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Reducing carbon footprint in cement material making: Characterizing costs of conserved energy and reduced carbon emissions
Sustainable Cities and Society 9 (2013) 54–61
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Reducing carbon footprint in cement material making: Characterizing costs of conserved energy and reduced carbon emissions Tengfang Xu ∗ , Tjebbe Galama, Jayant Sathaye Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
a r t i c l e
i n f o
Keywords: Energy efficiency Cost of conserved energy (CCE) Cost of carbon reduction (CCR)
a b s t r a c t Adoption of energy efficient technologies is an important strategy to reduce demand for fossil fuels and carbon footprint in cement making. We characterized the costs of energy savings and carbon-emission reduction from applying energy efficiency technologies in cement-making plants in the United States in three historical years. Final energy savings resulting from efficiency measures identified in this study were estimated as 82 PJ, 125 PJ, and 95 PJ in 1994, 2004, and 2010, respectively; equivalent to approximately 20%, 25%, and 31% of the sector’s annual final energy use. The associated carbon-emission reduction was 2.1 million metric tons of carbon (MtC), 3.3 MtC, and 2.5 MtC in 1994, 2004, and 2010, respectively. Using the concepts of cost of conserved energy (CCE) and cost of carbon-emission reduction (CCR), we estimated that cost effective measures contributed to final energy savings in the range of 15–25% of the sector’s annual energy use, and carbon-emission reduction equals to 8–12% of the sector’s annual carbon emissions. This study also points out the importance of future monitoring effort to track efficiency measure implementation for the industrial sector, and the need for an improved market for energy efficiency and reduced carbon footprint. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Cement is widely used in infrastructure including bridges, buildings, and roads. Cement making accounts for significant carbon footprints due to increasing demand induced by infrastructure upgrades and urbanization. According to the United States Geological Survey (USGS), global cement sector produced over 3.3 billion metric tons (Mt) of cement in 2010, with China, India and the U.S. leading the list of leading cement-producing countries (USGS, 2012). Fig. 1 shows the relative shares of annual cement production by country in 2010. We recently performed an assessment on potential energy savings from implementing efficiency measures in Chinese and Indian cement industries and projected that total primary energy savings from implementation of a set of 23 efficiency measures in the Chinese cement industry during 2010–2030 would be 33% of total primary energy supply of Latin America or Middle East (Hasanbeigi, Morrow, Masanet, Sathaye, & Xu, 2013). Total potential electricity savings from implementing a set of 22 efficiency measures in Indian cement sector was projected to be 89 TWh during 2010–2030 (Morrow, Hasanbeigi, Sathaye, & Xu, 2012).
∗ Corresponding author. Tel.: +1 510 486 7810; fax: +1 510 486 6996. E-mail addresses: [email protected], [email protected] (T. Xu). 2210-6707/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.scs.2013.03.002
According to the International Energy Agency (IEA, 2007), over one-third of the world’s energy consumption and 36% of carbon dioxide (CO2 ) emissions are attributable to manufacturing industries worldwide. Energy use in the cement industry is intensive; while a significant amount of carbon dioxide (CO2 ) emissions are associated with energy use as well as direct emissions from cementmaking processes. According to United States Department of State (USDOS, 2006), the aggregated amount of CO2 emitted from the global cement industry reached about 1.5 billion tons, accounting for approximately 5% of global anthropogenic CO2 emissions. Wide adoption of energy efficient technologies is an important strategy to reduce demand for energy, fossil fuels and carbon footprint in industries. Ke, Zheng, Fridley, Price, and Zhou (2012) analyzed potential energy savings and CO2 reduction of China’s cement sector, and concluded that increasing energy efficiency is the most important policy measure for reducing the cement industry’s energy and emission intensity. The U.S. cement industry includes Portland cement plants that produce clinker in either wet or dry kilns and then grind the clinker to make finished cement, and clinker-grinding plants that intergrind clinker obtained elsewhere. Clinker is produced through a controlled high-temperature burn in a kiln of a measured blend of calcareous rocks (usually limestone) and lower quantities of siliceous, aluminous, and ferrous materials. The kiln feed blend (also called raw meal or raw mix) is adjusted depending on the chemical compositions of the raw materials and the types of cement
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curves, we assumed that the energy efficiency measures are mutually exclusive and that energy impact from the interaction between measures if any is negligible. 2.1. Calculation of cost of conserved energy A typical cost curve plots the marginal cost of conserved energy (annualized capital cost) of an efficiency measure against the energy conserved. Eq. (1) shows the parameters typically used in estimating the marginal cost of conserved energy (Meier, 1984; Stoft, 1996). By calculating and ranking CCE value for each energy efficiency measure, a curve can be developed by plotting the ranked CCE values consecutively on the y-axis against cumulative energy savings along the x-axis. Fig. 1. Shares of annual cement production by country in 2010. (Data source: USGS, 2012).
CCE =
desired. Portland cement accounted for the majority of total annual cement products made in the U.S. The objectives of this article are to quantify the magnitudes of energy savings and carbon-emission reduction from applying energy efficiency measures in the U.S. cement-making sector in three historical years, and to characterize the associated costs. Specifically, we will apply the concepts of cost of conserved energy (CCE) and cost of carbon-emission reduction (CCR) to develop cost curves of the efficiency measures based upon compiled information and historical data reported by Sathaye, Xu, and Galitsky (2010), and quantify annual energy savings and carbon-emission reduction from implementing different sets of efficiency measures in three different years. The outcomes will advance understanding of cost effectiveness of energy efficiency measures, and energy and carbon-emission reduction magnitudes in the U.S. cement-making sector, and may also help enhancing bottom-up, empirical descriptions of relevant energy technologies in energy-climate assessment modeling.
q=
2. Methods In order to quantify magnitudes of energy savings and carbonemission reduction from applying energy efficiency measures in the U.S. cement-making sector and to characterize the associated costs, we used the compiled data and information from a broader study (Sathaye et al., 2010), and applied the concept of cost of conserved energy to develop cost curves for the energy efficiency measures for three historical years (i.e., 1994, 2004, and 2010). We also calculated the cost of carbon-emission reduction associated with applying efficiency technologies selected in each year. The methods for different industrial sectors were documented in Xu, Sathaye, and Galitsky (2010) and Xu, Sathaye, and Kramer (2013). Details of data compilation and descriptions of the energy efficiency measures, production, and energy use are reported in Sathaye et al. (2010), along with additional literature reviews (EIA, 1997, 2005, 2009; EPA, 2008; PCA, 1995, 2005, 2011; Schipper, 2006; USGS, 2012; Van Oss, 2012). In this article, we identified and included 31 efficiency measures in 1994; 37 efficiency measures in 2004, and 46 efficiency measures in 2010 for analysis. Appendix A enlists the efficiency measures included in this study. Because additional efficiency measures and their data became available in later year, the total number of the measures increased slightly over the years. The measures selected were applied in the field and energy savings and costs associated with individual measure were quantified based upon review. Because the majority of measures are process related, they were considered independent from each other. For the purpose of estimating overall energy savings and constructing cost
I·q , E d
1 − (1 + d)
(1)
−n ,
(2)
where CCE = cost of conserved energy for an energy efficiency measure, in $/GJ; I = capital cost associated with an efficiency measure ($); q = capital recovery factor (year−1 ); E = annual energy savings for the efficiency measure (GJ/year); d = discount rate; n = lifetime of the efficiency measure (years). Earlier calculation of energy efficiency options typically did not include other non-energy effects of their implementation (Meier, 1984). Worrell, Laitner, Ruth, and Finman (2003) estimated nonenergy costs and benefits of efficiency measures, and found that inclusion of non-energy benefits significantly increased the amount of cost effective energy savings potential because more measures became cost effective when compared with the same unit price of primary energy in the year. Similar to the method presented in Xu et al. (2013), we use Eq. (3) to account for changes in measure investments and other nonenergy costs and benefits associated with changes in operation and maintenance (O&M). For example, changes in labor, material, and other resource requirements, which may lead to positive or negative “M” value. Requirements for additional labor or materials will make “M” more positive, while an increase in productivity or reduction in labor or equipment would make the “M” more negative. A CCEi value no greater than market energy price indicates that adopting the efficiency measure is cost effective, while a higher CCEi value than the energy price indicates that the measure is not cost effective. CCEi =
Ii · q + Mi Ei
(3)
where CCEi = cost of conserved energy for energy efficiency measure i, in $/GJ; Ii = change in capital cost associated with measure i ($); q = capital recovery factor (year−1 ), see Eq. (2); Mi = annual change in monetizable non-energy costs and benefits from O&M changes associated with measure i ($/year); Ei = annual energy savings associated with measure i (GJ/year). 2.2. Calculation of cost of carbon reduction Adopting energy efficient efficiency measures can reduce carbon emissions associated with energy use in the industry. Associated with the energy savings from implementing efficiency measures is the mitigation cost and carbon-emission reduction. Similar to the concept developed for other industrial sectors (Xu et al., 2010, 2013), we consider that the cost of carbon reduction is the same as the cost of applying efficiency measures. Eq. (4) is used to calculate
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Table 1 Annual U.S. cement production, energy use, and carbon emissionsa in 1994, 2004 and 2010.
Wet cement production Production (Mt/year) Final energy consumption (PJ/year) Primary energy consumption (PJ/year) Energy related carbon emissions (MtC/year) Total carbon emissions (MtC/year) Final energy intensity (GJ/ton) Primary energy intensity (GJ/ton) Dry cement production Production (Mt/year) Final energy consumption (PJ/year) Primary energy consumption (PJ/year) Energy related carbon emissions (MtC/year) Total carbon emissions (MtC/year) Final energy intensity (GJ/ton) Primary energy intensity (GJ/ton) U.S. Total cement production Production (Mt/year)b Dry cement share Final energy consumption (PJ/year) Primary energy consumption (PJ/year) Energy related carbon emissions (MtC/year) Total carbon emissions (MtC/year) Final energy intensity (GJ/ton) Primary energy intensity (GJ/ton) Energy related carbon emission intensity (kgC/ton) Total carbon emission intensity (kgC/ton)
1994
2004
2010
21.2 143 164 3.6
20.2 141 158 3.5
6.5 45 51 1.1
6.3 6.8 7.7
5.8 7.0 7.8
1.9 6.8 7.8
53.1 268 325 6.9
78.8 369 456 9.6
56.7 266 326 6.9
13.7 5.0 6.1
19.5 4.7 5.8
14.4 4.7 5.8
74.3 71.5% 411 490 10.5
99.0 79.6% 510 614 13.1
63.2 89.7% 311 377 8.1
20.0 5.5 6.6 141
25.3 5.2 6.2 132
16.4 4.9 6.0 128
269
256
259
a
Fuel carbon coefficient assumptions (in MtC/PJ): residual fuel oil (0.0204); distillate fuel oil (0.0189); LPG (0.0161); natural gas (0.0137); coal (0.0243); coke (0.0295); electricity (0.045); industrial “other” (0.0192). b Sources: PCA (1995, 2005, 2011).
cost of carbon reduction (CCRi ) associated with efficiency measure i. CCRi =
Ii · q + Mi Ci
(4)
where CCRi = cost of carbon reduction associated with energy efficiency measure i, in $/tC (carbon ton); Ii = change in capital cost associated with measure i ($); q = capital recovery factor (year−1 ), see Eq. (2); Mi = annual change in monetizable non-energy costs and benefits from O&M changes associated with measure i ($/year); Ci = annual carbon reduction associated with measure i (tC/year). 3. Results The energy efficiency of a cement plant is affected by factors such as products, technologies, plant size, and quality of raw materials. Table 1 summarizes the annual production, energy use and carbon emissions from the U.S. cement sector in the years selected in this paper (i.e., 1994, 2004, and 2010). For simplicity, we assume a conversion factor of 3.08 from final electricity energy to primary energy. In 1994, cement plants in the U.S. produced a total of 74.3 Mt cement (PCA, 1995). Final and primary energy use for cement making was 411 PJ and 490 PJ, respectively, which was associated with 10.5 MtC carbon emissions. Including emissions generated directly from the cement-making processes, the annual total carbon emissions were 20.0 MtC. In 2004, annual cement production was 99.0 Mt (PCA, 1995). Final and primary energy use for cement making was 510 PJ and 614 PJ, respectively. The energy related carbon emissions were 13.1 MtC, with the annual total carbon emissions of 25.3 MtC. In 2010, annual cement production was
63.2 Mt in the U.S. (PCA, 2011); final and primary energy use for cement making was 311 PJ and 377 PJ, respectively. Energy related carbon emissions were 8.1 MtC, with the annual total carbon emissions of 16.4 MtC. The table also shows a trend of production shifts from wet cement to dry cement that was less energy intensive over the historical years. In combination with technology uptake, the structural shifts resulted in an overall reduction in energy intensity from 1994 to 2010 in the U.S. cement industry. For example, final energy intensity decreased from 5.5 GJ/ton to 4.9 GJ/ton while primary energy intensity decreased from 6.6 GJ/ton to 6.0 GJ/ton for, by approximately 9–11%. Energy related carbon emission intensity also shows a similar reduction trend (a reduction of approximately 9% from 141 kgC/ton-cement to 128 kgC/ton-cement) while the total carbon emission intensity was reduced from 269 kgC/toncement to 259 kgC/ton-cement, albeit to less extent (i.e., a reduction by approximately 5%). 3.1. Cost of conserved energy In this paper, we first calculated CCE of each efficiency measure identified in this study, based upon the cost data, benefit data, and energy savings compiled for each measure. Individual CCE values were ranked from the lowest to the highest. A cost curve line is then developed using CCE values calculated from ranked individual CCE values for each specific year. Within a curve line, the length of each horizontal line section represents the magnitude of energy savings per production for an efficiency measure; while the height of each vertical line section represents the cost per unit of energy saved corresponding to the same efficiency measure. For simplicity, we assumed that nominal capital costs for energy efficiency measures had changed over the years compared to 1994, and that each of the cost data in different years could be adjusted with the GDP Price index using 1994 as the reference year (e.g., a factor of 1.21 for 2004 and 1.39 for 2010 (BEA, 2011)). The following is a sample list of the measures applicable to both dry and wet cement clinker production: kiln shell heat loss reduction; use of waste fuels, modern multi-channel burners; improvement of raw mix burnability, e.g., by mineralizers; and conversion to grate clinker cooler. Improved grinding media; high-pressure roller-press pre-grinding; roller press/horomill system; and high-efficiency classifiers are applicable to finish grinding for all cement production. In addition, more general measures include variable speed drives; high efficiency motors; energy management and process control system, and preventative maintenance; and improvement of compressed air system efficiency. Using the available data sets, capital cost adjustments, inclusion of other non-energy cost and benefits, and 30% discount rate assumed for the energy efficiency measures, we calculated the energy savings due to applicable measures identified for each year, and developed the CCE cost curve for each year (i.e., 1994, 2004, and 2010). Fig. 2 shows the cost curves for 1994, 2004 and 2010. Table 3 further summarizes the results. Final energy savings resulting from applying the energy efficiency measures were 82 PJ in 1994, 125 PJ in 2004, and 95 PJ in 2010, corresponding to final energy savings of 1.10 GJ/ton, 1.26 GJ/ton, and 1.5 GJ/ton, respectively. The annual energy savings from different sets of efficiency measures equaled to 20%, 25% and 31% of total annual final energy use in the U.S. cement sector in 1994, 2004 and 2010, respectively. Besides structural changes (increasing production of dry cement), additional efficiency measures included for 2004 and 2010 also contributed to the increase in relative energy savings exhibited here. We also identified cost effective measures from the pool of efficiency measures by comparing CCE value with weighted average energy price of each year. Then we estimated final energy
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Table 2 Historical nominal energy price, energy mix, weighted average price for the U.S. cement industry in 1994, 2004, 2010 (EIA, 1997, 2005, 2009, 2012). 1994 Price
2004 Energy share
Nominal energy price and energy mix for U.S. cement industry ($/GJ) $12.33 9.2% Electricity $2.36 0.1% Residual fuel oil $4.76 1.1% Distillate fuel oil Gas $2.35 5.1% Coal and other $1.71 72.0% $2.25 6.8% Coke $1.07 5.7% Other (i.e., tires) $2.76 100% Final energy (weighted average)
savings resulting from each set of cost effective efficiency measures. Table 2 shows historical fuel energy price, energy mix, and estimated weighted average energy price in each year. As a result, Table 3 shows that for each unit ton of cement making, cost effective energy savings was 62 PJ, 92 PJ, 76 PJ in 1994, 2004 and 2010, respectively; corresponding to intensity of 0.83 GJ/ton, 0.93 GJ/ton, and 1.21 GJ/ton, respectively. The number of cost effective measures increased from 15 in 1994 to 21 in 2010. Overall, cost effective energy savings increased from 15% to 25% of total annual final energy over the years. 3.2. Cost of carbon-emission reduction Adopting energy efficient measures can reduce carbon emissions associated with energy use in the industry. Similar to the concept developed for other sectors (Xu et al., 2013), we consider that the cost of carbon-emission reduction is the same as the cost of applying efficiency measures in the cement-making sector. Based upon Eq. (4), we calculated the cost of carbon-emission reduction associated with conserved energy from each applicable efficiency measure for each of the selected years in this study. Fig. 3 exhibits the cost of carbon-emission reduction (in U.S. dollar per metric ton of carbon) versus the carbon-emission reduction (metric ton of carbon) for the U.S. cement industry in 2010. Fig. 3 shows that CCR values for some measures were above $1000/tC while their carbon-reduction potential was rather limited. It was far from being cost effective or practical to apply such energy efficiency measures for the purpose of reducing carbon emissions. On the other hand, there were a number of measures with much lower CCR values. Fig. 4 shows the same cost curves as in Fig. 3, with an
2010
Price
Energy share
Price
Energy share
$13.74 $3.65 $5.51 $6.19 $2.04 $2.69 $1.07 $3.33
11% 0.2% 1.5% 5.1% 58% 2.0% 23% 100%
$17.00 $8.46 $10.34 $5.20 $4.03 $5.31 $2.53 $5.57
11% 0.1% 1.3% 5.2% 71.2% 6.9% 4.6% 100%
Table 3 Annual and cost effective energy savings in the U.S. cement making in 1994, 2004, and 2010. Year
Annual final energy savings Wet cement final energy savings (PJ/year) Dry cement final energy savings (PJ/year) Total annual final energy savings (PJ/year) Total final energy savings per production unit (GJ/ton) Total savings as a percentage of total final energy use (%) Total number of measures identified Cost effective final energy savings Wet cement making final energy savings (PJ/year) Dry cement making final energy savings (PJ/year) Total annual cost effective final energy savings (PJ/year) Total cost effective final energy savings per production unit (GJ/ton) Cost effective savings as a percentage of total annual final energy use (%) Weighted average final energy price ($/GJ) Total number of cost effective measures (GDP Price index included)
1994
2004
2010
24 58 82 1.10
27 99 125 1.26
8 87 95 1.50
20%
25%
31%
31
37
46
18
17
6
44
75
71
62
92
76
0.83
0.93
1.21
15%
18%
25%
2.76 15
3.33 15
5.57 21
Note: Weighted average price of final energy is estimated based on industrial energy uses and costs (EIA, 1997, 2005, 2009, 2012).
Fig. 3. Cost of carbon-emission reduction in 2010 (discount rate 30%). Fig. 2. Cost curves of final energy savings for the U.S. cement industry for 1994, 2004, and 2010.
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Fig. 4. Primary energy cost curves for inclusion and exclusion of other non-energy benefits in 2010.
enlarged scale on the Y-axis to illustrate CCR variations of different efficiency measures with lower CCR values. Total carbon-emission reduction is defined as the carbonemission reduction resulted from total annual energy savings due to implementing the efficiency measures as identified and quantified in this study. Table 4 summarizes the aggregated numbers for carbon-emission reduction in each year as they were associated with the energy efficiency measures identified in this study. We estimated that the total carbon-emission reduction resulting from all applicable energy efficiency measures was 2.1 MtC in 1994, and 3.3 MtC in 2004, and 2.5 MtC in 2010, approximating 11–15% of total carbon emission in the sector. In addition, Table 4 also presents the total carbon-emission reduction corresponding to the cost effective efficiency measures that were identified based on CCE values. This set of efficiency measures is the same set of cost effective measures based upon comparisons of CCE value with average weighted energy price for each year. Applying this set of cost effective measures would reduce carbon emissions by 1.6 MtC in 1994, 2.4 MtC in 2004, and 2.0 MtC in 2010, corresponded to 8%, 10%, and 12% of total annual carbon emissions in the sector, respectively. This is an important finding in that implementing existing cost effective efficiency measures can result in significant reduction in carbon emissions in each year. 4. Discussion 4.1. Effects of including non-energy benefits on cost curves Cost curves in Fig. 2 are plotted including other non-energy benefits. Different curves of conserved energy (in U.S. dollar per GJ Table 4 Total carbon-emission reduction in the U.S. cement-making in 1994, 2004, and 2010. 1994
2004
2010
Total carbon-emission reduction from all applicable efficiency measures 2.1 3.3 2.5 Total carbon-emission reduction from all measures (MtC/year) Total carbon emission in the sector (MtC/year) 20 25.3 16.4 11% 13% 15% Total carbon-emission reduction as a percentage of total carbon emissions in the sector Carbon-reduction from cost effective measures Total cost effective carbon-emission reduction based on CCE (MtC/year) Cost effective carbon-emission reduction as a percentage of total carbon emissions from the sector
1.6
2.4
2.0
8%
10%
12%
energy saved) of energy efficiency measures can be plotted against the specific energy savings (GJ per ton of cement) of two scenarios: with and without inclusions of other non-energy benefits for the U.S. cement industry in 2010 as shown. Fig. 4 shows differences in the values for costs of conserved energy (in primary energy terms), in 2010 U.S. dollar per primary energy saved (GJ), between curves with non-energy benefits included and excluded for the cement industry. Including other non-energy benefits significantly lowered the CCE values. For example, with the same total primary energy savings of 1.2 GJ/ton cement in 2010, including non-energy benefits in the cost curves for the cement industry can significantly decrease the total cost of conserved primary energy for measures from $5.0/GJ to $1.0/GJ. Corresponding to average primary energy price of $4.36/GJ for the sector in 2010, the cumulative primary energy savings would be 1.0 GJ/t when non-energy benefits are not included and would increase to 1.2 GJ/t when non-energy benefits are included in CCE calculation. In parallel, Fig. 5 shows the final energy cost curves for year 2010, which exhibits a similar difference between including and excluding other non-energy benefits in the cost curve. For example, corresponding to average final energy price of $5.57/GJ for the sector in 2010, the cumulative final energy savings would be 1.10 GJ/t when non-energy benefits are not included and would increase to 1.21 GJ/t when non-energy benefits are included in CCE calculation. In summary, inclusion of other non-energy benefits of implementing efficiency measures can reduce CCE values of efficiency measures, and may achieve a higher level of conserved energy corresponding to specific energy price.
4.2. Treatment of energy prices The energy efficiency measures in the cement industry processes are operated by using a wide variety of energy or fuel types. For example, energy reduction in the blast furnace could reduce the need for coal, while an efficiency measure in an EAF could reduce only electricity. The savings from reduced use of coal are in general less cost effective compared to electricity savings, mainly due to much lower coal price (e.g., coal price in 2010 was $4.75/GJ, much lower than electricity price of $13.80/GJ). When using the concept of CCE to identify cost effective measures applicable to the cement sector, we actually compared CCE value with the weighted average fuel price for the cement industry in the previous section, even though the fuel or energy type applicable to an individual measure is homogeneous (e.g., for 2010 a weighted average fuel price was calculated at $7.38/GJ while actual fuel price could be much lower or higher). The potential drawback of using CCE and weighted energy price to characterize cost effectiveness of an individual measure is that if the measure operates only with electricity, its cost effectiveness would be biased (unfavorably) when using weighted average price to compare, because the weighted average price is lower than electricity price. In another word, a measure that was in fact cost effective (if the corresponding energy price for the specific fuel type was used) could be otherwise identified as not so cost effective compared to weighted average energy price, if at all. On the other hand, for a measure that uses only coal of which unit price is generally lower than other fuels, the degree of its cost effectiveness could be overestimated when its CCE is compared with the weighted average energy price that is higher than coal price. In addition, while conventional CCE is a very good index when energy supply (thus price) is homogeneous, a cost curve based upon CCE values (e.g., Fig. 5) may lack in readiness for evaluating cost effectiveness of individual measures for different years. Using the conventional CCE, one has to compare the CCE value with weighted average of energy price in a particular year. Because fuel prices and
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Table 5 Comparison of cost effective savings using the concepts of conventional CCE and modified CCE (30% discount rate, cost inflation considered). Year 1994
2004
2010
Cost effective final energy savings of energy efficiency measures using CCE method Wet cement making final energy savings (PJ/year) 18 17 6 Dry cement making final energy savings (PJ/year) 44 75 71 Total annual cost effective final energy savings 62 92 76 (PJ/year) 0.83 0.93 1.21 Total cost effective final energy savings per production unit (GJ/ton) 15% Cost effective savings as a percentage of total 18% 25% annual final energy use (%) 15 Total number of cost effective measures (GDP Price 15 21 index included)
Fig. 5. Final energy cost curves for inclusion and exclusion of other non-energy benefits in 2010.
energy supplies changed from year to year, the weighted average of energy price would be a moving target across years. In order to better understand the cost effectiveness from different treatments of energy price, we calculated the modified CCE (MCCE) values, using the following equation to further investigate the effects of specific energy price corresponding to various fuel types. MCCEi =
Ii · q + Mi − Ei · Pi Ei
(5)
where MCCEi = cost of conserved energy for energy efficiency measure i, in $/GJ; Ii = change in capital cost associated with measure i ($); q = capital recovery factor (year−1 ), see Eq. (2); Mi = annual change in monetizable non-energy costs and benefits from O&M changes associated with measure i ($/year); Pi = market price of energy use associated with measure i ($/GJ); Ei = annual energy savings associated with measure i (GJ/year). Essentially, a MCCEi value no greater than zero indicates that adopting the efficiency measure is cost effective, while a positive MCCEi value indicates that the measure is not cost effective based upon the available data. MCCE takes into account energy prices that vary by years and by fuels applicable to a specific measure; therefore, some changes in ranking orders of MCCE values for a same measure should be expected from year to year. Using MCCE method provides an alternative to readily evaluate cost effectiveness of individual measures. Table 5 shows the comparison of cost effective measures and savings based upon conventional CCE and MCCE calculations. As a result from using both MCCE and CEE methods, the table shows that cost effective savings per unit of product were very close for each year, even though number of cost effective measures increased slightly when the MCCE method is used.
Cost effective final energy savings of energy efficiency measures using MCCE method 18 18 6 Wet cement final energy savings (PJ/year) 45 77 71 Dry cement final energy savings (PJ/year) 63 94 77 Total annual cost effective final energy savings (PJ/year) 0.85 0.95 1.21 Total cost effective final energy savings per production unit (GJ/ton) 15% Cost effective savings as a percentage of total 18% 25% annual final energy use (%) 18 20 24 Total number of cost effective measures (GDP Price index included) Note: Numbers in the table are rounded.
on the magnitudes of costs of conserved energy and savings for individual energy efficiency measures. For each of the selected years, we applied three discount rates, i.e., 10%, 20%, and 30%, respectively, to calculate CCE values and as they correspond to the efficiency measures. Fig. 6 shows the cost curves with various discount rates (10%, 20%, and 30%) in 2010. At lower discount rates (e.g., 10%), CCE values of several measures (e.g., roller press, improved compressed air system, high efficiency motor) became negative. CCE curve for the same set of efficiency measures moved upward with the increase of discount rates from 10% to 30%. When compared to weighted average energy price (i.e., $5.57/GJ) in the sector, more measures can be identified as cost effective when the discount rate is lower. Table 6 further presents the total final energy savings from applying the efficiency measures identified, and those from applying cost effective efficiency measures using three discount rates for each year. As can be seen in Table 6, the influence of the change in discount rates from 10% to 20% becomes more evident on the amount of energy savings associated with cost effective measures,
4.3. Effects of discount rate on cost curves and uncertainties In the CCE analyses presented earlier in this report, we assumed that a real discount rate of 30% is applied, partly reflecting the industry’s capital constraints and preference for short payback periods and high internal rates of return. The assumption of higher discount rates (e.g., 30%) can also indirectly account for program costs and various barriers against the adoption of cost effective efficiency measures. It is also clear that such an assumption would mathematically lead to a prediction with higher (e.g., positive) annualized costs of the efficiency measures. In this section, we performed sensitivity analyses to examine the effects of discount rates
Fig. 6. Cost curves of final energy savings with discounts rates 10%, 20%, and 30% in 2010.
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Table 6 Final energy reductions from cost effective efficiency measures at different discount rates. Total final energy savings 1994
2004
2010
Final energy reduction by cost effective measures at different discount measures All measures (PJ/year) 82 125 95 77 120 85 Cost effective measures (discount rate 10%) (PJ/year) 66 107 77 Cost effective measures (discount rate 20%) (PJ/year) 62 92 76 Cost effective measures (discount rate 30%) (PJ/year)
whereas the influence of the change in discount rates between 20% and 30% becomes smaller on cost effective energy savings. As an example in 2010, final energy savings of 85 PJ (accounting for approximately 89% of the total savings 95 PJ) were considered cost effective when a discount rate of 10% is used; whereas only 80–81% of the total energy savings (i.e., 76–77 PJ out of 95 PJ) was considered cost effective when a discount rate of 30% or 20% is used. In summary, while variations in discount rates do not affect the magnitudes of energy savings from efficiency measures in any given year, estimated cost effective energy savings increase modestly with the decrease of discount rates from 30% to 20%, and such an increase of energy savings becomes more significantly with further reduction of discount rates from 20% to 10% in the U.S. cement sector. While a high discount rate (i.e., 30%) partly reflects the industry’s capital constraints and preference for short payback periods, and can partly accounts for program costs and various barriers against the adoption of cost-effective energy efficient technologies, the magnitudes of energy savings due to cost effective measures can increase significantly if a lower discount rate is practically used. In this study, energy savings for each measure were determined by comparing the difference in energy use after the measure was implemented versus when it was absent. For each measure, the share of U.S. production to which the individual measure was applied was estimated based upon literature information and expert input (Sathaye et al., 2010). Because there was no sufficient information from the field to update the penetration rates reliably, we assumed penetration rate to be constant between 2004 and 2010, as well as 30% discount rate as a conservative way to estimate overall energy savings. Additional assumptions about conversion and emission factors may also affect the outcomes but the uncertainty bound smaller than the impacts from discount rate and penetration. Therefore it is very important that future effort should pursue monitoring the implementation of efficiency measures and programs in place to promote such effort. Lastly, our analysis indicates that policies that promote the implementation of efficiency measures and strategies in the sector may help to improve cost effectiveness of more measures and lead to an improved market.
5. Conclusions In this paper, we have developed cost curves for efficiency measures applied in the U.S. cement-making sector for the years 1994, 2004, and 2010; and characterized costs of conserved energy and associated carbon-emission reduction in the sector. The shapes of cost curves are influenced by the efficiency measures, baseline year, discount rate, production, industry structure (e.g., wet versus dry cement making), and whether or not other non-energy benefits are included. Inclusion of other non-energy benefits and lowered discount rates reduced the CCE values, making the efficiency measures more cost effective. We also estimated magnitudes of annual
energy savings and carbon-emission reduction associated with the efficiency measures in this study. • The final energy savings resulting from applicable energy efficiency measures were estimated as 82 PJ, 125 PJ, and 95 PJ in 1994, 2004, and 2010, respectively; equivalent to approximately 20%, 25% and 31% of the sector’s annual final energy use in those years. Besides structural changes (i.e., increasing production shares of dry cement observed over the period from 1994 to 2010), additional efficiency measures included for 2004 and 2010 also contributed to the increase in relative energy savings. • Final energy savings resulting from cost effective efficiency measures was estimated as 62 PJ, 92 PJ, and 76 PJ in 1994, 2004, and 2010, respectively, equivalent to a range of 15–25% of the total annual final energy use in the U.S. cement-making sector. • Carbon emission reduction resulting from efficiency measures was estimated as 2.1 MtC, 3.3 MtC, and 2.5 MtC in 1994, 2004, and 2010, respectively; corresponding to approximately 11%, 13%, and 15% of sector’s annual carbon emissions. • Applying cost effective energy measures would reduce carbon emissions by 1.6 MtC, 2.4 MtC, and 2.0 MtC in 1994, 2004, and 2010, respectively; corresponding to carbon-emission reduction by 8–12% of the sector’s annual carbon emissions. Similar to the findings reported for pulp and paper sector, implementing existing cost effective measures can result in significant energy savings and carbon reduction in the cement-making sector. This study further confirms that policies and strategies should be promoted to reduce the costs of efficiency measures (e.g., help reducing actual discount rates) and to improve cost effectiveness of more efficiency measures. This study also points out the importance of monitoring effort in the future to track the progress of efficiency measure implementation for the industrial sector. While there is a need for an improved market for energy efficiency and reduced carbon footprint, energy programs and promotion effort may in turn lead to the efficiency market improvement in industries. Acknowledgment This study is sponsored by Climate Economics Branch, Climate Change Division of U.S. Environmental Protection Agency, under Contract No. DE-AC02-05CH11231with the U.S. Department of Energy. Appendix A. List of efficiency measures identified in each year List of efficiency measures Raw materials preparation (wet cement) Mechanical transport systems (w) Slurry blending and homogenizing (w) Wash mills with closed circuit classifier (w) Raw materials preparation (dry cement) Mechanical transport systems (d) Raw meal blending systems (d) Use of high efficiency roller mills (d) Raw meal process control (d) High efficiency classifiers (d)
1994
2004
2010
X
X X X
X X X
X X X
X X X X X
X X X X X
X X
X X
X X X X
X X X X X
X
Fuel preparation (wet and dry) Roller mills (d) Roller mills (w) Clinker production (wet cement) Process control and management (w) Kiln combustion system improvements (w) Kiln shell heat loss reduction (w) Use of waste fuels (w) Modern multi channel burners (w)
X X X
T. Xu et al. / Sustainable Cities and Society 9 (2013) 54–61 Improve raw mix burnability, e.g. by mineralizers (w) Conversion to grate clinker cooler (w) Oxygen enrichment technology (w) Conversion to semi-dry process (w) Conversion to semi-wet kilns (w) Optimize heat recovery of clinker cooler (grate) (w) Conversion to dry multi-stage pre-heater, pre-calciner kilns (w) Clinker production (dry cement) Kiln shell heat loss reduction (d) Use of waste fuels (d) Modern multi channel burners (d) Improve raw mix burnability e.g. by mineralizers (d) Conversion to grate clinker cooler (d) Low pressure drop cyclones for suspension pre-heaters (d) Heat recovery for cogeneration (d) Low grade heat recovery with ORC (d) Oxygen enrichment technology (d) Conversion from dry to multi-stage pre-heater kilns (d) Conversion from multi-stage pre-heater to pre-calciner kiln (d) conversion from dry to pre-heater, pre-calciner kilns (d) Optimize heat recovery of clinker cooler (grate) (d) Finish grinding (all cement) Improved grinding media High pressure roller press-pre grinding Roller press/horomill system High efficiency classifiers General measures Variable speed drives High efficiency motors Energy management and process control system Preventative maintenance Replace smaller plants by BAT larger plants Improve compressed air system efficiency Product change Blended cements Total number
X X
X
X X X
X X X
X X X X X
X
X
X
X X
X X
X X X X
X X
X X
X X
X
X
X
X
X X X X
X
X
X
X
X
X
X
X
X
X X X X
X X X X
X X X X
X X X
X X X
X X X
X
X
X X X
X 31
X 37
X 46
References Bureau of Economic Analysis (BEA). (2011). National income and product accountsNIPAs, 2011. Section 1 all tables. GDP and Other Major NIPA Aggregates. U.S. Department of Commerce. http://www.bea.gov/ Energy Information Administration (EIA). (1997). 1994 Manufacturing Consumption of Energy 1994. Washington, DC: The United States Department of Energy.
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Energy Information Administration (EIA). (1997). 2002 Manufacturing Energy Consumption Surveyon manufacturing and industrial energy uses and costs. Washington, DC: The United States Department of Energy. http://www. eia.doe.gov/emeu/mecs/mecs2002/data02/shelltables.html Energy Information Administration (EIA). (1997). 2006 Manufacturing Energy Consumption Survey on manufacturing and industrial energy uses and costs. Washington, DC: The United States Department of Energy. Energy Information Administration (EIA). (2012). Prices. Washington, DC: The United States Department of Energy. (accessed May 2012). http://www.eia.gov/ tools/a-z/index.cfm?id=p Hasanbeigi, A., Morrow, W., Masanet, E., Sathaye, J., & Xu, T. (2013). Energy efficiency improvement and CO2 emission reduction opportunities in the cement industry in China. Energy Policy, http://dx.doi.org/10.1016/j.enpol.2013.01.053 International Energy Agency (IEA). (2007). Tracking industrial energy efficiency and CO2 emissions. http://www.iea.org/Textbase/npsum/tracking2007SUM.pdf Ke, J., Zheng, N., Fridley, D., Price, L., & Zhou, N. (June 2012). Potential energy savings and CO2 emissions reduction of China’s cement industry. Energy Policy, 45, 739–751. Meier, A. K. (1984). The cost of conserved energy as an investment statistic. In Sixth annual industrial energy technology conference, Vol. 2 Houston, TX, USA, April 1984, Morrow, W., Hasanbeigi, A., Sathaye, J., & Xu, T. (2012). Assessment of energy efficiency improvement and CO2 emission reduction potentials in India’s cement industry. Lawrence Berkeley National Laboratory Final Report to Climate Economics Branch Climate Change Division. Berkeley, CA: U.S. Environmental Protection Agency. Portland Cement Association (PCA). (1995). U.S. and Canadian portland cement industry plant information summary. Skokie, IL: Portland Cement Association. Portland Cement Association (PCA). (1995). U.S. and Canadian portland cement industry plant information summary. Skokie, IL: Portland Cement Association. Portland Cement Association (PCA). (2011). U.S. and Canadian portland cement industry plant information summary. Skokie, IL: Portland Cement Association. Sathaye, J., Xu, T., & Galitsky, C. (2010). Bottom-up representation of industrial energy efficiency technologies in integrated assessment models for the cement sector. Berkeley, CA: Lawrence Berkeley National Laboratory, LBNL-4395E. Schipper, M. (2006). 2002 Energy-related carbon dioxide emissions in U.S. manufacturing. Energy Information Administration (EIA) Report #: DOE/EIA-0573(2005). http://www.eia.doe.gov/oiaf/1605/ggrpt/pdf/industry mecs.pdf Stoft, S. (1996). The economics of conserved-energy “supply” curves POWER. Berkeley: University of California. PWP-028 The United States Department of State (USDOS). (2006). Asia-Pacific partnership on clean development and climate: Cement task force summary of action plan and projects—summary of cement task force action plan. The United States Environmental Protection Agency (EPA). (2008). Inventory of U.S. greenhouse gas emissions and sinks: 1990–2006. 1200 Pennsylvania Ave, NW, Washington, DC. The United States Geological Survey (USGS). (2012). Minerals yearbook (1994–2010): Cement statistics and information, Washington, D.C. http://minerals.er.usgs.gov/ minerals/cement Van Oss, H. G. (2012). U.S. Geological survey (USGS) mineral commodity summaries: Cement. http://minerals.usgs.gov/minerals/pubs/commodity/cement/ mcs-2012-cemen.pdf Worrell, E., Laitner, J. A., Ruth, M., & Finman, H. (2003). Productivity benefits of industrial energy efficiency measures. Energy, 28, 1081–1098. Xu, T., Sathaye, J., Galitsky, C. (2010). Development of bottom-up representation of industrial energy efficiency technologies in integrated assessment models for the iron and steel sector. Climate Economics Branch, Climate Change Division, U.S. Environmental Protection Agency. Berkeley, CA: Lawrence Berkeley National Laboratory, LBNL-4314E. Xu, T., Sathaye, J., Kramer, K. (2013). Sustainability options in pulp and paper making: Costs of conserved energy and carbon reduction in the U.S. sustainable cities and society, http://dx.doi.org/10.1016/j.scs.2013.01.006
Contents lists available at SciVerse ScienceDirect
Sustainable Cities and Society journal homepage: www.elsevier.com/locate/scs
Reducing carbon footprint in cement material making: Characterizing costs of conserved energy and reduced carbon emissions Tengfang Xu ∗ , Tjebbe Galama, Jayant Sathaye Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
a r t i c l e
i n f o
Keywords: Energy efficiency Cost of conserved energy (CCE) Cost of carbon reduction (CCR)
a b s t r a c t Adoption of energy efficient technologies is an important strategy to reduce demand for fossil fuels and carbon footprint in cement making. We characterized the costs of energy savings and carbon-emission reduction from applying energy efficiency technologies in cement-making plants in the United States in three historical years. Final energy savings resulting from efficiency measures identified in this study were estimated as 82 PJ, 125 PJ, and 95 PJ in 1994, 2004, and 2010, respectively; equivalent to approximately 20%, 25%, and 31% of the sector’s annual final energy use. The associated carbon-emission reduction was 2.1 million metric tons of carbon (MtC), 3.3 MtC, and 2.5 MtC in 1994, 2004, and 2010, respectively. Using the concepts of cost of conserved energy (CCE) and cost of carbon-emission reduction (CCR), we estimated that cost effective measures contributed to final energy savings in the range of 15–25% of the sector’s annual energy use, and carbon-emission reduction equals to 8–12% of the sector’s annual carbon emissions. This study also points out the importance of future monitoring effort to track efficiency measure implementation for the industrial sector, and the need for an improved market for energy efficiency and reduced carbon footprint. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Cement is widely used in infrastructure including bridges, buildings, and roads. Cement making accounts for significant carbon footprints due to increasing demand induced by infrastructure upgrades and urbanization. According to the United States Geological Survey (USGS), global cement sector produced over 3.3 billion metric tons (Mt) of cement in 2010, with China, India and the U.S. leading the list of leading cement-producing countries (USGS, 2012). Fig. 1 shows the relative shares of annual cement production by country in 2010. We recently performed an assessment on potential energy savings from implementing efficiency measures in Chinese and Indian cement industries and projected that total primary energy savings from implementation of a set of 23 efficiency measures in the Chinese cement industry during 2010–2030 would be 33% of total primary energy supply of Latin America or Middle East (Hasanbeigi, Morrow, Masanet, Sathaye, & Xu, 2013). Total potential electricity savings from implementing a set of 22 efficiency measures in Indian cement sector was projected to be 89 TWh during 2010–2030 (Morrow, Hasanbeigi, Sathaye, & Xu, 2012).
∗ Corresponding author. Tel.: +1 510 486 7810; fax: +1 510 486 6996. E-mail addresses: [email protected], [email protected] (T. Xu). 2210-6707/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.scs.2013.03.002
According to the International Energy Agency (IEA, 2007), over one-third of the world’s energy consumption and 36% of carbon dioxide (CO2 ) emissions are attributable to manufacturing industries worldwide. Energy use in the cement industry is intensive; while a significant amount of carbon dioxide (CO2 ) emissions are associated with energy use as well as direct emissions from cementmaking processes. According to United States Department of State (USDOS, 2006), the aggregated amount of CO2 emitted from the global cement industry reached about 1.5 billion tons, accounting for approximately 5% of global anthropogenic CO2 emissions. Wide adoption of energy efficient technologies is an important strategy to reduce demand for energy, fossil fuels and carbon footprint in industries. Ke, Zheng, Fridley, Price, and Zhou (2012) analyzed potential energy savings and CO2 reduction of China’s cement sector, and concluded that increasing energy efficiency is the most important policy measure for reducing the cement industry’s energy and emission intensity. The U.S. cement industry includes Portland cement plants that produce clinker in either wet or dry kilns and then grind the clinker to make finished cement, and clinker-grinding plants that intergrind clinker obtained elsewhere. Clinker is produced through a controlled high-temperature burn in a kiln of a measured blend of calcareous rocks (usually limestone) and lower quantities of siliceous, aluminous, and ferrous materials. The kiln feed blend (also called raw meal or raw mix) is adjusted depending on the chemical compositions of the raw materials and the types of cement
T. Xu et al. / Sustainable Cities and Society 9 (2013) 54–61
55
curves, we assumed that the energy efficiency measures are mutually exclusive and that energy impact from the interaction between measures if any is negligible. 2.1. Calculation of cost of conserved energy A typical cost curve plots the marginal cost of conserved energy (annualized capital cost) of an efficiency measure against the energy conserved. Eq. (1) shows the parameters typically used in estimating the marginal cost of conserved energy (Meier, 1984; Stoft, 1996). By calculating and ranking CCE value for each energy efficiency measure, a curve can be developed by plotting the ranked CCE values consecutively on the y-axis against cumulative energy savings along the x-axis. Fig. 1. Shares of annual cement production by country in 2010. (Data source: USGS, 2012).
CCE =
desired. Portland cement accounted for the majority of total annual cement products made in the U.S. The objectives of this article are to quantify the magnitudes of energy savings and carbon-emission reduction from applying energy efficiency measures in the U.S. cement-making sector in three historical years, and to characterize the associated costs. Specifically, we will apply the concepts of cost of conserved energy (CCE) and cost of carbon-emission reduction (CCR) to develop cost curves of the efficiency measures based upon compiled information and historical data reported by Sathaye, Xu, and Galitsky (2010), and quantify annual energy savings and carbon-emission reduction from implementing different sets of efficiency measures in three different years. The outcomes will advance understanding of cost effectiveness of energy efficiency measures, and energy and carbon-emission reduction magnitudes in the U.S. cement-making sector, and may also help enhancing bottom-up, empirical descriptions of relevant energy technologies in energy-climate assessment modeling.
q=
2. Methods In order to quantify magnitudes of energy savings and carbonemission reduction from applying energy efficiency measures in the U.S. cement-making sector and to characterize the associated costs, we used the compiled data and information from a broader study (Sathaye et al., 2010), and applied the concept of cost of conserved energy to develop cost curves for the energy efficiency measures for three historical years (i.e., 1994, 2004, and 2010). We also calculated the cost of carbon-emission reduction associated with applying efficiency technologies selected in each year. The methods for different industrial sectors were documented in Xu, Sathaye, and Galitsky (2010) and Xu, Sathaye, and Kramer (2013). Details of data compilation and descriptions of the energy efficiency measures, production, and energy use are reported in Sathaye et al. (2010), along with additional literature reviews (EIA, 1997, 2005, 2009; EPA, 2008; PCA, 1995, 2005, 2011; Schipper, 2006; USGS, 2012; Van Oss, 2012). In this article, we identified and included 31 efficiency measures in 1994; 37 efficiency measures in 2004, and 46 efficiency measures in 2010 for analysis. Appendix A enlists the efficiency measures included in this study. Because additional efficiency measures and their data became available in later year, the total number of the measures increased slightly over the years. The measures selected were applied in the field and energy savings and costs associated with individual measure were quantified based upon review. Because the majority of measures are process related, they were considered independent from each other. For the purpose of estimating overall energy savings and constructing cost
I·q , E d
1 − (1 + d)
(1)
−n ,
(2)
where CCE = cost of conserved energy for an energy efficiency measure, in $/GJ; I = capital cost associated with an efficiency measure ($); q = capital recovery factor (year−1 ); E = annual energy savings for the efficiency measure (GJ/year); d = discount rate; n = lifetime of the efficiency measure (years). Earlier calculation of energy efficiency options typically did not include other non-energy effects of their implementation (Meier, 1984). Worrell, Laitner, Ruth, and Finman (2003) estimated nonenergy costs and benefits of efficiency measures, and found that inclusion of non-energy benefits significantly increased the amount of cost effective energy savings potential because more measures became cost effective when compared with the same unit price of primary energy in the year. Similar to the method presented in Xu et al. (2013), we use Eq. (3) to account for changes in measure investments and other nonenergy costs and benefits associated with changes in operation and maintenance (O&M). For example, changes in labor, material, and other resource requirements, which may lead to positive or negative “M” value. Requirements for additional labor or materials will make “M” more positive, while an increase in productivity or reduction in labor or equipment would make the “M” more negative. A CCEi value no greater than market energy price indicates that adopting the efficiency measure is cost effective, while a higher CCEi value than the energy price indicates that the measure is not cost effective. CCEi =
Ii · q + Mi Ei
(3)
where CCEi = cost of conserved energy for energy efficiency measure i, in $/GJ; Ii = change in capital cost associated with measure i ($); q = capital recovery factor (year−1 ), see Eq. (2); Mi = annual change in monetizable non-energy costs and benefits from O&M changes associated with measure i ($/year); Ei = annual energy savings associated with measure i (GJ/year). 2.2. Calculation of cost of carbon reduction Adopting energy efficient efficiency measures can reduce carbon emissions associated with energy use in the industry. Associated with the energy savings from implementing efficiency measures is the mitigation cost and carbon-emission reduction. Similar to the concept developed for other industrial sectors (Xu et al., 2010, 2013), we consider that the cost of carbon reduction is the same as the cost of applying efficiency measures. Eq. (4) is used to calculate
56
T. Xu et al. / Sustainable Cities and Society 9 (2013) 54–61
Table 1 Annual U.S. cement production, energy use, and carbon emissionsa in 1994, 2004 and 2010.
Wet cement production Production (Mt/year) Final energy consumption (PJ/year) Primary energy consumption (PJ/year) Energy related carbon emissions (MtC/year) Total carbon emissions (MtC/year) Final energy intensity (GJ/ton) Primary energy intensity (GJ/ton) Dry cement production Production (Mt/year) Final energy consumption (PJ/year) Primary energy consumption (PJ/year) Energy related carbon emissions (MtC/year) Total carbon emissions (MtC/year) Final energy intensity (GJ/ton) Primary energy intensity (GJ/ton) U.S. Total cement production Production (Mt/year)b Dry cement share Final energy consumption (PJ/year) Primary energy consumption (PJ/year) Energy related carbon emissions (MtC/year) Total carbon emissions (MtC/year) Final energy intensity (GJ/ton) Primary energy intensity (GJ/ton) Energy related carbon emission intensity (kgC/ton) Total carbon emission intensity (kgC/ton)
1994
2004
2010
21.2 143 164 3.6
20.2 141 158 3.5
6.5 45 51 1.1
6.3 6.8 7.7
5.8 7.0 7.8
1.9 6.8 7.8
53.1 268 325 6.9
78.8 369 456 9.6
56.7 266 326 6.9
13.7 5.0 6.1
19.5 4.7 5.8
14.4 4.7 5.8
74.3 71.5% 411 490 10.5
99.0 79.6% 510 614 13.1
63.2 89.7% 311 377 8.1
20.0 5.5 6.6 141
25.3 5.2 6.2 132
16.4 4.9 6.0 128
269
256
259
a
Fuel carbon coefficient assumptions (in MtC/PJ): residual fuel oil (0.0204); distillate fuel oil (0.0189); LPG (0.0161); natural gas (0.0137); coal (0.0243); coke (0.0295); electricity (0.045); industrial “other” (0.0192). b Sources: PCA (1995, 2005, 2011).
cost of carbon reduction (CCRi ) associated with efficiency measure i. CCRi =
Ii · q + Mi Ci
(4)
where CCRi = cost of carbon reduction associated with energy efficiency measure i, in $/tC (carbon ton); Ii = change in capital cost associated with measure i ($); q = capital recovery factor (year−1 ), see Eq. (2); Mi = annual change in monetizable non-energy costs and benefits from O&M changes associated with measure i ($/year); Ci = annual carbon reduction associated with measure i (tC/year). 3. Results The energy efficiency of a cement plant is affected by factors such as products, technologies, plant size, and quality of raw materials. Table 1 summarizes the annual production, energy use and carbon emissions from the U.S. cement sector in the years selected in this paper (i.e., 1994, 2004, and 2010). For simplicity, we assume a conversion factor of 3.08 from final electricity energy to primary energy. In 1994, cement plants in the U.S. produced a total of 74.3 Mt cement (PCA, 1995). Final and primary energy use for cement making was 411 PJ and 490 PJ, respectively, which was associated with 10.5 MtC carbon emissions. Including emissions generated directly from the cement-making processes, the annual total carbon emissions were 20.0 MtC. In 2004, annual cement production was 99.0 Mt (PCA, 1995). Final and primary energy use for cement making was 510 PJ and 614 PJ, respectively. The energy related carbon emissions were 13.1 MtC, with the annual total carbon emissions of 25.3 MtC. In 2010, annual cement production was
63.2 Mt in the U.S. (PCA, 2011); final and primary energy use for cement making was 311 PJ and 377 PJ, respectively. Energy related carbon emissions were 8.1 MtC, with the annual total carbon emissions of 16.4 MtC. The table also shows a trend of production shifts from wet cement to dry cement that was less energy intensive over the historical years. In combination with technology uptake, the structural shifts resulted in an overall reduction in energy intensity from 1994 to 2010 in the U.S. cement industry. For example, final energy intensity decreased from 5.5 GJ/ton to 4.9 GJ/ton while primary energy intensity decreased from 6.6 GJ/ton to 6.0 GJ/ton for, by approximately 9–11%. Energy related carbon emission intensity also shows a similar reduction trend (a reduction of approximately 9% from 141 kgC/ton-cement to 128 kgC/ton-cement) while the total carbon emission intensity was reduced from 269 kgC/toncement to 259 kgC/ton-cement, albeit to less extent (i.e., a reduction by approximately 5%). 3.1. Cost of conserved energy In this paper, we first calculated CCE of each efficiency measure identified in this study, based upon the cost data, benefit data, and energy savings compiled for each measure. Individual CCE values were ranked from the lowest to the highest. A cost curve line is then developed using CCE values calculated from ranked individual CCE values for each specific year. Within a curve line, the length of each horizontal line section represents the magnitude of energy savings per production for an efficiency measure; while the height of each vertical line section represents the cost per unit of energy saved corresponding to the same efficiency measure. For simplicity, we assumed that nominal capital costs for energy efficiency measures had changed over the years compared to 1994, and that each of the cost data in different years could be adjusted with the GDP Price index using 1994 as the reference year (e.g., a factor of 1.21 for 2004 and 1.39 for 2010 (BEA, 2011)). The following is a sample list of the measures applicable to both dry and wet cement clinker production: kiln shell heat loss reduction; use of waste fuels, modern multi-channel burners; improvement of raw mix burnability, e.g., by mineralizers; and conversion to grate clinker cooler. Improved grinding media; high-pressure roller-press pre-grinding; roller press/horomill system; and high-efficiency classifiers are applicable to finish grinding for all cement production. In addition, more general measures include variable speed drives; high efficiency motors; energy management and process control system, and preventative maintenance; and improvement of compressed air system efficiency. Using the available data sets, capital cost adjustments, inclusion of other non-energy cost and benefits, and 30% discount rate assumed for the energy efficiency measures, we calculated the energy savings due to applicable measures identified for each year, and developed the CCE cost curve for each year (i.e., 1994, 2004, and 2010). Fig. 2 shows the cost curves for 1994, 2004 and 2010. Table 3 further summarizes the results. Final energy savings resulting from applying the energy efficiency measures were 82 PJ in 1994, 125 PJ in 2004, and 95 PJ in 2010, corresponding to final energy savings of 1.10 GJ/ton, 1.26 GJ/ton, and 1.5 GJ/ton, respectively. The annual energy savings from different sets of efficiency measures equaled to 20%, 25% and 31% of total annual final energy use in the U.S. cement sector in 1994, 2004 and 2010, respectively. Besides structural changes (increasing production of dry cement), additional efficiency measures included for 2004 and 2010 also contributed to the increase in relative energy savings exhibited here. We also identified cost effective measures from the pool of efficiency measures by comparing CCE value with weighted average energy price of each year. Then we estimated final energy
T. Xu et al. / Sustainable Cities and Society 9 (2013) 54–61
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Table 2 Historical nominal energy price, energy mix, weighted average price for the U.S. cement industry in 1994, 2004, 2010 (EIA, 1997, 2005, 2009, 2012). 1994 Price
2004 Energy share
Nominal energy price and energy mix for U.S. cement industry ($/GJ) $12.33 9.2% Electricity $2.36 0.1% Residual fuel oil $4.76 1.1% Distillate fuel oil Gas $2.35 5.1% Coal and other $1.71 72.0% $2.25 6.8% Coke $1.07 5.7% Other (i.e., tires) $2.76 100% Final energy (weighted average)
savings resulting from each set of cost effective efficiency measures. Table 2 shows historical fuel energy price, energy mix, and estimated weighted average energy price in each year. As a result, Table 3 shows that for each unit ton of cement making, cost effective energy savings was 62 PJ, 92 PJ, 76 PJ in 1994, 2004 and 2010, respectively; corresponding to intensity of 0.83 GJ/ton, 0.93 GJ/ton, and 1.21 GJ/ton, respectively. The number of cost effective measures increased from 15 in 1994 to 21 in 2010. Overall, cost effective energy savings increased from 15% to 25% of total annual final energy over the years. 3.2. Cost of carbon-emission reduction Adopting energy efficient measures can reduce carbon emissions associated with energy use in the industry. Similar to the concept developed for other sectors (Xu et al., 2013), we consider that the cost of carbon-emission reduction is the same as the cost of applying efficiency measures in the cement-making sector. Based upon Eq. (4), we calculated the cost of carbon-emission reduction associated with conserved energy from each applicable efficiency measure for each of the selected years in this study. Fig. 3 exhibits the cost of carbon-emission reduction (in U.S. dollar per metric ton of carbon) versus the carbon-emission reduction (metric ton of carbon) for the U.S. cement industry in 2010. Fig. 3 shows that CCR values for some measures were above $1000/tC while their carbon-reduction potential was rather limited. It was far from being cost effective or practical to apply such energy efficiency measures for the purpose of reducing carbon emissions. On the other hand, there were a number of measures with much lower CCR values. Fig. 4 shows the same cost curves as in Fig. 3, with an
2010
Price
Energy share
Price
Energy share
$13.74 $3.65 $5.51 $6.19 $2.04 $2.69 $1.07 $3.33
11% 0.2% 1.5% 5.1% 58% 2.0% 23% 100%
$17.00 $8.46 $10.34 $5.20 $4.03 $5.31 $2.53 $5.57
11% 0.1% 1.3% 5.2% 71.2% 6.9% 4.6% 100%
Table 3 Annual and cost effective energy savings in the U.S. cement making in 1994, 2004, and 2010. Year
Annual final energy savings Wet cement final energy savings (PJ/year) Dry cement final energy savings (PJ/year) Total annual final energy savings (PJ/year) Total final energy savings per production unit (GJ/ton) Total savings as a percentage of total final energy use (%) Total number of measures identified Cost effective final energy savings Wet cement making final energy savings (PJ/year) Dry cement making final energy savings (PJ/year) Total annual cost effective final energy savings (PJ/year) Total cost effective final energy savings per production unit (GJ/ton) Cost effective savings as a percentage of total annual final energy use (%) Weighted average final energy price ($/GJ) Total number of cost effective measures (GDP Price index included)
1994
2004
2010
24 58 82 1.10
27 99 125 1.26
8 87 95 1.50
20%
25%
31%
31
37
46
18
17
6
44
75
71
62
92
76
0.83
0.93
1.21
15%
18%
25%
2.76 15
3.33 15
5.57 21
Note: Weighted average price of final energy is estimated based on industrial energy uses and costs (EIA, 1997, 2005, 2009, 2012).
Fig. 3. Cost of carbon-emission reduction in 2010 (discount rate 30%). Fig. 2. Cost curves of final energy savings for the U.S. cement industry for 1994, 2004, and 2010.
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Fig. 4. Primary energy cost curves for inclusion and exclusion of other non-energy benefits in 2010.
enlarged scale on the Y-axis to illustrate CCR variations of different efficiency measures with lower CCR values. Total carbon-emission reduction is defined as the carbonemission reduction resulted from total annual energy savings due to implementing the efficiency measures as identified and quantified in this study. Table 4 summarizes the aggregated numbers for carbon-emission reduction in each year as they were associated with the energy efficiency measures identified in this study. We estimated that the total carbon-emission reduction resulting from all applicable energy efficiency measures was 2.1 MtC in 1994, and 3.3 MtC in 2004, and 2.5 MtC in 2010, approximating 11–15% of total carbon emission in the sector. In addition, Table 4 also presents the total carbon-emission reduction corresponding to the cost effective efficiency measures that were identified based on CCE values. This set of efficiency measures is the same set of cost effective measures based upon comparisons of CCE value with average weighted energy price for each year. Applying this set of cost effective measures would reduce carbon emissions by 1.6 MtC in 1994, 2.4 MtC in 2004, and 2.0 MtC in 2010, corresponded to 8%, 10%, and 12% of total annual carbon emissions in the sector, respectively. This is an important finding in that implementing existing cost effective efficiency measures can result in significant reduction in carbon emissions in each year. 4. Discussion 4.1. Effects of including non-energy benefits on cost curves Cost curves in Fig. 2 are plotted including other non-energy benefits. Different curves of conserved energy (in U.S. dollar per GJ Table 4 Total carbon-emission reduction in the U.S. cement-making in 1994, 2004, and 2010. 1994
2004
2010
Total carbon-emission reduction from all applicable efficiency measures 2.1 3.3 2.5 Total carbon-emission reduction from all measures (MtC/year) Total carbon emission in the sector (MtC/year) 20 25.3 16.4 11% 13% 15% Total carbon-emission reduction as a percentage of total carbon emissions in the sector Carbon-reduction from cost effective measures Total cost effective carbon-emission reduction based on CCE (MtC/year) Cost effective carbon-emission reduction as a percentage of total carbon emissions from the sector
1.6
2.4
2.0
8%
10%
12%
energy saved) of energy efficiency measures can be plotted against the specific energy savings (GJ per ton of cement) of two scenarios: with and without inclusions of other non-energy benefits for the U.S. cement industry in 2010 as shown. Fig. 4 shows differences in the values for costs of conserved energy (in primary energy terms), in 2010 U.S. dollar per primary energy saved (GJ), between curves with non-energy benefits included and excluded for the cement industry. Including other non-energy benefits significantly lowered the CCE values. For example, with the same total primary energy savings of 1.2 GJ/ton cement in 2010, including non-energy benefits in the cost curves for the cement industry can significantly decrease the total cost of conserved primary energy for measures from $5.0/GJ to $1.0/GJ. Corresponding to average primary energy price of $4.36/GJ for the sector in 2010, the cumulative primary energy savings would be 1.0 GJ/t when non-energy benefits are not included and would increase to 1.2 GJ/t when non-energy benefits are included in CCE calculation. In parallel, Fig. 5 shows the final energy cost curves for year 2010, which exhibits a similar difference between including and excluding other non-energy benefits in the cost curve. For example, corresponding to average final energy price of $5.57/GJ for the sector in 2010, the cumulative final energy savings would be 1.10 GJ/t when non-energy benefits are not included and would increase to 1.21 GJ/t when non-energy benefits are included in CCE calculation. In summary, inclusion of other non-energy benefits of implementing efficiency measures can reduce CCE values of efficiency measures, and may achieve a higher level of conserved energy corresponding to specific energy price.
4.2. Treatment of energy prices The energy efficiency measures in the cement industry processes are operated by using a wide variety of energy or fuel types. For example, energy reduction in the blast furnace could reduce the need for coal, while an efficiency measure in an EAF could reduce only electricity. The savings from reduced use of coal are in general less cost effective compared to electricity savings, mainly due to much lower coal price (e.g., coal price in 2010 was $4.75/GJ, much lower than electricity price of $13.80/GJ). When using the concept of CCE to identify cost effective measures applicable to the cement sector, we actually compared CCE value with the weighted average fuel price for the cement industry in the previous section, even though the fuel or energy type applicable to an individual measure is homogeneous (e.g., for 2010 a weighted average fuel price was calculated at $7.38/GJ while actual fuel price could be much lower or higher). The potential drawback of using CCE and weighted energy price to characterize cost effectiveness of an individual measure is that if the measure operates only with electricity, its cost effectiveness would be biased (unfavorably) when using weighted average price to compare, because the weighted average price is lower than electricity price. In another word, a measure that was in fact cost effective (if the corresponding energy price for the specific fuel type was used) could be otherwise identified as not so cost effective compared to weighted average energy price, if at all. On the other hand, for a measure that uses only coal of which unit price is generally lower than other fuels, the degree of its cost effectiveness could be overestimated when its CCE is compared with the weighted average energy price that is higher than coal price. In addition, while conventional CCE is a very good index when energy supply (thus price) is homogeneous, a cost curve based upon CCE values (e.g., Fig. 5) may lack in readiness for evaluating cost effectiveness of individual measures for different years. Using the conventional CCE, one has to compare the CCE value with weighted average of energy price in a particular year. Because fuel prices and
T. Xu et al. / Sustainable Cities and Society 9 (2013) 54–61
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Table 5 Comparison of cost effective savings using the concepts of conventional CCE and modified CCE (30% discount rate, cost inflation considered). Year 1994
2004
2010
Cost effective final energy savings of energy efficiency measures using CCE method Wet cement making final energy savings (PJ/year) 18 17 6 Dry cement making final energy savings (PJ/year) 44 75 71 Total annual cost effective final energy savings 62 92 76 (PJ/year) 0.83 0.93 1.21 Total cost effective final energy savings per production unit (GJ/ton) 15% Cost effective savings as a percentage of total 18% 25% annual final energy use (%) 15 Total number of cost effective measures (GDP Price 15 21 index included)
Fig. 5. Final energy cost curves for inclusion and exclusion of other non-energy benefits in 2010.
energy supplies changed from year to year, the weighted average of energy price would be a moving target across years. In order to better understand the cost effectiveness from different treatments of energy price, we calculated the modified CCE (MCCE) values, using the following equation to further investigate the effects of specific energy price corresponding to various fuel types. MCCEi =
Ii · q + Mi − Ei · Pi Ei
(5)
where MCCEi = cost of conserved energy for energy efficiency measure i, in $/GJ; Ii = change in capital cost associated with measure i ($); q = capital recovery factor (year−1 ), see Eq. (2); Mi = annual change in monetizable non-energy costs and benefits from O&M changes associated with measure i ($/year); Pi = market price of energy use associated with measure i ($/GJ); Ei = annual energy savings associated with measure i (GJ/year). Essentially, a MCCEi value no greater than zero indicates that adopting the efficiency measure is cost effective, while a positive MCCEi value indicates that the measure is not cost effective based upon the available data. MCCE takes into account energy prices that vary by years and by fuels applicable to a specific measure; therefore, some changes in ranking orders of MCCE values for a same measure should be expected from year to year. Using MCCE method provides an alternative to readily evaluate cost effectiveness of individual measures. Table 5 shows the comparison of cost effective measures and savings based upon conventional CCE and MCCE calculations. As a result from using both MCCE and CEE methods, the table shows that cost effective savings per unit of product were very close for each year, even though number of cost effective measures increased slightly when the MCCE method is used.
Cost effective final energy savings of energy efficiency measures using MCCE method 18 18 6 Wet cement final energy savings (PJ/year) 45 77 71 Dry cement final energy savings (PJ/year) 63 94 77 Total annual cost effective final energy savings (PJ/year) 0.85 0.95 1.21 Total cost effective final energy savings per production unit (GJ/ton) 15% Cost effective savings as a percentage of total 18% 25% annual final energy use (%) 18 20 24 Total number of cost effective measures (GDP Price index included) Note: Numbers in the table are rounded.
on the magnitudes of costs of conserved energy and savings for individual energy efficiency measures. For each of the selected years, we applied three discount rates, i.e., 10%, 20%, and 30%, respectively, to calculate CCE values and as they correspond to the efficiency measures. Fig. 6 shows the cost curves with various discount rates (10%, 20%, and 30%) in 2010. At lower discount rates (e.g., 10%), CCE values of several measures (e.g., roller press, improved compressed air system, high efficiency motor) became negative. CCE curve for the same set of efficiency measures moved upward with the increase of discount rates from 10% to 30%. When compared to weighted average energy price (i.e., $5.57/GJ) in the sector, more measures can be identified as cost effective when the discount rate is lower. Table 6 further presents the total final energy savings from applying the efficiency measures identified, and those from applying cost effective efficiency measures using three discount rates for each year. As can be seen in Table 6, the influence of the change in discount rates from 10% to 20% becomes more evident on the amount of energy savings associated with cost effective measures,
4.3. Effects of discount rate on cost curves and uncertainties In the CCE analyses presented earlier in this report, we assumed that a real discount rate of 30% is applied, partly reflecting the industry’s capital constraints and preference for short payback periods and high internal rates of return. The assumption of higher discount rates (e.g., 30%) can also indirectly account for program costs and various barriers against the adoption of cost effective efficiency measures. It is also clear that such an assumption would mathematically lead to a prediction with higher (e.g., positive) annualized costs of the efficiency measures. In this section, we performed sensitivity analyses to examine the effects of discount rates
Fig. 6. Cost curves of final energy savings with discounts rates 10%, 20%, and 30% in 2010.
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Table 6 Final energy reductions from cost effective efficiency measures at different discount rates. Total final energy savings 1994
2004
2010
Final energy reduction by cost effective measures at different discount measures All measures (PJ/year) 82 125 95 77 120 85 Cost effective measures (discount rate 10%) (PJ/year) 66 107 77 Cost effective measures (discount rate 20%) (PJ/year) 62 92 76 Cost effective measures (discount rate 30%) (PJ/year)
whereas the influence of the change in discount rates between 20% and 30% becomes smaller on cost effective energy savings. As an example in 2010, final energy savings of 85 PJ (accounting for approximately 89% of the total savings 95 PJ) were considered cost effective when a discount rate of 10% is used; whereas only 80–81% of the total energy savings (i.e., 76–77 PJ out of 95 PJ) was considered cost effective when a discount rate of 30% or 20% is used. In summary, while variations in discount rates do not affect the magnitudes of energy savings from efficiency measures in any given year, estimated cost effective energy savings increase modestly with the decrease of discount rates from 30% to 20%, and such an increase of energy savings becomes more significantly with further reduction of discount rates from 20% to 10% in the U.S. cement sector. While a high discount rate (i.e., 30%) partly reflects the industry’s capital constraints and preference for short payback periods, and can partly accounts for program costs and various barriers against the adoption of cost-effective energy efficient technologies, the magnitudes of energy savings due to cost effective measures can increase significantly if a lower discount rate is practically used. In this study, energy savings for each measure were determined by comparing the difference in energy use after the measure was implemented versus when it was absent. For each measure, the share of U.S. production to which the individual measure was applied was estimated based upon literature information and expert input (Sathaye et al., 2010). Because there was no sufficient information from the field to update the penetration rates reliably, we assumed penetration rate to be constant between 2004 and 2010, as well as 30% discount rate as a conservative way to estimate overall energy savings. Additional assumptions about conversion and emission factors may also affect the outcomes but the uncertainty bound smaller than the impacts from discount rate and penetration. Therefore it is very important that future effort should pursue monitoring the implementation of efficiency measures and programs in place to promote such effort. Lastly, our analysis indicates that policies that promote the implementation of efficiency measures and strategies in the sector may help to improve cost effectiveness of more measures and lead to an improved market.
5. Conclusions In this paper, we have developed cost curves for efficiency measures applied in the U.S. cement-making sector for the years 1994, 2004, and 2010; and characterized costs of conserved energy and associated carbon-emission reduction in the sector. The shapes of cost curves are influenced by the efficiency measures, baseline year, discount rate, production, industry structure (e.g., wet versus dry cement making), and whether or not other non-energy benefits are included. Inclusion of other non-energy benefits and lowered discount rates reduced the CCE values, making the efficiency measures more cost effective. We also estimated magnitudes of annual
energy savings and carbon-emission reduction associated with the efficiency measures in this study. • The final energy savings resulting from applicable energy efficiency measures were estimated as 82 PJ, 125 PJ, and 95 PJ in 1994, 2004, and 2010, respectively; equivalent to approximately 20%, 25% and 31% of the sector’s annual final energy use in those years. Besides structural changes (i.e., increasing production shares of dry cement observed over the period from 1994 to 2010), additional efficiency measures included for 2004 and 2010 also contributed to the increase in relative energy savings. • Final energy savings resulting from cost effective efficiency measures was estimated as 62 PJ, 92 PJ, and 76 PJ in 1994, 2004, and 2010, respectively, equivalent to a range of 15–25% of the total annual final energy use in the U.S. cement-making sector. • Carbon emission reduction resulting from efficiency measures was estimated as 2.1 MtC, 3.3 MtC, and 2.5 MtC in 1994, 2004, and 2010, respectively; corresponding to approximately 11%, 13%, and 15% of sector’s annual carbon emissions. • Applying cost effective energy measures would reduce carbon emissions by 1.6 MtC, 2.4 MtC, and 2.0 MtC in 1994, 2004, and 2010, respectively; corresponding to carbon-emission reduction by 8–12% of the sector’s annual carbon emissions. Similar to the findings reported for pulp and paper sector, implementing existing cost effective measures can result in significant energy savings and carbon reduction in the cement-making sector. This study further confirms that policies and strategies should be promoted to reduce the costs of efficiency measures (e.g., help reducing actual discount rates) and to improve cost effectiveness of more efficiency measures. This study also points out the importance of monitoring effort in the future to track the progress of efficiency measure implementation for the industrial sector. While there is a need for an improved market for energy efficiency and reduced carbon footprint, energy programs and promotion effort may in turn lead to the efficiency market improvement in industries. Acknowledgment This study is sponsored by Climate Economics Branch, Climate Change Division of U.S. Environmental Protection Agency, under Contract No. DE-AC02-05CH11231with the U.S. Department of Energy. Appendix A. List of efficiency measures identified in each year List of efficiency measures Raw materials preparation (wet cement) Mechanical transport systems (w) Slurry blending and homogenizing (w) Wash mills with closed circuit classifier (w) Raw materials preparation (dry cement) Mechanical transport systems (d) Raw meal blending systems (d) Use of high efficiency roller mills (d) Raw meal process control (d) High efficiency classifiers (d)
1994
2004
2010
X
X X X
X X X
X X X
X X X X X
X X X X X
X X
X X
X X X X
X X X X X
X
Fuel preparation (wet and dry) Roller mills (d) Roller mills (w) Clinker production (wet cement) Process control and management (w) Kiln combustion system improvements (w) Kiln shell heat loss reduction (w) Use of waste fuels (w) Modern multi channel burners (w)
X X X
T. Xu et al. / Sustainable Cities and Society 9 (2013) 54–61 Improve raw mix burnability, e.g. by mineralizers (w) Conversion to grate clinker cooler (w) Oxygen enrichment technology (w) Conversion to semi-dry process (w) Conversion to semi-wet kilns (w) Optimize heat recovery of clinker cooler (grate) (w) Conversion to dry multi-stage pre-heater, pre-calciner kilns (w) Clinker production (dry cement) Kiln shell heat loss reduction (d) Use of waste fuels (d) Modern multi channel burners (d) Improve raw mix burnability e.g. by mineralizers (d) Conversion to grate clinker cooler (d) Low pressure drop cyclones for suspension pre-heaters (d) Heat recovery for cogeneration (d) Low grade heat recovery with ORC (d) Oxygen enrichment technology (d) Conversion from dry to multi-stage pre-heater kilns (d) Conversion from multi-stage pre-heater to pre-calciner kiln (d) conversion from dry to pre-heater, pre-calciner kilns (d) Optimize heat recovery of clinker cooler (grate) (d) Finish grinding (all cement) Improved grinding media High pressure roller press-pre grinding Roller press/horomill system High efficiency classifiers General measures Variable speed drives High efficiency motors Energy management and process control system Preventative maintenance Replace smaller plants by BAT larger plants Improve compressed air system efficiency Product change Blended cements Total number
X X
X
X X X
X X X
X X X X X
X
X
X
X X
X X
X X X X
X X
X X
X X
X
X
X
X
X X X X
X
X
X
X
X
X
X
X
X
X X X X
X X X X
X X X X
X X X
X X X
X X X
X
X
X X X
X 31
X 37
X 46
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