries.

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Cement

Table 3 Energy intensity MJ/1993 pesos. 1990

2008

1990/2008

29.8 29.6 73.3 69.7 19.0 12.5 9.8 2.9 21.3 0.2 1.1 0.3 2.4 12.0 1.6 5.1

22.0 22.2 40.9 19.6 19.4 7.0 11.3 2.1 21.1 0.2 1.1 0.2 3.1 5.0 2.0 3.8

− 26% − 25% − 44% − 72% 2% − 44% 15% − 27% − 1% 28% 5% − 38% 29% − 58% 32% − 26%

MJ/constant 1993 pesos

Iron and steel Basic chemical Sugar Petrochemical Cement Paper and pulp Glass Malt and beer Fertilizers Tobacco Bottled waters Automotive Rubber Aluminum Others Total

51% of final energy consumption, 10% more than in 1990. Petcoke is the next largest energy source with 31% of consumption, just 2% more than in 1990. The remainder is accounted for mainly by electricity, whose participation was reduced from 15% to 11% during the analyzed period because of changes in the technology process and increase in cogeneration. From 1990 to 2008 final energy use in the iron and steel industries increased by 40% and CO2 emissions by 26%. The decomposition analysis showed that activity and structure effects pushed up emissions by 54% and 18% respectively, and the energy intensity and carbon index effect pushed down emissions by 34% and 13% respectively (Table 5). A recent study showed that the reduction in energy intensity of the Mexican iron and steel industry was due to technological changes that improved energy efficiency, such as the complete substitution of OHF (open hearth furnace) by BF–BOF (Blast Furnace–Basic Oxygen Furnace), a later substitution of BF–BOF by DRI-EAF (Direct Reduced Iron–Electric Arc Furnace) and scrap-EAF processes, the implementation of new technologies for DRI production, an increased use of coke oven and blast furnace gases for on-site electricity generation and a large increase of the share of continuous casting (Sheinbaum et al., 2010). The reduction of carbon index was due to a substitution of coke by NG because of the increased use of BF–BOF. Cement In 2008, cement represented the second largest final energy consuming industrial subsector (increasing from 9.2% in 1990 to 12% in

Aluminum

20

15

10

5

0 90

19

92

19

94

19

96

19

98

19

00

20

02

20

04

20

06

20

08

20

2008). The main energy source utilized was petcoke (60.1% of final energy use), that substituted fuel oil and NG whose share changed from 78.3% to 18.7% and 10.9% to 5.1% from 1990 to 2008 respectively. Between 1990 and 2008, final energy consumption increased by 58%, CO2 emissions by 78%, and cement value added increased by 55%. Decomposition analysis shows that the activity effect pushed up emissions by 65%, and structure drove them down by 6%. In this case however, energy intensity effect and carbon mix effect drove up emissions by 3% and 16% respectively. The important growth in the carbon mix effect is a result of the increased use of coal and petcoke to the detriment of fuel oil and natural gas. This fuel switch was a result of price differences and of course the possibility of rotary kilns to burn different fuels. In the case of energy intensity, Fig. 8 shows how it decreased from 1990 to 1999 (although the decrease was not linear), and increased again from 1999 to 2008. The drop of energy intensity in the first period was related to technology modernization, increased production of blended cements, and the use of alternative fuels such as tires (Sheinbaum and Ozawa, 1998). The increase of the later period might be explained by the increasing use of petcoke that promotes a less efficient consumption of energy. Sugar In 2008, sugar represented the third largest final energy consuming industrial subsector (decreasing from 11.4% in 1990 to 8.3% in 2008). From 1990 to 2008 sugar production reduced its final energy use by 12.5%, CO2 emissions by 85%, while sugar value added increased by

Iron and steel Basic chemical Sugar Petrochemical Fertilizers

Malt and beer Automotive

Tobacco Rubber

Bottled waters Others

4

90 80

MJ/constant 1993 pesos

MJ/constant 1993 pesos

Glass

Fig. 8. Trends in energy intensity for medium energy intensive industries.

Source: INEGI (2010); SE (1997, 2009).

100

Paper and pulp

25

70 60 50 40 30 20

3

2

1

10 0

0 0 99

1

1

2 99

1

4 99

1

6 99

1

8 99

2

0 00

2

2 00

2

4 00

2

6 00

8 00

2

Fig. 7. Trends in energy intensity for energy intensive industries.

90

19

92

19

94

19

96

19

98

19

00

20

02

20

04

20

06

20

08

20

Fig. 9. Trends in energy intensity for less energy intensive industries.

C. Sheinbaum-Pardo et al. / Energy for Sustainable Development 16 (2012) 57–67 Table 4 Results of CO2 emissions decomposition analysis 1990–2008 (Tg of CO2).

Iron and steel Cement Sugar Basic chemicals Glass Paper and pulp Petrochemical Malt and beer Bottled waters Automotive Rubber Aluminum Fertilizers Tobacco Others Total

Actual change

Activity

Structure

Energy intensity

Carbon index

4637.0 6358.0 − 3018.8 − 462.7 1198.1 − 961.2 − 8237.9 687.4 477.4 448.3 164.6 − 405.2 − 798.6 1.0 24319.4 24406.9

9912.9 5357.7 764.6 4118.2 1399.5 2177.1 2173.7 564.1 409.3 458.0 249.6 338.9 285.4 20.1 17218.6 45447.6

3210.7 − 527.6 − 56.1 − 1831.0 − 198.0 130.2 − 4645.6 473.7 140.3 485.8 − 140.4 3.9 − 1002.6 − 28.7 − 3473.0 − 7458.6

− 6178.6 209.1 − 920.5 − 2443.5 413.2 − 2607.7 − 5693.0 − 367.5 39.0 − 452.2 131.0 − 610.9 − 7.1 10.2 9778.4 − 8700.1

− 2308.0 1318.8 − 2806.8 − 306.3 − 416.6 − 660.8 − 73.0 17.1 − 111.2 − 43.2 − 75.7 − 137.0 − 74.3 − 0.6 795.5 − 4882.0

60%. Decomposition analysis shows that activity pushed up emissions by 22%, and structure, energy intensity and carbon index effects pushed down emissions by 2%, 26% and 79% respectively. The large reduction in carbon index effect reveals the decrease in diesel and fuel oil consumption (from 7% to 0.1% and 31% to 5.8% respectively) and the increased use of sugar cane bagasse (from 61% in 1990 to 94% in 2008). The Mexican sugar industry has confronted several problems in the last decades. Difficulties in its administration have led it from nationalization to privatization, then rescued by the government and privatized again. In addition, troubles in confronting the open market due to NAFTA, changes in the international market, and competition with high fructose corn syrup have put the Mexican sugar industry in a difficult position (Aroche, 2004). In spite of the negative circumstances, some modernization in production was achieved during the 1990s (Arguello, 2009). In addition, changes in final production have occurred. In 1994 (no earlier data is available), refined sugar represented 45% of production and standard sugar 55%. In 2008, the proportion changed to 37% refined and 63% standard (INEGI, 2010). Because manufacture of refined sugar needs more energy than standard sugar, the reduction of energy intensity might reflect this change in the structure of production. Basic chemicals The energy use and emissions of this industrial subsector reached 102.4 PJ and 8.3 Tg of CO2 respectively in 2008. In the analyzed period Table 5 Results of CO2 emissions decomposition analysis 1990–2008 (%).

Iron and steel Cement Sugar Basic chemicals Glass Paper and pulp Petrochemical Malt and beer Bottled waters Automotive Rubber Aluminum Fertilizers Tobacco Others Total

Actual change

Activity

Structure

Energy intensity

Carbon index

25% 78% − 85% − 5% 51% − 19% − 84% 80% 76% 61% 38% − 44% − 74% 2% 98% 29%

54% 65% 22% 47% 60% 44% 22% 66% 65% 62% 57% 37% 27% 49% 69% 53%

18% − 6% − 2% − 21% − 8% 3% − 47% 55% 22% 66% − 32% 0% − 93% − 70% − 14% − 9%

− 34% 3% − 26% − 28% 18% − 52% − 58% − 43% 6% − 61% 30% − 66% − 1% 25% 39% − 10%

− 13% 16% − 79% − 4% − 18% − 13% − 1% 2% − 18% − 6% − 17% − 15% − 7% − 1% 3% − 6%

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basic chemicals reduced final energy consumption by 2%, CO2 emissions by 5%, although basic chemicals value added increased by 31%. Results of decomposition analysis show that the activity effect pushed up emissions by 47%; but structure, energy intensity and carbon index effects drove down emissions by 21%, 28% and 4% respectively (Table 5). The diverse set of establishments and industrial processes which represent the production of basic chemicals makes it difficult to evaluate how much of the energy intensity changes were related to improvements in technology. However, an analysis of the structure of product production of this industrial subsector shows important changes that could have affected energy intensity too (Fig. 10). Manufacture of acids, alkalis, salts, and others reduced its participation in basic chemical production from 99.8% to 71.6%; manufacture of dyes and pigments from any source in basic form or as concentrate increased its share from 0.1% to 16.7% and manufacture of liquefied or compressed inorganic industrial or medical gases changed its share from 0.1% to 11.7% (INEGI, 2010). Glass In 2008, the glass industry represented 4.4% (54.7 PJ) of manufacturing final energy consumption, 3.2% of CO2 emissions (3.5 Tg of CO2) and 1.5% of manufacturing GDP. During the analyzed period, final energy consumption increased by 75%, CO2 emissions by 51% and glass GDP also increased by 52%. Decomposition analysis shows that activity and energy intensity pushed up emissions by 60%, and 18% respectively, and structure and carbon index effect drove down emissions by 9% and 16% respectively (Table 5). The decrease in the carbon index effect was a result of the reduction of fuel oil use and the increase of NG use (Table 2). As shown in Fig. 8, energy intensity of the glass industry decreased from 1990 to 2001 and increased from 2001 to 2008. The drop in the first period was associated with different strategies of the glass industry that included plant modernization (Corrales, 2010); however, the reasons of the energy intensity increase in the later years that shadowed the gains of the previous years, are not clear. Paper and pulp In 2008, this industrial subsector represented 4.1% (51.8 PJ) of manufacturing final energy use, 3.7% of CO2 emissions (4.0 Tg of CO2), and 2.2% of manufacturing GDP. From 1990 to 2008, final energy use decreased by 6%, CO2 emissions by 19%, while paper and pulp GDP increased by 67%. Decomposition analysis (Table 5) shows that the activity effect pushed up emissions by 44% and the structure effect by 3%. The decrease in energy use and emissions can be explained by the 52% decrease in energy intensity effect and 13% in carbon index effect. In this case, the drop in energy intensity might be attributed to the increased importation of pulp since NAFTA, as well as the increasing use of recycled paper as a raw material. The production of pulp is more energy intensive than the production of paper. During the analysis period, domestic pulp production decreased from 16.9 million MT in 1990 to 6.2 in 2001 (no more recent data is available). Some authors estimate that the use of recycled paper in Mexico constitutes close to 85% of the paper production raw material, although this is mainly imported too (de la Madrid Cordero, 2010). Petrochemicals During the analyzed period, final energy use of this industrial subsector decreased by 16.2%, CO2 emissions by 8.4%, and petrochemical value added decreased by 42%. Decomposition analysis for this industrial subsector shows negative effects for structure (−47%), energy intensity (− 58%), and carbon index (− 1%; Table 5). The drop in petrochemical production is a reflection of the lack of investment in this sector. In 1995 and 1996 several changes in the regulation of the petrochemical industry were promoted. Before 1996 petrochemical production was a state activity and developed

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100% 90% Manufacture of acids, alkalis, salts, and others

80% 70%

Manufacture of liquefied or compressed inorganic industrial or medical gases

60% 50% 40%

Manufacture of dyes and pigments from any source in basic form or as concentrate

30% 20% 10% 0% 19

90

19

92

19

94

19

96

19

98

20

00

20

02

20

04

20

06

20

08

Fig. 10. Structure of production of basic chemical industries.

exclusively by PEMEX (the state owned petroleum company). The new regulation divided petrochemical production into basic (ethane, propane, butane, pentanes, hexane, heptanes, and raw material for carbon black naphtha, and methane) and secondary products, and reduced state control to the production of basic petrochemicals (DOF, 1996; SE, 2010). The artificial division of products, as well as lack of security for private investment, neither promoted private participation in the industry nor state participation. Petrochemical production decreased by 31.5% during the period. Also changes in the structure of production occurred (Fig. 11). Under this situation it is difficult to evaluate reasons of energy intensity decrease, but probably they also reflect changes in the structure of production. Malt and beer From 1990 to 2008, final energy use of this industrial subsector increased by 78%, CO2 emissions by 80%, and GDP by 143%. Decomposition analysis shows that activity and structure pushed up emissions by 66% and 55% respectively, and energy intensity effect drove down emissions by 43% and carbon index by 2% (Table 5). The reduction in energy intensity is related to modernization of plants. The Mexican malt and beer industry is concentrated in two

large firms that have a very important international presence. Recently both of them established associations with other transnational firms. Bottled waters This industrial subsector represented 1.0% of final energy consumption and also 1% of CO2 emissions of the manufacturing industries. Its GDP grew by 91% from 1990 to 2008, while final energy increased by 101% and CO2 emissions by 78%. Decomposition analysis shows an increase in activity and structure effects by 65% and 22%, an increase in energy intensity effect by 6% and a decrease in carbon index effect by 17%. The reduction in the carbon content of final energy use (carbon index effect) is a consequence of the decrease in fuel oil and the increase in diesel and NG. Fig. 12 shows production by products. Purified water has increased its production since 1998. This situation might have influenced energy intensity. Automotive industry This is the industrial subsector (that includes cars, trucks and buses), with the largest increase in GDP (171%), while energy use

20000 18000

Paraxilene Benzene

16000

Ethylbenzene 14000

Toluene

Metric tons

Vinyl chloride 12000

Acetaldehyde Ethylene oxide

10000

Propylene 8000

Polyethylene Ammonia

6000

Ethylene Others

4000 2000 0 1990

2008

Fig. 11. Production of petrochemicals (grayscale is defined as shown in the stack on the right).

C. Sheinbaum-Pardo et al. / Energy for Sustainable Development 16 (2012) 57–67

Automobiles

Parts 80 70

1993 Billion pesos

increased by 68% and CO2 emissions by 61%. Decomposition analysis shows increase in activity and structure effect by 62% and 66% respectively and a decrease in energy intensity effect by 61% and carbon index effect by 6%. The reduction of the carbon index effect was a result of the increased use of electricity and reduction of its emission factor (Table 2). The reduction in the intensity effect was a result of both technology modernization and changes in production. Fig. 13 shows the automotive industry GDP by subsectors. Automotive parts have increased more rapidly than automobiles. This might have influenced the reduction of energy intensity.

65

Rubber

60 50 40 30 20 10

During the analyzed period this industrial subsector increased its energy use by 59%, and its CO2 emissions by 38%; while its value added increased by only 24%. Decomposition analysis explains that activity effect drove up emissions by 57%, while structure effect drove them down by 32%, while energy intensity effect increased emissions by 30% and carbon index effect pushed them down by 17%. The carbon index drop was due to a decrease in fuel oil consumption and an increased use of NG and diesel (Table 2). The increase in energy intensity is probably related to changes in the product mix. As shown in Fig. 14, the production of tires decreased in 1993 and did not recover, while the production of other products such as shoes, gloves, caps, etc., increased in 1993 and then decreased in 2003. The production of other rubber products for the automotive industry increased from 1993 to 1997 and maintained its production with some ups and downs until 2008.

0 88

19

90

19

92

19

94

19

98

96

19

19

00

20

02

20

04

20

Fig. 13. GDP of automotive industry.

Fertilizers During the analyzed period, this industrial subsector decreased its value added by 70%, its energy use by the same proportion and CO2 emissions by 74%. Decomposition analysis explains that the activity effect increased CO2 emissions by 27%, while structure reduced them by 93%, energy intensity by 1% and carbon index by 7%. In 1994, Fertimex, the stated-owned fertilizer company, was privatized. Some years later most of the industries closed and fertilizers started to be imported (Sacristan, 2006). The shutdown of this industry was related to the crisis in the petrochemical industry and problems related to the price of ammonia.

Aluminum Tobacco From 1990 to 2008, aluminum industries reduced their energy use by 32% and CO2 emissions by 44%, while its value added increased by 63%: This brought a reduction in energy intensity by 58%. Decomposition analysis clarifies the weight of the different effects on CO2 emissions. Activity made emissions increased by 37%, structure did not promote changes (0%), energy intensity and carbon index effect reduced emissions by 66% and 15% (Table 5). The decrease in energy intensity can be explained as a response to changes in production. As shown in Fig. 15, most of the products are not produced in Mexico with the exception of aluminum sheets. Carbon index reduction is a reflection of the reduction in diesel consumption and the increment in NG and LPG use (Table 2).

From 1990 to 2008 the tobacco industry's value added decreased by 19%, while energy use increased by 4% and CO2 emissions by 2%. Decomposition analysis shows an increase in the effect of activity and energy intensity on CO2 emissions by 49% and 25% respectively and a decrease in the structure and carbon index effects by 70% and 1% respectively. The reduction in structure is a reflection of a 15% decrease in cigarette production, the main product of tobacco industries; and the decline in carbon index effect reveals the drop in fuel oil and the increase in electricity use (and the reduction in electricity emission factor).

Other products for automotive industry Tires

Other products Mineral water 16000

Purified water

Carbonated beverages

450 400

14000

Thousands of pieces

350

Thousand liters

12000 10000 8000 6000 4000

300 250 200 150 100

2000

50

0

0 90

19

92

19

94

19

96

19

98

19

00

20

02

20

04

20

Fig. 12. Production of bottled waters.

06

20

08

20

19

90

19

92

19

94

19

96

19

98

20

00

20

02

20

04

Fig. 14. Production of rubber products.

20

06

20

08

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Ingots

Aluminum sheets Tubes

Other profiles 80 70

Thousand tonnes

60 50 40 30 20 10 0 90

19

92

19

94

19

96

19

98

19

00

20

02

20

04

20

06

20

08

20

Fig. 15. Production of aluminum products.

Others All other industrial subsectors are accounted in this category. Decomposition analysis explains that activity, energy intensity and carbon index effects increased CO2 emissions of this subsector by 69%, 39% and 1% respectively, while structure effect pushed down emissions by 9%. The variety of this category presents difficulties in explaining these changes, with the exception of the carbon index increase that reflects a decreased use of natural gas. Conclusions From 1990 to 2008, CO2 emissions related to manufacturing energy use in Mexico increased by 29%. Appling a decomposition analysis based on LMDI we found that activity pushed up emissions by 53% in the whole period, while structure, energy intensity and carbon index pushed down emissions by 9%, 11% and 6% respectively. Analyzing the effects for each industry, we found that the structure effect pushed down emissions for 10 manufacturing industry subsectors (fertilizers, tobacco, petrochemical, rubber, basic chemicals, glass, cement, sugar and others). This means that the share in manufacturing GDP of these industrial subsectors was higher in 1990 than in 2008. The cases where the structure effect was more significant were fertilizers, tobacco, petrochemical and rubber. In these subsectors, the production fell drastically during the analyzed period. With the exception of tobacco in which reduction in production was related to stronger regulation on smokers and increasing prices of cigarettes, the reduction in the other three manufacturing subsectors was the result of wrong privatization processes and increasing imports after NAFTA. The carbon index effect resulted negative for all industrial subsectors with the exception of others and cement. This is a result of reduction in fuel oil both in final energy and in production of electricity. However, the increased use of petcoke in the cement industry offset higher negative changes in the carbon index effect. The energy intensity effect was negative for 10 industrial subsectors (aluminum, automotive, petrochemical, paper and pulp, malt and beer, iron and steel, basic chemicals, sugar and fertilizers). This might suggest increased energy efficiency. However, we found that real intensity change can be also a consequence of changes in the product mix. Energy efficiency in the manufacturing industries can be enhanced in several ways. One is the improvement of energy efficiency in crosscutting technologies such as motors, steam boilers, energy recovery

techniques and cogeneration (Worrell, 2011; Sheinbaum and Masera, 2000). There are several energy policy measures such as energy standards and incentives that have been implemented in Mexico to increase energy efficiency in this area. For example, by 2010 the cogeneration installed capacity in Mexico reached 3385 MW, more than doubled that in year 2000 (CRE, 2011). Also, five energy efficiency standards concerning different kind of motors were established in Mexico from 1994 to 2011 (CONUEE, 2011). There are also different sector-specific technologies and measures for the most intensive industries such as iron and steel, chemicals, cement, pulp and paper, etc. In this case, depending on the industrial process, energy efficiency improvements are different. In Mexico, studies on iron and steel industry show an important progress towards energy efficiency in industrial processes (Sheinbaum et al., 2010). Another possibility to reduce energy consumption and CO2 emissions in the manufacturing sector is the re-design of products so that they require less material throughout the production chain, without reducing quality. This is the case, for example of increase in recycling materials in paper and pulp, plastics, etc. Based on production data, we claimed that probably, the main factor that drove down energy intensity for certain industrial subsectors was none of the opportunity areas described above, but changes in the product mix. In some cases, the changes in the product mix were a response to the open market policy developed by the Mexican government, especially since the entrance of NAFTA in 1994. For example, the reduction in paper and pulp energy intensity is more factual to be explained by the reduction in pulp production because of increment of pulp imports. Also, the reduction of energy intensity in the rubber industry can be explained by the reduction of Mexican automobile tire production and increment in tire imports. In some other cases, the changes in production might be explained by consumer demand, for example reduction in the production of refined sugar and increase in standard sugar. In this study, we found important changes in product mix in the cases of aluminum, petrochemical, paper and pulp, basic chemicals, rubber, bottled waters and sugar. These results show that energy intensity measured as energy use by GDP is a useful indicator, especially to compare performance of different manufacturing industries. However, the reduction in energy intensity not always reflects energy efficiency in terms of technological changes or material changes. It can reflect structural changes in product production. For this reason, it is important to carefully analyze the energy intensity effect in decomposition analysis of the industrial sector. In order to analyze the reasons underlying changes in energy intensity it is important to develop a disaggregate analysis of each industrial subsector. References Akbostanc E, Tunça T, Türüt-Aşıkdoi S. CO2 emissions of Turkish manufacturing industry: a decomposition analysis. Applied Energy 2011. doi:10.1016/j.apenergy.2010.12.076. Ang BW, Zhang FQ. A survey of index decomposition analysis in energy and environmental studies. Energy 2000;25(2000):1149–76. Arguello FJ. Desarrollo tecnológico de la agroindustria azucarera mexicana, impactos sociales y formas de gestión ambiental en Sociedad, Conflicto y Ambiente. Universidad Autónoma del Estado de México, Universidad Autónoma de Tamaulipas, Universidad Autónoma de Nuevo León; 2009http://www.eumed.net/libros/2009a/ 476/Desarrollo%20tecnologico%20de%20la%20agroindustria%20azucarera%20mexicana%20impactos%20sociales%20y%20formas%20de%20gestion%20ambiental.htm. Aroche, D. 2004. Problematica y Crisis de la Industria Azucarera Mexicana en el Marco del Tratado de Libre Comercio de América del Norte. Tesis de Licenciatura en Relaciones Internacionales. Universidad de las Américas. Puebla. Banco de Mexico (Banxico). Tipos de cambio y resultados históricos de las subastas CF373 Serie histórica diaria del tipo de cambio peso-dólar. Período: 19/04/1954 - 03/06/2011, Diaria, Pesos por Dólar, Tipo de Cambio; 2011http://www.banxico.org,mx. Cahill CJ, Gallacho BPO. Monitoring energy efficiency trends in European industry: which top-down method should be used. Energy Policy 2010;38:6910–8.

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