August 2010

Regulatory Impact Analysis:

Amendments to the National Emission Standards for Hazardous Air
Pollutants and New Source Performance Standards (NSPS) for the Portland
Cement Manufacturing Industry

Final Report

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards (OAQPS)

Air Benefit and Cost Group

(MD-C439-02)

Research Triangle Park, NC 27711

Regulatory Impact Analysis:

Amendments to the National Emission Standards for Hazardous Air
Pollutants and New Source Performance Standards (NSPS) for the Portland
Cement Manufacturing Industry

Final Report

August 2010

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards (OAQPS)

Air Benefit and Cost Group

(MD-C439-02)

Research Triangle Park, NC 27711

Contents

Section	Page

  TOC \o "1-3" \u  1	Introduction	  PAGEREF _Toc265840590 \h  1-1

1.1	Executive Summary	  PAGEREF _Toc265840591 \h  1-1

1.2	Organization of this Report	  PAGEREF _Toc265840592 \h  1-3

2	Industry Profile	  PAGEREF _Toc265840593 \h  2-1

2.1	The Supply Side	  PAGEREF _Toc265840594 \h  2-1

2.1.1	Production Process	  PAGEREF _Toc265840595 \h  2-1

2.1.2	Types of Portland Cement	  PAGEREF _Toc265840596 \h  2-3

2.1.3	Production Costs	  PAGEREF _Toc265840597 \h  2-3

2.2	The Demand Side	  PAGEREF _Toc265840598 \h  2-8

2.3	Industry Organization	  PAGEREF _Toc265840599 \h  2-10

2.3.1	Market Structure	  PAGEREF _Toc265840600 \h  2-10

2.3.2	Manufacturing Plants	  PAGEREF _Toc265840601 \h  2-11

2.3.3	Firm Characteristics	  PAGEREF _Toc265840602 \h  2-16

2.4	Markets	  PAGEREF _Toc265840603 \h  2-20

2.4.1	Market Volumes	  PAGEREF _Toc265840604 \h  2-21

2.4.2	Market Prices	  PAGEREF _Toc265840605 \h  2-22

2.4.3	Future Projections	  PAGEREF _Toc265840606 \h  2-22

3	Economic Impact Analysis	  PAGEREF _Toc265840607 \h  3-1

3.1	Regulatory Program Costs	  PAGEREF _Toc265840608 \h  3-2

3.2	Partial-Equilibrium Analysis	  PAGEREF _Toc265840609 \h  3-5

3.2.1	Regional Structure and Baseline Data	  PAGEREF _Toc265840610 \h
3-6

3.2.2	Near-Term Cement Plant Production Decisions	  PAGEREF
_Toc265840611 \h  3-6

3.2.3	Economic Impact Model Results	  PAGEREF _Toc265840612 \h  3-9

3.3	Other Economic Analyses: Direct Compliance Cost Methods	  PAGEREF
_Toc265840613 \h  3-18

3.4	Social Cost Estimates	  PAGEREF _Toc265840614 \h  3-19

3.5	Energy Impacts	  PAGEREF _Toc265840615 \h  3-21

3.6	Assessment	  PAGEREF _Toc265840616 \h  3-23

4	Small Business Impact Analysis	  PAGEREF _Toc265840617 \h  4-1

4.1	Identify Affected Small Entities	  PAGEREF _Toc265840618 \h  4-1

4.2	Sales and Revenue Test Screening Analysis	  PAGEREF _Toc265840619 \h
 4-1

4.3	Additional Market Analysis	  PAGEREF _Toc265840620 \h  4-3

4.4	Assessment	  PAGEREF _Toc265840621 \h  4-3

5	Air Quality Modeling of Emission Reductions	  PAGEREF _Toc265840622 \h
 5-1

5.1	Synopsis	  PAGEREF _Toc265840623 \h  5-1

5.2	Photochemical Model Background	  PAGEREF _Toc265840624 \h  5-1

5.3	Model Domain and Grid Resolution	  PAGEREF _Toc265840625 \h  5-2

5.4	Emissions Input Data	  PAGEREF _Toc265840626 \h  5-2

5.5	Model Results: Air Quality Impacts	  PAGEREF _Toc265840627 \h  5-5

5.5	Limitations (Uncertainties) Associated with the Air Quality Modeling
  PAGEREF _Toc265840627 \h  5-5

6	Benefits of Emissions Reductions	  PAGEREF _Toc265840628 \h  6-1

6.1	Synopsis	  PAGEREF _Toc265840629 \h  6-1

6.2	Calculation of PM2.5 Human Health Benefits	  PAGEREF _Toc265840630
\h  6-2

6.2.1	Methodology Improvements since Proposal	  PAGEREF _Toc265840631 \h
 6-2

6.2.2	Benefits Analysis Approach	  PAGEREF _Toc265840632 \h  6-3

6.2.3	Health Impact Analysis (HIA)	  PAGEREF _Toc265840633 \h  6-4

6.2.4	Estimating PM2.5-related premature mortality	  PAGEREF
_Toc265840634 \h  6-8

6.2.5	Economic valuation of health impacts	  PAGEREF _Toc265840635 \h
6-11

6.3	Health Benefits Results	  PAGEREF _Toc265840636 \h  6-13

6.4	Energy Disbenefits	  PAGEREF _Toc265840637 \h  6-20

6.4.1	PM2.5 Disbenefits	  PAGEREF _Toc265840638 \h  6-25

6.4.2	Social Cost of Carbon and Greenhouse Gas Disbenefits	  PAGEREF
_Toc265840639 \h  6-27

6.4.2	Total Disbenefits	  PAGEREF _Toc265840639 \h  6-27

6.5	Unquantified or Nonmonetized Benefits	  PAGEREF _Toc265840637 \h
6-20

6.5.1	Other SO2 and PM Benefits	  PAGEREF _Toc265840638 \h  6-25

6.5.2	HAP Benefits	  PAGEREF _Toc265840639 \h  6-27

6.6	Limitations and Uncertainties	  PAGEREF _Toc265840640 \h  6-41

6.6.1	Monte Carlo Analysis	  PAGEREF _Toc265840641 \h  6-41

6.6.2	Alternate Concentration-Response Functions for PM Mortality
PAGEREF _Toc265840642 \h  6-42

6.6.3	LML Assessment	  PAGEREF _Toc265840643 \h  6-42

6.6.4	Qualitative Assessment of Uncertainty and Other Analysis
Limitations	  PAGEREF _Toc265840644 \h  6-43

6.7	Comparison of Benefits and Costs	  PAGEREF _Toc265840645 \h  6-44

7	References	  PAGEREF _Toc265840646 \h  7-1

 Appendixes

A	Short-Run Regional Portland Cement Economic Model	A-1

B	The Cement Plant’s Production Decision: A Mathematical
Representation	B-1

C	Social Cost Methodology	C-1

D	Summary of Expert Opinions on the Existence of a Threshold in the
Concentration-Response Function for PM2.5-related Mortality	D-1

List of Figures

Number	Page

  TOC \t "Figure Title,5"  2-1.	Simplified Flow Sheet of Clinker and
Cement Manufacture	  PAGEREF _Toc265841183 \h  2-2

2-2.	Labor Costs per Metric Ton of Cement ($2005)	  PAGEREF
_Toc265841184 \h  2-7

2-3.	Distribution of Energy Consumption	  PAGEREF _Toc265841185 \h  2-8

2-4.	End Uses of Cement: 1975 to 2003	  PAGEREF _Toc265841186 \h  2-9

2-5.	Producer Price Indices for Competitive Building Materials: 2003 to
2008	  PAGEREF _Toc265841187 \h  2-10

2-6.	Distribution of Cement Kilns in the United States	  PAGEREF
_Toc265841188 \h  2-13

2-7.	Historical U.S. Cement Price	  PAGEREF _Toc265841189 \h  2-23

2-8.	Deviation from National Average Cement Price per Metric Ton by
Region: 2005	  PAGEREF _Toc265841190 \h  2-24

3-1.	Range of Per-Ton Total Annualized Compliance Costs (2005$)
PAGEREF _Toc265841191 \h  3-4

5-1.	Map of the Photochemical Modeling Domain	  PAGEREF _Toc265841192 \h
 5-3

6-1.	Total Monetized Benefits for the Final Cement NESHAP and NSPS in
2013	  PAGEREF _Toc265841193 \h  6-2

6-2.	Illustration of BenMAP Approach	  PAGEREF _Toc265841194 \h  6-5

6-3.	Data inputs and outputs for the BenMAP model	  PAGEREF
_Toc265841195 \h  6-6

6-4.	Breakdown of Monetized PM2.5 Health Benefits using Mortality
Function from Pope et al. (2002)	  PAGEREF _Toc265841196 \h  6-16

6-5.	Total Monetized PM2.5 Benefits for the Final Cement NESHAP and NSPS
in 2013	  PAGEREF _Toc265841197 \h  6-18

6-6.	Percentage of Total PM-Related Mortalities Avoided by Baseline Air
Quality Level for Final Portland Cement NESHAP and NSPS	  PAGEREF
_Toc265841198 \h  6-19

6-7.	Cumulative Percentage of Total PM-related Mortalities Avoided by
Baseline Air Quality Level for Final Portland Cement NESHAP and NSPS
PAGEREF _Toc265841199 \h  6-20

6-8.	Estimated County Level Carcinogenic Risk from HAP exposure from
outdoor sources (NATA, 2002)	  PAGEREF _Toc265841200 \h  6-28

6-9.	Estimated County Level Noncancer (Respiratory) Risk from HAP
exposure from outdoor sources (NATA, 2002)	  PAGEREF _Toc265841201 \h
6-29

6-10.	Reductions in Total Mercury Deposition (µg/m2) in the Eastern
U.S.	  PAGEREF _Toc265841202 \h  6-33

6-11.	Reductions in Total Mercury Deposition (µg/m2) in the Western
U.S.	  PAGEREF _Toc265841203 \h  6-34

6-12.	Net Benefits for the Final Portland Cement NESHAP and NSPS at 3%
Discount Rate	  PAGEREF _Toc265841204 \h  6-47

6-13.	Net Benefits for the Final Portland Cement NESHAP and NSPS at 7%
Discount Rate	  PAGEREF _Toc265841205 \h  6-48

List of Tables

Number	Page

  TOC \t "Table Title,5"  1-1.	Summary of the Monetized Benefits, Social
Costs, and Net Benefits for the Final Portland Cement NESHAP in 2013
(millions of 2005$)	  PAGEREF _Toc265841303 \h  1-4

2-1.	Portland Cement Shipped from Plants in the United States to
Domestic Customers, by Type	  PAGEREF _Toc265841304 \h  2-4

2-2.	Raw Material Input Ratios for the U.S. Cement Industry: 2000 to
2005	  PAGEREF _Toc265841305 \h  2-5

2-3.	Raw Material Costs by Market and State: 2005	  PAGEREF
_Toc265841306 \h  2-6

2-4.	Labor Productivity Measures for the U.S. Cement Industry by Process
Type: 2000 to 2005 (employee hours per metric ton)	  PAGEREF
_Toc265841307 \h  2-6

2-5.	Energy Consumption by Type of U.S. Cement Plant (million BTU per
metric ton)	  PAGEREF _Toc265841308 \h  2-8

2-6.	Number of Kilns and Clinker Capacity by State: 2005	  PAGEREF
_Toc265841309 \h  2-12

2-7.	Number of Kilns and Clinker Capacity by Age and Process Type
PAGEREF _Toc265841310 \h  2-14

2-8.	Clinker Capacity, Production, and Capacity Utilization in the
United States: 2000 to 2005	  PAGEREF _Toc265841311 \h  2-15

2-9.	Capacity Utilization Rates by State: 2005	  PAGEREF _Toc265841312
\h  2-17

2-10.	Cement Manufacturing Employment (NAICS 327310): 2000 to 2005
PAGEREF _Toc265841313 \h  2-18

2-11.	Ultimate Parent Company Summary Data: 2005	  PAGEREF _Toc265841314
\h  2-19

2-12.	Historical U.S. Cement Statistics (106 metric tons)	  PAGEREF
_Toc265841315 \h  2-21

2-13.	U.S. Cement Trade Data: 2000 to 2007	  PAGEREF _Toc265841316 \h
2-22

3-1.	Summary of Direct Total Annualized Compliance Costs (million,
2005$)	  PAGEREF _Toc265841317 \h  3-3

3-2.	Range of Per-ton Total Annualized Compliance Costs by State (2005$)
  PAGEREF _Toc265841318 \h  3-5

3-3.	Portland Cement Prices by Market ($/metric tons): 2005	  PAGEREF
_Toc265841319 \h  3-7

3-4.	Portland Cement Markets (106 metric tons): 2005	  PAGEREF
_Toc265841320 \h  3-8

3-5.	National-Level Market Impacts: 2005	  PAGEREF _Toc265841321 \h  3-9

3-6.	Regional Compliance Costs and Market Price Changes ($/metric ton of
cement): 2005	  PAGEREF _Toc265841322 \h  3-10

3-7.	Summary of Regional Market Impacts: 2005	  PAGEREF _Toc265841323 \h
 3-12

3-8.	Distribution of Industry Impacts: 2005	  PAGEREF _Toc265841324 \h
3-13

3-9.	Cement Plants with Significant Utilization Changes: 2005	  PAGEREF
_Toc265841325 \h  3-14

3-10.	Job Losses/Gains Associated with the Final Rule	  PAGEREF
_Toc265841326 \h  3-16

3-11.	Distribution of Social Costs ($106): 2005	  PAGEREF _Toc265841327
\h  3-20

3-12.	U.S. Cement Sector Energy Consumption (Trillion BTUs): 2013
PAGEREF _Toc265841328 \h  3-23

4-1.	Small Entity Analysis	  PAGEREF _Toc265841329 \h  4-2

5-1.	Geographic Elements of Domains Used in Photochemical Modeling
PAGEREF _Toc265841330 \h  5-3

5-2.	Cement Kiln Emissions in 2005 Base and Estimated Future Year (2013)
in tons per year	  PAGEREF _Toc265841330 \h  5-3

6-1.	Human Health and Welfare Effects of Pollutants Affected	  PAGEREF
_Toc265841331 \h  6-7

6-2.	Summary of Monetized Benefits Estimates for Final Cement NESHAP and
NSPS in 2013 (millions of 2005$)	  PAGEREF _Toc265841332 \h  6-14

6-3.	Summary of Reductions in Health Incidences and Monetized Benefits
from PM2.5 Benefits for the Final Cement NESHAP and NSPS in 2013 (95th
percentile confidence interval)	  PAGEREF _Toc265841333 \h  6-15

6-4.	Comparison of Monetized Benefits and Emission Reductions for Final
Cement NESHAP and NSPS in 2013 (2005$)	  PAGEREF _Toc265841334 \h  6-17

6-5.	Summary of Monetized PM2.5 Energy Disbenefits for the Final
Portland Cement NSPS and NESHAP in 2013 (2005$)	  PAGEREF _Toc265841334
\h  6-17

6-6.	Social Cost of Carbon (SCC) Estimates (per tonne of CO2) for 2013
PAGEREF _Toc265841334 \h  6-17

6-7.	Monetized Disbenefits of CO2 Emission Increases in 2013	  PAGEREF
_Toc265841334 \h  6-17

6-8.	Summary of the Monetized Benefits, Social Costs, and Net Benefits
for the final Portland Cement NESHAP in 2013 (millions of 2005$)
PAGEREF _Toc265841335 \h  6-46

Introduction

The U.S. Environmental Protection Agency (EPA) is finalizing amendments
to the National Emission Standards for Hazardous Air Pollutants (NESHAP)
from the Portland cement manufacturing industry and New Source
Performance Standards (NSPS) for Portland cement plants. The final
amendments to the NESHAP add or revise, as applicable, emission limits
for mercury (Hg), total hydrocarbons (THC), and particulate matter (PM)
from kilns located at a major or an area sources, and hydrochloric acid
(HCl) from kilns and located at major sources. EPA is also adopting
separate standards for these pollutants that apply during startup,
shutdown, and operating modes. Finally, EPA is adopting performance
specifications for use of Hg continuous emission monitors (CEMS) and
updating recordkeeping and testing requirements. The final amendments to
the NSPS add or revise, as applicable, emission limits for particulate
matter (PM), opacity, nitrogen oxides (NOx), and sulfur dioxide (SO2)
for facilities that commence construction, modification, or
reconstruction after June 16, 2008. The final rule also includes
additional testing and monitoring requirements for affected sources. As
part of the regulatory process, EPA is required to develop a regulatory
impact analysis (RIA). The RIA includes an economic impact analysis
(EIA) and a small entity impacts analysis and documents the RIA methods
and results.

Executive Summary

The key results of the RIA are as follows:

Options Analyzed: EPA’s analysis focuses on the results of the final
NESHAP and NSPS. We also present additional information on different
combinations of the regulatory programs to help stakeholders better
understand the size and scope of each. These include

final NSPS only,

final NESHAP only, and

alternative: more stringent NSPS and final NESHAP.

The rest of this summary addresses the results of analyzing the final
NESHAP and NSPS.

Engineering Cost Analysis: EPA estimates that total annualized costs
with the final NESHAP and NSPS will be $466 million (2005$).

Market Analysis: The partial-equilibrium economic model suggests the
average national price for Portland cement could be 5% higher with the
NESHAP, or $4.50 per metric ton, while annual domestic production may
fall by 11%, or 10 million tons per year. Because of higher domestic
prices, imports rise by 10%, or 3 million metric tons per year.

Industry Analysis: Net industry operating profits fall by $241 million;
EPA also identified 10 domestic plants with negative operating profits
and significant utilization changes that could temporarily idle until
market demand conditions improve. The plants have unit compliance costs
close to $8 per ton of clinker capacity and $116 million total change in
operating profits. Since these plants account for approximately 8% of
domestic capacity, a decision to permanently shut down these plants
would reduce domestic supply and could lead to additional projected
market price increases and reductions in pollution control costs.

Employment Changes: EPA uses two methods for estimating employment
impacts.   A simplistic, limited assessment narrowly focused on output
changes in the Portland cement industry indicates that the final
rule’s gross impact on employment is 1,500 job losses.  However, this
approach inherently overstates job losses, as it is based on the
assumption that employment is proportional to output, and because it
ignores offsetting general equilibrium and other effects as discussed in
detail in Chapter 3.  A more sophisticated analytical approach that
includes other types of employment effects estimates changes in net
employment could range from a loss of 600 to a net gain of 1,300 jobs.

Social Cost Analysis: The estimated social cost is $926 to $950 million
(2005$). The range represents the estimated difference in surplus if ten
facilities with low estimated post regulation capacity utilization
choose to idle or close rather than operate at a low capacity
utilization. The social cost estimates are significantly higher than the
engineering analysis estimates, which estimated annualized costs of $466
 million. This is a direct consequence of EPA’s assumptions about
existing market structure discussed extensively in previous cement
industry rulemakings and Section 2, Appendix A, and Appendix B of this
RIA. Under baseline conditions without regulation, the existing domestic
cement plants are assumed to choose a production level that is less than
the level produced under perfect competition. As a result, a preexisting
market distortion exists in the markets covered by the final rule (i.e.,
the observed baseline market price is higher than the [unobserved]
market price that a model of perfect competition would predict). The
imposition of additional regulatory costs tends to widen the gap between
price and marginal cost in these markets and contributes to additional
social costs.

Energy Impacts: EPA concludes that the rule when implemented will not
have a significant adverse effect on the supply, distribution, or use of
energy. The cement industry accounts for less than 0.4% of the U.S.
total energy use. EPA estimates the additional add-on controls may
increase national electrical demand by 780 million kWh per year and the
natural gas use to be 1.0 million MMBTU per year for existing kilns. For
new kilns, assuming that of the 16 new kilns to start up by 2013  all
16will add alkaline scrubbers and ACI systems, the electrical demand is
estimated to be 199 million kWh per year. This is less than 0.1% of AEO
2010 forecasts of total electricity and natural gas consumption.

Small Business Analysis: Only 4 of the over 40 cement parent companies
are small entities. EPA performed a screening analysis for impacts on
the 4 small entities by comparing compliance costs to average company
revenues. EPA’s analysis found that the ratio of compliance cost to
company revenue falls below 1% for two of the four small entities
(includes a Tribal government). Two small entities would have an
annualized cost of between 1% and 3% of sales. No small businesses would
have an annualized cost greater than 3% of sales.

Benefits Analysis: In the year of full implementation (2013), EPA
estimates that the total monetized benefits of the final NESHAP and NSPS
are $7.4 billion to $18 billion and $6.7 billion to $16 billion, at 3%
and 7% discount rates, respectively (Table 1-1). All estimates are in
2005 dollars for the year 2013. Using alternate relationships between
PM2.5 and premature mortality supplied by experts, higher and lower
benefits estimates are plausible, but most of the expert-based estimates
fall between these estimates. Due to data, methodology, and resource
limitations, the benefits from reducing other air pollutants have not
been monetized in this analysis, including reducing 4,400 tons of NOx,
5,200 tons of organic hazardous air pollutants (HAPs), 5,900 tons of
HCl, and 16,400 pounds of Hg each year. In addition, ecosystem benefits
and visibility benefits have not been monetized in this analysis.  These
estimates include the energy disbenefits associated with increased
electricity usage by the control devices.

Net Benefits: In the year of full implementation (2013), EPA estimates
the net benefits of the final NESHAP and NSPS are $6.5 billion to $17
billion and $5.8 billion to $16 billion, at 3% and 7% discount rates,
respectively. All estimates are in 2005 dollars for the year 2013.

Organization of this Report

The remainder of this report supports and details the methodology and
the results of the EIA:

Section 2 presents a profile of the affected industry.

Section 3 describes the economic impact analysis and energy impacts.

Section 4 describes the small business impact analysis.

Section 5 presents the air quality modeling of emission reductions.

Section 6 presents the benefits analysis.

Appendix A provides an overview of the economic impact model.

Appendix B discusses the model of the cement plant’s production
decision.

Appendix C presents the social cost methodology.

Table 1-1.	Summary of the Monetized Benefits, Social Costs, and Net
Benefits for the Final Portland Cement NESHAP in 2013 (millions of
2005$)a

Final NESHAP and NSPS

	3% Discount Rate	7% Discount Rate

Total Monetized Benefitsb	$7,400	to	$18,000	$6,700	to	$16,000

Total Social Costsc	   $926           to                 $950	$926
    to                 $950

Net Benefits	$6,500	to	$17,000	$5,800	to	$16,000

Nonmonetized Benefitsd	4,400 tons of NOx (includes energy disbenefits)

	5,200 tons of organic HAPs

	5,900 tons of HCl

	16,400 pounds of mercury

	Health effects from HAPs, NO2, and SO2 exposure

	Ecosystem effects

	Visibility impairment

Final NSPS only

 	3% Discount Rate	7% Discount Rate

Total Monetized Benefitsb	$510	to	$1,300	$460	to	$1,100

Total Social Costsc	$72	$72

Net Benefits	$440	to	$1,200	$390	to	$1,000

Nonmonetized Benefitsd	6,600 tons of NOx

	520 tons of HCl

	Health effects from HAPs, NO2, and SO2 exposure

	Ecosystem effects

	Visibility impairment

Final NESHAP only

	3% Discount Rate	7% Discount Rate

Total Monetized Benefitsb	$7,400	to	$18,000	$6,700	to	$16,000

Total Social Costsc	   $904           to                 $930	   $904
       to                 $930

Net Benefits	$6,500	to	$17,000	$5,800	to	$16,000

Nonmonetized Benefitsd	5,200 tons of organic HAPs

	5,900 tons of HCl

	16,400 pounds of mercury

	Health effects from HAPs, SO2 exposure

	Ecosystem effects

	Visibility impairment

Alternative: More Stringent NSPS and Final NESHAP

	3% Discount Rate	7% Discount Rate

Total Monetized Benefitsb	$7,400	to	$18,000	$6,700	to	$16,000

Total Social Costsc	   $955           to                 $979	   $955
       to                 $979

Net Benefits	$6,500	to	$17,000	$5,700	to	$15,000

Nonmonetized Benefitsd	7,800 tons of NOx (includes energy disbenefits)

	5,200 tons of organic HAPs

	5,900 tons of HCl

	16,400 pounds of mercury

	Health effects from HAPs, NO2, and SO2 exposure

	Ecosystem effects

	Visibility impairment

a	All estimates are for the implementation year (2013) and are rounded
to two significant figures.

b	The total monetized benefits reflect the human health benefits
associated with reducing exposure to PM2.5 through reductions of
directly emitted PM2.5 and PM2.5 precursors such as SO2. It is important
to note that the monetized benefits include many but not all health
effects associated with PM2.5 exposure. Benefits are shown as a range
from Pope et al. (2002) to Laden et al. (2006). These models assume that
all fine particles, regardless of their chemical composition, are
equally potent in causing premature mortality because there is no clear
scientific evidence that would support the development of differential
effects estimates by particle type. The total monetized benefits include
the energy disbenefits.

c	The methodology used to estimate social costs for 1 year in the
multimarket model using surplus changes results in the same social costs
for both discount rates.

d	Due to data, methodology, and resource limitations, we were unable to
monetize the benefits associated with these categories of benefits.

Industry Profile

Hydraulic cement (primarily Portland cement) is a key component of an
important construction material: concrete. Concrete is used in a wide
variety of applications (e.g., residential and commercial buildings,
public works projects), and cement demand is influenced by national and
regional trends in these sectors. Recent data for 2007 show that the
U.S. cement industry produced over 90 million metric tons of Portland
cement (Department of Interior [DOI], U.S. Geological Survey [USGS],
2008b  XE "U.S. Geological Survey [USGS], 2008b"  ). The value of total
U.S. sales, including imported cement, was about $11.8 billion, with an
average value of approximately $100 per metric ton. The vast majority of
cement sales went to ready-mixed concrete producers and concrete product
manufacturers (88%). Since 2003, the United States has relied on cement
imports to meet approximately 20% to 23% of its consumption needs.
However, this share dropped to approximately 17% in 2007 as overall
construction demand for cement fell (DOI, USGS, 2008b  XE "DOI, USGS,
2008b"  ).

The remainder of this section provides an introduction to the Portland
cement industry. The purpose is to give the reader a general
understanding of the technical and economic aspects of the industry that
must be addressed in the economic impact analysis. Section 2.1 provides
an overview of the production processes and costs data. Section 2.2
discusses the uses, consumers, and substitutes for cement. Section 2.3
summarizes the organization of the Portland cement industry. The
industry profile concludes with a discussion of historical market data
and the current industry outlook.

The Supply Side

Production Process

As shown in Figure 2-1, the manufacturing process of an integrated
cement plant includes

quarrying and crushing the raw materials,

grinding the carefully proportioned materials to a high degree of
fineness,

firing the raw materials mixture in a rotary kiln to produce clinker,
and

grinding the resulting clinker to a fine powder and mixing with gypsum
to produce cement.

Figure 2-1.	Simplified Flow Sheet of Clinker and Cement Manufacture

There are two processes for manufacturing cement: the wet process and
the dry process. In the wet process, water is added to the raw materials
during the blending process and before feeding the mixture into the
rotary kiln. In contrast, the dry process feeds the blended materials
directly into the rotary kiln in a dry state. Newer dry process plants
also use preheater and precalciner technologies that partially heat and
calcine the blended raw materials before they enter the rotary kiln.
These technologies can increase the overall energy efficiency of the
cement plant and reduce production costs.

The fuel efficiency differences between the wet and dry processes have
led to a substantial decline in clinker capacity provided by the wet
process over the last 3 decades. Historical data show capacity shares
falling from 52% in 1980 to approximately 22% in 2000 (Van Oss and
Padovani, 2002  XE “Van Oss and Padovani, 2002”  ). Data also show
that the number of wet process plants fell from 32 in 2000 to 23 in 2005
(DOI, USGS, 2007  XE "DOI, USGS, 2007"  ).

Types of Portland Cement

Portland cement manufacturers produce a variety of types of cement in
the United States designed to meet different requirements. The American
Society for Testing Materials (ASTM) specification C-150 provides for
eight types of Portland cement: five standard types (I, II, III, IV, V)
and three additional types that include air-entraining properties (IA,
IIA, IIIA) (PCA, 2008a  XE “PCA, 2008a”  ). We describe these below.

Types I and IA: These types are the usual product used in general
concrete construction, most commonly known as gray cement because of its
color.

Types II and IIA: These types are intended for use when moderate heat of
hydration is required or for general concrete construction exposed to
moderate sulfate action.

Type III and IIIA: These types are made from raw materials with a
lime-to-silica ratio higher than that of Type I cement and are ground
finer than Type I cements. They contain a higher proportion of
tricalcium silicate than regular Portland cements.

Type IV: This type contains a lower percentage of tricalcium silicate
and tricalcium aluminate than Type I, thus lowering the heat evolution.
Consequently, the percentage of tetracalcium aluminoferrite is
increased. Type IV cements are produced to attain a low heat of
hydration.

Type V: This type resists sulfates better than the other four types.

As shown in Table 2-1, the vast majority of Portland cement shipments in
2005 were Types I and II grey cement. However, Type V
(sulfate-resisting) is a growing market (DOI, USGS, 2007a  XE "DOI,
USGS, 2007a"  ); since 2000, Type V cement has increased its share of
shipments from 4% to 15%. Shipment shares for other types of cement
remained constant during this period.

Production Costs

Portland cement is produced using a combination of variable inputs such
as raw materials, labor, electricity, and fuel. U.S. Census data for the
cement industry (North American Industry Classification System [NAICS]
32731: cement manufacturing) provides an initial overview of aggregated
industry expenditures on these inputs (Department of Commerce [DOC],
Bureau of the Census, 2010  XE “Bureau of the Census, 2008”  ). In
2007, the total value of shipments was $10.6 billion, and the industry
spent approximately $1.7 billion on materials, parts, and packaging, or
16% of the value of shipments. Total compensation for all employees
(includes payroll and fringe benefits)

Table 2-1.	Portland Cement Shipped from Plants in the United States to
Domestic Customers, by Typea, b

Type	2000	Share	2005	Share

General use and moderate heat (Types I and II) (gray)c	90,644	88%	93,900
77%

High early strength (Type III)	3,815	4%	3,960	3%

Sulfate resisting (Type V)c	4,453	4%	18,100	15%

Whited	894	1%	1,190	1%

Blended	1,296	1%	3,160	3%

Expansive and regulated fast setting	60	0%	6	0%

Othere	1,786	2%	1,997	2%

Totalf	102,947	100%	122,000	100%

a	Includes imported cement.

b	Data are rounded to no more than three significant digits; may not add
to totals shown.

c	Cements classified as Type II/V hybrids are now commonly reported as
Type V.

d	Mostly Types I and II but may include Types III through V and block
varieties.

e	Includes block, oil well, low heat (Type IV), waterproof, and other
Portland cements.

f	Data are based on an annual survey of plants and importers.

Sources:	U.S. Department of the Interior, U.S. Geological Survey. 2007a
XE "U.S. Department of the Interior, U.S. Geological Survey. 2007a"  .
2005 Minerals Yearbook, Cement. Washington, DC: U.S. Department of the
Interior. Table 15.

U.S. Department of the Interior, U.S. Geological Survey. 2002  XE
“U.S. Department of the Interior, U.S. Geological Survey. 2002”  .
2001 Minerals Yearbook, Cement. Washington, DC: U.S. Department of the
Interior. Table 15.

amounted to $1.4 billion (13%). Fuels and electricity expenditures were
approximately $1.7 billion (16%).

Raw Material Costs

According to the USGS, approximately 159.7 million tons of raw materials
were required to produce approximately 95.5 million tons of cement in
2005 or 1.67 tons of raw materials per ton of cement. Table 2-2
summarizes the amount of raw material inputs used per ton of cement
produced in the United States between 2000 and 2005. As the data show,
the amount of raw materials required to produce one ton of cement has
remained essentially constant during this 6-year period.

Table 2-2.	Raw Material Input Ratios for the U.S. Cement Industry: 2000
to 2005

 	2000	2001	2002	2003	2004	2005

Raw material input (103 metric tons) 	144,949	147,300	153,100	150,500
158,200	159,700

Cement production (103 metric tons)	85,178	86,000	86,817	89,592	94,014
95,488

Metric tons of raw material input per ton of cement	1.70	1.71	1.76	1.68
1.68	1.67

Sources:	U.S. Department of the Interior, U.S. Geological Survey.
2002–2007a. 2001–2005 Minerals Yearbook, Cement. Table 6.  XE
“U.S. Department of the Interior, U.S. Geological Survey.
2002–2007a. 2001–2005 Minerals Yearbook, Cement. Table 6.”
Washington, DC: U.S. Department of the Interior.

U.S. Department of the Interior, U.S. Geological Survey. 2002–2007a.
2001–2005 Minerals Yearbook, Cement. Table 3.  XE “U.S. Department
of the Interior, U.S. Geological Survey. 2002–2007a. 2001–2005
Minerals Yearbook, Cement. Table 3.”   Washington, DC: U.S. Department
of the Interior.

The price of these raw materials varies across regions. Table 2-3 lists
the average price of raw materials per metric ton by state. In 2005, the
prices of raw materials were highest in Hawaii where they sold for an
average of $13.34 per metric ton. The prices of raw materials were
lowest in Michigan, where they sold for an average of $3.89 per metric
ton.

Labor Costs

In 2005, the Portland Cement Association (PCA) reported labor
productivity measures (in terms of metric tons of cement per employee
hour) for 2000 to 2005 in its U.S. and Canadian Labor-Energy Input
Survey. Using these data, we computed a measure of labor hour
requirements to produce cement (see Table 2-4). As these data show, wet
process plants are typically more labor intensive, requiring
approximately 45% more labor hours to produce a metric ton of cement
than dry process plants.

In addition, labor productivity has been improving more quickly in dry
process plants than in those using a wet manufacturing process. Between
2000 and 2005, labor requirements decreased by 15% in dry process
plants, while in wet process plants labor requirements remained
constant. As a result, the wet process labor costs relative to dry
process plants labor costs have risen in recent years (Figure 2-2).

Table 2-3.	Raw Material Costs by Market and State: 2005

State(s)	Price of Raw Materials

($/metric ton)a	State(s)	Price of Raw Materials

($/metric ton)a

AK	6.60	MT	$4.76

AL	6.57	NC	$8.59

AR	$6.29 	ND	$4.45

AZ	$5.75 	NE	$7.10

CA	$8.37 	NH	$8.02

CO	$6.85 	NJ	$7.04

CT	$9.19 	NM	$6.67

DE	$6.89 	NV	$7.17

FL	$8.67 	NY	$8.44

GA	$7.63 	OH	$5.82

HI	$13.34 	OK	$5.67

IA	$7.27 	OR	$6.01

ID	$5.37 	PA	$6.67

IL	$7.16 	RI	$7.74

IN	$5.40 	SC	$7.61

KS	$7.20 	SD	$4.60

KY	$7.24 	TN	$7.55

LA	$8.18 	TX	$6.15

MA	$9.19 	UT	$5.58

MD	$8.28 	VA	$9.03

ME	$6.85 	VT	$6.75

MI	$3.89 	WA	$6.92

MN	$8.30 	WI	$5.83

MO	$7.37 	WV	$6.86

MS	$11.90 	WY	$5.68

Source:	U.S. Department of the Interior, U.S. Geological Survey. 2007b.
XE "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.

Table 2-4.	Labor Productivity Measures for the U.S. Cement Industry by
Process Type: 2000 to 2005 (employee hours per metric ton)

Year	2000	2001	2002	2003	2004	2005

All plants	0.394	0.388	0.360	0.347	0.338	0.338

Wet process	0.469	0.457	0.450	0.465	0.452	0.463

Dry process	0.376	0.375	0.342	0.328	0.318	0.318

Source:	Portland Cement Association. December 2005  XE “Portland
Cement Association. December 2005”  . U.S. and Canadian Labor-Energy
Input Survey 2005. Skokie, IL: PCA’s Economic Research Department.

Figure 2-2.	Labor Costs per Metric Ton of Cement ($2005)

Sources:	Portland Cement Association. December 2005  XE “Portland
Cement Association. December 2005”  . U.S. and Canadian Labor-Energy
Input Survey 2005. Skokie, IL: PCA’s Economic Research Department.

U.S. Department of Labor, Bureau of Labor Statistics (BLS). 2007a  XE
"U.S. Department of Labor, Bureau of Labor Statistics (BLS). 2007a"  .
“Current Employment Statistics (National): Customizable Data Tables”
Available at <http://www.bls.gov/ces/>. As obtained on March 14, 2008.

U.S. Department of Labor, Bureau of Labor Statistics (BLS). 2008  XE
“Department of Labor, Bureau of Labor Statistics (BLS). 2008”  .
“Consumer Price Index All Items – U.S. City Average Data:
Customizable Data Tables.” Available at <http://www.bls.gov/cpi/>. As
obtained on March 14, 2008.

Energy Costs

Figure 2-3 provides a detailed breakdown of U.S. energy consumption in
2005. As this figure shows, the vast majority of energy in U.S. cement
plants is derived from coal and coke (75%). The remaining 25% of energy
consumption is derived from electricity, waste, natural gas, and
petroleum products.

PCA also reported energy consumption data by type of U.S. cement plant
(in terms of millions of BTUs per metric ton of cement) (see Table 2-5).
As these data show, wet process plants are typically more energy
intensive, consuming approximately 44% more energy per ton of cement
than dry process plants. In addition, the trends in energy consumption
continue to show that dry plants have become more energy efficient than
wet process plants. Between 2000 and 2005, energy consumption per ton of
cement in dry process plants decreased by 5%; in contrast, wet process
plants’ energy consumption increased slightly during this period.

Figure 2-3.	Distribution of Energy Consumption

Source:	Portland Cement Association. December 2005.  XE “Portland
Cement Association. December 2005.”   U.S. and Canadian Labor-Energy
Input Survey 2005. Skokie, IL: PCA’s Economic Research Department.

Table 2-5.	Energy Consumption by Type of U.S. Cement Plant (million BTU
per metric ton)

Year	2000	2001	2002	2003	2004	2005

All plants	4.982	4.93	4.858	4.762	4.755	4.699

Wet process	6.25	6.442	6.676	6.647	6.807	6.387

Dry process	4.673	4.655	4.498	4.433	4.407	4.433

Source:	Portland Cement Association. December 2005  XE “Portland
Cement Association. December 2005”  . U.S. and Canadian Labor-Energy
Input Survey 2005. Skokie, IL: PCA’s Economic Research Department.

The Demand Side

The demand for Portland cement is considered a “derived” demand
because it depends on the construction demands for its end
product—concrete. A recent study by the U.S. International Trade
Commission suggests that 0.192 metric tons of grey Portland cement were
used per $1,000 of construction in 1998 (USITC, 2006  XE “USITC,
2006”  ). Given cement prices at this time (approximately $75 per
metric ton), Portland cement costs represented only a small share of the
total value of construction expenditures (less than 2%).

Concrete is used in a wide variety of construction applications,
including residential and commercial buildings, and public works
projects such as the national highway system. As shown in Figure 2-4,
ready-mixed concrete producers have historically accounted for over half
of the Portland cement consumption. Although government and
miscellaneous expenditures saw substantial increases in the early 1990s,
their consumption share returned to pre-1990s levels after 1996. The
latest USGS use data show that ready-mixed concrete producers accounted
for

Figure 2-4.	End Uses of Cement: 1975 to 2003

Source:	Kelly, T. and G. Matos. 2007a.  XE “Kelly, T. and G. Matos.
2007a.”   “Historical Statistics for Mineral and Material
Commodities in the United States: Cement End Use Statistics.” U.S.
Geological Survey Data Series 140, Version 1.2. Available at   HYPERLINK
"http://minerals.usgs.gov/ds/2005/140/"
http://minerals.usgs.gov/ds/2005/140/ .

74% of cement sales in 2005, followed by concrete product manufacturers
(14%), contractors (6%), and other (6%) (Kelly and Matos, 2007a  XE
"Kelly and Matos, 2007a"  ).

Cement competes with other construction materials such as steel,
asphalt, and lumber. Lumber is the primary substitute in the residential
construction market, while steel is the primary substitute in commercial
applications. Asphalt is a key substitute in transportation projects
such as road and parking lot surfacing. However, concrete has advantages
over these substitutes because it tends to be available locally and has
lower long-term maintenance costs (Van Oss and Padovani, 2002  XE “Van
Oss and Padovani, 2002”  ).

The PCA regularly reports price trends for these competing building
materials (PCA, 2008b  XE “PCA, 2008b”  ). As shown in Figure 2-5,
steel and asphalt have risen sharply relative to cement since 2003 while
lumber has declined.

Figure 2-5.	Producer Price Indices for Competitive Building Materials:
2003 to 2008

Source:	Portland Cement Association. 2008b  XE “Portland Cement
Association. 2008b”  . “Market Research: Producer Price
Indices—Competitive Building Materials.” Available at <  HYPERLINK
"http://www.cement.org/market/"  http://www.cement.org/market/ >.

Industry Organization

Market Structure

A review and description of market characteristics (i.e., degree of
concentration, entry barriers, and product differentiation) can enhance
our understanding of how U.S. cement markets operate. These
characteristics provide indicators of a firm’s ability to influence
market prices by varying the quantity of cement it sells. For example,
in markets with large numbers of sellers and identical products, firms
are unlikely to be able to influence market prices via their production
decisions (i.e., they are “price takers”). However, in markets with
few firms, significant barriers to entry (e.g., licenses, legal
restrictions, or high fixed costs), or products that are similar but can
be differentiated, the firm may have some degree of market power (i.e.,
set or significantly influence market prices).

Cement sales are often concentrated locally among a small number of
firms for two reasons: high transportation costs and production
economies of scale. Transportation costs significantly influence where
cement is ultimately sold; high transportation costs relative to unit
value provide incentives to produce and sell cement locally in regional
markets (USITC, 2006  XE “USITC, 2006”  ). To support this claim,
the empirical literature has typically pointed to Census of
Transportation data showing over 80% of cement shipments were made
within a 200-mile radius (Jans and Rosenbaum, 1997  XE “Jans and
Rosenbaum, 1997”  ) and reported evidence of high transportation costs
per dollar of product value from case studies (Ryan, 2006  XE “Ryan,
2006”  ). The cement industry is also very capital intensive and entry
requires substantial investments. In additional, large plants are
typically more economical because they can produce cement at lower unit
costs; this reduces entry incentives for small-sized cement plants.
Using recent data for planned capacity expansions between 2008 and 2012,
the PCA reports these expansions will cost $5.9 billion and add 25
million metric tons (PCA, 2007  XE “PCA, 2007”  ), or $240 per
metric ton, of new capacity.

For a given construction application, consumers are likely to view
cement produced by different firms as very good substitutes. American
Society for Testing and Materials (ASTM) specifications tend to ensure
uniform quality, and recent industry reviews (USITC, 2006  XE “USITC,
2006”  ) suggest that there is little or no brand loyalty that allows
firms to differentiate their products.

Manufacturing Plants

During 2005, 107 cement manufacturing plants with 186 cement kilns were
operating in the United States. This section describes the location,
age, production capacity, and employment of these manufacturing
facilities. Section 2.3.2 concludes with a discussion of future trends.
Section 2.3.3 provides a detailed discussion of the characteristics of
the firms owning these facilities.

Location

Table 2-6 summarizes the geographic location of cement kilns in the
United States and clinker capacity. The top five states in order of
clinker capacity are California, Texas, Pennsylvania, Florida, and
Alabama. Together these states account for 75 (40%) of the kilns in the
United States and 41 million metric tons (44%) of clinker capacity.
Figure 2-6 provides a graphical depiction of the number of kilns
distributed by state.

Fourteen states (Alaska, Hawaii, Connecticut, Louisiana, New Hampshire,
North Dakota, Wisconsin, Delaware, Massachusetts, New Jersey, Rhode
Island, Minnesota, North Carolina, and Vermont) and the District of
Columbia had no clinker-producing facilities in 2005.

Table 2-6.	Number of Kilns and Clinker Capacity by State: 2005

 	No. Kilns	Clinker Capacity (103 metric tons per year)

AK	0

	AL	5	5,375

AR	3	831

AZ	8	2,809

CA	20	12,392

CO	2	2,117

CT	0

	DE	0

	FL	7	5,489

GA	2	1,020

HI	0

	IA	4	2,672

ID	2	260

IL	8	2,770

IN	8	3,191

KS	9	2,835

KY	1	1,365

LA	0

	MA	0

	MD	4	2,538

ME	1	392

MI	8	4,243

MN	0

	MO	6	5,169

MS	1	419

MT	2	573

NC	0

	ND

NE	2	845

NH	0

	NJ	0

	NM	2	432

NV	2	452

NY	4	2,886

OH	3	1,115

OK	7	1,869

OR	1	816

(continued)

Table 2-6.	Number of Kilns and Clinker Capacity by State: 2005
(continued)

 	No. Kilns	Clinker Capacity (103 metric tons per year)

PA	21	6,414

RI	0

	SC	6	3,480

SD	3	851

TN	2	1,438

TX	22	11,688

UT	2	1,514

VA	1	1,120

VT	0

	WA	2	1,100

WI	0

	WV	3	708

WY	2	597

Total	186	93,785

Source:	Portland Cement Association (PCA). 2004  XE “Portland Cement
Association (PCA). 2004”  . U.S. and Canadian Portland Cement
Industry: Plant Information Summary. Skokie, IL: PCA’s Economic
Research Department.

Figure 2-6.	Distribution of Cement Kilns in the United States

Source:	Portland Cement Association (PCA). December 2004  XE "Portland
Cement Association (PCA). December 2004"  . U.S. and Canadian Portland
Cement Industry: Plant Information Summary. Skokie, IL: Portland Cement
Association Economic Research Department.

Age

In 2005, 72% (134) of all kilns in the United States used the dry
manufacturing process, and it accounted for 83% (78 million metric tons)
of national clinker capacity. The growing prevalence of the dry process
among cement manufacturers is part of a long-term trend. As the data in
Table 2-7 indicate, no new wet clinker capacity has been added within
the past 30 years.

Table 2-7.	Number of Kilns and Clinker Capacity by Age and Process Type

 	No. Kilns	Clinker Capacity (103 metric tons per year)	Average Annual
Capacity per Kiln

Total

0–10	26	28,144	1,082.5

11–15	3	2,176	725.3

16–20	5	3,345	669.0

21–25	16	14,982	936.4

26–30	18	11,843	657.9

31–35	16	5,786	361.6

36–40	21	9,285	442.1

41–45	29	8,971	309.3

46–50	32	6,564	205.1

51–55	6	991	165.2

56–60	6	800	133.3

60+	8	898	112.3

Total	186	93,785	504.2

Dry Process

0–10	26	28,144	1,082.5

11–15	3	2,176	725.3

16–20	5	3,345	669.0

21–25	16	14,982	936.4

26–30	18	11,843	657.9

31–35	10	3,962	396.2

36–40	12	5,498	458.2

41–45	14	3,800	271.4

46–50	16	2,651	165.7

51–55	4	682	170.5

56–60	6	800	133.3

60+	4	328	82.0

Total	134	78,211	583.7

Wet Process

0–10	0

11–15	0

16–20	0

21–25	0

26–30	0

31–35	6	1,824	304.0

36–40	9	3,787	420.8

41–45	15	5,171	344.7

(continued)

Table 2-7.	Number of Kilns and Clinker Capacity by Age and Process Type
(continued)

 	No. Kilns	Clinker Capacity (103 metric tons per year)	Average Annual
Capacity per Kiln

Wet Process (cont.)

46–50	16	3,913	244.6

51–55	2	309	154.5

56–60	0

60+	4	570	142.5

Total	52	15,574	299.5

Source:	Portland Cement Association (PCA). 2004  XE “Portland Cement
Association (PCA). 2004”  . U.S. and Canadian Portland Cement
Industry: Plant Information Summary. Skokie, IL: PCA’s Economic
Research Department.

All 68 kilns that have become operational within the past 30 years use
the dry manufacturing process. These new kilns account for 64% (60
million metric tons) of national clinker capacity.

Production Capacity and Utilization

Between 2000 and 2005, apparent annual clinker capacity grew
approximately 17%, while clinker production grew by approximately 14%
(Table 2-8). Because capacity tends to grow more rapidly than
production, total capacity utilization decreased slightly in this period
from 87.5% in 2000 to 85.4% in 2005.

Table 2-8.	Clinker Capacity, Production, and Capacity Utilization in the
United States: 2000 to 2005

	2000	2001	2002	2003	2004	2005

Apparent annual capacity (103 metric tons)	89,264	100,360	101,000
102,000	105,000	104,000

Production (103 metric tons)	78,138	79,979	82,959	83,315	88,190	88,783

Capacity utilization (%)	87.5%	79.7%	82.1%	81.7%	84.0%	85.4%

Source:	U.S. Department of the Interior, U.S. Geological Survey.
2000–2005. Minerals Yearbook, Cement. Table 5.  XE “U.S. Department
of the Interior, U.S. Geological Survey. 2000–2005. Minerals Yearbook,
Cement. Table 5.”   Washington, DC: U.S. Department of the Interior.
Available at <http://minerals.usgs.gov/minerals/pubs/

commodity/cement/>. As obtained on March 14, 2008.

Much of the vast majority of the growth in clinker capacity came in 2001
when existing Portland cement plants completed major capacity upgrade
projects, resulting in a 12% increase in clinker capacity over the
previous year (USGS, 2002  XE “USGS, 2002”  ). As a result, capacity
utilization fell to 79.7% that year. After 2001, clinker capacity grew
an average of 1% each year, while production grew an average of 2%. As a
result, capacity utilization has risen slowly since 2001. However,
throughout these movements in clinker capacity and production, capacity
utilization tended to remain between 80% and 85%.

Capacity utilization often varies by geographic region as a result of
fluctuations in regional construction activity. For example, 2005 data
show that Idaho, Montana, and Nevada shared a capacity utilization rate
of 95.5%—well above the national average. In contrast, South Carolina
used only 64.5% of its clinker capacity. Table 2-9 provides a complete
listing of capacity utilization rates by state in 2005.

Employment

Each year, the Annual Survey of Manufactures (ASM) collects employment,
payroll, sales, and other data for all manufacturing establishments.
Table 2-10 summarizes the employment data collected by the ASM for the
cement manufacturing industry (NAICS 327310) from 2000 to 2005. As these
data indicate, total employment fell approximately 2% over this 6-year
period, from approximately 17,000 employees in 2000 to 16,900 in 2005.

Trends

As previously discussed, clinker capacity has been increasing at a
slower pace since 2001. However, according to the PCA, the cement
industry has announced that it will increase clinker capacity by nearly
25 million metric tons between 2007 and 2012. This represents a 27%
increase over U.S. 2006 clinker capacity and amounts to a $5.9 billion
investment (PCA, 2007  XE “PCA, 2007”  ).

In addition to these expected capacity expansions, likely changes in
U.S. specifications allowing the use of limestone in Portland cement
could also increase production capacity. According to the PCA, domestic
cement supply could increase by as much as 2 million additional tons by
2012. Increases in EPA production variances could also add another 1.1
million metric tons of domestic supply (PCA, 2007  XE “PCA, 2007”
).

Firm Characteristics

EPA has reviewed industry information and publicly available sales and
employment databases to identify the chain of ownership by accounting
for subsidiaries, divisions, and joint ventures to appropriately group
companies by size. Table 2-11 provides sales and employment data for
27 ultimate parent companies operating Portland cement manufacturing
plants in 2005.

Table 2-9.	Capacity Utilization Rates by State: 2005

State	USGS Geographic Area	Utilization Rate (percent)

AL	Alabama	86.7

AR	Arkansas and Oklahoma	90.9

AZ	Arizona and New Mexico	87

CA	California, northern and southern	88.8

CO	Colorado and Wyoming	79.5

FL	Florida	85.9

GA	Georgia, Virginia, West Virginia	78.4

IA	Iowa, Nebraska, South Dakota	85.5

ID	Idaho, Montana, Nevada, Utah	95.5

IL	Illinois	91.4

IN	Indiana	86.8

KS	Kansas	89.1

KY	Kentucky, Mississippi, Tennessee	87.4

MD	Maryland	89.1

ME	Maine and New York	83.6

MI	Michigan	85.5

MO	Missouri	90.3

MS	Kentucky, Mississippi, Tennessee	87.4

MT	Idaho, Montana, Nevada, Utah	95.5

NE	Iowa, Nebraska, South Dakota	85.5

NM	Arizona and New Mexico	87

NV	Idaho, Montana, Nevada, Utah	95.5

NY	Maine and New York	83.6

OH	Ohio	84.7

OK	Arkansas and Oklahoma	90.9

OR	Oregon and Washington	83.3

PA	Pennsylvania, eastern and western	83.7

SC	South Carolina	64.5

Source:	U.S. Department of the Interior, U.S. Geological Survey. 2007b
XE "U.S. Department of the Interior, U.S. Geological Survey. 2007b"  .
2005 Minerals Yearbook, Cement. Table 5. Washington, DC: U.S.
Department of the Interior.

Table 2-10.	Cement Manufacturing Employment (NAICS 327310): 2000 to 2005

Year	Number of Employees

2000	17,175

2001	17,220

2002	17,660

2003	17,352

2004	16,883

2005	16,877

Sources:	U.S. Department of Commerce, Bureau of the Census. 2006.  XE
“U.S. Department of Commerce, Bureau of the Census. 2006.”   2005
Annual Survey of Manufactures. M05(AS)-1. Washington, DC: Government
Printing Office. Available at
<http://www.census.gov/prod/2003pubs/m01as-1.pdf>. As obtained on March
14, 2008.

	U.S. Department of Commerce, Bureau of the Census. 2003  XE “U.S.
Department of Commerce, Bureau of the Census. 2003”  . 2001 Annual
Survey of Manufactures. M05(AS)-1. Washington, DC: Government Printing
Office. Available at <http://www.census.gov/prod/2003pubs/m01as-1.pdf>.
As obtained on March 14, 2008.

Distribution of Small and Large Companies

Firms are grouped into small and large categories using Small Business
Administration (SBA) general size standard definitions for NAICS codes.
These size standards are presented either by number of employees or by
annual receipt levels, depending on the NAICS code. The manufacture of
Portland cement is covered by NAICS code 327310 for cement
manufacturing. Thus, according to SBA size standards, firms owning
Portland cement manufacturing plants are categorized as small if the
total number of employees at the firm is less than 750; otherwise, the
firm is classified as large. As shown in Table 2-11, potentially
affected firms range in size from 160 to 71,000 employees. A total of 4
firms, or 15%, are categorized as small, while the remaining 23 firms,
or 75%, are large.

Capacity Share

As shown in Table 2-11, the leading companies in terms of capacity at
the end of 2005 were Holcim (U.S.) Inc.; CEMEX, Inc.; Lafarge North
America, Inc.; Buzzi Unicem USA, Inc.; HeidelbergCement AG (owner of
Lehigh Cement Co.); Ash Grove Cement Co.; Texas Industries, Inc.;
Italcementi S.p.A.; Taiheiyo Cement Corporation; Titan Cement; and
VICAT. The top 5 had about 57% of total U.S. clinker capacity, and the
top 10 accounted for 83% of total capacity. Small companies accounted
for less than 5% of clinker capacity.

Table 2-11.	Ultimate Parent Company Summary Data: 2005

Ultimate Parent Name	Annual Sales ($106)	Employ-ment	Type	Small Business
Plants	Kilns	Clinker Capacity (103 metric tons per year)	Capacity Share

Holcim, Inc	$14,034 	59,901	Public	No	14	17	13,089	14.0%

CEMEX, S.A. de C.V.	$18,290 	26,679	Public	No	13	21	12,447	13.3%

Lafarge S.A.	$22,325 	71,000	Public	No	13	23	12,281	13.1%

BUZZI UNICEM SpA	$3,495 	11,815	Private	No	10	19	8,129	8.7%

HeidelbergCement AG	$12,182 	45,958	Public	No	10	13	7,786	8.3%

Ash Grove Cement Company	$1,190 	2,600	Private	No	9	15	6,687	7.1%

Texas Industries, Inc.	$944 	2,680	Public	No	4	15	5,075	5.4%

Italcementi S.p.A.	$5,921 	20,313	Public	No	6	16	4,442	4.7%

Taiheiyo Cement Corporation 	$7,710 	2,061	Private	No	3	7	3,375	3.6%

Titan Cement	$1,589 	1,834	Public	No	2	2	2,612	2.8%

VICAT	$2,137 	6,015	Public	No	2	2	1,933	2.1%

Eagle Materials	$922 	1,600	Public	No	3	5	1,651	1.8%

Mitsubishi Cement Corporation	$1,134 	NA	Joint venture	No	1	1	1,543	1.6%

Rinker Materials	$4,140 	11,193	Private	No	2	2	1,533	1.6%

Hanson America Holdings	$3,000 	14,872	Private	No	1	1	1,497	1.6%

Salt River Materials Group a	$150b 	<750	Tribal Government	Yes	1	4	1,477
1.6%

Grupo Cementos de Chihuahua, S.A. de C.V.	$663 	2,591	Public	No	2	5
1,283	1.4%

Cementos Portland Valderrivas, S.A.	$1,159 	2,674	Public	No	2	6	1,257
1.3%

Zachary Construction	$152 	1,200	Private	No	1	2	868	0.9%

RMC Pacific Materials	$160 	800	Private	No	1	1	812	0.9%

(continued)

Table 2-11.	Ultimate Parent Company Summary Data: 2005 (continued)

Ultimate Parent Name	Annual Sales ($106)	Employ-ment	Type	Small Business
Plants	Kilns	Clinker Capacity (103 metric tons per year)	Capacity Share

Monarch Cement Company	$154 	600	Public	Yes	1	2	787	0.8%

Florida Rock Industries	$1,368 	3,464	Public	No	1	1	726	0.8%

Votorantim Group and Anderson Columbia Company 	$9,518 	30,572	Joint
venture	No	1	1	682	0.7%

Dyckerhoff AG	$1,876 	6,958	Public	No	1	1	586	0.6%

Continental Cement Company, LLC	$50b	<750	Private	Yes	1	1	549	0.6%

Cementos Del Norte	NA	NA	Private	No	1	1	392	0.4%

Snyder Associate Companies	$29 	350	Private	Yes	1	2	286	0.3%

a	Enterprise is owned by Salt River Pima-Maricopa Indian Community.

b	EPA estimate.

Sources:	Dun & Bradstreet, Inc. 2007  XE “Dun & Bradstreet, Inc.
2007”  . D&B million dollar directory. Bethlehem, PA.

LexisNexis. LexisNexis Academic [electronic resource]. Dayton, OH:
LexisNexis  XE “LexisNexis. LexisNexis Academic [electronic resource].
Dayton, OH\: Lexis-Nexis”  .

Company Revenue and Ownership Type

Cement manufacturing is a capital-intensive industry. The vast majority
of stakeholders are large global companies with sales exceeding $1
billion. In 2005, ultimate parent company sales ranged from $30 million
to $22.3 billion (Table 2-11), with average (median) sales of $4,565
($1,589) million. Small companies accounted for 0.3% share by sales.
Ultimate parent companies were either privately or publicly owned or
jointly operated by several companies. A majority of the companies (52%)
were publicly owned. Private companies had a slightly smaller share
(41%), and only two (or 7%) were joint ventures.

Markets

Portland cement is produced and consumed domestically as well as traded
internationally. The United States meets a substantial fraction of its
cement needs through imports; in contrast, it exports only a small
fraction of domestically produced cement to other countries. We provide
value, quantity, and price trends over the past decade for Portland
cement when detailed statistics are available. In the case of
international trade, we can report data only for hydraulic cement, which
includes Portland and masonry cement.

Market Volumes

Domestic Production

In 2007, the domestic shipments of Portland cement were 90.6 million
metric tons, reflecting an 8.5% increase from 2000 and, more recently, a
3% decrease from 2006 (see Table 2-12). Year-end stocks remained
relatively level during this period at 7.4 million metric tons. Stocks
fell slightly by 5% since 2006 and equaled 8.9 million tons in 2007. As
Table 2-12 shows, shipments to customers increased steadily since 2000,
reaching 128 million tons in 2006. However, affected by declines in the
housing market, the shipments fell by 9% in 2007.

Table 2-12.	Historical U.S. Cement Statistics (106 metric tons)

 	2000	2001	2002	2003	2004	2005	2006	2007

Production

Clinker 	78.1	78.5	82.0	81.9	86.7	87.4	88.6	87.2

Portland cement	83.5	84.5	85.3	88.1	92.4	93.9	93.2	90.6

Masonry cement	4.3	4.5	4.4	4.7	5.0	5.4	5.0	4.9

Total cement	87.8	88.9	89.7	92.8	97.4	99.3	98.2	95.5

Shipments to customers	110.0	113.1	110.0	112.9	120.7	127.4	127.9	116.0

Stocks, cement, year end	7.6	6.6	7.6	6.6	6.7	7.4	9.4	8.9

Sources:	U.S. Department of the Interior, U.S. Geological Survey. 2008b
XE "U.S. Department of the Interior, U.S. Geological Survey. 2008b"  .
Minerals Commodity Summaries, Cement 2008. Washington, DC: U.S.
Department of the Interior. Available at
<http://minerals.usgs.gov/minerals/

pubs/commodity/cement/mcs-2008-cemen.pdf>.

U.S. Department of the Interior, U.S. Geological Survey. 2003  XE
“U.S. Department of the Interior, U.S. Geological Survey. 2003”  .
2002 Minerals Yearbook, Cement. Washington, DC: U.S. Department of the
Interior. Available at <http://minerals.er.usgs.gov/minerals/pubs/

commodity/cement/>.

International Trade

Cement imports are a significant share of domestic consumption
(approximately 20%); they also grew by 30% from 2000 to 2006 (see Table
2-13). Major importing countries in 2007 included Canada (18% of total
imports in 2006), China (16%), and Thailand (11%) (DOI, USGS, 2008b  XE
"DOI, USGS, 2008b"  ). In 2007, the falling value of the dollar and
construction activity declines in the housing market tempered the
quantity of import demanded. As a result, the share of U.S. consumption
met by imports fell to its lowest level in 10 years.

Table 2-13.	U.S. Cement Trade Data: 2000 to 2007

 	2000	2001	2002	2003	2004	2005	2006	2007

Exports (106 metric tons)	0.7	0.7	0.9	0.8	0.7	0.8	1.5	1.9

Imports (106 metric tons)	24.6	23.6	22.5	21.0	25.4	30.4	32.1	21.3

Net import share of apparent consumption (%)	20.0	21.0	19.0	20.0	21.0
23.0	23.0	17.0

Sources: U.S. Department of the Interior, U.S. Geological Survey. 2008b
XE "U.S. Department of the Interior, U.S. Geological Survey. 2008b"  .
Minerals Commodity Summaries, Cement 2008. Washington, DC: U.S.
Department of the Interior. Available at
<http://minerals.usgs.gov/minerals/

pubs/commodity/cement/mcs-2008-cemen.pdf>.

U.S. Department of the Interior, U.S. Geological Survey. 2003  XE
“U.S. Department of the Interior, U.S. Geological Survey. 2003”  .
2002 Minerals Yearbook, Cement. Washington, DC: U.S. Department of the
Interior. Available at <http://minerals.er.usgs.gov/minerals/pubs/>.

During the period from 2000 to 2005, U.S. exports remained relatively
constant at about 800,000 tons and typically did not exceed 1% of
production. However, the level of U.S. exports has increased during the
last 2 years. In 2007, U.S. exports totaled 1.9 million metric tons. The
vast majority of U.S. exports of hydraulic cement are supplied to
Canada: U.S. producers shipped a total of 650,000 tons to Canada in
2005, or 85% of total U.S. exports. The remaining fraction of U.S.
exports in 2005 went to the Bahamas, Mexico, and 33 other countries
around the world (DOI, USGS, 2008b  XE "DOI, USGS, 2008b"  ).

Market Prices

Correcting for the effects of inflation, we find that the real price of
cement per metric ton (2005 dollars) has typically ranged between $75
and $95 since 1990 (see Figure 2-7). However, data for the last 2 years
suggest the average price of cement is at its highest level in over 2
decades (approximately $100). Because of transportation constraints,
there are regional differences in the price of cement across states. For
example, remote locations such as Alaska and Hawaii had the highest
deviation from the national average ($48 in 2005) (see Figure 2-8). In
the contiguous states, prices in Arizona, New Mexico, and California
were higher than the national averages, while prices in Texas, Indiana,
and South Carolina were among the lowest.

Future Projections

Although estimates of future cement demand are not publicly available,
the Energy Information Administration provides projections for the real
value of shipments for the stone, clay, and glass industry in its AEO
(DOE, 2007  XE “DOE, 2007”  ). The forecasted annual average growth
rate for 2005 to 2030 is approximately 1.7%.

Figure 2-7.	Historical U.S. Cement Price

Sources:	1990–2003: Kelly, T. and G. Matos. 2007b  XE “Kelly, T. and
G. Matos. 2007b”  . “Historical Statistics for Mineral and Material
Commodities in the United States: Cement Supply and Demand
Statistics.” U.S. Geological Survey Data Series 140, Version 1.2.
Available at <  HYPERLINK "http://minerals.usgs.gov/ds/2005/140/"
http://minerals.usgs.gov/ds/2005/140/ >. Last modified April 11, 2006.

2004–2007: U.S. Department of the Interior, U.S. Geological Survey.
2008b  XE "U.S. Department of the Interior, U.S. Geological Survey.
2008b"  . Minerals Commodity Summaries, Cement 2008. Washington, DC:
U.S. Department of the Interior. Available at
<http://minerals.usgs.gov/minerals/pubs/commodity/cement/mcs-2008-cemen.
pdf>.

Figure 2-8.	Deviation from National Average Cement Price per Metric Ton
by Region: 2005

Source:	U.S. Department of the Interior, U.S. Geological Survey. 2007a
XE "U.S. Department of the Interior, U.S. Geological Survey. 2007a"  .
2005 Minerals Yearbook, Cement. Washington, DC: U.S. Department of the
Interior. Table 11. Available at
<http://minerals.er.usgs.gov/minerals/pubs/commodity/cement/>.

Economic Impact Analysis

EPA prepares an EIA to provide decision makers with a measure of the
social costs of using resources to comply with a program (EPA, 2000  XE
"EPA, 2000"  ). The social costs can then be compared with estimated
social benefits (as presented in Section 5). As noted in EPA’s (2000)
Guidelines for Preparing Economic Analyses, several tools are available
to estimate social costs and range from simple direct compliance cost
methods to the development of a more complex market analysis that
estimates market changes (e.g., price and consumption) and economic
welfare changes (e.g., changes in consumer and producer surplus).

The Office of Air Quality Planning and Standards (OAQPS) has adopted the
standard industry-level analysis described in the Office’s resource
manual (EPA, 1999a  XE "EPA, 1999a"  ). This approach is consistent with
previous EPA analyses of the Portland cement industry (EPA, 1998  XE
"EPA, 1998"  ; EPA, 1999b, and 2009a  XE "EPA, 1999b. 2009a"  ) and uses
a single-period static partial-equilibrium model to compare pre-policy
cement market baselines with expected post-policy outcomes in these
markets. The benchmark time horizon for the analysis is the intermediate
run where 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. Key measures in
this analysis include

market-level effects (market prices, changes in domestic production and
consumption, and international trade),

industry-level effects (changes in (i.e. operating profits) and
employment),

facility-level effects (plant utilization changes), and

social costs (changes in producer and consumer surplus).

Absent forecasts and the uncertainties of future economic baselines, the
partial-equilibrium market analysis can only cover a subset of plants
presumed to be operating in conditions similar to 2005. Thus, this
analysis does not reflect changes in the state of the US economy which
may occur by the analysis year of 2013 which could significantly
influence the quantity of cement needed.  As shown in the following
sections, the market analysis covers $378 million of the total $466
million in regulatory program costs, or 81%; simulated post policy
outcomes described throughout Section 3.2 should be interpreted in light
of this modeling choice. EPA analyzed the remaining $88 million in
NESHAP and NSPS regulatory program costs “outside” of the partial
equilibrium market analyses using direct compliance costs methods (see
Section 3.3). EPA provides complete social cost accounting in the
section describing the social cost estimates (Section 3.4) and provides
a discussion of its overall assessment (Section 3.5).

Regulatory Program Costs

EPA is finalizing amendments to the NESHAP from the Portland cement
manufacturing industry and (NSPS for Portland cement plants. The final
amendments to the NESHAP add or revise, as applicable, emission limits
for Hg, THC, and PM from kilns located at a major or an area sources,
and HCl from kilns and located at major sources. EPA is also adopting
separate standards for these pollutants which apply during startup,
shutdown, and operating modes. Finally, EPA is adopting performance
specifications for use of mercury CEMS and updating recordkeeping and
testing requirements. The final amendments to the NSPS add or revise, as
applicable, emission limits for particulate matter (PM), opacity,
nitrogen oxides (NOx), and sulfur dioxide (SO2) for facilities that
commence construction, modification, or reconstruction after June 16,
2008. The final rule also includes additional testing and monitoring
requirements for affected sources. Although EPA’s analysis focuses on
the final NESHAP and NSPS engineering cost estimates, EPA also presents
additional information on different combinations of the regulatory
programs. This information helps stakeholders better understand the size
and scope of the each. These include

final NSPS only,

final NESHAP only, and

alternative: more stringent NSPS and final NESHAP.

For the year 2013, EPA’s engineering cost analysis estimates the total
annualized costs of the final NESHAP and NSPS are $466 million (in 2005
dollars) (see Table 3-1). These costs include a variety of pollution
control expenditures: equipment installation, operating and maintenance,
recordkeeping, and performance-testing activities. Capital costs are
annualized over the expected life of the control equipment which is 20
years for all devices except RTOs which are 15 years.  The majority of
the costs ($455 million, or 98%, are associated with the final NESHAP.
The remaining costs ($11 million) are associated with the final NSPS
limits for SO2 and NOx. Figure 3-1 illustrates the distribution of
annualized compliance costs per metric ton of clinker capacity by
different combinations of the regulatory programs. In Table 3-2, we
report state-level summary statistics for total annualized compliance
costs per metric ton of clinker capacity for the final NESHAP and NSPS
to highlight any regional differences in control costs.

Table 3-1.	Summary of Direct Total Annualized Compliance Costs (million,
2005$)

	Total Annualized Compliance Costs

Description	Final NSPS Only	More Stringent NSPS Only

Total:	$40a	$56a

	Final NESHAP Only

Partial Equilibrium Analysis (136 Kilns)	$378

NSPS kilns (7 kilns)	$29

Other kilns (13 kilns)	$48

Total:	$455

	Final NESHAP and NSPS	Final NESHAP and More Stringent NSPS

136 Kilns	$378	$378

20 Kilns	$88	$104

Total:	$466	$482

a	The final NSPS only also includes the $29 million in NESHAP costs for
7 kilns. The 7 kilns will also incur an additional $11 in compliance
costs to meet the final NSPS limits for SO2 and NOx. Alternatively, the
7 kilns would also incur an additional $27 in compliance costs to meet
the stringent NSPS limits for SO2 and NOx.

Figure 3-1.	Range of Per-Ton Total Annualized Compliance Costs (2005$)

Table 3-2.	Range of Per-ton Total Annualized Compliance Costs by State
(2005$)

ST	Data

	Average ($/ ton of clinker capacity)	Minimum ($/ ton of clinker
capacity)	Maximum ($/ ton of clinker capacity)

AL	$3	$1	$5

AZ	$3	$1	$6

CA	$4	$3	$5

CO	$2	$1	$3

FL	$3	$1	$5

GA	$1	$1	$1

IA	$6	$4	$8

ID	$10	$9	$10

IL	$6	$1	$8

IN	$9	$5	$14

KS	$6	$6	$6

KY	$4	$4	$4

MD	$6	$3	$9

ME	$1	$1	$1

MI	$5	$4	$6

MO	$5	$4	$5

MT	$2	$2	$2

NE	$6	$5	$6

NM	$2	$2	$2

NV	$2	$2	$2

NY	$3	$1	$4

OH	$5	$5	$5

OK	$8	$4	$13

OR	$4	$4	$4

PA	$5	$2	$7

SC	$4	$4	$4

SD	$2	$1	$2

TN	$3	$1	$5

TX	$5	$1	$8

UT	$5	$1	$9

VA	$4	$4	$4

WA	$1	$1	$2

WV	$7	$6	$8

WY	$7	$5	$8

U.S.	$5	$1	$14

Note:  Includes Final NESHAP only for 136 kilns included in economic
impact model.

Partial-Equilibrium   SEQ CHAPTER \h \r 1 Analysis

The partial-equilibrium analysis develops a cement market model that
simulates how stakeholders (consumers and firms) might respond to the
additional regulatory program costs. In this section, we provide an
overview of the economic model used during proposal (EPA, 2009  XE "EPA,
2009"  ). Appendix A provides additional details about economic model
updates made since proposal, model equations, and parameters.

Regional Structure and Baseline Data

Cement sales are often concentrated locally among a small number of
firms for two reasons: high transportation costs and production
economies of scale. Transportation costs significantly influence where
cement is ultimately sold; high transportation costs relative to unit
value provide incentives to produce and sell cement locally in regional
markets (USITC, 2006  XE “USITC, 2006”  ). To support this claim,
the empirical literature has typically pointed to Census of
Transportation data showing over 80% of cement shipments were made
within a 200-mile radius (Jans and Rosenbaum, 1997  XE “Jans and
Rosenbaum, 1997”  ) and reported evidence of high transportation costs
per dollar of product value from case studies (Ryan, 2006  XE “Ryan,
2006”  ). Based on this literature, the Agency assumes that the U.S.
Portland cement industry is divided into a number of independent
regional markets with each having a single market-clearing price.

The freight-on-board (f.o.b.) price of Portland cement for each regional
market is derived as the production weighted average of the state level
f.o.b. prices reported by the USGS for cement (see Table 3-3). The
production of Portland cement within each market is the sum of estimated
individual kiln production levels (EPA, 2009  XE "EPA, 2009"  ) and
include adjustments described in Appendix A (see Table 3-4). We obtained
estimates of Portland cement imports from the USGS and mapped them to
each market based on the port of entry.

Near-Term Cement Plant Production Decisions

A 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 production cost; if
price is above marginal production cost, producing and selling the extra
ton of cement increase profit. The company continues to produce
additional cement until the profit from

Table 3-3.	Portland Cement Prices by Market ($/metric tons): 2005

Market	Price ($/metric ton)

Atlanta	$81

Baltimore/Philadelphia	$82

Birmingham	$83

Chicago	$67

Cincinnati	$84

Dallas	$75

Denver	$89

Detroit	$93

Florida	$91

Kansas City	$86

Los Angeles	$78

Minneapolis	$92

New York/Boston	$89

Phoenix	$83

Pittsburgh	$88

St. Louis	$84

Salt Lake City	$91

San Antonio	$82

San Francisco	$97

Seattle	$88

producing an extra ton of cement is zero (price equals marginal cost) or
capacity constraints are reached. The decision rule is consistent with
the assumption of pure competition.

Although perfect competition is widely accepted for modeling many
industries regardless of the model time horizon (EPA, 2000  XE "EPA,
2000"  ), the cement industry has two characteristics that influenced
EPA’s modeling choice relating to market structure. First, high
transportation costs and other production economics tend to limit the
number of sellers (particularly over a short time horizon), so each
seller has a substantial regional market share. Timely market entry is
also constrained by the high capital costs that involve purchases and
construction of large rotary kilns that are not readily movable or
transferable to other uses. Second, cement producers offer similar or
identical products. American Society for Testing and Materials (ASTM)
specifications tend to ensure uniform quality, and recent industry
reviews (USITC, 2006  XE "USITC, 2006"  ) suggest that there is little
or no brand loyalty that allows firms to differentiate their products.

Table 3-4.	Portland Cement Markets (106 metric tons): 2005

Market	U.S. Production	Imports	Total

Atlanta	5.8	2.3	8.1

Baltimore/Philadelphia	7.8	0.6	8.5

Birmingham	5.9	2.2	8.1

Chicago	4.7	0.2	4.9

Cincinnati	3.7	0.0	3.7

Dallas	8.1	2.4	10.5

Denver	3.4	0.0	3.4

Detroit	3.8	1.3	5.2

Florida	5.5	5.8	11.4

Kansas City	5.0	0.0	5.0

Los Angeles	10.6	3.8	14.4

Minneapolis	1.7	0.4	2.1

New York/Boston	3.2	2.8	6.0

Phoenix	4.3	0.0	4.3

Pittsburgh	1.5	1.6	3.1

St. Louis	6.0	0.0	6.0

Salt Lake City	2.4	0.1	2.4

San Antonio	5.5	4.6	10.0

San Francisco	3.4	2.8	6.2

Seattle	1.1	2.5	3.6

Given entry barriers, product characteristics, and the need to
understand important near-term/transitory stakeholder outcomes, EPA
continued to use the economic impact model designed for previous
analyses (EPA, 1998, 1999b, 2009  XE "EPA, 1998, 1999b, 2009"  ). The
model considers how regional markets may operate in near-term time
horizons when 1) the number of companies is limited and 2) the companies
sell similar or identical products. Under these circumstances, the
short-run production decision rule that a cement company makes differs
from pure competition. The company continues to consider the production
effect described above; however, the company adds another dimension to
the decision-making process by also considering the market price effect
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
regional market may lower the market cement price and reduce the profits
on all the other cement sold. If the price effect is large enough,
companies may find it more profitable to reduce production below the
levels implied by pure competition. As a result, short-run regional
market prices tend to be higher than marginal production costs (i.e.,
there may be a preexisting market distortion within cement markets prior
to regulation). The size of the existing distortion depends on the
seller’s market share and how responsive cement consumers are to
changes in the cement price. Economic theory suggests the market
distortion will typically be higher the smaller the number of sellers
and when the quantity demanded is less sensitive to price (i.e., the
demand elasticity is inelastic) (see Appendix A).

Economic Impact Model Results

Market-Level Results

Market-level impacts include the regional price and quantity adjustments
for Portland cement, including the changes in imports for the
appropriate regions. As shown in Table 3-5, the average national price
for Portland cement increases by 5%, or $4.50 per metric ton, while
overall U.S. cement consumption falls by approximately 5%. Domestic
production falls by 11%, or 10 million tons per year. Cement imports
increase in response to higher domestic cement prices; imports increase
by 10%, or 3 million metric tons.

Table 3-5.	National-Level Market Impacts: 2005

−6	−4.8%

Domestic production	93	−10	−10.8%

Imports	33	3	10.0%

As shown in Table 3-6, price increases are the highest in regions with
high compliance costs per metric ton. For example, the Cincinnati market
price increase ($10 per metric ton) also includes kilns with higher
average compliance costs and a kiln with the highest per-unit

Table 3-6.	Regional Compliance Costs and Market Price Changes ($/metric
ton of cement): 2005

	Incremental Compliance Costs

($/metric ton of estimated

cement production)	Baseline Price	Market Price Change

Market	Mean	Minimum	Maximum

Absolute	Percent

Atlanta	$3.60	$1.10	$5.90	$81.30	$2.80	3.4%

Baltimore/Philadelphia	$6.20	$1.20	$10.00	$81.70	$6.10	7.5%

Birmingham	$3.60	$1.10	$4.80	$82.60	$3.80	4.6%

Chicago	$6.80	$0.90	$10.10	$66.90	$4.80	7.2%

Cincinnati	$8.10	$4.00	$14.10	$84.20	$10.40	12.4%

Dallas	$5.60	$3.50	$8.50	$75.10	$4.90	6.5%

Denver	$3.00	$1.00	$8.10	$88.70	$6.30	7.1%

Detroit	$6.50	$4.00	$10.30	$92.70	$4.20	4.5%

Florida	$3.40	$1.20	$5.50	$90.70	$3.50	3.9%

Kansas City	$8.60	$3.80	$13.80	$86.10	$8.20	9.5%

Los Angeles	$6.00	$3.20	$13.10	$78.20	$4.30	5.5%

Minneapolis	$6.30	$4.50	$8.80	$92.20	$8.50	9.2%

New York/Boston	$2.50	$1.00	$4.50	$89.00	$1.80	2.0%

Phoenix	$1.90	$1.00	$6.00	$83.10	$4.20	5.1%

Pittsburgh	$7.60	$6.90	$8.00	$88.00	$4.60	5.2%

St. Louis	$4.80	$3.80	$5.60	$84.10	$4.50	5.4%

Salt Lake City	$5.90	$1.60	$9.90	$91.40	$10.40	11.4%

San Antonio	$4.00	$0.80	$7.70	$82.30	$3.30	4.0%

San Francisco	$3.10	$1.00	$5.00	$96.90	$3.30	3.4%

Seattle	$1.20	$1.00	$1.40	$88.00	$0.70	0.8%

Grand Total	$5.20	$0.80	$14.10	$83.90	$4.50	5.4%

compliance costs ($14 per metric ton). It is important to note that EPA
uses a time horizon where transportation costs between regions are high
enough that interregional trade is unlikely to occur, at least in the
short run. The regional differences in unit compliance costs and the
significant simulated changes in relative regional prices suggest
domestic cement plants may be more likely to consider short-run
shipments of cement between regional markets. Choices would depend on
the additional benefits of selling cement to these markets and the costs
of transporting the cement outside the regional market. Although EPA has
not quantified this effect, additional flexibility would tend to temper
prices increases in some of these markets.

Imports also tend to limit price increases in certain regions. This
tends to reinforce U.S. production declines because cement plants have
more difficulty passing on compliance costs in the form of higher prices
when compared with similar plants operating in regions without import
competition. Because imports are only modeled for markets with imports
in the baseline without regulation, Table 3-7 separates the results into
markets with and without imports as well as providing the results for
all markets. As shown in Table 3-7, median price increases in regions
with imports are lower than the median price increases in regions
without import competition. In some regions with imports, the reductions
in U.S. production are significant. As shown in Table 3-7, the maximum
simulated U.S. regional production change is 23%. To the extent there
are any unobserved constraints on import supply that are not captured in
the import supply elasticity parameter, price and U.S. production
adjustments for regional markets with imports would tend to become more
similar to regional markets without imports.

Industry-Level Results

As shown in Table 3-8, compliance costs vary by cement plant, and this
variation suggests some plants will be more adversely affected than
others. To assess these differences, EPA collected industry operating
profit data and identified plants with operating profit increases and
losses. Absent plant-specific data, EPA assumed each plant’s baseline
profits were consistent with the median operating profit margin reported
by the PCA (2008c, Table 44 xe "2008c, Table 44" ). In 2005, this value
was $18 per metric ton, or 16%. Using this assumption, total operating
profits for 59 plants (58%) decrease by $387 million with regulation.
These plants tend to have higher per ton compliance costs. The remaining
plants’ compliance burden is offset by higher regional cement prices,
and total plant operating profits increase by $147 million. These 44
plants have lower unit compliance costs compared with their competitors.

Table 3-7.	Summary of Regional Market Impacts

	Regional Markets

	With Imports	Without Imports	All Markets

Change in Market Price

	Absolute ($/metric ton)

	Mean	$4.70	$6.40	$4.50

Median	$4.20	$5.40	$4.40

Minimum	$0.70	$4.20	$0.70

Maximum	$10.40	$10.40	$10.40

Percentage of baseline price

	Mean	5.5%	7.5%	5.4%

Median	4.9%	6.2%	5.3%

Minimum	0.8%	5.0%	0.8%

Maximum	11.4%	12.4%	12.4%

Change in Domestic Production

	Absolute (thousand metric tons)

	Mean	−559	−271	−501

Median	−421	−247	−372

Minimum	−74	−189	−74

Maximum	−1,539	−403	−1,539

Percentage of baseline production

	Mean	−11.8%	−6.6%	−10.8%

Median	−11.6%	−5.5%	−10.4%

Minimum	−6.8%	−4.4%	−4.4%

Maximum	−22.8%	−10.9%	−22.8%

Within the group of plants with operating losses, EPA identified 10
domestic plants with negative operating profits and significant
utilization changes that could temporarily idle until market demand
conditions improve (see Table 3-9). The plants have unit compliance
costs close to $8 per ton; they account for approximately 8% of domestic
capacity. These plants are modeled as continuing to operate despite low
capacity utilization and short run negative profits.  The model results
for them are included in the summary results for Tables 3-5, 3-6, 3-7,
and 3-8 but are also reported separately in Table 3-9.

If the plant owners did decide to permanently shut down these plants,
the reduction in domestic supply would lead to additional projected
market price increases. This would lead to an increased production at
other plants, a possible increase in imports (depending if the plant
that chooses to close is in a market where imports are anticipated) and
a decrease in control cost.  This scenario cannot be easily modeled.  In
an effort to bound this effect, the price increase needed to reduce
national consumption by the amount of production that would be lost if
the ten plants dropped from 55.5% capacity utilization to 0.0% capacity
utilization was estimated using the demand elasticity of 0.88.  This
ignores changes in other plants is response to an increased potential
market share and increases in imports. Both of these would tend diminish
the price increase.  The predicted price change was multiplied by the
change in production associated with the ten plants dropping capacity
utilization to zero and multiplied by one half to estimate the change in
surplus associated with the price and quantity change.  This gave a
result of a $10 million increase in social cost. This number was then
reduced by the avoided pollution control cost of $34 million at the ten
plants.  This resulted in a net reduction of $24 million in social cost
due to the adjustment.  Because of the method of estimating this
adjustment it cannot be distributed between producer and consumer
surplus.  An estimate of the social cost is provided with and without
this adjustment.

Table 3-8.	Distribution of Industry 2005

	Changes in Total Operating Profit:

	Plants with Loss	Plants with Gain	All Plants

Number	58	44	102

Cement Capacity (million metric tons)

	Total	55,202	38,145	93,346

Average per plant	952	867	915

Compliance Costs

	Total (thousand)	$308,740	$68,806	$377,546

Average ($/metric cement)	$5.59	$1.80	$4.04

Capacity Utilization (percent)

	Baseline	100.3%	98.7%	99.6%

With regulation	81.0%	100.3%	88.9%

Change in total operating profits (million)	−$387	$147	−$241

Table 3-9.	Cement Plants with Significant Utilization Changes 2005

	Total

Number	10

Cement Capacity (thousand metric tons)

	Total	7,815

Average per plant	782

Compliance Costs

	Total (thousand)	$62,222

Average ($/metric ton)	$7.96

Capacity Utilization (%)

	Baseline	99.0%

With regulation	55.5%

Change in Operating Profit (million)	−$116

  SEQ CHAPTER \h \r 1 Job Effects

Precise job effect estimates cannot be estimated with certainty.
Ideally, whenever a regulatory change results in a reallocation of labor
or other factors of production in an economy, a general equilibrium
approach should be applied to estimate the attendant economic impacts.
Unfortunately, time and resource constraints prevented the creation of a
model with the spatial and sectoral resolution necessary to analyze the
final rule. However, Morgenstern et al (2002) provides a theoretical
framework which allows us to approximate some of the relevant general
equilibrium effects by identifying three economic mechanisms by which
pollution abatement activities can indirectly influence:

higher production costs raise market prices, higher prices reduce
consumption, and employment within an industry falls (“demand
effect”);

pollution abatement activities require additional labor services to
produce the same level of output (“cost effect”); and

post-regulation production technologies may be more or less labor
intensive (i.e., more/less labor is required per dollar of output)
(“factor-shift effect”).

Several empirical studies, including Morgenstern et al. (2002 xe
"Morgenstern et al. (2002" ), suggest the net employment decline is zero
or economically small (e.g., Cole and Elliot, 2007 xe "Cole and Elliot,
2007" ; Berman and Bui, 2001 xe "Berman and Bui, 2001" ). However,
others show the question has not been resolved in the literature
(Henderson, 1996 xe "Henderson, 1996" ; Greenstone, 2002 xe "Greenstone,
2002" ). Morgenstern et al. use a 6-year panel (U.S. Census data for
plant-level prices, inputs [(including labor], outputs, and
environmental expenditures) to econometrically estimate the production
technologies and industry-level demand elasticities. Their
identification strategy leverages repeat plant-level observations over
time and uses plant-level and year fixed effects (e.g., dummy variables
for plant and years). After estimating their model, Morgenstern show and
compute the change in employment associated with an additional $1
million ($1987) in environmental spending. Their estimates cover four
manufacturing industries (pulp and paper, plastics, petroleum, and
steel) and Morgenstern et al. present results separately for the cost,
factor shift, and demand effects, as well as the net effect. They also
estimate and report an industry-wide average parameter that combines the
four industry-wide estimates and weight them by each industry’s share
of environmental expenditures.

Historically, EPA has most often estimated employment changes associated
with plant closures due to environmental regulation or changes in output
for the regulated industry (EPA, 1999a; EPA, 2000). This partial
equilibrium approach focuses only on the “demand” portion of the
projected change in employment and neglects other employment changes.
EPA provides this estimate because it employs the most detailed modeling
for the industry being regulated even if it does not capture all types
of employment impacts.   In addition to the employment effects
identified by Morgenstern et al., we also expect that the substitutes
for cement (e.g., asphalt) would expand production as consumers shift
away from cement to other products.  This would also lead to increased
employment in those industries. Focusing only on the “demand
effect”, it can be seen that the estimate from the historical approach
is within the range presented by the Morgenstern “demand effect”
portion. This strengthens our comfort in the reasonableness of both
estimates.  In April of this year, EPA started including an estimate
based on the Morgenstern approach because it is thought to be a broader
measure of the employment impacts of this type of environmental
regulation.  Thus, this analysis goes beyond what EPA has typically done
because the parameters estimated in the Morgenstern paper were used to
estimate all three effects (“demand,” “cost,” and “factor
shift”). This transfer of results from the Morgenstern study is
uncertain but avoids ignoring the “cost effect” and the
“factor-shift effect.”

−10%.   By comparison, using the Morgenstern approach, we estimate
that the net employment effects could range between 600 job losses to
1,300 job gains.

EPA has solely used this historical estimate in the past as a measure of
the projected employment change associated with a regulation.  However
there are a number of serious shortcomings with this approach.  First,
and foremost, the historical approach only looks at the employment
effects on the regulated industry from reduced output.  Second, to
arrive at that estimate, EPA needed to string together a number of
strong assumptions.  The employment impacts are independent of the
performance of the overall economy.  This rule takes effect in three
years.  If the economy is strong, the demand for cement strong, it is
unlikely that any contraction in the industry will take place, even with
the regulation.  Second, we assume that all plants have the same limited
ability to pass on the higher costs.  In reality, plants should be
modeled as oligopolists for each of their regional markets.  Finally,
EPA assumed that employment is directly proportional to output.  This is
unlikely, and biases the results towards higher employment losses.  The
Morgenstern methodology is a more complete consideration of probable
impacts of a regulation on the economy.

Table 3-10.	Job Losses/Gains Associated with the Final Rule

Method	1,000 Jobs

Partial equilibrium model 	−1.5

(demand effect only)

Literature-based estimate (net effect [A + B + C below])	0.3

(−0.6 to +1.3)

A. Literature-based estimate: Demand effect	−0.8

(−1.7 to +0.1)

B. Literature-based estimate: Cost effect	0.5

(+0.2 to +0.9)

C. Literature-based estimate: Factor shift effect	0.6

(+0 to +1.2)

ble from other studies. To do this, we multiplied the point estimate for
the total demand effect (−3.56 jobs per million [$1987] of
environmental compliance expenditure) by the total environmental
compliance expenditures used in the partial equilibrium model. For
example, the jobs effect estimate for is estimated to be 807 jobs
(−3.56 × $378 million × 0.6). Demand effect results are provided in
Table 3-10.  It is not appropriate to substitute the data from that
approach in to the Morgenstern due to the incompatibilities of the
underlying data.  Since the result from the historical approach is
within the confidence bounds for the Morgenstern results for the
“demand effect”, we are comfortable that the more general
Morgenstern result is a good representation of the change in employment.

We also present the results of using the Morgenstern paper to estimate
employment “cost” and “factor-shift” effects. Although using the
Morgenstern parameters to estimate these “cost” and
“factor-shift” employment changes is uncertain, it is helpful to
compare the potential job gains from these effects to the job losses
associated with the “demand” effect. Table 3-10 shows that using the
“cost” and “factor shift” employment effects may offset
employment loss estimates using either “demand” effect employment
losses. The 95% confidence intervals are shown for all of the estimates
based on the Morgenstern parameters. As shown, at the 95% confidence
level, we cannot be certain if net employment changes are positive or
negative.

Although the Morgenstern paper provides additional information about the
potential job effects of environmental protection programs, there are
several qualifications EPA considered as part of the analysis. First,
EPA has used the weighted average parameter estimates for a narrow set
of manufacturing industries (pulp and paper, plastics, petroleum, and
steel). Absent other data and estimates, this approach seems reasonable
and the estimates come from a respected peer-reviewed source. However,
EPA acknowledges the final rule covers an industry not considered in the
original empirical study. By transferring the estimates to the cement
sector, we make the assumption that estimates are similar in size. In
addition, EPA assumes also that Morgenstern et al.’s estimates derived
from the 1979–1991 are still applicable for policy taking place in
2013, almost 20 years later. Second, the economic impact model only
considers near-term employment effects in the cement industry where
production technologies are fixed. As a result, the economic impact
model places more emphasis on the short-term “demand effect,”
whereas the Morgenstern paper emphasizes other important long-term
responses. For example, positive job gains associated with “factor
shift effects” are more plausible when production choices become more
flexible over time and industries can substitute labor for other
production inputs. Third, the Morgenstern paper estimates rely on sector
demand elasticities that are different (typically bigger) from the
demand elasticity parameter used in the cement model. As a result, the
demand effects are not directly comparable with the demand effects
estimated by the cement model. Fourth, Morgenstern identifies the
industry average as economically and statistically insignificant effect
(i.e., the point estimates are small, measured imprecisely, and not
distinguishable from zero). EPA acknowledges this fact and has reported
the 95% confidence intervals in Table 3-10. Fifth, Morgenstern’s
methodology assumes large plants bear most of the regulatory costs. By
transferring the estimates, EPA assumes a similar distribution of
regulatory costs by plant size and that the regulatory burden does not
disproportionately fall on smaller plants.

Other Economic Analyses: Direct Compliance Cost Methods   SEQ CHAPTER \h
\r 1

In addition to the market-level partial equilibrium analysis, EPA
developed a separate economic analysis for the remaining 20 kilns that
EPA anticipates will be affected by the final rule. These costs ($88
million, or 19%) were not included in the economic impact model analysis
because of uncertainties and difficulties with developing an appropriate
set of baseline cement market conditions for future years.

The total annualized costs for two white cement kilns are $2 million, or
approximately $9 per metric ton of cement production. Using reported
2005 data from the USGS on the average mill net value of white cement
($176 per metric ton), this cost represents 5% of the product value.

EPA also conducted sales tests for 18 other kilns that were not included
in the partial equilibrium analysis. The total annualized NESHAP cost
for these 18 kilns is approximately $75 million. The median cost per ton
is approximately $3.80 and ranges from $1.90 to $4.40 per ton of cement
production. In addition, 7 of these 18 kilns would face an additional
control cost above the NESHAP (approximately $1 dollar per metric ton)
to meet the NSPS limits for SO2 and NOx.

The USGS reports that the real price of cement per metric ton (2005
dollars) has typically ranged between $75 and $100 since 1990. A sales
test using these price data shows cost-to-sales ratios (CSRs) could
range between 2% and 6%

Sales Test Ratio = Control Costs ($/ton)/F.O.B Cement Prices ($/ton).

From 2000 to 2006, the PCA reports that the average operating profit
rates for the industry ranged from 17 to 21% (PCA, 2008c  XE "PCA,
2008c"  ). If these profit data are representative of operating profit
rates for new kilns, kilns could potentially significantly reduce their
operating profit rates. As a result, companies may have the incentive to
look for less expensive alternatives to meet the emission standards. If
these alternatives are limited or not cost effective, the final rule may
lead companies to consider delaying rates of construction of new kilns
until market conditions change (e.g., increases in demand that lead to
rising cement prices) to cover additional control costs.

  SEQ CHAPTER \h \r 1 Social Cost Estimates

For the kilns modeled in our partial equilibrium model, the market
adjustments in price and quantity were used to estimate the changes in
aggregate economic welfare using applied welfare economics principles
(see Appendix C).  Higher cement prices and reduced consumption lead to
consumer welfare losses ($540 million). Domestic producers (in
aggregate) experience a net loss of $239 million. As noted in the
previous section, individual domestic producers may gain or lose
depending on the change in compliance costs versus the change in the
regional market prices. The total domestic surplus loss (consumer and
producers) totals $792 million.

  For the kilns not modeled in our partial equilibrium model, the $88
million in engineering costs were multiplied by 1.8 to approximate the
likely additional social cost associated with oligopoly market response.
 Thus the social cost estimate for the 20 kilns not in the partial
equilibrium model is $158 million.  Because of the approximation used,
we cannot estimate how the $158 million is distributed between consumers
and producers.

Table 3-11.	Distribution of Social Costs ($106): 2005

	Social Cost Estimates

	Description	Final NESHAP and NSPS	Final NESHAP and More Stringent NSPS
EIA Social Cost Method

Change in consumer surplus	$551	$551	Partial-equilibrium model

(baseline year 2005)

Change in domestic producer surplus	$241	$241	Partial-equilibrium model

(baseline year 2005)

	20 Kilns

	$158	$187	Direct Compliance Method

(scaled by 1.8 for oligopoly)

Change in domestic surplus	$950	$979	Combined methods

Adjustment if  ten low utilization facilities idle or close 	-$24	-$24

Total:	$926-$950	$955-$979	Change with and without adjustment

	Final NSPS Only	More Stringent NSPS Only

	Total:	$72	$101	Direct compliance cost method (scaled by 1.8 for
oligopoly)

	Final NESHAP Only

	Change in consumer surplus	$551	Partial-equilibrium model

(baseline year 2005)

Change in domestic producer surplus	$241	Partial-equilibrium model

(baseline year 2005)

NSPS kilns (7 kilns)	$52	Direct compliance cost method

(scaled by 1.8 for oligopoly)

Other kilns (13 kilns)	$86	Direct compliance cost method

(scaled by 1.8 for oligopoly)

Change in domestic surplus	$930	Combined methods

Adjustment if  ten low utilization facilities idle or close	$-24

	Total:	$904-$930	Change with and without adjustment

The estimated social cost of the final rule is $880 million. This
estimate includes the results for existing kilns included in the
partial-equilibrium analysis ($792 million),the final NESHAP direct
compliance costs 20 kilns not included in the economic impact model,
($77 million), and the additional NSPS direct compliance cost for 7
kilns coming on line in the future ($11 million). The social estimates
are significantly higher than the engineering analysis estimate of
annualized costs totaling $466 million. This is a direct consequence of
EPA’s assumptions about existing market structure discussed
extensively in previous cement industry rulemakings and in Section 2 and
Appendix B of this RIA. Under baseline conditions without regulation,
the existing domestic cement plants are assumed to choose a production
level that is less than the level produced under perfect competition. As
a result, a preexisting market distortion exists in the cement markets
covered by the final rule (i.e., the observed baseline market price is
higher than the [unobserved] market price that a model of perfect
competition would predict). The imposition of additional regulatory
costs tends to widen the gap between price and marginal cost in these
markets and contributes to additional social costs. The above social
costs for 2013 include annualized capital costs over the expected
lifetime of the equipment and an opportunity cost of capital (7%)
discount rate. To facilitate comparisons of benefits and costs when
estimates vary of time across multiple years, EPA typically estimates a
“consumption equivalent” present value measure of costs. This could
be computed using a consumption rate of interest of 3% and 7%. However,
this calculation was not necessary since the cost and benefit analyses
only produce estimates for a single year (OAQPS, 1999a  XE "OAQPS,
1999a"  ).

Energy Impacts

Executive Order 13211 (66 FR 28355, May 22, 2001) provides that agencies
will prepare and submit to the Administrator of the Office of
Information and Regulatory Affairs, OMB, a Statement of Energy Effects
for certain actions identified as “significant energy actions.”
Section 4(b) of Executive Order 13211 defines “significant energy
actions” as any action by an agency (normally published in the Federal
Register) that promulgates or is expected to lead to the promulgation of
a rule or regulation, including notices of inquiry, advance notices of
final rulemaking, and notices of final rulemaking: (1) (i) that is a
significant regulatory action under Executive Order 12866 or any
successor order, and (ii) is likely to have a significant adverse
effect on the supply, distribution, or use of energy; or (2) that is
designated by the Administrator of the Office of Information and
Regulatory Affairs as a significant energy action.

This rule is not a significant energy action as designated by the
Administrator of the Office of Information and Regulatory Affairs
because it is not likely to have a significant adverse impact on the
supply, distribution, or use of energy. EPA has prepared an analysis of
energy impacts that explains this conclusion below.

To enhance understanding regarding the regulation’s influence on
energy consumption, EPA examined publicly available data describing the
cement sector’s energy consumption. The AEO 2010 (DOE, 2010  XE "DOE,
2010"  ) provides energy consumption data. As shown in Table 3-12, this
industry accounts for approximately 0.4% of the U.S. total energy
consumption. As a result, any

Table 3-12.	U.S. Cement Sector Energy Consumption (Trillion BTUs)a:
2013

 	Quantity	Share of Total Energy Use

Residual fuel oil	0.9	0.00%

Distillate fuel oil	10.8	0.00%

Petroleum coke	47.3	0.10%

Other petroleumb	30.2	0.00%

Petroleum subtotal	89.2	0.10%

Natural gas	19.8	0.00%

Steam coal	206.6	0.20%

Metallurgical coal	6.8	0.00%

Coal subtotal	213.4	0.20%

Purchased electricity	38.9	0.00%

Total 	399.44	0.40%

Delivered Energy Use	72,407	72.20%

Total Energy Use	100,592	100.00%

a Fuel consumption includes consumption for combined heat and power.

b Includes petroleum coke, lubricants, and miscellaneous petroleum
products.

Source:	U.S. Department of Energy, Energy Information Administration.
2010. Supplemental Tables to the Annual Energy Outlook 2010.  XE "U.S.
Department of Energy, Energy Information Administration. 2010.
Supplemental Tables to the Annual Energy Outlook 2010."   Table 10 and
Table 39. Available at
<http://www.eia.doe.gov/oiaf/aeo/supplement/supref.html>.

energy consumption changes attributable to the regulatory program should
not significantly influence the supply, distribution, or use of energy.
EPA has also estimated the amount of additional electricity consumption
associated with add-on controls. The analysis shows the additional
national electrical demand to be 780 million kWh per year and the
natural gas use to be 1.2 million MMBTU per year for existing kilns. For
new kilns, assuming that of the 16 new kilns to start up by 2013, all 16
will add alkaline scrubbers and ACI systems, the electrical demand is
estimated to be 199 million kWh per year. This is less than 0.1% of AEO
2010 forecasts of total electricity and natural gas use.

Assessment

Although the economic analyses presented in this section cannot provide
precise estimates of the final NESHAP’s and NSPS’s economic impacts,
the evidence presented in this section suggests that the economic
impacts may be significant across several dimensions (price,
consumption, production, and international trade). There are several
broad issues we emphasize as stakeholders review the analysis. First,
OAQPS’s partial equilibrium analysis of NESHAPs has traditionally been
designed to assess small (marginal) changes in industry conditions. The
overall engineering cost analysis estimates are significant relative to
the size of the U.S. cement market; EPA acknowledges that use of demand
and import supply elasticities can be tenuous in these cases because the
exact functional relationships (demand and supply) are less certain when
simulated outcomes move further away from the observed pre-policy
equilibrium. Second, the partial equilibrium assumes that transportation
costs between regions are high enough that interregional trade is
unlikely to occur, at least in the short run. Allowing interregional
trade would expand the cement market definitions and increase the number
of producers in each market. 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 additional
trading opportunities may tend to moderate the relative price changes
simulated within the model. Third, as discussed earlier in this section,
the choice of market structure increases the agency’s social cost
estimate; it is almost 2 times higher than a model that assumes perfect
competition. Therefore, the analysis may overstate the social costs of
the rule. EPA continues to believe the market structure is reasonable
and provides an upper-bound social cost estimate for the following
reasons: (1) high transportation costs and other production economics
tend to limit the number of sellers (particularly over a short time
horizon), so each seller has a substantial regional market share; (2)
timely market entry is also constrained by the high capital costs that
involve purchases and construction of large rotary kilns that are not
readily movable or transferable to other uses; (3) cement producers
offer very similar or identical products; and (4) the Office of
Management and Budget (OMB) explicitly mentions the need to consider
market power–related welfare costs in evaluating regulations under
Executive Order 12866.

Small Business Impact Analysis

The Regulatory Flexibility Act (RFA) generally requires an agency to
prepare a regulatory flexibility analysis of any rule subject to notice
and comment rulemaking requirements under the Administrative Procedure
Act or any other statute unless the agency certifies that the rule will
not have a significant economic impact on a substantial number of small
entities (SISNOSE). The first step in this assessment was to determine
whether the rule will have SISNOSE. To make this determination, EPA used
a screening and market analysis to indicate whether EPA can certify the
rule as not having a SISNOSE. The elements of this analysis included

identifying affected small entities,

selecting and describing the measures and economic impact thresholds
used in the analysis, and

completing the assessment and determining the SISNOSE certification
category.

Identify Affected Small Entities

For the purposes of assessing the impacts of the final rule on small
entities, small entity is defined as (1) a small business as defined by
the Small Business Administration’s regulations at 13 CFR 121.201;
according to these size standards, ultimate parent companies owning
Portland cement manufacturing plants are categorized as small if the
total number of employees at the firm is fewer than 750 (see Table 4-1
for list); (2) a small governmental jurisdiction that is a government of
a city, county, town, school district, or special district with a
population of less than 50,000; and (3) a small organization that is any
not-for-profit enterprise that is independently owned and operated and
is not dominant in its field. As reported in Section 2, EPA has
identified four small entities (see Table 4-1). One of the four entities
is owned by a small Tribal government (Salt River Pima-Maricopa Indian
Community). The remaining three entities are small businesses.

Sales and Revenue Test Screening Analysis

In the next step of the analysis, EPA assessed how the regulatory
program may influence the profitability of ultimate parent companies by
comparing pollution control costs to total sales (i.e., a “sales”
test). To do this, we divided an ultimate parent company’s total
annualized compliance costs by its reported revenue:

Table 4-1.	Small Entity Analysis

Owner 	Entity Type	Annual Sales ($106)	Employees	Plants	Kilns	Clinker
Capacity (103 metric tons per year)	Cost-to-Sales Ratio

Salt River Materials Groupa	Tribal government	$184b	NA	1	1	1,477	0.7%

Monarch Cement Company	Business	$154 	600	1	2	787	3.0%

Continental Cement Company, LLC	Business	$93c	<750	1	1	1,164 	0.0%

Snyder Associate Companies	Business	$29 	350	1	2	286	2.0%

a	Enterprise is owned by Salt River Pima-Maricopa Indian Community.

b	EPA estimate. Estimate uses revenue data for four of the six
enterprises owned by Salt River Pima-Maricopa Indian Community.

c	EPA estimate. Estimate uses cement production levels and average
market prices.

 	(4.1)

where

CSR	=	cost-to-sales ratio,

TACC	=	total annualized compliance costs,

i	=	index of the number of affected plants owned by company j,

n	=	number of affected plants, and

TRj	=	total sales from all operations of ultimate parent company j or
annual government revenue.

The results of the screening analysis, presented in Table 4-1, show that
no small businesses have a CSR greater than 3%. Two small business have
an estimated CSR between 1 and 3%.

Additional Market Analysis

In additional to the screening analysis, EPA also examined small entity
effects after accounting for market adjustments. Under this assumption,
the entities recover some of the regulatory program costs as the market
price adjusts in response to higher cement production costs. Even after
accounting for these adjustments, small entity operating profits fall by
less than 1 million.

Assessment

After considering the economic impact of this final rule on small
entities, EPA has determined it will not have a significant economic
impact on the four small entities. No small companies have cost-to-sales
ratios greater than 3% and  only 4 of the over 40 cement companies are
small entities.

Air Quality Modeling of Emission Reductions

Synopsis

This section describes the air quality modeling performed by EPA in
support of the Portland cement NESHAP and NSPS. A national scale air
quality modeling analysis was performed to estimate the impact of the
sector emissions changes on future years: annual and 24-hour PM2.5
concentrations, total Hg deposition, as well as visibility impairment.
Air quality benefits are estimated with the Comprehensive Air Quality
Model with Extensions (CAMx) model. CAMx simulates the numerous physical
and chemical processes involved in the formation, transport, and
destruction of ozone, PM, and air toxics. In addition to the CAMx model,
the modeling platform includes the emissions, meteorology, and initial
and boundary condition data which are inputs to this model.

Emissions and air quality modeling decisions are made early in the
analytical process. For this reason, it is important to note that the
inventories used in the air quality modeling and the benefits modeling
are slightly different than the final adjusted cement kiln sector
inventories presented in the RIA. However, the air quality inventories
and the final rule inventories are generally consistent, so the air
quality modeling adequately reflects the effects of the rule.

The 2005-based CAMx modeling platform was used as the basis for the air
quality modeling for this final rule. This platform represents a
structured system of connected modeling-related tools and data that
provide a consistent and transparent basis for assessing the air quality
response to projected changes in emissions. The base year of data used
to construct this platform includes emissions and meteorology for 2005.
The platform is intended to support a variety of regulatory and research
model applications and analyses. This modeling platform and analysis is
described fully below. Additional details about the modeling system are
available in a separate technical support document: Air Quality Modeling
Technical Support Document: National Emission Standards for Hazardous
Air Pollutants from the Portland Cement Manufacturing Industry (U.S.
EPA, 2010c).

Photochemical Model Background

CAMx version 5.10 is a freely available computer model that simulates
the formation and fate of photochemical oxidants, primary and secondary
PM concentrations, and air toxics, over regional and urban spatial
scales for given input sets of meteorological conditions and emissions.
CAMx includes numerous science modules that simulate the emission,
production, decay, deposition and transport of organic and inorganic
gas-phase and particle-phase pollutants in the atmosphere (Nobel,
McDonald-Buller et al., 2001  XE "Nobel, McDonald-Buller et al., 2001"
; Baker and Scheff, 2007  XE "Baker and Scheff, 2007"  ; Russell, 2008
XE "Russell, 2008"  ).

CAMx is applied with ISORROPIA inorganic chemistry (Nenes et al., 1999
XE "Nenes et al., 1999"  ), a semivolatile equilibrium scheme to
partition condensable organic gases between gas and particle phase
(Strader et al., 1999  XE "Strader et al., 1999"  ), Regional Acid
Deposition Model (RADM) aqueous phase chemistry (Chang et al., 1987  XE
"Chang et al., 1987"  ), and Carbon Bond 05 (CB05) gas-phase chemistry
module (Gery et al., 1989  XE "Gery et al., 1989"  ; ENVIRON, 2008  XE
"ENVIRON, 2008"  ). All modeling domains were modeled for the entire
year of 2005. Data from the entire year were used when looking at the
estimation of PM2.5, total Hg deposition, and visibility impacts from
the regulation.

Model Domain and Grid Resolution

The modeling analyses were performed for a domain covering the
continental United States, as shown in Figure 5-1. This domain has a
parent horizontal grid of 36 km with two finer-scale 12 km grids over
portions of the eastern and western United States. The model extends
vertically from the surface to 100 millibars (approximately 15 km) using
a sigma-pressure coordinate system. Air quality conditions at the outer
boundary of the 36 km domain were taken from a global model and did not
change over the simulations. In turn, the 36 km grid was only used to
establish the incoming air quality concentrations along the boundaries
of the 12 km grids. Only the finer grid data were used in determining
the impacts of the emission standard program changes. Table 5-1 provides
some basic geographic information regarding the photochemical model
domains.

Emissions Input Data

The emissions data used in the base year and future reference and future
emissions adjustment case are based on the 2005 v4 platform. The
emissions cases use some different emissions data than the official v4
platform to use data intended only for the rule development and not for
general use. Unlike the 2005 v4 platform, the configuration for this
modeling application included some additional HAPs and a cement kiln
sector emissions inventory more consistent with the engineering analysis
of potential control options.

The 2013 reference case is intended to represent the emissions
associated with growth and controls in that year. The U.S. EGU point
source emissions estimates for the future year reference and control
case are based on an Integrated Planning Model (IPM) run for criteria
pollutants, HCl, and Hg in 2013 (although HCl was not modeled). Both
control and growth factors were applied to a subset of the 2005 non-EGU
point and nonpoint to create the 2013 reference case. The 2002 v3.1
platform 2020 projection factors were the starting point for most of the
2013 SMOKE-based projections.

Figure 5-1.	Map of the Photochemical Modeling Domaina

a	The black outer box denotes the 36 km national modeling domain; the
red inner box is the 12 km western U.S. grid; and the blue inner box is
the 12 km eastern U.S. grid.

Table 5-1.	Geographic Elements of Domains Used in Photochemical Modeling

	Photochemical Modeling Configuration

	National Grid	Western U.S. Fine Grid	Eastern U.S. Fine Grid

Map Projection	Lambert Conformal Projection

Grid Resolution	36 km	12 km	12 km

Coordinate Center	97 deg W, 40 deg N

True Latitudes	33 deg N and 45 deg N

Dimensions	148 x 112 x 14	213 x 192 x 14	279 x 240 x 14

Vertical extent	14 Layers: Surface to 100 millibar level

The 2013 reference scenario for the cement kiln sector assumed no growth
or control for the industry from the 2005 sector emissions estimates
with the exception that facilities that closed between 2005 and 2010
were removed from the 2013 inventory. The length of time required to
conduct emissions and photochemical modeling precludes using the final
facility-specific emissions estimates based on controls implemented for
this rule. A 2013 “control” or emissions adjustment case was
developed by removing all Portland cement sector emissions from the 2013
baseline inventory. This “zero-out” of the sector creates a policy
space where potential controls would be maximized at all locations.
Since this is unrealistic, the air quality estimates from the 2013
“zero-out” or “control” case are adjusted to reflect nationwide
estimates of control percentages by pollutant. It is important to note
that the scenario without cement kilns includes the zeroing-out of
emissions from hazardous waste kilns.  Out of 181 kilns nationwide,
there are 14 hazardous waste kilns, which represent 10 to 20% of total
kiln emissions.  This leads to a slight overestimate of the reduction in
PM2.5 levels and mercury deposition.

Table 5-2.	Cement Kiln Emissions in 2005 Base and Estimated Future Year
(2013) in tons per year

Specie	2005	2013

Nitrogen Oxides	216,525	199,391

Volatile Organic Compounds	8,817	8,419

Sulfur Dioxide	158,560	149,013

PrimaryPM2.5	16,758	15,403

PM2.5 Mercury	0.8	0.7

Reactive Gas Phase Mercury	6.2	6.0

Elemental Mercury	3.8	3.6

	The air quality estimates associated with 2013 zero-out of the cement
kiln sector are adjusted nationally to reflect various options.

A 90% reduction in mercury emissions for the NSPS and NESHAP , more
stringent NSPS and NESHAP, and NESHAP only

82% reductions in SOX and 86% reductions in primarily emitted PM2.5 for
the NSPS and NESHAP, more stringent NSPS and NESHAP,  and NESHAP only

6% reductions in SOX and 5% reductions in primarily emitted PM2.5 for
NSPS only

As part of the analysis for this rulemaking, the modeling system was
used to calculate daily and annual PM2.5 concentrations, annual total Hg
deposition levels, and visibility impairment. Model predictions are used
in a relative sense to estimate scenario-specific future-year design
values of PM2.5 and ozone. Specifically, we compare a 2013 reference
scenario, a scenario without the cement kiln controls, to a 2013 control
scenario that includes the adjustments to the cement kiln sector. This
is done by calculating the simulated air quality ratios between any
particular future year simulation and the 2005 base. These predicted
ratios are then applied to ambient base year design values. The design
value projection methodology used here followed EPA guidance for such
analyses (U.S. EPA, 2007). Additionally, the raw model outputs are also
used in a relative sense as inputs to the health and welfare impact
functions of the benefits analysis. Only model predictions for Hg
deposition were analyzed using absolute model changes, although these
parameters also considered percentage changes between the control case
and two future baselines.

Model Results: Air Quality Impacts

As described above, we performed a series of air quality modeling
simulations for the continental United States to assess the impacts of
emissions adjustments to the Portland cement kiln sector. We looked at
impacts on future ambient PM2.5, total Hg deposition levels, and
visibility impairment. In this section, we present information on
current and projected levels of pollution for 2013.

This section summarizes the results of our modeling of differences in
total Hg deposition impacts in the future based on changes to the cement
kiln emissions. Specifically, we compare a 2013 reference scenario to a
2013 emissions change scenario (approximating a nationwide 90% reduction
to mercury emissions). Model results for the eastern and central United
States indicate that total Hg deposition (wet and dry forms) would be
reduced by a total of 63,518 µg/m2. A reduction of 26,047 µg/m2 is
estimated for the western United States. The reductions to total annual
Hg deposition estimated by the photochemical model show that the
reductions tend to be greatest nearest the sources.

This section summarizes the results of our modeling of annual average
PM2.5 air quality impacts in the future due to reductions in emissions
from this sector. Specifically, we compare a 2013 reference scenario to
a 2013 control scenario. The modeling assessment indicates that a
decrease up to 0.3 µg/m3 in annual PM2.5 design values is possible
given an area’s proximity to controlled sources and the amount of
reduced sulfur dioxide emissions. The median reduction over all monitor
locations is 0.09 µg/m3. An annual PM2.5 design value is the
concentration that determines whether a monitoring site meets the annual
NAAQS for PM2.5. The full details involved in calculating an annual
PM2.5 design value are given in Appendix N of 40 CFR part 50. Projected
air quality benefits are estimated using procedures outlined by EPA
modeling guidance (U.S. EPA, 2007  XE "U.S. EPA, 2007"  ).

This section summarizes the results of our modeling of 24-hour average
PM2.5 air quality impacts in the future due to reductions in emissions
from this sector. Specifically, we compare a 2013 reference scenario to
a 2013 control scenario. The modeling assessment indicates that a
decrease up to 0.5 µg/m3 in 24-hour average PM2.5 design values at most
monitor locations in the United States is possible given an area’s
proximity to controlled sources and the amount of reduced sulfur dioxide
emissions. The median reduction over all monitor locations is 0.1
µg/m3. A 24-hour PM2.5 design value is the concentration that
determines whether a monitoring site meets the 24-hour NAAQS for PM2.5.
The full details involved in calculating a 24-hour PM2.5 design value
are given in Appendix N of 40 CFR part 50. Projected air quality
benefits are estimated using procedures outlined by EPA modeling
guidance (U.S. EPA, 2007  XE "U.S. EPA, 2007"  ).

Air quality modeling conducted for this final rule was used to project
visibility conditions in 138 mandatory Class I federal areas across the
United States in 2013 (U.S. EPA, 2007  XE "U.S. EPA, 2007"  ). The level
of visibility impairment in an area is based on the light-extinction
coefficient and a unitless visibility index, called a “deciview,”
that is used in the valuation of visibility. The deciview metric
provides a scale for perceived visual changes over the entire range of
conditions, from clear to hazy. Under many scenic conditions, the
average person can generally perceive a change of one deciview. Higher
deciview values are indicative of worse visibility. Thus, an improvement
in visibility is a decrease in deciview value. The modeling assessment
indicates that a decrease up to 0.31 deciviews in annual 20% worst
visibility days is possible given an area’s proximity to controlled
sources and the amount of reduced sulfur dioxide emissions. Median
reductions are 0.01 deciviews to the 20% worst days and 20% best days
over all monitor locations.

Limitations (Uncertainties) Associated with the Air Quality Modeling

Any deficiencies with the emissions or meteorological inputs may lead to
control scenario estimates that may not fully characterize the source
contribution mix at a receptor location. This application used a
complete year of meteorology to capture the variety of meteorological
formation regimes conducive to eleveted pollution. However, it is
possible that the meteorology used for these model applications may not
represent all elevated pollution formation regimes at every individual
receptor location in the continental United States.

Benefits of Emissions Reductions

Synopsis

In this section, we provide an estimate of the monetized benefits
associated with reducing exposure to particulate matter (PM) for the
final Portland Cement NESHAP and NSPS.  The PM reductions are the result
of emission limits on PM as well as emission limits on other pollutants,
including hazardous air pollutants (HAPs) for the NESHAP and criteria
pollutants for the NSPS.  The total PM2.5 reductions are the consequence
of the technologies installed to meet these multiple limits.  These
estimates include the number of cases of avoided morbidity and premature
mortality among populations exposed to PM2.5, as well as the monetized
value of those avoided cases.  Using a 3% discount rate, we estimate the
total monetized benefits of the final Cement NESHAP and NSPS to be $7.4
billion to $18 billion in the implementation year (2013).  Using a 7%
discount rate, we estimate the total monetized benefits of the final
Cement NESHAP and NSPS to be $6.7 billion to $17 billion in the
implementation year. All estimates are in 2005$. These estimates include
the energy disbenefits associated with increased electricity usage by
the control devices.

These monetized estimates reflect EPA’s most current interpretation of
the scientific literature and several methodology updates introduced in
the proposal analysis.  In addition, these estimates incorporate an
array of improvements since the proposal, including cement
sector-specific air quality modeling data, revised
value-of-a-statistical-life (VSL), lowest measure level (LML)
assessment, qualitative benefits for ecosystems and HAPs, and mercury
deposition maps.  Higher or lower estimates of benefits are possible
using other assumptions; examples of this are provided in Figure 6-1.
Data, resource, and methodological limitations prevented EPA from
monetizing the benefits from several important benefit categories,
including benefits from reducing hazardous air pollutants, ecosystem
effects, and visibility impairment.  The benefits from reducing other
air pollutants have not been monetized in this analysis, including
reducing 4,400 tons of NOx, 5,800 tons of HCl, 5,200 tons of organic
HAPs, and 16,400 pounds of mercury each year.

Figure 6-1.	Total Monetized PM2.5 Benefits for the Final Cement NESHAP
and NSPS in 2013 a

a	This graph shows the estimated benefits at discount rates of 3% and 7%