From: Torres.Elineth@epamail.epa.gov Sent: Thursday, August 05, 2010 2:58 PM To: Laney, Michael N. Cc: Barnett.Keith@epamail.epa.gov Subject:Comparative Memo and ISIS documentation for the docket Attachments: 20100805 ISIS Cement Documentation_Final.pdf; ISIS documentation_All Appendices in one document.pdf; Fina Technical Memo_ Comparison of Analytical Tools_Aug_5_2010.pdf

Mike,

Please find attached the ISIS peer
‐ reviewed documentation and the appendices to the ISIS documentation. Also attached the Final Technical memo comparing the analytical tools used in the NESHAP and NSPS analysis. I will send the other documents in another email due to their size.

(See attached file: 20100805 ISIS Cement Documentation_Final.pdf)(See attached file: ISIS documentation_All Appendices in one document.pdf) (See attached file: Fina Technical Memo_ Comparison of Analytical Tools_Aug_5_2010.pdf)

Elineth Torres Environmental Protection Specialist U.S. EPA OAQPS/SPPD/Program Design Group 109 T.W. Alexander Dr. Durham, NC 27711 Phone: 919

‐ 541

‐ 4347 Fax: 919

‐ 541

‐ 5600

# Industrial Sectors Integrated Solutions (ISIS) Model

for the Portland Cement Manufacturing Industry

Ravi K. Srivastava, Ph.D.
William H. Yelverton, PE
U.S. Environmental Protection Agency
Office of Research and Development

Air Pollution Prevention and Control Division
Research Triangle Park, NC 27711

Elineth Torres
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Sector Policies and Programs Division
Research Triangle Park, NC 27711

Samudra Vijay, Ph.D.
Sam Analytic Solutions, LLC
Morrisville, NC 27560

August 2010

# Acknowledgements

A large model such as ISIS could not have been completed without the support and advice of many individuals and organizations. We gratefully acknowledge the following contributions. Professor Richard Newell of Duke University and Dr. Dallas Burtraw of the Resources for the Future (RFF) engaged in many helpful discussions, which helped shape ISIS. Additionally, Dr. Burtraw helped develop the formulation of cement imports. Under EPA Contract EP-D-06-118, Mr. Brooks Depro of RTI International developed the cost functions and other economic data for the cement industry. Also under EPA Contract EP-C-07-015, Dr. James Staudt of Andover Technologies developed the technical information on controls and energy efficiency measures used in the current version of ISIS cement model. Dr. Jayant Sathaye and Dr. Tengfang Xu of Lawrence Berkeley National Laboratory (LBL) provided many useful insights on energy efficiency measures for the cement industry. Portland Cement Association (PCA) provided helpful comments on ISIS formulation, engaged in many fruitful discussions with the ISIS development team, and provided some needed data. The ISIS cement model was peer reviewed by a number of experts. These experts included Dr. Dallas Burtraw of RFF, Dr. Hendrik G. van Oss of the U.S. Geological Survey, Mr. Charles Drummond, Mr. Chris Nichols, and Mr. Sikander Khan of the U.S. Department of Energy, Mr. Hector Ybanez of Holcim Cement, Mr. Kevin Culligan of EPA, Dr. Fereidun Feizollahi of California Air Resources Board (Economic Studies Section), Mr. Eric Smith of EPA, and Dr. Ernst Worrell of LBL. Mr. Charles Fulcher and Mr. Tom Walton of EPA provided many quality assurance checks on the ISIS cement model. Finally, Dr. Wojciech Jozewicz, Kim Egler, and the staff at ARCADIS Inc. compiled the many comments received from peer reviewers and helped with development of this documentation under EPA Contract EP-C-09-027.i 

## Table of Contents

List of Tables ...............................................................................................................................................iii List of Figures.............................................................................................................................................. iv Acronyms, Initializations, and Abbreviations............................................................................................... v Conversion Table – English Units to SI Units...........................................................................................viii Chapter 1 Introduction............................................................................................................................1-1
1.1 The US Cement Industry..................................................................................................................1-1
1.1.1 Cement Types and Categories ..............................................................................................1-1
1.1.2 Overview of the Cement Manufacturing Process .................................................................1-2
1.1.3 Kiln Types and Their Use.....................................................................................................1-5
1.1.4 Portland Cement Production in the U.S................................................................................1-7
1.1.5 Imports of Portland Cement in the U.S.................................................................................1-8
1.1.6 Cement Demand Centers ......................................................................................................1-9
1.2 Emissions from the U.S. Cement Industry and Applicable Regulations..........................................1-9
1.3 Overview of ISIS............................................................................................................................1-10 References for Chapter 1 .........................................................................................................................1-13 Chapter 2 ISIS Mathematical Framework............................................................................................2-1
2.1 Indexes, Sets, and Mappings............................................................................................................2-3
2.2 Objective Function...........................................................................................................................2-4
2.3 Supply ..............................................................................................................................................2-7
2.4 Production Capacity and Supply Costs ..........................................................................................2-10
2.5 Emissions .......................................................................................................................................2-14
2.6 Controls and Costs .........................................................................................................................2-16
2.7 Costs of Energy Efficiency Measures ............................................................................................2-23
2.8 Policy Options................................................................................................................................2-26
2.9 Optimization and Post-Processing .................................................................................................2-28 References for Chapter 2 .........................................................................................................................2-29 Chapter 3 Cement Data...........................................................................................................................3-1
3.1 Data Requirements...........................................................................................................................3-1
3.2 Cement-Specific Data ......................................................................................................................3-1
3.2.1 Industry, Fuel, and Emissions...............................................................................................3-1ii

3.2.2 Control Technologies and Emission Abatement Approaches ............................................3-13
3.2.3 Policy and Economic Parameters .......................................................................................3-13 References for Chapter 3 .........................................................................................................................3-24 Chapter 4 Model Calibration..................................................................................................................4-1
4.1 Calibration Methodology .................................................................................................................4-1
4.2 Data for Calibration..........................................................................................................................4-1
4.2.1 Cement Prices in USGS Districts .........................................................................................4-2
4.2.2 Cement Production in USGS Districts..................................................................................4-2
4.2.3 Cement Imports by Import Districts .....................................................................................4-2
4.3 Results of Calibration.......................................................................................................................4-2
4.4 Recommendations..........................................................................................................................4-10
4.5 References for Chapter 4................................................................................................................4-11 Chapter 5 An Example Policy Analysis .................................................................................................5-1
5.1 An Example Analysis of Potential Reductions in CO 2 Emissions from the U.S. Cement Industry ............................................................................................................................................5-1
5.2 Summary and Thoughts for Future Work ........................................................................................5-8
5.3 Disclaimer ........................................................................................................................................5-9 References for Chapter 5 .........................................................................................................................5-10iii



### List of Tables

Table 1-1. Typical Average Heat Input by Cement Kiln Type ...........................................................1-5 Table 1-2. Number of Kilns by Kiln Type in the U.S. in 2005 and 2009 ...........................................1-6 Table 1-3. Largest Hydraulic Cement and Clinker Import Custom Districts in the U.S. in 2005.......1-8 Table 3-1. Summary of Kilns Modeled in the ISIS Cement Industry Model......................................3-1 Table 3-2. Portland Cement Demand in Millions of Metric Tons.......................................................3-4 Table 3-3. Bulk Shipment Costs (Cents per Metric Ton per Mile) .....................................................3-6 Table 3-4. Portland Cement and Clinker Imports in Million Metric Tons, by Customs District in

2005...................................................................................................................................3-7 Table 3-5. Specific Fuel Consumption and Total Exhaust Gas Flow Rate (wet) for Various Kiln

Types .................................................................................................................................3-9 Table 3-6. Estimated Uncontrolled NO X Emission Intensities for Cement Kilns .............................3-10 Table 3-7. Average SO 2 Emissions for Each Kiln Type in Each State .............................................3-11 Table 3-8. Approximate CO 2 and H 2 O Produced from Combustion of Fuels...................................3-12 Table 3-9. NO X Control Technologies for Cement Kilns..................................................................3-15 Table 3-10. SO 2 Control Technologies for Cement Kilns...................................................................3-18 Table 3-11. CO 2 Control Technologies for Cement Kilns ..................................................................3-19 Table 3-12. HCl, Hg, and THC Control Technologies for Cement Kilns...........................................3-20 Table 3-13. Multimedia Impacts of Process Capacity Replacement on Cement Kiln Operation 1 ......3-20 Table 3-14. Energy Efficiency Measures for Raw Materials Preparation...........................................3-22 Table 3-15. Energy Efficiency Clinker Making Measures..................................................................3-22 Table 3-16. Energy Efficiency Measures for Finish Grinding ............................................................3-23 Table 3-17. Energy Efficiency Plant-wide Measures..........................................................................3-23 Table 4-1. Cement Prices ($/short ton) for USGS Districts ................................................................4-4 Table 4-2. Cement Production (short tons) for Various USGS Districts ............................................4-5 Table 4-3. Cement Imports (except from Canada and Mexico) for Import Districts (short tons).......4-6 Table 4-4. Reported and Calculated Cement Prices in USGS Districts (2005)...................................4-7 Table 4-5. Reported and Calculated Cement Prices in USGS Districts (2006)...................................4-8 Table 4-6. Reported and Calculated Cement Prices in USGS Districts (2007)...................................4-9 Table 4-7. Aggregate production (reported and modeled) for 2005-2007 ..........................................4-9 Table 5-1. CO 2 Caps Modeled in this Analysis...................................................................................5-2iv



### List of Figures
Figure 1-1. Schematic of the Wet Cement Process...............................................................................1-3 Figure 1-2. Schematic of the Dry Cement Process with Cyclone Preheater.........................................1-4 Figure 1-3. Trends in Cement Kiln Type and Capacity in the U.S. (1995 to 2008) .............................1-6 Figure 1-4. Portland Cement Plant Locations.......................................................................................1-7 Figure 1-5. Imports of Clinker and Cement from 1998 to 2008 (PCA, 2009a)....................................1-9 Figure 1-6. Portland Cement Facilities and O 3 NAA, PM 2.5 NAA, and Class 1 Areas ......................1-11 Figure 1-7. An Integrated View of Pollution Generation Pathways, Emissions Abatement

Approaches, and Multimedia Impacts for an Industrial Sector.......................................1-12 Figure 2-1. Consumer and Producer Surplus in a Market ....................................................................2-2 Figure 2-2. Broad Modules and Associated Information Flows Utilized in the ISIS Framework........2-2 Figure 2-3. Stepwise Calculation of the Demand Curve ......................................................................2-5 Figure 3-1. Distribution of Cement Kilns in the United States as of 2009...........................................3-3 Figure 3-2. Commercial Fuel Use Profile by U.S. Cement Industry in 2005.......................................3-9 Figure 5-1. Projected CO 2 Allowance Prices........................................................................................5-2 Figure 5-2. Projected Revenue for the U.S. Cement Industry over the Horizon 2013-2020................5-3 Figure 5-3. Projected Average Cement Prices in 2013 for the U.S. Cement Industry .........................5-4 Figure 5-4. Projected Demand for Cement...........................................................................................5-4 Figure 5-5. Projected Imports for the U.S. Cement Industry over the Horizon 2013-2020..................5-5 Figure 5-6. Projected Capacity Retirement/Mothballing......................................................................5-6 Figure 5-7. Projected Emissions of NO X , SO 2 , and CO 2 from the U.S. Cement Industry over the

Horizon 2013-2020............................................................................................................5-6 Figure 5-8. Projected CO 2 Emissions and Reductions from the U.S. Cement Industry Under the

BAU and the 10-percent CO 2 Reduction Cases. ...............................................................5-7 Figure 5-9. Projected Control Technology Applications in the U.S. Cement Industry Under the

10-percent CO 2 Reduction Case........................................................................................5-8



### Appendix A
Andover Technology Partners and RTI International Me 

### mosv



### Acronyms, Initializations, and Abbreviations

ACI Activated Carbon Injection AEO Annual Energy Outlook APCA American Portland Cement Alliance ARB Air Resources Board (see CARB) ASD Adjustable Speed Drives ASR Alkali-Silica Reactivity ASTM American Society for Testing and Materials AVC Average Variable Cost AZ Arizona BACT Best Available Control Technology BAU Business As Usual BFS Blast Furnace Slag BLS Bureau of Labor Statistics CA California CARB California Air Resources Board CCS Carbon capture and sequestration CEMBUREAU European Cement Association based in Brussels CGC Convert to Reciprocating Grate Cooler CIF Cost, Insurance & Freight CKD Cement Kiln Dust CO Colorado CSI Combustion System Improvement DE Delaware DLI Dry Lime Injection EGFW Exhaust Gas Flow Rate (wet) EIA Energy Information Administration EMCS Energy Management and Control System EMD Efficient Mill Drives EMPC Energy Management and Process Control EPA U.S. Environmental Protection Agency ESP Electrostatic Precipitator ETS Efficient Transport System FL Florida FOM Fixed Operation and Maintenance GA Georgia GAMS General Algebraic Modeling System GDP Gross Domestic Productvi

GHG Greenhouse Gas H 2 O Water HAP Hazardous Air Pollutant HEC High-Energy Classifiers HEM High Efficiency Motors HERM High Efficiency Roller Mill HPRP High-Pressure Roller Press HRPG Heat Recovery for Power Generation ID Idaho IF Indirect Firing IGMBM Improved Grinding Media (Ball Mills) IL Illinois IPCC Intergovernmental Panel on Climate Change IPM International Petroleum Monthly ISIS Industrial Sectors Integrated Solutions LNB Low NO X Burner LWS Limestone Wet Scrubber MI Michigan MMBtu Million British Thermal Units MO Missouri MSA Mineralogical Society of America MYB Minerals Yearbook (USGS) NAA Nonattainment Area NAS National Academy of Science NATA National Air Toxics Assessment NC North Carolina NEI National Emission Inventory NESCAUM Northeast States for Coordinated Air Use Management NESHAP National Emission Standards for Hazardous Air Pollutants NM New Mexico NO X Oxides of Nitrogen (also Nitrogen Oxides) NRC National Research Council NV Nevada O&M Operations and Maintenance OCAS Optimization of Compressed Air Systems OGR Optimize Grate Cooler OK Oklahoma OMB U.S. Office of Management and Budgetvii

OR Oregon PA Pennsylvania PC Pulverized Coal PCA Portland Cement Association PCVM Process Control Vertical Mill PM Particulate Matter PRB Powder River Basin PSD Prevention of Significant Deterioration RMB Raw Materials Blending RMC Ready-Mix Concrete RMTHEC Raw Materials Transport High Energy Classifiers RTO Regenerative Thermal Oxidizer SBH Slurry Blending and Homogenization SC South Carolina SCR Selective Catalytic Reduction SFC Specific Fuel Consumption SG&A Sales, General and Administration SHLR Shell Heat Loss Reduction SLC Salt Lake City SNCR Selective Non-Catalytic Reduction SO X Oxides of Sulfur SPE Spatial Price Equilibrium SR Seal Replacement TDF Tire Derived Fuel USGS United States Geological Survey UT Utah WA Washington WBCSD World Business Council for Sustainable Development WMCCC Wash Mills with Closed Circuit Classifierviii



### Conversion Table – English Units to SI Units

To Obtain From Multiply by

m ft 0.3048

m 2 ft 2 9.29 × 10 -2

m 3 ft 3 2.83 × 10 -2
°C °F 5/9 × (°F – 32) kg lb 0.454 J/kg Btu/lb 1.33 × 10 -4

m 3 /s cfm 4.72 × 10 -4

m 3 /s gpm 6.31 × 10 -5
J/kWh Btu/kWh 1055.056 mills $ 0.001 kg/m 2 in. Hg 345.31 metric ton short ton 0.9071-1 

## Chapter 1 Introduction

In the National Academy of Science’s 2004 report, “Air Quality Management in the United States,” the National Research Council (NRC) recommended to the U.S. Environmental Protection Agency (EPA) that standard setting, planning, and control strategy development should be based on integrated assessments that consider multiple pollutants, and that these integrated assessments should be conducted in a comprehensive and coordinated manner (NAS, 2004). With these recommendations, EPA began to move toward establishing multipollutant and sector-based approaches to manage air quality and environmental protection. The benefits of multipollutant and sector-based analyses and approaches include the ability to identify optimum strategies (considering feasibility, costs, and benefits across all pollutant types such as criteria, toxics, and others), while streamlining administrative and compliance complexities and reducing conflicting and redundant requirements.
The development of policy options for managing emissions and air quality can be made more effective and efficient through sophisticated analyses of relevant technical and economic factors. Such analyses are greatly enhanced by the use of an appropriate modeling framework. Accordingly, the Industrial Sectors Integrated Solutions (ISIS) model has been developed at EPA (ARCADIS, 2010). Currently, the ISIS model is populated with US cement manufacturing data, and efforts are underway to build representations of the US pulp and paper sector and the US iron and steel sector. This document describes the framework of EPA’s ISIS model and its application to the US cement manufacturing industry

. 

### 1.1 The US Cement Industry

1.1.1 Cement Types and Categories
Cement is a finely ground powder which, when mixed with water, forms a hardening paste of calcium silicate hydrates and calcium aluminate hydrates. Cement is used in mortar (to bind together bricks or stones) and concrete (bulk rock-like building material made from cement, aggregate, sand, and water). Concrete production uses the majority of cement produced.
Portland cement and blended cement are used in concrete production, but portland cement is by far the most common type of cement used for concrete production. By modifying the raw material mix and, to some degree, the temperatures utilized in manufacturing, slight compositional variations can be achieved to produce portland cements with slightly different properties. In the U.S., the different varieties of portland cement are denoted per the American Society for Testing and Materials (ASTM) Specification C-150. The ASTM standard C-150 recognizes eight types of portland cement:

• Type I is for use in general construction (e.g., buildings, bridges, floors, etc.).

• Type IA is similar to Type I with the addition of an air-entraining agent.

• Type II generates less heat at a slower rate and has a moderate sulfate-attack resistance.

• Type IIA is similar to Type II with the addition of an air-entraining agent.1-2

• Type III is used when concrete must set and gain strength rapidly.

• Type IIIA is similar to Type III with the addition of an air-entraining agent.

• Type IV has low heat of hydration and slow strength development.

• Type V is used when concrete must resist high sulfate concentration in soil and groundwater.
Portland cements are usually gray, but a more expensive white portland cement (generally within the Type I or II designations) can be obtained by processing only raw materials with very low iron and transition-elements content. In addition to the eight types of portland cement listed above, small volumes of specialty cements are also manufactured. Other types of specialty cement include blended cement (portland cement mixed together with blast furnace slag or other pozzolan), pozzolan-lime cement, masonry cement, and aluminous cement (PCA, 2008). The common industry practice, and that of the US Geological Survey (USGS), includes, within the portland cement designation, a number of other cements not within ASTM C-150, which are composed largely of portland cement and are used for similar applications (e.g., concrete) (USGS, 2005). These concretes include blended cement, block cement, expansive cement, oil well cement, regulated fast setting cement, and waterproof cement. Plastic cements and portland-lime cements are being grouped within the masonry cement designation. Because portland cement accounts for approximately 95 percent of the cement industry’s total production (van Oss, 2008), and because the costs and trends of this industry sector can be adequately captured by describing the market processes associated with the production, distribution, and use of portland cement, in this work the focus is on portland cement. In 2006, portland cement’s market share in the U.S. was 94 percent, while masonry cement’s market share comprised the remaining 6 percent (USGS, 2007a).


### 1.1.2 Overview of the Cement Manufacturing Process
Portland cement is produced from raw materials such as limestone, chalk, shale, clay, and sand. These raw materials are quarried, crushed, finely ground, and blended to the correct chemical composition. Small quantities of iron ore, alumina, and other minerals may be added to adjust the raw material composition. The fine raw material is fed into a large rotary kiln (cylindrical furnace) where it is heated to extremely high temperatures (about 2640 °F [about 1450 °C]). The high temperature causes the raw material to react and form a hard nodular material called “clinker”. Clinker is cooled and ground with approximately 5-percent gypsum and other minor additives to produce portland cement. The main steps in the cement manufacturing process are illustrated in Figures 1-1 and 1-2 showing the wet process and the dry process with cyclone preheater. The schematic for a precalciner kiln would be very similar to that shown in Figure 1-2, with the addition of a calciner vessel.
The heart of the clinker production process is the kiln, which can be rotary or vertical shaft designs. Rotary kilns are commonly used in the U.S. and elsewhere. These kilns are 6-8 m in diameter and 60 m to well over 100 m long. The kilns are set at a slight incline and rotate at 1 to 3 revolutions per minute. The kiln is fired at the lower end and the feed materials move toward the flame as the kiln rotates. The materials reach temperatures between 1400-1500 °C in the kiln. Three steps occur with the raw material mixture during pyroprocessing. First, all moisture is driven off from the materials. Then the calcium carbonate in limestone decomposes into CO 2 and calcium oxide (free lime) during calcination. Finally, the lime and other minerals in the raw materials react to form calcium silicates and calcium aluminates, the main components of clinker.1-3ClassifierStackCoalFeederClassifierFigure 1-1. Schematic of the Wet Cement ProcessSource: CEMBUREAU, 19991-4ClassifierStackCoalFeederClassifierFigure 1-2. Schematic of the Dry Cement Process with Cyclone PreheaterSource: CEMBUREAU, 19991-5



### 1.1.3 Kiln Types and Their Use
Rotary kilns are broadly categorized as dry- and wet-process kilns, depending on how the raw materials are prepared. Wet-process kilns are fed raw material slurry with moisture content ranging between 30 and 40 percent. A wet-process kiln needs additional length to evaporate the water contained in the raw material feed. Nearly 33 -percent additional kiln energy is consumed in evaporating the water in the slurry.
In dry-process kilns, raw material is fed as dry powder. There are three major variations of dry-process kilns in operation in the U.S.: long dry kilns, preheater kilns, and preheater/precalciner kilns. In preheater kilns and preheater/precalciner kilns, the early stages of pyroprocessing occur before the materials enter the rotary kiln. Preheater and preheater/precalciner kilns have higher production capacities and greater fuel efficiency compared to other types of cement kilns. Table 1-1 shows heat input in terms of millions of British Thermal Units (MMBtu)/ton 1 of clinker for various types of kilns. As the data clearly demonstrate, preheater/precalciner kilns provide greater fuel efficiency. The replacement of wet and (certain) dry process kiln capacity with modern kiln processes can yield, theoretically, substantial reductions in fuel use due to fuel efficiency gains. As the industry moves toward more efficient processes, replacement of wet and long dry process capacity with more efficient kiln process technologies is expected.
Table 1-1. Typical Average Heat Input by Cement Kiln Type

Kiln Type Heat Input,

MMBtu/ton of clinker
Wet 6.0 Long Dry 4.5
Preheater 3.8
Preheater/Precalciner 3.3 Source: EPA, 2007 (Table 3-3)

As expected, a recent trend in the cement sector has shown the replacement of lower capacity, inefficient wet and long dry kilns with bigger and more efficient kilns. This trend is expected to continue. In the U.S., the overall number of kilns decreased by 11 percent from 1995 to 2004. During the same period, total clinker production capacity increased by 18.6 percent. The Portland Cement Association (PCA) data show that average kiln capacity also increased by 27 percent, from 405,000 to 556,000 tons per year between 1995 and 2004. The number of kilns operating in the U.S. in 2005 compared with the number of kilns in operation in 2009 is shown in Table 1-2. The trend in kiln design and average kiln capacity is shown in Figure 1-3.

1 PLEASE NOTE: for the purposes of this document, short tons will be referred to simply as “tons” and represents 2000 lbs. A unit conversion table is provided in the front matter of this document.1-6

Table 1-2. Number of Kilns by Kiln Type in the U.S. in 2005 and 2009 Kiln Type Number of Kilns (2005) Number of Kilns (2009)
Wet 50 42 Dry 48 32
Preheater 36 29
Precalciner 47 58 Source: PCA, 2006 and PCA, 2009a

0 100 200 300 400 500 600

0 25 50 75 100 125 150 175 200 225

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008Average Capacity, thousands of metrictons/yearNumber of kilns

Dry Kilns Wet Kilns Average Kiln Capacity

Figure 1-3. Trends in Cement Kiln Type and Capacity in the U.S. (1995 to 2008) Note: The PCA Plant Information Summary became biennial in 2004. The 2005 data were obtained by personal communications between EPA and the PCA.

As reported by the USGS, in 2005, the U.S. portland cement industry produced approximately 87 million metric tons of clinker, of which 13.5 percent was produced by plants with wet process kiln systems while 81 percent was produced by plants operating only dry kilns of all three types (long-dry, preheater and preheater/precalciner). The remaining 5.5 percent was produced by plants that operate both wet and dry kilns (USGS, 2007b: Table 7).1-7



### 1.1.4 Portland Cement Production in the U.S.
The cement industry remains a vital industry in the U.S. and throughout the world. In the U.S., portland cement is a $12 billion industry (van Oss, 2008). In 2005, the U.S. consumed a record 128 million metric tons of portland cement (USGS, 2007b: Table 1).
In 2005, portland cement was produced at 107 plants in the U.S., including 37 states and Puerto Rico. The locations of the clinker-producing portland cement plant facilities in 2005 are shown in Figure 1-4. The cement manufacturing sector in the U.S. is concentrated among a relatively small number of companies, many of which are owned by or are subsidiaries of foreign companies (USGS, 2007b). Together, ten companies accounted for about 80 percent of the total cement production in U.S. for 2005 (USGS, 2007b). California, Texas, Pennsylvania, Florida, and Alabama are the five leading cement-producing states, which accounted for about 43 percent of the total production in 2005 (USGS, 2007b: Table 3).
In 2009, PCA projected a capacity expansion of 27 million tons between 2008 and 2013, an 18 -percent increase in existing capacity from 2006. PCA’s projected capacity expansions are to come from 23 kilns; 5 came on-line in 2008 and 18 more are expected to come on-line between 2009 and 2013 (PCA, 2009b). The investment in these projected capacity expansions is projected at $6.9 billion. Note that a typical project for a new facility (greenfield) from ground breaking to startup has a timeframe of about 2 to 3 years. Building a new kiln in an existing facility (brownfield) can take approximately 1 year (EPA, 2007). If permitting for mining and (re)construction is accounted, a typical project can take as long as 4 to 6 years for a greenfield facility and up to 3 years for a brownfield facility (Andover Technology Partners, 2009a).

Mississippi-Hudson River

Cement Plant Locations Largest Cement Import Custom Districts Cement Import Custom Districts

Figure 1-4. Portland Cement Plant Locations1-8



### 1.1.5 Imports of Portland Cement in the U.S.
Portland cement is not only produced and consumed domestically, but it is also traded internationally. In 2005, the U.S. (not including Puerto Rico) produced 94 million metric tons of cement (USGS, 2007b: Table 3) and imported 34 million metric tons of hydraulic cement and clinker (USGS, 2007b: Tables 3 and 18). The level of imports to the U.S. is highly cyclical, with domestic producers importing primarily when domestic plants are at full capacity and cannot meet excess demand. Imports also occur when domestic producers seek to capture market share. Generally, imported cement and clinker make up 20 to 27 percent of domestic cement consumption. In 2005, total imports of cement and clinker (especially clinker) increased, owing to continued high demand; imported cement accounted for about 24 percent of the total cement sales in the U.S. (USGS, 2007b).
In 2005, the ten leading international cement and clinker suppliers to the U.S. were, in descending order, Canada, China, Thailand, Greece, the Republic of Korea, Venezuela, Mexico, Colombia, Taiwan, and Sweden. The ten busiest ports of entry within customs districts existing in 2005 were, in descending order, New Orleans, Tampa, Los Angeles, Houston-Galveston, San Francisco, Miami, Seattle, Detroit, New York, and Charleston (South Carolina) (USGS, 2007b). Table 1-3 shows the major customs districts for hydraulic cement and clinker imports in the U.S. Figure 1-5 shows the imports of clinker and cement from 1998 to 2008.
Table 1-3. Largest Hydraulic Cement and Clinker Import Custom Districts in the U.S. in 2005 Import of Hydraulic Cement and Clinker Custom District thousands of metric tons thousands of tons Percentage of Total US Imports New Orleans, LA 4,095 4,514 12.31 Tampa, FL 3,478 3,834 10.46 Los Angeles, CA 3,053 3,365 9.18 Houston-Galveston, TX 2,619 2,887 7.87 San Francisco, CA 2,363 2,605 7.10 Miami, FL 2,265 2,497 6.81 Seattle, WA 1,489 1,641 4.48 Detroit, MI 1,317 1,452 3.96 New York, NY 1,264 1,394 3.80 Charleston, SC 1,102 1,215 3.31
Total 23,046 25,404* 69.29% * rounding, original data in metric tons (Source: USGS, 2007b (Table 18)1-9Thousands of Metric Tons

Figure 1-5. Imports of Clinker and Cement from 1998 to 2008 (PCA, 2009a)



### 1.1.6 Cement Demand Centers
Because of the relatively high transportation costs, the U.S. cement industry is structured around statespecific cement demand centers. PCA reports that the vast majority of cement produced in the U.S. is being transported less than 300 miles by truck due to cement's low value by weight and high cost of transport (PCA, 2005). However, cement may be transported over longer distances, especially when the less expensive rail and water transportation modes are available (APCA, 1997).


### 1.2 Emissions from the U.S. Cement Industry and Applicable Regulations
Criteria pollutants, hazardous air pollutants, and CO 2 are released during cement manufacturing. Nitrogen oxides (NO X ) emissions from cement kilns result primarily from the combustion process: oxidation of fuel nitrogen (fuel NO X ) and the oxidation of nitrogen in the combustion air (thermal NO X ). EPA’s 2005 National Air Toxics Assessment (NATA) Inventory reports that cement kilns released 181,000 metric tons (200,000 short tons) of NO X emissions from the combustion of fuels (EPA, 2009).
Sulfur dioxide (SO 2 ) emissions 2 from cement kilns result from the combustion of sulfur-bearing compounds in coal, oil, and petroleum coke, as well as sulfur compounds in raw materials. Sulfur in the fuel will oxidize to SO 2 during pyroprocessing and a significant amount is likely to be captured in the form of sulfates as the flue gas passes through the calcination zone. Compared to long dry and wet kilns, preheater and precalciner kilns tend to be more effective at capturing fuel-generated SO 2 . Accordingly, oxidation of sulfur in the feed materials is likely to be the major component of total SO 2 emissions. The

2 Small amounts of SO 3 may be released in addition to bulk SO 2 but the SO 3 emissions are treated as SO 2 for computational purposes. Small amounts of CO may be released in addition to bulk CO 2 but CO emissions are treated as CO 2 for computational purposes.1-10

2005 NATA Inventory reflects that cement kilns released 133,000 metric tons (147,000 short tons) of SO 2 emissions in 2005.
Particulate matter (PM) emissions result from quarrying operations (the crushing and grinding of raw materials and clinker) as well as kiln line operations. The 2005 NATA Inventory estimates show that, in 2005, cement kilns released 10,000 tons of PM 10 emissions. The cement industry is also a source of HAPs (e.g., hydrochloric acid vapor and chlorine), as well as metals including but not limited to mercury, antimony, cadmium, and lead (EPA, 2008).
The cement manufacturing process is also a source of carbon dioxide (CO 2 ) emissions. CO 2 emissions are a product of the combustion of fuel as well as the calcination of the limestone in the raw meal. The CO 2 from fuel combustion can be calculated from heat input and fuel characteristics combined with clinker production. The CO 2 from calcination can be calculated taking into account the amount of limestone used as a source of clinker calcium. Limestone currently is the predominant source of calcium for the clinker. Pure limestone would produce 0.44 tons of CO 2 for every ton of limestone completely calcined to calcium oxide. Substitute materials may be used in lieu of limestone with the effect of reducing the CO 2 emissions from clinker production. The CO 2 emissions reduction would be proportional to the amount of substitute materials added. Detailed discussion of CO 2 emissions from cement kilns can be found in Appendix A.
Multiple regulatory requirements to reduce criteria air pollutants and HAPs emissions currently apply to the cement industry sector. The New Source Performance Standards (NSPS) and the National Emissions Standards for Hazardous Air Pollutants (NESHAPs) are two of the federal requirements that apply to cement facilities. Additionally, state and local regulatory requirements might apply to individual cement facilities depending on their locations. In 2008, 44 cement facilities were located within ozone (O 3 ) nonattainment areas (NAA), while 20 facilities were within PM 2.5 nonattainment areas. Seventeen facilities were found to be located in (or within 30 miles of) Class 1 areas, as shown in Figure 1-6. Class 1 areas are areas of special natural, scenic, recreational, or historic (national or regional) value for which the Prevention of Significant Deterioration (PSD) regulations provide special protection.


### 1.3 Overview of ISIS
ISIS, a sector-based dynamic programming model, will facilitate the analyses of emission reduction strategies for multiple pollutants while taking into account plant-level economic and technical factors such as the type of emission units (for cement –kiln), associated capacity, location, cost of production, applicable controls, and their costs. For each of the emission reduction strategies under consideration, the model is able to provide information on the following:

• Optimal (least cost) industry operation

• Cost-effective controls to meet the demand for cement

• Emission reduction requirements over the time period of interest
ISIS design allows for incorporating multiple industries within a multi-market, multi-product, multipollutant, and multi-region emissions trading framework. The objective function in ISIS maximizes total surplus and uses an elastic formulation of the demand function to estimate area under the demand

curve.1-11

Figure 1-6. Portland Cement Facilities and O 3 NAA, PM 2.5 NAA, and Class 1 Areas

The ISIS code is written in the General Algebraic Modeling System (GAMS) language. Input data, organized in various spreadsheets of a Microsoft Excel workbook, are passed on to the GAMS files. These input data consist of an industry database, which provides unit-level production, capacity, production cost, and emissions information. The controls database provides information regarding applicable air pollution control technologies and their cost and emission control characteristics. A policy module is used to specify various parameters of interest to the policy analyst, such as emissions cap, emission reduction scenarios, and discount rate. The input data, control data, and policy parameters are then transmitted to the optimization part of the ISIS model, where they are used to solve the selected base and policy cases. After solving, the results are post-processed to calculate values of various outputs of interest. The output data are exported to Excel spreadsheets for further analyses and graphical representation of selected results.
Within an industrial sector, generally emissions arise from four pathways: (1) on-site emissions due to combustion of fossil fuels for energy at plants, (2) on-site emissions due to processing of certain raw materials (e.g., limestone calcination in cement plants, non-energy uses of fossil fuels in chemical processing and metal smelting), (3) off-site emissions due to combustion of fossil fuels at power plants to generate the electricity needed by the industrial sector, and (4) overseas emissions associated with imports. These pathways are depicted in Figure 1-7.1-12

Also shown in Figure 1-7 are the potential options for abating emissions from industrial sectors and multimedia impacts. The options shown in green are pollution prevention measures and the ones in red are mitigation measures. Clearly, the integrated picture presented in Figure 1-7 makes a compelling case for considering commodity production/supply activities along with emissions while developing holistic emission reduction strategies. While developing the ISIS framework, care has been taken to build the emission pathways and abatement options shown in Figure 1-7. Example emission reduction policies that can be evaluated using ISIS are:

• Criteria pollutants (NO X , SO 2 , PM, CO) –emission limits and/or cap-and-trade

• Hazardous Air Pollutants (e.g. Hg, HCl) – emission limits

• CO 2 – cap-and-trade and/or emission taxes

• Long and short time horizons: CO 2 (decades), criteria pollutants (annual)

• Regional or national requirements

Pollution Controls (NOx, SO 2 ,PM, CO 2 , VOC, .. )



### Industrial Plants Improvements 

### Fuel(s) Pollution Reduction Policy (Rate-based, cap-and-trade, emission taxes)



### Air emissions

Product(s) Product Substitution Fuel Substitution/ Reduction (NOx, SO2, PM, CO2, ...) 

### Raw Materials
Raw Material Substitution



### Electricity Change in use (Power plant emissions) 

### Water

Waste

Market(s) Imports (Overseas emissions)

Figure 1-7. An Integrated View of Pollution Generation Pathways, Emissions Abatement

Approaches, and Multimedia Impacts for an Industrial Sector1-13



### References for Chapter 1
APCA (1997). Comments on EPA’s Draft Economic Analysis of Air Pollution Regulations for the Portland Cement Industry (May 1996), prepared for American Portland Cement Alliance by Environomics, January 29, 1997.
ARCADIS (2010). Development of U.S. EPA Industrial Sector Integrated Solutions (ISIS) Model, Quality Assurance Project Plan. Prepared under contract number EP-C-09-027 for the U.S. Environmental Protection Agency, Air Pollution Prevention and Control Divisions, Research Triangle Park, NC. February 3, 2010.
CEMBUREAU (1999). Best Available Techniques for the Cement Industry, CEMBUREAU Report, The European Cement Association, December 1999. D/1999/5457/December, Brussels. http://www.cembureau.be

E PA (2007). Alternative Control Techniques Document Update – NO X Emissions from New Cement Kilns. EPA-453/R-07-006, November 2007. http://www.epa.gov/ttn/catc/dir1/cement_updt_1107.pd f
, accessed October 21, 2008.
EPA (2008). AP 42, Fifth Edition, Compilation of Air Pollutant Emission Factors, Volume I, Chapter 11: Mineral Products Industry. http://www.epa.gov/ttn/chief/ap42/ch11/final/c11s06. pdf , accessed October 21, 2008. Complete document: http://www.epa.gov/ttn/chief/ap42/ , accessed October 21, 2008.
EPA (2009). EPA 2005 National Air Toxics Assessment Inventory. U.S. Environmental Protection Agency. October 2009.
NAS (2004). Air Quality Management in the United States. National Research Council (U.S.), Committee on Air Quality Management in the United States, National Academies Press, Washington, 2004. http://books.nap.edu/catalog.php?record_id=10728 , accessed October 21, 2008.
PCA (2005). Letter from David S. Hubbard, Director, Legislative Affairs, Portland Cement Association. RE: Hours of Service of Drivers; Proposed Rule (Docket Number FMCSA-2004-19608), March 10, 2005. http://www.cement.org/exec/DHOS%20Comments percent20 3.10.05.pdf , accessed October 21, 2008.
PCA (2006). U.S. and Canadian Portland Cement Industry: Plant Information Summary. Portland Cement Association, Skokie, IL, 2006.
PCA (2008). History & Manufacture of Portland Cement. Portland Cement Association. http://www.cement.org/basics/concretebasics_history. asp , accessed October 21, 2008.
PCA (2009a). PCA Annual Yearbook 2009. North American Cement Industry. Portland Cement Association.
PCA (2009b). PCA Capacity Report. Flash Report. Portland Cement Association’s Economic Research Department. Updated October 19, 2009.
Andover Technologies Partners (2009a). Memorandum: NO X , SO 2 and CO 2 Emissions from Cement Kilns (Emissions Memo) , from Jim Staudt to Ravi Srivastava, Samudra Vijay, Elineth Torres. Dated March 10, 2009 (see Appendix A of this document).1-14

USGS (2005). Background Facts and Issues Concerning Cement and Cement Data. U.S. Geological Survey, Open-File Report 2005-1152. http://pubs.usgs.gov/of/2005/1152/2005-1152.pdf , accessed October 21, 2008.
USGS (2007a). Mineral Commodity Summaries. pp. 40-41, January 2007, http://minerals.usgs.gov/minerals/pubs/commodity/cem ent/cemenmcs07.pdf , accessed September 24, 2009.
USGS (2007b). 2005 Minerals Yearbook: Cement. U.S. Geological Survey, p. 16.2, February 2007, http://minerals.usgs.gov/minerals/pubs/commodity/cem ent/cemenmyb05.pdf , accessed September 24, 2009.
van Oss, H.G. (2008). Personal communication from Hendrik G. van Oss, USGS, to Elineth Torres, US EPA, on July 7, 2008.2-1 

## Chapter 2 ISIS Mathematical Framework

ISIS is a sector-based dynamic linear programming model that can determine optimal sector operation for meeting demand and pollution reduction requirements over specified time periods. The objective in an ISIS simulation is to maximize total surplus (see Figure 2-1) over a horizon of interest for an industry, which, in general, can be a multi-product one.
The general concept of spatial price equilibrium (SPE) in a network, where the mutual influences of production, transportation, and consumption patterns are given full consideration, has been developed over the past 6 decades. In SPE network models, interregional economies are simulated by finding the balance of demand, supply, and trade that will result in competitive market equilibrium among the regions. Enke (1951) first demonstrated how the cost of transportation might be included in an equilibrium analysis of spatially separated markets by means of analogy with resistance to the flow of current in an electric circuit. Shortly after Enke, Samuelson (1952) analyzed interregional flows of commodities and market equilibrium using a linear programming formulation. In this type of formulation, the equilibrium for each market of a sector is equivalent to the quantities and prices that result while maximizing the sum of consumer and producer surpluses for each market of the sector. This sum is referred to as the total surplus or net social payoff of the sector; McCarl and Spreen (1980) provide interpretation and justification. The linear programming formulation of the SPE problem was developed by Duloy and Norton (1975).
Using Figure 2-1, the definition of the suppliers’ surplus corresponding to a quantity Q of a commodity is the difference between the total revenue and the total cost of supplying the commodity. This surplus (gross profit) is given by the area under the horizontal line P1-P minus the area under the inverse supply curve up to point P. Similarly, the consumers’ surplus corresponding to a quantity Q is given by the area under the inverse demand curve up to point C minus the area under the horizontal line C1-C. This area is the cumulative opportunity gain of all consumers who purchase the commodity at a price lower than the price they would have been willing to pay. It is evident from Figure 2-1 that the total surplus is maximized exactly when Q is equal to the equilibrium quantity QE. This is a very useful result, as it provides a method for computing the equilibrium.
The total surplus concept has long been a mainstay of social welfare economics because it takes in to account the interests of both consumers and of producers (Samuelson and Nordhaus, 1977).
The broad modules and associated information flows utilized in the ISIS framework are shown in Figure 2-2. While ISIS structure permits accounting for multiple products, the description below is provided relative to one product to bring out the important elements of the formulation and not burden the reader with many details. Also, to make the description more readable and understandable, the input data (i.e., those supplied by the user, or derived from user-supplied data) are shown in bold and the variables, whose values are determined in the optimization process, are shown in italics . This scheme helps in organizing the numerous data elements and variables, and hopefully makes it easier for the reader to relate the data element to descriptions in the previous chapters. Finally, the names of variables and data elements have been chosen to be self-explanatory as far as possible.2-2

Price Supply curve

Quantity Demand curve Equilibrium Consumer surplus

Producer surplus 

### C1

P1

Q Q E



### P C

Figure 2-1. Consumer and Producer Surplus in a Market

ISIS Engine Industry Information • Products

• Production capacities and costs • Demand • Imports parameters • Transportation costs • Noted retirements and growth • Energy Intensity Production Technologies
a nd Emission Abatement Approaches
Availability, applicability,
c ost, and performance Policy Parameters • Time horizon

• Policy type

Model Outputs • Base case and controlled emissions

• Production, Inter-market trades, imports • Commodity and allowance prices • Retirements and capacity growth • Controls installed • Costs • Other Economic Parameters • Discount rate

• Escalation rates • Demand elasticity • Economic life

Fuels • Primary: coal, coke,
n atural gas, coal+TDF • Substitute: tires, TDF Emissions • Sulfur dioxide

• Nitrogen oxides • Carbon dioxide

Figure 2-2. Broad Modules and Associated Information Flows Utilized in the ISIS Framework2-3



### 2.1 Indexes, Sets, and Mappings
Before we start the description of the mathematical structure of ISIS, it is helpful to define the sets of relevant entities and mappings describing the relationships among various entities.
Indexes (one-dimensional sets)

• ISIS data structures (sets and parameters), variables, and equations use the following indexes:

• t is the set of years in the time horizon of interest;

• i is the set of all units, including existing, replacement, expansion, and new units. Subsets of i described below define more-specific populations of units;

o iE(i) is the set of existing units

o irepl(i) is the set of replacement units

o iExp(i) represents the set of expansion units

o iNew(i) represents the set of new units

• f is the set of fuels applicable to the sector;

• m is the set of raw materials specific to the sector;

• j is the set of sector-specific pollutants of interest;

• k is the set of sector-specific controls relevant to the emission reduction policy of interest;

• ee is the set of energy efficiency measures; and

• r is the set of geographic regions where units are located.
Mappings
The mappings used in ISIS are:

• ri(i,r) is the mapping relating a unit i to its geographic location r ;

• poltikjee(t,i,k,j,ee) is the mapping relating availability, applicability, and the ability to change emissions of controls k and energy efficiency measures ee to unit i, pollutant j , and year t ;

• poltik(t,i,k) is the mapping relating availability and applicability of controls k to unit i and year t ;

• poltiee(t,i,ee) is the mapping relating availability and applicability of energy efficiency measures ee to unit i and year t ;

• poltirk(t, ri(i,r),k) is the mapping relating availability and applicability of controls k to unit i located in geographic region r and year t ; and2-4

• poltiree(t, ri(i,r),ee) is the mapping relating availability and applicability of energy efficiency

measures ee to unit i located in geographic region r and year t

. 

### 2.2 Objective Function
As mentioned above, the objective function solved in the ISIS model corresponds to maximizing the total surplus (or minimizing the negative of the total surplus) for the sector of interest over the selected time horizon. This objective function is:



# ∑ ∫ ∑ ∑ ∑ ∑ ∑ ∑

     

⋅ ⋅ − +

⋅ ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅=

t dc t,j t,i,ee t,i,k t,id t,dc t,i



### dc) ddemand(t, )price(t,dc ions(t,j) totalemiss ee)scost(t,i, teemeasure

st(t,i,k) tcontrolco st(t,id) timportsco

(t,dc) ttranscost )dncost(t,i tannualpro z

dis(t)

j)alprice(t, dis(t) dis(t) dis(t) dis(t) dis(t) dis(t) Minimize

(2.2.1)

where the quantities appearing in the equation above are defined for year t as follows,
dis(t) is the discount factor,
tannualprodncost(t,i) is the annual production cost ($) for production unit i
, ttranscost(t,dc) is the cost ($) of transporting the product to demand center dc
, timportscost(t,id) is the cost ($) of importing foreign product in import district id
, tcontrolcost(t,i k) is each unit’s total control cost ($) using control technology k
, teemeasurescost(t, i, ee) is each unit’s total cost ($) using the energy efficiency measures ee , alprice(t,j) is the allowance price input by the user,
totalemissions(t,j) is emission of pollutant j from the sector, 

# ∫

⋅
dc 

### dctddemand dctprice ),( ),( is the area under the demand-price curves for all markets dc

.2-5

Note that in the objective function the term with alprice(t,j) comes into effect only if the user provides values for alprice(t,j) . If these values are specified, the model runs as described under the “Allowance Price Inputs” in a later section.
A stepwise approximation of the demand curves (FPL-PELPS, 2003) is used in ISIS so that relevant area can be computed in a linear programming scheme. This approximation is explained below.
Stepwise Approximation of Demand Curves in ISIS
For clarity, the subscripts t and dc corresponding to time and demand center are dropped in the following explanation.
The relationship between demand and price in a market dc is expressed as

σ 1



### D0 P0      

= D DP )( (2.2.2)

where

D is the demand for the commodity with corresponding price P ( demand ),

σ is the elasticity of demand relative to price, and

D0 and P0 are the initially-specified demand quantity and price, respectively.
Figure 2-3 shows a representation of the above equation and also reflects how a stepwise approximation of the price-demand curve can be created.

P ( d 1 )

P ( d 2 )

P ( d 3 ) P ( d 4 ) P 0

D min D 0 D max

d 1 d

2 d

3 d

4 P ( D )

D wid

D wid Price

Quantity

Figure 2-3. Stepwise Calculation of the Demand Curve2-6

First the range of the demand-price curve is defined using
range)-(1D0D min ⋅= (2.2.3)

range)(1D0D max +⋅= (2.2.4)

where

range is a user-supplied parameter with value between 0 and 1. This parameter defines the interval D min - D max within which the new equilibrium demand quantity is expected to be found. Note range should be large enough to ensure that the solution does fall in the interval D min - D max. On the other hand a smaller value of range can increase precision of the stepwise approximation. In ISIS a value of 0.5 is used for range

. Next, a series of steps is defined within the interval D min - D max with the width of each step given by



### stepsofNumber D-D dwidth min max 

### = (2.2.5)

where
Number of steps is another user-supplied parameter. Increasing the value of this parameter will increase precision of the stepwise approximation, but will increase the model size. In ISIS, a value of 100 is used for Number of steps

. Now the demand quantity at the center of the slice dstep inside the interval is



### 2 1)-dstep(2dwidth DD min dstep 

### ⋅

⋅ 

### += (2.2.6)

Using the above information, the price-demand curve is determined

σ 1 dstep dstep 

### D0

D P0DP 

      

= )( (2.2.7)

Finally, the approximated area under the price-demand curve is



## )( dstep dstep 

## DD P stepsofNumber

1dsteps 

# ∑

= 

## ⋅ (2.2.8)2-7

Substituting (2.2.8) in (2.2.1), the objective function becomes



## ∑ ∑ ∑ ∑ ∑ ∑ ∑ ∑

     

⋅ ⋅ − +

⋅ ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅=

t dstepdc t,j t,i,ee t,i,k t,id t,dc t,i

dstepdctdemand ions(t,j) totalemiss ee)scost(t,i, teemeasure

st(t,i,k) tcontrolco st(t,id) timportsco

(t,dc) ttranscost )dncost(t,i tannualpro z

dstep)dc,, P(demand(t dis(t) j)alprice(t, dis(t) dis(t) dis(t) dis(t) dis(t) dis(t)

, ),,( Minimize

(2.2.9)

The above objective function is minimized with the constraints and related equations described in the following sections to arrive at the relevant optimum solution.
Equation (2.2.7) is used to generate the price-demand curves for all time periods and demand centers. However, this equation needs specifications of one point on each demand function in each time period (i.e., [P0{t, dc}, D0{t, dc}]) . To determine such points, a single run of the inelastic version of the ISIS model (with exogenous D0[t, dc]) is made and then the resulting shadow prices P0(t, dc) are used in Equation (2.2.7) to generate price-demand curves for all time periods and demand centers. These curves are used in the last term of the objective function and in the supply constraint, Equation (2.3.1), presented in the next section.


### 2.3 Supply
The demand for a commodity in a market can be satisfied by domestic production and foreign imports as follows:

.),,( ),,( ),,( 

# ∑ ∑ ∑ ≥ + dstep id i dstepdctdemand dcidtantity importedqu dcitity prodnquant (2.3.1)

where
prodnquantity(t,i,dc) is the quantity supplied from the domestic production unit i to demand center dc in year t , importedquantity(t,oi,id,dc) is the quantity of commodity received from the origin (country) of imports oi at the domestic import district id and supplied from that district to demand center dc in year t , and
demand(t, dc,dstep) is the demand for the commodity at the dstep th level of the price-demand curve for the demand center dc in year t . The construction of the price-demand curves has been explained above.2-8

Note that transportation of quantity from production units and import districts to demand centers is implicit in the above equation.
The sum of all quantities in year t supplied from a kiln i to various demand centers dc must equal the production level of unit i in that year. Then,



### . prodn(t,i) )ity(t,i,dc prodnquant

dc 

### = 

# ∑ (2.3.2)

where
prodn(t, i) is the production level (tons/year) of manufacturing unit i in year t . Note that, in general, production can be from existing units, units added at a plant (i.e., expansion units), newer units replacing units at a plant (i.e., replacement units), and new kilns. Treatment of these is explained in a subsequent section.
Production of a unit is constrained by its capacity. So,



### i).,capacity(t ≤ 

### ),( itprodn (2.3.3)

where
capacity(t, i) is the capacity (tons product/year) of manufacturing unit i in year t

. The sum of all imported quantities supplied from an import district id to various demand centers dc in year t must equal the imports available at that import district in that year. Then,



# ∑ ∑ = istepoi dc 

### id,istep)oiImports(t,

d,dc) antity(t,i importedqu

, 

### , (2.3.4)

where
Importedquantity(t,id,dc) is the imported quantity supplied from import district id to demand center dc in year t, and
Imports(t,oi,id,istep) is the imported quantity available at the import district id in year t at the istep th level of the imports curve for country oi . Construction of the country (or region) and import district specific imports-cost curves is explained below.
Stepwise Approximation of Imports Curves in ISIS
The treatment of imports is similar to the treatment for elastic demand curves. Again, for clarity, the subscripts t, oi, and id corresponding to time, origin of imports, and import district are dropped in the following explanation.
The relationship between imports arriving from oi at id and their price is expressed as2-9 α 1


### Imports0 Iprice0 

      

= I

mports orts) Iprice(Imp (2.3.5)

where
Imports is the imports of the commodity arriving from oi at id with corresponding imports price (value) Iprice ,



### α is the elasticity of imports relative to imports price, and
{Imports0, Iprice0} is a point on the applicable quantity-price curve.
First the range of the imports-price curve is defined using



### range)-(1 Imports0 I min 

### ⋅ = (2.3.6)



### range)(1 Imports0 I max 

### +⋅ = (2.3.7)

where

range is a user-supplied parameter with value between 0 and 1. This parameter defines the interval I min - I max within which the new equilibrium imports quantity is expected to be found. Note range should be large enough to ensure that the solution does fall in the interval I min - I max. On the other hand a smaller value of range can increase precision of the stepwise approximation. In ISIS a value of 0.5 is used for range

. Next, a series of steps is defined within the interval I min - I max with the width of each step given by



### steps ofNumber I-I Iwidth min

max 

### = (2.3.8)

where
Number of steps is another user-supplied parameter. Increasing the value of this parameter will increase precision of the stepwise approximation, but will increase the model size. In ISIS, a value of 100 is used for Number of steps

. Now the import quantity at the center of the slice istep inside the interval is



### 2 1)-istep(2Iwidth I Imports min

istep 

### ⋅

⋅ 

### += (2.3.9)2-10

Using the above information, the imports-price curve is determined

α 1 istep istep 

### Imports0

Imports Iprice0 Imports Iprice        

= 

### ) ( (2.3.10)

Equation (2.3.10) is used to generate the imports-cost curves for all time periods, origins of imports, and import districts. However, this equation needs specifications of one point on each import function in each time period (i.e., [Iprice0{t, oi, id}, Imports0{t, oi, id}]) . To determine such points, a single run of the inelastic version of the ISIS model (with exogenous Imports0[t, oi, id] corresponding to capacities of import districts) is made and then the resulting Iprice0(t, oi, id) are used in Equation (2.3.10) to generate the imports-cost curves for all time periods, origins of imports, and import districts.


### 2.4 Production Capacity and Supply Costs
The ISIS model includes constraints for ensuring that endogenous production capacity changes occur in a realistic way. This section describes how the capacity changes take place in the ISIS framework and the treatment of related costs. Note that various cost elements (e.g., capital cost of a unit [$/ton clinker] in the cement sector) are escalated appropriately to reflect values in years of interest.
Production Capacity Related Constraints
Added capacity in year t is given by

When t = 1,

(2.4.1a)

For t > 1,



## { }

.iNew(i) iExp(i) irepl(i)i ants); techlifepl (vyear(v) tyear(t) vyear(v) ;i),capacity(t

∪∪ ∈ + <≤ ⋅ +

− = 

# ∑

v 

### )tcap(t,i,v i)timeblock, addcap(t)addcap(t,i
(2.4.1b)

where

v is the set of vintages of unit i
, vyear(v) and tyear(t) are parameters with values corresponding to years in the selected time horizon,
tcap(t,i,v) is a binary variable that can bring v th vintage of unit i online in year t,2-11

timeblock is the block of years used in simulation
, and
techlifeplants is the technical life of a unit.
Only one vintage of a unit is possible for the period starting when the vintage comes on line and ending with its technical life.

(2.4.2)

The annual costs associated with meeting the demand for the commodity include: (1) annualized capital costs associated with capacity growth (i.e., replacement units, expansion units, and new capacity) and projected units, (2) annual fixed operation and maintenance (FOM) costs, (3) annual variable costs associated with use of labor, raw material, fuel, electricity, and operation and maintenance, (4) annual transportation costs, and (5) annual cost of imports. These costs are described below.
Capital Recovery
If the existing units are paid for and do not have capital recovery costs, then



## { } .iE(i)i ∈= ;0 st(t,i) plantcapco (2.4.3)

where
plantcapcost(t,i) is the annual capital cost of a unit.
For projected units, for which startup date is known, annual capital cost is given by



## { }

. ; iP(i)i nts); ecolifepla (tstart(i) tyear(t) tstart(i) i)t, pcapcostt( i),capacity(t CRFplant

∈

+ ≤≤ ⋅

⋅ = st(t,i) plantcapco (2.4.4)

where
pcapcostt(t,i) is the capital cost (e.g., $/ton of clinker for the cement sector) of i th unit in year t, and
CRFplant is the capital recovery factor calculated using an appropriate interest rate and time period, ecolifeplants , for capital recovery.
Annual capital costs for all populations except existing and projected is 

### CRFplant itAddcap st(t,i) plantcapco

⋅ ⋅ = 

### i),capcostt(t),( (2.4.5)2-12

where
capcostt(t,i) is the capital cost (e.g., $/ton of clinker for the cement sector) for the i th unit

.
Variable Costs
The annual variable cost at a unit is calculated using



## [ ]

. ),( ),(



# ∑ + + + ⋅ + + + =

sw 

### (t,i,SW) SWdispcost )tncost(t,i H2Oconsump itfc itprodn i)varcost(t, i)ELCt(t,i)LBRt(t,i)VOMt(t,

i)RMTt(t, (2.4.6)

where
RMTt(t,i) is the raw material cost ($/ton product) at unit i in year t , VOMt(t,i) is the cost of operation and maintenance ($/ton product) at unit i in year t , LBRt(t,i) is the cost of labor ($/ton product) at unit i in year t , ELCt(t,i) is the cost of electricity use ($/ton product) at unit i in year t , fc(t, i) is the cost of fuel ($/ton product) at unit i in year t , and
varcost(t,i) is the annual variable cost ($/ton product) at unit i in year t.

The fuel cost for a unit is calculated as follows:



### . 1 ]] pollutants ofNumber f)i,t,fuelcostt( y(i) [eintensit

ee)j,k,i,t,poltikjee( m, f



### ⋅ ⋅ ⋅ = 

# ∑ ∑

,ee),i,f,m,j,k varprodn(t fc(t,i)

(2.4.7)

where
eintensity(i) is the energy intensity (MMBtu/ton product) for unit i
, fuelcostt(t,i, f) is the cost of fuel f ($/MMBtu) at unit i in year t , and
varprodn(t,i,f,m,j,k,ee) is a production coefficient described in the next section.
Annual water consumption related cost is given by



### 1000/ 2 cos 2 ) H2Ocostt(t

⋅ = 

### (t,i) Oconsumptn Ht(t,i) Oconsumptn H (2.4.8)

With annual water consumption given by2-13 

### ).,( 2 itprodn

(t,i) Oconsumptn H

⋅

= 

### ty(i) H2Ointensi (2.4.9)

where
H2Ocostt(t) is the cost of water ($/1000 gallon) in year t , and
H2Ointensity(i) is the gallons of water needed to produce a ton of product at unit i

. Annual solids discharge related cost is given by


### sw)costt(t, SWdisposal

⋅ = 

### sw) SWgen(t,i (t,i,sw) SWdispcost
, (2.4.10)

With annual solids discharges given by


### ).,( itprodn sw) SWgen(t,i,

⋅

= 

### sw)on(i, SWgenerati (2.4.11)

where
SWdisposalcostt(t,sw) is the cost of disposing of a solid discharge sw in year t , and
SWgeneration(i,sw) is the discharge of a solid sw (tons) in the process of producing a ton of product at unit i

.
Note that SWdisposalcostt(t,sw) value can be positive (disposal cost) or negative (sale price).

Total Annual Cost of Production
Using the above information, the total annual cost of production at unit i in year t is



### . i)varcost(t, st(t,i) plantcapco )dncost(t,i tannualpro +

= (2.4.12)

Annual Cost of Imported Commodity
The cost of imports of commodity at import district id in year t is calculated using the following equation



## ( ) )].,,,( [

, istepsidoitImports st(t,id) timportsco

istepsoi 

# ∑

⋅ + + = d) handling(i (id) InsFreight isteps)id,oi,Iprice(t, (2.4.13)

where
Iprice(t,oi,id,isteps) is the price (value) of importing commodity from origin oi (foreign country) at the import district dc , at the istep th level of the relevant price-import curve.
InsFreight(id) is the insurance and freight at the import district.2-14

handling(id) is the handling cost at the import district.
Total Annual Transportation Cost
The cost of transporting the commodity from unit i and import district id to demand center dc is calculated using



### )].,,( )],,(
dcidtquantity Imported dcitquantity

prodn (t,dc) ttranscost

id i 

# ∑ ∑

⋅ + ⋅ = dc)id,(t,sportcostt [imprttran dc)i,(t,sportcostt

[prodntran

(2.4.14)

where
prodntransportcostt(t,i,dc) is the cost of transporting one ton of commodity ($/ton) from unit i to demand center dc , and
imprttransportcostt(t,id,dc) is the cost of transporting one ton of commodity ($/ton) from imprt district id to demand center dc.


### 2.5 Emissions
As discussed in the previous chapter, emissions can be generated from fuel firing and also from use of raw materials (e.g., CO 2 emissions from calcination of limestone in cement kiln). As such, both of these emission generation pathways are included in ISIS. Further, the ISIS framework includes algorithms to account for tracking multiple pollutant streams associated with uncontrolled emissions, controlled emissions, pollution prevention from process modifications and energy efficiency measures, and any controls-related effects (e.g., generation of CO 2 in a wet SO 2 scrubber). These algorithms are described below.



### k)/100].j,cp(i,[1ee)k,ity(i, modeintens j)f,yfuel(i, emintensit ee)k,j,f,i,polfuel(t,

−⋅ ⋅ = (2.5.1)



### ee).,eHIdispl(i k)Ichange(i, secondaryH k)hange(i, primaryHIc (i)eintensity ee)k,ity(i, modeintens

+ +

+ =

(2.5.2)

where
polfuel(t,i,f,j,k,ee) is emission (tons pollutant per ton product) of pollutant j resulting from processing (firing) fuel f

and application of any control k and/or energy efficiency measure ee at unit i in year t, taking into account whether a unit is available for operation in that year;
emintensityfuel(i,f,j) is the emission intensity (tons pollutant per ton product) of pollutant j resulting from processing (firing) fuel f at unit i, taking in to account whether any controls (e.g., Best Available Control Technology [BACT]) are already installed on the unit;2-15

modeintensity(i,k,ee) is the modified energy intensity (MMBtu per ton product) needed to produce 1 ton of product at unit i . This energy intensity takes into account any heat input changes accompanying a control k and/or an energy efficiency measure ee; eintensity(i) is the energy intensity (MMBtu per ton product) needed to produce 1 ton of product at unit i;
primaryHIchange(i,k) is the change in primary heat input (MMBtu per ton product) due to application of control k at unit i;
secondaryHIchange(i,k) is the change in heat input (MMBtu per ton product) due to any secondary fuel addition resulting from application of control k at unit i;
eHIdispl(i,ee) is the amount of heat input (MMBtu per ton product) displaced (reduced) due to application of energy efficiency measure ee at unit i; and
cp(i,j,k) is the reduction efficiency for pollutant j using control k at unit i

. Similarly,



### k)/100].j,cp(i,[1 k)/100 rcent(i, MTchangepe secondaryR k)/100 ent(i, changeperc primaryRMT 1 j) m, yrmt(i, emintensit ee) k, j, m, i, polrmt(t,



### − ⋅       + + ⋅

=

(2.5.3)

where
polrmt(t,i,m,j,k,ee) is emission (tons pollutant per ton product) of pollutant j resulting from processing raw material m and application of any control k and/or energy efficiency measure ee at unit i in year t, taking into account whether a unit is available for operation in that year;
emintensityrmt(i,m,j) is the emission intensity (tons pollutant per ton product) of pollutant j resulting from processing raw material m at unit i, taking into account whether any controls (e.g., BACT) are already installed on the unit;
primaryRMTchangepercent(i,k) is the percent change in primary raw material input (tons raw material per ton product) due to application of control k at unit i; and
secondaryRMTchangepercent (i,k) is the percent change in raw material input (tons raw material per ton product) due to any secondary raw material addition resulting from application of control k at unit i

. Finally, 

### k).j ,m,i,polrmt(t, ee)k,j,f,i,polfuel(t, ee)k,j,m,f,i,pol(t, +

= (2.5.4)

where2-16

pol(t,i,f,m,j,k,ee) is emission (tons pollutant per ton product) of pollutant j resulting from processing fuel f and raw material m, and application of any control k and/or energy efficiency measure ee, at unit i in year t, taking into account whether a unit is available for operation in that year.
Emissions of pollutant j at unit i in year t are given by



### .),,,,,,( ),,( 

# ∑

⋅ = ee)j,k,i,t,poltikjee( m,f, 

### ee)k,j,m,f,i,pol(t, eekjmfitvarprodn jitemissions (2.5.5)

where
varprodn(t,i,f,m,j,k,ee) is the production variable associated with use of k th control and/or ee th energy efficiency measure for j th pollutant at unit i using fuel f and raw material m in year t;
emissions(t,i,j) are the emissions (tons of pollutant per ton of clinker) of pollutant j at unit i ; and
poltikjee(t,i,k,j,ee) is the mapping described above.

Now total emissions from all units are


### .),,( ),( 

# ∑ =
i 

### jitemissions jtions totalemiss (2.5.6)

where
totalemissions(t,,j) are total emissions (tons of pollutant per ton of clinker) of pollutant j resulting from production activity in the entire sector.
Note that production associated with each pollutant is the same and therefore


### ;);,,,,( ),,,,( jjjjjmfitprodnpol jmfitprodnpol ≠

= (2.5.7)

with,



### .),,,,,,(

),,,,( ),,,,(



# ∑ = eejkitpoltikjee



### eekjmfitvarprodn jmfitprodnpol (2.5.8)

where
prodnpol(t,i,f,m,j,) production variable associated with pollutant j

. 

### 2.6 Controls and Costs
The ISIS framework includes constraints to ensure that endogenous applications of sector-based controls and energy efficiency options occur in a realistic manner. A description of these constraints and costs for2-17

controls is presented in this section. The treatment of energy efficiency measures is described in a subsequent section.

Controls Related Constraints
Only one vintage of a control on a unit is possible for the period starting when the vintage comes on line and ending with its technical life.

.n trols(k)] techlifeco + [(vyear(v) tyear(t) vyear(v) ;1

<≤ ≤ 

# ∑

vt ,v)t,i,kc(poltikts

, )(_

(2.6.1)

where

v is the set of vintages of a control for unit i
, vyear(v) and tyear(t) are parameters with values corresponding to years in the selected time horizon,
ts_c(t,i,k,v) is a binary variable that can bring v th vintage of control k for unit i online in year t, and
techlifecontrols(k) is the technical life of control k.
Control capacity is given by the following equations.

For t = 1,

.ntrols(k)) techlifeco (vyear(v) tyear(t) vyear(v) ;i),capacity(t

,_,

+ <≤ ⋅ = 

## ∑

v v)c(t,i,ktsk)(t,i ControlCap (2.6.2a)

For t > 1,

.ntrols(k)) techlifeco (vyear(v) tyear(t) vyear(v) ;i),capacity(t
,_, ,

+ <≤ ⋅ +

− = 

# ∑

v v)c(t,i,ktsk)itimeblock, (t ControlCap k)(t,i ControlCap (2.6.2b)

In any year, no two incompatible controls can coexist on a unit,


### ),( ),,( ),,( itcapacity

kkit ControlCap kit ControlCap ≤

+ (2.6.2c)

where

k and kk are incompatible controls.
Finally, the production coefficient associated with a control is less than the capacity of the unit the control is installed on,2-18 

### tyear(t). vyear(v) ;i),capacity(t

_ pollutants ofNumber ),,,,(



### ≤ ⋅

≤ 

# ∑ ∑

v eejkitjeef,m,poltik 

### c(t,i,k,v)ts

,ee),i,f,m,j,k varprodn(t

(2.6.3)

where
capacity(t,i) is the capacity of unit i in year t

. In general, the costs associated with controls comprise the following components: (1) capital and fixed operation and maintenance costs, (2) costs associated with any reagent and/or catalyst consumption, (3) costs associated with any reduction in fuel and/or raw material use, (4) cost associated with electricity consumption, (5) cost associated with byproduct(s), and (6) costs associated with water use. The calculations of these costs are described below. Note that various cost elements (e.g., capital cost of a control [$/ton clinker] for the cement sector) are escalated appropriately to use values in years of interest.
Capital Recovery and Fixed Cost
Annual recovery of capital cost of control k is given by



### trols(k)]. ecolifecon [vyear(v) tyear(t) vyear(v) ;(k) CRFcontrol k)i,alcostt(t, cntrlcapit _

+ <≤ ⋅ ⋅ = 

### (t,i,k) ControlCap , i,k)) c(poltik(t capcost

(2.6.4)

Similarly, annual FOM cost is given by



### .ntrols(k)] techlifeco [vyear(v) tyear(t) vyear(v) ;k)i,costt(t,

cntrlfixed ) (_

+ <≤ ⋅ = 

### (t,i,k) ControlCap i,k)poltik(t, c FOMcost

(2.6.5)

where
cntrlcapitalcostt(t,i,k) is the capital cost ($/ton of clinker) of application of control k on i th unit
, cntrlfixedcostt(t,i,k) is the annual fixed operation and maintenance (FOM) cost ($/ton of clinker) of application of control k on i th unit
, capcost_c(t,i,k) is the annualized capital cost ($) of k th control application on i th unit,
FOMcost_c(t,i,k) is the annual fixed operation and maintenance cost ($) of k th control application on i th unit, and
CRFcontrol(k) is the capital recovery factor calculated using an appropriate interest rate and time period, ecolifecontrols(k) , for capital recovery.2-19

Variable Costs
Change in fuel cost associated with application of controls is given by

. ] [

),,,( ),,,(,),(

pollutants ofNumber f)r,t,fuelcostt( k) Ichange(i, secondaryH fr,t,fuelcostt(

k)hange(i, primaryHIc 

# ∑

∑

⋅ ⋅ + ⋅ ⋅ =

j,eekitpoltikjee kf(k,f),m, j,eekitpoltikjee,mfifi ,ee),i,f,m,j,k

varprodn(t ) ,ee),i,f,m,j,k varprodn(t i,r),k)) tirk(t,ri( ange_c(pol fuelcostch

(2.6.6)

where
primaryHIchange(i,k) is the primary heat input change (MMBtu per ton clinker) with use of k th technology,
secondaryHIchange(i,k) is the primary heat input change (MMBtu per ton clinker) with use of k th technology,
fuelcostt(t,r,f) is the regional cost of fuel ($/MMBtu) in year t,
ri(i,r) is a set with elements corresponding to mapping between kiln and their geographic locations, and
kf(k,f) is a set with elements corresponding to mapping between fuels and technologies.
poltirk(t, ri(i,r),k) is a mapping described above.
Change in raw material cost associated with application of controls is given by

. ] 100/ 100/ [

),,,( ),( ),,,( ),(

pollutants ofNumber i)RMTt(t, rcent MTchangepe secondaryR i)RMTt(t, ent changeperc primaryRMT 

# ∑ ∑

⋅ ⋅ + ⋅ ⋅ =

j,eekitee,m,poltikjfifi j,eekitee,m,poltikjfifi ,ee),i,f,m,j,k

varprodn(t ,ee),i,f,m,j,k varprodn(t ,r),k)) irk(t,ri(i nge_c(polt RMTcostcha

(2.6.7)

where
primaryRMTchangepercent is the percent change in primary raw material with use of k th technology,
secondaryRMTchange(i,k) is the percent change raw material input corresponding to any secondary raw material addition with use of k th technology, and
RMTt(t,i) is the unit-specific cost of raw material ($/ton clinker) in year t.2-20

Annual reagent consumption costs are



### rgnt).cet(t, reagentpri



### ⋅ = 

# ∑

rgnt 

### rgntkitcpt rgntconsum kitpoltikcptcost rgntconsum ),,,(_

)),,((_

(2.6.8)

The annual consumption of a reagent given by

. ] [ ),,,(_

),,,,(),(
, ),,,,( ),(

pollutants ofNumber rgnt)j,k,m,, sumptrmt(i reagentcon pollutants

ofNumber rgnt)j,k,f,i, sumptfuel( reagentcon

],ee),i,f,m,j,k varprodn(t [ ,ee),i,f,m,j,k varprodn(t rgnt)kitc(poltikpt rgntconsum

eejkit,poltikjeefifi jm eejkitem,poltikje ,jfifi



# ∑ ∑ ∑ ∑

⋅ + ⋅ =

(2.6.9)

where
reagentconsumptfuel(i,f,k,j,rgnt) is the reagent consumption due to control (tons reagent/tons clinker) associated with fuel-based emission intensity,
reagentconsumptrmt(i,m,k,j,rgnt) is the reagent consumption due to control (tons reagent/tons clinker) associated with raw material-based emission intensity,
reagentpricet(t,rgnt) is the price of reagent rgnt ($/ton of reagent) in year t , and
rgntconsumpt_c(t,i,k,rgnt) is the annual reagent consumption due to control (tons reagent/year).
Catalyst consumption cost is



### ;)

),,,(_

)
, , ( (

_ 

# ∑

⋅ =

cat 

### catkitct catconsump )

k i t poltik c tcost catconsump 

### catice(t, catalystpr (2.6.10)

with2-21 . ),,(_

),,,,( ),( pollutants ofNumber EGFW(i) cat)j,k, nsumpt(i, catalystco 

# ∑ ∑

⋅⋅ =

j eejkitee,m,poltikjfifi ,ee),i,f,m,j,k varprodn(t 10000 ,cat)kitc(poltikt catconsump

(2.6.11)

where
catalystconsumpt(i,k,j,cat) is the catalyst consumption rate (ft 3 catalyst/10000 ft 3 flue gas),
EGFW(i) is the exhaust gas flow rate (scf/ton clinker),
catalystpricet(t,cat) is the price of the catalyst ($/ft 3 ) in year t , catconsumpt_c(t,i,k,cat) is the catalyst consumption rate (ft 3 /year), and
catconsumptcost_c(t,i,k) is the catalyst cost ($/year).
Annual cash flow associated with byproduct generation disposal/sale is



### byprod); ricet(t, byproductp



### ⋅ = 

# ∑
byprod 

### prod)

c(t,i,k,by en byproductg )kitc(poltik ost byproductc

_

),,(_

(2.6.12)

with annual generation of a byproduct given by

.

),,(_

),,,,(),( ),,,,( ),(

pollutants of Number byprod)j,k,m, rodnrmt(i, byproductp pollutants of Number byprod)j,k,f,,rodnfuel(i byproductp

],ee),i,f,m,j,k varprodn(t [ ],ee),i,f,m,j,k varprodn(t [ ,byprod)kitc(poltiken byproductg

eejkit,poltikjeefifi m,j eejkitem,poltikje ,jfifi



# ∑ ∑ ∑ ∑

⋅ + ⋅ =

(2.6.13)

where
byproductprodnfuel(i,f,k,j,byprod) is the byproduct generation due to control (tons reagent/tons clinker) associated with fuel-based emission intensity,
byproductprodnrmt(i,m,k,j,byprod) is the byproduct generation due to control (tons reagent/tons clinker) associated with raw material-based emission intensity,2-22

byproductpricet(t, byprod) is the price of disposing or selling the byproduct byprod ($/ton of reagent) in year t , and
byproductgen_c(t,i,k,byprod) is the annual byproduct generation due to control (tons reagent/year).

Note that byproductpricet value can be positive (disposal cost) or negative (sale price).
Annual electricity consumption (kWh/yr) due to control is

. ] [ ),,( ),( ),,,,(, pollutants ofNumber k)f,i, kWhperton( 

# ∑ ∑

⋅

= fifi eejkitpoltikjeem ,ee),i,f,m,j,k varprodn(t )kitik kwh_c(polt (2.6.14)

The cost of electricity consumption is 

### i).ycostt(t, electricit

⋅ = 

### k)kwh_c(t,i, )kitpoltik kwhcost_c( ),,( (2.6.15)

where
KWhperton(i,f,k) is the electrical requirement (kWh per ton of clinker) for technology k , and
electricitycostt(t,r) is the electricity price ($/kWh) in year t at unit i.
Annual water consumption associated with control k is

. _ 2

),,,,(),( ),,,,( ),(

pollutants

ofNumber k)m,i, H2Ousermt( pollutants

ofNumber k)f,(i, H2Ousefuel

],ee),i,f,m,j,k varprodn(t [ ],ee),i,f,m,j,k varprodn(t [ ,i,k)) c(poltik(t Oconsumpt H

eejkit,poltikjeefifi m,j eejkitem,poltikje ,jfifi



# ∑ ∑ ∑ ∑

⋅ + ⋅ =

(2.6.16)

The cost of water consumption is

.1000/ ) H2Ocostt(t

⋅ = t_c(t,i,k) H2Oconsump ,k)) poltik(t,i H2Ocost_c( (2.6.17)

where
H2Ousefuel(i,f,k) is the water use due to control (tons reagent/tons clinker) associated with fuelbased emission intensity,2-23

H2Ousermt(i,m,k) is the water use due to control (tons reagent/tons clinker) associated with raw material-based emission intensity,
H2Ocostt(t) is the price of water ($/1000 gallons) in year t , and
H2Oconsumpt_c(t,i,k) is the annual water use due to control (gallons/year).

Total Annual Cost
Using the above costs, the total annual cost of controls is



### t,i,k) H2Ocost_c( t,i,k) kWhcost_c( k)ost_c(t,i, byproductc i,k) tcost_c(t, catconsump ,i,k) ptcost_c(t rgntconsum k)nge_c(t,i, RMTcostcha ,k) ange_c(t,i fuelcostch t,i,k)

FOMcost_c( t,i,k) capcost_c(

st(t,i,k) tcontrolco

+ + + + + + + + =

(2.6.18)



### 2.7 Costs of Energy Efficiency Measures
As described below, the treatment of energy efficiency measures in ISIS is similar to that for control.
Energy Efficiency Measures Related Constraints
As for controls, constraints are needed to ensure realistic applications of energy efficiency measures. These constraints are described below.
Only one vintage of an energy efficiency measure on a unit is possible for the period starting when the vintage comes on line and ending with its technical life.



### (ee)]. eetechlife + [(vyear(v) tyear(t) vyear(v) ;1



### <≤ ≤ 

# ∑

vt 

### ,v)t,i,ee ee(poltiee ts

, 

### )(_

(2.7.1)

where

v is the set of vintages of measure ee , poltiee(tpolc(t) is the mapping described before,
vyear(v) and tyear(t) are parameters with values corresponding to years in the selected time horizon,
ts_ee(t,i,ee,v) is a binary variable that can bring v th vintage of measure ee online on unit i in year t, and
eetechlife (ee) is the technical life of measure ee. Energy efficiency measure capacity is given by the following equations.2-24

For t = 1,

e)). techlife(e (vyear(v) tyear(t) vyear(v) ;i),capacity(t ),(

_ ,

ee v)t,i,ee

ee(poltiee tsee) EECap(t,i

v + <≤ ⋅ = 

## ∑ (2.7.2a)

For t > 1,

e)). techlife(e (vyear(v) tyear(t) vyear(v) ;i),capacity(t ),(

_ , ,

ee v)t,i,ee ee(poltiee tsee)itimeblock, EECap(t ee) EECap(t,i

v + <≤ ⋅ +

− = 

# ∑ (2.7.2b)

In any year, no two incompatible measures can coexist on a unit, 

# [ ] 1 ;),,(_),,(_ 

# ∑ ≤ +

v 

### ,v)eeeitee(poltiee ts,v)eeitee(poltiee ts (2.7.2c)

where

ee and eee are incompatible measures.
Finally, production coefficient associated with an energy efficiency measure is less than the capacity of the unit the measure is installed on,



### tyear(t) vyear(v) i);,capacity(t

pollutants ofNumber
≤ ⋅

≤ 

# ∑ ∑

v j,eekijee(t f,m,poltik 

### v)ee(t,i,ee,ts

,ee),i,f,m,j,k varprodn(t

_ ),,,

(2.7.3)

where
capacity(t,i) is the capacity of unit i in year t.
Capital Recovery and Fixed Cost
For an energy efficiency measure ee , annual recovery of capital and annual FOM cost are given by Equations 2.7.4 and 2.7.5, respectively.

ee)]. ecolifeee( [vyear(v) tyear(t) vyear(v) ;CRFee(ee) ee)i,stt(t, ecapitalco _

+ <≤ ⋅ ⋅ = ee) EECap(t,i, (t, i,ee)) ee(poltiee capcost

(2.7.4)2-25 

### (ee)]. eetechlife [vyear(v) tyear(t) vyear(v) ;ee)i,t(t,

efixedcost ) (_

+ <≤ ⋅ = 

### ee) EECap(t,i, i,ee)

poltiee(t,ee FOMcost

(2.7.5)

where
ecapitalcostt(t,i,ee) is the capital cost ($/ton of clinker) of ee th energy efficiency measure application

on i th unit
, efixedcostt(t,i,ee) is the annual fixed operation and maintenance (FOM) cost ($/ton of clinker) of ee th energy efficiency measure application on i th unit
, ts_ee(t,i,ee,v) is a binary variable that can bring v th vintage of measure ee online on unit i in year t , capcost_ee(t,i,ee) is the annualized capital cost ($) of ee application on i th unit, and
FOMcost_ee(t,i,ee) is the annual fixed operation and maintenance cost ($) of ee application on i th unit, and
CRFee(ee) is the capital recovery factor calculated using an appropriate interest rate and time period, ecolifeee(ee) , for capital recovery.

Variable Costs
Change in fuel cost associated with application of ee measures is given by



### pollutants ofNumber fr,t,fuelcostt( ee),eHIdispi(i 

# ∑

⋅

⋅ =

),,,,( 

### _

eejkitjee f,m,poltik 

### )

,ee),i,f,m,j,k varprodn(t

),ee)) e(t,ri(i,r ee(poltire ange fuelcostch

(2.7.6)

where
eHIdispi(i,ee) is the displacement of primary heat input (MMBtu per ton clinker) with use of ee th energy efficiency measure,
fuelcostt(t,r,f) is the regional cost of fuel ($/MMBtu) in year t,
ri(i,r) is a set with elements corresponding to mapping between kiln and their geographic locations, and
poltiree(t, ri(i,r),ee) is a mapping described above.
Annual electricity consumption (kWh/yr) due to an energy efficiency measure is2-26 

### pollutants ofNumber ee)i, kWhperton( 

# ∑

⋅

= ),,,,(,, 

### ),,(_ eejkitpoltikjeemf 

### ,ee),i,f,m,j,k varprodn(t e )eeitee(poltiee kwh (2.7.7)

The cost of electricity consumption is 

### i)ycostt(t, electricit

⋅ = 

### ,ee) kwh_ee(t,i )eeit(poltiee kwhcost_ee ),,( (2.7.8)

where
eKWhperton(i,f,ee) is the electrical requirement (kWh per ton of clinker) for ee, and
electricitycostt(t,i) is the electricity price ($/kWh) in year t at unit i.

Total Annual Cost
Using the above costs, the total annual cost of energy efficiency measures is



### ee(t,i,ee) kWhcost ee(t,i,ee) ange fuelcostch ee(t,i,ee)

FOMcost ee(t,i,ee) capcost ee)scost(t,i, teemeasure

_

_ _ _ + +

+ =

(2.7.9)



### 2.8 Policy Options
ISIS can help design and evaluate a number of emissions reduction policy options including cap-andtrade, emissions taxes, and emissions limits. Additionally, appropriate combinations of these options can also be evaluated. The policy options included in ISIS are described below.
Cap-and-Trade
Under this option, an emissions cap is set on the amount of a pollutant that can be emitted. Sources, companies, or other groups are issued emission permits (allowances) which represent the right to emit a specific amount of the pollutant. Allowances may be banked for use in future. The total amount of allowances available in the current period and those banked in previous periods cannot exceed the cap in the current period. Sources or companies that need to increase their emissions must buy allowances from those who pollute less. The transfer of allowances is referred to as a trade. In effect, the buyer is paying a charge for polluting, while the seller is being rewarded for having reduced emissions by more than was needed. Thus, in theory, those that can easily reduce emissions most cheaply will do so, achieving the pollution reduction at the lowest possible cost to society.
Generally, annual caps have been utilized in ongoing programs (e.g., Title IV SO 2 reduction program). However, ISIS does permit evaluation of potential programs with caps over user-selected time periods (e.g., 5-yearly caps). This evaluation is accomplished using,
),(),( ),( jperiodtbnkjtbnk jtions totalemiss +−+≤

j)ec(t, (2.8.1)2-27

where
ec(t,j) is the emission cap for pollutant j in year t , and
bnk(t+period, j) are the allowances of the pollutant j banked in year t for the year t + period

. Cap-and-Trade with a Minimum Reduction Requirement
While designing a cap-and-trade program, there may be an interest in requiring a minimum level of emission reduction from each affected entity. Such a requirement may be able to help address any local emissions-related concerns. In ISIS, this requirement can be imposed using

j)i,,ecpminer(t j)i,t, emissions( ≤ (2.8.2)

where
ecpminer(t,i,j) is the unit-specific minimum emission reduction requirement for pollutant j in year t

.
Emissions Limits
ISIS permits evaluation of the costs and emissions reductions associated with more traditional emission reduction programs utilizing unit-specific rate-based emission limits. Such requirements are imposed using
),(

),,( itprodn jitemissions ⋅≤

j)el(t, (2.8.3)

where
el(t,j) is the rate-based emission limit for pollutant j in year t and every affected unit complies with this limit.
Allowance Price Inputs
In some cases, there may be an interest in endogenously determining the level of emission reduction corresponding to a certain allowance price. This information may be useful, for example, in a situation where an allowance price is set for reducing emissions from many industrial sectors. In such a case the levels of emission reductions corresponding to the same allowance price may be different for the sectors under consideration. The emissions response to a given allowance price is driven by the following term in the objective function (see section 2.1),

),( )(

, jtions

totalemiss tdis jt 

# ∑

⋅ ⋅ j)alprice(t, (2.8.4)

where
alprice(t,j) is the exogenous allowance price of pollutant j in year t

.2-28

Note that the allowance price inputs scheme above is equivalent to emission-tax-based programs in which affected units or companies pay a tax for every unit of pollution they produce. Thus this scheme can also be used to evaluate such programs.


### 2.9 Optimization and Post-Processing
In ISIS, the input data are pre-processed to arrive at suitable input parameters for use in the model equations explained in this chapter. Once the data have been pre-processed, ISIS solves for the appropriate levels of production, imports and controls required to meet the constraints associated with commodity demand and emissions, while maximizing total surplus. Once the surplus maximization problem has been solved, the results are post-processed to obtain parameters and level values of the variables of interest. The key variables of interest are: production level of each production unit to meet regional demand, level of imports in each region, installation of various controls, emissions, and various costs. Output data are written in appropriate worksheets in an Excel workbook and further linked to various plots to enable visual presentation and analyses of the results.2-29



### References for Chapter 2
Duloy, J. H.; Norton, R.D. (1975). Prices and incomes in linear programming models. American Journal of Agricultural Economics . 57(4): 591.600.
Enke, S. (1951). Equilibrium among spatially separated markets: solution by electric analogue. Econometrica . 19: 40.47.
FPL-PELPS, A price endogenous linear programming system for economic modeling, supplement to PELPS III, version 1.1, USDA Research paper FPL-RP-614, 2003.
McCarl, B.A.; Spreen, T.H. (1980). Price endogenous mathematical programming as a tool for sector analysis. American Journal of Agricultural Economics . 62: 87.102.
Samuelson, P.A. (1952). Spatial price equilibrium and linear programming. American Economic Review

. 42(3): 283.303.
Samuelson, P.A.; and W. Nordhaus. (1977). Economics (17th edition) , John Wiley.3-1 

## Chapter 3 Cement Data

3.1 Data Requirements
Data requirements for ISIS include sector-specific (in this case, cement-specific) data as well as policy and economic parameters. The cement-specific data requirements are discussed below.


### 3.2 Cement-Specific Data
The inputs to the ISIS model for the cement industry can be broadly categorized into three main components:

• Industry production, fuel, and emissions

• Control technologies, and emission abatement approaches

• Policy and economic parameters



### 3.2.1 Industry, Fuel, and Emissions

3.2.1.1 Existing, Planned/Committed, and Potential Units
The ISIS cement industry model contains information on 189 cement kilns that were in existence in 2009 and PCA’s projected capacity expansions from 2009 to 2012, as shown in Table 3-1 (PCA, 2009a). Additionally, the model also includes potential kiln representations that may come on line as a result of endogenous capacity addition (i.e., new production capacity [by state] and replacements [by kilns]).
Table 3-1. Summary of Kilns Modeled in the ISIS Cement Industry Model

Kiln Population Number of Kilns Existing (2009) 189 PCA’s Projected New Kilns (2009 – 2012) 17

Each kiln modeled in ISIS is characterized by its location, design (i.e., wet, dry, preheater, or precalciner), daily and annual clinker capacity 3 , vintage, and retirement information when available (PCA, 2006). In addition, each kiln is characterized by its average variable costs components (AVC).

3 Annual clinker capacity as reported by PCA refers to the kiln daily capacity multiplied by 365 less normal downtime days, where daily capacity is the normal clinker output a kiln can produce per day given a realistic work pattern and normal downtime days are number of days of downtime required for maintenance, repair or cleanup.3-2

3.2.1.2 Average Variable Costs
In previous economic analyses, five input variables in cement production have been identified to determine the kiln-level AVC functions: raw materials, repair and maintenance, labor, electricity, and fuel (Depro et al., 2007; Depro, 2010; Depro and Lentz, 2010). Raw materials serve as the kiln feed, and repair and maintenance are required for periodic upkeep of the kiln. Labor is used in the quarry, in the operation of the kiln, and for packing. Electricity is consumed mainly by the auxiliary equipment and fuel is largely consumed in the kilns. The AVC for raw materials, labor, repair and maintenance, and electricity was determined following the methodology in the EPA regulatory impact analysis of the cement kiln dust rulemaking (EPA, 1998).

3.2.1.3 Cement Demand Centers
The U.S. cement markets are organized in state-specific demand centers. Figure 3-1 shows the distribution of portland cement kilns operating in 2009. Each state containing at least one kiln is shaded. The ISIS-cement model simulates each cement plant’s ability to compete in each of the demand centers as a function of the plant’s production cost and transportation cost associated with supply to each demand center.

3.2.1.4 Portland Cement Demand
One of the key data inputs for the ISIS-cement model is the demand projection for each demand center. In general, this demand is a function of gross domestic product (GDP) growth, interest rates, special construction projects (e.g., highways), and public sector construction spending. Portland cement demand was 128 million metric tons in 2005. PCA expects cement demand will reach 192 million metric tons by 2035, which reflects an increase of nearly 64 million metric tons with a compound annual growth rate of 1.4 percent. Cement demand through year 2035 is reported in the PCA Long-Term Cement Consumption Outlook (PCA, 2009b). PCA projections of cement demand (in million metric tons) by state for 2005 through 2035, in 5-year increments, are shown in Table 3-2.3-3

Figure 3-1. Distribution of Cement Kilns in the United States as of 20093-4

Table 3-2. Portland Cement Demand in Millions of Metric Tons

State Demand Center 2005 2010 2015 2020 2025 2030 2035
Alabama 1.92 1.45 2.02 2.16 2.32 2.49 2.67
Arizona 4.77 2.21 3.85 5.16 6.55 7.95 9.59
Arkansas 1.30 0.93 1.29 1.41 1.54 1.67 1.81
California 16.01 8.33 13.88 15.43 17.11 18.95 20.96
Colorado 2.55 1.74 2.76 3.08 3.47 3.90 4.33
Connecticut 0.82 0.54 0.77 0.83 0.88 0.94 0.98
Delaware 0.22 0.18 0.26 0.28 0.29 0.31 0.32
District of Columbia 0.21 0.15 0.18 0.18 0.17 0.18 0.18
Florida 12.28 4.77 8.99 11.05 13.47 16.33 19.67 Georgia 4.75 2.52 3.95 4.96 5.67 6.17 6.65
Hawaii 0.44 0.35 0.47 0.49 0.52 0.55 0.57
Idaho 0.70 0.44 0.70 0.82 0.92 1.03 1.15
Illinois 4.64 3.10 4.29 4.62 4.99 5.44 5.98
Indiana 2.27 1.69 2.30 2.49 2.73 2.98 3.25
Iowa 1.94 1.59 1.98 2.04 2.10 2.15 2.20
Kansas 1.55 1.36 1.65 1.71 1.78 1.85 1.91 Kentucky 1.60 1.06 1.48 1.59 1.71 1.84 1.97
Louisiana 2.23 2.44 2.91 3.15 3.29 3.42 3.52
Maine 0.35 0.20 0.29 0.31 0.32 0.34 0.35 Maryland 1.66 1.12 1.63 1.78 1.94 2.12 2.31
Massachusetts 1.26 0.81 1.11 1.21 1.31 1.43 1.56 Michigan 3.06 1.54 2.05 2.19 2.44 2.68 2.75
Minnesota 2.06 1.29 1.86 2.09 2.34 2.57 2.80 Mississippi 1.14 1.07 1.50 1.58 1.66 1.76 1.85
Missouri 2.87 2.03 2.71 3.18 3.58 3.90 4.29
Montana 0.38 0.30 0.42 0.45 0.48 0.51 0.53
Nebraska 1.37 1.14 1.46 1.55 1.66 1.76 1.87
Nevada 2.63 1.20 2.33 3.26 4.27 5.14 6.16 New Hampshire 0.37 0.23 0.33 0.36 0.39 0.42 0.45 New Jersey 2.06 1.45 1.89 1.99 2.09 2.18 2.28
New Mexico 0.91 0.65 0.94 1.00 1.07 1.12 1.15
New York 3.29 2.84 3.60 3.73 3.87 3.98 4.083-5

State Demand Center 2005 2010 2015 2020 2025 2030 2035
North Carolina 3.25 2.16 3.43 3.92 4.50 5.16 5.88
North Dakota 0.36 0.39 0.47 0.47 0.46 0.44 0.42
Ohio 4.06 2.59 3.61 3.75 3.90 4.02 4.12
Oklahoma 1.67 1.57 1.68 1.76 1.87 1.98 2.11 Oregon 1.24 0.83 1.22 1.40 1.61 1.86 2.15 Pennsylvania 3.44 2.61 3.49 3.64 3.78 3.89 3.97
Rhode Island 0.19 0.12 0.17 0.18 0.19 0.19 0.20
South Carolina 1.94 1.07 1.81 1.99 2.19 2.38 2.56
South Dakota 0.48 0.44 0.55 0.57 0.61 0.64 0.67
Tennessee 2.52 1.54 2.38 2.61 2.89 3.19 3.53
Texas 15.09 12.11 17.51 21.03 24.10 27.48 30.58
Utah 1.53 1.22 1.82 2.08 2.40 2.78 3.23
Vermont 0.16 0.11 0.16 0.17 0.18 0.20 0.21 Virginia 2.87 1.87 2.84 3.13 3.45 3.80 4.17 Washington 2.24 1.68 2.50 2.75 3.04 3.36 3.73 West Virginia 0.54 0.47 0.59 0.60 0.60 0.59 0.58
Wisconsin 2.37 1.59 2.18 2.32 2.45 2.59 2.74 Wyoming 0.47 0.43 0.55 0.55 0.55 0.55 0.54
Total 128.03 83.54 122.81 139.06 155.70 173.14 191.51

3.2.1.5 Transportation-Interregional Trade
In ISIS-cement, a transportation matrix is used to describe the costs for transporting cement from kiln and import district locations to demand centers. To develop these costs, information on distances between supply and demand points and costs of transportation modes (truck, rail, or water transport) was obtained. In particular, the Transportation Routing Analysis GIS (TRAGIS) model (TRAGIS, 2003) was used to develop the origin-destination distances as described below. Also, in the matrix, the applicable lowest cost transportation option is used to connect a supply point with a destination. While the cement demand centers are interlinked through a transportation matrix, the competition is generally maintained on a regional level because the cost of transporting cement is relatively high.
As mentioned above, the TRAGIS model was used to calculate transportation distances associated with delivery of portland cement from domestic U.S. manufacturing sites and import terminals to each of the demand centers. Operation of the TRAGIS program requires the identification of a shipment’s origin anddestinations, as well as the selection of mode of transportation (highway, rail, or water) for each origindestination pair. The TRAGIS program does not use actual addresses or coordinates as origins or destinations. Instead, the program uses a fixed set of pre-determined locations within the model corresponding to locations in a number of U.S. cities and towns. The locations of domestic portland cement manufacturers used correspond to the lists of manufacturing plants published in the Cement3-6

Americas (Penton Media Inc.), 2009; North American Cement Directory (2008) (Cement Americas 2008); and the Portland Cement Association, U.S. and Canadian Portland Cement Industry Plant Information Summary December 31, 2006 (2007).
The cost of transportation for interregional trade takes into account the impact of terminals and the frequent use of modes other than truck. According to the USGS (2007a), nearly half of cement shipments reach customers via terminals rather than direct. Shipments to terminals are more than 80 percent by rail or water, rather than by truck. Table 3-3 provides information on cost per ton mile for bulk shipping via truck, rail, and barge. In ISIS-cement, transportation costs for each mode of transportation (truck, rail,and barge) are calculated from each kiln and import district to each demand center. For a given origindestination pair, the dominant mode (lowest cost of shipment) is used to determine the transportation cost for that route. The TRAGIS model was used to arrive at the origin-destination distances and feasible routes for rail and barge; Google Maps was used for truck transportation. The shipment costs shown in Table 3-3 were used to determine the transportation costs for the routes in ISIS.
Table 3-3. Bulk Shipment Costs (Cents per Metric Ton per Mile)

Journal of Transport Geography Report, 2005 N&S American Cement, 2004 Mode BTS 1 WDOT 2 NACT 3 American University, 1994 Averages Used

in Model

Truck 33.06 7.64 11.02 7.18 14.73
Rail 2.78 3.32 5.51 N/A 3.87 Barge 0.89 1.05 2.20 N/A 1.38 1. (Bureau of Transportation Statistics) General Bulk Transportation "...can only be considered the upper boundary of transport costs for each mode assuming each industry is operating at-cost or at a profit". 2. (Washington State Department of Transportation) Cost study to examine options for the transport of wheat (Jessup and Casavant, 1998). 3. (North American Cement Transportation) Report covers cement-specific transportation costs, assumes short tons--converted to metric.

3.2.1.6 Imports
U.S. cement markets receive imported quantities of cement and clinker from a number of countries, and these imports arrive at more than 30 import districts (USGS, 2007b). In ISIS-cement, international supplies from exporting countries to U.S. import districts are modeled using a supply elasticity and then these imports are transported to the demand centers.
The five largest international suppliers of cement and clinker to the U.S. are China, Thailand, Venezuela, South Korea, and Greece. An econometric study was conducted to provide an estimate of international supply elasticity for supplies from these countries and the rest of the world. The results of this study (Burtraw, 2010) reflected that the best estimate of the international supply elasticity of cement and clinker from China, Thailand, Venezuela, South Korea, Greece, and the rest of the world into the U.S. is 3.94. This value indicates that if the price of cement were to increase by 1 percent within any import district in the U.S., then, ceteris paribus , the quantity of cement imported from each of these five supply countries into that district would increase by 3.94 percent.
Table 3-4 shows the import levels by USGS Customs District, then state, for 2005, estimated by using USGS data (USGS, 2007b).3-7

Table 3-4. Portland Cement and Clinker Imports in Million Metric Tons, by Customs District in

2005

USGS Customs District Quantity, million metric tons Alabama, Mobile 0.51 Alaska, Anchorage 0.14 Arizona, Nogales; Mexico 1.07 California, Los Angeles 3.05 California, San Diego 0.72 California, San Francisco 2.36 Florida, Miami 2.27 Florida, Tampa 3.48 Georgia, Savannah 0.08 Hawaii, Honolulu 0.43 Illinois, Chicago 0.01 Louisiana, New Orleans a 1.75 Louisiana, New Orleans a 2.43 Maine, Portland 0.16 Maryland, Baltimore 0.13 Massachusetts, Boston 0.13 Michigan, Detroit 1.32 Minnesota, Minneapolis; Canada 0.04 Minnesota, Duluth; Canada 0.16 Missouri, St. Louis 0.01 Montana, Great Falls 0.06 New York, Buffalo 0.82 New York, New York 1.26 New York, Ogdensburg 0.33 North Carolina, Wilmington 0.39 North Dakota, Pembina; Canada 0.18 Ohio, Cleveland 0.79 Oregon, Columbia-Snake 0.87 Pennsylvania, Philadelphia 0.49 Rhode Island, Providence 0.74 South Carolina, Charleston 1.13-8

USGS Customs District Quantity, million metric tons Texas, El Paso; Mexico 0.72 Texas, Houston-Galveston 2.61 Texas, Laredo; Mexico 0.14 U.S. Virgin Islands 0.06 Vermont, St. Albans; Canada 0.13 Virginia, Norfolk 0.7 Washington, Seattle 1.49 Wisconsin, Milwaukee; Canada 0.19

Total 33.33

a Imports for New Orleans are distributed between Birmingham and Dallas markets using baseline domestic production levels. Source: USGS, 2007b. Data do not include Puerto Rico

3.2.1.7 Capacity Changes
Cement plants have a relatively long lifespan, typically 50 years or more (FLSmidth, 2007). Various factors, including (but not limited to) raw material availability in the quarry, technology changes, productivity, efficiency, longevity, reliability, maintenance, and long-term costs can affect the lifespan of a cement kiln/plant. In ISIS-cement, retirements from 2002 to 2009 and projected retirements after 2009 of existing kilns were based on information from PCA on capacity expansion estimates. These estimates were supplemented with information from individual cement companies on their plans for shut-downs, new construction, and kiln consolidation (PCA, 2004). Further, as mentioned earlier, ISIS-cement includes algorithms for endogenous capacity growth and retirement of kilns. To determine capital recovery factor for capital costs associated with kiln capacity changes, an economic life of 25 years and an interest rate of 15 percent are used. Capital costs in 2005 $ per short ton of clinker for new, replacement of wet, and replacement of dry capacity are 208, 296, and 238, respectively (PCA, 2009b).

3.2.1.8 Fuel Intensity
The Annual Energy Outlook energy use profile for 2005 (EIA, 2008) is shown in Figure 3-2. In 2005, the cement sector consumed 451.2 trillion Btu (476.0 trillion kJ) of energy (EIA, 2008). As shown in Figure 3-2, the primary fuel being burned in kilns is coal. Coal is projected to remain the dominant fuel used by the U.S. cement industry. However, there has been an increasing trend towards using other fuels, particularly alternative fuels, such as coke, 4 waste tires, and other wastes, especially oily wastes.

4 PCA does not specify if “coke” is metallurgical coke or petroleum coke. Authors believe it is the latter.3-9 3.72%

0.76% 64.11% 1 9.30%
3.20% 0 .50%

8.40% Natural Gas

Fuel Oil Coal Petroleum Coke
Tires Other Solid Wastes Liquid Wastes

Figure 3-2. Commercial Fuel Use Profile by U.S. Cement Industry in 2005. Source: EIA, 2008

In the ISIS-cement model, to determine the fuel intensity of each kiln, correlations of kiln type to heat input and/or gas flow were developed (see Appendix A). Once determined, the kiln’s specific fuel intensity is used to calculate fuel cost for each kiln. PCA’s data on heat input to various kilns by type were used to develop kilns’ fuel intensities. The data, expressed in heat input per unit of clinker (specific fuel consumption [SFC]) and exhaust gas flow rate (wet) (EGFW) per unit of clinker, are summarized in Table 3-5.
Table 3-5. Specific Fuel Consumption and Total Exhaust Gas Flow Rate (wet) for Various Kiln

Types

SFC a EGFW b Kiln Type MMBtu/ton a Nm 3

/kg SCF/ton c
Wet 6.0 3.4 108,990 Dry 4.5 1.8 57,701
Preheater 3.8 1.5 48,084
Preheater/Precalciner 3.3 1.4 44,878 a. SFC=specific fuel consumption; (Source: EPA, 2007 (Table 3-3) b. EGFW=exhaust gas flow rate (wet): (Source: PCA, 2004; original data in metric units) c. short ton

For each individual kiln, the ISIS model determines the optimal fuel type(s) based on the regional cost of the chosen fuel and the kiln’s specific fuel intensity.

3.2.1.9 Emission Intensities
The design of the ISIS Model can accommodate any number of pollutants of interest. In ISIS-cement, each kiln is characterized by its NO X , SO 2 , PM, hydrochloric acid (HCl), mercury, total hydrocarbon3-10

(THC), and CO 2 emission intensities. These emission intensities were developed using available data (Andover Technology Partners, 2009a).

NO X emissions from cement kilns result primarily from the following combustion process: oxidation of fuel nitrogen (fuel NO X ) and the oxidation of nitrogen in the combustion air (thermal NO X ). Oxidation of nitrogen in the feed materials (feed NO X ) can also influence total NO X emissions. Table 3-6 shows NO X emission intensities for cement kilns in lb/ton of clinker and in lb/MMBtu (EPA, 2007).

Table 3-6. Estimated Uncontrolled NO X Emission Intensities for Cement Kilns

Uncontrolled NO X Emissions Kiln Type Heat Input,

MMBtu/ton of clinker lb/ton of clinker * lb/MMBtu

Wet 6.0 9.7 1.62 Long Dry 4.5 8.6 1.91
Preheater 3.8 5.9 1.55
Preheater/Precalciner 3.3 3.8 1.15 * Average Source: EPA, 2007 (Table 3-3 and Table 6-1)

SO 2 emissions from cement kilns are the product of sulfur in the fuel as well as sulfur in the feed materials. Sulfur in the fuel will oxidize to SO 2 during pyroprocessing, and a significant amount is likely to be captured in the form of sulfates as the gas passes through the calcination zone. Compared to longdry and wet kilns, preheater and preheater/precalciner kilns tend to be more effective at capturing fuelgenerated SO 2 . Accordingly, oxidation of sulfur in the feed materials is likely to be a major component of total SO 2 emissions. Table 3-7 shows average SO 2 emissions for each kiln type for each state (Andover Technology Partners, 2009a). State-specific emission intensities of SO 2 were determined from emissionsreported for the kilns in that state. For any state where the emission intensity was not available for a kilntype, the national average emission intensity was assigned to kilns in that state.

CO 2 emissions from cement kilns result from limestone calcination and fuel combustion. Appendix A explains how CO 2 emission intensities from calcination and combustion are calculated in the ISIS model. Calcination releases 0.52 tons of CO 2 per ton of clinker produced, while fuel-based CO 2 emission factors range from 199.52 lb CO 2 /MMBtu for coal to 105.02 lb CO 2 /MMBtu for natural gas (Andover Technology Partners, 2009b, 2010a, and 2010b). Table 3-8 shows approximate CO 2 and H 2 O produced from combustion for the most important fuels for cement kilns.3-11

Table 3-7. Average SO 2 Emissions for Each Kiln Type in Each State

SO 2 (lb/ton clinker) State Precalciner Preheater Dry Wet
AL 0.09 0.61 9.02 13.99
AZ 1.30 0.07 8.51 7.81
AR 2.94 2.32 3.45 7.59
CA 0.33 1.12 0.81 0.00
CO 0.32 0.10 1.07 4.24
CT 1.15 2.32 9.02 7.81
DE 1.15 2.32 9.02 7.81
FL 0.45 0.02 9.02 7.81
GA 0.95 2.73 11.42 12.25
ID 0.13 2.32 9.02 0.70
IL 5.58 5.77 5.88 9.50
IN 1.15 2.32 9.02 7.81
IA 1.15 2.32 9.02 7.81
KS 1.25 5.88 24.85 8.61
KY 0.19 5.04 12.53 7.81
LA 1.15 2.32 9.03 7.81
ME 0.30 0.30 N/A 11.98
MD 3.14 3.95 7.31 7.49
MA 1.15 2.32 9.03 7.81
MI 5.23 2.32 5.31 18.00
MN 1.15 2.32 9.03 7.81
MS 0.09 0.61 9.02 13.99
MO 2.18 2.32 1.51 7.02
MT 0.13 2.32 9.02 0.70
NE 1.25 5.88 24.85 8.61
NV 0.49 0.05 1.51 7.81
NH 1.15 2.32 9.02 7.81
NJ 1.15 2.32 9.02 7.81
NM 1.30 0.07 8.51 7.81
NY 0.30 0.30 9.02 11.98
NC 1.15 2.32 9.02 7.813-12 SO 2 (lb/ton clinker) State Precalciner Preheater Dry Wet
ND 1.15 2.32 9.02 7.81
OH 0.19 5.04 12.53 7.81
OK 1.25 5.88 24.85 8.61
OR 0.13 2.32 9.02 0.70
PA 1.15 2.32 9.02 7.81
RI 1.15 2.32 9.02 7.81
SC 0.95 2.73 11.42 12.25
SD 0.32 0.10 1.07 4.24
TN 0.95 2.73 11.42 12.25
TX 1.15 2.32 9.02 7.81
UT 0.13 2.32 9.02 0.70
VT 1.15 2.32 9.02 7.81
VA 0.95 2.73 11.42 12.25
WA 0.53 2.32 9.02 3.80
WV 3.14 3.95 7.31 7.49
WI 1.15 2.32 9.02 7.81
WY 0.32 0.10 1.07 4.24 National Average 1.15 2.32 9.02 7.81
N/A Not available.

Table 3-8. Approximate CO 2 and H 2 O Produced from Combustion of Fuels

Variable Name Flue Gas Tires Petroleum Cokes Heavy

Fuel Oil Rosemont

PRB a Logan,

WV BIT b Natural

Gas

LBMCO2MMBTU lbmoles

CO 2 /MMBtu 4.26 4.83 3.85 4.25 4.53 2.39

LBCO2MMBTU lb CO 2 /MMBtu 187.44 212.56 169.32 186.83 199.52 105.02

LBMH2OMMBTU lbmoles

H 2 O/MMBtu 2.76 2.76 2.23 3.23 4.14 2.77

LBH2OMMBTU lbs H 2 O/MMBtu 49.71 49.73 40.26 58.21 74.64 49.92
a. PRB = Powder River Basin coal b. WV BIT = West Virginia bituminous coal3-13



### 3.2.2 Control Technologies and Emission Abatement Approaches
ISIS-cement contains information on abatement approaches for NO X , SO 2 , PM, HCl, mercury, THC, and CO 2 emissions described above. The three categories of abatement approaches included are: process modifications and upgrades, raw material and/or fuel substitution, and mitigation technologies. For each emission abatement approach, where possible, information on the following parameters was developed (Andover Technology Partners, 2009b and 2009c) and included in the model: capital cost, fixed operating cost, variable operating cost, emission reduction performance for all of the pollutants, impacts on fuel and/or raw material use, impact on electricity consumption, byproduct generation and cost, and impact on water use.
To estimate capital recovery factors for capital costs associated with control technologies, economic life values of 15 and an interest rate of 7 percent are generally used, but different values can be selected by the user. Payback periods and technical life for the energy efficiency measures shown in Tables 3-14 through 3-17 are given in Worrell and Galitsky (2004). Economic life for each of these measures can be taken to be the average of the technical life and the payback period. Again, an interest rate of 7 percent can be used for capital recovery in the absence of more specific information.
Tables 3-9 through 3-12 show the NO X , SO 2, CO 2 , HCl, Hg, THC emissions control technologies being used in the ISIS-cement model. Tables also reflect the impacts of these technologies on pollution reduction, electricity use, and water use. Multimedia impacts of changes to the capacity of cement kilns are listed in Table 3-13. Tables 3-14 through 3-17 show the electricity consumption and heat input changes accomplished as a result of implementation of energy efficiency measures for Raw Materials Preparation, Clinker Making, Finish Grinding, and Plant-Wide Measures, respectively.
More details on cost, efficiency, and co-impacts for each of the above control technologies or process modifications are given in Appendix A.



### 3.2.3 Policy and Economic Parameters

3.2.3.1 Policy Parameters
The ISIS model framework allows the user to select a variety of potential policy options for evaluation. The user can select from cap-and-trade policy (with or without de minimis requirements), emissions charge policy, or rate-based policies. In a cap-and-trade policy scenario, separate caps on pollutants of interest can be specified. The user has the option to run a cap-and-trade policy scenario with or without banking of emissions. Further, a cap-and-trade policy scenario can include de minimis requirements, where the user defines a minimum level of emission reduction required for each emission unit. As mentioned before, it is also possible for the user to input an emission charge for pollutants of interest. Furthermore, traditional policy scenarios (rate-based policies) with unit specific emission reduction requirements specified by the user can be modeled in ISIS.
The user can specify the policy horizon (time period) to be used for the model runs. Since climate-related simulation horizons can be long (e.g., 40 years), the user may choose to run ISIS with blocks of years (e.g., 5-year blocks). The simulation horizon and blocks of years can be chosen by the user subject to availability of data.

3.2.3.2 Additional Economic Parameters
In the ISIS framework, the following additional economic parameters are used: discount rate, escalation rates, and demand elasticity. For the ISIS-cement model, the default discount rate has been chosen as3-14

7-percent, as recommended by the U.S. Office of Management and Budget (OMB) for project evaluation (OMB, 1992). Escalation rates used can be found in the “ISIS_Inputs.xls” workbook. Escalation rates for labor are based on historical data from Bureau of Labor and Statistics (BLS). Raw materials escalation factors are calculated from historical price data of crushed sandstone and gypsum from USGS. The escalation factors for variable operating and maintenance costs are based on Chemical Engineering Index. Escalation factors for various fuels and electricity are estimated based on data from the EIA’s Annual Energy Outlook 2008 (RTI, 2010). Demand for cement is relatively inelastic and an elasticity value of - 0.88 is used in the model (EPA, 1998).3-15Table 3-9. NOXControl Technologies for Cement KilnsImpact on Emissions,±% changeElectricity Consumption,kWh/ton of cementControl TypeNOXSO2PM Hg Other GrindingKiln OperationWaterConsumption,gal/ton ofcementLow NOXBurners –Indirect Firing-20% to -30%1No impact203-1.2403Mid KilnFiring-Tires-20% to -40%1May vary5030603Low NOXBurner + MidKiln Firing- Tires-20% to -40%1May vary503-1.24,603Low NOXBurners + TireDerived Fuel-20% to -40%7May vary503-1.24,603Low NOXBurner +Selective Non CatalyticReduction-50%2No data5No data8No data8Nodata80-1.24,9+1.259Low NOXBurner +Selective CatalyticReduction-90%2Oxidation10No data8Oxidation10Nodata80-1.24,9+1.259Low NOXBurners +CemStara-30%11-1.3 (wetprocess);-1.9 (dryprocess)12-1.24,12from LNBand-1.5 (wet process)or-2.2 (dry process)from CemStar130CemStar/Fly Ash Injection-20%14-1.3 (wetprocess);-1.9 (dryprocess)13-1.5 (wet process)or-2.2 (dry process)from CemStar130Notes to Table 3-9 on following pages3-161.See EPA (2004), Table 5-1.2.See Andover Technology Partners 2009b memo.3.These technologies do not use and do not affect the consumption of water in raw mix preparation or significantly affect electric powerconsumption in cement manufacturing processes.4.Conversion from direct firing systems typical of wet and dry process kilns and older preheater kilns to indirect firing systems, required toimplement low NOXburner (LNB) technology, could result in reductions in primary air fan and kiln-induced draft fan power requirements andconcomitant slight increases in coal conveying power requirements. A reduction in fan/blower power on the order of 100 hp might beanticipated for a moderately sized (300,000 – 500,000 clinker tons per year) kiln converted from direct firing to indirect firing. No powersavings on adding an LNB would be anticipated if the kiln system is already indirect-fired.5.SO2emissions from cement kilns are strongly related to fuel and raw materials sulfur content and to method of kiln operation. Sulfur contentof TDF (typically, 1.24% by weight, dry) may be higher or lower than the sulfur content of other fuels commonly used in cement kilns, suchas coal or coke. Therefore it is not practical to relate SO2emissions to the use of these NOXcontrol methods. With respect to use of an SO2wet scrubber using ground limestone, it is assumed that, for wet process kiln systems, uncontrolled SO2emissions of 8.2 lb per ton of clinker(8.9 lb/ton of cement) (EPA, 1995: Table 11.6-8) are treated by use of a stoichiometric amount (with respect to uncontrolled SO2) of limestoneof 90-percent purity in a 15-percent limestone slurry. Limestone and water consumption are 15.5 lb and 87.7 lb, respectively, per ton ofcement produced. For a precalciner kiln, it is assumed that uncontrolled SO2emissions of 1.1 lb per ton of clinker (1.2 lb/ton of cement) (EPA,1995: Table 11.6-8) are treated similarly (stoichiometric amount limestone of 90% purity in a 15% limestone slurry). Limestone and waterconsumption are 2.1 lb and 11.8 lb per ton of cement produced.6.Kiln system and raw materials grinding electric power consumption would not be significantly affected by introduction of tires or tire-derivedfuel.7.Combined effect will vary. Low NOX20 to 40 percent, MKF 20 to 40 percent.8.While there may be theoretical or limited experimental bases to assume increases or decreases in emissions of various pollutants in connectionwith NOXemission controls, statistics on such effects are not available. See, generally, EPA (2007a), Chapter 11.9.Assumes SNCR or SCR both with stoichiometric addition of NH3in 20-percent solution, typical precalciner NOXemissions of 4.2 lb/tonclinker before treatment (EPA 1995, Table 11.6-8), and 0.92 tons of clinker being used in each ton of cement. It should also be noted thatSNCR is not applicable to wet process, long dry process, and many preheater kilns because the kiln gas exit temperatures are too low fromthose units for the necessary reactions to take place. See EPA (2007a). SNCR is assumed to achieve 63-percent reduction in NOXemissionsfrom applicable kiln systems. See EPA (2007a), Chapter 8. There may be an attendant small increase in kiln system electric power inconnection with injection of water into the kiln system due to an increase in gas volume handled by the kiln’s fan system. The increase is notconsidered in the calculation.10.Typically, up to about 1 percent of SO2can be oxidized to SO3.Elemental form of Hg oxidized across SCR provided there is sufficientconcentration of halogens in flue gas.11.On a lb/ton of clinker basis.12.Use of the CemStar process may have multiple effects on electric power consumption, including reduced raw mix preparation costs in theevent that unground CemStar material is fed to the rotary kiln, and reduced fan power requirements resulting from reduced kiln gas volumes in3-17connection with both combustion gases and raw mix calcination. Assuming a 5-percent replacement of raw mix with carbonate-free CemStarmaterial, a concomitant 5-percent reduction in raw mix preparation energy is also assumed. An approximate 5-percent reduction in kilnelectrical energy consumption is assumed based on a roughly 5-percent reduction in kiln exit gases from both calcination and combustion.13.CemStar and fly ash injection are expected to have similar effects on raw mix preparation and kiln process electrical energy requirements.14.See NESCAUM (2000) for effect of CemStar on NOXreductions from cement kilns. Investigation of the combined effects of multipletechnologies on pollutant emissions was not carried out for this summary.General NotesA. Cement kiln processes do not use steam.B. Cement kiln dust (CKD) disposal rates as functions of NOXor SO2emissions control technology has not been reported. Typical CKD disposalrates range from 0.042 to 0.115 tons CKD/ton clinker (0.046 to 0.125 tons CKD/ton cement assuming 0.92 tons clinker per ton of cement).C. CKD disposal costs vary widely by region, CKD characteristics, CKD volumes, and location of disposal site (on-site or off-site). In addition,disposal costs are expected to be of comparable cost to transportation costs in connection with off-site disposal. For example, prices at threenorthern California landfills range from $26/short ton to $69/short ton of CKD plus transportation, which may range from approximately $500to $1,200 per truck load. Pers. Comm., E. Leamer (ARCADIS) Feb. 26, 2009. CKD disposal prices would be expected to be generallyunaffected by the type of cement kiln pollution controls employed.References for Table 3-9 (references called out in the above notes can be found at the end of the chapter)Air Pollution Controls and Efficiency Improvement Measures for Cement Kilns, Prepared by ARCADIS Under Contract No. EP-C-04-023, March31, 2008.Srivastava et al., ES&T, March 2006, pp.1385-1393.Theoretical Approach for Enhanced Mass Transfer Effects in-Duct Flue Gas Desulfurization Processes. Final Report. 1992.3-18Table 3-10. SO2Control Technologies for Cement KilnsImpact on Emissions,±% changeElectricity Consumption,kWh/ton of cementControl TypeNOXSO2PM Hg Other Grinding Kiln OperationWaterConsumption,gal/ton ofcementWet Scrubber-90% to -95%1-80%-50% for THC-99.9% for HCl+0.2(wet processkilns)2+52+12 (wetprocess); +1.5(dry process)3Dry Lime Injection-50%4-75% for HCl555Notes to Table 3-101.See Andover Technology Partners 2009b memo.2.Electric power consumption in connection with wet scrubbing is assumed to be primarily a result of: 1) grinding of limestone to below 45 to74 micrometers in particle size and pumping limestone slurry; and 2) increased kiln exhaust gas fan power requirements. The latter energyincrease is caused by increased pressure drop demand on kiln ID fans due to conveying kiln exit gases across the scrubber spray tower plusincreased gas volume demand on kiln ID fans due to the addition of water in the limestone slurry. Slurry preparation and pumping is assumedto require 20 kWh per ton of limestone. The spray tower pressure drop is assumed to add 500 hp to ID fan requirements on a 300,000 to500,000 ton per year cement kiln process.3.SO2emissions from cement kilns are strongly related to fuel and raw materials sulfur content and to method of kiln operation. Sulfur contentof TDF (typically 1.24% by weight, dry) may be higher or lower than the sulfur content of other fuels commonly used in cement kilns, such ascoal or coke. Therefore it is not practical to relate SO2emissions to the use of these NOXcontrol methods. With respect to use of an SO2wetscrubber using ground limestone, it is assumed that, for wet process kiln systems, uncontrolled SO2emissions of 8.2 lb per ton of clinker (8.9lb/ton of cement) (EPA, 1995: Table 11.6-8) are treated by use of a stoichiometric amount (with respect to uncontrolled SO2) of limestone of90-percent purity in a 15-percent limestone slurry. Limestone and water consumption are 15.5 lb and 87.7 lb, respectively, per ton of cementproduced. For a precalciner kiln, it is assumed that uncontrolled SO2emissions of 1.1 lb per ton of clinker (1.2 lb/ton of cement) (EPA, 1995:Table 11.6-8) are treated similarly (stoichiometric amount limestone of 90% purity in a 15% limestone slurry). Limestone and waterconsumption are 2.1 lb and 11.8 lb per ton of cement produced.4.20 percent at Ca:S stoichiometry of 2:1 to 5:1. See Dry Sorbent Injection report (ARCADIS, 1992).5.Dry lime injection technology is not well developed for the cement industry and no statistics are available.General Notes:See Table 3-9 notes3-19References for Table 3-10 (references called out in the above notes can be found at the end of the chapter)Andover Technology Partners, Cost and Performance of Controls, March 10, 2009.Srivastava et al., ES&T, March 2006, pp.1385-1393.Theoretical Approach for Enhanced Mass Transfer Effects in-Duct Flue Gas Desulfurization Processes. Final Report. ARCADIS, 1992.EPA (1995). Compilation of Air Pollution Emission Factors - Volume 1: Stationary Point and Area Sources. Fifth Edition, Supplements A-F, AP42. U.S. Environmental Protection Agency, Research Triangle Park, North Carolina.Table 3-11. CO2Control Technologies for Cement KilnsImpact on Emissions,+/- % changeControl TypeNOXSO2PM Hg CO2OtherElectricityConsumption,MWh/ton ofclinkerProcess WaterConsumption,ton/ton ofclinkerCooling WaterConsumption,ton/ton of clinkerSolvent CCS1New -99% -99% -85% -0.0220.4294.82Solvent CCS1Retrofit -99% -99% -85% -0.1030.1604.82Oxy-combustion -99% -99% -85%0.17414.3Notes to Table 3-111.CCS = carbon capture and sequestration.References for Table 3-11Andover Technology Partners,, Cost and Performance of Controls, March 10, 2009.EPA, Report to Congress on Cement Kiln Dust, Chapter 3: CKD Generation and Characteristics; US Environmental Protection Agency: 1993.3-20

Table 3-12. HCl, Hg, and THC Control Technologies for Cement Kilns Impact on Emissions, ± % change Control Type 1
NO X SO 2 PM Hg Other
ACI 2 -99.9% -90% -50% for THC Membrane Bag -99.9%
RTO 3 -98% for THC Dry Lime Injection -50% -75% for HCl

Wet Scrubber -90% to -95% -80%

Notes to Table 3-12 1. Feasible combinations of the above control technologies may be utilized as necessary. 2. ACI = activated carbon injection. 3. RTO = regenerative thermal oxidizer

Table 3-13. Multimedia Impacts of Process Capacity Replacement on Cement Kiln Operation 1
Electricity Consumption, kWh/ton of cement Waste
Kiln Type Water

Consumption, gal/ton of cement 2 Grinding 3 Kiln Operation 4 Generation

Rate, ton/ton of cement 5 Disposal Cost,

$/ton of cement
Wet to Precalciner -214 2,6 -12 8 -7 8 -0.072 see notes 9,10

Long Dry to Precalciner No change 2 Not available 7 Not

available 7 -0.062 see notes 9,10

Preheater to Precalciner No change 2 Not available 7 Not

available 7 0 11 see notes 9,10

Notes to Table 3-13. 1. Unless specifically noted otherwise, impacts are presented on a per-short-ton-of-cement basis and generally make use of published data reported on a per-short-ton-of-clinker basis. These values are converted to a per-ton-of-cement basis by assuming that cement consists of 92-percent clinker. All weight units in this table are short tons. 2. Water is not normally consumed in dry process cement kiln processes, except on an emergency basisto prevent damage to process equipment by hot gas or solid process streams. Water is used in noncontact cooling processes that are common in both wet process and dry process cement plants, some of which may or may not use closed circuit cooling systems with no evaporation losses. Water is consumed in direct contact cooling processes such as cement grinding in both wet process and dry3-21

process plants. However, the nature and amount of such water consumption is not intrinsically different between wet process and dry process plants. 3. Power data reported in Worrell and Galitsky (2004) are used for raw mix preparation and kiln process electrical energy consumption for wet and all dry processes. 4. Air pollution control device contributions to electric power consumption data on cement kiln process systems are assumed to include only existing particulate matter control devices and not scrubbers for SO 2 or other criteria pollutants. 5. Solid waste from all process types is assumed to be cement kiln dust (CKD). Data used here are as reported in EPA (1993). 6. Cement is assumed to consist of 92-percent clinker. Clinker is assumed to require 1.42 tons of raw kiln feed (dry) per ton of clinker. Kiln feed loss on ignition is assumed to be 35 percent. Kiln feed slurry is assumed to contain 36-percent water. 7. Industry-wide statistics on electrical energy use do not distinguish among the various cement processing stages between the various dry processes – all dry process plants are averaged together. Published data that distinguish between various process types combine all process phases without indicating energy use for individual process phases. Therefore, electrical energy use is reported here to be the same for all dry process plants. See Worrell and Galitsky (2004). 8. As stated in note 7, industry data on electric power use in raw materials preparation and kiln processing are not available for every dry process. Data are for all dry processes are combined. 9. Data reported in EPA (1993) on CKG generation by cement plants doe not distinguish between preheater and precalciner kilns with respect to net CKD generation rates. 10. CKD disposal prices vary widely by location. Transportation of CKD is a significant component of the cost of disposal if disposal is off-site. For example, an estimated off-site disposal cost ranging from $26 to $69 per ton of CKD for disposal, plus transportation costs ranging from $500 - $1,500 per truck load for one northern California location, depending on the landfill chosen. (ARCADIS, 2009) On-site disposal costs would include costs of transportation, dust control, and landfill operation. These costs have not been determined and would most certainly vary widely by location based on terrain, site geology, landfill operating requirements, and permit and future closure costs. 11. Modern preheater cement kilns and precalciner cement kilns generate similar volumes of CKD. Older preheater cement kilns are similar in CKD generation to long dry process cement kilns.3-22

Table 3-14. Energy Efficiency Measures for Raw Materials Preparation Electricity Consumption Change, kWh/ton clinker Energy Efficiency Improvement Method Dry Wet Preheater Precalciner ETS ( Efficient Transport System) -3.20 -3.20 -3.20 RMB (Raw Materials Blending) -2.70 -2.70 -2.70 PCVM ( Process Control Vertical Mill) -0.90 -0.90 -0.90 HERM (High Efficiency Roller Mill) -11.05 -11.05 -11.05 SBH (Slurry Blending and Homogenization) -0.35 WMCCC (Wash Mills with Closed Circuit Classifier) -12.00 RMTHEC (High-Efficiency Classifiers) -5.05 -5.05 -5.05 -5.05

Table 3-15. Energy Efficiency Clinker Making Measures Electricity Consumption Change, kWh/ton clinker Heat Input Change, MMBtu/ton of clinker Energy Efficiency Improvement Method Dry Wet Preheater Precalciner Dry Wet Preheater Precalciner EMCS ( Energy Management and Control System) -1.90 -1.50 -1.90 -1.90 -0.15 -0.21 -0.15 -0.15

SR (Seal Replacement) -0.02 -0.02 -0.02 -0.02

CSI ( Combustion System Improvement) -0.25 -0.35 -0.25 -0.25

IF ( Indirect Firing) -0.16 -0.16 -0.16 -0.16

SHLR ( Shell Heat Loss Reduction) -0.20 -0.20 -0.20 -0.20

OGR (Optimize Grate Cooler) 0.90 0.90 0.90 -0.09 -0.10 -0.09 -0.09

CGC (Convert to reciprocating grate cooler) 2.40 2.40 2.40 2.40 -0.23 -0.24 -0.23 -0.23

HRPG ( Heat Recovery for Power Generation) -18.0

EMD ( Efficient Mill Drives) -2.00 -1.70 -2.00 -2.003-23

Table 3-16. Energy Efficiency Measures for Finish Grinding Electricity Consumption Change, kWh/ton clinker Energy Efficiency Improvement Method Dry Wet Preheater Precalciner EMPC (Energy Management and Process Control) -1.60 -1.60 -1.60 -1.60 IGMBM (Improved Grinding Media [Ball Mills]) -1.80 -1.80 -1.80 -1.80 HPRP (High-Pressure Roller Press) -16.00 -16.00 -16.00 -16.00 HEC (High-Efficiency Classifiers) -3.85 -3.55 -3.85 -3.85

Table 3-17. Energy Efficiency Plant-wide Measures Electricity Consumption Change, kWh/ton clinker Energy Efficiency Improvement Method Dry Wet Preheater Precalciner PM* (Preventive Maintenance) -2.50 -2.50 -2.50 -2.50 HEM (High Efficiency Motors) -2.50 -2.50 -2.50 -2.50 ASD (Adjustable Speed Drives) -6.25 -6.00 -6.25 -6.25 OCAS (Optimization of Compressed Air Systems) -1.00 -2.50 -1.00 -1.00 *This is the only occurrence wherein “PM” does not stand for “particulate matter”3-24



### References for Chapter 3
American University (2008). TED Case Studies: Cemex Case . http://www.american.edu/TED/cemex.htm
, accessed October 21, 2008.
Andover Technologies Partners (2009a). Memorandum: NO X , SO 2 and CO 2 Emissions from Cement Kilns (Emissions Memo) , from Jim Staudt to Ravi Srivastava, Samudra Vijay, Elineth Torres. Dated March 10, 2009 (see Appendix A of this document).
Andover Technology Partners (2009b). Memorandum: Costs and Performance Controls , from Jim Staudt to Ravi Srivastava, Samudra Vijay, Elineth Torres. Dated March 10, 2009 (see Appendix A of this document).
Andover Technology Partners (2009c). Memorandum: GHG Mitigation Methods for Cement , from Jim Staudt to Ravi Srivastava, Nick Hutson, Samudra Vijay, Elineth Torres. Dated July 10, 2009 (see Appendix A of this document).
Andover Technologies Partners (2010a). Memorandum: Wet Scrubber Cost Algorithms , from Jim Staudt to Ravi Srivastava, Elineth Torres, Keith Barnett. Dated February 26, 2010 (see Appendix A of this document).
Andover Technologies Partners (2010b). Memorandum: Electrical Load for Wet Scrubbers , from Jim Staudt to Elineth Torres. Dated May 7, 2010 (see Appendix A of this document).
ARCADIS (1992). Theoretical Approach for Enhanced Mass Transfer Effects in-Duct Flue Gas Desulfurization Processes. Final Report. ARCADIS, 1992.
ARCADIS (2009). Personal Comm. with E. Leamer of ARCADIS, 26 February, 2009.
Burtraw, D. (2010). Supply Elasticity Estimation, memorandum to Ravi Srivastava, U.S. EPA, March 10, 2010.
Depro, Brooks, Rogozhin, Alex, and Wood, Dallas (2007). RTI International. “ Documentation for Portland Cement Kiln Cost Functions (2005 )”, Memorandum to Keith Barnett, US EPA, August 31, 2007 (see Appendix A of this document).
Depro, Brooks. (2010). RTI International. “ISIS Cement Production Costs”, Memorandum to Elineth Torres, US EPA, March 31, 2010 (see Appendix A of this document).
Depro, Brooks and Lentz, Anthony. (2010). RTI International. “ISIS Cement Production Costs”, Excel Spreadsheet Attachment to Memo of Same Name from Brooks Depro (2010), February 16, 2010.
BLS (2008). Bureau of Labor Statistics, Databases, Tables & Calculators by Subject, Major Sector Productivity and Costs Index. Series ID: PRS30006112, Sector: Manufacturing. http://data.bls.gov/PDQ/servlet/SurveyOutputServlet? data_tool=latest_numbers&series_id=PRS30006112
, accessed November 24, 2008.
EIA (2008) Annual Energy Outlook 2008, DOE/EIA-0383(2008), June 2008. http://www.eia.doe.gov/oiaf/aeo/pdf/0383(2008).pdf , accessed October 21, 2008.3-25

EPA (1993). Report to Congress on Cement Kiln Dust, Chapter 3: CKD Generation and Characteristics; US Environmental Protection Agency: 1993.
EPA (1995). Compilation of Air Pollution Emission Factors - Volume 1: Stationary Point and Area Sources. Fifth Edition, Supplements A-F, AP-42. U.S. Environmental Protection Agency, Research Triangle Park, North Carolina.
EPA (1998). June 1998. Regulatory Impact Analysis of Cement Kiln Dust Rulemaking . Washington, DC: U.S. Environmental Protection Agency. http://www.epa.gov/osw/nonhaz/industrial/special/ckd /ckd/ckdcostt.pdf , accessed October 21, 2008.
EPA (2004). Alternative Control Techniques Document - NO X Emissions from Cement Manufacturing, dated March 1994 (EPA-453/R-94-004)
EPA (2005). EPA 2002 National Emission Inventory v3. http://www.epa.gov/ttn/chief/net/2002inventory.htm l , accessed October 21, 2008
EPA (2006). EPA 2005 National Emissions Inventory Version 2. http://www.epa.gov/ttn/chief/net/2005inventory.html accessed November 17, 2008
EPA (2007). November 2007. Alternative Control Techniques Document Update - NO X Emissions from New Cement Kilns. EPA-453/R-07-006 . Research Triangle Park, NC. US Environmental Protection Agency.
FLSmidth & Co. A/S (2007). Q2 Report 2007. August 2007 http://hugin.info/2106/R/1148414/219358.pdf , accessed October 21, 2008.
NESCAUM (2000). Status Report on NO X Controls for Gas Turbines, Cement Kilns, Industrial Boilers, Internal Combustion Engines: Technologies & Cost Effectiveness. Northeast States for Coordinated Air Use Management, December 2000. Accessed at http://www.nescaum.org/documents/nox-2000.pdf/
OMB (1992). Guidelines and Discount Rates for Benefit-Cost Analysis of Federal Programs. OMB Circular No.A-94 (Revised). U.S. Office of Management and Budget, October 29, 1992. http://www.whitehouse.gov/omb/circulars/a094/a094.ht ml#8 , accessed October 21, 2008.
PCA (2004). Innovations in Portland Cement Manufacturing. Portland Cement Association. Edited by J. I. Bhatty, F. M. Miller, and S. H. Kosmatka. 2004.
PCA (2004a). U.S. and Canadian Portland Cement Industry: Plant Information Summary of December 31, 2004.
PCA (2006). U.S. and Canadian Portland Cement Industry: Plant Information Summary. Portland Cement Association, Skokie, IL, 2006.
PCA (2008). Forecast Report: Long-Term Cement Consumption Outlook. By Ed Sullivan January 31, 2008 . http://www.cement.org/econ/pdf/Long-TermFlashwinte r2007nonmember.pdf , accessed October 21, 2008.
PCA (2009a). PCA Capacity Report. Flash Report. Portland Cement Association’s Economic Research Department. Updated October 19, 2009.3-26

PCA (2009b). Forecast Report: Long-Term Cement Consumption Outlook. By Ed Sullivan. October 28, 2009. Portland Cement Association.
Ryan, S. (2006). The Costs of Environmental Regulation in a Concentrated Industry. Department of Economics, MIT, Cambridge, MA, October 5, 2006. http://econ-www.mit.edu/files/116 6 , accessed October 21, 2008.
RTI (2010). ISIS Input Price Escalation Factors, Excel Spreadsheet.
TRAGIS (2003). Transportation Routing Analysis Geographic Information System (TRAGIS) User’s Manual, Revision 0, Oak Ridge National Laboratory, June 2003. https://tragis.ornl.gov/TRAGISmanual.pdf

. USGS (2005). Background Facts and Issues Concerning Cement and Cement Data. U.S. Geological Survey, Open-File Report 2005-1152 . http://pubs.usgs.gov/of/2005/1152/2005-1152.pdf , accessed October 21, 2008.
USGS (2007a). 2005 Minerals Yearbook: Cement. U.S. Geological Survey, p. 16.2, February 2007, http://minerals.usgs.gov/minerals/pubs/commodity/cem ent/cemenmyb05.pdf , accessed October 21, 2008
USGS (2007b). Mineral Commodity Summaries: Cement, U.S. Geological Survey, pp. 40-41, January 2007. http://minerals.er.usgs.gov/minerals/pubs/commodity/ cement/cemenmcs07.pdf , accessed October 21, 2008.
USGS (2009). 2005 Minerals Yearbook: Cement. U.S. Geological Survey (Table 17), pp. 16.21. http://minerals.usgs.gov/minerals/pubs/commodity/cem ent/myb1-2007-cemen.pdf

. Worrell, E.; Galitsky, C. (2004). Energy Efficiency Improvement Opportunities for Cement Making; Lawrence Berkeley National Laboratory, LBNL-54036, Jan 2004. An ENERGY STAR ® Guide for Energy and Plant Managers, http://www.osti.gov/energycitations/servlets/purl/821915-Re2kcK/native/.
Yates, J.R. et al. (2003). CemStar Process and Technology for Lowering Greenhouse Gases and Other Emissions while Increasing Cement Production. http://www.hatch.ca/Environment_Community/Sustainabl e_Development/Projects/Copy%20of%20Cem Star-Process-final4-30-03.pdf accessed February 27, 2009.4-1 

## Chapter 4 Model Calibration

Large techno-economic models of ISIS framework size require model calibration as they utilize extensive amount of data which comes from different sources. This chapter outlines calibration methodology that was used, discusses data used for calibration, presents calibration results, and gives further recommendations.


### 4.1 Calibration Methodology
Calibration methodology utilizes the concept of calibration constant. The calibration constant has been developed to account for possible errors in costs. The value of calibration constant, calconst(i) , is set by trial and error during calibration. The objective of the trial and error approach is to minimize the absolute difference in the reported and model-predicted prices (which are marginal values of the supply equation) for each USGS district.
In the first step of calibration, the model is set to run for 2005-2007 by making appropriate changes in the input “Policy” worksheet, and GAMS input files. The import quantities are then adjusted equal to reported import quantity for each of the import district, except for those of Mexico and Canada.
In the next step, impact of changing the calibration constant is monitored. This impact of the calibration constant is assessed on estimated production quantities to keep the difference between reported and model predicted production values within reasonable limits 5 . The calibration constant modifies each kiln’s variable cost of production. “Calibration” worksheet within the Inputs workbook has values of calibration constant assigned for each USGS district. Finally, in the input GAMS file, the values are assigned for a given USGS district to each of the kilns located in that USGS district.
The model is first calibrated for year 2005, to obtain values of the calibration parameter calconst(i) for the year. Next, calconst(i) values for 2005 are used as starting point and obtain values for the same parameter for 2006. Similarly, the process is repeated to obtain the values for 2007. Then, an average of the calconst(i) values over the three years is taken and used for the future model runs. Current values of the parameter Calconst(i) being used in the model runs can be found in the worksheet “ Calibration ” of the “ISIS_Inputs.xls” workbook.
Calibration is a dynamic process, and it is recommended that model calibration be performed periodically. In this fashion, any available new production, imports, or price data could be utilized in t he model..


### 4.2 Data for Calibration
Production quantities in various USGS production districts, import levels in the import districts and reported cement prices for USGS districts are the key quantities used for calibration of the model.

5 There is no standard method to guide user in determining acceptable level of “error” in the reported and predicted values for the purpose of calibration. In this works, we have set acceptable level for the absolute gap between the individual reported and predicted values to ± 15%, although effort has been made to keep this level below 10% for most of the quantities. However, due to discontinuities in the transportation matrix, error in the reported data, or other unknowns, the gap in the estimated and reported values may be higher in certain markets.4-2

Reported data for years 2005, 2006 and 2007 were used to calibrate the model and obtain values of appropriate calibration parameters.



### 4.2.1 Cement Prices in USGS Districts
Reported cement prices in various USGS districts are shown in Table 4-1 for years 2005 through 2007. For a given year, the reported cement price shows significant variation across USGS districts. For most districts the cement price has increased over the three year period. USGS districts assignation is the location of the reporting production facilities.


### 4.2.2 Cement Production in USGS Districts
Reported cement production in various USGS districts is shown in Table 4-2 for years 2005 through 2007. For a given year, the reported cement production shows significant variation across USGS districts. Generally production dropped from 2005 to 2007, due to a decrease in demand resulting from the economic downturn.


### 4.2.3 Cement Imports by Import Districts
Reported cement import quantity in various import districts is shown in Table 4-3 for years 2005 through 2007. For a given year, the reported cement imports show a significant variation across import districts. Generally imports dropped from 2005 to 2007, due to a decrease in demand resulting from the economic downturn. New Orleans (LA), San Francisco (CA) and Tampa (FL) suffered large drops in the quantities of cement imported in 2007 compared to that in 2005.


### 4.3 Results of Calibration
Reported and calculated values of cement prices by USGS district are shown for years 2005, 2006, and 2007 in Table 4-4, Table 4-5, and Table 4-6, respectively. As can be seen from these tables, in most of the districts reported and calculated cement prices are within 10% range, whereas in a few they are higher. It should be noted that in general the price differentials are smaller in the year 2005 and have increased in 2007. In some USGS districts the reported and calculated prices are different than the model predicted prices due to several factors, including error in reported prices, discontinuities in the transportation matrix, and/or unique factors for some specific markets.
Specifically, the Arizona and New Mexico USGS district has a price differential due to capacity constraints in New Mexico. New Mexico has only two small, very old kilns with a capacity half than the demand in New Mexico. The balance demand is met by kilns in Texas, and imports, which incur a significant transportation cost, resulting in a high price for cement in this market. Similarly, Oregon and Washington USGS District is dependent on supplies from other states. While demand in Washington is met by domestic production, and imports from Canada, Oregon, relies on imports from Canada, and other nearby states, resulting in higher cost.
Generally, individual market prices are within the criteria specified in the QA document, the aberrations are explained by the demand-supply gap and transportation cost. Moreover, root-mean-square values of the price difference for 2005 and 2006 are about 12% and 10% respectively, and 18% for 2007.4-3

Further while calibrating for price, aggregate production level is also tracked to make sure that it is within reasonable limits. The reported and predicted aggregate production levels for 2005-2007 are shown in Table 4-7.
The current set of calibration constant values are averaged over the years of calibration, and are available in the “Calibration” worksheet in the “ISIS_Inputs.xls” workbook.4-4

Table 4-1. Cement Prices ($/short ton) for USGS Districts

USGS District 2005 2006 2007
Alabama 74.61 81.74 87.09
Illinois 80.29 89.81 91.17
Indiana 72.03 80.04 79.99
Kansas 76.58 86.50 92.87 Maryland 74.76 81.19 80.18
Missouri 78.92 86.61 89.36
Ohio 82.08 90.24 91.47
South Carolina 68.57 80.46 87.54
Maine and New York 80.74 92.53 96.62 Pennsylvania 79.73 89.99 90.85 Michigan and Wisconsin 79.83 84.82 90.12 Iowa, Nebraska and South Dakota 78.72 89.83 93.08

Florida 77.56 90.44 95.55 Georgia, Virginia and West Virginia 84.49 95.93 93.60 Kentucky, Mississippi and Tennessee 84.37 89.81 88.90
Arkansas and Oklahoma 89.00 96.99 97.74
Texas 74.72 85.10 88.33
Arizona and New Mexico 75.76 84.16 86.64 Colorado and Wyoming 82.24 92.90 92.73 Idaho, Montana, Nevada and Utah 83.61 90.26 95.25

California 88.20 99.09 100.24 Oregon and Washington 79.38 90.72 90.724-5

Table 4-2. Cement Production (short tons) for Various USGS Districts

USGS District 2005 2006 2007 Alabama 5,647,141 5,733,121 5,578,650 Illinois 3,568,182 3,425,984 3,434,254 Indiana 3,370,868 3,334,492 3,285,999 Kansas 3,182,373 3,310,241 3,039,164 Maryland 2,813,098 2,922,227 3,305,160 Missouri 5,877,524 5,776,111 5,763,479 Ohio 1,086,879 1,064,833 1,010,077 South Carolina 3,601,251 3,654,162 4,057,414 Maine and New York 3,572,591 3,699,357 3,471,388 Pennsylvania 6,931,334 6,631,505 6,239,551 Michigan and Wisconsin 6,171,841 5,993,267 6,047,588 Iowa, Nebraska and South Dakota 4,962,606 5,024,335 4,889,607

Florida 6,311,835 6,477,181 6,076,137 Georgia, Virginia and West Virginia 2,612,478 2,696,253 2,528,648 Kentucky, Mississippi and Tennessee 3,649,753 3,849,271 3,770,250 Arkansas and Oklahoma 3,097,495 2,979,547 2,879,982 Texas 12,737,207 12,510,131 12,038,919 Arizona and New Mexico 3,073,244 2,809,792 2,902,131 Colorado and Wyoming 2,918,920 2,842,861 2,797,240 Idaho, Montana, Nevada and Utah 3,400,630 3,354,333 3,308,645

California 12,747,128 12,069,207 11,941,198 Oregon and Washington 2,175,963 2,101,005 2,103,4814-6

Table 4-3. Cement Imports (except from Canada and Mexico) for Import Districts (short tons)

Import District 2005 2006 2007 Baltimore, MD 146,300 203,500 18,700 Boston, MA 145,200 50,600 3,300 Buffalo, NY 6,600 4,400 0 Charleston, SC 1,212,200 1,100,000 363,000 Chicago, IL 1,100 1,100 0 Cleveland, OH 0 1,100 0 Columbia-Snake, ID-OR-WA 831,600 1,115,400 1,180,300 Detroit, MI 59,400 0 0 Duluth, MN 0 0 0 El Paso, TX 0 0 0 Great Falls, MT 0 0 0 Houston-Galveston, TX 2,880,900 3,705,900 3,641,000 Laredo, TX 0 0 0 Los Angeles, CA 3,357,200 3,759,800 2,029,500 Miami, FL 2,395,800 2,311,100 980,100 Minneapolis, MN 0 0 0 Mobile, AL 565,400 573,100 0 New Orleans, LA 4,503,400 5,090,800 1,171,500 New York, NY 1,390,400 1,327,700 810,700 Nogales, AZ 0 0 0 Norfolk, VA 767,800 793,100 447,700 Ogdensburg, NY 0 0 0 Pembina, ND 0 0 0 Philadelphia, PA 544,500 665,500 342,100 Portland, ME 0 0 0 Providence, RI 814,000 680,900 509,300 San Diego, CA 620,400 708,400 427,900 San Francisco, CA 2,599,300 3,081,100 1,524,600 Savannah, GA 88,000 204,600 376,200 Seattle, WA 368,500 733,700 644,600 St. Albans, VT 0 0 0 St. Louis, MO 0 0 3,300 Tampa, FL 3,825,800 3,791,700 1,523,500 Wilmington, NC 427,900 416,900 284,9004-7

Table 4-4. Reported and Calculated Cement Prices in USGS Districts (2005)

USGS District Reported Calculated % ∆
Alabama 74.61 78 5
Illinois 80.29 83 3
Indiana 72.03 84 16
Kansas 76.58 81 6 Maryland 74.76 74 -1
Missouri 78.92 82 4
Ohio 82.08 83 1
South Carolina 68.57 76 10
Maine and New York 80.74 73 -9 Pennsylvania 79.73 77 -3 Michigan and Wisconsin 79.83 81 2 Iowa, Nebraska and South Dakota 78.72 81 3

Florida 77.56 75 -3 Georgia, Virginia and West Virginia 84.49 80 -6 Kentucky, Mississippi and Tennessee 84.37 81 -4
Arkansas and Oklahoma 89.00 87 -2
Texas 74.72 78 4
Arizona and New Mexico 75.76 105 39 Colorado and Wyoming 82.24 98 20 Idaho, Montana, Nevada and Utah 83.61 70 -16

California 88.20 85 -4 Oregon and Washington 79.38 69 -134-8

Table 4-5. Reported and Calculated Cement Prices in USGS Districts (2006)

USGS District Reported Calculated % ∆
Alabama 81.74 85 4
Illinois 89.81 83 -8
Indiana 80.04 85 6
Kansas 86.50 83 -4 Maryland 81.19 80 -1
Missouri 86.61 81 -6
Ohio 90.24 83 -8
South Carolina 80.46 85 6
Maine and New York 92.53 78 -16 Pennsylvania 89.99 80 -11 Michigan and Wisconsin 84.82 80 -6 Iowa, Nebraska and South Dakota 89.83 81 -10

Florida 90.44 82 -10 Georgia, Virginia and West Virginia 95.93 86 -10 Kentucky, Mississippi and Tennessee 89.81 84 -6
Arkansas and Oklahoma 96.99 91 -6
Texas 85.10 81 -4
Arizona and New Mexico 84.16 105 25 Colorado and Wyoming 92.90 100 8 Idaho, Montana, Nevada and Utah 90.26 83 -8

California 99.09 85 -14 Oregon and Washington 90.72 74 -184-9

Table 4-6. Reported and Calculated Cement Prices in USGS Districts (2007)

USGS District Reported Calculated % ∆
Alabama 87.09 73 -17
Illinois 91.17 72 -21
Indiana 79.99 75 -7
Kansas 92.87 71 -24 Maryland 80.18 74 -8
Missouri 89.36 71 -21
Ohio 91.47 76 -17
South Carolina 87.54 69 -21
Maine and New York 96.62 74 -24 Pennsylvania 90.85 75 -17 Michigan and Wisconsin 90.12 76 -15 Iowa, Nebraska and South Dakota 93.08 71 -23

Florida 95.55 66 -31 Georgia, Virginia and West Virginia 93.60 74 -20 Kentucky, Mississippi and Tennessee 88.90 71 -20
Arkansas and Oklahoma 97.74 88 -10
Texas 88.33 80 -10
Arizona and New Mexico 86.64 101 17 Colorado and Wyoming 92.73 89 -4 Idaho, Montana, Nevada and Utah 95.25 83 -13

California 100.24 81 -20 Oregon and Washington 90.72 75 -18

Table 4-7. Aggregate production (reported and modeled) for 2005-2007

Year Reported Production

(million short tons) Calculated Production (million short tons) % ∆

2005 111.84 112.54 0.63
2006 110.30 111.23 0.84
2007 108.17 101.95 -5.754-10



### 4.4 Recommendations
If any of the key input parameters, specifically those relating to production quantities and costs, are refined or otherwise modified or additional observed data becomes available, the calibration of the model should be repeated. Transportation matrix, modes, and cost of transportation also have significant impact on the behavior of production distribution across the districts and production prices. Therefore, if anyfurther modifications or refinements are made to the transportation matrix, the model needs to be recalibrated.
At the time of calibration of the current version of the model, production, import and price values for only 2005 to 2007 were available. As discussed above, when the new values become available, the model needs to be calibrated again. Calibration of the model should be repeated as soon as new information or new observed data become available. Due to practical limitations it is recommended that the calibration of the model be repeated every two years. Further, since the calibration data is available only for three years, equal weight was given to the parameters obtained for each year. Once larger data-set is available, a modified weighing system can be adopted to give highest weight to the most-recent year data.4-11



### 4.5 References for Chapter 4
United States Geological Service. Mineral Yearbook 2008. Table 5. http://minerals.usgs.gov/minerals/pubs/commodity/cem ent/
United States Geological Service. Mineral Yearbook 2008. Table 3. http://minerals.usgs.gov/minerals/pubs/commodity/cem ent/
United States Geological Service. Mineral Yearbook 2008. Table 11. http://minerals.usgs.gov/minerals/pubs/commodity/cem ent/5-1 

## Chapter 5 An Example Policy Analysis

5.1 An Example Analysis of Potential Reductions in CO 2 

### Emissions from the U.S. Cement Industry
This section presents an example analysis of the U.S. cement industry utilizing ISIS-cement model. The analysis investigates the potential for near-term reductions in emissions of CO 2 and other pollutants,associated costs, and industry operation. The regulatory mechanism selected for analysis was cap-andtrade of CO 2 . This mechanism has been used in many of the recent policy proposals addressing reduction of CO 2 emissions. In a cap and trade framework, CO 2 allowance price is a metric of primary importance for deciding on CO 2 reduction levels. For a reduction range selected for analysis to be practicable, CO 2 allowance price projected by the model for a given year should be in agreement with allowance prices determined by recent analyses. The recent analysis selected for comparison with model projections was the American Clean Energy and Security Act of 2009. Once the range of CO 2 emission reduction is determined to be practicable, the model projects characteristics of the industry for this emission reduction range. The analysis as described above is an example of the type of sector-specific analyses that may be needed for developing GHG reduction policies for industrial sectors.
Two broad questions were investigated in this example analysis: 1) what range of CO 2 reduction options may be practicable in the near-term (i.e., the decade ending 2020), and (2) for that range, what may be the market characteristics for the U.S. cement industry? The first question is relevant because in the absence of carbon capture technology, the path forward for reducing emissions in the near-term will need to depend on the currently available energy efficiency measures and raw material and product substitution approaches, some of which are described earlier. The second question speaks to industry operation under the potentially practicable options determined while answering the first question.
To investigate the above questions, CO 2 emissions targets corresponding to a range of reductions from projected CO 2 emissions in 2013 were analyzed. Relatively modest reduction levels ranging from 5 to 25 percent were chosen to be generally consistent with the capabilities of energy efficiency and raw material substitution measures. These targets are summarized in Table 5-1. Only the measures depicted in Tables 3-15 and 3-17 were considered in this example analysis because at this time ISIS-cement does not include calculation procedures for the measures shown in Tables 3-14 and 3-16. In addition to the energy efficiency measures of Tables 3-15 and 3-17, a fuel substitution technology, MKF-tires, and a raw material substitution technology, CemStar, are also considered in this analysis. As mentioned before, the use of MKF-tires results in reduced fossil fuel consumption (by about 15%) and this fuel consumption reduction is included in ISIS-cement. Relative to CemStar, a 7.5-percent reduction in limestone and a 3-percent reduction in fuel for every short ton of clinker produced is included in ISIS-cement. The costs for energy efficiency measures are described in Andover Technology Partners (2009) and for MKF-tires and CemStar in Andover Technology Partners (2008). These costs are included in ISIS-cement. Information on the extent to which each of the energy efficiency measures in Tables 3-15 and 3-17 could be applied on existing kiln capacity was obtained (Xu, 2010) and included in ISIS-cement. These penetration numbers ranged from 5 percent for CGC to 88 percent for preventive maintenance

. Also for this example analysis it was assumed that each of CemStar and MKF-tires cannot be applied on more than 25 percent of the existing and unretired kiln capacity over the horizon 2013-2020.5-2

Table 5-1. CO 2 Caps Modeled in this Analysis

CO 2 Cap (short tons) Reduction from projected 2013 Emission Level (%)* 64,099,115 5 60,725,478 10 57,351,840 15 53,978,202 20 50,604,565 25
*2013 emissions were those under the BAU case.

Runs were made with ISIS-cement for the BAU case (i.e., when no emission reduction requirements are in effect) and with each of the above caps. The corresponding results are presented in Figures 5-1 through 5-7.
In a cap-and-trade framework, CO 2 allowance price is a primary metric for deciding on CO 2 reduction levels. Figure 5-1 reflects that CO 2 allowance price (in 2013 for example) for various reduction levels ranging from about 10 to 35 $ per short ton of CO 2 . A recent analysis of the American Clean Energy and Security Act of 2009 reflects a price range of 13-24 $ per metric ton in 2015 (EPA, 2009). Considering this indication, a reduction range of 5 to 15 percent appears practicable for purposes of this example analysis.

0

5 10 15 20 25 30 35 40

0.0 5.0 10.0 15.0 20.0 25.0CO2Allowance Price ($/short ton)

CO 2 Reduction (%)

Figure 5-1. Projected CO 2 Allowance Prices5-3

Two metrics for additional evaluation of potential emission reductions levels could be: (1) U.S. industry revenue under policy, and (2) cement price under policy. Arguably, these metrics speak to the interests of both the industry and consumers.
An increase in cement price under a CO 2 reduction policy will cause a drop in demand. Also, if the policy does not impose any requirements on imports, these can increase under policy because production can shift to other countries. Both factors, drop in demand and increased levels of imports, can cause a reduction in revenue for the cement industry in the U.S.
An increase in price will, in general, result in a reduction in demand because consumers will reduce their needs at higher prices. And the drop in demand will contribute to reduction in revenue for the industry. As mentioned before, ISIS-cement includes a procedure for calculating drop in demand with increase in price.
Figures 5-2 and 5-3 show the U.S. industry revenue and cement price (in 2013, for example) for the BAU case (0% reduction), and for emission reductions ranging from 5 to 25 percent. Figure 5-2 shows that the drop in U.S. industry revenue under policy relative to BAU ranges from about 4 to 6.5 percent for the reduction range of 5 to 15 percent. For the same reduction range, Figure 5-3 reflects that the increase in cement price ranges from about 5 to 12 percent. Figure 5-4 shows the drop in demand due to rising prices under increasing CO 2 reduction levels. This drop contributes to the loss of revenue seen in Figure 5-2. Notably, the drop in demand relative to BAU is less than about 16 percent if the reduction levels are kept at or below 15 percent.

-9 -8 -7 -6 -5 -4 -3 -2 -1 0

43 44 45 46 47 48

0.0 5.0 10.0 15.0 20.0 25.0Change in U.S. Industry Revenue (%)U.S. Industry Revenue (billion $)

CO 2 Reduction (%)

U.S. Industry Revenue (billion $) Change in U.S. Industry Revenue (%)

Figure 5-2. Projected Revenue for the U.S. Cement Industry over the Horizon 2013-20205-4 0 5 10 15 20 25

0 40 80 120

0.0 5.0 10.0 15.0 20.0 25.0Change in Cement Price (%)Cement Price ($/short ton)

CO 2 Reduction (%)

Cement Price Change in Cement Price (%)

Figure 5-3. Projected Average Cement Prices in 2013 for the U.S. Cement Industry

-25 -20 -15 -10 -5 0

0 100 200 300 400 500 600 700 800 900 1,000 1,100 1,200

0.0 5.0 10.0 15.0 20.0 25.0Change in Demand (%)Demand (million short tons)

CO 2 Reduction (%)

Demand (million short tons) Change in Demand (%)

Figure 5-4. Projected Demand for Cement5-5

Figure 5-5 reflects that under example policy options imports increase relative to the BAU case. Also, as the cap is tightened from the 15-percent reduction level to the 25-percent reduction level, the industry resorts to increasing imports in a monotonic fashion. Since imports come with zero emissions in the U.S. and result in reduced domestic fuel and raw materials processing, they can help comply with a policy requiring reductions in domestic emissions. While the impact of increases in imports in the U.S. on emissions in exporting countries is beyond the scope of this analysis, such increases in imports will generally result in increases in CO 2 and other emissions in exporting countries.

0 1 2 3 4 5

250 260 270 280 290 300

0.0 5.0 10.0 15.0 20.0 25.0Change in imports (%)Imports (million short tons)

CO 2 Reduction (%)

Imports (million short tons) Change in Imports (%)

Figure 5-5. Projected Imports for the U.S. Cement Industry over the Horizon 2013-2020

A concern related to drop in revenue can be retirement/mothballing of kiln capacity in the U.S. cement industry. Figure 5-6 reflects the potential for retirements/mothballing under the example reduction options. For this work, a unit is considered retired or mothballed if it does not produce in any year of the horizon 2013-2020. The figure shows that even under the BAU case, 12 to 13 percent of the existing capacity may be retired or mothballed because in each year of the horizon 2013-2020, the U.S. cement industry has excess kiln capacity relative to BAU demand. For the reduction range 5 to 15 percent, the retired or mothballed capacity ranges from 23 to 27 percent of the existing capacity, or about 10 to 14 percentage points over the BAU projection.
Significant collateral reductions in other pollutant emissions may be possible under the range of practicable CO 2 reduction levels arrived at in this example analysis. Figure 5-7 shows such collateral reductions in NO X and SO 2 emissions. At the 15-perecnt CO 2 reduction level, each of NO X and SO 2 emissions may be reduced by more than 250 thousand short tons. These reductions result from use of energy efficiency measures (see below) and reduced production.5-6 0 5 10 15 20 25 30 35 40

0 10 20 30 40 50

0.0 5.0 10.0 15.0 20.0 25.0Change in Retired/mothballed Capacity (%)Retired/mothballed Capacity (million short tons)

CO 2 Reduction (%)
Retired/mothballed Capacity (million tons) Retired/mothballed Capacity (%)

Figure 5-6. Projected Capacity Retirement/Mothballing

0 100 200 300 400 500 600 700

0 200 400 600 800 1000

0.0 5.0 10.0 15.0 20.0 25.0CO2Emissions (million short tons)NOx, SO2Emissions (thousand short tons)

CO 2 Reduction (%)

NOx SO 2 CO 2

Figure 5-7. Projected Emissions of NO X , SO 2 , and CO 2 from the U.S. Cement Industry over the

Horizon 2013-20205-7

For the cap at the 15-percent reduction level, which is in the range of practicable reductions for purposes of this example analysis, additional detailed results are presented in Figures 5-8 and 5-9.
Figure 5-8 shows the projected CO 2 emissions under the BAU case, emission caps corresponding to 15-percent reduction from CO 2 emissions in 2013 and banked allowances. The industry engages in relatively modest levels of CO 2 allowance banking and related trading activity, practices consistent with the relatively modest level of reduction required.
Figure 5-9 reflects that, in response to the CO 2 reduction requirement, the industry installs and operates measures with multi-pollutant (NO X , SO 2 , and CO 2 ) reduction benefits. The majority of these measures are installed in 2013 to help comply with the reduction requirement. The energy efficiency measures reflected in the legend of this figure are defined in Tables 3-15 and 3-17. Also, CemStar and MKF-tires are briefly described in the section on raw material and/or fuel substitution. Note that Figure 5-9 reflects that CemStar will need to be applied on about 40 percent of operating capacity in 2013. Consequently, a reliable and adequate supply of blast furnace slag (BFS) will need to be ensured for this level of CemStar application.

0 10 20 30 40 50 60 70 80 90

2013 2014 2015 2016 2017 2018 2019 2020CO2(million tons)

BAU Case Emissions, CO2 (tons) Emission Cap, CO2 (tons)

Controlled Emissions, CO2 (tons) Banked Allowances, CO2 (tons)

Figure 5-8. Projected CO 2 Emissions and Reductions from the U.S. Cement Industry Under the BAU and the 10-percent CO 2 Reduction Cases.5-8 0 5 10 15 20 25 30 35 40 45

2013 2014 2015 2016 2017 2018 2019 2020Percent of Operating Capacity (%)

MKF-tires CEMstar PM EMCS SR CSI IF SHLR OGR

Figure 5-9. Projected Control Technology Applications in the U.S. Cement Industry Under the

10-percent CO 2

Reduction Case.



### 5.2 Summary and Thoughts for Future Work
In this chapter, ISIS-cement was used to conduct an example analysis of the U.S. cement sector to gain some insights relative to two broad questions: (1) what range of CO 2 reductions options may be practicable in the near-term, and (2) for that range, what may be the market characteristics for the U.S. cement industry? These questions are relevant because in the absence of carbon capture and sequestration technology, the path forward for reducing CO 2 emissions in the near-term (decade ending 2020) will need to depend on the available energy efficiency measures and raw material and product substitution options. The energy efficiency measures for clinker making and plan-wide application were considered in thisexample analysis. In addition to the energy efficiency measures, a fuel substitution technology, MKFtires, and a raw material substitution technology, CemStar, were also included in the analysis.
The example analysis reflects that, based on CO 2 allowance prices, a range of CO 2 reductions, 5 to 15 percent, from the projected 2013 emissions appears to be practicable. For this range, the drop in U.S. industry revenue under policy ranges from about 4 to 6.5 percent of the revenue in the BAU case and the increase in cement price (in 2013, for example) ranges from about 5 to 12 percent relative to the BAU. Significant collateral reductions in other pollutant emissions may be possible under the range of 5- to 15-percent CO 2 reductions. For example, at the 15-percent CO 2 reduction level, each of NO X and SO 2 emissions may be reduced by more than 250 thousand short tons. To meet a CO 2 reduction level of15 percent from the projected emissions in 2013, the U.S. cement industry would potentially use multipollutant energy efficiency improvement options and reduce domestic production.5-9

The results of the example analysis presented above are indicative only for several reasons. First, as mentioned before, the analysis did not include the full suite of abatement options potentially available in the near-term (i.e., the decade ending 2020). In particular, the analysis did not take into account the energy efficiency measures of Tables 3-14 and 3-16 and feasible raw material and product substitution approaches. Second, some assumptions associated with the abatement measures that were considered need additional evaluation. In particular, availability of materials (e.g., blast furnace slag, tires) and the degree to which a specific abatement measure could be applied across the industry need further assessment. Finally, extra-U.S. CO 2 emissions associated with imports need to be taken into account while setting reduction targets. These areas need to be addressed to permit more comprehensive evaluation of the CO 2 reduction potential relative to the U.S. cement industry. Work is being initiated to address these areas and modify ISIS-cement as needed.
The focus of the example analysis presented is on more modest CO 2 reductions potentially possible with use of energy efficiency approaches in the near-term. However, in the longer term more significant CO 2 reductions (e.g., greater than 50%, perhaps) can only be achieved with use of CO 2 -specific mitigation technologies currently under development.


### 5.3 Disclaimer
Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government, and shall not be used for advertising or product endorsement purposes.5-10



### References for Chapter 5
Andover Technology Partners (2008). Cost and Performance of Controls, memorandum to U.S. EPA, September 25, 2008.
Andover Technology Partners (2009). GHG Mitigation Methods for Cement,, memorandum to U.S. EPA, July 10, 2009.
EPA (2009). EPA Analysis of the American Clean Energy and Security Act of 2009 HR 2454 in the 111th Congress. U.S Environmental Protection Agency, Washington, DC, June 2009. http://www.epa.gov/climatechange/economics/economica nalyses.html

. Xu, T. (2010). Personal communication: Tengfang Xu, Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory with Ravi Srivastava, U.S. EPA, May 2010.A-1 

## Appendix A Andover Technology Partners and RTI International Memos

Andover Technology Partners
May 7, 2010 Electrical Load for Wet Scrubbers
February 26, 2010 Wet Scrubber Cost Algorithms
July 10, 2009 GHG Mitigation Methods for Cement
March 10, 2009 Costs and Performance of Controls – revised from comments
March 10, 2009 NO X , SO 2 and CO 2 Emissions from Cement Kilns (Emissions Memo) – revised

from comments

RTI March 31, 2010 ISIS Cement Production Costs
August 31, 2007 Documentation for Portland Cement Kiln Cost Functions (2005)A-2 This page intentionally left blank.

### Andover Technology Partners Page 1 May 7 , 2010

To: Elineth Torres Fm: Jim Staudt

Re: Electrical load for wet scrubbers

From my analysis it appears that there was a mistake in the original memo.
In my original memo I used the following equation: from Reference 1 that says that to estimate fan kW,
Shaft kW = Q * dp / (367,000 * fan efficiency) E.32
Where Q is in actual cubic meters per hour dp is in mm H 2 

### O
Since I didn’t develop that equation, t o be safe, I’ m going to do this from the basics

– Mechanical Engineering 101 :

Fan kW = Q (volume flowrate in cubic meters per second) * dp (pressure difference in newtons per square meter)/(1000 W/kW * fan efficiency expressed as a decimal)

From my Feb 26 memo, the gas flowrate is roughly 100000 d scf per short ton clinker. Also, from the data I was provided by Keith Barnett, the average kiln s tack tempe rature was 350 0 F (1 77 0 C)

. This will vary from one kiln to another, and the volume flow is on the high side for a precalciner or preheater kiln

– the kilns most likely to have a scrubber installed for SO 2 

### due to their size and the economi cs. Q is therefore equal to Tons per second of clinker * 100,000 dscf per ton of clinker * [ (273 0C + 1 77 0C )/273 0 C ] actual cubic feet per standard cubic feet / 35.5 cubic feet per cubic meter
Q d 

### = TP S CLINKER * 4 643 actual cubic meters per sec We usually don ’t express kiln output in tons per second of clinker. Expressing in tons per hour of clinker

1 The Cement Plant Operations Handbook, Third Edition, International Cement Review , November 2001 

# Andover Technology Partners

### Andover Technology Partners Page 2 Q d 

### = TP S CLINKER * 4 643 actual cubic meters per hour/ ( 3600 TPSCLINKER/TPHCLINKER)
Q d 

### = 1 .29 * TPHCLINKER actual cubic meters per second

This of course is dry gas volume and does not account for moisture. For a precalciner and preheater kiln s , this number is sufficiently high that it should roughly account for moisture

. For a wet process kiln it may be low. But, the dry kilns are far more important becaus e the age and inefficiency of the wet kilns is such that no one is likely to add a scrubber to them.

F or wet kilns the water content of the slurry is roughly 40%. So, that for every ton of solids fed, there is 0.67 tons of water. Since there a re 1.65 tons of raw material per ton of clinker
, for each ton of clinker there a re 1.11 tons of water

. T he volume of water vapor at 1 77 ° C and 1 atm is 2 .044 m 3 /kg water

. Therefore, for each ton of clinker

1.11 ton of water/ ton of clinker * 2.044 m3/kgwater *908 kg/ton = 2060 m3 of water p er ton of clinker
So, for wet kilns, the volume is 4643 + 2060 = 6703 m3 per ton of clinker , or
Q w 

### = TP S CLINKER * 6 703 actual cubic meters per sec , or Q w 

### = TP H CLINKER * 1 .86 actual cubic meters per sec

O r Q w = 1.44 * Q d


### Now we need to get the pressure drop ( dp ) in newtons per square meter. But, we normally have dp in inches of water. Since,

1 inch of water column = 249 Newtons per square meter = 249 Pa and
We are assuming 18 inches water column of pressure drop , which ought to be plenty. This assumes a Monsanto Environmental Control Dynawave scrubber , which has a frothing section

. For a spray tower scrubber, which ha s also been used in cement kilns, the pressure drop could be about half of that.

d p = 18 IWC * 249 Pa /IWC = 4482 Pa
And, since we will assume a fan efficiency of 0.75, we have the equation:
Shaft power in newton meters per second (or watts) = Q * dp
For a dry kiln

= 1 .29 * TPHCLINKER ( equals volume in cubic meters per second) * 4482 Newtons per square meter/0.75

### Andover Technology Partners Page 3 = 7 709 * TPHCLINKER (shaft power in watts)
For kW divide by 1000 W per kW
Shaft power in kW = 7 .709 * TPHCLINKER , or

Since TPHCLINKER is estimated as TPYCLINKER/(8760*0.9)
Shaft power in kW = 7 .709 * TPYCLINKER/(8760*0.9)
Shaft power in kW = 9 .78 E

- 4 * TPYCLINKER

Add roughly 15% for recirculating pump demands, etc. and it results in
Total power in kW (dry kiln) = 1.12 E

- 3 *TPYCLINKER
For a wet kiln, multiply times 1.44 to result in
Total power in kW ( w et kiln) = 1. 6 2 E

- 3 *TPYCLINKER

Now, to estimate the cost per year, we multiply times COSTKWH

So,

Annual Cost of Power (dry) = 1 .12 E

- 3 * TPYCLINKER * COSTKWH

Annual Cost of Power ( w et ) = 1

. 6 2 E

- 3 * TPYCLINKER * COSTKWH

Where COSTKWH is the cost of power in $/kWhr And TPYCLINKER is the annual clinker output in short tons per year

Hopefully, that spells it out a bit clearer, and it is correct. I apologize for not catching
this earlier. Keep in mind that there are several assumptions ma de along the way

– gas flowrate, temperature, pressure drop, load from recirc pumps, etc.

– that impact the actual power requirement for any particular application. I expect that the results from these calculations should be pretty representative for most applications.

### Andover Technology Partners Page 1 February 2 6 , 2010

To: Ravi Srivastava , Elineth Torres , Keith Barnett C c: Clint Burklin Fm: Jim Staudt

Re: Wet Scrubber Cost Algorithms
Industry comme nted that both the gas flowrate and the capital cost estimating approach that w ere described in my March 10 memo and used in ISIS underestimated kiln gas flowrates and kiln capital cost. In response to questions raised by industry, I am revisiting the gas flowrate estimating approach and capital cost estimates for wet scrubbers.
Background The flowrate calculation in my original Technical memo issued last spring is based upon the kiln exhaust gas flow rate information provided in Table 3.1.1 on page 247 of “Innovations in Portland Cement Manufacturing” published by the Portland Cement Associatio n, 2004, which was used to develop Table 1 of the memo I prepared on NOx, SO 2 

### and CO 2 

### emissions last spring.
Data from Table 3.1.1 that included specific fuel consumption and kiln exit gas flowrate

was converted from metric to English units for Table 1 of my March 10 memo, and the resulting flowrates were used to estimate the gas flowrate of kilns for the purpose of estimating the cost of wet scrubbers.

Evaluation of Data Industry comments suggested that the data in Table 3.1.1 of “Innovations in Portland Cement Manufact uring” underestimate actual flowrates experienced in practical cement kilns that would need to be treated with a scrubber

. Data submitted by industry (National Cement and the PCA ), and d ata provided to me by Mr. Keith Barnett of US EPA showed that the sta ck gas flow rates did, in fact, generally exceed the flowrates (expressed in terms of scf/ton clinker) that were on Table 1 of my original memo. Where this data provided oxygen concentrations, they were generally much higher than what would be expected if the gas were from the kiln alone. This indicates that there are other sources of gas flow that dilute the kiln exhaust and increase the total flowrate beyond what is expected at the kiln exit

. Therefore, while the data in my original memo may have

accur ately represented the kiln gas flow, it did not capture all of the gas that would likely be treated if a wet scrubber were installed. Data provided by Keith Barnett included data from 57 kilns including kilns of all major types. The data included informa tion on whether or not there was an alkali bypass or an in

- line raw mill. In estimating dscf per short ton of feed or dscf per short ton of clinker (assuming 1.65 tons of feed per ton of clinker) there was a relatively wide scatter from kiln to kiln, but regardless of kiln type 

# Andover Technology Partners

### Andover Technology Partners Page 2 the rates were generally in the same range

. Table 1 below shows the results of an analysis of this data. With regard to use of alkali bypass or in

- line raw mill, there was no consistent pattern (either above or below the average o r median).
Recognizing that the data showed a fairly wide scatter in reported flowrate s , it is not possible to arrive at a single value that will be precisely accurate for each kiln; however my goal was to arrive at a number that would likely be represe ntative for many facilities and for any individual facility the error would b e minimized

. Based upon the data in Table 1, and because the ISIS data is represented in the form of clinker output, I recommend using a gas flowrate equal to 100,000 dscf/ton of clinker, resulting in:

D SCFM = 100000 * TPDCLINKER/ (24*60) = 69 * TPDCLINKER E.1 TPDCLINKER = TPY CLINKER/(365*0.90) = 3.04E

- 3 * TPY CLINKER E.2

Where DSCFM is the stack flowrate of the kiln in dscfm TPDCLINKER is the capacity of the kiln in short tons per day TPYCLINKER is the capacity of the kiln in short tons per year
Equations E.1 and E.2 should be used in lieu of equations E.28 and E.29 of my original

memo. I recommend that th e s e equation s be used for all kiln types because there doesn’t seem to be enough difference between kiln type, e xcept possibly for a slight difference for preheater kilns, to warrant different numbers.

Table 1. Stack flowrates of cement kilns

dscf/short

ton feed ds cf/short ton clinker Stack Temp

- deg F number of kilns All Kilns Average 62,586 103,266 351 57 Median 59,112 97,534 330 Dry Average 64,074 105,722 379 15 Median 60,171 99,283 375 Preheater Average 62,513 97,669 438 10 Median 49,104 79,119 398 Precalciner Average 61,182 100,951 266 18 Median 56,214 92,752 259 Wet Average 63,249 104,361 363 14 Median 65,457 108,004 347 Analysis of data that was provided by Mr. Keith Barnett, US EPA, 2/24/10


### Wet Scrubber Capital Costs
My March mem o provided a means to estimate capital costs that related capital cost to flowrate. This was developed based upon information in a PCA article (SP129) by Gerald Young in 2002 entitled “Review of SO 2 

### (HCl) Scrubbers” as well as other data cited in the memo, including a PSD analysis from Florida Rock industries

. The PCA article discussed use of a scrubber at an Essroc cement kiln and provided cost information. Also cited in my earlier memo was the cost of the Lehigh Cement Mason

### Andover Technology Partners Page 3 City, IA plant, which appeared at the time to be much more costly (in $/scfm) than o ther data. Because it was much higher and because it was also part of a facility expansion, it raised some doubt about whether the cost information was comparable. It is important to note that, unlike power plants, there are very few cement kilns that have actually installed, no less retr ofit, wet scrubbers. And, the cement companies are not under an obligation similar to that of an electric utility which must publicly release information to a utility commission on project cost once executed . As a res ult, the data on actual cement kiln wet scrubber projects is very limited and it is necessary to rely on industry estimates, which may be biased. Industry provided the estimates shown in Table 2 along with estimated SCFM and $/SCFM using equation E.1. If equation E. 1 is used to estimate the gas flowrate of the 1.2 million tpy Mason City scrubber at about $28 million 1 

### , then 250,000 scfm results, and the cost is roughly $113/scfm

.

Table 2. Capital Cost Estimates Provided by PCA.

TPY Capital Cost E st

. SCFM est. $/scfm
Wet 1,300,000 $44,000,000 272,688 $161 Dry 537,201 $24,200,000 112,683 $215 Precalciner (Existing) 784,799 $24,000,000 164,619 $146 Precalciner (Proposed) 1,600,000 $19,000,000 335,616 $57 Source: PCA comments to NESHAP, Appendix 2, page 500 of 513


### The PCA paper “Review of SO 2 

### (HCl) Scrubbers” mentioned that a scrubber cost of about $30

- $60 per scfm (2 002 dollars). However, it is necessary to add a device to remove chlorides in many cases because chlorides cannot be readmitted to the kiln in the manner sulfates and sulfites could. The chloride removal equipment would add roughly another $30

- $60/scfm to the cost according to the PCA paper . I did not include the chloride removal in my prior memo because of the focus on SO 2 

### . Nevertheless, if the mid

- point of $45/scf is used for both the scrubber and the chloride removal for a total of $90/scf and this is escalated to 2007 d ollars using the CEPCI, then this results in $120/scfm (or $107/scfm if in 2005 dollars) , which is slightly abo ve the estimated cost for Mason City and slightly below the estimated cost of the existing precalciner kiln shown in Table 2 above. It is my opinion that the industry is far more likely to install scrubbers on newer kilns than older ones. This means that they are more likely to install them on precalciner and preheater kilns than on wet or long dry kilns. So, I suggest that we focus on the cost numbers above for precalciner kilns. As for the proposed kiln, this cost may be low because it is both larger and because it does not have the added cost associated with a retrofit.
Therefore, I suggest that we use $120/scfm (or $107/scfm if using 2005 dollars ) as the capital cost for a wet scrubber. So, the following equation should be used for capital cost:

1 Bahner, Icenhour, Lany, Barnett, Summary of Environmental and Cost Impacts of Proposed Revisions to Portland Cement New Source Performance Standards (40CFR Part 60, subpart F), Docket Number EPA

HQ

- OAR

- 2007

- 0877

### Andover Technology Partners Page 4 CC (2007$ ) = 120 * DSCFM E.3a CC (2005$) = 107 * DSCFM E.3b
Since, DSCFM is directly proportional to the kiln size, you could alternatively make capital cost directly related to kiln size using equations E.1 and E.2. Equations E.3a and E.3b should be used in lieu of equation E.30 of my original memo on the capital cost of scrubbers.
Operating costs of wet scrubbers

The PCA comments to the NESHAP show total annual costs that in two of the four cases
are ov er half of the capital cost, in one case are about a third of the capital cost and in another case are over one fourth of the capital cost. Since PCA did not outline the assumptions regarding capital recovery or SO 2 

### content, both of which are important factors in estimating annual costs, it is not possib le to fully evaluate these costs. However, in two of the four cases several million dollars a year are claimed to be necessary for natural gas , presumably to reheat the gas. My opinion is that this natural gas should not be necessary. Wet scrubbers don’t require r eheating of the gas because normally a new chimney is installed with a wet scrubber that is capable of handling the moisture

- laden exhaust gas

– at least that has been the experience with hundreds of wet scrubbers used in the power industry

. In the past the exhaust from the wet scrubbers was reheated. However, this was before companies realized that it was far better to install a

new stack that could handle the wet gas than use so much natural gas

. Alternatively, it m ay be possible that these facilities are also including RTO’s for VOC control and they have mistakenly included natural gas in the scrubber cost. But, in any event, natu ral gas is not needed for a wet scrubber.
Therefore, it is my opinion that the variable and fixed operating cost equations s hould be maintained as they were, except as follows:

**•** Because the gas flowrate calculations have changed, the water usage should change as well. Since the estimated SCFM have roughly doubled from the previous memo, the estimate of water usage should increase from 30 gallons per ton of clinker to 60 gallons per ton of clinker and cost increased to about $0.025 per ton of clinker.

**•** For equation E.33 of my previous memo that is used to estimate the fan power usage, substitute 100,000 for EGFW and also substitute 0.90 for 0.85 (90% capacity factor) , making it Shaft kW= (TPY CLINKER /(8760*0.90)) * 100,000 * 5.8 (10) - 5 

### =7.36E

- 4 * TPY CLINK ER E.33

**•** Because chlorides cannot be readmitted to the kiln, there is a wast e stream associated with this . The size of this stream would largely be determined by the chloride levels in the fee d materials and fuel. I do not have typical data for chloride s or what is involved in disposing of them (chlorides were not with in the scope of my analysis) ; but, the people working on the NESHAP might have that

### Andover Technology Partners Page 5 information. The cost to l andfill dry, inert material, such as coal ash, will vary by location, but from my recollection is on average about $10/ton. I do n ot know what form the chlorides would be in or i f landfill would be appropriate or if there is a beneficial use for them.

Summary
Upon review of reported data I determined that the information used to estimate kiln exhaust gas flow underestimates stack gas flow. This is because of other equipment that exists at the cement plant that dilutes the kiln exhaust, increasing total volume flow. A means of estimating the total stack flow was developed from actual plant data and provided.
Until there are some m ore scrubbers built and data more available, there will be some uncertainty in the capital cost of scrubbers. Nevertheless, a cost estimating equation was developed and this is consistent with much of the data that is available; however, some data suggests higher costs and some much lower costs. Based upon my revi ew of operating cost estimates and the aforementioned changes to gas flowrate estimates, I recommended changes to some of the operating cost equations

. Finally, I have come to learn that th e industry generally assumes a capacity factor of 90% when relating daily or hourly capacity to annual capacity rather than 85%, which is what I assumed when I wrote my original memo. This w ill have a small effect on a number of the equations developed i n the original memo

. T he effect will, in general
, result in slightly more conservative results (higher costs or flows). I will take a look at the memo and let you know what equations might need to be changed.

### Andover Technology Partners Page 6 Appendix List of Terms Term Definition 

### DSCFM TPDCLINKER TPYCLINKER is the stack flowrate of the kiln in dscfm is the capacity of the kiln in short tons per day is the capacity of the kiln in short tons per year

### Andover Technology Partners Page 1 July 10, 2009
To: Ravi Srivastava, Nick Hutson, Samudra Vijay, Elineth Torres Cc: Clint Burklin Fm: Jim Staudt
Re: GHG Mitigation Methods for Cement

The greenhouse gas mitigation methods that will be examined in this work are broken down generally into four categories:

 Energy Efficiency Options – these options will reduce the amount of fossil fuels used to manufacture cement, either directly through reduction of heat input at the plant, or indirectly though reduction of electricity demands.

 Supplementary Cementitious Materials – These are materials that can be used in lieu of manufactured Portland cement in blended cements or concrete,
and therefore do not release the CO 2 

### that is involved in production of Portland cement. Their use will mitigate the amount of CO 2 

### produced per ton of
concrete used.

 Decarbonated kiln feedstocks – These include materials that do not require calcining and are a substitute for CaCO 3 

### , which is a source of CO 2 

### emissions.

 CO 2 

### Capture and Sequestration – This is technology for capture of the CO 2 

### produced from the kiln that would otherwise be released to the atmosphere. The captured CO 2 

### would be sequestered. 

# Ando v er T echno lo gy

### Andover Technology Partners Page 2 

## Energy Efficiency Options
Reduction of energy consumption will reduce the CO 2 

### emissions either directly through reduction of fossil fuel requirements at the kiln or indirectly, through reduction of electrical demands. Energy efficiency methods are especially attractive because there is an economic as well as environmental benefit. Therefore, these methods can often be justified even absent an environmental motivation. However, an environmental
motivation in addition to economic benefits will increase the likelihood that these “low hanging fruit” approaches will be utilized.
Energy efficiency improvement options generally entail an up-front capital cost to install or modify equipment. The up-front investment is recovered over time through the realized reductions in fuel or electricity costs. Assuming similar year-to-year facility operation, the energy savings should be similar from year-to-year. Hence, these methods lend themselves to being represented economically in terms of simple payback, or how many years of savings it takes to recover the cost of the initial investment. A shorter payback period (typically represented in years) implies an economically more attractive energy savings approach – at least from the perspective of the measure of payback period. Worrell & Galitsky 1 

### developed estimates of the payback period and the energy savings of several energy saving methods. This report summarizes the capital cost algorithms that have been developed for the energy efficiency measures that are described by Worrell & Galitsky.
Summary of Capital Cost Estimation
Capital cost algorithms were developed which estimate capital cost of the energy efficiency measure in proportion to the capacity of the kiln raised to the 0.60 power as in Equation E.1. Table 1 provides a tabulation of the scale-up factors to estimate the capital cost in 2008$ of various energy efficiency measures in the cement industry using Equation E.1. Equation E.1 is developed based upon the approach described by Peter and

1 Worrell, E., and Galitsky, C. (2008). Energy efficiency improvement and cost saving opportunities for cement making an Energy Star guide for energy and plant managers. Berkeley, CA: U.S. Environmental Protection Agency, Environmental Energy Technology Division.

### Andover Technology Partners Page 3

Timmerhaus. 2 

### The scale-up factors for the energy efficiency measures are grouped according to their kiln types, wet, long dry, preheater, and precalciner. To obtain the capital costs, the scale-up factors are to be multiplied with the production capacity of a cement plant, expressed in tons of cement per year (TPY), raised to the six-tenth power :

Capital Cost ($2008) = Scale-Up Factors * Capacity 0.6 

### E. 1
The scale-up factors were calculated primarily by the payback period method or, by capital cost (in $/TPY of capacity) when capital cost information was provided by Worrell and Galitsky with a base year of the cost. In the payback period method, capital cost was back-calculated from the payback period using fuel and electricity savings provided by Worrell and Galitsky.
Payback Period Method
To estimate capital cost, and express it in dollars per tons per year of cement (TPY), recall that Capital cost (CC) divided by the value of the annual savings equal the payback period (PP) in years. So, if the value of the annual savings (S) is estimated and multiplied times the payback period it is possible to estimate the capital cost in tons per year of capacity as.
CC = S * PP E. 2 Savings (expressed in $ per ton of cement) can be estimated by Fuel Saving (MBtu/ton) * Cost of Fuel ($/MBtu) + Electric Savings (kWh/ton) * Cost of Electricity ($/kWh) = Savings ($/ton) E. 3 Capital cost will equal

Plant Capacity (in TPYCEMENT) * PP * S E. 4
The payback period in years along with the energy savings (Btu/ton of cement and kWh/ton of cement) are found in Tables 3 and 4 on pages 47-46 of Worrell and Galitzky. The body of the Worrell and Galitzky report includes a method description along with the base year of the estimate and, in a few cases, estimates of capital cost.
Energy costs were estimated from average retail price of delivered coal for industrial users in the particular year and average cost of electricity for industrial users in

2 Peters, M.S., and Timmerhaus, K.D. (1991). Plant design and economics for chemical engineers (4 th ed.) New York: McGraw-Hill, p 169

### Andover Technology Partners Page 4

the particular year of the estimate. The payback calculation yielded capital costs in dollars per ton per year of cement capacity for the year that the energy savings or the payback period was determined. Accounting for inflation through the application of a GDP deflator allowed the scale-up factors to be adjusted to 2008$. The scale up factor was determined by multiplying the average estimated cost (in $/TPY of cement capacity) times the average capacity for the applicable type of kiln (wet, dry, preheater, etc.) raised to the 0.40 power. The average capacity for the kiln type was based upon existing kiln capacity data in the Cap+Trade workbook used for ISIS. Worrell and Galitzky provided a table for energy saving methods applicable to wet kilns and another for dry kilns. So, for most energy saving methods listed for dry kilns the average capacity of all dry process kilns was used in formulating the scale up factor for dry process kilns. If a process was applicable to only one type of dry process (ie., long dry), the average capacity for that particular type of dry process was used in formulating the scale up
factor.
In some cases the body of Worrell and Galitsky provided information on capital costs, and in these cases alternative capital cost factors were developed and are shown on Table 1 for comparison. These are also in 2008 $. The Capital Cost Computations section in the Appendices contains additional information regarding the derivation of the
factors.
There are some cases where the payback period approach was not employed for technologies listed in Tables 3 and 4 of Worrell and Galitsky. The scale-up factors for indirect firing for both wet and dry kilns and for raw meal blending for the dry kiln were computed using reported figures of capital cost in $/ton of cement. In the case of indirect firing, the scale-up factor was calculated using a single point datum of an actual plant that installed the system in 1997. For raw meal blending, we used the retrofit cost of $5.61/ton of cement. The value was calculated from the reported cost of $3.30/ton of raw materials (Worrell & Galitsky, 2008, p. 22). A conversion factor of 1.7 was applied to change the cost from $/ton of raw materials to $/ton of cement since this is the rough ratio of raw materials to final Portland cement product. The Capital Cost Computations in the Appendices have further details.

### Andover Technology Partners Page 5

Table 1. Scale

- Up Factors for Use with Equation E.1 Capital Cost Estimation of Energy Efficiency Measure in the Cement Industry for Capital Costs in 2008$
Energy Saving Method From Payback Calculation From Reported Capital Cost Capital Cost Description Wet

Process Long Dry Preheater Precalci

ner Wet

Process Long

Dry Preheate

r Precalci

ner Raw Materials Preparation Efficient Transport System Minimum - 392 392 392 787 787 787 Raw Materials Blending Average - 1,181 1,181 1,181 1,181 1,181 1,181 Process Control Vertical Mill Average

- 19 19 19 High Efficiency Roller Mill Minimum - 1,352 1,352 1,352 1,458 1,458 1,458 Slurry Blending and Homogenization Maximum 1,546 -

- - Wash Mills with Closed Circuit Classifier Minimum 1,136 -

- - High-Efficiency Classifiers Minimum 553 714 714 714 451 584 584 583 Clinker Making Energy Management and Control System Average/Maximum a 207 220 220 220 Seal Replacement Maximum 6 8 8 8 Combustion System Improvement Average 370 334 334 334 188 244 244 243 Indirect Firing Average 1,986 1,986 1,986 1394 1,802 1,802 1,802 Shell Heat Loss Reduction Average 66 88 88 88 47 60 61 60 Optimize Grate Cooler Average 48 78 78 78 Conversion to Grate Cooler Average 83 101 101 101 38 50 50 49 Heat Recovery for Power Generation Average - 604 - - Conversion to Semi-Dry Process Kiln Minimum 2,455 Efficient Mill Drives Average 194 30 30 30 Finish Grinding Energy Management and Process Control Maximum 16 20 20 20 Improved Grinding Media in Ball Mills Average 178 230 230 230 High Pressure Roller Press Minimum 1,515 1,958 1,958 1,958 903 1,166 1,166 1,166 High-Efficiency Classifiers Minimum 389 545 545 545 451 584 584 583 Plant Wide Measures Preventative Maintenance Maximum 40 51 51 51 High Efficiency Motors Maximum 29 37 37 37 Adjustable Speed Drives Average 158 213 213 213 70 91 91 90 Optimization of Compressed Air Systems Maximum 86 44 44 44 Product Change Blended Cement Maximum 294 294 294 294 Limestone Portland Cement Maximum 153 153 153 153

a Average refers to the wet process; maximum refers to the dry processes.

### Andover Technology Partners Page 6 The capital costs estimated from Equation E.1 are not necessarily the average costs for all of the energy efficiency measures shown in Table 1. In some instances, the capital costs reflect not the average, but the maximum or minimum investment required based upon the payback period shown. Table 1 notes how each measure’s capital cost is to be interpreted in the column “Capital Cost Description”. The variation in interpretation is a result of how the payback period was expressed in Worrell and Galitzky. The payback period for certain measures indicates either a minimum or a maximum number of years necessary to pay off an investment. For example, installing an efficient transport system in a dry process has a payback period greater than 10 years (Worrell & Galitsky, 2008, p. 47). A scale-up factor based on this 10 year period will yield the minimum capital requirement for the measure. For some of the measures listed in Worrell & Galitsky, the scale-up factors are not available. A few of the measures, such as fuel preparation and efficient lighting, do not have the payback period necessary for computation of the capital costs. For others, computations were not performed as cost equations have already been developed in other reports. 3 

### And, a few measures were applicable only to certain types of kilns. One source of uncertainty in the data from Worrell & Galitsky is the year in which the savings and the payback period were evaluated. Worrell & Galitsky did not always report this consistently. Due to such inconsistencies, the year had to be estimated in some cases. This has an impact since energy costs were evaluated in a base year and capital costs were escalated using a GDP deflator. This may explain the differences between the scale up factors developed from the energy savings payback period method and those developed from the capital costs provided in Worrell and Galitzky. A final comment regarding estimates using this data is that it is uncertain how representative the energy savings and payback period data in Worrell and Galitsky are for applicable kilns. As a result, when using the cost estimates developed here, it should be understood that some situations may experience significantly different costs or energy savings than estimated.

3 Memo J. Staudt to R. Srivatava, S. Vijay, E. Torres, Re: Cost and Performance of Controls – revised from comments, dated March 10, 2009, pp 34-36

### Andover Technology Partners Page 7

Oxygen Enrichment
An energy efficiency technology that is not addressed in Worrell and Galitzky is oxygen enrichment. This technology has the potential to improve kiln output while potentially reducing fuel input. This is made possible by the higher heat intensity of the kiln and reduction of total gas flow for any given level of clinker production. Oxygen enrichment will require additional electrical energy for the oxygen generation, or alternatively, purchase of liquid oxygen. For oxygen enrichment, it is possible to use vacuum swing absorption (VSA) with a molecular sieve rather than cryogenic air separation because high purity oxygen is not necessary. This has the advantage of a low pressure system and reduced electrical demand compared to cryogenic air separation.
The technology is limited by:

 Increased thermal load on kiln refractory. – the increased flame temperature will cause refractory to deteriorate at an accelerated rate. While short term tests have been performed to higher enrichment rates, it has been reported that the process is limited to about 23%-25% oxygen concentration (versus 21% for normal air). 4



###  Increased NOx emissions from elevated flame temperature. – Elevated flame temperature will elevate NOx emissions. TXI reported 50% increase in NOx emissions from their wet kilns when using oxygen. But, oxygen lance position can be optimized. So, this level of NOx increase may not be typical.
Four papers on oxygen enrichment in the US provide information on the capabilities of oxygen enrichment as it is applied to cement kilns. The results and citations are shown in Table 2. In each of these cases oxygen enrichment was performed for the purpose of increasing the kiln capacity because at that time US cement demand far exceeded domestic supply. In each case kiln capacity was increased. And, in one case a decrease in fuel use was reported. The other three papers did not report a decrease in fuel use. However, ECRA has reported that an estimated reduction of 100-200 MJ/tonne of
clinker is achieved with an increase in electric demand of 10-35 kwh/tonne of clinker.

4 European Cement Research Academy, “Development of State of the Art Techniques in Cement Manufacturing: Trying to Look Ahead (CSI/ECRA Technical Papers), March 2009.

### Andover Technology Partners Page 8

The 100-200 MJ/tonne of fuel savings is roughly consistent with the 3-5% fuel savings reported by the Hercules plant.

Table 2 . Oxygen Enrichment at four US cement plants

Plant Kiln

Type Clinker

increase % Marginal Clinker increase

Tons/ton O 2 

### Fuel decrease
Midlothian Wet 6.5% Not Reported Not reported Victorville PC 3.1% 3.5 t/t Not reported Mojave PC 8.9% 4.4 Not reported Hercules PH, PC 8-10% 4.7 3-5% Sources: Mayes, G., “Oxygen Enrichment at the TXI Midlothian Cement Plant”, Cement Industry Technical Conference, IEEE/PCA Proceedings, 2001 Shafer, B., “Oxygen Enrichment at California Portland Cement’s Mojave Plant”, Cement Industry Technical Conference, IEEE/PCA Proceedings, 2001 Gotro, C., “Oxygen Enrichment at CEMEX’s Victorville Plant”, Cement Industry Technical Conference, IEEE/PCA Proceedings, 2001 Leger, C., Friday, J., “Oxygen Enrichment for Cement Kiln Firing”, Cement Industry Technical Conference, IEEE/PCA Proceedings, 2001



### At Cemex’s Victorville plant, higher total clinker increases were possible than 3.1% (estimated by 40 tpd of oxygen times 3.5 ton clinker/ton oxygen/4550 tpd of clinker), but at a lower clinker production rate per unit of oxygen (tons of clinker per ton of oxygen).
Cost of oxygen enrichment will depend upon whether or not a permanent system is desired or if a temporary system is desired. Liquid oxygen can be delivered on site and requires little equipment. However, this can cost about $0.30 per pound. 5 

### A pressure swing absorption system can provide oxygen for a price of $0.05 per pound. California Portland Cement installed a 95 TPD VSA system at its Mojave plant and they reported electrical demand of 0.01kwh/scf of oxygen (or 0.01kwh/0.089 lbm of oxygen, or 178 kwh per short ton of oxygen), and this cost (which reportedly represents virtually all of the variable cost) is reported to be roughly 30% of the operating cost at the Mojave plant. At 4.4 ton of additional clinker per ton of oxygen, his electrical demand of 178 kwh/short ton of oxygen translates to about 40 kwh per short ton of clinker. ECRA reported an

5 Remedial and Natural Attenuation Services, Inc. http://www.rnasinc.com/o2zone/productdescriptiom/Cost_Of_Oxygen_Delivery , viewed July 3, 2009

### Andover Technology Partners Page 9

electrical demand of 10-35 kwh/tonne of clinker; but, it is unclear whether this is per total clinker or additional clinker from oxygen addition.

CAPITAL COST
According to the European Cement Research Academy, capital cost is estimated at between 5 and 10 million euros for an oxygen enrichment system and an operational cost ranging from 0.5 – 2.3 euros per tonne of clinker based on clinker capacity of 2 million tonnes/year. Since the report is published in 2009, it is presumed that these are costs in 2009 euros. Using a conversion rate of $1.40/ € (July 3, 2009, Bloomberg), it is possible to convert to dollars. Using the average cost of 7.5 million euros and a plant size of 2 million tonnes/yr, the cost can be shown to be $4.77/ton per year capacity.
Using the six tenths rule, the capital cost can be estimated to be:
(2 (10) 6 

### tonnes/yr x 1.1 ton/tonne) 0,4 

### x 4.77 x TPYCLINKER 0.60



### = 1642 * TPYCLINKER ^ 0.6 E.5
Fixed Operating Cost
Fixed operating cost can be assumed to be a fraction of capital cost. For the moment, we will assume, consistent with many other technologies, $59,200/year plus 4% of capital cost.
Variable Operating Cost
Since this is predominantly power, it can be estimated as roughly 40 kwh/short ton of additional clinker times the cost of power, or COSTKWH*40*TPYCLINKER * O2ENRCLINKER. O2ENRCLINKER is the fraction by which clinker output increases.
Impacts
Clinker output: The average clinker increase from Table 2 is 6.88%, making
O2ENRCLINKER = 0.0688.
Based on the ECRA estimates and the fact that the impacts are probably mainly realized in the kiln, fuel impacts are estimated at about 0.1 million Btu/ton clinker heat input reduction for precalciner kilns and about 0.2 million Btu/ton clinker heat input
reduction for other kilns.

### Andover Technology Partners Page 10 CO2 from fuel will be reduced in direct proportion to the reduction of fuel as discussed above. There will be no impact on CO2 from calcination except that increased clinker output will increase the total CO2 from calcination in proportion to clinker output. Total CO2 from fuel and from calcination per ton of clinker, however, will drop
somewhat due to the reduction in CO2 from fuel.
Electricity demand will increase by around 20 kwh per ton of clinker (using the average of the ECRA estimates) or around 40 kwh per ton of clinker (using the data from Mojave plant).
NOx emissions will increase. TXI reported a 50% increase from a wet kiln. It is unclear how representative this is. Assuming about half of the fuel is burned in the calciner in a precalciner kiln, assume about 25% increase in NOx for precalciner kilns and 50% for others. Hopefully, we can find some data in the future that will give us a better picture.
Negligible impacts are expected for other emissions.

### Andover Technology Partners Page 11



## Supplementary Cementitious Materials (SCMs)
Supplementary Cementitious Materials (SCMs) are materials that can be used as a
substitute for Portland cement and can be blended into concrete to reduce the amount of Portland cement that is used. These materials are broadly divided into two types: cementitious materials; and pozzolans, as shown in Table 3.

Table 3 . Cements and Supplementary Cementitious Materials

Cementitious Pozzolanic (or materials with pozzolanic characteristics) Hydraulic Cements Portland cement
Blended cement

Supplementary cementitious materials GGBF Slag GGBF Slag Class C fly ash Class C fly ash

Class F fly ash Natural pozzolans (diatomite, calcined clay, calcined shale, metakaolin), Silica fume


### Portland cement clinker is a manufactured hydraulic cement – which is a cement that sets and hardens by chemical interaction with water and is capable of doing so underwater. Hydraulic cement can also be produced by blending Portland cement with SCMs. For example, Ground Granulated Blast Furnace Slag (GGBF slag – also called Slag Cement) is a cementitious material that can be blended to make hydraulic cement. Hydraulic cement can also be produced by combination of pozzolans with material providing calcium hydroxide. Some fly ashes have adequate lime present to be
cementitious.
A pozzolan, in general, is a material that when mixed with calcium hydroxide will exhibit cementitious properties. Most natural pozzolans are vitreous siliceous materials,
and these are often found in nature in volcanic rock formations. In the United States these natural pozzolans are found principally west of the Mississippi River. Clays (especially kaolin) and Shale can also be pozzolanic when calcined. 6 

### When combined with calcium hydroxide they form calcium silicates similar to Portland cement. Silica fume is a man-made pozzolan from silicon production that has limited availability; but, it

6 Actually, kaolin and shale undergo dehydroxilization rather than a release of CO 2 when heated, and this process makes them pozzalonic. So, this is different than what happens when limestone is calcined.

### Andover Technology Partners Page 12

is useful for very high strength cements. Metakaolins are produced by dehydroxilization of kaolin clays and are mainly used in white cement.
Fly ash from coal combustion is a man-made pozzolan, and it can be blended with Portland Cement. In fact, it is the SCM that is used in the greatest amounts because it is available in many locations at a reasonable in price. Fly ash also improves the properties of the final concrete for some applications, particularly with regard to sulfate resistance and strength. Some coal fly ashes are pozzolans that also contain sufficient CaO that they
are cementitious.
The advantage of SCMs is that they can be blended into concrete or cement and reduce the need for Portland cement, and therefore their use can mitigate the environmental impact of Portland cement manufacturing. The use of these materials will be limited by availability and the type of end use product that is desired. Of the SCMs shown, fly ash, blast furnace slag and natural pozzolan, are the most likely to end up in the final concrete product. Cement manufacturers generally only blend a small amount of SCMs into their cements to aid with flow or grinding. On the other hand, concrete suppliers often blend far more significant amounts of SCMs into the concrete that they supply. As a result, increased use of SCMs in the final concrete will reduce the amount of manufactured Portland cement necessary to fill the same concrete demand. However, each of these SCMs impacts the product properties, such that the amount of SCM used will differ by how the concrete is expected to be used.
The chemical compositions of the three most widely used cement substitutes - fly ash, blast furnace slag, and natural pozzolanic materials - as compared to clinker are shown in the ternary phase diagram of Figure 1. The three main mineral constituents are CaO, SiO 2 

### and Al 2 

### O. 7 

### Control of these three constituents will impact the characteristics of the cement. The close chemical resemblance of blast furnace slag to Portland cement is why it is a very useful SCM that can be blended at high rates. Fly ash is not quite as close in chemical composition to Portland cement as blast furnace slag, and for that reason fly ash is usually not cementitious unless there is also high CaO present in the fly

7 Claude LOREA – CEMBUREAU, “USE OF ALTERNATIVE FUELS AND MATERIALS IN THE EUROPEAN CEMENT INDUSTRY”, IEA meeting-4 Sept 06-Use of alternative fuels-CL

### Andover Technology Partners Page 13

ash (such as class C fly ash). Also, this is why fly ash is generally blended at lower concentrations than blast furnace slag.

Figure 1. Ternary diagram of mineral constituents in Portland cement

A term that is used to characterize the amount of SCM in a cement is the clinker ratio (CR), which is the percent of cement produced that is composed of clinker. A CR of 95% is 100% Portland cement (95% clinker and 5% gypsum). Table 4 shows the CR for five different cement grades sold by Cembureau (the European Cement Association). The five cement types referred to in this table are:
Type I: Portland Cement Type II: Portland Composite Cement Type III: Blastfurnace slag Cement Type IV: Pozzolana Cement Type V: Composite Cement The different cement types are formulated for various strength, hardening, hydration or sulfate resistance characteristics.

### Andover Technology Partners Page 14 Table 4 . Five different cement grades sold by CEMBRAU 8



### In the United States Portland cement substitutes are added in very limited amounts by the cement companies. So, such statistics as those in Table 3 for different cement types are not available for the United States. These substitutes tend to be added by the concrete companies when blending the concrete. The reason the blending occurs to a greater extent by concrete companies than cement companies is likely due to the market structure in the US, making it less expensive for concrete companies to add these materials that may be available from local markets. Also, concrete companies can blend the concrete to meet the specific needs of their market.

8 Claude LOREA – CEMBUREAU, “USE OF ALTERNATIVE FUELS AND MATERIALS IN THE EUROPEAN CEMENT INDUSTRY”, IEA meeting-4 Sept 06-Use of alternative fuels-CL

### Andover Technology Partners Page 15 Ground Granulated Blast Furnace Slag (or Slag Cement)
Blast furnace slag is the SCM that most closely resembles Portland cement. For this reason ground, granulated blast furnace slag (also known as slag cement) is a cementitious material that can be blended to high rates. Slag cement is a product of the conversion of iron ore to iron in a blast furnace. It is produced by rapidly cooling the blast furnace slag with water as it leaves the furnace to form granules. The slag granules are then dried and ground to make slag cement. Slag cement is frequently substituted for manufactured cement in ratios of about 50% by weight and potentially higher ratios, depending upon the application. Growth in the use of slag cement has been nearly 12% annually over the last ten years, with peak slag cement shipments of 3.6 million metric
tons in 2006. 9 

### There was a slight drop off in 2007 as shown in Figure 2. This was likely due to the drop off in construction that started in late 2007.
Figure 2 . US Slag Cement Shipments (source: Slag Cement Association)



### Cost of Slag Cement – Ground granulated blast furnace slag is reported by USGS to cost in the range up to about $100/ton (2008$), although prices for slags on average are
less. 10 

### This may not factor in shipping costs, which in some cases might make slag less

9 Slag Cement Association, http://www.slagcement.org/shared/custompage/custompage.jsp?_event=view&_id=445505_U128801__14 8636 10 http://minerals.usgs.gov/minerals/pubs/commodity/iron_&_steel_slag/mcs-2009-fesla.pdf

### Andover Technology Partners Page 16

attractive or cause actual price to be less to offset transportation costs. USGS reported costs for granulated (not necessarily ground granulated) blast furnace slag between $19 and $95, with the average around $80 in 2006. 11 

### Since over 90% of the granulated slag was reported by USGS to be cementitious (likely slag cement), the average is probably representative for this application. As a by-product of iron production, blast furnace slag availability will be impacted by the production levels of the iron industry. As a result, if demand for iron produced from iron ore drops, slag availability could drop as well.
Benefits of Slag Cement – Use of slag cement will offset the environmental impacts of the Portland cement it replaces on a one-for-one basis. That is to say that one ton of slag cement should offset the environmental impacts (NOx, SO 2 

### , CO 2 

### , PM and other emissions) of manufacturing one ton of Portland cement (roughly 0.95 ton of clinker). Slag cement is blended into concrete at levels of around 50%.

11 USGS: 2006 Minerals Yearbook, Slag – Iron and Steel

### Andover Technology Partners Page 17 Fly Ash
Fly ash from coal fired power plants is, by far, the most widely used SCM. In the United States fly ash is generally not blended into the cement at the cement plant, but added to the concrete during the blending of the concrete. In other countries it may be mixed with the cement. Two major classes of fly ash are specified in ASTM C 618 on the basis of their chemical composition; these are designated Class F and Class C. Class F is fly ash most often (but not always) produced from burning anthracite or bituminous coal, and Class C is most often (but not always) produced from the burning of subbituminous coal and lignite (as are found in some of the western states of the United States). Class C fly ash usually has cementitious properties in addition to pozzolanic properties due to available free lime, whereas Class F is rarely cementitious when mixed with water alone. In most states fly ash as an SCM is limited to about 15%-25% of the concrete, at least for highway purposes. Both fly ashes, if high in quality, are desirable for blending into concrete due to strength and sulfate resistance characteristics. 12


### Fly ash mineral oxide constituents for different fly ash types are compared to those of Portland Cement and Slag Cement in Table 5. 13 

### As shown, Class C fly ash has a much higher CaO content than Class F fly ash, which is why it often has cementitious properties while type F generally does not. For any given fly ash, actual mineral matter content could differ significantly from these values.

Table 5. Comparison of Portland Cement, Slag Cement, Class C Fly Ash and Class F Fly Ash Source: Slag Cement Association

12 US DOT Federal Highway Administration, www.fwha.dot.gov/infrastruction/materialsgrp/flyash.htm 13 Slag Cement Association, “Slag Cement And Fly Ash”, www.slagcement.org

### Andover Technology Partners Page 18 According to the American Coal Ash Association’s 2007 Coal Combustion Product Production & Use Survey, of about 72 million short tons of ash produced, almost 14 million short tons (19.4%) were used in concrete and concrete products. Another 3.6 million short tons were used in blended cement or as raw feed for clinker production. Of the total fly ash produced, about 32 million short tons (44.4% of the total) were somehow beneficially reused. The balance – about 40 million short tons – was not beneficially
reused.
Although this suggests an ample supply of fly ash for increased use in the concrete or cement industry, usefulness for any particular application is limited by:

 Quality and consistency – for concrete blending the fly ash must meet fairly stringent quality specifications and have good consistency. The best quality fly ash generally comes from base loaded power plants that can closely control conditions. When used as a feed material for a kiln (either as a fuel or a raw material) fly ash quality is less critical, but is not unimportant.

 Local market factors – Fly ash is heavy and can only be economically used in regional markets. As a result, in some regions there may be a shortage of fly ash while in other regions there might be more than adequate supply. Costs of Fly Ash as an SCM - According to Robl, 14 

### in 1997 the price of high quality fly ash pozzolan was in the range of $25-$30 per ton while displacing an equivalent weight of cement at a cost of about $70-$80/ton (all in 1997$). Since these prices are market based, they likely move in proportion to the price of cement. And, this does not factor in the cost of transport. According to Robl, in 1997 the cost of transporting fly ash by pneumatically-loaded trailer truck was roughly $0.10 to $0.13 per ton per mile. It is likely that these transportation costs are similar for other heavy, powdery materials, such as cement or ground limestone.
Benefits of Fly Ash as an SCM – Since the fly ash is blended into concrete and offsets Portland cement, it should reduce the environmental impact of Portland cement manufacture when used roughly on a one-to-one basis. That is to say that one ton of fly ash should offset the environmental impacts (NOx, SO 2 

### , CO 2 

### , PM and other emissions)

14 Robl, T., McCormick, C., “We Are Running Out of Fly Ash: The Nature of Regional Supply Problems”, 3 rd Conference on Unburned Carbon in Fly Ash, Pittsburgh, PA, May 13-14, 1997

### Andover Technology Partners Page 19

of manufacturing up to one ton of Portland cement (roughly 0.95 ton of clinker and 0.05 ton of gypsum). At very high replacement rates where it may be necessary to add additional CaO, some of the benefits may not be on a one-for-one basis. However, fly ash blending rates are limited, particularly for highway use. Fly ash is blended into concrete at levels that are limited up to around 15%-25% in the US. So, a reasonable average to assume is up to 20%. This is a somewhat lower blending rate than in Europe,
as demonstrated in the data of Table 3.

### Andover Technology Partners Page 20 Natural Pozzolans
Natural pozzolans are only available in certain locations and are therefore not as widely used as slag cement or fly ash. Diatomite is one pozzolanic material that is often used as an SCM. According to USGS, 26% of the 654,000 tons of diatomite, or 170,000 tons, was used for cement applications in 2008. This compares to millions of tons of fly ash or slag cement that is used. There are 7 diatomite-producing companies with 12 mining areas and 9 processing facilities in California, Nevada, Oregon, and Washington.

15 

### Other pozzolans include calcined clay and shales. Clay and shale are normally used (and in large quantities) in the production of Portland cement since calcination will be performed in the cement kiln. 16


### Cost of Natural Pozzolans Diatomite was reported to cost under $9.00 per ton (FOB plant). Clay and Shale was reported to cost about $11/ton (FOB plant). 17


### Benefits of Natural Pozzolans
These materials are not cementitious, and therefore require CaO to be provided by other materials that provide the CaO. However, the addition of pozzolans should mitigate the use and impacts of Portland cement on a roughly one-to-one basis. That is to say that one ton of pozzolan should offset the environmental impacts (NOx, SO 2 

### , CO 2 

### , PM and other emissions) of manufacturing one ton of Portland cement (roughly 0.95 ton of clinker). At very high replacement rates where it may be necessary to supplement CaO, some of the benefits may not be on a one-for-one basis. Because of their limited availability and far less use than fly ash or slag cement as an SCM, it may not be useful to include natural pozzolans in the ISIS model.

15 USGS: http://minerals.usgs.gov/minerals/pubs/commodity/diatomite/mcs-2009-diato.pdf 16 USGS: http://minerals.usgs.gov/minerals/pubs/commodity/clays/myb1-2007-clays.pdf 17 USGS: http://minerals.usgs.gov/minerals/pubs/commodity/clays/mcs-2009-clays.pdf

### Andover Technology Partners Page 21 

## Decarbonated Kiln Feedstocks (DKFs)
Previous work described the use of steelmaking slag as a substitute or additional material for input to a kiln to produce clinker. Steelmaking slag as a kiln feed reduces the amount of limestone that must be calcined per ton of clinker produced. This helps to
reduce CO 2 

### emissions per ton of clinker produced by the kiln. Other sources of calcium that do not require calcining will provide similar benefits as those described for steel slag when using the CemStar process.
Table 6 shows data collected from the USGS regarding the amounts of materials that were used in producing clinker and in producing cement in 2005 and 2006. Of all of the calcareous materials, all require calcination (lime is calcined limestone and marl is made of clay and calcium carbonate). A number of the siliceous materials can also be a source of calcium, such as coal ash or slag, and these are highlighted in yellow.
The Costs of Using Decarbonated Kiln Feedstocks - Use of decarbonated kiln feedstocks requires a relatively modest capital cost that is primarily for material handling equipment. This is discussed in the description of the CemStar process in a previous

memo. 18 

### The cost of steel slag will vary, as shown in Table 7 which shows the costs of iron and steel slag reported to USGS in 2005 and 2006. 19 

### Blast Furnace Slag used as kiln feed is likely less expensive than Slag cement, and the costs of the air cooled blast furnace slag and the lower end of the cost of granulated blast furnace slag are probably most representative for this application.

18 Memo J. Staudt to R. Srivatava, S. Vijay, E. Torres, Re: Cost and Performance of Controls – revised from comments, dated March 10, 2009, pp 34-36 19 USGS: 2006 Minerals Yearbook, Slag – Iron and Steel

### Andover Technology Partners Page 22 TABLE 6

### Andover Technology Partners Page 23 TABLE 7

The value of fly ash used as a kiln feed is likely to be significantly less than fly ash that is blended directly into concrete. To estimate this value, power plant fly ash revenue data was evaluated. Figure 3 shows a plot of the cumulative percent of plants that reported fly ash revenue received (in $/ton) at or below a given price. This data was derived from reported data from the EIA 767 reports for the year 2005 (no later data is available since DOE changed their reporting requirements) and fuel data from EIA 423 for that year. The median reported fly ash value is about $5=$10/ton or less, regardless of fuel type, and this is consistent with the estimated cost of slag for this purpose. So, $5-$10/ton may be a reasonable assumption for kiln additives. As shown, there are a significant number of facilities that are capable of selling their fly ash at prices well above the median price of $10/ton. These plants are most likely selling their ash for blending with concrete.
Use of decarbonated kiln feedstocks will also reduce heat input by reducing the amount of energy necessary to calcine the feed materials. This should result in energy savings per unit of clinker produced. How to estimate this will be described in the following section.

### Andover Technology Partners Page 24 Figure 3. Cumulative Percent (by number) of Plants Reporting in 2005 Fly Ash Revenue Below Value Developed from EIA Form 767



### Benefits of Decarbonated Kiln Feedstocks - Based upon the CaO content of decarbonated feedstocks, it is possible to estimate the avoided CO 2 

### emissions when comparing their equivalent CaO content to that of Clinker (the end product) and that of
Limestone. Table 7 shows the amount of CO 2 

### emissions from calcination that is avoided using these feedstocks. These were calculated based upon the CaO content shown. Table 7 also shows the estimated energy reductions. Having CaO present already will mitigate energy demands that would be necessary to dissociate CaCO 3 

### from limestone. The energy associated with dissociation of CaCO 3 

### to CaO is 2.45 million Btu/ton of CaO. 20


### The reduction in CO 2 

### released from the reduced heat input will be determined by the particular fuel used. For example, in the case of a kiln burning Rosemont PRB coal, which produces 187 lbs CO2/million Btu 21 

### , use of one ton of steel slag as a kiln feed

20 Ha n s o n , G.
, “ E n e r g y E f f icie n c y I m

p r o v e m e n t I d e a s & P r o

jec ts f o r L i m e R e c o v e r y K il n S y s te m s ”
, Vir g i n ia- C a r o li n a & S o u th e a s t e r n T A P P I L o c a l S e c ti o n s , F e b r u a r y 1 7 , 2 0 0 5
, R o c k Hil l, S C

. 21 M e m o J

. S tau d t to R

. S r iv a ta v a , S

. Vij a y , E

. T o r r e s , R e : NO x , S O 2 a n d C O 2 e m is s io n s f r o m C e m e n t Kil n s , d a ted M a r c h 1 0
, 2 0 0 9 , T a b le 3

### Andover Technology Partners Page 25

would reduce CO 2 

### from calcination by 0.51 tons and would reduce CO 2 

### from fuel burning by 297 lbs, or another 0.15 tons, for a total reduction of 0.66 tons. Since one ton of steel slag is equivalent in CaO to one ton of clinker, these reductions of CO 2 

### per ton of steel slag will equal the reductions of CO 2 

### per ton of clinker.
From the data in Table 6, it is estimated that 2.8% of total feedstocks to produce clinker were fly ash in 2006. The limit on the use of fly ash use will be determined by the mineral content of the fly ash relative to the clinker and the other available feedstocks at the site. So, it is hard to characterize how high the fly ash addition rate could be increased. But, the upper limit would likely be less than that of the blending rate for concretes. So, perhaps up to 10% kiln feed may be used.
CO2 reduction (tons) = CAR * TONSDKF E.6

Where TONSDKF are the tons of the decarbonated kiln feedstock used and CAR
is the CO2 Avoidance Ratio from Table 8.

Table 8. Limestone Equivalence Ration, Clinker Equivalence Ratio, Calcination CO2 Avoidance Ratio, and Heat Input Reduced for various kiln feedstocks

% CaO Limestone

Equiv. Ratio 1 Clinker Equiv.

Ratio 2 Calcination CO 2

Avoid Ratio 3 Heat input

reduced 4 Variable designation %CAO LER CER CAR HIR Clinker 65% 1.16 1.00 NA NA Blast Furnace Slag 45% 0.80 0.69 0.35 1.10 Steel Slag 65% 1.16 1.00 0.51 1.59 Class C Fly Ash 25% 0.45 0.38 0.20 0.61 Class F Fly Ash 3% 0.05 0.05 0.02 0.07 Limestone (as CaCO 3 ) 56% 1.00 0.86 0 0 1. tons of limestone (as CaCO 3 ) that provide same CaO as ton of material 2. equiv. ton clinker produced per ton material used based on CaO equivalence 3. Tons of released calcined CO 2 avoided per ton of material used in lieu of limestone 4. Million Btu reduced heat input for each ton of material used in lieu of limestone



### In a previous memo a parameter called CASUB was used to estimate the amount of CO2 reduced by DKFs. 22 

### CASUB can be estimated by dividing the limestone equivalent of the substituted material divided by the total equivalent limestone (substitute plus limestone added) to equal:

22 See equation E.4 of Memo J. Staudt to R. Srivatava, S. Vijay, E. Torres, Re: NOx, SO 2 and CO 2 emissions from Cement Kilns, dated March 10, 2009,

### Andover Technology Partners Page 26 CASUB = LER*TONSDKF/ [(LER*TONSDKF) +TONSLIMESTONE* PURLIMESTONE] E. 7
Where LER is the limestone equivalent ratio from Table 8, PURLIMESTONE is the purity of the limestone as CaCO 3 

### , TONSLIMESTONE is the tons of limestone used.
Thie analysis in the previous memo regarding addition of steel slag, or CEMSTAR, 23 

### did not include the effect of energy savings on CO 2 

### emissions or on energy
costs. CO 2 

### emissions reduction can be determined by:

CO2 avoided from fuel (lbs per ton clinker) = CASUB*(HIR / CER) * LBCO2MMBTU E.8
Tons CO2 avoided per ton of clinker (calcination and fuel) = CASUB*[(HIR / 2000*CER) * LBCO2MMBTU + 0.51 * MCLINKER] E.9
Where from Equation E.6, CASUB = LER*TONSDKF/[(LER*TONSDKF) +TONSLIMESTONE* PURLIMESTONE]

CO2TOTAL (in short tons) = MCLINKER*[(LBCO2MMBTU/2000)*(SFC- CASUB*(HIR / CER)) +0.51* (1–CASUB)] E.10

Fuel Cost Reduction – This was previously mentioned. This can be estimated by Fuel Cost (in $/million Btu) * Heat input reduction (million Btu per ton clinker) = Fuel

Cost (in $/million Btu) CASUB*(HIR / CER) E.11
The value of the fuel savings is determined by multiplying the results of equation E.10 by the cost of fuel. For example, there will be a fuel cost reduction as a result In the case of the steel slag, the value of energy savings per unit of clinker produced will be the CAR * 1.59 million Btu/ton of material *(1.0 ton of material per ton of clinker produced)* the fuel cost in $/million Btu.

23 Memo J. Staudt to R. Srivatava, S. Vijay, E. Torres, Re: NOx, SO 2 and CO 2 emissions from Cement Kilns, dated March 10, 2009. Also note corrections to some equations in this memo that are included in the Appendices

### Andover Technology Partners Page 27 

## Carbon Capture and Sequestration

Carbon capture at a cement plant has not been performed. IEA has performed a study of carbon capture, primarily focusing on new plants 24 

### . This is the most recent and comprehensive study that I am aware of. The European Cement Research Academy (ECRA) also undertook a study. 25 

### The two technologies that were examined in greatest
detail are:

 Oxycombustion

 Solvent capture and stripping (Amine-based) The Oxycombustion approach results in a concentrated CO 2 

### exhaust stream from the kiln that can be compressed and sequestered. In oxycombustion, nitrogen is removed from the combustion air that is introduced to the kiln/precalciner with an air separation unit. This leaves a stream that is high in CO 2 

### after combustion and calcination. To avoid overheating of materials, CO 2 

### is recirculated to maintain a similar total volume of gas as in a normal kiln. Because oxycombustion represents a major process modification to the cement-making process, and it is unclear if the calcination reactions will be effective at the same temperatures under a high CO 2 

### partial pressure, the IEA study determined that oxycombustion is best applied to new facilities.
Solvent capture and stripping entails removal of CO 2 

### from the exhaust gas stream, and re-release in a concentrated form that is subsequently compressed for storage. Solvent capture, being an “end of pipe” technology, could potentially be retrofit to existing facilities as well applied to new facilities. Solvents include monoethanolamine (MEA), MEA with additives to improve performance, and related amine chemicals. The solvent capture process requires extremely low SO 2 

### and NOx concentrations to avoid high solvent attrition. So, scrubbers and SCR may be necessary, and are assumed to be so in the study by IEA. Further, solvent capture and stripping requires substantial steam requirements to heat the solvent for release of CO 2 

### and regeneration of the solvent. So,

24 IEA Greenhous Gas R&D Programme, “CO2 Capture in the Cement Industry”, Technical Study, Report Number 2008/3, July 2008. 25 European Cement Research Academy, Technical Report TR 044/2007, “Carbon Capture Technology - Options and Potentials for the Cement Industry”. 3 July 2007

### Andover Technology Partners Page 28

the EIA study assumed that a small combined heat and power (CHP) plant would have to be provided on site.
Other technologies are under development and may offer advantages to these two technologies once they are at a more mature state. However, at this point other technologies are at development stages that are too early to develop reasonable cost and performance estimates.
The EIA study estimated the capital cost, fixed operating cost, and variable operating cost of a one million metric ton (tonnes) per year cement plant (910,000 tonnes per year of clinker) three ways: 1) without carbon capture and storage; 2) with oxycombustion carbon capture and storage; and 3) with solvent-based carbon capture and storage. For these three plant conditions, the costs (in million € or € /year) are shown in Table 9. Based upon these estimates, it is also possible to assume a cost of retrofit of a Solvent CCS system to an existing one million tonne per year cement plant assuming that there is a retrofit difficulty factor of 1.3 to account for the additional difficulties associated with retrofitting an existing facility. This retrofit difficulty factor is typical of what is used for power plant flue gas desulfurization systems. 26 

### Because CCS has never actually been applied to a cement kiln, these costs should all be regarded as preliminary.

Table 9 . Costs of CCS Cement Plants (all in 2008 € )
Cost/Emissions New Cement Plant Total Cost Retrofit Cost Base Plant Oxycomb. CCS Solvent CCS Solvent CCS Capital cost Million € 263 327 558 383.5
Fixed Operating Cost Million € /year 19.1 22.8 35.3 16.2
Variable Operating Cost Million € /year 16.8 21.9 30.9 14.1

CO 2 

### Emitted, tonnes/y 1,256,158 282,853 188,424 188,424 CO 2 

### Captured, tonnes/y 0 465,014 1,067,734 1,067,734 Percent Capture 0% 62% 85% 85% Percent below Base 0% 73.5% 85% 85%

26 Staudt, J., Khan, S., “Updating Capital Cost of SO 2 Control Technologies in the Integrated Planning Model and the Coal Utility Environmental Cost Model”, EPRI-DOE-EPA Combined Utility Power Plant Air Pollution Control Symposium, The MEGA Symposium, Baltimore, MD, August 28-31, 2006

### Andover Technology Partners Page 29 We can develop algorithms from these estimated costs to estimate the cost of CCS on cement kilns of various sizes. As noted above, the costs are preliminary. So, any algorithms developed from these costs should be regarded as preliminary as well.
Since these costs are represented in € and are for plants sized in metric tonnes of cement, we need make some adjustments. Data on page 5 of the EIA report shows a $/ € conversion rate of $161= € 107. The costs are for a 910,000 tonne per year of clinker plant, which is nearly exactly equal to a one million short ton per year of clinker plant. Table 10 is derived by converting the values shown in Table 9.

Table 10 . Costs CCS Cement Plants Based on IEA Study (2008$ assuming $1.5= € 1.0, one million tpy clinker)

variable cost New Cement Plant Total Cost of Plant and CCS Retrofit Cost CCS only Base Plant Oxycomb.

CCS Solvent

CCS Solvent CCS
CAPCO2 Capital cost

Million $ $396 $492 $840 $577
FOCCO2 Fixed Operating Cost

Million $/year $29 $34 $53 $24
VOCCO2 Variable Operating

Cost Million $/year $25 $33 $47 $21

The cost of the base plant does seem high when compared to costs from other sources and described in a previous memo. 27 

### So, simply applying a conversion rate to the cost reported in euros in the IEA study appears to overstate the cost in dollars. For example, Essroc announced plans to spend $400 million to build a 1.8 million tpy cement plant (probably about1.6-1.7 million tpy of clinker for about $233/tpy of clinker) in Virginia 28 

### , or under 60% of what is indicated in the data in Table 10. The apparently high capital cost shown in Table 10 is possibly because the use of the exchange rate to convert the costs in Table 9 from euros to dollars assumes purchasing power parity between the costs of cement plants in the EU and the US, and this likely is not actually true in the case of cement plants because they are not goods that can be traded between

27 Memo J. Staudt to R. Srivatava, S. Vijay, E. Torres, Re: Cost and Performance of Controls – revised from comments, dated March 10, 2009, pp 34-36 28 Umstead, M., “Cement plant expansion to cost about $400 million”, The Herald Mail, January 25, 2008; http://www.herald-mail.com/?cmd=displaystory&story_id=184298&format=html

### Andover Technology Partners Page 30

countries cheaply or easily. As a result, the exchange rate between euros and dollars at a point in time may result in incorrect translation of cost from euros to US $ because the exchange rate changes very quickly – far faster than the actual price of the cement plant equipment. So, it may be necessary to revisit these numbers– scale them down perhaps. But, that is something that should be discussed.
Capital Costs
In any event, capital cost algorithms can be developed in the form of scaling capacity for a given kiln to the 0.6 power. For new plants, this is straightforward since the algorithms were based on new plants. Using the capital costs from the above tables (in million $), designated CAPCO2, the capital cost can be determined by the following: Capital cost (in million $) = CAPCO2*(1,000,000)^0.4*(TPYCLINKER)^0.6 Capital cost (in million $) = CAPCO2*251*(TPYCLINKER)^0.6 E.12
Where TPYCLINKER is the rated capacity of the kiln in short tons per year.
For retrofit plants, which will only apply to solvent technology, like a wet FGD system the capital cost is most likely proportional to the gas flow being treated, which will differ by kiln type for any given kiln capacity. The simplest approach would be to
scale costs to the EGFW. 29 

### The costs on Table __ that are based on the IEA study presume a modern precalciner kiln. So the costs should roughly be: Capital cost (in million $) = CAPCO2*251*(TPYCLINKER*EGFW/44878)^0.6 Capital cost (in million $) = CAPCO2*0.406*(TPYCLINKER*EGFW)^0.6 E.13 Fixed Operating Costs
Fixed operating cost can be scaled in much the same way. For any new kilns,

Fixed Operating Cost (in million $ per year) = FOCCO2*251*(TPYCLINKER)^0.6 E.14 For retrofit of Solvent technology on an existing kiln,

Fixed Operating Cost (in million $ per year = FOCCO2*0.406*(TPYCLINKER*EGFW)^0.6 E.15

29 Memo J. Staudt to R. Srivatava, S. Vijay, E. Torres, Re: NOx, SO 2 and CO 2 emissions from Cement Kilns, dated March 10, 2009, Table 1

### Andover Technology Partners Page 31 Variable Operating Cost
Variable operating cost for oxycombustion should probably be scaled in direct proportion to the size of the kiln. Since oxycombustion is assumed to be applicable only to new kilns, kiln type is not likely to differ, and VOC for oxycombustion should be directly proportional to the size of the kiln.
For Oxycombustion: VOC (in million $ per year) = VOCCO2 * TPYCLINKER/1,000,000 E.16

For Solvent CCS:
For a new kiln, the total VOC for the plant when a kiln is equipped with solventbased CCS can also be regarded as proportional to the size of the kiln, and Equation E.15
can be used.
For a retrofit of the solvent CCS, another approach is needed for estimating the VOC associated with the CCS. For the Solvent technology, it is reasonable to assume that the variable operating costs are roughly in proportion to the CO 2 

### levels being treated.
Recalling from a previous memo: 30



### CO2FUEL (in Short tons) = (LBCO2MMBTU/2000) * SFC * MCLINKER
And, CO2CLINKER (in Short tons) = 0.51 * MCLINKER * (1 – CASUB)
So that the annual tpy of uncontrolled CO 2 

### emissions are:
CO2UNCYR = TPYCLINKER * [LBCO2MMBTU/2000) * SFC + 0.51 * (1 – CASUB)] E.17 With CO2UNCYR expressed in short tons per year. VOC for Solvent capture should be roughly in proportion to CO2UNCYR. So, that Variable Operating Costs (in million $/year) = VOCCO2 * CO2UNCYR/(1,256,158*1.1)

Variable Operating Costs (in million $/year) = VOCCO2 * CO2UNCYR/(1,381,774) E.18

30 Memo J. Staudt to R. Srivatava, S. Vijay, E. Torres, Re: NOx, SO 2 and CO 2 emissions from Cement Kilns, dated March 10, 2009,

### Andover Technology Partners Page 32 Other effects
Both of the carbon capture approaches have other impacts on emissions and resource or energy consumption. The cost impacts of the resource or energy consumption are incorporated into the costs described earlier.
Oxycombustion Impacts –
Oxycombustion requires a substantial increase in electricity consumption over the base new cement plant. The base cement plant consumes about 80,809 MWh per year (80.8 KWh/ton of clinker) as compared to about 174,562 million MWh per year (174.6 KWh/ton of clinker) for the oxycombustion plant – or more than doubling of electric
load.
Solvent CCS Impacts –
For solvent CCS systems, the addition of the combined heat and power plant increases coal usage but results in less net electricity demand due to the on-site generation.
Table 11 shows the resource use for cement kilns using different carbon capture methods from the IEA study. For cooling water, seawater used for cooling was combined with other cooling water.
Other emission impacts

NOx and SO 2 

### emissions are near zero for each of the CO 2 

### capture methods. NOx
and SO 2 

### must be very low for solvent-based systems to work effectively. Therefore, upstream NOx and SO 2 

### removal – which are incorporated into the cost of the solvent CCS system - reduce the concentration of NOx and SO 2 

### to very low levels. For oxycombustion, the NOx and SO 2 

### are condensed into acids during compression of the
CO 2 

### -rich exhaust gas.

### Andover Technology Partners Page 33 Table 1 1 . Resource Usage of Cement Kiln (one million tpy clinker)

variable Resource New Plant Retrofit CCS only Base Plant Oxycomb.

CCS Solvent

CCS Solvent CCS
COALPY Coal or Coke (tpy) 105,000 109,000 356,000 251,000 ELECPY Electricity

(MWh per yr) 80,809 174,562 -22,734 -103,543

H2OPY Process Water

(tpy) 264,000

- 429,000 165,000

H2OCOOLPY Cooling Water

(million tpy) - 14.3 4.82 4.82
All mass units in short tons, converted from data in EIA Study Power for solvent CCS is net of cement plant and combined heat and power plant

### Andover Technology Partners Page 34 Appendices

### Andover Technology Partners Page 35

Capital Cost Algorithmns
The following elucidates the derivation of the scale-up factors used for the calculation of capital costs for energy saving methods. Equation E.1 Capital Cost ($2008) = Scale-Up Factors * Capacity 0.6 

### (A1)
is based on the sixth-tenth factor rule for computing capital costs. This rule appears as follows (Peter & Timmerhaus, 1991, p. 169): Cost of Equip. a = Cost of Equip. b * (Capac. Equip. a / Capac. Equip. b) 0.6 

### (A2) where Cost of Equip. a = Cost of Equipment a Cost of Equip. b = Cost of Equipment b Capac. Equip. a = Capacity of Equipment a Capac. Equip. b = Capacity of Equipment b The scale-up factor is defined as:

Scale-up Factor = Cost of Equip. b / (Capac. Equip. b) 0.6 

### (A3) This can alternatively be determined by:

Scale-up Factor = ($/annual capacity) * (Base capacity)^0.4 (A4) Where the Base Capacity is equal to the capacity level that is the basis of the $/annual capacity estimate. As indicated in Equation A3, two variables are essential to the calculation of the scale-up factor: the cost of a base equipment, which is shown as Cost of Equip. b, and the capacity of this equipment. For the determination of the scale-up factor in Equation 1, the base capacity is the median or the average capacity of cement kilns in the U.S. These capacities are organized by kiln types as follows:

Kiln Type Unit Average Capacity Wet Tons per year 338,740 Long Dry Tons per year 310,064 Preheater Tons per year 498,301 Precalciner Tons per year 1,101,045 All Dry Tons per year 643,039 All Kilns Tons per year 559,440

Note: Determined from Cap+Trade Workbook

### Andover Technology Partners Page 36 To calculate the Cost of Equip. b, this project obtains the capital cost of the equipment in $/ton of cement and multiplies it with the base capacity. To find the capital cost ($/ton of cement), the project relies on two methods. The primary method is to use the payback period. The capital cost can be computed from the payback period as shown:

Capital Cost = Payback Period X Total Savings (A5)

where Capital Cost = $/ton of cement Payback Period = Time it takes to pay off an investment, year Total Savings = Fuel Saving + Electricity Saving, $/( ton of cement * year)

As noted in the Summary section, the payback period along with the savings of fuel and electricity consumptions are contained in Worrell & Galitsky. The document, however, expressed the savings for fuel as MMBtu/ton of cement and for electricity as kWhr/ton of cement (Worrell & Galitsky, 2008, pp. 47-48). Since it is $/ton of cement that is required, both the fuel and electricity savings have to be adjusted. The fuel was assumed to be coal. So, the fuel savings were multiplied with the price of coal ($/short ton), its high heating value (Btu/lb), and various conversion factors to obtain $/ton of cement:

Fuel Savings = Fuel Savings o 

### * Price of Fuel (A6)

(HHV of Fuel) * CF 1 

### * CF 2


### where Fuel Savings = Savings in coal consumption, $/ton of cement Fuel Savings o 

### = Savings in coal consumption, MMBtu/ton of cement Price of Fuel = Price of Coal, $/ton of coal HHV of Fuel = High Heating Value of Coal, Btu/lb CF 1 

### = Conversion factor 1 

### , 2000 lb/ton CF 2 

### = Conversion factor 2 

### , MMBtu/10 6 

### Btu The high heating value (HHV) of coal, Btu/lb, was calculated by multiplying the average HHV of two coal ranks, bituminous and sub-bituminous coals, with their proportion: Average Coal HHV =

Σ [(Average HHV of Coal Rank) * (Proportion of Coal Rank)] (A7)

### Andover Technology Partners Page 37 The HHV of the individual coal rank was obtained by averaging its range. For bituminous coal, the HHV range is 10,500 – 14,000 Btu/lb; for sub-bituminous coal, it is 8,300 – 11, 500 Btu/lb (Kitto & Stultz, 2005, p. 9-6). The proportion of each coal rank was assumed to be 50% each. As a result of Equation A7, the average coal HHV was determined to be 11,075 Btu/lb. The price of coal used is the average delivered coal price to other industrial users. They are contained in the Coal Annual Report generated by the EIA and in the website http://www.eia.doe.gov/cneaf/coal/page/acr/backissues.html. For electricity consumption, to change the savings from kWhr/ton of cement to $/ton of cement, the former was multiplied with the price of electricity ($/kWhr):

Electricity Saving = Electricity Saving o 

### * Price of electricity (A8)

where Electricity Saving = Saving in electricity, $/ton of cement Electricity Saving o 

### = Saving in electricity, kWhr/ton of cement Price of electricity = Retail price to industrial users, $/kWhr

The price of electricity is the average retail price to industrial users and is found on the EIA website in two separate tables. One table has the average price of electricity from 1940 to 2007. (EIA, n.d.). For the latest 2008 data, the project consulted another table (EIA, 2009).
Note that the prices of electricity and fuel correspond to the year in which the savings or the payback period was determined. The time period, however, cannot always be gauged precisely. For some of the measures, it had to be estimated or assumed. This is because the source document did not always specify a time period for the savings and the payback period. When dates are missing for all three variables, the project used the publication year of the source document 2008 for its calculation. In cases where the date of only one variable is known (i.e. the date of the electricity saving is given, but not for the fuel savings or the payback period), this one available date is utilized. Furthermore, the project assumed that the date is applicable to the other two variables as well. In some instances, there is a surplus of dates. Various years of publication can be given for a

### Andover Technology Partners Page 38

single variable. In this situation, the project chose the latest date. The same approach is adopted when the dates of the variables are not compatible with one another.
Before multiplying the total savings with the payback period in Equation A4, the project also estimated the value of the individual measure’s savings. The source document expressed the fuel savings as either an average value or a range of values. If the savings appeared as a range, the project averaged them. For the payback period, Worrell & Galitzky listed it in one of four ways: (a) an average, (b) a range (c) a minimum or (d) a maximum. The project treated the payback period range the same way as it did the savings. With the minimum and maximum payback period, the project used
them as the minimum or maximum floors for calculations.
As a result of the variation in the expression of the payback period, there is no consistent interpretation of the capital cost in this project. The interpretation varies depending on how the cost was calculated from the payback period. If the maximum payback period was utilized, the capital cost would be the maximum required and conversely, if the minimum was utilized, the capital cost would be the minimum required.
Besides averaging the data ranges, the project also modified the high and low values of one energy efficiency measure. According to the source document, the electricity savings on the process control of a vertical mill was 0.8 – 1 kWhr/ton of raw material (Worrell & Galitsky, 2008, p. 22). This same figure, however, was also used to reflect the electricity savings in kWhr/ton of cement (p. 47). To convert the savings to ton of cement, this project utilized a factor of 1.7. This led to a saving of 1.4-1.7
kWhr/ton of cement.
The factor of 1.7 was derived from the basis that one ton (750 grams) of clinker can be obtained from 1.53 tons (1150 grams) of dry raw materials (European Commission, 2001, p. 22). This basis excluded gypsum and moisture. Accounting for gypsum, which made up about 5% of the cement product, the dry raw material usage increased to 1.61 tons per ton of cement. After moisture, which was assumed to constitute approximately 5% of raw materials, was incorporated, the final raw material requirement grew to roughly 1.7 tons per ton of cement.

### Andover Technology Partners Page 39 The application of the 1.7 factor is consistent with how the authors of the source document treated the savings of other measures of dry processes that are expressed in kWh/ton of raw materials. As shown in Table A.2, the electricity savings of these measures increase by a factor of 1.7 when their unit was changed from $/ton of raw materials to $/ton of cement.

Table A.2
Differences between Values Reported in $/tons of raw materials and $/ton of cement for Dry Processes
Efficiency Measure Reported

Value Unit Table Value Unit

Efficient Transport System 1.9 $/tons of raw materials 3.2 $/ton of cement

Raw Meal Blending 0.9-2.3 $/tons of raw materials 1.5-3.9 $/ton of cement

High Efficiency Roller Mill 6-7 $/tons of raw materials 10.2-11.9 $/ton of cement

High Efficiency Classifiers 2.5-3.4 $/tons of raw materials 4.3-5.8 $/ton of cement

Note: Both the reported and the table values are from Energy Efficiency Improvement and Cost Saving Opportunities
for Cement Making: An Energy Star Guide for Energy and Plant Managers (pp. 21-23, 47-48) by Ernst Worrell and
Christina Galitsky, 2008, Berkeley, California: U.S. Environmental Protection Agency, Environmental Energy
Technology Division. The energy efficiency measures pertain to raw materials preparation.



### The resulting capital cost from Equation A5 is multiplied with the average capacity of the kilns for both dry and wet processes to generate the cost of the base equipment: Cost of Equip. b = Capital Cost ($/ton of cement) * (Capac. of Equip. b) (A9)
where Cost of Equip. b = Cost of the base equipment, $ Capital Cost = Cost of capital, $/ton of cement Capac. of Equip. b = Median or average kiln capacity (Table 5), tons per year

### Andover Technology Partners Page 40 Once the Cost of Equip. b is known, the scale-up factor can be determined using Equation A3. The equation, however, will only generate a scale-up factor that is valid for the time period specified by the savings and/or the payback period. To obtain current 2008 value for the capital outlay, a GDP deflator is incorporated into Equation A3 as
follows: Scale-up Factor = [Cost of Equip. b / (Capac. Equip. b) 0.6 

### ] * GDP Def. 2008 

### (A10)
GDP Def. Payback/Savings



### where Scale-up Factor = Calculated factor to determine capital cost, $2008/ton of cement Cost of Equip. b = Cost of base equipment, $ Capac. Equip. b = Average or median kiln capacity, tons per year GDP Def. 2008 

### = GDP Deflator for the year 2008 GDP Def. Payback/Savings 

### = GDP Deflator of the year payback period or savings were estimated

The website of the Bureau of Economic Analysis (2009, Table) supplied the data
for the GDP deflator. The second method for computing capital cost is to directly apply the reported value of the installation cost ($/ton of cement) from the source document. This was done only if the payback approach was not feasible. Two scale-up factors were obtained in this manner. The first was based on a single system installation in California. A plant in Colton that installed the indirect firing system in 1997 furnished the retrofit cost of $5 million per 680,000 tonnes (Worrell & Galitsky, 2008, p. 26). This translates to a capital investment of $6.67/ton of cement. The second pertains to the cost of the raw meal blending measure, which the source document indicated to be $3.30/ton of raw materials. Since the scale-up factor requires ton of cement instead of raw materials, the conversion factor of 1.7 was applied. This generated a value of $5.61/ton of cement. As mentioned previously in this section, using the conversion factor is an approach consistent with how the authors, Worrell &

### Andover Technology Partners Page 41

Galitsky, treated the installed cost of the Raw Material Preparation efficiency measures of the dry processes. A number of the measures do not have scale-up factors. For a few of those measures, such as Fuel Preparation: Roller Mills, and Efficient Lighting, the lack of data, especially the payback period and the capital cost/ton of cement, prevented the development of the factors. The project also did not attempt to make any computations when more precise algorithms are available. For example, the measures of conversion of one form of kiln into another and the use of secondary fuel, can be obtained from my previous memo (see footnote 3) to the EPA (2009, pp.6-9, 34-43). And finally, not all the measures in Worrell & Galitsky are applicable to all the kiln types. Those listed on Table 1 under the Raw Meal Preparation, for instance, are divided into wet and dry types. The first four measures pertain to dry processes, and the next two are unique to wet kilns.

.

### Andover Technology Partners Page 42

Corrections to equations in Revised Memo.

I discovered errors on equations in the preciously revised memo that were introduced when I included the effects of the purity of the limestone into some of the equations. However, in some of the equations where I introduced the purity effects, this was not correct. The correct equations for the “Cost and Performance of Controls – revised from comments, dated March 10, 2009 are:

CO2CLINKER (in Short tons)= 0.51 * MCLINKER (in short tons) E.3

And, this can be modified to address substitutes for limestone as follows: CO2CLINKER (in Short tons)= 0.51 * MCLINKER * (1 – CASUB) E.4

CO2TOTAL (in short tons) = MCLINKER*[(LBCO2MMBTU/2000)*SFC+0.51* (1–CASUB)] E.11

### Andover Technology Partners Page 43

List of Terms Term Definition CAPACITYHR CAP CO2 CAR CASUB

CC CER CO2FUEL CO2CLINKER CO2UNCYR COALPY COSTKWH COSTNH3LB COSTNH3YR CR DLI DSCFM EGFW ELECPY FC FF i FOCCO2 H H2OPY H2OCOOLPY HIR LBCO2MMBTU LBMCO2MMBTU LBH20MMBTU LBMH20MMBTU LBNOXHR LBSO2CLINKER LER LNB LWS MAT MCLINKER MCLINKERHR MKF MLIMESTONE MLIMESTONEHR MSLAG MSLAGHR NOXMMBTU PEC PP PURLIMESTONE Q S Clinker capacity of the kiln in tons per hour

Capital Cost Factor for CO 2 Control Tech Calcination CO 2 Avoidance Ratio Calcium Substitution Fraction – fraction of total calcium from material that does not need to be calcined Capital Cost Clinker Equivalence Ratio Fuel CO 2 in pounds that is released from fuel combustion CO 2 produced by calcination during clinker production Uncontrolled CO2 per year Coal used per year (in tons) Cost of Power in $/KWhr Cost of ammonia in $ per pound Cost of ammonia in $ per year CR Dry Lime Injection Dry standard cubic feet per minute Exhaust Gas Flowrate (wet) in standard cubic feet per short ton of clinker Electricity Used per Year (MWhr) Fixed Cost Fuel Fraction of i th component of fuel on a Btu basis Fixed Operating Cost Factor for CO2 Capture Technology Burner heat duty in MM Btu/hr Process Water used per year (tons) Cooling Water used per year (tons) Heat Input Reduced Pounds (mass) of CO2 per MMBtu of fuel input Pound moles of CO2 per MMBtu of fuel input Pounds (mass) of H2O per MMBtu of fuel Pound moles of H2O per MMBtu of fuel Pounds (mass) of NOx per hour Lbs of SO 2 per ton of clinker Limestone Equivalence Ratio Low NOx Burner Limestone Wet Scrubber Mixing Air Technology Mass of clinker in tons Mass rate of clinker in tons per hour Mid Kiln Firing Mass of limestone, tons Mass rate of limestone, tons/hr Mass of slag, tons Mass rate of slag, tons/hr NOx lb/MMBtu for the kiln Purchased Equipment Cost Payback Period Purity of the limestone at CaCO 3 Flow in actual cubic meters per hour Savings (energy)

### Andover Technology Partners Page 44

SCC SCR SFC SCFH SNCR TDFPC TONSDKF TPY TPYCEMENT VC VOCCO2 Staged Combustion Calciner

Selective Catalytic Reduction Specific Fuel Consumption in MMBtu per ton of clinker Standard Cubic Feet per Hour of gas Selective Non-Catalytic Reduction Tire Derived Fuel Precalciner Tons of Decarbonated Feedstock Tons per Year of clinker Tons per Year of Cement Variable Cost Variable Operating Cost of CO2 capture technology

### Andover Technology Partners Page 1 March 10 , 2009

To: Ravi Srivastava , Samudra Vijay, Elineth Torres Fm: Jim Staudt

Re: Costs and Performance of Controls

– revised from comments
In this program we will examine the costs, performance, and impacts of NOx and SO 2 

### controls for cement kilns as well as energy

- saving approaches that may have a beneficial impact on fuel consumption and/or CO 2 

### release and may be incorporated into the ISIS model

. In this memo I will frequently refer to the memo regarding “NOx , SO 2 

### and CO 2 

### E missions from Cement Kilns” and dated September 23, 2003 that I will refer to as the “Emissions Memo”.
Although this effort is intended to examine NOx, SO 2 

### , and energy (CO 2 

### ) saving technologies, some of these technologies offer multiple ben efits. So, categorizing technologies by benefit (NOx reduction, SO 2 

### reduction, or CO 2 

### reduction, etc.) can be misleading. In this effort, I will categorize the technologies by method, such as combustion technologies, gas treatment technologies, process m odifications (including material substitution), etc . For each technology I will provide estimates of each of the benefits or impacts as well as cost. For instance, the following will be provided:

**•** Capital Cost algorithm

**•** Fixed Operating Cost algorithm

**•** Var iable Operating Cost algorithm

**•** NOx reduction (if any)

**•** SO 2 

### reduction (if any)

**•** Fuel Savings or increase (if any)

**•** Power Increase or Decrease

**•** Calcination CO 2 

### impact (if any)

**•** By product benefits (if any)

**•** Water usage

Costs and Benefits of Controls or Process Modifications
The addition of controls or the modification of a cement kiln process entails the addition of equipment and perhaps annual costs for reagent or energy in order to realize the benefit of reduced emissions.

Costs of controls can be broken dow n to:

**•** Capital costs (CC)

– these are the costs of purchasing, installing, and commissioning the equipment that are realized on a one

- time basis



# Andover Technology Partners

### Andover Technology Partners Page 2 **•** Variable annual costs (V C)

– these are the costs that are realized in proportion to the operation of the facilit y. Regents, parasitic power, and t hermal energy are examples of V C.

**•** Fixed annual costs (F C)

– these are costs that are realized each year that are not realized in proportion to the operation of the facility. Additional staffing and training of personnel, and taxes and insurance are examples of F C.
Generally, the most difficult costs to estimate are the capital costs. This is for the following reasons:

**•** Capital costs for retrofit s can be very site specific . So, actual costs for installing a technology on a specific kiln will vary based upon factors that are not well characterized by the general kiln characteristics

- kiln type and capacity

- which

are included in the database of kilns

.
**•** The relationship between capital cost and kiln output or another indicator of size is rarely constant. There frequently are “economies of scale” that make costs per unit output lower for larger units. To characterize these economies of scale it is necessary to have multiple data points for different sized kilns of the same type. Alternatively, some scaling factors can be assumed, but should be examined for their applicab ility.

**•** Data on capital cost can be sparse. Facility owners don’t always p ublish the capital cost or may not provide adequate detail on what the cost includes to make the information as useful as it could be

. Also, in the case of some technologies, there may be very few actual installations to base estimates on.

**•** Cost information can be from different years, which makes it less comparable. It is necess ary to adjust for this when possible. To address th is , a ll reported capital costs are shown in the year dollars of the source, and also for 2005$. Converting to 2005$ was performed using the Chemical Engineering Plant Cost Index (CEPCI) that is published in Chemical Engineering magazine.
Technologies
In the following sections, the technologies will be briefly described, recognizing that these technologies are described in more detail in referenced documents. The three major categories of technologies con sidered include Combustion Technologies, Gas Treatment Technologies, and Process Modification Technologies. Combustion Technologies operate by reducing emissions or otherwise improving operation by making changes to the firing process. Gas treatment tech nologies treat the gas and remove the pollution by addition of a reagent or by otherwise treating the gas without affecting the pyroprocessing portion of the kiln

. Process modifications actually c hange the process or change the feed materials. A final category of technologies is “Other”. These are generally energy saving methods that don’t easily fit into the other categories.

### Andover Technology Partners Page 3 

## Combustion Technologies
There are up to three possible combustion locations on a cement kiln facility. There are two possible locations to add fuel within the kiln itself (at the hot end and mid

- kiln) , and the third location is the calciner. The most modern kilns are calciner type kilns with at least two combustion locations

– kiln and calciner. The other kiln types ge nerally only fire fuel within the kiln. Therefore, combustion technologies will be distinguished by whether they are in the kiln or in the calciner.

Kiln Combustion Technologies
There are two possible kiln combustion locations, the primary combustion zone and the mid

- kiln zone. The technologies include low NOx burners and Mid Kiln Firing. Mid Kiln Firing may be firing of coal or waste

– often tires.

Low NOx burner (LNB)

Low NOx burners may be supplied in a direct firing mode where the burner is fed directly from the coal mill. However low NOx burners for the primary kiln combustion

zone are typically used in an indirect firing mode, where the fuel is fed from a particle collection devic e that collects pulverized fuel downstream of the fuel mill. Indirect firing enables the low NOx burner to be run with lower primary air levels than a direct firing system. The low primary air levels help to reduce NOx formation. A low NOx burner retrof it is possible on all kiln types.

Reference 1
, showed cost algorithms for the Purchased Equipment Cost (PEC) for low NOx burners:

For a direct fired low NOx burner:

PEC (1997$) = 172,000 + 152 * H , or E.1 PEC (2005$) = 216 ,000 + 19 1 H, where PEC = Multi

- channel direct fired low NO X 

### burner purchase equipment cost in $, and
H = Burner heat duty in MM Btu/hr.
Reference 1 showed annual costs for maintenance and operation of $59,200/year. Other annual costs included in this reference we re Taxes, insurance, and admin of 4% of total capital costs

.
For an indirect fired low NOx burner:

1 NOX Control Technologies for the Cement Industry, FINAL REPORT
, EPA Contract No. 68

- D98

- 026, Work Assignment No. 2

- 28, EC/R Project No. ISD

- 228, September 19, 2000

### Andover Technology Partners Page 4 PEC (1997$) = 835,000 * (H/225) ^ 0.6 , or E. 2

PEC (2005$) = 1,050,000 * (H/225) ^ 0.6 , where

PEC = Multi

- channel direct fired low NO X 

### burner purchase equipment cost in $, and
H = Burner heat duty in MM Btu/hr.
The exponent of 0.6 that is used in Reference 1 in these algorithms to scale capital cost to kiln capacity will be used for all other equipment except where there is data to support another scaling factor.
To arrive at total capital costs, it is necessary to multiply PEC by a factor that accounts for other costs . Based on Reference 1 , these other costs are direct installation costs (45% of PEC), indirect installation costs (33% of PEC), Contingency (20% of PEC), Sales Tax (3% of PEC), and Freight (5% of PEC), totaling 108% of PEC. An allowance for production downtime should be included as well. In Reference 1, this was roughly $3500/ tph of clinker capacity. So, to arrive at the capital costs, the PEC should be multiplied by 2 .08 and production downtim e added. Assuming an 85% capacity factor, the equation for total capital is:
Total Capital ( 2005 $) = 2.08 * PEC + $3500 * ( TPY/(0.85*8760) ) E.3
Where TPY is the tons per year of annual capacity.
Also, H can be determined from the kiln specific fuel consumption SFC . For all kilns except for precalciners, specific fuel consumption times the clinker capacity will prov ide H. For precalciner kilns, the kiln burner receives anywhere from about 40% to 60% of the fuel, depending upon whether or not there i s bypass. The more modern kilns bypass gas from the cooler and use more fuel in the calciner than in the kiln to provide fully calcined material to the kiln

. 2 

### So, about 0.5 0 times specific fuel consumption times kiln capacity will provide H for precalcin er kilns. However, recognize that some older precalciner kilns may have a greater portion of total heat go to the kiln than the precalciner.
Applicability

All kilns
Capital Cost

For a direct fired low NOx burner:

2 Wikipedia, http://en.wikipedia.org/wiki/Cement_kiln#Precalciners

### Andover Technology Partners Page 5 **•** Capital Cost (2005 $) = 2.08 * [ 216,000 + 191 * SFC * ( TPY/(0.85*8760) ] + 3500* ( TPY/(0.85*8760) for all kilns but precalciners

**•** Capital Cost (2005 $) = 2.08 * [ 216,000 + 191 * 0.5 0 SFC * ( TPY/(0.85*8760) ] + 3500* ( TPY/(0.85*8760) for precalciners

For an indirect fired low NOx burner:

**•** Capital Cost ( 2005 $) = 2.08 * 1,050,000 * ( SFC * ( ( TPY/(0.85*8760) ) /225) ^ 0.6 + 3500* TPY /(0.85*8760 for all kilns but precalciners

**•** Capital Cost ( 2005 $) = 2.08 * 1,050,000 * (0. 5 0 * SFC * ( ( TPY/(0.85*8760) ) /225) ^ 0.6 + 3500* TPY/(0.85*8760) for precalciners

Fixed Costs
According to Reference 1, thes e are estimated at $59,200/year plus 4% of capital cost for taxes, insurance, etc.

Variable Costs
Variable annual costs are negligible for low NOx burners.
Impacts of burners:

The amount of NOx reduced by installation of a low NOx burner will be determined by the particulars of the kiln. Reference 1 showed data from low NOx burner installat ion s that varied from 15% to 47% for burners with indirect firing. No data was shown for direct firing, although the impact would certainly be less than indirect firing. A reasonable estimate of NOx reduction might therefore be in the range of 30% for a low NOx burner with indirect firing . For a low NOx burner with direct firing, the reduction would be less, perhaps in the range of 10%. However, due to the small benefit of direct firing, it would be reasonable to neglect it for the ISIS model.

Low NOx b urners will have no impact on SO 2 

### emissions and will have minimal impact on plant efficiency. However, there is a small impact on power demand that can be estimated. Assuming that there is roughly 6% primary air passing into the direct fired burner and t hat this air has a higher pressure drop of 15 IWC and is driven with a fan that is 75% efficient, for a kiln with a nominal flowrate of 50,000 SCF/ton, the incremental load of an indirect fired system is estimated to be about 0.09 kW per short ton. E .5 E.4

E .7 E .6

### Andover Technology Partners Page 6 Mid Kiln Firing (MKF)
Mid kiln firing allows the firing of tires, coal or other fuels at the mid

- kiln area. This permits less intense firing at the primary burner and will reduce NOx formation in the kiln. Tires or other waste fuels are often used at the mid

- kiln location because of the high temperatures and residence time in the kiln that permit good combustion and because these waste fuels also come with tipping fees. The other benefit is that MKF permits reduction of fossil fuel consumption when waste fue ls are used.

Reference 1 included estimates of capital cost for MKF

. Figure 1 shows the estimated $/TPY from the Reference 1 capital cost estimates

. Table 1 from R eference 3 is a more recent estimate that shows a tot al purchased equipment cost of roughly $1.1 million for a mid

- kiln firing system that fires lump coal mid

- kiln , including mixing air technology, which improves the perfo rmance of the mid

- kiln firing

. To address direct and indirect installation costs, this should be multiplied by about 2.08 an d then an allowance for production downtime might be added

. The result is close to the range of the estimates of Reference 1

. Figure 1. Capital cost of Mid Kiln Firing (MKF) in $/TPY (1997$)

Applicability
Primarily Wet and Long Dry.
Capital Cost
The following capital costs are determined from Figure 1 :

3 E

- mail from Eric Hansen, Cadence Technologies, 6/20/08

### Andover Technology Partners Page 7 Capital Cost (1997$) = $2.0 (10) 6 

### * TPY - 0.959 

### * TPY = $2.0 (10) 6 

### * TPY 0.041 

### Capital Cost (2005$) = $2.52 (10) 6 

### * TPY 0.041 

### E.8

Table 1

. Budgetary cost for MKF with MA from Reference 3
Lump coal handling system $500,000 Mid

- Kiln equipment on kiln $250,000 MA equipment $250,000 Variabl e Frequency Drive $ 20,000 MKT and MA installation $ 35,000 Technical support commissioning and training $ 40,000

MA Equipment = overfire air injection sys tem



### Fixed Costs
According to Reference 1, these are estimated at $59,200/year plus 4% of capital cost for taxes, insurance, etc. Reference 1 also shows a n annual license fee for tire injection that is equal to $300/MMBtu/hr of heat input. Or, on an annua l basis is equal to:
License fee = TPY * SFC *$300/(8760*0.85) E.9

Variable Costs
Variable costs include some additional power (about 50KW per Ref 3 ) and also a reduction in fuel costs if tires are used. Since MKF is installed mainly on wet and long dry kilns, which have typical capaciti es in the range of 300,000 TPY, the power usage would be roughly :

50 kW* 760*0.85 hr/300,000 TPY = 1.24 kWhr/ton cli nker E.10
Assuming an electrici y cost of $35/MWhr, then the energy cost is roughly:

VC power 

### = 1.24 kWhr / ton clinker * 35/1000 = 4.34 cents per ton of clinker E.11

Mid

- kiln firing will a lso reduce fuel costs if tires are added. Rather than paying for the cost of coal, with mid

- kiln firing of tires it is possible to receive a tipping fee for burning the tires. In this case, the cement plant is actually paid to receive the fuel, called a tipping fee. Tipping fees were found to range from around $70/ton to around $150/ton, as shown in the inset on the next page

. If tires have a heating value of about 14,000 Btu/lb and a tipping fee of $100/ton can be received, then the tipping fee is about $3.60 per MMBtu. For a $70/ton tipping fee, the tipping fee is equal to about $2.50/MMBtu. This also offsets purchased fuel. If it offsets

### Andover Technology Partners Page 8 coal, a rough delivered cost of $2.50/MMBtu might apply (this, of course, will vary based upon location). So, the net benefit might be in the range of $5/MMBtu or more for each Btu of displaced coal.
As a result of this fuel benefit, it might be expected that all virtually kilns would use tires. However, some don’t. Used tires may be abundant in some locations, but not in others

. Another reason some kilns don’t burn tires is likely due to permitting and community perception issues that create an obstacle.

For the mid

- kiln firing cases of Reference 4 , heat inputs for mid kiln firing range from 8% to 20 percent of the thermal input without mixing air technology. Wet kilns are typically limited to 15% to 20% substitution and dry kilns to 20% to 25% substitution without mixing air. With mixing air, fue l substitution rat e can be doubled in some cases

. 5 

### With mixing air technology, coal can be injected mid

- kiln at rates of about 35%, according to Cadence

. 6


### So, for tire injection, an assumption of 15% displacement of heat input is reasonable and

conserv ative, and is consistent with what was assumed in Ref. 1 . In this case, the net fuel cost benefit might be in the range of:

VC Annual Savings from tires 

### = TPY * SFC * 0.15 * 5 E.12

4 Northeast States for Coordinated Air Use Management (NESCAUM), “Status Report on NOx

– Control Technologies and Cost Effectiveness for Industri al Boilers, Gas Turbines, IC Engines, and Cement Kilns”, 2000 5 Hansen, E., “ "Staged Combustion for NOx Reduction Using High Pressure Air Injection", IEEE/PCA Conference 2002 6 http://www.cadencerecycling.com/pages/NOxReduction.html

Tire Tipping Fees

**California Integrated Waste Management Board** : http://www.ciwmb.ca.gov/landfills/tipfees/
2000 Survey Tires $/Each Tires $/Ton Lowest (Except 0) $.75 $42.00 Highest $14.65 $280.00
Median $2.00 $95.00 Average $2.61 $102.70 Weighted Average (Landfills Only) $3.55 $67.67

Weighted Average (All Facilities) $3.53 $71.41
**Tennessee Solid and Hazardous Waste Management** $70per ton http://www.state.tn.us/environment/swm/tires/tiresfaq.shtml
**Waseca county Minnesota** : current tipping fee $100/ton and $150/ton proposed. http://www.co.waseca.mn.us/E

- board%20meetings/2008/04

- 01

- 08/tipping%20fee%203.pd

### Andover Technology Partners Page 9 Impacts of MKF
Mid kiln firing of tires or fuel can reduce NOx emissions significantly

– in the range of about 35%, per Reference 1 and shown in Table 2 . Mid

- Kiln Firing, particularly when used with mixing air, can have a positive impact on SO 2 

### emissions because it helps promote oxidation of SO 2 

### to sulfate (SO 4 

### ) in kilns where there may be poor mixing

. 5
, 7 

### The SO 2 

### benefit is hard er to predict because mixing air technology is relatively new and because the amount of SO 2 

### benefit will vary based upon particular conditions in the kiln.

Carbon dioxide may be affected. Tires make about the same amount of CO 2 

### per unit heat input as coal ( slightly less CO 2 

### per MMBtu than bituminous coal, about the same amount as PRB coal, ) and significantly more CO 2 

### per MMBtu than natural gas

. Tires, how ever, are not fossil fuel , although fossil fuel is used to make them . I f CO 2 

### emissions from tire comb ustion are treated differently from a regulatory perspective than CO 2 

### emissions from fossil fuel , the regulatory difference will need to be factored in to how CO 2 

### emissions are accounted for

. In any event , if the Mid

- Kiln fuel is different than the primary fuel, then the actual CO 2 

### emissions would change. The calc ulation is straightforward.

CO2FUEL = MCLINKER * SFC * ( FF 1 

### *LBCO2MMBTU 1 

### + FF 2 

### * LBCO2MMBTU 2 

### + . . . FF i 

### * LBCO2MMBTU i 

### ) E.13

Where FF i 

### is the fuel f raction for each fuel in thermal input

. A typical heat input for mid kiln firing is 15%. However, higher values are possible. If an annual estimate is desired , simply substitute TPY for MCLINKER.

Table 2. NOx missions from Kilns with Mid

- Kiln Firing (from Reference 1) Kiln Emissions (lb NOX/ton of clinker) Percent Reduction (%) Emissions Based on CEMS Data Dry Kilnsa A not given 13.6 unknown B not given 11.1 unknown C not given 45.1 yes C not given 55.3 yes D 2.7 not given unknown E 10.2 13.9 unknown F not given 46.6 unknown F not given 50.4 unknown F not given 28.3 unknown Average (Dry Kilns) 6.4 33.3 Wet Kilns G not given 59.0 yes H not given 35.0 unknown I not given 27.6 unknown Average (Wet Kilns) n/a 40.5 Average (Dry & Wet Kilns) 6.4 35.1
Source: NOX Control Technologies for the Cement Industry, FINAL REPORT
, EPA Contract No. 68

- D98

- 026
, Work Assignment No. 2

- 28, EC/R Project No. ISD

- 228, September 19, 2000

7 Hansen, E., "Changing Process Priorities when Firing Alternate Fuels" IEEE/PCA Conference 2003

### Andover Technology Partners Page 10 Mixing Air Technology (MAT)
Mixing Air Technology may be used in combination with or not in combination with Mid Kiln firing or in combination with fuel addition at the preheater inlet (also called Riser Duct Firing) . MAT will help to enhance NOx reduction by facilitating staged combustion and can also help to reduce SO 2 

### emissions from long kilns or preheaters equipped in this way

. MAT is beneficia l even without mid

- kiln firing. Higher temperature oxygen

- rich gasses tend to travel along the top of the kiln while cooler, carbon dioxide

- ri ch gasses tend to travel along the bottom. When Mixing Air is added, stratified kiln gasses begin to rotate and mix , as shown in Figure 2 . This rotation improves combustion, serves to reduce emissions and improves th e overall stability of the kiln. Kiln s tability will improve NOx emissions, by reducing high NOx excursions, and can improve product quality and kiln output. Figure 3 shows a photo of a MAT installation.
By enhancing oxidizing conditions in a region where there is ample free lime, MAT will als o improve conversion of SO 2 

### to sulfate. Reductions of fuel SO 2 

### in excess of 90% have been reported

. 5 

### However, this may not be typical . The actual reduction in SO 2 

### emissions will vary depending upon the particular facility

. 5 

### Figure 4 shows the improvement in NOx, SO 2 

### , CO and to tal hydrocarbons when using MAT at one kiln.
Applicability
Primarily Wet, Long Dry and Preheater

– not as widely used on precalciner , except to facilitate stag ed combustion on the precalciner

. Capital Cost
MAT equipment PEC is $250,000 per kiln per Reference 3 . Accounting for other costs, the total capital cost is therefore, roughly 2.08 times that, or about $520,000, plus an allowance for lost production. Using the same allowance for lost production as the low NOx burner would be conservatively high.
MAT Capital Cost (2008$) = $520,000 + 3500 * TPY/(0.85*8760) MAT Capital Cost (2005$) = $470,000 + 3500 * TPY/(0.85*8760) E.14

Fixed Annual Costs
Being a combustion technology that does not require additional material handling equipment, F ixed Annual costs are expected to be similar to those of a low NOx burner.

### Andover Technology Partners Page 11 Variable Costs
There will be a small amount of power needed. If it is assumed that MAT uses about 5% of the total gas flow (probably conservatively high) the additional kW load can be estimated to be equal to roughly 0.025 kWhr per short ton if 50,000 S CF /short ton is typical . In fact, there may be no increase in power usage at all if the outlet oxygen is maintained the same because the primary or secondary air flow into the kiln would have to be reduced by an equivalent amount to keep outlet oxygen con stant.
Impacts
The impacts of MAT will va ry from one facility to another and are not as well characterized as the impacts of other technologies that have been available longer. CO emissions will be reduced quite a bit. NOx reductions will be determined by how much the operation is improved and stabilized. SO 2 

### emissions from the fuel will likely be reduced; however, MAT will have little effect on SO 2 

### that is produced by pyritic sulfur in feed materials. Since output of the ki ln might be improved somewhat, CO 2 

### emissions (on

a lb/ton clinker basis) might be reduced slightly. Figure 3 shows emissions impacts at one kiln equipped with Mixing Air Technology. Although impacts are not well characterized for MAT, MAT can have an imp ortant role for some technologies, su ch as MKF, riser duct firing low NOx precalciner and is therefore discussed here

. Figure 2 . Mixing Air Technology from Ref. 5

### Andover Technology Partners Page 12 Figure 3 . Photo of Mixing Air Technology (Ref 5 )

Figure 4 . Emissions improvement with MAT at one kiln. (Ref. 5 )

### Andover Technology Partners Page 13 Non

- Kiln Combustion Technologies

For calciner kilns a substantial amount of combustion occurs in the calciner

– typically 60 % of the heat input (Ref 38 at p 245), but sometimes 50% (See Ref 22 at p 168). Preheater kilns typically only have combustion in the kiln. However, f or preheater kilns, the practice of riser duct firing has been employed in some cases primarily to reduce the thermal load on the kiln and to increase the amount of calcination that occurs in the preheater. About 15% of the fuel heat input may be into the preheater riser duct. 8 

### Due to the temperature in t he calciner and riser duct , thermal NOx formation in the calciner or riser duct burners is low , although thermal NOx is generated in greater amounts within the kiln

. Preheater Riser Duct Firing (RDF)
In the case of preheater kilns with riser duct firing (RDF), the use of tires in the preheater (13% of heat input) produced a reduction of NOx of about 30%

- 40% at Mitsubishi Cement Company’s Cushenbury Plant in Lucerne Valley, CA. 8 

### According to Reference 5
, some NOx reduction should be possible using lump fuel, such as lump coal, if tires are not available , and with mixing air technology (MAT) the combustion in the preheater riser duct can be s taged to provide lower NOx emissions. Use of high volatile fuels are preferred.
Applicability
Preheater Kiln only

. Capital cost
The cost of the addition of riser duct firing would likely be on the same order as mid

- kiln firing, since similar material hand ling equipment would be needed.

Fixed Annual Cost

This also should be similar to that of mid

- kiln firing

Variable Cost

Variable cost and power consumption will also be similar to that of mid kiln firing. It is important to include the fuel benefit when firing tires.

8 ASSESSMENT OF NOx EMI SSIONS REDUCTION STRATEGIES FOR CEMENT KILNS

- ELLIS COUNTY FINAL REPORT
, 

### TCEQ Contract No. 582

- 04

- 65589, Work Order No.05

- 06, July 14, 2006

### Andover Technology Partners Page 14 Impacts
The impacts will be to reduc e NOx by roughly 30% if tires are used. For use o f coal, the NOx reduction is likely to be less due to the lower volatile content of the coal versus tires.
Carbon dioxide may be affected. Tires make s lightly less CO 2 

### per MMBtu than bituminous coal, about the same amount as PRB coal, and significantly more CO2 per MMBtu than natural gas. Use the same equation described in the MKF section.
Low NOx Calciner ( LNC )

Combustion in the calciner can be s taged t o reduce NOx emissions with a rich combustion zone and a downstream air addition zone, as shown in Figure 5

. In this approach, NOx from the kiln is reduced in the fuel rich zone and then there is a burnout

zone. According to Reference 9 , there are three ways to achieve staging depending upon the kiln. Table 3 shows the emissions reduction from some plants that used staged precaliners

. As shown in Table 3 , the use of tires significantly enhanced performance. The minimum NOx level achieved under any condition was 1.4 lb/ton clinker and the highest was 3.0 lb/ton clinker, depending upon the kiln. With NOx reduction ranging from 17% to 44%, a reasonable “average” might be around 30%. However, it should be unde rstood that the actual level achievable for any particular kiln might differ from this.
Applicability
Precalciner only . Most precalciners likely use this to some degree.
Capital Costs
Capital cost information was not found. However, t o add fuel staging t o an existing calciner kiln might be similar to the cost of adding mixing air technology (MAT)

.
Fixed Annual Costs
Again, this is likely to be similar to adding mixing air technology..

Variable Costs
Variable cost changes should be negligible, except if ti res are substituted, which will actually be a cost reduction.
Impacts
NOx reduction of about 30% with few other impacts.

9 Alternat ive Control Techniques Document Update

- NOx Emissions from New Cement Kilns, EPA

- 453/R

- 07

- 006, November 2007

### Andover Technology Partners Page 15 Figure 5

. Principle of NO x 

### reduction by SCC 9



### Table 3. Summary of NO x 

### Performance of SCC in U.S. Kilns

Source/Location NO x Uncontrolled (lb/t) NO x Controlled (lb/t) Efficiency

11 US kilns(from Table 7

- 2) NA 2.2

– 3.3 NA (avg. 2.7)
Florida Rock 3.5 3.0

- w/o tires 17%

- w/otires
1.5

– 2.5 (midpoint 2.0)

- w/ tires 43%

- w/ tires
Suwannee American NA 2.2

– 2.6 (range) NA 2.4 (midpoint)
Titan American NA 2.0 NA
Lone Star 2.8 1.8 35%
Cemex Santa Cruz 9 NA 2.5 (0% coal to reducing zone NA 1.7 (50% coal to reducing zone) 

### 32% 1.4 (100% coal to reducing zone) 

### 44% 1.8 (midpoint) 

### 28% Alternat ive Control Techniques Document Update

- NOx Emissions from New Cement Kilns, EPA

453/R

- 07

- 006, November 2007

### Andover Technology Partners Page 16 

## Gas Treatment

SNCR

SNCR is commercially used on cement kilns to provide NOx reduction. It has been generally accepted as an approach for providing significant reduction on preheater and precalciner kilns. However, for long wet and long dry kilns an approach for admitting the reagent (ammonia or ur ea) to the furnace has been an obstacle to implementation of SNCR on long kilns. Cadence Technology has developed a method for injecting ammonia using technology similar to their mixing air t echnology, and shown in Figure 6 installed on a long kiln. 10



### Figure 7 shows nominal capital equipment costs of SNCR from Reference 9 plotted on a $/ton clinker basis versus year basis of the estimate. As shown, costs appear to have generally declined over time. 9 

### The most recent costs, in 2004 and 2006 base yea r dollars, are in the range of about $1/ tpy of clinker capacity for new kilns. The 1992 costs shown in Figure 6 are not costs for actual projects, but are based upon model kilns estimates. At the time of these estimates, SNCR had not been implemented on any kiln. So, the cost estimates were speculative. In any event, it is apparent that nominal costs have not risen and real costs have likely declined for SNCR. Or, the previous estimates were simply too high. Reference 8 project ed higher costs as well; but, these were based upon a speculative approach for how to employ SNCR on long

- wet cement kilns using mid

- kiln tire injection with urea in the tires, not the f airly simple approach that has been used by Cadence pictured in Figure 5.

10 Hansen, E, Reese, T,, “Eliminating NOx Barriers to Fuel Conversions with SNCR and Staged Combustion”, Global Fuels Conference, London, February 3

- 5, 2008, available for download at: http://www.cadencerecycling.com/pdf/CadenceGlobalFuelsPaper.pdf 

### Figure 6. SNCR installed on a long kiln (Ref 10 )

Figure 7. SNCR Capital Costs in $/TPY from 2007 ACT

### Andover Technology Partners Page 17 Reference 11 cited a European study that found SNCR cost at around $ 1 /tpy on a roughly 1.2 million tpy kiln. So, an assumption of cost of $1/ TPY would be a reasonable estimate for S NCR costs for a 1.2 million TPY kiln

. Captial Cost
So, for capital cost of SNCR, a reasonable estimate is :

CC (2005$) = $1 * TPY * ( 1,200,000 / TPY )^0.4

= $270 * TPY ^0.6 E.15

Fixed Cost
Fixed annual cost is relatively low, probably on the order of that for low NOx burners

Variable Cost
The single largest annual cost item for SNCR is reagent. Reference 12 , which is a recent study, included prices shown in Table 4 for SNCR reagent.

Table 4 . SNCR Reagent Cost (COSTNH3LB)

Reagent $/lb Anhydrous Ammonia 0.425 19% Ammonia 0.475 Urea 0.125 Source: PCA R&D SN3046, “Current State of Practice for Selective Non

- Catalytic Reduction (SNCR)” by Schreiber & Yonley Associates, Portland Cement Association 2008



### As described in Reference 13 , ammonia SNCR in particular can be very effective on cement kilns, producing high reduction levels at moderate treatment rates. On the kilns that used ammonia, reduction rates of 50% were achieved with normalized stoichiometric ratios (NSR) of 0.50 and r eduction of about 70% with NSRs of about 1.0. According to this reference, urea is somewhat less effective, no doubt due to its higher reaction temperature. At least part of the reason for the high effectiveness of ammonia is the time and temperature cha racteristics of cement kilns. The SNCR performance results of Table 5 are from Reference 9

.

11 TECHNICAL EVALUATION PRELIMINARY DETERMINATION
, DRAFT BACT DETERMINATIONS
, CEMEX CEMENT COMPANY BROOKSVILLE, HERNANDO COUNTY New Portland Cement Lin e DEP File N o. 0530010

- 029

- AC (PSD

- FL

- 384) Department of Environmental Protection Division of Air Reso urces Management Bureau of Air Regulation, April 3, 2007 12 PCA R&D SN3046, “Current State of Practice for Selective Non

- Catalytic Reduction (SNCR)” by Schreiber & Yonley Associates, Portland Cement Association 2008 13 Linero, A., SNCR Technology for the Cement Sector, CEMTECH Florida, 2006, Orlando

### Andover Technology Partners Page 18 Table 5 . NOx reduction with SNCR (Ref. 9 )

Plant/Source Control Level (lb/t) Efficiency (%) NSR 3 European kilns 9 NA 25

– 50; 35

– 60; 42

– 72 0.6; 0.8; 1.0 Ash Grove, Seattle 2.2; 1.3 25; 55 0.5; 1.0 Hercules; PA 300 ppm ~3.0 12

– 25 NA Suwannee American 38 2.0 33

– 50 NA Florida Rock without tires 1.9; 2.6 47; 29 0.47; 0.35 Florida Rock with tires 2.1 34 0.12

– 0.25 Holcim

– Texas 54 (2 kilns) NA 47, 32 0.7 Skovde, Sweden 0.5

– 1.0 80

– 85 1.0

– 1.1 Slite, Sweden 1.1 80 1.0 Taiwan

- 2 kilns 1 194 ppm; 284 ppm ~2.0; 2.9 50; 46 NA Cemex; FL

- preheater kiln 24 2.0 50 0.6

– 0.7 European Report

- achievable 1.0 80

– 85 NA European Report

- actual operation 2.5

– 4.0 10

– 50 0.5

– 0.9


### Although the performance will vary somewhat from one kiln to another, a conservative reduction and treatment rate would be around 50% reduction with an NSR of roughly 0.70. Using these to estimate cost of ammonia, the
Cost of ammonia per year (COSTNH3YR ) = TPY *SFC*NOXMMBTU*(17/60)*0.70*COSTNH3LB E.16
SNCR may use water. Assuming (DIL) dilution at the injectors, Water use of SNCR (SNCRH2OYR) in lb/yr = TPY*SFC*NOXMMBTU*(17/60)*0.70*(1

- DIL)/DIL E.17
If aqueous ammonia (~18% by weight) is used and not diluted , DIL = 0.18. However, it is often diluted to match injector flow requirements to, say, 10%. In that case, DIL = 0.10.
A small amount of pumping power is necessary for SNCR. Assuming 40 psi pumping pressure, 90% efficient pump, and the flowrate above, annual power needs in kWhr i s estimated as :
(SNCRH2OYR/62.4) * (1/(1

- DIL))* 144 * 40/(1.3558 * 0.9 *3,600,000) = 2.10 *(10) - 5 

### * SNCRH2OYR* (1/(1

- DIL)) E.18

### Andover Technology Partners Page 19 Impacts
SNCR will reduce NOx roughly 50%.
Use of urea will have very small impact on CO 2 

### emissions. This effect is relatively small since it amounts to perhaps a few hundred ppm of CO 2 

### versus percent levels in the flue gas. Ammonia SNCR will not have an impact on CO 2 

### emissions.
SNCR will have no impact on SO 2 

### emissions.
There can be an energy benefit or disadvantage to SNCR, depending upon the concentration of the ammonia or urea. The SNCR reaction is exothermic. But, injection of ammonia or urea and water offset this effect by cooling the gas. Reference 14 showed the results of an estimate of fuel savings based upon use of ammonia SNCR and other assumption s. In this estimate it was determined that the effect could result in a reduction of fuel CO 2 

### in the range of 0.40

- 0.88 kg of CO 2 

### per metric ton of clinker, dependin g upon kiln type. However, the actual dilution rate of the ammonia in water will vary based upon the injection system, as the flowrate is usually matched to the injectors to optimize atomization. So, this effect is really not possible to gene ralize and i s nevertheless very small compared to other sources of CO 2 

### .

14 Arcadis, for US EPA, “Air Pollution Controls and Efficiency Improvement Measures for Cement Kilns” Contrac t No.: EP

- C

- 04

- 023
, Project No.: RN990234.0030

### Andover Technology Partners Page 20 SCR
SCR is not in use at any cement facilities in the US. However, it has been installed on cement plants in Europe. SCR is capable of about 90% reduction of NOx. SCR is more expensive than S NCR. Figure 8 shows normalized cost in $/ TPY clinker versus the year of the estimate. 9 

### The two estimates from 1992 are far above the more current estimates. It should be noted that the estimates in 1992 dollars are from the 1994 cement kiln ACT, and was before there was any e xperience with SCR on cement kilns. The basis of the 1992 estimate was a 1991 estimate provided by a Japanese company for an SCR on a US cement kiln. Translation of the estimate entailed currency exchange estimates, as described in Reference 1. Referenc e 1 uses the same algorithms developed from the 1994 ACT on the basis of that 1991 estimate. However, in the early 1990s there was limited experie nce with SCR on coal power plants overseas and virtually no experience with SCR on coal

- fired power plants in the US. As a result, these 1992 estimates

– and others developed from the same original 1991 Japanese company estimate

– are not especially relia ble because they were based upon very limited knowledge of SCR. Recent studies are fairly consistent with one another. Reference 15 cited a European kiln study of a ~1
, 25 0, 000 tpy kiln at a cost of about $7/ TPY

. Reference 8 , produced in 2006, also had estimates of SCR capital cost in the range of $6.5

- $7.6 /TPY to retrofit dry calciner kilns, to $10.26

- $13.5/tpy to retrofit wet kilns with SCR. There is additional equipment necessary for the wet kilns that makes them more expensive to retrofit than dry kilns. The more recent estimates are in a fairly consistent range . Because the recent estimates build up on the knowledge gained from actual applicati on of SCR on numerous high

- dust sources such as coal

- fired boilers and cement kilns , they are likely more reliable than the estimates based upon the algorithms in the old ACT document.
Capital Costs

All of the estimates in the 2004 to 2006 time frame shown in Figure 8 are in the size range of about 1 million TPY to about 1.25 million TPY

. It might be reasonable to estimate Capital cost for a dry kiln at $7/ TPY at 1 million tpy. For a wet kiln, it might be reasonable to estimate the cost as $12/tpy for a kiln (or group of kilns ) in the range of 1 million tpy (the average of the two Ash Grove and TXI wet kiln “groups” that are evaluated in Reference 8 )

.
To estimate the capi tal cost of S CR for a dry kiln , a reasonable estimate is :
CC (2005 $) = $7 * TPY * ( 1,000,000/tpy )^0.4

= $1758 * TPY ^0.6 E.19

15 TECHNICAL EVALUATION PRELIMINARY DETERMINATION
, DRAFT BACT DETERMINATIONS
, CEMEX CEMENT COMPANY BROOKSVILLE, HERNANDO COUNTY New Portland Cement Line DEP File N o. 0530010

- 029

- AC (PSD

- FL

- 384) Department of Environmental Protection Division of Air Reso urces Management Bureau of Air Regulation, April 3, 2007

### Andover Technology Partners Page 21 To estimate the capital cost of SCR for a wet kiln , or wet kilns , a reasonable estimate is :
CC (2005 $) = $12 * TPY * (1,000,000/tpy)^0.4 = $3014* TPY^0.6 E. 20

Fixed Costs
These are estimated in Reference 1 to be equal to:
$54,300 + 4% of Capital Costs

Since this is similar to the cost for low NOx burners, when adjusting for year dollars, we will make it the same as for burners :
$ 59,200 + 4% of Capital Costs E. 21

Variable Costs
Variable costs are comprised of:

**•** Ammonia reagent

**•** Parasitic Loads for pressure drop

**•** Catalyst Figure 8. SCR Capital Costs in $/TPY from Ref. 9

### Andover Technology Partners Page 22 Ammonia

- Assuming 90% reduction and 98% chemical utilization, the NSR will be 0.92, and could be less depending upon the presence of ammonia in raw materials. This results in:
Cost of ammonia per year = TPY *SFC*NOXMMBTU*(17/60)*0.92*COSTNH3LB E.22

Parasitic Loads

- Parasitic loads are mostly related to overcoming pressure drop. At the Solnhofen Plant in Germany and the Monselice plant in Italy, the pressure drop was 5 millibars or less (500 N/m2 or less) 13
, 16 

### At Monselice, at 1800 tpd the gas flow was 110,000 Nm2/hr (wet), or about 235,000 m3/hr at about 370 C. Assuming 75% efficient blower, this equates to an additional 44 KW of load. At 180 0 tpd, the heat input of the Monselice preheater kiln can be estimated from characteristic heat demand data as about 360 MMBtu/hr or about 380 GJ/hr.
Assuming the gas flow is directly related to the heat input, the load associated with this pressure drop c an be estimated by:

Annual Power Demand (in KW hr ) = 44* TPY * SFC/360 E.2 3
Other power demands, such as pumping power for urea or ammonia, and carrier air, tend to be small when compared to the fan demand, and would typically be less than 10% of the fan power demand.
Catalyst

- Catalyst is another variable cost. Catalyst is generally installed in layers. At Solnhofen and Monselice, six layers were available, although only three layers were filled with catalyst initially. 13
, 16 

### Assuming a space velocity of 2 000/hr, which is significantly below typical SV for coal plants , then the catalyst loading can be estimated by the EGFW (see Table 1 of the Emissions Memo ).
Catalyst loading = MCLINKERHR * EGFW /2000 E.2 4
A conservatively high estimate of catalyst cost is $10,000/m3, or about $285/cubic foot,
Assuming a life of 40,000 hours, which was experience in Solnhofen 13 

### and, then the annual catalyst usage and catalyst cost are : Annual catalyst usage (in cubic meters) = TPY * EGFW/(2000*40,000) =1.25 (10) - 8 

### * TPY * EGFW E.2 5
Annual catalyst cost = TPY * EGF W * 285 / ( 2000 *40
, 000) Annual catalyst cost = 3.56 (10) - 6 

### * TPY * EGFW E.26

16 Ulrich Leibacher, Alvaro Linero, “High Dust SCR Solutions”, International Cement Review , December 2006

### Andover Technology Partners Page 23 With T P Y in short tons per year and EGFW in SCF /short ton
So, the total variable costs for SCR are:

VC = TPY * ( SFC*NOXMMBTU*(17/60)*0.92*COSTNH3LB + 44 * COSTKWH * SFC/360 + 3.56 (10) - 6 

### * EGFW) E.27

With COSTKWH is equal to the cost of power in $/KWhr

. Impacts
The impact of SCR is to reduce NOx by close to 90%. A reasonable assumption is 85% NOx reduction which has proven to be effective at these levels on coal fired boilers.
Other pollutants will be affected as well. Oxidation of organics occurs to some degree

across SCR catalyst. CO 2 

### will not be affected. SO 2 

### will not be affected except that a small portion of the SO 2 

### (typically 1% or less) of the SO 2 

### will be oxidized acros s the SCR catalyst to form SO 3 

### .

### Andover Technology Partners Page 24 Limestone Wet Scrubber (LWS)
Limestone Wet Scrubbers can provide in excess of 90% SO 2 

### removal

– often over 95%.
Capital costs
Some capital cost estimates are shown in Table 6.

Table 6. Wet FGD Capital Costs
Kiln type Size, tph, ( TPY ) Capital Cost Estimated $/dscfm Reference

PH/PC 150 (1,200,000) $28 million $276 ** 17 PH/PC 125 (990,000) $5.5 million $65 ** 18 Any $30

- $60/dscfm $30

- $60/dscfm 19



### PH/PC 170 $6.6 million $58 ** 20 

### PH/PC 250 (1,964,000) $13 million $77 ** 21 

### * installed, not including fans and ducting ** estimated using estimated dscfm, not from references
Some of the reported scaled costs were in terms of $ per dry scfm. When costs are scaled against scfm, this is generally dry scfm because moisture in the exhaust gas would otherwise have to be added to achieve saturation. So, moisture should be subtracted from the gas flow to arrive at dry scfm

. Using the average SFC f rom Table 1 of the Emissions Memo and the EGFW from that t able and also the moisture from combustion, it is possible to estimate dry gas flow by subtracting combustion moisture from the wet exit gas flowrate. This neglects for the moment moisture from inp ut materials, which is very significant for wet kilns, but it is less important for dry kilns. According to Reference 22 the difference between gases from the feed for a wet kiln versus a dry kiln is 19,329 SCF/sh.ton clinker (1,536 lb/sh. Ton clinker) , an d this is mostly moisture. Reducing the EFGW for a wet kiln by this amount results in 89,661 SCF/sh.ton.
So, dry SCFH for a kiln can be estimated by:
(TPY/(8760*0.85)) * 89661

– moisture from combustion (for a wet kiln), and

17 Bahner, Icenhour, Lany, Barnett, Summary o f Environmental and Cost Impacts of Proposed Revisions to Portland Cement New Source Performance Standards (40CFR Part 60, subpart F), Docket Number EPA

HQ

- OAR

- 2007

- 0877 18 Miller, S., Hansen, J., “Controlling SO2 Emission” Cement International , 5/2004 19 Young, G., REVIEW OF SO2

- (HCl) SCRUBBERS, Portland Cement Association, SP129, 2002 20 REPORT IN SUPPORT OF AN APPLICATION FOR A PSD CONSTRUCTION PERMIT REVIEW FLORIDA ROCK INDUSTRIES, INC. Thompson S. Baker Cement Plant Newberry, Alachua County, Florida, N ovember 8, 2004, http://www.dep.state.fl.us/air/permitting/construction/fri/PSDREPT.pdf 21 Telephone conversation with Al Linero, FL DEP,8/22/08 22 Peray, K., The Rotary Cement Kiln,

### Andover Technology Partners Page 25 (TPY/(8760*0.85)) * EGFW

– mo isture from combustion (for other kilns)

Where EGFW is taken from the
Moisture from combustion can be estimated by multiplying
(TPY/(8760*0.85)) * SFC * LBMH20MMBTU * 379.63
, Where 379.63 cubic feet is the volume of a lb mole of gas at 60 F and one atmos phere and LBMH20MMBTU is fuel dependent and is from Table 3 of the Emissions Memo

. So, equations to estimate dry SCFM are:

DSCFM = (TPY/(8760*0.85)) * (89661

– SFC * LBMH20MMBTU * 379.63 )/60 E.28 (for a wet kiln), and

DSCFM = (TPY/(8760*0.85)) * (EGFW

– SFC * LBMH20MMBTU * 379.63 )/60 E.2 9 (for dry kilns)
Using these equations to estimate dry SCFM, t he capital cost scaling in $/dry SCFM are fairly consistent for References 18
, 19
, 20 , and 21

. But, Reference 17 seems to result in a much higher cost estimate in $/dry SCFM

. The Reference 17 estimate was based upon a PSD analysis for a Lehigh Cement plant. The original source of information cited in Reference 17 was not available to determine if there was anything uniq ue about the plant in that study that made a scrubber so costly to install . A ccording to Refe rence 21 , this project included a plant expansion, which might mean other costs are incorporated into the reported scrubber cost

. On the other hand
, the other re ferences were relatively consistent

. Based upon these references, a cost in the range of $75/DSCFM (2004$) was assumed for an estimated 114,000 DSCFM plant . On this basis, assume the following algorithm:
CC (2004 $) = $ 75 *DSCFM* (114,000/DSCFM)^0.4 = $7900 * DSCFM ^0.6 CC (2005$) = $ 8650 * DSCFM^0.6 E.30

Fixed Costs

Reference 23 estimated $186,553 in annual costs for Operating, Supervisory, and Maintenance Labor and Maintenance Materials on a 1.2 million tpy plant

. These fixed costs do tend to scale somewhat with size. Additional costs estimated were replacement parts at roughly 5% of purchased equipment cost (or, roughly 2.5% of capital cost). Also assume 4% of capital costs for taxes, insurance, etc.
FC (2008$) = ( $186,55 3/1.2 million tpy)*TPY * (1.2 million/TPY) ^0.4 + 0.04* CC

= $42*TPY^0.6 + 0.04* CC

23 Bahner, M., Icenhour., M., Laney, M., Barnett, K., memo to Docket #: EPA

- HQ

- OAR

- 2007

- 0877, Re: Summary of Environmental and Cost Impacts of Proposed Revisions to Portland Cement New Source Performance Standards (40 CFR Part 60, subpart F), May 29, 2008

### Andover Technology Partners Page 26 FC (2005$) = $38*TPY^0.6+ 0.04* CC E.31

Variable Costs

The kiln uses calcite (CaCO 3 

### ) which is the major constituent in limestone. It also consumes power and water, and it will also produce gypsum. The gypsum is a useful by product that is used to make the finished cement

.

**•** Limestone

**•** Water

**•** Power

**•** Gypsum

Limestone

- Calcite is used at a stoichiometric rate of about 1.03 moles of CaCO 3 

### pe r mol e of SO 2 

### to achieve over 9 0 % reduction , and typically 95% or so reduction

. 18 

### Since CaCO 3 

### has a molecular weight of 100 and SO 2 

### has a molecular weight of 64, it takes about 1.70 pounds of pure calcite to capture one pound of SO 2 

### . If limestone cost is $15/ton, then the limestone cost is roughly $25.5 /ton of SO 2 

### removed divided by the limestone purity

. A limestone of 90% calcite would then cost $28/ton of SO 2 

### removed

Water

- Makeup water is necessary for the scrubber to compensate for the moisture that is added to humidify the gas and is released to the atmosphere . The amount of makeup water was estimated in two ways that produced r esults that came out close to one another:

**•** comparing moisture inherent to kiln gas to the moistur e to saturate gas at roughly 140 F.

**•** using a rule of thumb for power plant scrubbers (1.4 gal/MW and 2500 SCFM per MW) and applying it to the estimated gas flow for cement kilns
For most kiln types the estimated makeup water came out to abou t 30 gallons per ton of clinker. At $0.05/1000 lb of water ($0.0004 2 /gallon), this is equal to $0.0125/ton of clinker.

Power

- The D ynawave scrubber by Monsanto has roughly a n 18 IWC pressure drop according to Ref. 19 and a pressure drop of 8 IWC according to Ref. 24 . The pressure drop will req uire additional fan power. Reference 25 shows that to estimate fan kW,
Shaft kW = Q * dp / (367,000 * fan efficiency) E.32
Where Q is in actual cubic meters per hour dp is in mm H 2 

### O

24 Koskolos, B, “Unique Slurry Scrubber for Cement Kilns”, International Cem ent Journal, 2/1998 25 The Cement Plant Operations Handbook, Third Edition, International Cement Review , November 2001

### Andover Technology Partners Page 27 T here are about 35.5 SCF/N m 3 

### . And, if the exit tempera ture of the wet scrubber is 150 0 F (65 ° C), 18 inches of water pressure drop is assumed, and a fan efficiency of 75% is assumed, the equation can be shown to be equal to:

Shaft kW= (TPY/(8760*0.85)) * (EGFW/35.5) * ((273+65)/273)* 18 * 25.4 /(367,000* 0.75)

= (TPY/(8760*0. 85)) * EGFW * 5.8 (10) - 5 

### E.33

So, for a 150 tph precalciner kiln, the fan load would be

150 * 44,878 * 5.8 (10) - 5 

### = 390 kW
To account for additional power for pumping liquids and slurry and for preparing limestone, etc., add roughly 15%, or about 450 kW for 150 tph kiln, or 3 kW hr per ton of clinker. To get annual kWhrs, multiply 3 kWh/ton time s the TPY of clinker. And, to get the cost of power, multiply by COSTKWH in $/kWhr. Gypsum

- The final effect is the gypsum, which is useful and has a value to t he cement

making process if it offsets purchased gypsum . Gypsum values vary based upon location. A ccording to Reference 26 , this is worth about $45/ton to a cement plant since they would otherwise have to buy it

. For every 64 tons of SO 2 

### captured, this re sults in about 136 tons of CaSO 4 

### , or 172 tons of gypsum (CaSO 4 

### :2H 2 

### O)

. So, this may have the effect of producing an offsetting benefit worth about $ 120 /ton of SO 2 

### removed. Using the data of T able 9 from the Emissions Memo as LBSO2 CLINKER in lbs of SO 2 

### per ton of clinker, and assuming 95% removal, you get Total Variable cost = TPY * {[ LBSO2CLINKER * 0.95* ( 28

- 120 ) /2000] + EGFW * 5.8 (10) - 5 

### * 1.15* COSTKWH } +TPY*0.0125 = TPY* { EGFW*6.67 (10) - 5 

### * COSTKWH

- 4.4 (10) - 2 

### LBSO2CLINKER + 0.0125 } E.34 a If gypsum from the FGD cannot be used, then

= TPY*{EGFW*6.67 (10) - 5 

### * COSTKWH +1.3 (10) - 2 

### LBSO2CLINKER+ 0.0125} E.34b Impacts The primary impact of a scrubber is SO 2 

### removal

– 95% removal of SO 2 

### is a reasonable assumption to make considering that Reference 27 found scrubbers providing capture efficiencies ranging from about 91% to about 99% . There are other pollutants removed as well, such as mercury, PM, and heavy metals. Water consumption and power demand are significant, and were discussed earlier

.

26 Laney, M., memo to Docket # EPA

- HQ

- OAR

- 2007

- 0877, Re: Use of Synthetic Gypsum at Holcim Plant with Wet Scrubbers, May 23, 2008 27 Bahner , M., Laney, M., Barnett, K., memo to Docket # EPA

- HQ

- OAR

- 2007

- 0877, Re: Summary of Cement Kiln Wet Scrubber and Lime Injection Design and Performance Data, May 29, 2008

### Andover Technology Partners Page 28 Dry Li me Injection (DLI)
Dry Lime injection (DLI) simply entails injecting dry lime from a silo into a location in the ductwork where the lime can react with the SO 2 

### . SO 2 

### released from pyritic sulfur in feed materials doesn’t get exposed to lime from the calcined feed materials because of where this SO 2 

### is released. Lime might be added to a location in the preheater tower or at another location to capture some of the SO 2 

### released from feed materials as CaSO 4 

### . Generally, this approach is lo w in cost but results in modest SO 2 

### emissions reduction

. Capital Cost
Table 7 shows estimates of capital cost for a dry lime injection system

Table 7. Dry Lime Injection Capital Costs
Kiln type Size, tph, (TPY) Capital Cost Reference PH/PC 125 (990,000) $160,000 18
Scaling this to estimate capital cost:
CC (2004$) = (160000/990000) * TPY * (990000/TPY)^0.4 = 40 * TPY ^ 0.6
CC (2005$) = 44 * TPY ^ 0.6 E.35

Fixed Cost
The fixed cost would be fairly low since the equipment is simple. Assume 4% of capital for taxes, insurance and overhead. Plus assume similar maintenance costs as for low NOx burners

- $59,00

.
Variable Cost

Variable cost is the cost of the lime plus power

. There is power used to transport the lime, but this is very small

. According to Reference 18 , a stoichiometric ratio of 3:1 or 5:1 might be needed , and this provides about 50% reduction. However, this will vary quite a bit from plant to plant.
Using 4 :1, this means that you would react 4.63 tons of Ca(OH) 2 

### for every ton of SO 2 

### and capture half of that SO 2 

### , or 9.25 tons of hydrated lime for ea ch ton of SO 2 

### removed. With the hydrated lime cost at about $ 130 /ton, this equates to $ 1200 /ton of SO 2 

### captured or $ 600 /ton of SO 2 

### in the gas stream

. Power can be estimated by assuming that a gas flow of perhaps 5% of the kiln volume is used to transport the lime. If a pressure drop of 10 IWC is assumed, this is estimated to be about 0.05 kWhr per short ton of clinker.

### Andover Technology Partners Page 29 No water is necessary for dry lime injection and there is no by

- product to dispose of. In fact, the by

- product, calcium sulfate, actually contributes to the final product.

Total Variable cost = TPY * [ LBSO2CLINKER * 345 /2000 = 0.17 * TPY * LBSO2CLINKER + 0.05*COSTKWH E.36

I

mpacts
The major impact is a roughly 50% reduction in SO 2 

### , that will in fact vary from facility to facility. There may be an impact on the kiln’s particulate control device. But this will be very site specific.

### Andover Technology Partners Page 30 CKD wet scrubber (Passamaquoddy Technolo gy)
Passamaquoddy Technology (PassTech) is a technology that enables SO 2 

### reduction by use of cement kiln dust (CKD). CKD is composed primarily of oxides of calcium, potassium, magnesium and silicon . Without a means of utilizing CKD, CKD must be disposed of. CKD was shown to be effective as an SO 2 

### capture reagent in the Pa ssTech technology. PassTech was in operation at the Dragon Cement wet kiln in Maine as part of a DOE sponsored program

. However, this wet kiln has since been modified to a precalciner kiln.

PassTech is primarily applicable to wet kilns because on other kiln types CKD disposal is not an issue. For dry kilns CKD can be readmitted to the kiln depending upon whether or not the kiln has an alkali bypass system and the alkali co ntent of the CKD and the resulting clinker. W ith wet kilns the CKD can increase the viscosity of the slurry too much to be readmitted to the kiln , which may require more water or less CKD

. According to Reference 28 , the capital cost of a PassTech scrubber is roughly $10.5 million (1996$) for a 450,000 TPY kiln, or about $23.3/ton of clinker , which is significantly more expensive than a wet scrubber. According to Reference 28 , the economics of the PassTech technology are heavily impacted by the ability to receive tipping fees for accepting waste from paper mills and also to sell potassium sulfate fertilizer. Moreover, in light of the general trend toward replacement of wet process kilns with larger and more efficient precalciner kilns, expenditure of large amounts of capital on these kilns is probably unlikely. As a result, this technology is probably only a niche technology and is not examined further.

28 US DOE, “Cement Kiln Flue Gas Recovery Scrubber Project: A DOE Assessment”, DOE/NETL

2002/1163, November 201

### Andover Technology Partners Page 31 

## Oxidation Technologies

Oxidation technologies entail oxidizing NOx to soluble forms and then washing them out. Lo

- Tox is one such technology offered by BOC gases to remove NOx from the gas stream. It consists of an ozone generator that introduces ozone into the e xhaust gas to oxidize NOx to water soluble species. Other approaches entail injection of hydrogen peroxide or other means. In any event, after the oxidation the soluble forms of the pollutants are then washed out of the gas in a downstream water wash or a wet scrubber.

Reference 8 developed a cost estimate of LoTox for some kilns in Texas

. C apital cost for wet kilns (unscrubbed) ranged from $10/ tpy to $20/tpy. This averaged out to $16.80/tpy for kilns in the range of 280 tpy.
For precalciner kilns with scrubbers, the cost per tpy ranged from $3/tpy for a 1,964,000 tpy kiln and from $5

- $7/tpy for roughly one million tpy kilns.

Table 8. Economics of LoTox at Texas cement kilns 8

Existing Unit Control Technology Capital Cost per

kiln millions Capacity per kiln

1000 tpy * Normalized Cost $/tpy Annual Cost millions Effectiveness $/ton NOx Burden Cost $/tonne clinker Ash Grove #1

- wet (c} LoTOxTM $4.80 291 16 $1.4 $3,400 $5.00 Ash Grove #2

- wet (c} LoTOxTM $5.20 291 18 $1.5 $3,500 $5.40 Ash Grove #3

- wet (c} LoTOxTM $5.80 291 20 $1.6 $3,700 $5.70 TXI #1 & #4

– wet (b,c) LoTOxTM $5.40 273 20 $1.6 $3,300 $4.70 TXI #2 & #3

– wet (b,c) LoTOxTM $2.80 273 10 $0.5 $11,000 $10.50
TXI#5

– dry LoTOxTM $5.20 1,964 3 $2.4 $2,600 $0.90 Holcim #1

– dry LoTOxTM $6.70 987 7 $3.1 $2,400 $2.35 Holcim #2

– dry LoTOxTM $5.40 1,028 5 $2.5 $2,300 $1.90 *From US and Canadian Portland Cement Industry: Plant Information Survey, December 31, 2006



### Using this information, the following algorithms might be used to estimate the cost of a LoTOX system

For scrubbed kilns:
CC(2006$) = $6 * TPY* ( 1 million/TPY)^0.4 = $1500 * TPY^0.6
CC(2005 $) = $1 460 * TPY^0.6 E.37

### Andover Technology Partners Page 32 For unscrubbed kilns:
CC (2006$) = $16.8 * TPY * (280000/TPY) ^0.4 = $2536 * TPY^0.6
CC (2005$) = $2 467 * TPY^0.6 E.38

Fixed Cost
4% of capital cost for taxes, insurance, overhead, etc. Other fixed costs should also be relatively low

– similar to that of a dry injection system.

Variable cost

A major variable cost is power to produce ozone . Based upon information in a table in Reference 29 , the power consumption appears to be roughly 2300 kW per ton of NOx removed. Another cost is oxygen , and then a modest cost for water

. The information in the table provided in this reference enables the total variable cost to be estimated at about $2,17 5/ton of NOx removed. So, annual variable costs would be calculated by:

VC= $2175* (0.90)* TPY*SFC*NOXLBMMBTU /2000 E.39
Impacts
LoTOX can produce about 90% NOx removal. Reference 8 assumed 85% , but the variable cost calculations are based upon 90% removal . Other pollutants that are destroyed by oxidation, such as hydrocarbons, can be reduced as well.

29 Letter from Steve Eckhardt, BOC Gases, to Christa O. Russell, Schreiber Yonley & Associates, October 4, 2006

### Andover Technology Partners Page 33 Combinations of Combustion and Gas Treatment Technologies
This memo covered a range of control technologies. However, the ISIS model being developed by EPA will initially incorporate only those technologies or technology combinations that are most likely to be applied. This is not to disparage any technology

o r technology combination. However, this is to initially keep the modeling options simple. The other technologies and technology combinations can be added later as experience with the model is gained, and it is envisioned that this will be done with time.

C ombustion and post combustion technologies normally can be combined. However, some combinations may be technically infeasible or may be feasible but very unlikely. An example of a situation that is feasible but unlikely is addition of SNCR or SCR with out LNB or some form of combustion controls. P ost combustion NOx control technologies would not likely be used without first installing combustion controls, since combustion controls are generally less expensive.
Some of the technologies discussed in thi s memo are feasible but have not been employed , likely due to less expensive alternatives . LoTox is an example of this. For the purpose of the model, LoTox will not be included. It may be added later. M ixing Air Technology (MAT) appears to have signifi cant application potential since it can improve performance of Mid Kiln Firing systems. However, we will not include it at this time due to uncertainties in how much improvement results from it. Ris er Duct Firing (RDF) of tires on preheater kilns and MKF effectively provide similar benefits and are expected to have similar cost. For the purpose of the model they are being treated as similar technologies

. Low NOx Calciner (LNC) is a technology that, for the time being, will be assumed to be instal led on existing precalciner kilns. Once more information is gained on application of LNC , we may decide to include it in ISIS.

Table 9 shows technology combinations and kiln types where these combinations may apply: Table 9. Technology Combinations and Applicable Kiln Types Technology Combination Applicable Kiln Types LNB all LNB + MKF (coal or tires ) W, LD, PH * LNB + SNCR all LNB + MKF + SCR W, LD, PH * LNB + SCR all Wet FGD May be combined with NOx controls all
Dry Lime Injection May be combined with NOx controls PH, PC
* For the purpose of the model, RDF for PH kilns is being treated as MKF

### Andover Technology Partners Page 34 

## Process Modification
Slag injection (ie, Cemstar) or Fly Ash addition
Cemstar, or slag injection or power plant fly ash addition has several benefits:

**•** Reduction of NOx

**•** Reduction of heat input

**•** Increase of kiln output

**•** Reutilization of what would otherwise be a waste

**•** Reduction of CO 2 

### emissions per unit of clinker produced

As noted in the discussion on calculation of CO 2 

### emissions when using steel slag, the amount of slag used varies between about 5% and 10% of the clinker output because of the need to obtain the right mineral matter constituents in the clinker. So, 7.5% slag addition might be considered a reasonable ave rage. Applicability
All kiln types
Capital Costs
The capital costs for CemStar are mostly associated with the material handling equipment to handle the slag, and are in the range of $1 million, as shown in Table 10 from Reference 1. 1
, 4



### Table 10

. Basis for Cost Analysis of CemStar (1997 $) Capital Cost of Material Handling Equipment $500,000 Type of Kiln Wet Primary Fuels Coal and natural gas Kiln Production Rate

Before CemStar 42 tons/hour After CemStar 45 tons/hour Quantity of Steel Slag 3.2 tons/hour Average kiln heat requirement 5.00 MMBtu/ton Total Capital Investment $1,176,000 Annualized Cost a 

### $220,000

a 

### Includes cost of steel slag, royalties, and credit for the reduction in raw materials.
The $1.17 million would be $1.47 million in 2005$

No information was found for capital cost associated with fly ash addition. Assume similar capital costs for addition of fly ash.

### Andover Technology Partners Page 35 Fixed Costs
Because the equipment for Cemstar is very minimal, the additional fixed cost should be fairly low. Assume 4% of capital for taxes, insurance, etc. plus additional maintenance in the range of $59,200 (similar to combustion technologies).

Variable Cost Although steel slag may be used as a substitute for limestone that reduces the limestone

n ecessary for the same clinker output, the cases I have evaluated have been where limestone feed was not reduced, but output of the kiln was simply increased in proportion to the slag being added on roughly a ton

- for

- ton basis. As a result, in most cases I would not envision a reduction in limestone demand for the kiln, although a reduction in limestone used per ton of clinker due to the increased output would be experienced. There is a reduction in iron to be added from other minerals. And Reference 1 es timates the savings to be roughly $0.50

- $1.00 per ton of clinker.

Because in most cases CemStar is used to increase kiln clinker output o n close to a ton

for

- ton basis with the use of steel slag, the variable cost (or be nefit) equals the difference betw een increased clinker revenues and increased cost of using steel slag. Steel slag cost s in the range of $5

- 15 per ton, whereas clinker cost is estimated in Reference 1 to cost $72.59 per ton. Market conditions will also affect these prices. Average cost savings equal $62.59 per ton times increase in production. Most plants increase production by five to ten percent with the addition of the CemStar process. The Levy Company that offers CemStar is also a marketer of slag. So, the revenues they receive from selling the steel slag address any license fees. In the past when TXI owned Cemstar and often didn’t sell the slag, royalties we re imposed at approximately $16 per ton of steel slag used. 1


### The variable cost will be equal to the cost for purchasing slag and for power plus the cost of any additional fuel to pyroprocess the incremental steel slag . According to Reference 1 , the costs include roughly $16/ton of slag in royalties plus the cost of slag, roughly $5

- $15 per ton, or a total cost of $21

- $31/ton. With clinker cost at $72.59/ton (2000$), and

av erage slag cost of $10/ton, savings are about $62.59 per ton. 1 

### If royalties of $16/ton of slag are considered, this will cause net savings to equ al about $45

- $50/ton, neglecting incremental pyroprocessing fuel. However, in most cases this license fee will not apply since Levy Company would likely sell the slag to the user. Because the steel slag is chemically similar to clinker, most of the incre mental heat needed is simply to melt and dissociate the slag . With slag t here is no energy requirement for calcining or for some of the other chemical transformations that are necessary for limestone, shale, clay and sand.
According to EIA 767 data, fl y ash costs are similar to those of steel slag (on the order of $5

- $15/ton, sometimes more and sometimes less). Fly ash would likely be used as a substitute for shale. But, depending upon the mineral composition of the fly ash, it might be used as a subs titute for other materials , such as limestone . There are no royalties for use of fly ash as a substitute material. Assume similar economics as Cemstar for variable cost, with the exception of the royalty.

### Andover Technology Partners Page 36 In most cases, slag is used to increase the output of the kiln. The increased output of the kiln will increase the power demand for finish milling the clinker to Portland Cement. According to Reference 25
, finish milling requires roughly 27

- 35 kW/ton, depending upon the mill types and characteristics of the clinker. Using the average and assuming roughly one ton of additional clinker per ton of slag added, that would be 31 kW/ton of slag added . Assuming that slag addition is 7.5% of kiln clinker output, the incremental power would be about 2.2 kW/ton of total clinker output . There is additional power associated with handling the slag on the front end. But, thi s is minimal compared to the additional milling demands from the increased kiln output. The incremental power for finish milling is important fo r the particular cement plant . However, finish milling is necessary for all clinker. So, assuming a constant total demand, to the extent that the finish milling load for one plant increases, it may alternatively decrease elsewhere.
Impacts

Studies have shown that Cemstar reduces CO 2 

### emissions and NOx emissions per ton of clinker. Testing on a precalciner kiln showed CO 2 

### reductions of 4% on a ton of CO 2 

### per ton of clinker basis . On a long

- term test on a wet kiln when firing coal the CO 2 

### reductions were from 4.7% to 13.9% on a ton of CO 2 

### per ton of clinker basis. Reductions in NOx emissions were even greater at about 10%

- 44%, depending upon the feed mix

– 30%

- 44% at the optimal feed mix depending upon slag addition rate. At a wet kiln when firing coal, a 24% reduction in NOx was observed. 1
, 30



### CO 2 

### reduction (on a ton/ton of clinker basis) can be assumed to be about equal to the percent of slag added because the slag is contributing to higher output on roughly a ton for ton basis without additional cal cination and with minimal additional heat demand. So, if 7.5% of rated clinker output without slag is the average percentage for slag addition, that is roughly the average for CO 2 

### reduction on a ton of CO 2 

### per ton of slag basis. This is roughly consisten t with the results of testing. By and large, operators tend to use the slag to increase output of the kiln rather than to reduce the limestone being added or the fuel use.
NOx emission reductions will vary by kiln. But, a NOx reduction of about 30% on a lb/ton of clinker basis should be reasonable for most kilns.
There will be a slight increase in power demand on the kiln since the slag requires some additional material handling

. Finally, questions have arisen about the possibility of Cr +6 

### release from steel slag. Studies have shown that Cr is generally present in the trivalent form , rather than the more mobile and toxic hexavalent form
, in steel slag

. 31

30 Staudt, J., “Steelmaking Slag as Recovered Mineral Components (RMC) in Portland Cement Production”, for National Slag Association, December 12, 2007 31 Chaurand, et. Al., “Environmental impacts of steel slag reused in road construction: A crystallographic and molecular (XANES) approach ”, Journal of Hazardous Materials
, HAZMAT

- 5460 , Elsevier, 2006, http://www2.ademe.fr/theses

- fichiers/604_ChaurandJHM.pdf , viewed March 9, 2009

### Andover Technology Partners Page 37 Conversion from Wet to Dry

Conversion of an existing Wet kiln to a preheater/precalci ner kiln is estimated to be between $50/tpy and $100/tpy in capital by Reference 32 . This is likely in 1999$. A more recent study estimated costs in the range of $130/tpy for TXI’s Midlothian Plant wet kilns and about $190/tpy for the Ash Grove Midlothian plant wet kilns. 8 

### These costs start to approach the cost of a new plant of around $200/tpy. 33 

### However, in that particular study , the kilns were assumed to be replaced with a single precalciner kiln that was of the same size. So, the existing kilns were not modified, but replaced. In practice, it would make more sense to replace those small, wet kilns with a precalciner with much more capacity th an the multiple wet kilns altogether. 8 

### So, the $130

- $180/tpy cost may be artificially high due to the constraints of that study. Using a value of $ 75 /tpy (1999$) for the cost of conversion of a single existing wet kiln to a shor ter kiln and addition of a precalciner with a median size of about 300,000 tpy from the Cap+Trade workbook, would provide the formula below.
Applicability
Wet kilns only
Capital Cost :
CC(1999 $) = $75 * TPY * (300,000/TPY) ^ 0.4 = $ 11,638 * TPY^0.6
CC(200 5$) = $ 14,442 * TPY^0.6 E.40
Where TPY is the annual clinker capacity in short tons per year of the final kiln size (if expanded.

Fixed Costs
The increase in fixed costs would partly be additional taxes and insurance, at 4% of capital.
Another effect would be on labor. According to Reference 34 productivity at dry kilns in 2006 was 3.15 tons per employee hour and at wet kilns it was 2.15 tons per employee hour.

32 Energy Efficiency Improvement Opportunities for Cement Making An ENERGY STAR Guide for Energy and Plant Managers, Lawrence Berkel ey National Laboratory, January 2004. 33 E

- mail from Greg Mayes, TXI, June 2, 2008 34 Portland Cement Association, U.S. AND CANADIAN LABOR

- ENERGY INPUT SURVEY , 2006, ER374

### Andover Technology Partners Page 38 Variable Costs
Variable costs would entail a significant reduction in fuel d emand and a likely increase in power use. Reference 32 showed roughly a 9 kW/ton clinker increase in electric load. This is because dry materials are harder to g rind.
Impacts
Specific Fuel consumption would drop, from an estimated 6.38 MMBtu per short ton of clinker to 4.05 MMBtu per short ton of clinker, or a roughly 2.3 MMBtu per short ton reduction in fuel requirement.
Capaci ty c ould increase since the thermal demand on the kiln per ton of c linker is much lower for a precalciner.
Overall, all emissions would drop. CO 2 

### emissions would drop due to the reduction in fuel demand. NOx and SO 2 

### emissions would both to emissions levels typical of a precalciner, which h as lower emissions than a wet kiln.
Water consumption would also drop. Moisture added to the materials of a wet kiln amount to about 0.3

- 0.4 tons per ton of raw material, or about 0.6 tons of water per short ton of clinker , assuming about 1.7 tons of raw material per ton of clinker

. 35

35 Peray, The Rotary Cement Kiln , Chemical Publish ing Company, New York, 1986 , pg 6

### Andover Technology Partners Page 39 Conversion from Wet to Semi

- Wet

Conversion from a Wet kiln to Semi

- Wet using filter presses to reduce moisture consumption is described in Reference 36 to cost about $1.6/tpy (1996$).
Applicability
Wet kilns only
Capital Cost : Using $1.6/tpy and an average kiln size of about 280 tpy.
CC(199 6$) = $1.6 * TPY * (280,000/TPY) ^ 0.4 = $241 * TPY^0.6
CC(2005$) = $306 * TPY^0.6 E.41

Fixed Costs
The increase in fixed costs would partly be additional taxes and insurance, at 4% of capital.

Variable Costs
Variable costs would entail a significant reduction in fuel demand and a likely increase in power use. Reference 36 showed roughly a 3

- 5 kW/ton clinker increase in electric load and a reduction in heat input of 1 MMBtu/ton.
Impacts
NOx, SO 2 

### and CO 2 

### emissions would all drop as a result of the reduction in heat input. Reductions in NOx and combustion CO 2 

### can be directly related to the reduction in heat input. SO 2 

### emissions reduction is more difficult to estimate because SO 2 

### emissions also result from materials.

36 Energy Efficiency Improvement Opportunities for Cement Making An ENERGY STAR Guide for Energy and Plant Managers, Lawrence Berkeley National Laboratory, January 2004.

### Andover Technology Partners Page 40 Conversion from Dry to Multi

- Stage Preheater
According to Reference 32 , the cost of upgrading a long dry kiln to a multi

- stage preheater kiln is about $36

- $37/tpy (1993$) for conversion to a multi

- stage preheater, while addition of a suspension preheater would be in the range of $25/ tpy (1994$).
Applicability
Long Dry Kilns
Capital cost
From the Cap+Trade worksheet, the median long dry kiln is about 250,000 tpy. Using this as the basis to estimate capital cost,
CC (1993$) = $36.5 * TPY * (250000/TPY)^0.4 = $5256 * TPY ^ 0.6

CC (2005$) = $ 7114 * TPY ^ 0.6 E.42

Fixed Cost
This will largely be the insurance and taxes, about 4% of capital cost.

Variable Cost
Fuel Costs will drop due to the higher efficiencies of preheater kilns. This is determined by the change in the Specific Fu el Consumption associated with dry and preheater kilns.
Impacts
NOx, CO 2 

### , and SO 2 

### will be reduced because preheater kilns have significantly lower emissions of each of these. This will result in change in SFC as well as change in the specific emissions ra tes for the kiln type.

### Andover Technology Partners Page 41 Conversion from Long Dry to Preheater Precalciner
Applicability
Long Dry Kilns
Capital Cost
Conversion of a long dry kiln to a preheater/precalciner is estimated to cost in the range of $21

- $26/tpy (1993$). 32 This is actually lower than the reported cost in Reference 32 to convert a long dry kiln to a preheater kiln, which is contrary to what is expected. As a result, I recommend that a higher number be used, perhaps $45/tpy.
CC (1993$) = $45 * TPY * (250000/TPY)^0.4 = $6492 * TPY ^ 0.6
CC (2005$) = $8787 * TPY ^ 0.6 E. 43

Fixed Cost
This will largely be the insurance and taxes, about 4% of capital cost.

Variable Cost
Fuel Costs will drop due to the higher efficiencies of precalciner kilns. This is determined by the change in the Specific Fuel Consumption.
Impacts
NOx, CO 2 

### , and SO 2 

### will be affected by the change in SFC as well as change in the specific emissions rates for the kiln type.

### Andover Technology Partners Page 42 Conversion from Preheater to Precalciner
This primarily entails addition of a calciner and associated ductwork and burner piping. It may also entail an additional preheater stage. As such, it would be expected to be much less expensive than conversion of a long dry kiln to a precalciner. This will generally have the effect of increasing capacity, reducing specific fuel consumption and reducing some emissions.
Applicability
Preheater only
Capital Cost

Reference 32 assumes a cost of around $15/ton of clinker based upon two data points, $28/TPY i n 1994 and $8.5/TPY in 1996). The median preheater kiln size in the Cap+Trade workbook is 414,000 TPY. Using these numbers,
CC (1995$) = $15 * TPY * (414000/TPY)^0.4 = $2648 * TPY ^ 0.6
CC (2005$) = $3123 * TPY ^ 0.6 E.44

Fixed Cost
This will largely be the insurance and taxes, about 4% of capital cost.

Variable Cost
Specific fuel consumption will drop due to the higher efficiencies of precalciner kilns. This is determined by the change in the Specific Fuel Consumption. Also, capacity will be increas ed. Reference 32 gave examples of capacity increases from 58% to about 80%. An average capacity increase might be 65%.
Impacts
NOx, CO 2 

### , and SO 2 

### will be affected by the change in SFC as well as change in the specific emissions rates for the kiln type.

Note:
This may seem like an easy and inexpensive a way to increase capacity. However, there are other issues to consider, such as the adequacy of l imestone reserves, the triggering of harsher environmental requirements, and how much of a boost in capacity will occur versus other capacity expansion options.

### Andover Technology Partners Page 43 Low Pressure Drop Cyclones
Cyclones are a basic component of most preheating systems. Newer cyclones with lower pressure losses will reduce gas pressure drop and load on the exhaust gas system. For most olker kilns this amounts to 0.6

- 1.0 kWh/ton of clinker, but examples of kiln s where 4 kWh/ton were saved exist. 32 

### It may be beneficial to also add an in

- line raw mill to address possible increases in dust loading carried over from the preheater tower.
Applicability

Preheater kilns
Capital Cost

Reference 32 indicates a capital cost of $2.7/TPY for a low pressure drop cyclone system.

Fixed Cost
None, other than 4% for additional taxes, insurance, etc.

Variable cost

Reduction of load will reduce v ariable cost of operating the plant by about $0.03/ton assuming 0.8kWh/ton saving and electric cost of $35/MWhr.
Impacts
Reduced power demand and possible increase in dust carryover from preheater tower.

### Andover Technology Partners Page 44 New kiln or Expansion
Generally, new kilns are ins talled as part of facility expansions or upgrades, as new kilns are usually larger in capacity than older kilns that they replace. Or, new kilns can be installed as part of new plants. Most new kilns are part expansion of existing sites. But,

some are new, green

- field facilities. According to Cement Americas:
Significant increases in clinker capacity are expected to materialize during 2008

— 2012. The U.S. cement industry has announced plans to increase clinker capacity by nearly 25 million metric ton s between 2007 and 2012. The aggressive capacity expansion reflects a $5.9 billion investment, which will increase capacity 27% compared to 2006 U.S. clinker capacity. The expansion spans seven greenfield sites and expansion of 18 existing facilities 37



### Th us, the “blended” cost of all of these facilities is about $236/ tonne or about $213/short ton , which is consistent with information from Reference 33 . Reference 25 provides some insight to the difference in cost between expansions and green

- field plants.
New green

- fie l d ce m ent p l an t s cost $ 2 0 0

- 300 pe r t onne of a n n u a l prod u c t io n , w hi le k iln ex pan s i ons co s t $8 0

- 150 d e p en d ing u po n th e u sa bl e excess c ap aci t y o f

ex i sti n g a n c ill ary e qui p m en t and s t orage

. Per mitt i n g of h eavy i n dus t r i al faci lit ies b eco m es ev er more diff ic ul t a nd ex p e n s i ve, so t h a t co n si d era bl e inta n g ibl e value may at t ac h t o an ex i s t i n g o p era t io n a nd it s m ark et , ev e n i f th e e qui pm e nt is

a nt i qu a t ed a nd i n eff i cient

.
Reference 25 provided the estimate in Table 11 for a “typical” project to add 1.5 million tonne per year to an existing plant.

Table 11 . “Typical” 1.5 million tonne/year expansion to an existing plant (Ref 25 )

Equipment Qua r ry equipment US$3,000,000 Raw milling & blending 13,000,000 Kiln
, preheater & cooler 18,000,000 Coal s y s tem & storage 5,000
, 000 Clinker storage 3
, 000,000 Cement milling 9,000
, 000 Cement storage and pac k ing 3,000,000 Electrical & cont r ol 9.000,000 Sub

- total $63,000,000 Civil, structural & erection $38
, 000,000 Engineeri n g, construct i o n m a nagement, f r eight,

co mmis s ioning $19
, 000,000

Owner's c apitalised cost $5
, 000,000 Construction interest $ 14
, 000
, 000 Spares $4,000,000 Contingency (5%) $7,000,000 Total project cost $150,000,000

37 Cement Americas: downloaded at http://cementamericas.com/mag/cement_forecast_0101/

### Andover Technology Partners Page 45 The choice between expansion of an existing facility to fulfill growing demand and Greenfield is complex. If cost alone were used, expansion would most often be chosen over Greenfield

. However, the re are other factors. The three most important decision criteria

– starting with the most important

- are:

1. Environmental Factors

– The attainment status of a location or the location relative to a non

- attainment area is very important. If a facility is in an oz one or fine PM non

- attainment area (or upwind of one) , expansion is far more difficult than if it is located in an attainment area. Expansion would certainly be limited by Prevention of Significant Deterioration (PSD) impacts. If no existing plant servin g a market is in an attainment area , and there is a Greenfield site available in an attainment area that can serve the market, Greenfield development may be more attractive than expansion. If there are no sites

– existing or Greenfield

– without non

- attai nment issues, then importing may be the best way to meet increased market demand. 2. Available mineral deposits

– A rule of thumb is that a site needs 100 years of limestone to be viable. Keeping in mind that many existing plants were put in place 40 or mor e years ago with smaller kilns, some sites may not be suitable for expanding with much more capacity due to inadequate limestone reserves

. 3. Qualified labor pool

– Modern cement plants are sophisticated. As a result, the labor pool needs to be able to suppl y workers that can operate and service the equipment and manage the overall plant . Limited labor pools may favor expansion of existing facilities over Greenfield plants that will require addition of more people.
Addressing the choice between expansion and g reenfield will be di fficult in the ISIS model. However, a suggested approach follows. EPA probably knows the attainment status of the county where each kiln is

– or the kiln’s location relative to non

- attainm ent
areas . So, the first effect can be addressed. USGS may have information on available limestone deposits. This information, if available, will make it possible to rule out some sites for expansion. If available, it will also make it possible to iden tify potential g reenfield sites. The third factor is harder to address . But, perhaps it may be unnecessary to do so. A suggested decision tree is shown in Figure 9 to help with the choice between expansion and g reenfield

. The decision tree assumes that it may be possible (albeit, difficult) to expand a facility that is within a non

- attainment area. However, if that is considered too difficult, the decision to meet demand with increased imports to the region may be an alternative

. Another option a ceme nt company might consider is adding a terminal or other options that could provide for demand from outside the immediate area.

### Andover Technology Partners Page 46 Figure 9. Suggested decision tree for expansion of existing facility or Greenfield

.

If limestone information isn’t available, a nother way to approach the decision is to see if there are any plants in a market that are in attainment areas, and these would always be expanded first. If none were in attainment areas, then build a Greenfield plant in an attainment area within the market region. If there are no attainment areas within a market region, then the solution would be to increase imports to the market. Expansion might occur then in an adjacent market.
Capital Costs
So, depending up on the circumstances, green

- field plan t s cost in the range of $180

- $270/short ton (2001$), while expansions can be performed between $72

- $135/short ton (2001$). Selecting the Mid

- Points,

Green

- field CC(2001$) = $225/short ton Green

- field CC(2005 $) = $277/short ton E.45
Expansions CC(2001$) = $105/short ton Expansions CC(2005$) = $130/short ton E.46 Is existing facility in/near non

- attainment area?

Is there a Greenfield site available to serve market that is outside

non

- attainment and has adequate adequate limestone? Expand facility (3 years) Does existing facility have adequate mineral reserves?

no yes yes no

no

yes yes no
Does existing facility have adequate mineral reserves?

Expand existing facility within PSD limits (6 years) Build Greenfield (5 years)

No additional capacity

Or possibly no expansion

### Andover Technology Partners Page 47 However, it should be recognized that actual costs could vary s ubstantially from these numbers

.
Fixed Costs
Fixed costs would be roughly 4% of capita l for taxes, insurance, etc., plus the costs to staff and operate the plant. As a first cut at staffing, use 3.15 tons of clinker per employee hour (average for dry plants in 2006 PCA survey). However, a modern plant would likely be more productive than t his. A 20% greater productivity than average for dry plants, assuming a modern plant, would yield about 3.8 tons per employee hour. In fact, 20% may be conservative.

Variable Costs

Variable costs would be consistent with state

- of

- the

- art technology since new technology would typically be installed . Assume SFC and energy consumption consistent with the most efficient kilns.
Impacts
Expansions would generally be with modern, more efficient, and lower emitting technology. NOx, SO 2 

### emissions would be consis tent with recent BACT determinations. CO 2 

### emissions would be consistent with state of the art as well.

### Andover Technology Partners Page 48 Other Energy Saving Methods

Reference 32 identified numerous energy efficiency improvement opportunities for

cemen t production plants . In addition to kiln process modifications to improve thermal efficiency that were discussed earl ier , there are opportunities facility

- wide to improve energy efficiency. Some of these are discussed below:
High Efficiency Motors

– replacing older motors with higher efficiency electric motors could reduce electric load from 3%

- 8%, and this is estimate d to cost in the range o f $0.2 per annual ton of cement. Assuming that this was in 1993$, in 2005$ this would be $0.27 pr annual ton of cement.
Use of adjustable speed drives (ASD)

– Instead of using single

- speed motors, ASDs permit the speed of the moto r to be varied to match the load for more efficient operation. In this manner pumps, fans and mechanical drives can be operated more efficiently. R eference 32 c ites that potential savings are at 15%

- 44% of the installed power, or roughly 7 KW per ton of cement

. Costs to u pgrade to ASDs vary, but are estimated in a range around $0.9 per annual ton of cement (1993 $), or $1.2 2/annual ton of cement in 2005$.
Compre ssed Air Systems

– Compressed air system efficiency can be improved substantially. It is often overlooked because it is a small part of the total plant load. Reference 32 cites numerous maintenance activities that can improve efficiency; but, there isn’t good quantitative information on the cost and benefit. However, Reference 32 cites that air leakage is another source of inefficiency, and that typical air leakage is between 20% and 50% of total production capacity. Reference states that overall a 20% reduction in annual compressor energy consumption is projected for fixing leaks.
Possible improvement in electric load Overall, each of the above points to a possible improvement in electric load for cement plants. According to Reference 38
, electric loads range from about 17

- 25 kW/ton, with dry kilns generally at the higher end of the range due to the higher grinding energy needed.
It also seems reasonable that the greatest improvement in efficiency is likely from older kiln s that have olde r equipment. A reasonable approach to estimating this might entail assuming a level of potential improvement that is associated with the age of the plant. The cost to achieve the improvement would then be associated with the amount of improvement, to tha t larger improvements cost more money. At this point, am contemplating an approach that would entail, for each kiln estimates of the potential reduction in electricity demand and estimates of capital cost or maintenance cost for that reduction in demand, each of which increase based upon the age of the facility.
For high efficiency motor or ASD savings, I suggest the following:

38 “I nnovations in Portland Cement Manufacturing”, Portland Cement Association, 2004

### Andover Technology Partners Page 49 **•** 2 kW/ton of cl inker in savings for every $0.27 /annual ton of clinker (2005 $) in investment in new motors , with the maximum savings on a sliding scale based upon age of the plant. New plants would have new motors, so the savings would be nil. But, perhaps plants 30 years old or older could get up to the maximum benefit.

**•** For ASD’s I suggest a similar approach

– Up to 7 kW/ton of clinker for every $1.2 0/annual ton of clinker (1993$) in capital investment, with the maximum benefit and maximum cost on a sliding scale based upon age of the plant. New plants would have new equipment, so the savings and cost would be nil. But, per haps plants 30 years old or older could get up to the maximum benefit for the maximum cost

.

**•** I also suggest that you might not want to be able to do both motor upgrade and ASD upgrade

– you could pick one or the other. The reason is that if you replace th e largest motors (such as fans, mills and pumps) with ASDs, you will also be replacing the motors as well. So, the motor replacement option is a less costly approach to get electric savings.
For compressors, according to Reference 32 , the bigg est benefits are li kely from increased maintenance and also from newer controls , and the bigge st benefit is from older plants that have less efficient equipment and more leak s

– the biggest source of inefficiency. The activities identified maintenance measures to improve efficiency and reduce leaks . Improved controls were also identified. Unfortunately, Reference 32 did not quantify the amount of energy that could be saved or at what cost. So we will need to get some more information before quantifying it. However, I suggest a similar approach as the one I suggested for motors
, where the newest plants have no benefit possible and the older plants have the maximum potential benefit.

### Andover Technology Partners Page 50 Appendix List of Terms Term Definition CAPACITYHR CASUB

CC CO2FUEL CO2CLINKER COSTKWH COSTNH3LB COSTNH3YR DLI DSCFM EGFW

FC FF i H LBCO2MMBTU LBMCO2MMBTU LBH20MMBTU LBMH20MMBTU LBNOXHR LBSO2CLINKER LNB LWS MAT MCLINKER MCLINKERHR MKF MLIMESTONE MLIMESTONEHR MSLAG MSLAGHR NOXMMBTU PEC PURLIMESTONE PSD Q SCC SCR SFC SCFH SNCR TDFPC TPY VC Clinker capacity of the kiln in tons per hour Calcium Substitution Fraction

– fraction of total calcium from material that does not need to be calcined Capital Cost Fuel CO 2 in pounds that is released from fuel combustion CO 2 produced by calcination during clinker production Cost of Power in $/KWhr Cost of am monia in $ per pound Cost of ammonia in $ per year Dry Lime Injection Dry standard cubic feet per minute Exhaust Gas Flowrate (wet) in standard cubic feet per short ton of clinker

Fixed Cost Fuel Fraction of i th component of fuel on a Btu basis Burner hea t duty in MM Btu/hr Pounds (mass) of CO2 per MMBtu of fuel input Pound moles of CO2 per MMBtu of fuel input Pounds (mass) of H2O per MMBtu of fuel Pound moles of H2O per MMBtu of fuel Pounds (mass) of NOx per hour Lbs of SO 2 per ton of clinker Low NOx Burn er Limestone Wet Scrubber Mixing Air Technology Mass of clinker in tons Mass rate of clinker in tons per hour Mid Kiln Firing Mass of limestone, tons Mass rate of limestone, tons/hr Mass of slag, tons Mass rate of slag, tons/hr NOx lb/MMBtu for the kiln Purchased Equipment Cost Purity of the limestone

– fraction as CaCO 3 Prevention of Significant Deterioration Flow in actual cubic meters per hour Staged Combustion Calciner Selective Catalytic Reduction Specific Fuel Consumption in MMBtu per ton of clinker Standard Cubic Feet per Hour of gas Selective Non

- Catalytic Reduction Tire Derived Fuel Precalciner Tons per Year of clinker Variable Cost

### Andover Technology Partners Page 1 March 10
, 200 9

To: Ravi Srivastava , Samudra Vijay, Elineth Torres Fm: Jim Staudt

Re: NOx , SO 2 

### and CO 2 

### emissions from Cement Kilns (Emissions Memo)

– revised from comments
In this effort I am developing NOx, SO 2 

### , and CO 2 

### emissions estimating algorithms as well as cost alg orithms for control technologies used in cement kilns. This memo will focus primarily on algorithms to assess emissions, gas flowrates, and heat inputs to cement kilns , which will be useful in helping assess control strategies for cement kilns. Terms use d in the algorithms are shown in a table in the appendices of this memo.
Kiln Energy Intensity
Gas treatment technologies generally have capital costs that tend to be related to the gas volume being treated because this parameter impacts the sizing of th e hardware. Burners have costs related to thermal input

. As a result, it is necessary to relate the kiln type and kiln capacity (in short tons or metric ton ne s clinker per unit of time 1 

### ) to the heat input and /or the gas flow. Fortunately, there is publis hed data to help develop these relations. This approach also has the benefit of permitting us to relate many more things to heat input, such as NOx, SO 2 

### , and CO 2 

### emissions. Heat input is also related to clinker production, depending upon the kiln type. So, algorithms can be produced that are related to clinker capacity, but also take advantage of the relationships with heat input. Fortunately, the Portland Cement Association (PCA) has published data on the heat input to various kilns by type of kiln an d by size. The data is expressed in heat input per unit of clinker and wet gas flow per unit of clinker , and is summarized in Table 1

. Table 1. Specific Kiln Fuel Consumption and Total Exit Gas Flows for Various Kiln Types
Kiln Type Specific Fuel Consu mption (SFC) Exit Gas Flowrate (EGF W ) Kcal/kg MMBtu/sh.ton Low High Avg. Low High Avg. Nm3/kg SCF/sh.ton wet 1,300 1,650 1,475 4.679 5.939 5.309 3.4 108,990 long dry 1,100 1,300 1,200 3.959 4.679 4.319 1.8 57,701 preheater 750 900 825 2.699 3.239 2 .969 1.5 48,084 precalciner 720 850 785 2.591 3.059 2.825 1.4 44,878 Metric units from “Innovations in Portland Cement Manufacturing ”, Portland Cement Association, 200 4 , p 247, and converted to English units for this memo 

### The primary fuel being burned in kilns is coal. However, the kilns have been trending toward using other fuels, particularly alternative fuels, such as coke, waste tires, and

1 Clinker capacity is normally expressed in metric ton ne s (tonnes) or in short tons (tons) per hour. 

# Andover Technology Partners

### Andover Technology Partners Page 2 other waste , especially oily wastes . Table 2 shows different fuels and available heat at 700 0 C for a kiln. 2 

### Bear in mind that the heat values of Table 2 are representative and there is significant variation among fuels and the manners in which plants measure and report this data

. Figure 1 shows the temperature of the material and the gas as it passes though the kiln. As shown in Figure 1, 700 0 C is where preheating of feed material ends and where calcination begins

. 2 

### A cement kiln is a counter

- current heat exchanger, so is important to keep in min d that the gas flow is from left to right (initially increasing but then steadily decreasing temp) and the material is passing from right to left (steadily increasing temp and then temp drop) as it transforms from raw material to clinker.

Table 2 Comparis on of “Available Heat” at 700 C of Different Fuels

Hansen, E., "Changing Process Priorities when Firing Alternate Fuels", 2003 IEEE PCA meeting

Hansen, E., "Changing Process Priorities when Firing Alternate Fuels", 2003 IEEE PCA meeting

2 

### Hansen, E., "Changing Process Priorities when Firing Alternate Fuels", 2003 IEEE PCA meeting

### Andover Technology Partners Page 3 The most impor tant fuels are Coal, Petroleum Coke, Tires/Tire Derived Fuel (TDF) and Heavy Fuel Oil (HFO). Other fuels are not as widely used or are difficult to characterize in general. Liquid hazardous waste may be oily waste with significant moisture content (thus a low heating value) that would produce similar CO 2 

### per Btu of heat input as heavy fuel oil, but with a higher moisture content . In order to relate the gas flowrate to heat input for coal, calculations were made. The combustion calculations in the Consta nts_CC worksheet of CUECost 3 

### were used in order to estimate the CO 2 

### and moisture generation from bituminous coal combustion (shown as Logan, WV BIT) , PRB coal combustion (Rosemont PRB) , heavy oil combustion, tire derived fuel combustion and petroleum coke combustion, which are the most important fuels for cement kilns. The results are shown in Table 3 and the detailed calculations from CUECost’s Constants_CC worksheet are shown in the appendices. As with the fuel available heat data, the data in this tab le should be regarded as representative, and there will be some variation even within fuel types

.
Table 3 . Approximate CO 2 

### and H 2 

### O quantity from combustion of fuels

Variable Name Flue Gas Tires Petroleum Coke Heavy Fuel Oil Rosemont PRB Logan, WV BIT Met hane
LBMCO2MMBTU lbmoles CO 2 /MMBtu 4.26 4.83 3.85 4.25 4.53 2.39 LBCO2MMBTU lb CO 2 /MMBtu 187.44 212.56 169.32 186.83 199.52 105.02 LBMH2OMMBTU lbmoles/MMBtu 2.76 2.76 2.23 3.23 4.14 2.77 LB H2O MMBTU lbs/MMBtu 49.71 49.73 40.26 58.21 74.64 49.92



### . CO 2 

### f rom Fuel Combustion

It is possible at this point to relate the CO 2 

### production from fuel combustion and gas flow to fuel heat input

. CO2FUEL (in Short ton s) = (LBCO2MMBTU/2000) * SFC * MCLINKER E.1
Where MCLINKER is the amount of clinker that is produced in short tons and LBCO2MMBTU is determined by the weighted average (weighted by heat input) of the L BCO2MMBTU for the fuels used, and CO2FUEL is the amount of CO 2 

### released by the fuel during combustion . To arrive at the amount of CO 2 

### from fuel combustion from a kiln for the year, substitute tons per year of clinker produced by the kiln (TPY) for MCLINKER.

3 US EPA’s Coa l Utility Environmental Cost model, available at: http://cfpub.epa.gov/si/si_public_record_Report.cfm?dirEntryID=63456

### Andover Technology Partners Page 4 CO 2 

### from Limestone Calcination and the effect of Substitute Materials
Limestone is the predominant so urce of calcium for the clinker . Assuming limesto ne as pure calcium carbonate (CaCO 3 

### ) , c hemistry dictates that it will produce 0.44 tons of CO 2 

### f

or every ton of pure calcium carbonate calcined to CaO

. Of cou rse, actual mined limestone is not pure CaCO 3 

### . If substitute materials that do not require calci nation , such as steelmaking slag or fly ash
, are used in lieu of limestone as a feed material , this will reduce the CO 2 

### from producing the clinker in proportion to the amount of substitute materials added. The approximate weight percent of CaO in clinker i s 65 %, 4 

### and 56% of CaCO 3 

### is CaO. Assuming that CaCO 3 

### is the primary source of calcium, which is usually the case, it therefore takes about 1. 16 ton s of CaCO 3 

### to provide the CaO for 1 ton of clinker

. O ther sources of calcium may offer some advantages. Ac cording to Reference 5 , 172 pounds of steelmaking slag provides about the same amount of calcium as 200 pounds or more of limestone, but without the release of roughly 88 pounds of CO 2 

### that is released upon calcination of the 200 pounds of limestone (44% o f CaCO 3 

### is released as CO 2 

### during calcination )

. Using this ratio, roug hly 1 ton of steelmaking slag will prov ide enough calcium for one ton of clinker and will replace the 1. 16 ton s of CaCO 3 

### that, when calcined, releases about 0.51 tons of CO 2 

### . From che mistry,
CO2CLINKER = 0.44 * MLIMESTONE * PURLIMESTONE E.2
Where MLIMESTONE and MCLINKER are in the same mass units and PURLIMESTONE is the fraction of limestone used in that kiln that is 

### CaCO 3 . 

### Now, when limestone is the only source of calcium and 1. 16 to n s of CaCO 3 

### provide the CaO for one to n of clinker
, from Equation E.2 it is apparent that

. CO2CLINKER (in Short ton s) = 0.5 1 * MCLINKER * PURLIMESTONE (in short tons) E. 3 And, this can be modified to address substitutes for limestone as follows:
CO2CLINKE R (in Short ton s)

= 0.51 * MCLINKER * PURLIMESTONE * (1

– CASUB) E. 4
Where
CASUB is the fraction of clinker calcium sourced from materials that do not need to be calcined , such as steelmaking slag or fly ash from power plants . So, if 80 % of the calcium i s sourced from limestone and the remainder of the calcium i s from a material that does not need to be calci ned, then CASUB is equal to 0.20

. Now, if the alternative source of calcium is steelmaking slag of similar composition as in Reference 5 (172 pounds of slag provides as much calcium as 200 pounds of limestone)
, then

4 “ Innovations in Portland Cement Manufacturing”, Portland Cement Association, 2004, p 260 , 5 J. Staudt, “ Steelmaking Slag as Recovered Mineral Components (RMC) in Portland Cement Production ”, prepared for the National Slag Association, December 12, 2007

### Andover Technology Partners Page 5 MCLINKER = MLIMESTONE * PURLIMESTONE /1. 16 + MSLAG E. 5
Where MSLAG , MLIMESTONE and MCLINKER are in the same units (ie, short tons)

. 

### Kilns may be limited by th e amount of feed materials that they can process , in other cases it may be by the gas volume or heat input

. It depends upon the particular kiln. In the case where material handling limits the kiln output, MLIMESTONE + MSLAG are effectively limited and de termine the capacity of the kiln . As a result, and because slag is more efficient than limestone at providing the calcium for clinker, the use of slag also increases the amount of clinker that can be produced from a kiln

. Assuming that the rated capacity of the kiln is based upon the use of limestone, then
CAPACITYHR *1.16 / PURLIMESTONE = MAX (MLIMESTONEHR) =MAX(MLIMESTONEHR +MSLAGHR) E. 6 is a limitation of the kiln, or in other words the total limestone and slag injection cannot exceed the clinker capa city of the kiln times 1. 16 Where CAPACITYHR is the rated capacity in clinker production per hour based on only limestone , MLIMESTONEHR is the limestone per hour and MSLAGHR is the slag per hour Equation E.5 can be represented on an hourly basis as:
MCLIN KER HR = MLIMESTONE HR * PURLIMESTONE /1. 16 + MSLAG HR E.7 Using equations E.6 and E.7, it can be shown that at full capacity : MCLINKERHR = (CAPACITYHR*1. 16 /PURLIMESTONE

– MSLAGHR)/1. 16 +MSLAGHR E.8 Or MCLINKERHR = CAPACITY HR /PURLIMESTONE + 0.13 8 * MSLAGHR E. 9 These will apply for any period of time so long that you are consistent with the time (such as capacity or clinker or slag mass per hour, per day, year, e tc.) and with units (ie., all in short tons ). So, in theory, if slag w ere used as the only source of calcium up to the limit of the kiln’s material handling capacity where
MSLAGHR=CAPACITYHR*1.16/PURLIMESTONE
, the kiln o utput could be increased by 16 %. But, material handling is usually not the limiting factor. O ther factors limit the use of slag, ofte n the composition of the slag relative to the desired mineral content of the clinker . Since it is necessary to have the correct mineral composition for the clinker, the slag composition relative to the desired clinker composition is often the limiting fact or . N ormally the slag addition rate can be roughly between 5% and 10% of the original clinker capacity, which typically increases kiln output roughly by the amount of slag added

. 6 

### So, the ability to increase kiln output while using slag will actually var y for each kiln based upon the particulars of its design

6 NOX Control Technologies for the Cement Industry, FINAL REPORT
, EPA Contract No. 68

- D98

- 026
, Work Assignm ent No. 2

- 28, EC/R Project No. ISD

- 228, September 19, 2000

### Andover Technology Partners Page 6 and the composition of the slag that is available

. But, it is fair to say that substitution of limestone with slag or another source of calcium that does not require calcining (such as power plant f ly ash if it is high in free lime ) wil l increase capa city of the kiln, and this is a major reason why kiln operator s frequently add slag or fly ash when these materials are available

. Other effects of substitute materials
S teelmaking slag is closer in chem ical composition to the clinker than limestone, which reduces the amount of thermal energy necessary to produce an equivalent amount of clinker. Therefore, this will reduce fuel consumption. This will be examined later when evaluating energy saving effec ts. Moreover, substitution of limestone with slag will reduce NOx emissions as well. Total CO 2 

### Total CO 2 

### emissions are the sum of the CO 2 

### generated from fuel combustion and the CO 2 

### generated from calcination, and is represented by:
CO2TOTAL = CO2FUEL + CO 2CLINKER E.1 0 From equa tions E.1 and E.4, equation E.10 can be shown to be: CO2TOTAL (in short tons) = MCLINKER*[(LBCO2MMBTU/2000)* SFC + 0.5 1 *PURLIMESTONE *(1

– CASUB)] E.11



### Where MCLINKER is in short tons

. To arrive at the total CO 2 

### per year, substitute the tons per year of clinker (TPY) for MCLINKER.

### Andover Technology Partners Page 7 Uncontrolled NOx Emissions from Cement Kilns
NOx emissions from cement kilns result from oxidation of fuel nitrogen (fuel NOx), oxidation of nitrogen in the combustion air (thermal NOx), and oxidation of nitrogen in the feed materials (feed NOx). Feed materials sometimes have significant levels of ammonia, which can also tend to reduce the NOx produced during combustion. Therefore, there is some variability in NOx emissions for kilns of similar type d epending upon a range of factors. However, as will be shown, some trends can be found.

The uncontrolled NOx emission s from cement kilns were shown in the 1994 ACT , AP

- 42 per Reference 7 and a 2000 EPA NOx Report as reported in Reference 8
, and these are shown in Table 4.

Table 4. NO x 

### Emissions (pounds per ton clinker [lb/t]) by Kiln Type

EPA 1994 ACT AP

- 42 2000 EPA NOx Report

Kiln Type Range Average/ Percent Higher than PH/PC Kiln percent Higher than PH/PC Kiln Average Range

Wet 3.6

– 19.5 9.7 /155 7.4 /76 6.2 1.9

- 13.4 Long Dry 6.1

– 10.5 8.6 /126 6.0 /43 4.5 2.5

- 7.1 Preheater 2.5

– 11.7 5.9 /55 4.8 /14 1.7 0.4

- 3.7 PH/PC 0.9

– 7.0 3.8 /

---- 4.2 /

---- 2.9 1.1

- 5.6 Alternative Control Techniques Document Update

- NOx Emissions from New Cement Kilns, EPA

- 453/R

- 07

- 006, November 2007 Portland Cement Association, “Summary of Control Techniques for Nitrogen Oxides”, PCA R&D SN3049, 2008 NOX Control Technologies for the Cement Industry, FINAL REPORT
, EPA Contract No. 68

- D98

- 026
, Work Assignmen t No. 2

- 28, EC/R Project No. ISD

- 228, September 19, 2000 

### It is possible to estimate the average NOx emission in lb/MMBtu of various kiln types using the data of Table 4 and Table 1 by divid ing the NOx generation per ton of cli nker by the heat input per to n of clinker for each kiln type . According to the average va lues from the 1994 ACT shown in Table 4 , the NOx emissions range from a low of 0.85 lb/MMBtu (for precalciner kilns) to a high of 1.38 lb/MMBtu for Long Wet and Long Dry kilns. Using the AP

- 42 e stimates, NOx emissions are over a narrower band around 1 lb/MMBtu

– ranging from a low of 0.95 lb/MMBtu for a precalciner to a high of 1.05 lb/MMBtu for a Wet process kiln , and the EPA 2000 numbers suggest lower values

. Table 5 shows the results of these calculations. An interesting result of these estimates is that

– except for the estimates made with the EPA 2000 data

- the emissions rates for cement kil ns appears to be roughly in the range of 1 lb/MMBtu to 1.5 lb/MMBtu for all kiln types, and that , f or uncontrolled kilns, the emissions rate in lb/ ton of clinker is

7 Alternat ive Control Techniques Document Update

- NOx Emissions from New Cement Kilns, EPA

453/R

- 07

- 006, November 2007 8 Portland Cement Association, “Summary of Control Techniques for Nitrogen Ox ides”, PCA R&D SN3049 , 2008

### Andover Technology Partners Page 8 primarily a function of the heat demand of the kiln per ton of clinker. These results are consistent with information from Hansen (e

- mail June 20, 2008) that states that uncontrolled NOx em issions (all process types, wet, long dry, preheater and precalciner with the exception of low NOx calciners or those equipped with staged combustion) are in the range of 1.0 to 1.3 lb/MMBtu . Therefore, this is a reasonable range to use for baseline, unco ntrolled NOx emissions from cement kiln s, with the lower part of the range perhaps being newer precalciner kilns and the higher end of the range long kilns. Since a precalciner kiln burns a significant part of the fuel in the calciner at a lower temperatu re where negligible thermal NOx is formed, it is reasonable that the NOx in lb/MMBtu might be somewhat less for a precalciner than for other kilns. Also, precalciner and perhaps preheater kilns, having a separate temperature zone for preheat with high int eraction between gas and solids, might benefit more from ammonia that sometimes is released from feed materials and can reduce NOx through selective non

- catalytic reduction (SNCR) reactions. Finally, wet kilns often burn a significant amount of waste fuel, which can impact NOx emissions

– sometimes positively and sometimes negatively.

Table 5. Estimated Uncontrolled NOx Emission s for Cement Kilns in lb/MMBtu Estimated from Average D ata in Tables 1 and 4.

1994 ACT AP

- 42 2000 EPA Wet 1.52 1.16 0.97 Long Dry 1.52 1.06 0.79 Preheater 1.35 1.10 0.39 PH/PC 0.94 1.04 0.72


### For cement kilns with additional controls, such as fuel staging, emission will be less. The cost and performance of these controls will be discussed later in this document. To deter mine the uncontrolled NOx level for a cement kiln, the following equation would be used.

MCLINKERHR * SFC * NOXMMBTU = LBNOXHR (lbs of NOx per hour)
, or TPY * SFC * NOXMMBTU = LBNOXYR (lbs of NOx per year) E.12

Where MCLINKERHR is equal to the ton s of clinker produced per hour and NOXMMBTU may be in the range of 1 to 1.3 lb/MMBtu, depending upon the kiln type and other characteristics

. TPY is equal to the tons of clinker per year. In the following section, the effects of kiln age and capacity will be examined.
Impact of Kiln Age and Capacity on NOx Emissions
The 2002 National Emissions Inventory (2002 NEI) reflects the estimates of emiss ions as submitted by states. Because it has kiln

- specific emissions data, it enables us to relate the emissions to the specific kilns, which enables us to examine factors that may impact emissions. 2002 NE I data provided i n the Cap+Trade worksheet was plotted by kiln type, by capacity and by year installed to determine the impact of these parameters on

### Andover Technology Partners Page 9 NOx emissions in lb/ton of clinker and lb/MMBtu of heat input

. The NEI data is provided by states as their estimates of emissions from sources. So, t here is some variability in the methods used to develop this data that makes it somewhat less reliable than, for instan ce, power plant continuous emission monitoring system (CEMS) data under the Title I V program. Nevertheless, this data is examined on the following pages since it is the best data currently available for all kilns

. An important aspect of this data is that it represents emissions from kilns with whatever controls that they have installed. So, newer kilns, which are more likely to have combustion controls, are more likely to have lower NOx emissions. Some older kilns have installed NOx controls due to loca l requirements. Some of these kilns have post combustion controls as well, which will affect the values shown. The information regarding the NOx control equipment is not available for each kiln. Therefore, it is not possibl e to discern the effect of NOx control equipment from this data. The averages and medians are shown in Table 6 by kiln type. These dif fer from the previous estimates. While the trends are generally consistent with what i s expected, the estimated value in lb/MMBtu for wet kilns is highe r than the other estimates . The average result showing a higher NOx in lb/ ton of clinker for wet versus dry kilns is unexpected. However, as will be shown, there is a lot of scatter in the data that can throw the averages off such that they are not repre sentative. Because there are no negative emission rates, the distribution of emissions values tends to behave more like a log

- normal distribution than a normal distribution, with high values being far higher than the mode (or most frequent level) than low values. As a result, the m edian values are less affected by these high outliers than mean values , and that is why median values are also shown. Median values are therefore probably more reliable than the averages in estimating the behavior of the popula tion as a whole.
Table 6. Averages /Medians of NOx emissions from NEI data in Cap+Trade workbook

PC PH D ry Wet NOx, lb/ton clinker (average) 3.69 7.06 8.86 8.40 NOx, lb/MMBtu (average) 1.08 1.78 1.85 2.07 NOx, lb/ton clinker (median) 3.37 4.68 7.19 7. 71 NOx, lb/MMBtu (median) 0.99 1.27 1.38 1.99


### In the following pages the NOx emissions reported in the NEI data will be presented for each kiln type as a function of kiln date of operation and kiln capacity.

### Andover Technology Partners Page 10 Wet Kilns As shown in Figures 4a and 4b a nd 4c
, there is no apparent correlation between NOx emissions from wet kilns and either kiln age or kiln capacity.

Fig ure 4a. NOx emissions (lb/ton clinker) versus year on line for wet kilns

Fig ure 4b. NOx emissions (lb/ton clinker) versus capacity for wet kilns

Figure 4b. NOx emissions (lb/MMBtu) versus capacity for wet kilns

### Andover Technology Partners Page 11 Long Dry Kilns In the case of long dry kilns, there is at best a very weak correlation between NOx emissions and year on line or capacity , as shown in Figures 5a, 5b and 5c . However, any trend appears too weak to be of great use in characterizing kiln NOx rate with any accuracy.

Figure 5a. NO x emissions (lb/ton clinker) versus year on line for long dry kilns

Fig ure 5b. NOx e missions (lb/ton clinker) versus capacity for long dry kilns

Figure 5c. NOx emissions (lb/MMBtu

clinker) versus capacity for long dry kilns

### Andover Technology Partners Page 12 Preheater Kilns In the case of preheater kilns, there appears to be a significant correlation bet ween NOx emissions and year on line or capacity , as shown in Figures 6a, 6b and 6c

. The correlation appears slightly stronger when using kiln capacity

. Kiln capacity and year on line are related since newer kilns tend to be larger. Larger or newer kilns tend to have lower emissions. This may be explained by better efficiency and more controls.

Figure 6 a. NOx emissions (lb/ton

clinker) versus year on line for preheater kilns

Figure 6 b. NO x emissions (lb/ton clinker) versus capacity for preheater kilns

Figure 6c. NOx emissions (lb/MMBtu) versus capacity for preheater kilns

### Andover Technology Partners Page 13 Precalciner Kilns As shown in Figure 7a, 7b and 7c, i n the case of precalciner kilns there appears to be a very slight correlation between NOx emissio ns and year on line or capacity, albeit much weaker than that for preheater kilns. The correlation appears slightly stronger when using kiln capacity. Kiln capacity and year on line are related since newer kilns are usually larger. Hence, newer and larg er kilns tend to have lower emissi ons; but the data does not support that in every case, as demonstrated by the scatter.

Figure 7 a. NOx emissions (lb/ton clinker)

versus year on line for precalciner kilns

Figure 7 b. NOx emissions (lb/ton clinker) versus capacity for precalciner kilns

Figure 7c. NOx emissions (lb/MMBtu) versus capacity for precalciner kilns

### Andover Technology Partners Page 14 Uncontrolled SO 2 

### Emissions From Cement Kilns

SO 2 

### emissions from cement kilns are the product of sulfur in the fuel as we ll as sulfur in the feed materials. Ideally, the SO 2 

### will be well captured to form gypsum by the free CaO that is released in the kiln

. In addition to reducing undesir able SO 2 

### emissions
, conversion to sulfates can be beneficial for the product. Gypsum i s used in finished cement, and gypsum produced on site may reduce the amount of gypsum that must be purchased. Synthetic gypsum from wet FGD systems may be used in place of natural
, purchased gypsum if of adequate quality. Therefore, SO 2 

### capture has both environmental as well as economic benefits for cement manufacturing.
However, the processes in a kiln that affect conversion of sulfur in the fuel and conversion of the sulfur in the feed materials to sulfates are many. Sulfur in the fuel will oxidize t o SO 2 

### during pyroprocessing and a significant amount is likely to be captured in the form of sulfates as the gas passes through the calcination zone. Preheater and Precalciner kilns tend to be very effective at capturing fuel

- generated SO 2 

### , while long dry and wet kilns are less effective.
Local oxygen concentrations in the kiln play a significant role. Kiln operators attempt to maintain an oxidizing environment throughout the kiln because this is beneficial to both calcination and clinker reactions. Red uced sulfur comp ounds, which can form in oxygen

depleted environments, are undesirable in the product while sulfates are desirable in the product

. However, kiln operators also minimize excess air to keep efficiency high and NOx low . As a result of the lo w excess air , lo cal reducing zones may result. Sulfates in processed materials may be reduced to SO 2 

### or to reduced sulfur compounds in reducing

zones

. Alternatively, other sulfur forms in the feed may be released and oxidize to form SO 2 

### . Changing the fo rm of sulfur in the feed material will therefore affect the SO 2 

### emissions. Because sulfur in the feed materials may be released prior to calcining reactions, for most kiln types the SO 2 

### released from feed materials is not as readily captured as SO 2 

### from fu el sulfur. For example, if the sulfur in the feed materials is of a form that readily releases SO 2 

### upon heating, much of the SO 2 

### from this source will be emitted unless there is an SO 2 

### control device to treat the exhaust gas. Table 7 shows emissions dat a from a 2001 Portland Cement Survey. The results show a great deal of variation. The consolidated results also don’t examine the impacts of kiln feed materials, just kiln type.

Table 7. 2001 Emissions Data from Portland Cement Association 2001 Survey

Kiln type Number of plants in database Number of tests in database SO 2 emission rates, Kilograms SO 2 per metric ton clinker (pounds SO 2 per ton clinker) Minimum Maximum Average Wet 11 20 <0.01 (<0.01) 16.32 (32.63) 2.90 (5.80) Long dry 9 27 0.01 (0.02) 9.09 (18.17) 1.43 (2.85) Preheater 11 30 <0.01 (<0.01) 3.27 (6.54) 0.70 (1.39) Calciner 7 24 <0.00 (<0.00) 4.42 (8.83) 0.96 (1.92) F. M. Miller, G. L. Young, and M. von Seebach , Formation and Techniques for C ontrol of Sulfur Dioxide and Other Sulfur Compounds in Portland Cement Kiln Systems, PCA R&D Serial No. 2460

### Andover Technology Partners Page 15 In order to examine the effects of kiln type, fuel and raw materials on SO 2 

### emissions, average SO 2 

### emissions in lb/ton clinker were estimated from 2002 National Emissions Inventory data in the Cap+Trade workbook for each market (except for Maine, which was separated from New York) by kiln type. Location has a major role in determining the fuel and limestone used. Limestone (or an alternate source o f calcium) is typically sourced from quarries that are close to the kiln since limestone is heavy and expensive to transport and the kiln uses a lot of it. Coal is also sourced from what is available in that market. Other feed materials may be from other locations and are less plant

- specific. As shown on Figure 8, preheater and precalciner kilns generally, but not always, have the lowest SO 2 

### emission rate. Wet and long dry kilns generally have the highest SO 2 

### emissions rates. However, even within kiln t ypes there is substantial variation in SO 2 

### emissions when comparing different locations. Locations are markets in the Cap+Trade workbook, except for Maine, which was separated because that kiln (which has since been converted to a precalciner kiln) was kn own to be scrubbed at the time . Atlanta, Birmingham, Detroit, Minneapolis, Kansas City, and New York have very high SO 2 

### emissions compared to other locations, such as Dallas, Denver, Florida, Los Angeles Maine, Phoenix, Pittsburgh, Salt Lake City, San Fra ncisco and Seattle. Table 8 shows the average emissions level for each kiln type for each market, and the color indicates whether or not the emissions rate is above or below the average. Since several locations show that their emissions are consistently ab ove or below the average for all or nearly all kiln types, location definitely has a significant role in SO 2 

### emissions from cement kilns.
Figure 8. Average SO 2 

### emissions (in lbs/ton clinker) by kiln type and location

### Andover Technology Partners Page 16 Kiln age and capacity were also examined in order to determine if capacity or age has a significant impact on SO 2 

### emissions within kiln types. The results of this analysis are shown on the following pages

. Table 8. Average SO 2 

### Emission fo r each kiln type in each market (lbs/ton clinker) (red is above the average and green is below the average for that kiln type)
PC PH Dry Wet Atlanta 1.76 2.73 11.42 11.92 Baltimore/Philadelphia 3.14 4.79 7.53 6.31 Birmingham 0.33 0.61 0.00 13.99 Chicago 5.58 4.47 5.88 9.50 Cincinnati 0.19 4.93 12.53 0.00 Dallas 2.12 0.00 3.45 7.26 Denver 0.32 0.27 1.07 4.24 Detroit 5.23 0.00 18.10 17.69 Florida 0.45 0.02 0.00 0.00 Kansas City 3.81 5.88 14.88 8.61 Los Angeles 0.43 2.18 0.27 0.00 Minneapolis 13.37 0.00 8.15 0.00 Maine 0.00 0.00 0.00 1.67 New York/Boston 0.00 0.30 0.00 20.06 Phoenix 0.87 0.07 5.69 0.00 Pittsburgh 0.00 0.00 5.17 3.29 Salt Lake City 0.13 0.00 0.00 0.77 San Antonio 0.84 0.58 0.51 8.98 San Francisco 0.78 0.05 1 .51 0.00 Seattle 0.53 0.00 0.00 3.80 St. Louis 2.18 0.00 1.42 7.02 Average of above 2.34 2.07 6.51 8.34 Average for all in kiln type 1.75 2.03 7.14 8.27



### Figure 9 and Table 9 show the median SO 2 

### emissions (in lb/ton clinker). There is a slight difference from what is shown in Figure 8 and Table 8. But, the trends overall are similar. Median values tend to be less impacted by outliers than averages

. So, in most (but not all) cases the median values are lower because they are less impacted by v ery high values . So, median is more represent ative than the average for the majority of kilns, but will not be representative for kilns with unusually high values.

### Andover Technology Partners Page 17 Figure 9

. Median SO 2 

### emissions (in lbs/ton clinker) by kiln type and location

### Andover Technology Partners Page 18 Table 9. Median SO 2 

### Emission for each kiln type in each market (lbs/ton clinker)

. (red is above the average and green is below the average for that kiln type PC PH Dry Wet Atlanta 0.95 2.73 11.42 12.25
Baltimore/Philadelphia 3.14 3.95 7.31 7.49 Birmingham 0.09 0.61 0.00 13.99 Chicago 5.58 5.77 5.88 9.50 Cincinnati 0.19 5.04 12.53 0.00 Dallas 2.94 0.00 3.45 7.59 Denver 0.32 0.10 1.07 4.24 Detroit 5.23 0.00 5.31 18.00 Florida 0.45 0.02 0.00 0.00 Kansas City 1. 25 5.88 24.85 8.61 Los Angeles 0.17 2.18 0.11 0.00 Minneapolis 13.37 0.00 8.15 0.00 Maine 0.00 0.00 0.00 1.67 New York/Boston 0.00 0.30 0.00 11.98 Phoenix 1.30 0.07 8.51 0.00 Pittsburgh 0.00 0.00 5.41 3.95 Salt Lake City 0.13 0.00 0.00 0.70 San Antonio 0.75 0.61 0.51 8.98 San Francisco 0.49 0.05 1.51 0.00 Seattle 0.53 0.00 0.00 3.80 St. Louis 2.18 0.00 1.51 7.02 Median of above 0.85 0.61 5.41 7.59 Median of all in kiln type 0.88 0.63 2.13 7.43

### Andover Technology Partners Page 19 Effects of year on line and capacity were also examined in the same way as for NOx emissions. Figures 10a and 10 b show that there are no trends between SO 2 

### emissions and year on line or capacity for wet kilns. This is consistent with the previous result that suggests that other conditions, such as fuel and feed materials, have a larger impact.
Figure 10 a. SO 2 

### emissions (lb/ton clinker) versus year on line for wet kilns

Figure 10b

. SO 2 

### emissions (lb/ton clinker) versus capacity for wet kilns

### Andover Technology Partners Page 20 Figures 11a and 11 b show that there are no trends between SO 2 

### emissions and year on line or capacity for dry kilns either. This is consistent with the previous result that suggests that other conditions, such as fuel and feed m aterials, have a larger impact.
Figure 11 a. SO 2 

### emissions (lb/ton clinker) versus year on line for dry kilns

Figure 1b

. SO 2 

### emissions (lb/ton clinker) versus capacity for dry kilns

### Andover Technology Partners Page 21 Figures 12 a and 12 b show that there are no strong trends between SO 2 

### emissions and year on line or capacity for preheater kilns

– at least for lower capacities. This is consistent with the previous result s that suggest that other conditions, such as fuel and feed

m aterials, can have a large impact

. However, at larger capacities and for newer units, the SO 2 

### emissions tend to be consistently low , as demonstrated by the red line . So, it appears that the larger or newer units may have better inherent SO 2 

### capture than the smaller and older ones.

Figure 12 a. SO 2 

### emissions (lb/ton clinker) versus year on line for preheater kilns

Figure 12b

. SO 2 

### emissions (lb/ton clinker) versus capacity for preheater kilns

### Andover Technology Partners Page 22 F igures 13a and 13 b show that there are no strong trends between SO 2 

### emissions and year on line or capacity for precalciner kilns at lower capacities. This is consistent with the previous results that suggest that other conditions, such as fuel and feed ma terials, can have a large impact. However, at larger capacities and for newer units, the SO 2 

### emissions are consistently low , as shown by the red line . So, it the larger or newer units appear to have better inherent SO 2 

### capture than the smaller and older ones.

Figure 13 a. SO 2 

### emissions (lb/ton clinker) versus year on line for precalciner kilns

Figure 13b

. SO 2 

### emissions (lb/ton clinker) versus capacity for precalciner kilns

### Andover Technology Partners Page 23 Summary of Emissions
It is acknowledged that the data available for estimating emissions rates, particularly for NOx and SO 2 

### , has some uncertainties. However, reasonable estimating methods, as described in this memo, are possible at this time. And, as more information beco mes available, the estimating methods described in this memo will be refined and improved upon. The following conclusions have been reached regarding CO 2 

### , NOx and SO 2 

### emissions from kilns.

**•** CO 2 

### emissions from a kiln can be estimated from heat input and fu el characteristics and from clinker production and the amount of clinker calcium sourced from limestone versus other sources that do not require calcining. Algorithms are provided in this memo to permit these calculations.

**•** Average uncontrolled NOx emissio ns may be in the range of abo ut 1

- 2 lb/MMBtu for all kiln types
, and a narrower range for most dry process kilns (1

- 1.3 lb/MMBtu)
, and kilns with controls will likely have lower NOx than in this range

.
**•** For long kilns (wet and dry) there is no observed impa ct from kiln age or kiln size on NOx emissions (lb/ton clinker basis and lb/MMBtu basis ).

**•** For preheater and precalciner kilns, trends were observed that show ed lower NOx emissions (lb/ton clinker basis and lb/MMBtu basis ) for larger and newer kilns

**•** SO 2 

### emi ssions are impacted by location and by kiln type , with wet kilns generally having the highest emissions and preheater kilns the lowest

.
**•** SO 2 

### emissions from long kilns (wet or dry) are not impacted by kiln size or age

. **•** SO 2 

### emissions from preheater and precal ciner kilns do not appear to be impacted by size or age for smaller or older kilns. However newer and larger kilns appear to have consistently low SO 2 

### emissions.

For estimating NOx emissions, the median NOx levels in lb/MMBtu in Table 10 are recommended for the model

. Earlier discussion cited the variability within kiln types that is not captured in Table 10. Of course, as better data is available in the future, the emissions assumptions for the model will be improved.

Table 10 . Median NOx emission ( lb/MMBtu) PC PH D ry Wet NOx, lb/MMBtu (median) 0.99 1.27 1.38 1.99



### For SO 2 

### emissions, I recommend using the median SO 2 

### emissions by kiln type and region shown in Table 9. However, for each data point in Table 9 that represents median emissions within a market and kiln type, there may be very few numbers behind it . So, there may be a question of statistical relevance . However, since the values in Table 9 are being used only to characterize the specific kilns of that type within those markets rather th an used to represent a broader population of kilns, this approach should provide reasonable results. Of course, as better data is available in the future, the emissions assumptions for the model will be improved.

### Andover Technology Partners Page 24 

## Appendices

1 Typical properties of delaye d petroleum coke 2. Ultimate Analysis values for Heavy No. 6 Fuel Oil‚ lb/lb fuel 3. Tire Derived Fuel Analysis 4. Combustion Calculations from CUECost
5. List of Terms

### Andover Technology Partners Page 25 Appendix 1. Typical properties of delayed petroleum coke (Ultimate Analysi s as Received, Weight %) World Energy Council Website http://217.206.197.194:8190/wec

geis/publications/default/tech_papers/17th_congress/1_2_26. asp Constituent Average Range Carbon 79.74 75.0

- 86.0 Hydrogen 3.31 3.0

- 3.6 Nitrogen 1.61 1.3

- 1.9 Sulfur 4.47 3.4

- 5.3 Ash 0.27 0.0

- 0.6 Oxygen 0.00 0.0

- 0.1
Moisture 10.60 5.5

- 15.0 HHV, MJ/kg 31.3 29.3

- 33.7

Ash Properties, ppm Average Range

Vanadium <2,000 500

- 2,000 Nickel 336 250

- 450
Iron 84 50

- 250

Volatile Matter, % 10 8

- 16

Appendix 2. Ultimate Analysis values for Heavy No. 6 Fuel Oil‚ lb/lb fuel

Natural R esources Canada website: http://www.oee.nrcan.gc.ca/industrial/technical

- info/tools/boilers/heavy

- fuel.cfm?attr=24
Carbon (C) 0.874 Hydrogen (H 2 ) 0.101 Nitrogen (N 2 ) 0.003 Oxygen (O 2 ) neg ligible Sulphur (S) 0.020 Ash 0.001

Higher heating value (HHV) 18‚250 Btu/lb

### Andover Technology Partners Page 26 Appendix 3. Tire Derived Fuel Analysis

Representative Analysis of TDF Produced By WRI (Source: TDF Produced From Scrap Tires with 96+% Wire Removed) Description %By Wt (As Received) %By Wt (Dry Basis)

Proximate Analysis Moisture 0.62

---- Ash 4.78 4.81
Volatile Matter 66.64 67.06
Fixed Carbon 27.96 28.13
Total 100.00 100.00
Ultimate Analysis
Moisture 0.62

---- Ash 4.78 4.81
Carbon 83.87 84.39 Hydro gen 7.09 7.13 Nitrogen 0.24 0.24 Sulfur 1.23 1.24 Oxygen (by difference) 2.17 2.19
Total 100.00 100.00

Heat Value BTU/lb kJ/kg
HHV 16,250 37,798
HV Ave 15,500 36,053

TDF Combustion
Characteristics **°** F **°** C Tires ignite (flash point) 550

- 650 288

- 343 Carbon begins to burn 842 450 Carbon completely burnt 1202 650

© 1986 Waste Recovery, Inc. 84% OF A TIRE,S WEIGHT IS FROM RUBBER COMPOUNDS. REMAINDER IS BEAD AND BELT WIRE PLUS CARCASS AND CHAFE R FABRIC 

### From North Carolina Department of Environment and Natural Resources, Division of Pollution Prevention and Environmental Assistance. http://www.p2pays.org/ref/11/10504/html/usa /tdfdata.htm

### Andover Technology Partners Page 27 Appendix 4. Combustion Calculations from CUECost

### Andover Technology Partners Page 28 Appendix 5. List of Terms Term Definition CAPACITYHR CASUB

CC CO2FUEL CO2CLINKER COSTKWH COSTNH3LB COSTNH3YR DLI DSCFM EGFW

FC FF i H LBCO2MMBTU LBMCO2MMBTU LBH20MMBTU LBMH20MMBTU LBNOXHR LBSO2CLINKER LNB LWS MAT MCLINKER MCLINKERHR MKF MLIMESTONE MLIMESTONEHR MSLAG MSLAGHR NOXMMBTU PEC PURLIMESTONE Q SCC SCR SFC SCFH SNCR TDFPC TPY VC Clinker capacity of the kiln in tons per hour Calcium Substitution Fraction

– fraction of total c alcium from material that does not need to be calcined Capital Cost Fuel CO 2 in pounds that is released from fuel combustion CO 2 produced by calcination during clinker production Cost of Power in $/KWhr Cost of ammonia in $ per pound Cost of ammonia in $ p er year Dry Lime Injection Dry standard cubic feet per minute Exhaust Gas Flowrate (wet) in standard cubic feet per short ton of clinker

Fixed Cost Fuel Fraction of i th component of fuel on a Btu basis Burner heat duty in MM Btu/hr Pounds (mass) of CO2 pe r MMBtu of fuel input Pound moles of CO2 per MMBtu of fuel input Pounds (mass) of H2O per MMBtu of fuel Pound moles of H2O per MMBtu of fuel Pounds (mass) of NOx per hour Lbs of SO 2 per ton of clinker Low NOx Burner Limestone Wet Scrubber Mixing Air Techno logy Mass of clinker in tons Mass rate of clinker in tons per hour Mid Kiln Firing Mass of limestone, tons Mass rate of limestone, tons/hr Mass of slag, tons Mass rate of slag, tons/hr NOx lb/MMBtu for the kiln Purchased Equipment Cost Purity of the limest one at CaCO 3 Flow in actual cubic meters per hour Staged Combustion Calciner Selective Catalytic Reduction Specific Fuel Consumption in MMBtu per ton of clinker Standard Cubic Feet per Hour of gas Selective Non

- Catalytic Reduction Tire Derived Fuel Precalc iner Tons per Year of clinker Variable CostRTI International is a trade name of Research Triangle Institute



### TO: Elineth Torres, U.S. EPA

FROM: Brooks Depro

DATE: March 31, 2010

SUBJECT: ISIS Cement Production Costs

This memorandum documents the data and methods used to develop unit costs ($/short ton) for raw materials, repair and maintenance, electricity use, and labor. This documentation accompanies the XL spreadsheet entitled “ISIS_cement_production_costs.xlsx.”

Raw Materials In Table 1, we report the quantities of raw material inputs, cement production, and the raw material input ratio for the U.S. cement industry. In 2005, approximately 1.67 metric tons of raw materials were required to make a short ton of clinker. State-level material prices (approximated by USGS data for crushed stone) range between $4 and $13 per metric ton (Table 2). To calculate raw material costs, we multiplied state-level average prices by the material input ratio (1.67). Table 1. Raw Material Input Ratios for the U.S. Cement Industry: 2005 Variable Description Short Tons (10 3 ) Raw material input a 160,937 Clinker production b 96,348 Material Input Ratio 1.67

a U.S. Department of the Interior, U.S. Geological Survey. 2006a. 2005 Minerals Yearbook, Cement . Table 6. Washington, DC: U.S. Department of the Interior.
b U.S. Department of the Interior, U.S. Geological Survey. 2006a. 2005 Minerals Yearbook, Cement . Table 3. Washington, DC: U.S. Department of the Interior.

### Elineth Torres

March 19, 2010 Page 2

Table 2. Raw Material Prices by State: 2005

State Price of Raw Materials ($/short ton) a AL $5.96 AK $5.99 AZ $5.22 AR $5.71 CA $7.59 CO $6.21 CT $8.34 DE $6.25 FL $7.87 GA $6.92 HI $12.10 ID $4.87 IL $6.50 IN $4.90 IA $6.60 KS $6.53 KY $6.57 LA $7.42 ME $6.21 MD $7.51 MA $8.34 MI $3.53 MN $7.53 MS $10.80 MO $6.69 MT $4.32 NE $6.44 NV $6.50 NH $7.28 NJ $6.39 NM $6.05 NY $7.66 NC $7.79 ND $4.04 OH $5.28 OK $5.14 OR $5.45 PA $6.05 RI $7.02 SC $6.90 SD $4.17 TN $6.85 TX $5.58 UT $5.06 VT $6.12 VA $8.19 (continued)

### Elineth Torres

March 19, 2010 Page 3

Table 2. Raw Material Costs by Market and State: 2005 (continued)

State Price of Raw Materials ($/short ton) WA $6.28 WV $6.22 WI $5.29 WY $5.15 Source: U.S. Department of the Interior, U.S. Geological Survey. 2006a. 2005 Minerals Yearbook, Crushed Stone Table 4. Washington, DC: U.S. Department of the Interior.

### Elineth Torres

March 19, 2010 Page 4

Repair and Maintenance
Rock Products (1994) magazine reports the 1993 values of annual repair and maintenance costs by kiln capacity (Table 3). Since more recent repair and maintenance costs are not available, we adjusted these costs to 2005 dollars using the Chemical Engineering Plant Cost Index (Chemical Engineering, 1999 and Lowzoski, 2010). Table 3. Annual Repair and Maintenance Costs by Kiln Capacity: 2005
Annual Kiln Clinker Capacity (short tons) 1993 ($/short ton) 2005 ($/short ton) a <500,000 $9.56 $12.46 500,000 to 750,000 $7.53 $9.81 >750,000 $5.31 $6.92 Sources: Rock Products. 1994. “Cement Plant Operating Cost Study.” Overland Park, KS: Intertec Publishing. September, p. 19. Chemical Engineering. 1999. Economic Indicators. Chemical Engineering,January, 154. Lowzoski, Dorothy. 2010. Economic Indicators. Chemical Engineering, January, 63.

### Elineth Torres

March 19, 2010 Page 5

Electricity To reflect the differences in electricity consumption process type and kiln size, we collected energy consumption (kWh) and clinker production data (Table 4). To calculate electricity costs, we multiplied state electricity prices (Table 5) by the electricity input ratio (last column of Table 4) Table 4. Electricity Consumption of U.S. Cement Producers by Process Type: 2005

Process Type Clinker

Production (Short tons) Electricity

Consumption (1,000 kWh) Electricity

Input Ratio (kWh per short ton) a
Wet Process
≤500,000 ton capacity 3,558,496 515,451 145
>500,000-ton capacity 8,627,124 1,144,757 133 Dry Process
≤500,000-ton capacity 1,723,766 276,358 160
>500,000-ton capacity 75,561,840 10,501,877 139

Precalciner 48,827,792 6,725,423 138

Preheater 17,704,683 2,499,535 141 Source: Portland Cement Association. December 2005. U.S. and Canadian Labor-Energy Input Survey 2005

. Skokie, IL: PCA’s Economic Research Department.

### Elineth Torres

March 19, 2010 Page 6

Table 5. Electricity Price by Market and State: 2005

State Cents per kWh AL 4.52 AK 9.29 AZ 5.85 AR 4.74 CA 9.55 CO 5.74 CT 9.40 DE 6.21 FL 6.46 GA 5.28 HI 15.79 ID 3.91 IL 4.61 IN 4.42 IA 4.56 KS 4.85 KY 3.60 LA 6.71 ME 7.28 MD 7.01 MA 9.22 MI 5.32 MN 5.02 MS 5.37 MO 4.54 MT 4.83 NE 4.43 NV 7.71 NH 11.48 NJ 9.76 NM 5.61 NY 8.23 NC 5.04 ND 4.32 OH 5.10 OK 5.11 OR 4.83 PA 6.29 RI 10.01 SC 4.55 SD 4.95 TN 4.73 TX 7.14 UT 4.24 (continued)

### Elineth Torres

March 19, 2010 Page 7

Table 5. Electricity Price by Market and State: 2005 (continued)

State Cents per kWh VT 7.77 VA 4.46 WA 4.27 WV 3.85 WI 5.39 WY 3.99 Source: U.S. Energy Information Administration. 2006. Electric Power Annual 2005 . Figure 7-7. Washington, DC: U.S. Energy Information Administration.

### Elineth Torres

March 19, 2010 Page 8

Labor To calculate labor costs, we grouped labor into two categories:

 Direct or “variable” labor costs ($/short of clinker production): Labor costs that vary with clinker production levels.

 Other or “fixed” labor costs ($/short ton of clinker capacity): Labor costs that do not vary with clinker production levels but can be avoided by closing a cement plant.

Direct Labor 

### To reflect the differences in labor use, we collected direct labor use and clinker production data (Table 6). To calculate electricity costs, we multiplied state average hourly manufacturing wage
rates 1 

### (Table 7) by the direct input ratio (last column of Table 6). To better account for additional labor costs, we approximated these costs by adding PCA estimates of plant payroll taxes ($0.90 per short ton) and fringe ($1.50 per short ton) to the direct labor calculations.
Table 6. Direct Labor Use: 2005

Process Type Clinker

Production (Short tons) Direct Labor

(hours) Direct Labor

Input Ratio (hours per short ton)
Wet Process
≤500,000 ton capacity 3,558,496 1,453,200 0.41
>500,000-ton capacity 8,627,124 2,516,988 0.29 Dry Process
≤500,000-ton capacity 1,723,766 780,390 0.45
>500,000-ton capacity 75,561,840 18,403,466 0.24

Precalciner 48,827,792 11,115,457 0.23

Preheater 17,704,683 5,149,221 0.29 Source: Portland Cement Association. December 2005. U.S. and Canadian Labor-Energy Input Survey 2005

. Skokie, IL: PCA’s Economic Research Department.

1 BLS only has a complete state-level series for manufacturing. We compared BLS 2005 national earnings data for the manufacturing ($16.56 per hour) with the cement and concrete products industry ($16.68 per hour) and found they were comparable (BLS, 2010b). To account for the small differences, we adjusted the manufacturing data by +0.7 percent (column 3, Table 5).

### Elineth Torres

March 19, 2010 Page 9

Table 5. Average Hourly Earnings by Market and State: 2005

State Manufacturing

Average Hourly Earnings ($/hour) Estimated Cement Industry Average Hourly Earnings ($/hour)

AL $14.93 $15.04 AK $14.22 $14.32 AZ $14.55 $14.66 AR $13.71 $13.81 CA $15.70 $15.81 CO $15.91 $16.03 CT $18.96 $19.10 DE $17.74 $17.87 FL $13.89 $13.99 GA $14.56 $14.67 HI $14.34 $14.44 ID $14.96 $15.07 IL $15.84 $15.95 IN $18.14 $18.27 IA $16.25 $16.37 KS $17.14 $17.26 KY $16.65 $16.77 LA $17.30 $17.43 ME $17.28 $17.41 MD $16.98 $17.10 MA $17.66 $17.79 MI $21.50 $21.66 MN $16.63 $16.75 MS $13.53 $13.63 MO $17.42 $17.55 MT $15.62 $15.73 NE $15.44 $15.55 NV $14.98 $15.09 NH $15.87 $15.99 NJ $16.33 $16.45 NM $13.66 $13.76 NY $17.77 $17.90 NC $14.38 $14.48 ND $15.29 $15.40 OH $19.07 $19.21 OK $14.56 $14.67 OR $15.49 $15.60 PA $15.26 $15.37 RI $13.12 $13.22 (continued)

### Elineth Torres

March 19, 2010 Page 10

Table 5. Average Hourly Earnings by Market and State: 2005 (continued)

State Manufacturing

Average Hourly Earnings ($/hour) Estimated Cement Industry Average Hourly Earnings ($/hour) SC $15.23 $15.34 SD $13.47 $13.57 TN $14.02 $14.12 TX $14.03 $14.13 UT $14.73 $14.84 VT $15.06 $15.17 VA $16.40 $16.52 WA $18.83 $18.97 WV $17.14 $17.26 WI $16.29 $16.41 WY $17.08 $17.20 Source: U.S. Department of Labor, Bureau of Labor Statistics. 2010a. “Employment, Hours, and Earnings from the Current Employment Statistics survey (State)” Washington, DC: U.S. Department of Labor. Accessed February 11, 2010.

Other Labor 

### To reflect other labor operating costs, we also added PCA estimates of salaried employee costs ($2.80 per short ton of clinker capacity), and other payroll expenses (SG&A) ($3.20 per short ton of clinker capacity).

### Elineth Torres

March 19, 2010 Page 11



### REFERENCES Chemical Engineering. 1999. Economic Indicators. Chemical Engineering, January, 154.
Lowzoski, Dorothy. 2010. Economic Indicators. Chemical Engineering, January, 63.
Portland Cement Association (PCA). December 2005. U.S. and Canadian Labor-Energy Input Survey 2005 . Skokie, IL: Portland Cement Association Economic Research Department.

Rock Products . 1994. “Cement Plant Operating Cost Study.” Overland Park, KS: Intertec Publishing. September, p. 19. U.S. Department of the Interior, U.S. Geological Survey. 2006a. 2005 Minerals Yearbook, Cement . Tables 3, 4, and 6. Washington, DC: U.S. Department of the Interior. U.S. Department of the Interior, U.S. Geological Survey. 2006b. 2005 Minerals Yearbook, Crushed Stone . Table 4. Washington, DC: U.S. Department of the Interior. U.S. Department of Labor, Bureau of Labor Statistics. 2010a. Employment, Hours, and Earnings from the Current Employment Statistics survey (State). Washington, DC: U.S. Department of Labor. Accessed February 11, 2010. U.S. Department of Labor, Bureau of Labor Statistics. 2010b. “Employment, Hours, and Earnings from the Current Employment Statistics survey (National).” Washington, DC: U.S. Department of Labor. Accessed February 11, 2010. U.S. Energy Information Administration. 2006. Electric Power Annual 2005 . Figure 7-7. Washington, DC: U.S. Energy Information Administration.

### TO: Keit h Barnett, U.S. EPA

CC: Michael Laney, RTI International

Ra vi Srivastava , U.S. EPA Elineth Torres, U.S. EPA S am udra Vijay, U.S. EPA Tom Walton, U.S. EPA

FROM: Brooks Depro, RTI International

Alex Rogozhin, RTI International Dallas Wood , RTI I nt ernational

DATE: August 31 , 2007

SUBJECT: Draft: Do cumentation for Portl and Cement Kiln Cost Funct io ns (2005)

This memorandum documents how RTI International updated Portl and cement average variable cost (AVC) funct io ns. The update process currently e xcludes estimates of f ixed operating and maintenance (O&M) costs that may be paid by kilns to cover any costs th at are not a funct io n of overall cement production

. These data ( expr essed in terms of dollars per ton of annual capacit y ) are currently not avai lable.

The fo llo wing el ements are included in the analysis: th e peer

- reviewed kiln

- level average cost funct io n met hod used in the Cement Kiln Dust Rulemaking RIA ( U. S . Environmental Protection Agency [ EPA ] , 1998 ), all the data RTI used in th e analysis
, and new kiln

- level AVC est imates.



### BACKGROUND
Previous econo mic impact analyses (EPA, 1998) used a kiln

- level AVC funct io n developed in a microeconomic study of kiln use and reti rement (Das, 1992) . Das describes five varia ble inputs in cement production : raw material s, repai r and maintenance , labor, electricit y, and fuel . R aw materi als serve as the kiln feed
, repai r and m aintenance are required for periodic upkeep of th e kiln , l abor i s use d in the quarry and for packing
, el ectri ci ty is consumed ma i nly by th e auxiliary equi pment , and fu el i s largely consumed by the kilns.

The AVC fu nct io n (expressed in dollars per met ric ton of cem ent) can be written as

AVC = AVMI *P m 

### + AVRI * P r 

### + AVLI * w + AVFI *P f 

### f + AVEI * P e, 

### where AV RI, AVLI, AVFI, AVEI, and AVMI are the average vari able input s of mat eri als, repai r and maintenance
, la bor, fuel, and electri ci ty , and P m , 

### P r 

### , w, P f 

### , and P e 

### are the pri ces of each variable input.

### K ei

th Barnett August 31, 2007 Page 2

For the emissio ns trading model, RTI collected data fro m t h e Portland Cement Associat io n (PCA, 2005 ) and government statist ical publicat io ns and updated selected cost fu nction param eters . These updates are presented and discussed in t his memorandum

.


### COST FUNCTION UPDATE S FOR 2005

Raw Materials
In Table 1, we report the quant it ies of raw material inputs, cement production, and the raw materi al input ratio for the U .S. cem ent industry

. In 2005, approximately 1.67 metric tons of raw materi als were required to make a metric ton of cement

. Table 1 . Ra w Material Input Ratios for the U .S. Cement Industry : 2005

M etric Tons (10 3 ) Raw material input a 159,700 Cement p roduction b 9 5,488 Ratio (AVMI) 1.67

a U.S. Department of the Interior, U.S. Geological Survey. 2006a

. 2005 Minerals Yearbook, Cement

. Tab le 6

. Washingto

n , DC : U.S. Department of the Interior.
b U.S. Department of the Interior
, U.S. Geological Survey. 2006 a

. 2005 Minerals Yearbook, Cement . Table 3

. Washingto

n , DC : U.S. Department of the Interior.



### State r aw material prices for crushed stone range betw een $4 and $13 per metric ton (Table 2)

. To calculate raw material costs, we mult ip lied state raw material prices by the raw material input rati o (1.6 7). Repair and Maintenance
Rock Products (1994) magazine reports the 1993 values of annual repair and maintenance costs by kiln capacit y ( Table 3). Since more recent repair and maintenance costs are not available, we adj usted th ese costs to 2005 dollars using the gross domest ic product (GDP) deflator.

Labor
The Portl and Cement Associat io n reports la bor productivit y measures in terms of metric tons of

cem ent per emp lo yee hour. We used these data to calculate the average variable l abor inputs (AVLI): a measure of emplo yee hours needed per ton of cement. AVLI estimates are computed by t aking the inverse of each labor productivit y measure. Table 4 shows la bor productivit y continues to vary by process t ype and kiln size. Productivit y i s higher for dry process kilns

com pared wi th wet kilns; it is also higher for large

- capacit y k ilns.

### K ei

th Barnett August 31, 2007 Page 3

Table 2. Raw Material Costs by Market and State : 2005

State(s) Price of Raw Materials ($/m etric ton) a Cost of Raw Materials ($/m etric ton of cement) AL $6.57 $10.99 AK $6.60 $11.04 AZ $5.75 $9.62 AR $6.29 $10.52 CA $8.37 $14.00 CO $6.85 $11.46 CT $9.19 $15.37 DE $6.89 $11.52 FL $8.67 $14.50 GA $7.63 $12.76 HI $13.34 $22.31 ID $5.37 $8.98 IL $7.16 $11.97 IN $5.40 $9.03 IA $7.27 $12.16 KS $7. 20 $12.04 KY $7.24 $12.11 LA $8.18 $13.68 ME $6.85 $11.46 MD $8.28 $13.85 MA $9.19 $15.37 MI $3.89 $6.51 MN $8.30 $13.88 MS $11.90 $19.90 MO $7.37 $12.33 MT $4.76 $7.96 NE $7.10 $11.87 NV $7.17 $11.99 NH $8.02 $13.41 NJ $7.04 $11.77 NM $6.67 $11.16 NY $8.44 $14.12 NC $8.59 $14.37 ND $4.45 $7.44 OH $5.82 $9.73 OK $5.67 $9.48 OR $6.01 $10.05 PA $6.67 $11.16 RI $7.74 $12.94 SC $7.61 $12.73 SD $4.60 $7.69 TN $7.55 $12.63 TX $6.15 $10.29 UT $5.58 $9.33 VT $6.75 $11.29 VA $9.03 $15.1 0 WA $6.92 $11.57 (continued)

### K ei

th Barnett August 31, 2007 Page 4

Table 2. Raw Material Costs by Market and State : 2005 (continued)

State(s) Price of Raw Materials ($/m etric ton) a Cost of Raw Materials ($/m etric ton of cement) WV $6.86 $11.47 WI $5.83 $9.75 WY $5.68 $9.50

a U.S. Department of the Interior, U.S. Geological Survey. 2006a. 2005 Minerals Yearbook, C rushed Stone . Table 4

. Washingto

n , DC : U.S. Department of the Interior. 

### Table 3. Annual Repair and Maintenance Costs by Kiln Cap acity : 2005 Kiln Capacity (short tons) 1993 ($/metric ton) 2005 ($/metric ton) a <500, 000 tons $10.54 $15.46 500,000 to 750,000 tons $8.30 $12.17 >750,000 tons $5.85 $8.59

a Adjusted by chained (real) GDP obtained from the U.S. Department of Commerce, Bu reau of Economic Analysis. 2007

. Current

- Dollar and “ Real ” Gross Domestic Product

. Available at http://www.bea.gov/national/xls/gdplev.xls

. 

### Table 4. Labor Productivity Measures for the U.S. Cement Industry b y Proce ss Type and Kiln Size : 2005

Process Type Metric Ton s p er Employee Hour a, b AVLI (employee h ours p er metric t on ) a
Wet Process 2.16 0.4630

• 500,000 -t on capacity 1.87 0.5348

> 500,000 -t on capacity 2.31 0.4329 Dry Process 3.14 0.3185

• 500,000 -t on capacit y 1.93 0.5181

> 500,000 -t on capacity 3.19 0.3135 Precalciner 3.36 0.2976 Preheater 3.2 0.3125 All Plants 2.96 0.3378

a Following the Portland Cement Association (PCA, 2005 ), th e metric tons used to measure labor efficiency are an equiv alent to

n measure , composed of 85 % clinker production and 15 % finished cement production.
b Portland Cement Association. December 2005

. U.S. and Canadian Labor

- Energy Input Survey 2005 . Skokie, IL : PCA ’ s Economic Research Department

.

### K ei

th Barnett August 31, 2007 Page 5

State average hourly e arnings for the durable goods industry are presented in Table 5. To cal culate labor costs, we mult iplied state average hourly earnings by labor hours per metric ton. Table 5. Average Hourly Earnings by Market and State : 2005

State U.S. BLS Series Report I D Average Hourly Earnings ($ ) AL SMU0100000310000006 $15.33 AK SMU0200000300000006 $14.22 AZ SMU0400000310000006 $14.72 AR SMU0500000310000006 $13.98 CA SMU0600000310000006 $16.47 CO SMU0800000310000006 $16.17 CT SMU0900000310000006 $19.57 DE SMU10 00000310000006 $23.20 FL SMU1200000310000006 $13.94 GA SMU1300000310000006 $15.96 HI SMU1500000300000006 $14.34 ID SMU1600000300000006 $14.96 IL SMU1700000310000006 $16.35 IN SMU1800000310000006 $18.90 IA SMU1900000310000006 $15.95 KS SMU2000000310 000006 $17.82 KY SMU2100000310000006 $17.50 LA SMU2200000310000006 $16.62 ME SMU2300000310000006 $16.77 MD SMU2400000310000006 $18.67 MA SMU2500000310000006 $18.48 MI SMU2600000310000006 $23.07 MN SMU2700000310000006 $16.99 MS SMU2800000310000006 $ 14.26 MO SMU2900000310000006 $19.12 MT SMU3000000310000006 $14.87 NE SMU3100000310000006 $15.30 NV SMU3200000310000006 $15.29 NH SMU3300000310000006 $15.95 NJ SMU3400000310000006 $17.42 NM SMU3500000300000006 $13.66 NY SMU3600000310000006 $19.02 N C SMU3700000310000006 $15.04 ND SMU3800000310000006 $15.07 OH SMU3900000310000006 $20.62 OK SMU4000000310000006 $15.93 OR SMU4100000310000006 $15.76 PA SMU4200000310000006 $15.59 RI SMU4400000310000006 $13.08 SC SMU4500000310000006 $16.00 SD SMU460 0000300000006 $13.47 TN SMU4700000310000006 $14.01 TX SMU4800000310000006 $13.53 (continued)

### K ei

th Barnett August 31, 2007 Page 6

Table 5. Average Hourly Earnings by Market and State: 2005 (continued)

State U.S. BLS Series Report ID Average Hourly Earnings ($ ) UT SMU4900000310000006 $14.7 1 VT SMU5000000310000006 $15.45 VA SMU5100000310000006 $17.45 WA SMU5300000300000006 $18.83 WV SMU5400000310000006 $16.71 WI SMU5500000310000006 $17.04 WY SMU5600000300000006 $17.08 U.S. Department of La bor , Bureau of Labor Statistics. 2007. “ State and Area Employment, Hours and Earnings 2005.” Washington, DC: U.S. Department of Labor

. 

### Electricity
To reflect the differences in electri ci ty consumpti on process ty pe and kiln size
, we collected energy consumpt io n (k

Wh) and production data (Table 6). We computed el ectri ci ty consumpt io n rates (AVEI) as fo llo ws:
AVEI = kWh/(0.92*Clinker Production + 0.08*Finished Cement Production). This approach fo llo ws the Portland Cement Association’s (PCA, 2005 ) e nergy efficiency measures using “equivalent tons.” This measure is com posed of 92 % clinker production and 8 % finished cement production.
Table 6 . Electricity Consumption of U.S. Cement Producers b y Process Type : 2005

Process Type Clinker Production ( metric tons ) Finished Cement

Production ( metric tons ) Electricity

C onsumption (1,000 kWh) AVEI

(k Wh per metric ton) a Wet Process 11,054,608 12,150,780 1,660,208 149.0

• 500,000

- ton capacity 3,228,213 3,563,013 515,451 158.4

> 500,000

- ton capacity 7,826,395 8,587,767 1,144,757 145.1 Dry Process 70,112,322 77,036,853 10,778,235 152.5

• 500,000

- ton capacity 1,563,774 1,690,568 276,358 175.6

> 500,000

- ton capacity 68,548,548 75,346,285 10,501,877 152.0 Precalciner 44,295,828 48,559,311 6,725,423 150.7 Preheater 60,357,246 66,278,745 9,224,958 151.6 All Plants 81,166,930 89,187,633 12,438,443 152.0

a Following the Portland Cement Association (PCA, 2005) , the metric tons used to measure energy efficiency are an equivalent ton measure composed of 92 % clinker production and 8 % finished cement production. Source: P or tland Cement Association. December 2005

. U.S. and Canadian Labor

- Energy Input Survey 2005

. Skokie, IL : PCA ’ s Economic Research Department

.

### K ei

th Barnett August 31, 2007 Page 7

Table 7 presents state electricit y pri ces. To calculate electricit y co sts, we mult ip lied these prices by AVEI.
Table 7 . Electricity Price b y Market and State : 2005

State Cents per kWh AL 4.52 AK 9.29 AZ 5.85 AR 4.74 CA 9.55 CO 5.74 CT 9.40 DE 6.21 FL 6.46 GA 5.28 HI 15.79 ID 3.91 IL 4.61 IN 4.42 IA 4.56 KS 4.85 KY 3.60 LA 6.71 ME 7.28 MD 7.01 MA 9.22 MI 5.32 MN 5.02 MS 5.37 MO 4.54 MT 4.83 NE 4.43 NV 7.71 NH 11 .48 NJ 9.76 NM 5.61 NY 8.23 NC 5.04 ND 4.32 OH 5.10 OK 5.11 OR 4.83 PA 6.29 RI 10.01 SC 4.55 SD 4.95 TN 4.73 TX 7.14 UT 4.24 (continued)

### K ei

th Barnett August 31, 2007 Page 8

Table 7 . Electricity Price b y Market and State: 2005 (continued)

State Cents per kWh VT 7.77 VA 4.46 WA 4.27 WV 3.85 WI 5.39 WY 3.99
U.S. En er gy Information Administration. 2006a. Electric Power Annual 2005

. Figure 7 -7

. Washington, DC: U.S. Energy Information Administration.



### Fuel Das (1992 ) represents average variable fuel input rates using the fo llo wing expressio n:

AVFI = (1 + constant) Age in 2005 

### * average variable fuel input of a new kiln

. W e used the calibration procedures described fro m EPA ’ s 1998 cement study (EPA, 1998 ) to

com pute a revised average variable primary fuel input of a new kiln . The constant used remains 0.0087
, and Table 8 reports the average variable fuel input of a new kiln by it s process ty pe and it s capacit y

. Table 8

. Calibrated Average V ar iable Primary Fuel Input for New Kiln by Process Type : 2005

Process Type Average Variable Fuel Input for a New Kiln (million Btu per metric ton) Wet Process •500,000 -t on capacity 2.84

> 500,000 -t on capacity 3.34 Dry Process •500,000 -t on capacity 3 .43
> 500,000 -t on capacity 2.61 Precalciner 2.97 Preheater 3.01



### The AEO 2007 reports other industrial coal, natural gas, and residual fuel prices by census regi on (Table 9) (EIA, 2007 )

. For petroleum coke pri ce , we use d th e procedure outlined in the EIA ’ s State Energy Consumption, Price, and Expenditure Estimates (SEDS): Technical Notes Prices and Expenditures Section 4 (EIA, 2006b )

. In the process described there, t he average pri ce was calculated by dividing the sum of the value of calcined and uncalcined petroleum coke exports by th e sum of export quantit ies. We collected th ese data from the U.S. International

### K ei

th Barnett August 31, 2007 Page 9

Table 9 . Fuel Prices by Census Region, State, and Fuel Type : 2005

Fue l Price ($/million Btu)
Census Region State Other Industrial Coal a Petroleum

Coke b Natural Gas a Residual Oil a East South Central AL $2.47 $1.80 $8.51 $7.81 Pacific AK $2.24 $1.80 $7.46 $7.98 Mountain AZ $1.73 $1.80 $7.71 $7.59 West South Central AR $ 1.79 $1.80 $7.80 $7.02 Pacific CA $2.24 $1.80 $7.46 $7.98 Mountain CO $1.73 $1.80 $7.71 $7.59 New England CT $3.71 $1.80 $10.47 $7.79 Middle Atlantic DE $2.13 $1.80 $9.65 $8.33 South Atlantic FL $2.83 $1.80 $9.11 $7.93 South Atlantic GA $2.83 $1.80 $ 9.11 $7.93 Pacific HI $2.24 $1.80 $7.46 $7.98 Mountain ID $1.73 $1.80 $7.71 $7.59 East North Central IL $2.24 $1.80 $8.52 $7.65 East North Central IN $2.24 $1.80 $8.52 $7.65 West North Central IA $1.21 $1.80 $7.86 $7.18 West North Central KS $1.21 $1 .80 $7.86 $7.18 East South Central KY $2.47 $1.80 $8.51 $7.81 West South Central LA $1.79 $1.80 $7.80 $7.02 New England ME $3.71 $1.80 $10.47 $7.79 South Atlantic MD $2.83 $1.80 $9.11 $7.93 New England MA $3.71 $1.80 $10.47 $7.79 East North Central M I $2.24 $1.80 $8.52 $7.65 West North Central MN $1.21 $1.80 $7.86 $7.18 East South Central MS $2.47 $1.80 $8.51 $7.81 West North Central MO $1.21 $1.80 $7.86 $7.18 Mountain MT $1.73 $1.80 $7.71 $7.59 West North Central NE $1.21 $1.80 $7.86 $7.18 Moun tain NV $1.73 $1.80 $7.71 $7.59 New England NH $3.71 $1.80 $10.47 $7.79 Middle Atlantic NJ $2.13 $1.80 $9.65 $8.33 Mountain NM $1.73 $1.80 $7.71 $7.59 East North Central NY $2.24 $1.80 $8.52 $7.65 South Atlantic NC $2.83 $1.80 $9.11 $7.93 West North Central ND $1.21 $1.80 $7.86 $7.18 East North Central OH $2.24 $1.80 $8.52 $7.65 West South Central OK $1.79 $1.80 $7.80 $7.02 Pacific OR $2.24 $1.80 $7.46 $7.98 Middle Atlantic PA $2.13 $1.80 $9.65 $8.33 New England RI $3.71 $1.80 $10.47 $7.79 South Atlantic SC $2.83 $1.80 $9.11 $7.93 West North Central SD $1.21 $1.80 $7.86 $7.18 East South Central TN $2.47 $1.80 $8.51 $7.81 East South Central TX $2.47 $1.80 $8.51 $7.81 Mountain UT $1.73 $1.80 $7.71 $7.59 (continued)

### K ei

th Barnett August 31, 2007 Page 10

Table 9 . Fuel Prices by Cens us Region, State, and Fuel Type: 2005 (continued)
Fuel Price ($/million Btu)
Census Region State Other Industrial Coal a Petroleum

Coke b Natural Gas a Residual Oil a New England VT $3.71 $1.80 $10.47 $7.79 South Atlantic VA $2.83 $1.80 $9.11 $7.93 P acific WA $2.24 $1.80 $7.46 $7.98 South Atlantic WV $2.83 $1.80 $9.11 $7.93 East North Central WI $2.24 $1.80 $8.52 $7.65 Mountain WY $1.73 $1.80 $7.71 $7.59

a Other industrial coal, natural gas, and residual oil: U.S. Energy Information Administ ration. 2007

. Annual Energy Outlook 2007

. Supplemental Tables 12
, 15 , and 16. Washington, DC: U.S. Energy Information Administration. For kilns using w aste o il as a primary fuel, we u sed the residual fuel oil p rice as a proxy.
b Petroleum coke: Export trade data come from USITC Interactive Tariff and Trade DataWeb (2007)
< http://dataweb.usitc.gov/scripts/user_set.asp >. HTS codes: 271311 and 271312. The price calculation is described in Sta te Energy Consumption, Price, and Expenditure Estimates (SEDS): Technical Notes Prices and Expenditures Section 4 (EIA, 2006b ). < http://www.eia.doe.gov/emeu/states/sep_prices/notes/pr_petrol.pdf. >.



### Trade Commissio ns Database (USITC, 2007 ). To convert units to millio n Btu, we converted fro m met ri c tons to barrels by mult iplying by 5.51, and we converted fro m barrels to millio n Btu by mult iplying by 6.024.
To calculate fuel costs, we used the primary fuel used by the kiln reported by the Portland Cement Associat io n (2004 ) and mult iplied fuel prices by the fuel input equation described above.



### RESULTS
RTI used the methods described above to re vise the kiln

- level AVC functions and to reflect the cost differences across kiln technologies and kiln size. The new AVC est imates for each kiln in th e Atlanta and Balt imo re/Philadelphia markets are reported in Table 10. We report them in reported in doll ars per metric ton and dollars per short ton.August 31, 2007



### Table 10 . Average Variable Cost by Kiln : 2005

Emissions Trading Kiln ID Market

Name Company Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1,000 Metric Tons/Year Average

Vari able Costs ($/Metric Ton) Variable

Costs $/Short Ton GA101 Atlanta Lafarge North America Atlanta Plant Atlanta GA 42 C Dry 315 $60 $54

TN101 Atlanta Buzzi Unicem USA, Inc. Chattanooga Plant Chattanooga TN 5 K Dry -C 771 $38 $35

GA201 Atlanta Cemex Clinch field Plant Clinchfield GA 6 C Dry -X 705 $48 $43 VA101 Atlanta Titan America LLC Roanoke Plant Cloverdale VA 9 C Dry -C 1,120 $45 $41 SC101 Atlanta Giant Cement Holding, Inc. Harleyville Plant Harleyville SC 53 C Wet 164 $57 $51

SC102 Atlanta Giant Cemen t Holding, Inc. Harleyville Plant Harleyville SC 49 C Wet 156 $56 $51

SC103 Atlanta Giant Cement Holding, Inc. Harleyville Plant Harleyville SC 45 C Wet 164 $56 $51

SC104 Atlanta Giant Cement Holding, Inc. Harleyville Plant Harleyville SC 33 C Wet 164 $55 $50

SC201 Atlanta Lafarge North America Harleyville Plant Harleyville SC 17 C Dry -C 972 $43 $39

SC401 Atlanta Holcim (US) Inc. Holly Hill Plant Holly Hill SC 2 C Dry -C 1,860 $41 $38 TN201 Atlanta Cemex Knoxville Plant Knoxville TN 27 C Dry -C 667 $45 $41 PA601 Baltimore/

Philadelphia Giant Cement

Holding, Inc. Bath Plant Bath PA 49 C Wet 103 $54 $49

PA602 Baltimore/

Philadelphia Giant Cement

Holding, Inc. Bath Plant Bath PA 49 C Wet 506 $50 $45

PA801 Baltimore/

Philadelphia Lehigh Cement

Company Alle ntown Plant Blandon PA 40 C Dry 470 $56 $51

PA802 Baltimore/

Philadelphia Lehigh Cement

Company Allentown Plant Blandon PA 40 C Dry 470 $56 $51

MD101 Baltimore/

Philadelphia Essroc Cement

Corp. Frederick Plant Buckeystown MD 47 C Wet 155 $62 $57

MD102 B altimore/

Philadelphia Essroc Cement

Corp. Frederick Plant Buckeystown MD 47 C Wet 155 $62 $57

MD301 Baltimore/

Philadelphia St. Lawrence

Cement Company Hagerstown Plant Hagerstown MD 34 C Dry 513 $52 $48
(continued)August 31, 2007



### Table 10 . Average Variable Cost by Ki ln : 2005 (continued)

Emissions Trading Kiln ID Market

Name Company Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1,000 Metric Tons/Year Average

Variable Costs ($/Metric Ton) Variable

Costs $/Short Ton WV101 Baltimore/

P hiladelphia Essroc Cement

Corp. Martinsburg Plant Martinsburg WV 50 C Wet 177 $54 $49

WV102 Baltimore/

Philadelphia Essroc Cement

Corp. Martinsburg Plant Martinsburg WV 45 C Wet 177 $54 $49

WV103 Baltimore/

Philadelphia Essroc Cement

Corp. Martinsburg Pl ant Martinsburg WV 40 C Wet 354 $53 $48

PA501 Baltimore/

Philadelphia Essroc Cement

Corp. Nazareth Plant I Nazareth PA 27 C Dry -X 1,116 $43 $39

PA502 Baltimore/

Philadelphia Essroc Cement

Corp. Nazareth Plant III Nazareth PA 48 C Dry 150 $57 $52

PA503 B altimore/

Philadelphia Essroc Cement

Corp. Nazareth Plant III Nazareth PA 48 C Dry 155 $57 $52

PA504 Baltimore/

Philadelphia Essroc Cement

Corp. Nazareth Plant III Nazareth PA 56 C Dry 107 $58 $52

PA505 Baltimore/

Philadelphia Essroc Cement

Corp. Nazaret h Plant III Nazareth PA 56 C Dry 107 $58 $52

PA201 Baltimore/

Philadelphia Buzzi Unicem

USA, Inc. Stockertown Plant Stockertown PA 26 K Dry -X 365 $49 $44

PA202 Baltimore/

Philadelphia Buzzi Unicem

USA, Inc. Stockertown Plant Stockertown PA 12 K Dry -X 543 $45 $40

MD201 Baltimore/

Philadelphia Lehigh Cement

Company Union Bridge Union Bridge MD 4 C Dry -C 1,715 $47 $43

PA701 Baltimore/

Philadelphia Lafarge North

America Whitehall Plant Whitehall PA 40 C Dry -X 419 $51 $46

PA702 Baltimore/

Philadelphia Lafar ge North

America Whitehall Plant Whitehall PA 30 C Dry -X 283 $50 $46

MS101 Birmingham Holcim (US) Inc. Artesia Plant Artesia MS 31 C Wet 419 $61 $55 AL301 Birmingham Lafarge North America Roberta Plant Calera AL 3 C Dry -C 1,498 $38 $35

AL101 Birmingham Cemex Demopolis Plant Demopolis AL 28 C Dry -X 821 $41 $38 AL401 Birmingham Lehigh Cement Company Leeds Plant Leeds AL 29 C Dry -X 716 $45 $41
(continued)August 31, 2007



### Table 10 . Average Variable Cost by Kiln : 2005 (continued)

Emissions Trading Kiln ID Market

Name Compa ny Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1,000 Metric Tons/Year Average

Variable Costs ($/Metric Ton) Variable

Costs $/Short Ton AL501 Birmingham National Cement Co. of Alabama Ragland Plant Ragland AL 30 C Dry -C 900 $40 $37

AL201 Birmingham Holcim (US) Inc. Theodore Plant Theodore AL 24 C Dry -C 1,440 $40 $36 IA201 Chicago Lafarge North America Buffalo Plant Buffalo IA 24 C Dry -C 946 $37 $33

IL201 Chicago Cemex Dixon Plant Dixon IL 50 K Dry -X 120 $49 $44 IL20 2 Chicago Cemex Dixon Plant Dixon IL 50 K Dry -X 120 $49 $44 IL203 Chicago Cemex Dixon Plant Dixon IL 50 K Dry -X 120 $49 $44 IL204 Chicago Cemex Dixon Plant Dixon IL 40 K Dry 184 $53 $48 IN101 Chicago Buzzi Unicem USA, Inc. Greencastle Plant Greencastle IN 5 C Dry -C 1,190 $37 $33

IL301 Chicago Eagle Materials La Salle Plant La Salle IL 31 K Dry -X 602 $44 $40 IN201 Chicago Essroc Cement Corp. Logansport Plant Logansport IN 43 K Wet 202 $49 $44

IN202 Chicago Essroc Cement Corp. Logansport Plant Loganspor t IN 43 K Wet 202 $49 $44

IL101 Chicago Buzzi Unicem USA, Inc. Oglesby Plant Oglesby IL 33 C Dry 569 $44 $40

KY101 Cincinnati Cemex Kosmosdale Plant Louisville KY 5 C Dry -C 1,365 $39 $35 IN402 Cincinnati Lehigh Cement Company Mitchell Plant Mitchell IN 55 C Dry -X 251 $49 $44

IN401 Cincinnati Lehigh Cement Company Mitchell Plant Mitchell IN 45 C Dry -X 251 $48 $44

IN403 Cincinnati Lehigh Cement Company Mitchell Plant Mitchell IN 29 C Dry -X 274 $47 $42

IN301 Cincinnati Essroc Cement Corp. Speed Plant Spe ed IN 33 C Dry 279 $52 $47

IN302 Cincinnati Essroc Cement Corp. Speed Plant Speed IN 27 C Dry -X 542 $43 $39

OH101 Cincinnati Cemex Fairborn Plant Xenia OH 31 K Dry -X 661 $44 $40 (continued)August 31, 2007



### Table 10 . Average Variable Cost by Kiln : 2005 (continued)

Emiss ions Trading Kiln ID Market

Name Company Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1,000 Metric Tons/Year Average

Variable Costs ($/Metric Ton) Variable

Costs $/Short Ton OK201 Dallas Holcim (US) Inc. Ada Plant Ada OK 47 C Wet 278 $49 $45 OK202 Dallas Holcim (US) Inc. Ada Plant Ada OK 47 C Wet 278 $49 $45 AR101 Dallas Ash Grove Cement Company Foreman Plant Foreman AR 47 C Wet 246 $49 $44

AR102 Dallas Ash Grove Cement Company Foreman Plant Foreman AR 43 C Wet 246 $48 $44

AR103 Dallas Ash Grove Cement Company Foreman Plant Foreman AR 41 C Wet 339 $48 $44

TX201 Dallas Ash Grove Texas, L.P. Midiothian Plant Midiothian TX 39 C Wet 283 $54 $49

TX202 Dallas Ash Grove Texas, L.P. Midiothian Plant Midiothian TX 36 C Wet 283 $54 $49

TX203 Dallas Ash Grove Texas, L.P. Midiothian Plant Midiothian TX 33 C Wet 283 $54 $49

TX701 Dallas Holcim (US) Inc. Holnam Texas L.P. Midiothian TX 18 C Dry -C 1,036 $42 $38 TX702 Dallas Holcim (US) Inc. Holnam Texas L.P. Midiothian TX 5 C D ry -C 990 $41 $37 TX901 Dallas Texas Industries In c. Midiothian Plant Midiothian TX 45 C Wet 286 $55 $50

TX902 Dallas Texas Industries In c. Midiothian Plant Midiothian TX 42 C Wet 286 $54 $49

TX903 Dallas Texas Industries In c. Midiothian Plant Midiothian TX 38 C Wet 286 $54 $49

TX904 Dallas Texas Industries In c. Midiothian Plant Midiothian TX 33 C Wet 286 $54 $49

TX905 Dallas Texas Industries In c. Midiothian Plant Midiothian TX 4 C Dry -C 1,964 $41 $37

OK301 Dallas Lafarge North America Tulsa Plant Tuls a OK 44 C Dry 347 $51 $46

OK302 Dallas Lafarge North America Tulsa Plant Tulsa OK 42 C Dry 341 $51 $46
(continued)August 31, 2007



### Table 10 . Average Variable Cost by Kiln : 2005 (continued)

Emissions Trading Kiln ID Market

Name Company Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1,000 Metric Tons/Year Average

Variable Costs ($/Metric Ton) Variable

Costs $/Short Ton CO201 Denver Holcim (US) Inc. Portland Plant Florence CO 4 C Dry -C 1,631 $39 $35 WY101 Denver Eagle Materials Laramie P lant Laramie WY 9 C Dry 181 $47 $43 WY102 Denver Eagle Materials Laramie Plant Laramie WY 6 C Dry -X 416 $43 $39 CO101 Denver Cemex Lyons Plant Lyons CO 25 C Dry -X 486 $48 $44 SD101 Denver GCC of America, In c. Dacotah Cement Rapid City SD 50 C Wet 147 $44 $39

SD102 Denver GCC of America, In c. Dacotah Cement Rapid City SD 48 C Wet 147 $43 $39

SD103 Denver GCC of America, In c. Dacotah Cement Rapid City SD 10 C Dry -X 557 $36 $33

MI301 Detroit Lafarge North America Alpena Plant Alpena MI 43 C Dry 364 $54 $49

MI302 Detroit Lafarge North America Alpena Plant Alpena MI 40 C Dry 364 $54 $49

MI303 Detroit Lafarge North America Alpena Plant Alpena MI 40 C Dry 364 $54 $49

MI304 Detroit Lafarge North America Alpena Plant Alpena MI 40 C Dry 536 $42 $38

MI305 De troit Lafarge North America Alpena Plant Alpena MI 40 C Dry 536 $42 $38

MI101 Detroit Cemex Charlevoix Plant Charlevoix MI 26 C Dry -C 1,211 $38 $35 MI201 Detroit Holcim (US) Inc. Dundee Plant Dundee MI 46 C Wet 431 $52 $47 MI202 Detroit Holcim (US) Inc. Dundee Plant Dundee MI 46 C Wet 437 $52 $47 OH201 Detroit Lafarge North America Paulding Plant Paulding OH 49 A Wet 226 $78 $70

OH202 Detroit Lafarge North America Paulding Plant Paulding OH 49 A Wet 228 $78 $70

FL501 Florida Suwannee American Cement Branford FL 2 C Dry -C 682 $49 $45

FL101 Florida Cemex Brooksville Plant Brooksville FL 29 C Dry -X 550 $53 $48 FL102 Florida Cemex Brooksville Plant Brooksville FL 20 C Dry -X 506 $52 $47 FL301 Florida Rinker Materials Brooksville Plant Brooksville FL 18 C Dry -X 605 $52 $47 (continued)August 31, 2007



### Table 10 . Average Variable Cost by Kiln : 2005 (continued)

Emissions Trading Kiln ID Market

Name Company Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1,000 Metric Tons/Year Average

Variab le Costs ($/Metric Ton) Variable

Costs $/Short Ton FL601 Florida Titan America LLC Pennsuco Plant Medley FL 1 C Dry -C 1,492 $45 $41 FL401 Florida Rinker Materials Miami Plant Miami FL 5 C Dry -C 928 $46 $41 FL201 Florida Florida Rock Industries Thompson S. Baker

Plant Newberry FL 6 C Dry -C 726 $49 $45

KS101 Kansas City Ash Grove Cement Company Chanute Plant Chanute KS 4 C Dry -C 1,308 $37 $34

KS301 Kansas City Lafarge North America Fredonia Plant Fredonia KS 69 A Wet 169 $82 $74

KS302 Kansas City Lafarg e North America Fredonia Plant Fredonia KS 49 A Wet 243 $76 $69

KS401 Kansas City Monarch Cement Company Humbolt Plant Humbolt KS 32 C Dry -X 284 $46 $42

KS402 Kansas City Monarch Cement Company Humbolt Plant Humbolt KS 30 C Dry -C 503 $42 $38

KS201 Kansa s City Buzzi Unicem USA, Inc. Independence Plant Independence KS 88 K Dry 82 $58 $53

KS202 Kansas City Buzzi Unicem USA, Inc. Independence Plant Independence KS 88 K Dry 82 $58 $53

KS203 Kansas City Buzzi Unicem USA, Inc. Independence Plant Independence KS 88 K Dry 82 $58 $53

KS204 Kansas City Buzzi Unicem USA, Inc. Independence Plant Independence KS 88 K Dry 82 $58 $53

NE101 Kansas City Ash Grove Cement Company Louisville Plant Louisville NE 29 C Dry -X 338 $44 $40

NE102 Kansas City Ash Grove Cement Co mpany Louisville Plant Louisville NE 23 C Dry -C 507 $40 $36

OK101 Kansas City Buzzi Unicem USA, Inc. Pryor Plant Pryor OK 45 C Dry 189 $51 $46

OK102 Kansas City Buzzi Unicem USA, Inc. Pryor Plant Pryor OK 43 C Dry 186 $51 $46

OK103 Kansas City Buzzi Uni cem USA, Inc. Pryor Plant Pryor OK 25 C Dry 250 $50 $45
(continued)August 31, 2007



### Table 10 . Average Variable Cost by Kiln : 2005 (continued)

Emissions Trading Kiln ID Market

Name Company Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1 ,000 Metric Tons/Year Average

Variable Costs ($/Metric Ton) Variable

Costs $/Short Ton MO501 Kansas City Lafarge North America Sugar Creek Plant Sugar Creek MO 4 C Dry -C 930 $37 $34

CA101 Los Angeles California Portland Cement Colton Plant Colton CA 43 C Dry 340 $66 $60

CA102 Los Angeles California Portland Cement Colton Plant Colton CA 43 C Dry 340 $66 $60

CA801 Los Angeles National Cement Co. of California Lebec Plant Lebec CA 6 K Dry -C 1,033 $48 $43

CA701 Los Angeles Mitsubishi Cement Corporation Cu shenbury Plant Lucerne Valley CA 23 C Dry -C 1,543 $50 $45

CA201 Los Angeles California Portland Cement Mojave Plant Mojave CA 24 C Dry -C 1,363 $50 $45

CA1101 Los Angeles Texas Industries In c. Oro Grande Plant Oro Grande CA 57 C Dry 155 $67 $61

CA1102 Lo s Angeles Texas Industries In c. Oro Grande Plant Oro Grande CA 57 C Dry 155 $67 $61

CA1103 Los Angeles Texas Industries In c. Oro Grande Plant Oro Grande CA 57 C Dry 155 $67 $61

CA1104 Los Angeles Texas Industries In c. Oro Grande Plant Oro Grande CA 53 C Dry 155 $67 $61

CA1105 Los Angeles Texas Industries In c. Oro Grande Plant Oro Grande CA 53 C Dry 155 $67 $61

CA1106 Los Angeles Texas Industries In c. Oro Grande Plant Oro Grande CA 46 C Dry 155 $66 $60

CA1107 Los Angeles Texas Industries In c. Oro Grande Plant Oro Grande CA 46 C Dry 155 $66 $60

CA601 Los Angeles Lehigh Southwest Cement Company Tehachapi Plant Tehachapi CA 14 C Dry -C 958 $49 $45

CA301 Los Angeles Cemex Victorville Plant Victorville CA 22 C Dry -X 1,046 $51 $47 CA302 Los Angeles Cemex Vic torville Plant Victorville CA 4 C Dry -X 1,681 $50 $46 IA101 Minneapolis Holcim (US) Inc. Mason City Plant Mason City IA 39 C Dry 600 $41 $37 IA102 Minneapolis Holcim (US) Inc. Mason City Plant Mason City IA 39 C Dry 371 $50 $45 (continued)August 31, 2007



### Table 10 . Ave rage Variable Cost by Kiln : 2005 (continued)

Emissions Trading Kiln ID Market

Name Company Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1,000 Metric Tons/Year Average

Variable Costs ($/Metric Ton) Variable

Costs $/Short Ton IA301 Minneapolis Lehigh Cement Company Lehigh

- Mason City Mason City IA 27 C Dry -C 755 $37 $33

NY301 New York/

Boston St. Lawrence

Cement Company Catskill Plant Catskill NY 41 C Wet 580 $57 $52

NY101 New York/

Boston Glens Fall Lehigh

Cement Co. Gl ens Falls Plant Glens Falls NY 32 C Dry -X 586 $55 $50

NY201 New York/

Boston Lafarge North

America Ravena Plant Ravena NY 43 C Wet 852 $54 $49

NY202 New York/

Boston Lafarge North

America Ravena Plant Ravena NY 43 C Wet 868 $54 $49

ME101 New York/

Bosto n Dragon Products

Company Thomaston Plant Thomaston ME 34 C Wet 392 $62 $56

AZ201 Phoenix Phoenix Cement Company Clarkdale Plant Clarkdale AZ 46 C Dry -C 187 $46 $42

AZ202 Phoenix Phoenix Cement Company Clarkdale Plant Clarkdale AZ 46 C Dry -C 187 $46 $42

AZ203 Phoenix Phoenix Cement Company Clarkdale Plant Clarkdale AZ 44 C Dry -C 191 $46 $42

AZ204 Phoenix Phoenix Cement Company Clarkdale Plant Clarkdale AZ 3 C Dry -C 912 $37 $33

UT101 Phoenix Ash Grove Cement Company Leamington Plant Nephi UT 24 C Dry -C 810 $35 $32

AZ101 Phoenix California Portland Cement Rillito Plant Rillito AZ 56 C Dry 121 $53 $48

AZ102 Phoenix California Portland Cement Rillito Plant Rillito AZ 54 C Dry 121 $52 $48

AZ103 Phoenix California Portland Cement Rillito Plant Rillito AZ 50 C Dry 121 $52 $47

AZ104 Phoenix California Portland Cement Rillito Plant Rillito AZ 3 C Dry -C 969 $37 $33

NM101 Phoenix GCC of America, In c. Tijeras Plant Tijeras NM 46 C Dry -X 216 $48 $43
(continued)August 31, 2007



### Table 10 . Average Variable Cost by Kiln : 2005 (con tinued)

Emissions Trading Kiln ID Market

Name Company Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1,000 Metric Tons/Year Average

Variable Costs ($/Metric Ton) Variable

Costs $/Short Ton NM102 Phoenix GCC of America, I nc. Tijeras Plant Tijeras NM 45 C Dry -X 216 $48 $43

PA401 Pittsburgh Essroc Cement Corp. Bessemer Plant Bessemer PA 44 C Wet 225 $54 $49

PA402 Pittsburgh Essroc Cement Corp. Bessemer Plant Bessemer PA 41 C Wet 339 $54 $49

PA101 Pittsburgh Armstrong Ceme nt & Sup. Corp. Cabot Plant Cabot PA 79 C Wet 143 $57 $52

PA102 Pittsburgh Armstrong Cement & Sup. Corp. Cabot Plant Cabot PA 79 C Wet 143 $57 $52

PA301 Pittsburgh Cemex Wampum Plant Wampum PA 47 C Dry 215 $57 $51 PA302 Pittsburgh Cemex Wampum Plant Wam pum PA 47 C Dry 205 $57 $51 PA303 Pittsburgh Cemex Wampum Plant Wampum PA 47 C Dry 238 $57 $51 OR101 Salt Lake

City Ash Grove Cement

Company Durkee Plant Durkee OR 7 C Dry -C 816 $38 $34

ID101 Salt Lake

City Ash Grove Cement

Company Inkom Plant Inkom ID 77 C Wet 115 $48 $44

ID102 Salt Lake

City Ash Grove Cement

Company Inkom Plant Inkom ID 54 C Wet 145 $46 $42

MT101 Salt Lake

City Ash Grove Cement

Company Montana City Plant Montana City MT 42 C Wet 293 $46 $42

UT201 Salt Lake

City Holcim (US) Inc. Devi l’ s Slide Plant Morgan UT 8 C Dry -C 704 $38 $34

MT201 Salt Lake

City Holcim (US) Inc. Trident Plant Three Forks MT 32 C Wet 280 $45 $41

TX1201 San Antonio Texas

- Lehigh Cement Company Buda Plant Buda TX 27 C Dry -C 1,125 $43 $39

TX501 San Antonio Cemex Ba lcones Plant New Braunfels TX 25 K Dry -X 1,005 $41 $38 TX1001 San Antonio Texas Industries In c. Hunter Cement Plant New Braunfels TX 26 C Dry -C 780 $43 $39

TX601 San Antonio Cemex Odessa Plant Odessa TX 47 C Dry 256 $58 $53 TX602 San Antonio Cemex Odess a Plant Odessa TX 26 C Dry -X 285 $51 $46 (continued)August 31, 2007



### Table 10 . Average Variable Cost by Kiln : 2005 (continued)

Emissions Trading Kiln ID Market

Name Company Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1,000 Metric Ton s/Year Average

Variable Costs ($/Metric Ton) Variable

Costs $/Short Ton TX101 San Antonio Alamo Cement Company 1604 Plant San Antonio TX 24 C Dry -C 821 $43 $39

TX401 San Antonio Capitol Aggregates, Ltd. Capitol Cement

Division San Antonio TX 40 C Wet 269 $54 $49

TX402 San Antonio Capitol Aggregates, Ltd. Capitol Cement

Division San Antonio TX 22 C Dry -C 599 $46 $42

TX301 San Antonio Buzzi Unicem USA, Inc. Maryneal Plant Sweetwater TX 34 C Dry -X 153 $52 $47

TX302 San Antonio Buzzi Unicem USA, Inc. Maryn eal Plant Sweetwater TX 34 C Dry -X 153 $52 $47

TX303 San Antonio Buzzi Unicem USA, Inc. Maryneal Plant Sweetwater TX 34 C Dry -X 162 $52 $47

CA401 San

Francisco Hanson

Permanente Cemente Permanente Plant Cupertino CA 24 C Dry -C 1,497 $50 $45

CA901 San

Fr ancisco RMC Pacific

Materials Santa Cruz Plant Davenport CA 24 C Dry -C 812 $50 $45

NV101 San

Francisco Eagle Materials Nevada Cement Femley NV 41 C Dry 226 $57 $52

NV102 San

Francisco Eagle Materials Nevada Cement Femley NV 19 C Dry -X 226 $51 $46

CA501 San

Francisco Lehigh Southwest

Cement Company Redding Plant Redding CA 24 C Dry -C 592 $54 $49

WA101 Seattle Ash Grove Cement Company Seattle Plant Seattle WA 13 C Dry -C 675 $43 $39

WA201 Seattle Lafarge North America Seattle Plant Seattle WA 38 K Wet 425 $51 $46

MO101 St. Louis Buzzi Unicem USA, Inc. Cape Girardeau Plant Cape Girardeau MO 24 C Dry -C 1,265 $38 $34

MO401 St. Louis Holcim (US) Inc. Clarksville Plant Clarksville MO 38 C Wet 1,241 $41 $38 MO201 St. Louis Buzzi Unicem USA, Inc. Festus Plant Festus MO 40 K Dry 592 $44 $40
(continued)August 31, 2007



### Table 10 . Average Variable Cost by Kiln : 2005 (continued)

Emissions Trading Kiln ID Market

Name Company Name Plant Name City State Age in 2005 Primary Fuel ID a Process b Clinker Capacity 1,000 Metric Tons/Year Av erage

Variable Costs ($/Metric Ton) Variable

Costs $/Short Ton MO202 St. Louis Buzzi Unicem USA, Inc. Festus Plant Festus MO 36 K Dry 592 $44 $40

IL401 St. Louis Lafarge North America Joppa Plant Grand Chain IL 42 K Dry 443 $53 $48

IL402 St. Louis Lafar ge North America Joppa Plant Grand Chain IL 30 K Dry 612 $42 $38

MO301 St. Louis Continental Cement Co., Inc. Hannibal Plant Hannibal MO 39 C Wet 549 $45 $41

CA1001 White

Cement Texas Industries

In c. Crestmore Riverside CA 47 O Dry 51 $96 $87

CA1002 Whi te

Cement Texas Industries

In c. Crestmore Riverside CA 45 O Dry 51 $95 $86

TX801 White

Cement Lehigh Cement

Company Waco Plant Waco TX 37 G Wet 97 $78 $70

PA901 White

Cement Lehigh Cement

Company York Plant York PA 43 O Wet 112 $79 $72

a Primary Fuel ID codes are coal (C), coke (K) , oil (O), and waste (A)

. b Process codes are preheater (X) and precalciner (C).

### Keit h Barnett

August 31, 2 007 Page 22



### REFERENCES Das, S. 1992. “ A Micro

- Econometric Model of Capital Utilizat io n and Ret ir ement: The Case of th e U.S. Cement Industry. ” Review of Econo mic Studies 59(2):277

- 297.

Portl and Cement Associat io n (PCA)

. December 2004. U.S. and Canadian Portland Cement Industry: Plant Information Summary . Skoki e, IL : P ortl and Cement Associat io n Economic Research Depart me nt

. Portl and Cement Associat io n (PCA) . D ecember 2005

. U.S. and Canadian Labor

- Energy Input Survey 2005 . Skoki e, IL : P ortl and Cement Association Economic Research Department

. Rock Products . 1994. “ Cement Plant Operating Cost Study. ” Overland Park, KS: Intertec Publishing. September
, p. 19.

U.S. Department of Commerce, Bureau of Economic Analysis. 2007. Current

- Dollar and

“ Real ” Gross Domestic Product

. Available at ht tp://www.bea.gov/nat io nal/xls/gdplev.xls. U.S. Department of the Interior, U.S. Geological Survey. 2006a. 2005 Minerals Yearbook, C ement

. Table s 3, 4, and 6. Washington, DC : U .S. Departm ent of th e Interi or. U.S. Department of the Interior, U.S. Geological Survey. 2006b. 2005 Minerals Yearbook, C rushed Stone

. Table 4. Washington, DC: U .S. Department of the Interi or. U.S. Department of Labor, Bureau of Labor Statistics. 2007. “ State and Area Emplo yment, Hours and Earnings 2005. ” Washington, DC: U.S. Department of Labor. U.S. Energy Inform at io n Ad ministration (EIA). 2006a

. Electric Pow er Annual 2005

. Fi gure 7

- 7. Washington, DC : U.S. Energ y I nformation Administration

. U.S. Energy Inform at io n Ad ministration (EIA). 2006b

. State Energy Consumption, Price, and Expenditure Estimates (SEDS) : Technical Notes Prices and Expenditures Section 4

. Washington, DC : U.S. Energy Informati on Administration

. Available at ht tp://www.eia.doe.gov/emeu/states/sep_prices/notes/pr_petrol.pdf. U.S. Energy Inform at io n Ad ministration (EIA). 2007. Annual Energy Outlook 2007

. Suppl emental Tables 12 , 15 , and 16

. Washington, DC : U.S. Energy Inform at io n Ad ministrati on

. U.S. Environmental Protection Agency. June 1998

. Regulatory Impact Analysis of Cement Kiln Dust Rulemaking . Appendix C, p

. 12. Washington, DC: U.S. Environmental Pr otecti on Agency. Available at http://www.epa.gov/epaoswer/other/ckd/ckd/ckdriafn.pdf

. U.S. International Trade Co mmissio n. 2007. USITC Interactive Tariff and Trade DataWeb

. Available at http://dataweb .usi tc.gov/scri pts/user_set.asp . HTS codes: 271311 and 271312.08/0412010



### Technical Merm: Comparison of Analytical Tools

Used to Evaluate the Final Cement NESHAP and NSPS Rulemakings

For the National Emission Standards for Hazardous Air Pollutants (NESHAP) from the Portland Cement Manufacturing Industry and the New Source Perfonnance Standards (NSPS) for Portland Cement Plants, EPA utilized three models to evaluate the impacts of the regulation

on the industry and the economy. The models include: the Control Cost Model from the Engineering Analysis, the Economic Impact Analysis model, and the Industrial Sector Integrated Solutions (ISIS) model.

Typically in 

### a regulatory analysis, EPA dctennines the regulatory options suitable to
meet statutory obligations under the Clean Air Act. Based on the stringency of those options, EPA then detennines the control technologies and monitoring requirements that may be selected

to comply with the regulation. This is conducted in an Engineering Analysis. The selected control technologies and monitoring requirements are then evaluated in a cost model to determine the total annualized control costs. The annualized control costs serve as inputs to an Economic Impact Analysis model that evaluates the impacts of those costs on the industry and society as a whole.

For the Portland cement NESHAP and NSPS, EPA also employed the Industrial Sectors Integrated Solution Model (ISIS) which conducts both the engineering cost analysis and the economic analysis in a single modeling system. The ISIS Model 

### is a dynamic and integrated model that simulates potential decisions made in the cement industry to meet an environmental policy under a regulatory scenario. ISIS simultaneously estimates I) optimal industry operation

to meet the demand and emission reduction requirements, 2) the suite of control technologies needed to meet the emission limit, 3) the engineering cost of controls, and 4) economic response of the policy. The objective function in ISIS maximizes the total surplus for a sector while meeting projected demand for applicable commodities and emissions constraints over the time horizon of interest. ISIS has been designed to analyze the impacts of control strategies upon the

cement manufacturing industry. The model has the capability to estimate the change in cost of

### production, prices, and output for the cement industry resulting from implementation of a regulation, and determining applicable control technology installations.

The costs of the Engineering Analysis are estimated based on the type of control device that is assumed necessary for a source to comply with the proposed emission standards. Based on

a kiln's baseline emissions of pollutants of interest and the removal efficiency necessary to comply with the proposed emission limit for each regulated pollutant an appropriate control device, or control devices, is identified. In assigning control devices to each kiln where more than one control device would reduce emissions of a particular regulated pollutant below the limit, it is assumed that the least costly control would be installed. However, in some instances, a

more expensive technology is considered appropriate because the selected control reduced emissions of multiple pollutants. For many kilns, this analysis assumes that multiple controls will have to be added because more than one control will be needed to control all regulated pollutants under analysis. This approach and the resulting cost estimates are considered conservative in that it is not possible to consider what other alternatives, in lieu of multiple add·on controls, may be available to cement plants to comply with the proposed emission limits. Because individual

cement manufacturing plants may implement process or other changes to reduce emissions, the
costs of the proposed amendments likely overstate the costs that actually will be incurred by individual cement plants.

The Cement Economic Impact Analysis (EIA) model uses a single-period static partialequilibrium model to compare a pre-policy cement market baseline with expected post-policy

outcomes in cement markets. This model was used in previous EPA analyses of the Portland
cement industry (EPA, 1998; EPA, 1 999b) and for the proposal. The time horizon for the analysis is for the intermediate run when producers have some constraints on their flexibility to adjust factors of production. This time horizon allows us to capture important transitory impacts of the program on existing producers. The model uses traditional engineering costs analysis as "exogenous" inputs (i.e. determined outside of the economic model) and computes the associated economic impacts of the proposed regulation.

This memo provides a comparison of parameters in these models to provide an evaluation of how the differences between the models may impact the results presented in 

### the supporting documentation to the regulation.

2

### Engineering Analysis

In table I, we present the comparison of the Engineering Analysis and the Cost Module ofISIS. With regard to data inputs, both models used the same control technologies inputs such

as control efficiency, and installation and operation cost, as well as used the same 2009 database of kilns. A key difference regarding the two models is that while the Engineering Analysis

assumes the kiln population to be constant for its analysis, ISIS takes into account change in operation, e.g., closure, expansion, retirements, and new units that operate more efficiently and thus emit lower levels of pollution. Another difference between these two models resides in the
way the total cost of controls is calculated. While, the Engineering Analysis identify the specific controls required to meet the proposed emissions limits for each kiln, and then developed capital and annualized control costs, ISIS uses a dynamic optimization approach to select control technologies to meet the emission limits at each kiln in a manner that considers cost, co-pollutant reductions, and economics of operation, simultaneously. For example, ISIS allows for optimization at the kiln and plant level. Ifone plant operates two kilns, ISIS might detennine that it is more cost effective to decrease production at one kiln to a level that meets the emission limit, and increase production at the second kiln while applying control technology. In this example, the Engineering Analysis would apply controls at both kilns, while ISIS applies controls at only one kiln. Overall, because ofthese differences, we would expect the total control costs from ISIS to be lower than that of the Engineering Analysis.

Table 1: Comparison of the Analytical Models: Engineering Cost Model Dimension

Parameter Engineering Analysis 

### ISIS

Kiln Population

-Existing Non hazardous waste kilns in All kilns in existence in 2009 (148 existence 

### in 2009 (154 kilns) non hazardous waste kilns ' and 20 hazardous waste kilns 2 )



### No retirements, expansions or Model allows for replacement and replacements from existing kilns retirements of existing kilns when optimizing production costs in a given year.

-New A total of9 new kilns are estimated A total of9 new kilns are estimated based on industry growth projected based on industry growth projected between 201 Oand 20 

### J 3. Capacity 0 

### f between 2010 and 2013. Capacity of

I ISIS does nol include two white cement kilns and 2 gray cement kilns in Puerto Rico.

2 Hazardous waste kilns in ISIS are nol subject to the NESHAP limits.



### 3

### each kiln is based on the Portland each kiln is based on PCA's Capacity Cement Association (PCA) Capacity Report (October, 2009). Report (October, 2009). Control Detennined by engineering Endogenously detennined in the technology judgment assuming operation of the model based on maximizing total application kiln constant at a 2009 levels. surplus while meeting the demand and emission reduction requirements.

Cost of Control Based on empirical cost data, EPA Based on empirical cost data, EPA Technology Control Cost Manual, published Control Cost Manual, published data, data, Manufacturer Data and Manufacturer Data and emission test emission test data when available. data when available.

Total Control Summation of capital and Uses same technology costs as the Cost annualized costs for each control Engineering Analysis for calculating technology applied to the kilns total control costs. However, the

comes from EPA reports such as control cost also takes into account EPA Air Pollution Control Cost the operation of the kiln. Further, the Manual, Alternative Control model allows for fuel-switching, Technology (ACT) reports, and which could affect flue gas volume others. and control costs.

Costs for existing sources are Costs on new and existing sources are estimated separately from new estimated simultaneously.

sources.

Total Control Costs are summed and Total Control Costs are summed and amortized using a 7% discount rate. the net present value is calculated using a 7% discount rate.
Major vs. Area Known area sources not subject to Will allow unaffected area sources to Source Kilns emission limits are factored into increase production to meet demand. engineering cost estimates. Has the capability to apply differential regulatory requirements

on major point and area sources which can affect supply curve 

### in a given demand center.

Hazardous Waste Kilns not subject to emission limits Kilns not subject to emission limits Kilns under this analysis. under this analysis.

Will allow unaffected hazardous waste kilns to increase production to meet demand which can affect supply

curve in a given demand center.

4

### Emission Emission reductions are based of Begins with baseline emissions in reductions emissions in 2009. Baseline 2009 and considers growth and emissions at each kiln/facility are capacity changes out to the year of then multiplied by the control promulgation ofthe rule (2013). efficiency measures for each pollutant reduced by the selected control technology. Estimates ex-ante and ex post emissions of pollutants under consideration.

Evaluates collateral impacts, such as reductions (or increases) 

### in criteria pollutants emissions as a result of 

## I pOlicy-induced control applications.



### Economic Impact Analysis

In table 2, we present the comparison of the Cement EIA Model and the Economic framework of the ISIS Model. With regard to the characterization of the cement industry, both models treat the cement industry as regional in nature due to the costs of transporting the commodity across long distances (i.e., cost prohibitive conditions creates regional markets)

.. A key difference between the models is 

### in the treatment of markets and supply points (i.e., kilns and import districts). In the Cement EJA Model, each kiln is modeled in one of20 cement markets and each cement market is an independent market (i.e., markets are treated as isolated regions). In ISIS, each of the 50 demand centers can be supplied by any of the kilns or import districts in the U.S. In ISIS, the decision to supply from a kiln or an import district takes in to
account the cost of transportation, which in turn is dependent on the relevant mode of transportation and applicable distance. The EIA's model of independent markets is consistent with review of recent economic literature on cement market behavior undertaken prior to the running of this model for this regulation and documented in the RIA. 

### On the other hand, the trading that takes place within ISIS is consistent with the market behavior reported by the Portland Cement Association (PCA) (APCA, 1997)3. The EIA model characterizes the cement industry as an**olig~poly** 

### while the ISIS model characterizes the industry as perfectly competitive with supplies to demand centers affected by transportation costs. Because the oligopoly structure

3 ISIS characterization of seller behavior takes into account peA comments that producers "rather than restricting output to control price they seek to produce whatever amount of cement their customers demand at the prevailing price levels. arranging for imported cement when domestic production capacity is insufficient to meet demand" (APCA. 1997).



### 5

### models finn choices in a way that takes into account the impact of the firm 

### choice on price rather than as a price taker as ISIS does, production changes are expected to be larger for a given policy than if the market were modeled as perfectly competitive.

Regarding imports, both models characterize imports as a perfect substitute for domestically produced cement. Both models treats imports as elastic but use different values for supply elasticity (see Table 2 below). ISIS also includes capacity constraints associated with import districts.



### Table 2: Comparison of Analytical Models: Economic Model Dimension

Characteristic Cement EIA Model ISIS Model

Kiln Population Kilns in existence in 2005 and six All kilns in existence in 2009 plus kilns that have since replaced kilns kilns projected to come on-line from in existence in 2005 are modeled. 20 tOto 2013 are modeled. This 13 other kilns on-line after 2005 includes hazardous waste kilns. and 7 NSPS kilns are treated outside of the model.

Direct Compliance Costs Assigned to kiln based on Choice of control technology (before market Engineering Analysis. determined within the model. adjustments)

Markets 20 markets 50 demand centers

Cement Supply & Demand Single period Single Period

Baseline year: 2005 Baseline Year: Average projected PCA's demand from 2013-2018

Model Horizon: 2013

USGS Data USGS combined with PCA future year projections

Supply & Demand adjust with Supply & Demand adjusts with

cement price changes cement price changes

Imports Perfect substitution Perfect substitution

USGS custom district data USGS custom district data

Import elasticity = 2.4. Import elasticity = 3.94

Seller behavior Coumot multi-firm oligopoly Perfect comoetition with suonlies



### 6affected by transportation costs

With a small number of firms in Firms lake the market price as given each region, firm's recognize their production decision influences the market price

Seller behavior implies there is a Assumes no**pre~existing** distortion in**pre~existing** distortion in the market the market (e.g. price is not equal to marginal (e.g. price is equal marginal costs) costs) Energy Use No Fuel Switching Fuel Switching is pennitted, which gives additional flexibility to a finn to meet the emission requirements

Closures No closures modeled. If the model A kiln is idling if in the policy case its predicts for a kiln that profits will capacity utilization rale is zero be negative and utilization will drop significantly the kiln is identified to be to be in danger of being idled until market conditions imorove. Regional Market Each regional market is Each kiln or import district can Interactions independent o(the other with no supply any of the 50 demand centers,
cross boundary trades subject to cost of production, cost of imports, and cost of transportation. Total Regulatory Cost Measure

- Measure

- Direct Compliance Costs Social cost 

### + total cost to meet the demand (cost Social cost is estimated based on of production, imports and intertraditional social wei fare economics market transportation) (changes in producer and consumer surplus) in reaction to the direct compliance costs. Job losses The employment effect (the demand Calculated in the post processing of effect) is estimated assuming that the model based on the difference employment is proportional to between base case employee hour/ton 

### I production. of clinker to the Dolicv case.



### Further details on how 

### economic impacts are estimated by these models can be found in the Regulatory Impact Analysis (RIA) and the ISIS Technical Support Document (TSD) for the final NESHAP. In addition, EPA conducted a peer review ofISIS, which can be found in the docket to this rulemaking.

7

### APPENDIX A

PARTIAL EQUILIBRIUM ANALYSIS: COMPARISON OF MODEL FEATURES

EPA considered the rule's economic effects using partial equilibrium analysis; the 

### approach is highlighted as an important assessment tool in EPA's Guidelines for Preparing
Economic Analyses (EPA, 2000). However, partial equilibrium models can he implemented in a variety of ways. As a result, 

### it is important to discuss key model features when presenting a
range of estimated economic effects.

Since the Economic Impact Model and the ISIS Model put partial equilibrium analysis into practice in different ways, this appendix provides additional information about two model features that can help key stakeholders better understand and interpret the analysis. First, we discuss how the two approaches define a cement company's "best" production decision given the market definition and the existing number of plants producing cement in these markets. Second,

we discuss differences in the ways the approaches allow regional markets to interact.



### A.I Cement Production Decision and Marginal Analysis

Both economic models assume that the cement company acts in the best interest of its shareholders and maximizes profits. When deciding whether to make another ton of cement, the
company considers the 

### production effect on profits by comparing the current market price of

cement and the marginal cost; if price is above marginal cost, producing and selling the extra ton of cement increases profit. The company continues to produce additional cement until the profit from producing an extra ton of cement is zero (price equals marginal cost) or capacity constraints

are reached. The ISIS Model uses this decision rule and is consistent with the assumption of pure competition.

Now consider an alternative view used in the Economic Impact Model that examines the possible implications of a different market structure; one that has 

### few companies but sells similar

or identical products. 4 

### In this case, the cement company continues to consider the 

### production effect described above but adds another dimension to the decision-making process; it considers the 

### market price e.ffect that is associated with producing an additional ton of cement. Given the small number of cement producers, adding an extra ton of cement to the market may 

### lower the market price of cement and reduce the profits on all the other cement sold. lithe price effect is large enough, it may be more profitable for the company to reduce production below the levels

4 This model is formally known as a multi-finn Coumot Oligopoly model.



### 8

### implied by pure competition. As the number of producers expands, the cement company would become less concerned about the market price effect, and the production decision becomes more consistent with decisions made in pure competition.



### A.l.l Market-Level Effects

What are the consequences of these differences as they relate to measures of the projected market-level price and quantity changes? To provide some intuition about the size of the differences, we present a simple market analysis with two kilns operated by different companies. Assume the marginal cost of cement production for each plant 

### is $98 and $1 ()() per metric ton. The market demand for cement 

### is met by both kilns; the least expensive kiln operates at full capacity, and 

### the highest cost kiln operates at 85% capacity. The baseline cement price is equivalent to the high-cost kiln ($1 (0).



### Three examples show the mechanics of how the pure competition model projects market price changes in response to the regulation. The market price changes are driven by underlying differences in the baseline kiln production costs and 

### the distribution of incremental compliance
costs across kilns.



### Example I: Both kilns face an additional $1 per ton in compliance costs. The marginal
cost of production for each kiln is now $99 and $101. In equilibrium, the new market price is $101 (I % 

### increase). Assuming a demand elasticity of -I, 

### the quantity demanded with regulation falls by 1%.



### Example 2: Next, only the least-cost kiln faces an additional $1 per ton in compliance
costs. The marginal cost of production for each kiln is now $99 and $100. In equilibrium, there is

no change in the market price ($100), and there is no change in the quantity demanded.



### Example 3: Now the least-cost kiln faces an additional $3 per ton 

### in compliance costs. The marginal cost of production for each kiln is now SI 01 and $100. In equilibrium, the new market price is SIOI (1 % increase). Assuming a demand elasticity of 

### -1. the quantity demanded with regulation falls by 1 %. Note the similarity with the market outcomes in Example 1.

Now consider the same market 

### in the Economic Impact Model. As discussed earlier. the
company considers the market price effect of the production decision. For example, when



### 9

### making the decision to raise production by one ton of cement, the change in marginal revenue (dMRi) must equal the change in the marginal cost of producing cement: s

6Marginal Revenue = 

### 6Marginal Cost

where the change in marginal revenue depends on the market price effects brought on by producing an additional ton of cement. To estimate price and quantity changes in this framework,

we used the model equations described in Appendix C of the RIA.

Example 

### 1: Both kilns face an additional $1 per ton in compliance costs. In equilibrium, the new market price 

### is $102 (2% increase). Assuming a demand elasticity of -I, 

### the quantity demanded with regulation falls by 2%.

Example 

### 2: Next, only the least-cost kiln faces an additional $1 per ton in 

### compliance
costs. In equilibrium, the new market price is $101 (l % 

### increase). Assuming a demand elasticity of -I. 

### the quantity demanded with regulation falls by 1%.

Example 

### 3: The least-cost kiln faces an additional $3 per ton in compliance costs. In equilibrium, the new market price is $103 (3% increase). Assuming a demand elasticity of -I, 

### the quantity demanded with regulation falls by 3%.

Table A-I compares the projected market-level changes in these examples. As expected, the projected relative price and quantity changes are higher under the multi-frrm Coumot oligopoly model.

S The equation is fonnally discussed in Appendix A and Appendix B of the RIA.

10

### Table A-I. 

### Market-Level Effects Comparisons

Baseline Price Change Quantity Change Marginal (Percent) (percent) Cosl Incremental ($Imetric Compliance Cost P"", Cournol Pur< Cournot Type Ion) (Slmetric ton) Competition Oligopoly Competition Oligopoly Example 1
Kiln I $98 $1 1.0% 2.0% -1.0010 -2.()D1o Kiln 2 $100 $1 Extlmple 2
Kiln I $98 $1 0.0% 1.0% 0.0% -1.0"10 Kiln 2 $100 $0 Example 3
Kiln 1 $98 $3 1.0-;' 3.0010 -1.0% -3.0010 Kiln 2 $100 $0



### A.2 Cement Transportation and Trade between U.S. Cement Regions

The Economic Impact Model uses 20 regional markets and the ISIS Model uses the 50 regtonal demand centers. The Economic Impact Model assumes that transportation costs between regions are high enough that interregional trade 

### is unlikely to occur. at least in the short run. In

contrast. the ISIS Model adds some additional flexibility in the model that allows cement plants

to ship cement to other demand centers if the additional benefits of selling cement to these
markets outweigh the costs of transporting the cement outside the regional market. Details of transportation cost assumptions of this ISIS Module are described in the ISIS technical documentation.



### A.Z.l Market-Level Effects

What are the consequences ofthe trade assumptions as they relate to measures of the projected market-level price and quantity changes? Allowing trade 

### in the Economic Impact Model would expand the cement market definitions and increase the number of producers. As discussed above, as the number of producers in a market increases, the production decision becomes more consistent with decisions made in pure competition. The extent to which trade

across regions is feasible would be driven by the assumptions about transportation costs. The examples in Table A-I show that increasing the number of producers participating in the market
could moderate projected price increases and subsequent consumption changes.

I I