Regulatory Impact Analysis of the Standards of
Performance for Stationary
Compression Ignition Internal Combustion Engines
-------
EPA-452/R-06-003
June 2006
Regulatory Impact Analysis of the Standards of Performance for
Stationary
Compression Ignition Internal Combustion Engines
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Air Benefits and Costs Group
Research Triangle Park, NC 27711
-------
CONTENTS
Section Page
1 Introduction 1-1
1.1 Executive Summary 1-2
1.2 Organization of this Report 1-3
2 Industry Profile 2-1
2.1 The Supply Side 2-1
2.1.1 Materials and Other Costs of Producing Equipment 2-1
2.1.1.1 Generator Sets and Welding Equipment 2-1
2.1.1.2 Pumps and Compressors 2-3
2.1.1.3 Irrigation Systems 2-5
2.1.2 Potential Changes in Material Inputs 2-5
2.2 The Demand Side 2-6
2.2.1 Generators and Welding Equipment 2-6
2.2.2 Stationary Pumps and Compressor Equipment 2-8
2.2.3 Irrigation 2-8
2.2.4 Empirical Data Elasticities 2-9
2.3 Industry Organization 2-10
2.3.1 Diesel Engines: The Equipment Firm's "Make" or
"Buy" Decision 2-10
2.3.2 Defining the Products that Constitute the Market 2-11
2.3.3 Key Firms Currently Participating in these Markets 2-11
2.3.3.1 Generators and Welders 2-11
2.3.3.2 Pumps and Compressors 2-11
2.3.3.3 Irrigation Equipment 2-12
2.3.3.4 Diesel Engines 2-13
2.3.4 Description of Small and Large Firms 2-13
2.3.5 Pricing Behavior in Equipment Markets 2-14
111
-------
2.4 Market Data 2-14
2.4.1 Baseline Quantities 2-15
2.4.2 Baseline Prices 2-16
2.4.3 Historical Data 2-16
2.4.4 Projections 2-17
3 Regulatory Program Cost Estimates 3-1
4 Economic Impact Analysis: Methods and Results 4-1
4.1 Analytical Approach 4-1
4.2 Diesel Equipment Markets Affected by the CINSPS 4-4
4.3 Overview of Partial Equilibrium Model 4-5
4.3.1 Market Supply 4-5
4.3.2 Market Demand 4-8
4.3.3 Equilibrium Solution 4-9
4.4 Results 4-9
5 Small Business Impact Analysis 5-1
5.1 Description of Small Entities Affected 5-2
5.2 Small Business Screening Analysis 5-2
5.3 Assessment 5-5
6 Benefits Analysis 6-1
6.1 Calculation of Human Health Benefits 6-1
6.2 Characterization of Uncertainty in the Benefits Analysis 6-4
6.3 General Approach 6-7
6.4 Monte-Carlo Based Uncertainty Analysis 6-8
6.5 Results of the CAIR RIA Monte Carlo Analysis 6-10
6.6 Benefits by Engine Size Category 6-12
IV
-------
6.7 Benefit-Cost Comparison 6-15
References R-l
-------
LIST OF FIGURES
Number Page
4-1 Derived Demand for Equipment from the Construction Industry 4-3
6-1 Nonroad Engine in the U.S. by State 6-2
VI
-------
LIST OF TABLES
Number Page
2-1 Motor and Generator Manufacturing: 1997 to 2002 ($billion) 2-2
2-2 Welding and Soldering Equipment Manufacturing: 1997 to 2002 ($billion) . . 2-3
2-3 Pumps and Pumping Equipment Manufacturing: 1997 to 2002 ($billion) .... 2-4
2-4 Air and Gas Compressor Manufacturing: 1997 to 2002 ($billion) 2-4
2-5 Farm Machinery and Equipment Manufacturing: 1997 to 2002 ($billion) .... 2-5
2-6 Generator Set and Welding Equipment Use by Industry: 1997 2-7
2-7 Pumps and Compressor Equipment Use by Industry: 1997 2-9
2-8 Empirical Demand Elasticity Estimates: Final Product Markets Where
Stationary Diesel Equipment is Used 2-10
2-9 Firm Market Shares by Equipment Market: 2000 2-12
2-10 Baseline Quantities for Engines and Equipment: 2015 2-15
2-11 Baseline Equipment Prices: 2015 2-16
2-12 Historical Unit Sales Data by Market: 1990-2000 2-17
2-13 Projected Annual Unit Sales for Nonemergency CI Engines: Selected Years . 2-18
3-1 Summary of Total Costs Associated with the NSPS 3-1
4-1 Markets Included in Economic Impact Model 4-6
4-2a Baseline Data: Nonemergency Stationary Diesel Generator Sets and
Welders, 2015 4-7
4-2b Baseline Data: Nonemergency Stationary Diesel Pumps and
Compressors, 2015 4-7
vn
-------
4-2c Baseline Data: Nonemergency Stationary Diesel Irrigation Systems, 2015 ... 4-7
4-3 Summary of Economic Impacts: 2015 4-10
4-4 Detailed Results for Generator and Welder Equipment: 2015 4-11
4-5 Detailed Results for Pump and Compressor Equipment: 2015 4-12
4-6 Detailed Results for Irrigation Equipment: 2015 4-12
4-7 Shift of Diesel Fuel Supply and Demand Quantities in 2015
(billion gallons) 4-13
5-1 Summary Statistics for SBREFA Screening Analysis 5-4
6-1 Estimate of Monetized Benefits in 2015 ($2000) Presuming CI Engines are
Spatially Distributed Similar to Nonroad Engines 6-4
6-2 Results of Monte Carlo Uncertainty Assessment fromCAIRRIA 6-10
6-3 Estimated Monetized Benefits Compared to Two Approaches for Estimating
the Uncertainty Range 6-12
6-4 Benefits of Emission Reductions in 2015 by Engine Size Category 6-14
Vlll
-------
SECTION 1
INTRODUCTION
The Sector Policies and Programs Division (SPPD) of the U.S. Environmental
Protection Agency's (EPA's) Office of Air Quality Planning and Standards (OAQPS) is
developing a final rule to implement New Source Performance Standards (NSPS) on
compression ignition (CI) stationary internal combustion engines by June 28, 2006. This
rule, which is in response to a consent decree and is under the authority of Section 11 l(b) of
the Clean Air Act, will address emissions for nitrogen oxides (NOX), sulfur dioxide (SO2),
particulate matter (PM), nonmethane hydrocarbons (NMHC), and carbon monoxide (CO)
from new CI engines. The requirements of the NSPS generally follow the nonroad diesel
engine rule developed by EPA's Office of Transportation and Air Quality (OTAQ) in 2004.
The NSPS contains requirements for owners, operators, and manufacturers of stationary CI
engines. The NSPS requires manufacturers to certify their 2007 and later model year
stationary nonemergency CI engines to the Tier 2, Tier 3, and Tier 4 certification emission
standards for nonroad diesel engines for all the pollutants (except SO2). This NSPS
incorporates most of the requirements of the final nonroad engine rule. All new stationary
CI engines ordered after the proposal date of this rule (June 29, 2005) and manufactured after
April 1, 2006 (or July 1, 2006, for fire pump engines) will be covered. Engine manufacturers
must follow the certification procedures and warranty, maintenance, installation, and labeling
requirements specified in the nonroad engine rule. Only certain new engines will have to put
on controls in response to this NSPS. Emergency engines have to certify to the Tier 2 and
Tier 3 standards. Nonemergency engines with engine displacement greater than or equal to
10 liters per cylinder and less than 30 liters per cylinder displacement have to certify to the
Tier 2 standards for marine engines, and engines with displacement greater than or equal to
30 liters per cylinder do not have to be certified by engine manufacturers; the owners and/or
operators of engines with displacement greater than or equal to 30 liters per cylinder have to
meet NOX and PM limits. All other engines must be certified to the final Tier 4 emission
standards for all pollutants. Such engines are hereafter referred to as "subject stationary CI
engines."
1-1
-------
To support EPA's development of these standards, EPA's Air Benefits and Costs
Group (ABCG) has conducted an economic impact analysis (EIA) to assess the potential
costs of the rule. This report documents the methods and results of this EIA.
1.1 Executive Summary
EPA estimates the NSPS will result in significant increases in market prices but small
reductions in output of diesel-powered equipment using the affected engines. The economic
approach and engineering cost approach yield approximately the same estimate of the total
change in surplus ($57 million). However, the economic approach illustrates how costs flow
through the economic system and identifies important transitory impacts on stakeholders. In
addition, it identifies the distribution of welfare losses across affected markets. The key
results of the RIA are as follows:
Engineering Costs (2002$): Total annualized costs measure the costs incurred by
affected industries annually. The average annualized costs for the rule totaled
approximately $57.1 million.
Price and Quantity Impacts: The price impacts are significant; however, demand
responses to price changes are estimated to be small.
- The average prices for affected equipment are projected to increase between 2
and 10 percent. Generator set and welding equipment markets experience the
highest relative change in baseline price (9.4 percent).
- Production/consumption remain essentially unchanged, declining by less than
0.5 percent. The analysis shows that demand responses to price changes are
small because the elasticities of demand for the final products or services that
use affected equipment and the cost share of equipment in production of these
goods and services are small.
Small Businesses: EPA performed a screening analysis for impacts on small
businesses by comparing compliance costs to baseline company revenues. When
we compare compliance costs (costs of controls, testing, and monitoring) to total
company revenue, the ratio of compliance cost to company revenue falls below 1
percent for 57 of the 60 small companies included in the screening analysis. Two
small businesses have costs between 1 and 3 percent of company sales, and one
small company has costs exceeding 3 percent of company sales. Assuming that
these small businesses or new businesses like them will be affected by the NSPS,
we do not believe that the CI NSPS will have a significant impact on a substantial
number of small entities.
Social Costs (2002$): The economic model estimates a total social cost of the rule
of $57.0 million, including $21.0 million of recordkeeping and reporting costs
1-2
-------
borne largely by emergency equipment owners to record hours of nonemergency
operation. Equipment producers pass on essentially all costs of control to
downstream markets and consumers. Total consumer surplus change is -$37.6
million. Three-quarters of these losses occur in the generator set and welding
equipment markets.
Energy Use Impacts: The NSPS will reduce emissions of SO2 by requiring the use
of ultra-low sulfur diesel (ULSD) fuel. Use of low-sulfur fuel is required
beginning in 2007, and in the baseline year of analysis (2015), new stationary CI
equipment subject to the NSPS will be required to switch to ULSD fuel (i.e., must
consume fuel meeting a 15 ppm sulfur standard). As a result, demand for ULSD
fuel will increase and demand for high-sulfur No. 2 distillate will decline. Based
on review of fuel consumption data from the nonroad rule, the size of the shift in
quantities between these markets in 2015 is very small, and EPA anticipates this
change will have negligible influence on diesel fuel prices and
production/consumption choices.
Benefits: The NSPS will yield benefits of almost $1.4 billion in 2015. This is due
the emission reductions primarily of direct PM2.5, but the reductions in SO2 and
NOx also contribute to this total. These benefits exceed the costs by more than
20 to 1.
1.2 Organization of this Report
The remainder of this report supports and details the methodology and the results of
the RIA:
Section 2 presents a profile of the affected industry.
Section 3 describes the estimated costs of the regulation.
Section 4 describes the EIA methodology and reports market welfare impacts.
Section 5 presents estimated impacts on small companies.
Section 6 present the benefits methodology and reports the results from applying
this methodology.
1-3
-------
SECTION 2
INDUSTRY PROFILE
2.1 The Supply Side
In this industry profile, we discuss related supply-side issues associated with
industries that manufacture equipment powered by diesel engines affected by the NSPS.
These industries provide three broad services: power (generator sets and welding
equipment), pumping and compression, and irrigation. In this section, we discuss two
important supply-side issues: costs of equipment production and technologies associated
with emission controls.
2.1.1 Materials and Other Costs of Producing Equipment
The U.S. Economic Census data provide production cost data by industry. Because
industry definitions are so broad, the data are limited in their ability to provide insight into
absolute expenditures levels; however, the statistics provide a reasonable proxy of the
relative importance of inputs in the manufacturing process. As discussed below, all of the
industries have similar distributions of production costs across materials, labor, and capital.
Diesel engine costs are approximately 1 to 2 percent of product value in these industries.
2.1.1.1 Generator Sets and Welding Equipment
The U.S. Economic Census classifies generator sets under "Motor and Generator
Manufacturing" (North American Industry Classification System [NAICS] 33512). This
industry comprises establishments primarily engaged in manufacturing electric motors
(except internal combustion engine starting motors), power generators (except battery
charging alternators for internal combustion engines), and motor generator sets (except
turbine generator set units). It also includes establishments rewinding armatures on a factory
basis.
2-1
-------
As shown in Table 2-1, the variable production costs include materials (including
energy), and labor. Of these categories, materials (including fuel and energy) represent about
half of the total product value. Within the materials category, diesel and semidiesel engines
account for approximately 2 percent of product value in 2002. Labor expenditures account
for approximately 13 percent, and other costs such as capital, transportation, marketing, and
markup represent the remaining 40 percent.
Table 2-1. Motor and Generator Manufacturing: 1997 to 2002 (Sbillion)
Year
2002
2001
2000
1999
1998
1997
Value of
Shipments
$9.1
$9.4
$10.0
$10.8
$11.6
$12.2
Cost of
Materials
$4.3
$4.5
$4.9
$5.4
$5.7
$6.0
Cost as a
Share of
Product
Value(%)
47%
48%
49%
50%
49%
49%
Labor
$1.2
$1.2
$1.3
$1.4
$1.5
$1.5
Cost as a
Share of
Product
Value (%)
13%
13%
13%
13%
13%
12%
Capital
$0.2
$0.2
$0.2
$0.3
$0.4
$0.3
Cost as a
Share of
Product
Value(%)
2%
2%
2%
3%
3%
2%
Source: U.S. Bureau of the Census. 2004b. "Motor and Generator Manufacturing: 2002." 2002 Economic
Census Manufacturing Industry Series. EC02-311-335312(RV). Washington, DC: U.S. Bureau of the
Census. Table 1.
The U.S. Economic Census classifies welding equipment under "Welding and
soldering equipment manufacturing" (NAICS 333992). This U.S. industry comprises
establishments primarily engaged in manufacturing welding and soldering equipment and
accessories (except transformers), such as arc, resistance, gas, plasma, laser, electron beam,
and ultrasonic welding equipment; welding electrodes; coated or cored welding wire; and
soldering equipment (except handheld).
As shown in Table 2-2, the variable production costs include materials (including
energy) and labor. Of these categories, materials (including fuel and energy) represent about
50 to 57 percent of the total product value. Within the materials category, the Census did not
report diesel and semidiesel engine costs. Labor expenditures account for approximately 11
percent, and other costs such as capital, transportation, marketing, and markup represent the
remaining 40 percent.
2-2
-------
Table 2-2. Welding and Soldering Equipment Manufacturing: 1997 to 2002 (Sbillion)
Year
2002
2001
2000
1999
1998
1997
Value of
Shipments
$3.8
$3.9
$4.2
$4.2
$4.3
$4.4
Cost of
Materials
$1.9
$2.1
$2.3
$2.3
$2.3
$2.5
Cost as a
Share of
Product
Value (%)
50%
54%
55%
55%
53%
57%
Labor
$0.4
$0.4
$0.4
$0.4
$0.4
$0.5
Cost as a
Share of
Product
Value (%)
11%
10%
10%
9%
9%
11%
Cost as a
Share of
Product
Capital Value (%)
$0.1 3%
$0.1 3%
$0.1 2%
$0.1 2%
$0.1 2%
$0.1 2%
Source: U.S. Bureau of the Census. 2004d. "Welding and Soldering Equipment Manufacturing: 2002." 2002
Economic Census Manufacturing Industry Series. EC02-311-333992(RV). Washington, DC: U.S.
Bureau of the Census. Table 1.
2.1.1.2 Pumps and Compressors
The U.S. Economic Census classifies pumps and pumping equipment under "Pump
and pumping equipment manufacturing" (NAICS 333911). This U.S. industry comprises
establishments primarily engaged in manufacturing general purpose pumps and pumping
equipment (except fluid power pumps and motors), such as reciprocating pumps, turbine
pumps, centrifugal pumps, rotary pumps, diaphragm pumps, domestic water system pumps,
oil well and oil field pumps and sump pumps.
As shown in Table 2-3, the variable production costs include materials (including
energy), and labor. Of these categories, materials (including fuel and energy) represent about
half of the total product value. Within the materials category, diesel and semidiesel engines
accounted for approximately 0.5 percent of product value in 2002. Labor expenditures
account for approximately 9 percent, and other costs such as capital, transportation,
marketing, and markup represent the remaining 43 percent.
The U.S. Economic Census classifies compressors under "Air and gas compressor
manufacturing" (NAICS 333912). This U.S. industry comprises establishments primarily
engaged in manufacturing general purpose air and gas compressors, such as reciprocating
compressors, centrifugal compressors, vacuum pumps (except laboratory), and
nonagricultural spraying and dusting compressors and spray gun units.
2-3
-------
Table 2-3. Pumps and Pumping Equipment Manufacturing: 1997 to 2002 (Sbillion)
Year
2002
2001
2000
1999
1998
1997
Value of
Shipments
$7.0
$7.4
$7.6
$7.2
$7.6
$6.7
Cost of
Materials
$3.4
$3.6
$3.7
$3.5
$4.0
$3.3
Cost as a
Share of
Product
Value (%)
49%
49%
49%
49%
53%
49%
Labor
$0.6
$0.6
$0.6
$0.6
$0.7
$0.7
Cost as a
Share of
Product
Value (%)
9%
8%
8%
8%
9%
10%
Capital
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
Cost as a
Share of
Product
Value (%)
3%
3%
3%
3%
3%
3%
Source: U.S. Bureau of the Census. 2004c. "Pump and Pumping Equipment Manufacturing: 2002." 2002
Economic Census Manufacturing Industry Series. EC02-311-333911(RV). Washington, DC: U.S.
Bureau of the Census. Table 1.
As shown in Table 2-4, the variable production costs include materials (including
energy), and labor. Of these categories, materials (including fuel and energy) represent 55 to
60 percent of the total product value. Within the materials category, diesel and semidiesel
engines account for approximately 1.8 percent of product value in 2002. Labor expenditures
account for approximately 8 percent, and other costs such as capital, transportation,
marketing, and markup represent the remaining 35 percent.
Table 2-4. Air and Gas Compressor Manufacturing: 1997 to 2002 (Sbillion)
Year
2002
2001
2000
1999
1998
1997
Value of
Shipments
$4.8
$5.6
$6.2
$5.7
$5.7
$5.6
Cost of
Materials
$2.7
$3.0
$3.3
$3.0
$3.1
$3.1
Cost as a
Share of
Product
Value(%)
56%
54%
53%
53%
54%
55%
Labor
$0.4
$0.4
$0.4
$0.4
$0.5
$0.5
Cost as a
Share of
Product
Value (%)
8%
7%
6%
7%
9%
9%
Capital
$0.2
$0.2
$0.2
$0.2
$0.2
$0.2
Cost as a
Share of
Product
Value(%)
4%
4%
3%
4%
4%
4%
Source: U.S. Bureau of the Census. 2004c. "Pump and Pumping Equipment Manufacturing: 2002." 2002
Economic Census Manufacturing Industry Series. EC02-311-333911(RV). Washington, DC: U.S.
Bureau of the Census. Table 1.
2-4
-------
2.1.1.3 Irrigation Systems
The U.S. Economic Census classifies irrigation equipment under "Farm Machinery
and Equipment Manufacturing" (NAICS 333111). This U.S. industry comprises
establishments primarily engaged in manufacturing agricultural and farm machinery and
equipment, and other turf and grounds care equipment, including planting, harvesting, and
grass mowing equipment (except lawn and garden-type).
As shown in Table 2-5, the variable production costs include materials (including
energy), and labor. Of these categories, materials (including fuel and energy) represent 52 to
57 percent of the total product value. Within the materials category, diesel and semidiesel
engines accounted for approximately 2.2 percent of product value in 2002. Labor
expenditures account for approximately 9 percent, and other costs such as capital,
transportation, marketing, and markup represent the remaining 39 percent.
Table 2-5. Farm Machinery and Equipment Manufacturing: 1997 to 2002 (Sbillion)
Year
2002
2001
2000
1999
1998
1997
Value of
Shipments
$14.7
$14.1
$13.5
$11.8
$16.5
$16.0
Cost of
Materials
$7.7
$7.6
$7.7
$6.4
$8.5
$8.4
Cost as a
Share of
Product
Value (%)
52%
54%
57%
54%
52%
53%
Labor
$1.3
$1.3
$1.4
$1.3
$1.5
$1.6
Cost as a
Share of
Product
Value (%)
9%
9%
10%
11%
9%
10%
Capital
$0.3
$0.3
$0.3
$0.3
$0.4
$0.5
Cost as a
Share of
Product
Value (%)
2%
2%
2%
3%
2%
3%
Source: U.S. Bureau of the Census. 2004a. "Farm Machinery and Equipment Manufacturing: 2002." 2002
Economic Census Manufacturing Industry Series. EC02-311-3331 ll(RV). Washington, DC: U.S.
Bureau of the Census. Table 1.
2.1.2 Potential Changes in Material Inputs
Under the NSPS, subject nonemergency stationary CI internal combustion engines
must be certified to meet Tier 4 emission standards for NOX, NMHC, PM, and CO (Parise,
2005a, 2005b). To address emissions of these pollutants, several changes in the
manufacturing design and/or material inputs have been considered. Among those are the
following:
2-5
-------
catalyzed diesel particulate filters (CDPFs): Tier 4 emission standards for engines
greater or equal 25 horsepower (hp) are based on the use of this control
technology. It is estimated CDPFs will reduce PM emissions by more than 90
percent, and also reduce NMHC and CO emissions by a significant amount.
NOX adsorbers: Tier 4 emission standards for engines greater or equal to 75 hp are
based on the use of this control technology. It is estimated NOX adsorbers will
reduce NOX emissions by 90 percent.
lower-sulfur fuel: the owners and operators of the subject stationary CI internal
combustion engines will be required to use diesel fuel containing 500 parts per
million (ppm) sulfur or less by October 1, 2007. This requirement will be lowered
to 15 ppm (ultra-low sulfur diesel or ULSD) by October 1, 2010.
2.2 The Demand Side
The demand for diesel equipment is derived from consumer demand for the services
and products the equipment provides. We describe uses and consumers of these products as
well as provide examples of substitution possibilities in consumption. Results of econometric
estimates of elasticities for downstream service and product markets are included as well.
2.2.1 Generators and Welding Equipment
Generator sets provide power for prime, standby, and peaking power industrial,
commercial, and communications facilities. Prime power units typically have lower
horsepower ratings while standby units have higher horsepower ratings. Potential substitutes
including natural gas generation units and a recent industry study suggests over 1/3 of 1,000
hp or higher sets use fuels other than diesel (Rhein Associates, 2002). However,
diesel-engine generators appear to be still preferred in remote/offsite agriculture and
construction uses (EPA, 2004).
EPA's profile of nonroad welding machines found that similar substitution issues
exist for on-site versus remote locations (EPA, 2004). On-site facility welding can be
accomplished with electric (AC or battery-operated) units, an arrangement not possible for
off-site uses. Gas welders provide a third option, one that is not dependent on a local
infrastructure.
In Table 2-6, we use the latest detailed Benchmark Input-Output Data report by the
Bureau of Economic Analysis (U.S. BE A, 2002) to identify industries that use generators and
welding equipment. Note that these data include all types of generators and welding
2-6
-------
Table 2-6. Generator Set and Welding Equipment Use by Industry: 1997
Direct
Commodity IO-CodeDetail_I-O Industry Use Requirements
Code Description Code IO-CodeDetail_I-O Description Value Coefficients"
335312 Motor and generator
manufacturing
333415 AC, refrigeration, and forced air 1,364.2 6.23%
heating
811300 Commercial machinery repair and 453.4 1.38%
maintenance
333911 Pump and pumping equipment 451.4 6.97%
manufacturing
335312 Motor and generator manufacturing 408.7 3.46%
334119 Other computer peripheral 398.7 1.67%
equipment manufacturing
333992 Welding and soldering
equipment
manufacturing
811300
332312
811400
333298
230220
Commercial machinery repair and
maintenance
Fabricated structural metal
manufacturing
Household goods repair and
maintenance
All other industrial machinery
manufacturing
Commercial and institutional
buildings
408.3
170.5
140.9
107.3
61
1.24%
1.13%
0.57%
1.34%
0.03%
Note: The data include generators and welding equipment that is not affected by the proposed NSPS.
"These values show the amount of the commodity required to produce $1.00 of the industry's output.
Source: U.S. Bureau of Economic Analysis. 2002. 1997 Benchmark Input-Output Accounts: Detailed Make
Table, Use Table and Direct Requirements Table. Tables 4 and 5.
equipment and are not restricted to stationary diesel-powered equipment affected by the
NSPS. For all generators and welding and soldering equipment, NAICS 33415 (AC,
refrigeration, and forced air heating) is the largest users of generators, and other industries
that are relatively large demanders include pumping equipment manufacturing, generators
and welders manufacturing, and machinery repair. NAICS 811300 (Commercial machinery
repair and maintenance) is the largest user of welding and soldering equipment; other major
users include fabricated metal manufacturing, household goods repair, and other industrial
machinery manufacturing.
2-7
-------
2.2.2 Stationary Pumps and Compressor Equipment
The construction industry is an important consumer of pump and compressor
equipment; as a result, demand for this equipment fluctuates with construction activity. Oil
field drilling and well servicing applications are primary consumers of high horsepower
equipment such as drills and compressors. Demand in these areas is influenced by changes in
fuel prices and changes in overall economic activity.
In Table 2-7, we use the latest detailed Benchmark Input-Output Data report by the
Bureau of Economic Analysis (U.S. BE A, 2002) to identify industries that use pumps and
compressor equipment. Again, these data include all types of pumps and compressor
equipment and are not restricted to stationary diesel-powered equipment affected by the
NSPS. Nonagricultural demanders of pumps and pumping equipment include railway
transportation, nonfarm single family homes, and semiconductor machinery manufacturing.
Major demanders of compressor equipment include construction of single-family homes and
additions, and manufacturing of compressor equipment, motor vehicle parts, and plastic
products.
2.2.3 Irrigation
Demand for irrigation equipment is driven by farm operators' supply decisions,
optimal replacement considerations, and climate and weather conditions. The National
Agriculture Statistics Service (NASS) 2003 Farm and Ranch Irrigation Survey
(USDA-NASS, 2004) shows the top five states ranked by total acres irrigated are California,
Nebraska, Texas, Arkansas, and Idaho. The survey showed that approximately 500,000
pumps were used on U.S. farms in 2003 with energy expenses totaling $1.5 billion dollars.
Electricity is the dominant form of energy expense for irrigation pumps, accounting for 60
percent of energy expenses. Diesel fuel is second (18 percent), followed by natural gas (18
percent), and other forms of energy (4 percent). The report also notes that 411 pumps were
powered by solar or other renewable energy sources. In 2003, farmers and ranchers spent
approximately $13,000 per farm on irrigation investments.
2-8
-------
Table 2-7. Pumps and Compressor Equipment Use by Industry: 1997
Direct
Commodity IO-CodeDetail_I-O Industry Use Requirement
Code Description code IO-CodeDetail_I-O Description Value s Coefficients
333911 Pump and pumping
equipment manufacturing
333912 Air and gas compressor
manufacturing
482000 Rail transportation 508.4 1.34%
230110 New residential 1-unit structures, 208.1 0.12%
nonfarm
333295 Semiconductor machinery 173.7 1.64%
manufacturing
230210 Manufacturing and industrial 92.6 0.34%
buildings
213111 Drilling oil and gas wells 77.7 0.82%
230110 New residential 1-unit structures, 211.9 0.12%
nonfarm
333912 Air and gas compressor 115.0 2.22%
manufacturing
230130 New residential additions and 56.1 0.10%
alterations, nonfarm
336300 Motor vehicle parts manufacturing 50.0 0.03%
32619A Plastics plumbing fixtures and all 50.0 0.08%
other plastics products
Note: The data includes pumps and compressor equipment that is not affected by the NSPS.
"These values show the amount of the commodity required to produce one dollar of the industry's output.
Source: U.S. Bureau of Economic Analysis. 2002. 1997 Benchmark Input-Output Accounts: Detailed Make
Table, Use Table and Direct Requirements Table. Tables 4 and 5.
2.2.4 Empirical Data Elasticities
Stationary diesel equipment is used in the production of a variety of goods and
services. Economic theory suggests the demand for stationary diesel equipment is strongly
influenced by the elasticity of final demand for the product or service the equipment is used
to produce. EPA's nonroad diesel economic analysis (EPA, 2004) identified key markets
where stationary diesel equipment was used and econometrically estimated demand
elasticities for these markets. Demand elasticities measure the percent change in quantity
demanded in response to a percent change in price. As shown in Table 2-8, final
product/service demand is inelastic, that is, not very responsive to changes in prices. For
example, a one percent
2-9
-------
Table 2-8. Empirical Demand Elasticity Estimates: Final Product Markets Where
Stationary Diesel Equipment is Used
Stationary Gen Sets
and Welders
Stationary Pumps and
Compressors
Stationary Irrigation
Systems
Demand Characterization
Final Product Market and
Demand Elasticity (r|D)
Derived demand
Manufacturing
-0.6
Derived demand
Manufacturing
-0.6
Derived demand
Agriculture
-0.2
EPA (2004)
Econometric estimate
(inelastic)
EPA (2004)
Econometric estimate
(inelastic)
EPA (2004)
Econometric estimate
(inelastic)
increase in agricultural prices leads to only a 0.2 percent decline in demand for agricultural
output.
2.3 Industry Organization
To estimate the economic impacts of a regulation, it is important to have an
understanding of industry organization. We discuss key issues in this industry, identify firms
and small businesses participating in the market, and discuss issues related to pricing
behavior in these markets.
2.3.1 Diesel Engines: The Equipment Firm's "Make " or "Buy " Decision
Vertically integrated firms own a combination of "upstream" and "downstream"
production operations; for example, vertically integrated diesel equipment manufactures
make the engines used in equipment rather than buy diesel engines from independent diesel
engine manufacturers. Although there are several reasons firms may choose this structure,
two frequently cited benefits are reducing transaction costs associated with input purchases
and taking advantage of technological economies that arise through integrated production
structures (Viscusi, Vernon, and Harrington, 1992). A review of the Power Systems Research
(PSR) data for 2000 shows that vertical operations are more likely to occur in diesel-powered
generator set and irrigation system industries relative to the other directly affected markets.
Approximately 30 to 40 percent of manufactured diesel engines in these equipment markets
were consumed internally by integrated manufacturers in these applications.
2-10
-------
2.3.2 Defining the Products that Constitute the Market
To assess market structure, we need a clear definition of the "market(s)" along
geographic and product dimensions. There are two distinctive product characteristics we use
to define the products. First, consumers are more likely to view products with similar
horsepower ratings as close substitutes, so it seems reasonable to delineate the markets by
horsepower categories defined in the engineering cost analysis and by EPA (2004). Second,
after reviewing the EPA industry characterization for the Clean Air Nonroad Diesel Rule
(EPA, 2004), the California Air Resources Board's (CARB's) Staff Report for the Airborne
Toxic Control Measure for Stationary Compression-Ignition Engines (CARB, 2003), and a
private industry study of the diesel engine markets (Rhein Associates, 2002), we have
identified three broad nonemergency stationary diesel equipment applications where buyers
and sellers would generally be unwilling to shift consumption/production among groups.
These include generator sets and welding equipment, pumps and compressors, and irrigation
systems. Market data associated with these applications are discussed in Section 2.4.
2.3.3 Key Firms Currently Participating in these Markets
EPA identified key firms in each of the markets using market share data from 2000
(PSR, 2004). As discussed below, sales are concentrated among a few top firms identified in
each market (see Table 2-9).
2.3.3.1 Generators and Welders
Sales leaders in the diesel-powered generator set market include two Korean firms
(Korean GenSets and Daewoo Heavy Industries & Machinery Ltd.) and Honda Motor
Company. Large public firms Lincoln Electric and Illinois Tool Works dominate sales of
diesel-powered welding equipment. Hoovers identifies Lincoln Electric as a leading
manufacturer of arc-welding, cutting products, and welding supplies including arc-welding
power sources, automated wire-feeding systems, and consumable electrodes for arc-welding.
Its major competitor is Illinois Tool Works, a diversified company that makes products in the
automotive, construction, paper products, and food and beverage industries (Hoovers, 2005).
2.3.3.2 Pumps and Compressors
Leaders in the pump sector include a small privately owned business, Pacer Pumps,
and a public company, Gorman-Rupp Company. Gorman-Rupp makes pumps used in a
variety of industries, including agriculture and construction work, sewage treatment,
2-11
-------
Table 2-9. Firm Market Shares by Equipment Market: 2000
Market Share
Pumps
Pacer Pumps 13%
Gorman-rupp Company 11%
Godwin Pumps of America 9%
Air and Gas Compressors
Ingersoll-rand 43%
Atlas Copco ab 17%
SulliarCorp. 13%
Hydraulic Power Units
Hydra-tech Pumps 26%
Griffin Dewatering Corporation 14%
Blount Inc. 14%
Generator Sets
Korean Gen-sets 13%
Daewoo Heavy Ind. 11%
Honda Motor Company Ltd. 11 %
Welders
Illinois Tool Works Inc. 43%
Lincoln Electric 55%
Irrigation Sets
Springfield Remanufacturing 28%
Deere & Company 27%
Tradewinds Power Corporation 19%
Source: Power Systems Registry (PSR). 2004. OELink. .
petroleum refining, agriculture, and fire fighting, as well for HVAC and military applications
(Hoovers, 2005). The top three pump makers accounted for only one-quarter of pump sales
in 2000. Industrial machinery giant Ingersoll-Rand led sales in the air and gas compressor
market in 2000. Atlas Copco AB and Sulliar Corporation (a division of Hamilton Sundstrand
Corporation) are other key players in this market.
2.3.3.3 Irrigation Equipment
Sales leaders in this market include Springfield Remanufacturing, Deere and
Company, and Tradewinds Power Corporation. Deere & Company is one of the two largest
makers of farm equipment (Hoovers, 2005). Tradewinds Power is a small private firm that
makes a range of engines for the power generation industry as well as power units, pump
sets, and transmissions for industrial and irrigation use (Hoovers, 2005). Together, these
2-12
-------
three companies account for approximately 75 percent of the diesel-powered irrigation
system market in 2000.
2.3.3.4 Diesel Engines
Engine production leaders for these markets include well-known domestic names
Deere and Company, Caterpillar, and Cummins. Kubota Engine America, a subsidiary of
Japanese Kubota Corporation, is another major seller in this market, primarily of small
engines in industrial, agricultural, construction, and power generation equipment. Other
Asian competitors are Korean companies Kukje Machinery Co. Ltd and Daewoo Heavy
Industries & Machinery Ltd. European competitors include German companies Deutz AG
and Motorenfabrik Hatz, which owns North American subsidiary Hatz Diesel of America,
Inc. Small businesses in this industry include Wisconsin Motors (owned by V&L Tools).
Wisconsin Motors produces diesel engines for a small niche market and served as a Small
Entity Representative (SER) during the Small Business Advocacy Review Panel process for
the Clean Air Nonroad Diesel Rule (EPA, 2004, p 11-8).
2.3.4 Description of Small and Large Firms
Small entities include small businesses, small organizations, and small governmental
jurisdictions. For purposes of assessing the impacts of the CINSPS, a small entity is defined
as
a small business whose parent company has fewer than 1,000 employees (for
NAICS 335312 [Motor and Generator Manufacturing]) or 500 employees (for
NAICS 333911 [Pump and Pumping Equipment Manufacturing], NAICS 333912
[Air and Gas Compressor Manufacturing], and NAICS 333992 [Welding and
Soldering Equipment Manufacturing]).
a small governmental jurisdiction that is a government of a city, county, town,
school district, or special district with a population of fewer than 50,000.
a small organization that is any not-for-profit enterprise, which is independently
owned and operated and is not dominant in its field.
To identify sales and employment characteristics of affected parent companies, we
use a company database developed for small business analysis of the Clear Air Nonroad
Diesel Rule (EPA, 2004). Since the rule does not affect all companies included in the
database, the analysis only includes companies that produce the following types of
equipment:
2-13
-------
Pumps and compressors (Pump and Pumping Equipment Manufacturing [NAICS
333911] or Air and Gas Compressor Manufacturing [NAICS 333912])
Welders and generators (Motor and Generator Manufacturing [NAICS 335312] or
Welding and Soldering Equipment Manufacturing [NAICS 333992])
We identified 60 small companies and 44 large companies with sales data. Using the data,
we found 62 companies manufacture products that are included in the Pump and Pumping
Equipment Manufacturing (NAICS 333911) or Air and Gas Compressor Manufacturing
(NAICS 333912) industries and 30 companies manufacture products included in the Motor
and Generator Manufacturing (NAICS 335312) or Welding and Soldering Equipment
Manufacturing (NAICS 333992) industries. The remaining 12 companies manufacture
equipment in both PSR segments. The average small firm's annual sales are approximately
$30 million compared to nearly $6 billion for large firms. The average small firm employed
100 people while the average large firm employed over 20,000 people.
2.3.5 Pricing Behavior in Equipment Markets
In the Clean Air Nonroad Diesel Rule, EPA argued that the competitive assumption is
"widely accepted economic practice for this type of analysis (see, for example, EPA [2000],
p. 126), especially in cases where existing analysis suggests that mitigating factors limit the
potential for raising price above marginal cost" (EPA, 2004, p. 10-5). The mitigating factors
cited in the nonroad rule include significant levels of domestic and international competition
and significant excess capacity enabling competitors to quickly respond to changes in price.
In addition, there were no indications of barriers to entry or evidence of high levels of
strategic behavior in the price and quantity decisions of the firms. Our review of the
available industry data suggests similar conditions are likely to be present in the markets
included in this analysis.
2.4 Market Data
To perform the economic impact analysis, we compare baseline market conditions for
affected markets with counterfactual conditions produced under a new policy. This
comparison requires developing a dataset for generator sets and welders, pumps and
compressors, and irrigation equipment markets for the year 2015, the baseline year of
analysis. In this section, we describe elements of the dataset and include information on
quantities and prices for these three markets together with historical and projected data.
2-14
-------
2.4.1 Baseline Quantities
EPA has estimated that there will be approximately 16,000 new stationary
nonemergency CI engines produced in the United States in 2015. This is 20 percent of the
total population of stationary CI engines (which is 82,000). The other stationary CI engines
are used for emergency applications (such as producing power when electric generation from
the local utility is interrupted, pumping water in case of fire or flood). The majority (10,200,
or 62 percent) of stationary nonemergency CI engines will be used in the generator sets and
welders equipment market, with 32 percent of the engines used in the pumps and
compressors market, and 6 percent used in the irrigation equipment market (see Table 2-10).
Under the assumption that there is one-to-one correspondence between engines and
equipment, it is reasonable to assume that these statistics reflect the equipment population as
well.
Table 2-10. Baseline Quantities for Engines and Equipment: 2015
Stationary Nonemergency
Generator Sets and Welders
51-75 hp
1,066
76-100 hp
1,532
101-175 hp
2,479
>176 hp
5,132
Total
10,210
Stationary Nonemergency
Pumps and Compressors
51-75 hp
693
76-100 hp
1,343
101-175 hp
1,111
>176 hp
2,011
Total
5,158
Stationary Nonemergency
Irrigation Systems
50-100 hp
272
101-600 hp
707
Total
979
Grand Total
16,347
Source: Sorrels, Larry, EPA, e-mail to Ruth Mead, ERG and Katherine Heller and Brooks Depro, RTI
International. CI engine population by NAICS. April 20, 2005.
2.4.2 Baseline Prices
For the Clean Air Nonroad Diesel Rule, EPA collected price data for the nonroad
diesel equipment from a variety of sources, including the U.S. General Services
Administration and various Web sites. A relationship between price and horsepower was
obtained using a linear regression technique (see Guerra [2005], p. 2). Using these linear
equations and median horsepower for each market, we estimated national prices for
stationary nonemergency CI equipment. As shown in Table 2-11, estimates range from
2-15
-------
$7,200 to $86,200 and vary among applications. In each horsepower category, prices for
small horsepower pumps and compressors and irrigation systems are typically higher than
those for generator sets and welders.
2.4.3 Historical Data
Despite significant declines in 2000 sales, generator sets and welding markets grew at
an average annual rate of 9 percent between 1990 and 2000. As shown in Table 2-12, this
growth was led by low horsepower equipment (less than 100 hp). Irrigation equipment
showed similar strong growth rates during the period (7 percent), followed by pumps and
compressors.
Table 2-11. Baseline Equipment Prices: 2015
Stationary Nonemergency Stationary Nonemergency Pumps Stationary Nonemergency
Generator Sets and Welders and Compressors Irrigation Systems
51-75 hp
$7,231
76-100 hp
$10,101
101-175 hp
$15,840
>176 hp
$44,535
51-75 hp
$13,960
76-100 hp
$19,499
101-175 hp
$30,578
>176 hp
$86,192
50-100 hp
$42,247
101-600 hp
$75,815
Note: Calculated computed using Guerra (2005) and midpoint value of horsepower range.
2-16
-------
Table 2-12. Historical Unit Sales Data by Market: 1990-2000
Stationary
50-75
76-100
101-175
>176
Total
Stationary
50-75
76-100
101-175
>176
Total
Stationary
50-100
101-600
Total
2000
1999
Nonemergency
762
993
1,773
2,926
6,454
1,637
1,355
2,179
2,591
7,762
Nonemergency
289
494
427
993
2,203
357
460
459
939
2,216
Nonemergency
81
663
744
72
620
692
1998
Generator
658
525
1,247
2,588
5,019
1997
Sets and
466
434
1,081
2,093
4,074
1996
Welders
279
315
886
1,485
2,965
1995
361
342
1,122
1,792
3,617
1994
303
289
1,137
1,708
3,437
1993
282
238
1,133
1,607
3,260
1992
336
206
928
1,522
2,991
1991
354
249
934
1,577
3,114
1990
304
164
774
1,415
2,656
Pumps and Compressors
354
421
508
875
2,158
Irrigation
62
584
646
334
384
533
784
2,036
Systems
65
528
592
285
326
590
823
2,024
75
511
585
285
321
604
809
2,017
72
477
549
254
289
517
658
1,718
60
460
521
203
260
456
566
1,485
57
410
468
204
228
436
487
1,355
65
360
425
254
258
531
606
1,649
70
328
399
297
266
504
712
1,780
63
293
356
Source: Sorrels, Larry, EPA, e-mail to Ruth Mead, ERG and Katherine Heller and Brooks Depro, RTI
International. CI engine population by NAICS. April 20, 2005.
2.4.4 Projections
Using 10-year growth data for engines (Sorrels, 2005), the Agency estimated that
stationary nonemergency CI engine markets will continue to grow at historical rates (see
Table 2-13). The total affected population is estimated to grow from 11,700 to 16,300
engines between 2005 and 2015.
2-17
-------
Table 2-13. Projected Annual Unit Sales for Nonemergency CI Engines: Selected Years
Hp Range
50-75
75-100
100-175
175-300
300-600
600-750
750-1,200
1,200-3,000
Over 3,000
Total
2005
1,314
2,068
3,148
3,029
1,203
172
391
382
32
11,738
2010
1,551
2,593
3,701
3,710
1,368
189
453
446
32
14,042
2015
1,788
3,119
4,255
4,391
1,532
205
515
510
32
16,347
Source: Sorrels, Larry, EPA, e-mail to Ruth Mead, ERG and Katherine Heller and Brooks Depro, RTI
International. CI NSPS Cost Impacts 05-26-05. June 1, 2005.
2-18
-------
SECTION 3
REGULATORY PROGRAM COST ESTIMATES
Under the NSPS, subject nonemergency stationary CI internal combustion engines
must be certified to meet Tier 4 emission standards for NOX, NMHC, PM, and CO (Parise,
2005a, 2005b). To address emissions of these pollutants, several changes in the
manufacturing design and/or material inputs have been considered. Among those are the
following:
CDPFs: Tier 4 emission standards for engines greater than or equal to 25 hp are
based on the use of this control technology. It is estimated CDPFs will reduce PM
emissions by more than 90 percent and also reduce NMHC and CO emissions by
a significant amount.
NOX adsorbers: Tier 4 emission standards for engines greater or equal to 75 hp are
based on the use of this control technology. It is estimated NOX adsorbers will
reduce NOX emissions by 90 percent.
The total estimated costs of the NSPS for stationary CI engines are presented in Table
3-1. The capital cost of control of the NSPS is estimated to be $67 million in 2015, the model
year for which stationary CI internal combustion engines would have to meet final Tier 4
emission standards. The annualized cost of control of the NSPS is estimated to be $36
million in 2015. The total annualized cost including accumulated reporting costs in 2015 is
estimated to be $57.1 million.
Table 3-1. Summary of Total Costs Associated with the NSPS
Type of Cost
Capital control cost
Annual control cost
Reporting
Total annualized cost
2011
31.0
4.4
10.2
15.4
2012
40.1
10.4
12.5
23.8
Total
2013
42.4
16.8
15.0
32.7
Costs ($million)
2014
62.7
26.1
17.5
44.5
2015
66.8
36.1
20.0
57.1
2016
68.6
46.3
23.0
70.1
2017
70.3
56.8
25.6
83.4
3-1
-------
SECTION 4
ECONOMIC IMPACT ANALYSIS: METHODS AND RESULTS
The EIA uses a combination of theory and simulation modeling to evaluate potential
behavior changes associated with a new regulatory program. The goal is to estimate the
impact of the regulatory program on producers and consumers. For this analysis, we chose to
use a partial equilibrium (PE) modeling approach for the affected markets for two reasons.
First, although these commodities may be an intermediate good used in the market, price
changes that will occur in these markets will be small enough that production and
consumption choices in related markets will be approximately unaffected. Similarly, changes
in household income that could affect the demand for other products and services are
expected to be small enough that they are not explicitly modeled.1 In addition, an
intermediate run approach is used in this EIA because it is likely that producers have
flexibility to adjust selected factors of production but some of the factors (e.g., capital) still
remain fixed. This lack of resource mobility captures potential transitory impacts on
producers during the analysis period.
4.1 Analytical Approach
The CINSPS and Clean Air Nonroad Diesel rule affect similar markets, so their
impacts can be modeled in similar ways. Both rules increase the costs of manufacturing
engines, the demand for which derives from the demand for the equipment in which the
engines will be used. However, size and other differences between the rules led to the
development of a separate model for the CINSPS analysis. For example, the Nonroad Diesel
Economic Impact Model (NDEIM) models derive the demand for equipment and engines
from those "final" application markets; in the CI NSPS EPA simplified this approach and
only models diesel equipment markets that use affected engines in their production process.
EPA characterizes the response of equipment demand to changes in equipment prices with an
Mas-Colell et al. (1995) and Vives (1987) provide a technical discussion of these issues.
4-1
-------
elasticity parameter.2 We discuss and compare NDEEVTs characterization of equipment
demand responses and the CINSPS method below.
NDEIM's relationships explicitly link the demand for engines and equipment to the
market behavior in an "application" market. A demand curve specified in terms of its
downstream consumption is referred to as a derived demand curve (see Figure 4-1 for a
graphical illustration of how a derived demand curve is identified). Consider an event in the
equipment market that causes the price of equipment to increase by AP (such as an increase
in the price of engines). This increase in the price of equipment will cause the supply curve
in the application market to shift, leading to a decreased quantity of activity (AQC). The
change in activity leads to a decrease in the quantity demanded for equipment (AQE). The
new point (QE - AQE, P + AP) traces out the derived demand curve. The supply and demand
function in the application market are needed to identify the derived demand in the
construction equipment market.
An alternative approach to identifying the demand response is to derive an expression
for the derived demand elasticity parameter using economic theory. Economist Alfred
Marshall identified four factors that influence an industry's price elasticity of demand for a
factor (Hicks, 1963; Layard and Walters, 1978). We restate these "rules" in terms of the
industry elasticity of demand for equipment (£IE) and the two factor production functions
(equipment and labor). The (absolute) elasticity of demand for equipment in industry varies
directly with
the (absolute) elasticity of demand for the product or service the industry
produces (r|D),
the cost share of equipment (VE) in production,
the elasticity of supply of other factors (i.e., labor) (r|s), and
the elasticity of substitution between equipment and other factors (OEL).
By doing this, we implicitly assume engine manufacturers fully pass on the control costs up the supply chain to
the equipment market. The elasticity parameters and results of the numerical simulations in the nonroad
economic impact analysis support the use of this simplification.
4-2
-------
Unit Price of
Construction
Construction
Output
Price Equip merit
AP
t
-Y
AQr
Derived
Demand
Equipment
Output
APrice
Equipment
Upward Shift
Construction
Supply Curve
AQ
C
AQC
Figure 4-1. Derived Demand for Equipment from the Construction Industry
4-3
-------
It can be shown that if the production function exhibits constant returns to scale with
fixed factor proportions technology (i.e., OEL = O)3, price elasticity of demand for equipment
can be expressed as a function of the selected variables included in Marshall's rules (Hicks,
1963; Layard and Walters, 1978):
D
1 -il-v,, ixT-
* s
This expression can be further simplified by assuming the supply of other factors is
perfectly elastic (r|s = °°). This simplification is appropriate because we expect the changes in
production in the equipment market to be small enough that they do not influence prices in
other factor markets:
£iE = vExnD. (4.2)
Therefore, we can estimate this behavioral parameter with cost share data and final
product/service demand elasticities.
4.2 Diesel Equipment Markets Affected by the CI NSPS
EPA identified three national competitive markets for the economic impact
analysisan approach consistent with the geographic definition and pricing behavior
assumptions for nonroad diesel equipment markets within NDEEVI. In selecting the
competitive model, EPA argued that the competitive assumption is "widely accepted
economic practice for this type of analysis (see, for example, EPA [2000], p. 126), especially
in cases where existing analysis suggests that mitigating factors limit the potential for raising
price above marginal cost" (EPA, 2004, p. 10-5). The mitigating factors cited in the nonroad
rule include significant levels of domestic and international competition and significant
excess capacity enabling competitors to quickly respond to changes in price. In addition,
there were no indications of barriers to entry or evidence of high levels of strategic behavior
in the price and quantity decisions of the firms. Our preliminary review of the available
The fixed proportions technology assumption is reasonable for this industry. For interested readers, the
expression for the more complicated formula that includes the elasticity of substitution is included in J.R.
Hicks' Theory of Wages, pp. 243-244. A similar expression is reported in Layard and Walters (1978,
p. 267).
4-4
-------
industry data and literature suggests similar conditions are likely to be present in the markets
included in this analysis.
We used two distinctive product characteristics to define the products that constitute
the markets. First, consumers are more likely to view products with similar horsepower
ratings as close substitutes, so it seems reasonable to delineate the markets by horsepower
categories defined in the engineering cost analysis and by EPA (2004). Second, after
reviewing the EPA industry characterization for the Clean Air Nonroad Diesel Rule (EPA,
2004), the California Air Resources Board's (CARB's) Staff Report for the Airborne Toxic
Control Measure for Stationary Compression-Ignition Engines (CARB, 2003), and a private
industry study of the diesel engine markets (Rhein Associates, 2002), EPA identified three
broad nonemergency stationary diesel markets where buyers and sellers in the market would
be unwilling to shift consumption/production among these products on a large scale.
To characterize behavioral responses in these three markets, EPA uses existing model
elasticity parameters available from NDEIM model. The U.S. Bureau of Economic Analysis
(2002) and U.S. Department of Agriculture (2004) provide data that allow us to approximate
associated cost shares in final application markets. Table 4-1 provides the baseline data set
for the economic impact analysis, and Section 4.3 describes the partial equilibrium model
equations used for the economic impact analysis.
4.3 Overview of Partial Equilibrium Model
We illustrate our approach for estimating market-level impacts using a numerical
simulation model. Our method involves specifying a set of nonlinear supply and demand
relationships for the three diesel equipment markets identified in Table 4-1, simplifying the
equations by transforming them into a set of linear equations, and then solving the
equilibrium system of equations (see, for example, Fullerton and Metcalfe [2002]).
4. 3. 1 Market Supply
First, we consider the formal definition of the elasticity of supply with respect to
changes in own price:
£ = . (4.3)
dp Ip
4-5
-------
Table 4-1. Markets Included in Economic Impact Model
Power Systems Research
(PSR) application
descriptions
Geographic scope
Product groupings
Firm behavior
Baseline engine population
Baseline year
Supply elasticity
Demand characterization
Stationary Gen Sets
and Welders
Generator sets, welders
National
4 horsepower
categories
Perfect competition
See Table 4-2a
2015
2.9
EPA (2004)
Derived demand
Stationary Pumps and
Compressors
Air compressors, gas
compressors, hydro
power units, pressure
washers, pumps
National
5 horsepower
categories
Perfect competition
See Table 4-2b
2015
2.8
EPA (2004)
Derived demand
Stationary Irrigation
Systems
Irrigation systems
National
2 horsepower
categories
Perfect competition
See Table 4-2c
2015
2.1
EPA (2004)
Derived demand
Final product market and
demand elasticity (r|D)
Manufacturing
-0.6
EPA (2004)
Econometric estimate
(inelastic)
Manufacturing
-0.6
EPA (2004)
Econometric estimate
(inelastic)
Agriculture
-0.2
EPA (2004)
Econometric estimate
(inelastic)
Cost share (VE)
7%
1 %
2 %
Estimated derived demand
elasticity (?IE )
-0.042
-0.006
-0.004
4-6
-------
Table 4-2a. Baseline Data: Nonemergency Stationary Diesel Generator Sets and
Welders, 2015
Application
Quantity (units)
Price ($/unit)
51-75 hp
1,066
$7,231
76-100 hp
1,532
$10,101
101-175 hp
2,479
$15,840
>176 hp
5,132
$44,535
Sources: U.S. Environmental Protection Agency. 2004. Final Regulatory Analysis: Control of Emissions from
Nonroad Diesel Engines. EPA 420-R-04-007. Available from
.
Sorrels, Larry, EPA, e-mail to Ruth Mead, ERG and Katherine Heller and Brooks Depro, RTI
International. CI engine population by NAICS. April 20, 2005.
Table 4-2b. Baseline Data: Nonemergency Stationary Diesel Pumps and Compressors,
2015
Application
Quantity (units)
Price ($/unit)
51-75 hp
693
$13,960
76-100 hp
1,343
$19,499
101-175 hp
1,111
$30,578
>176 hp
2,011
$86,192
Sources: U.S. Environmental Protection Agency. 2004. Final Regulatory Analysis: Control of Emissions from
Nonroad Diesel Engines. EPA 420-R-04-007. Available from
.
Sorrels, Larry, EPA, e-mail to Ruth Mead, ERG and Katherine Heller and Brooks Depro, RTI
International. CI engine population by NAICS. April 20, 2005.
Table 4-2c. Baseline Data: Nonemergency Stationary Diesel Irrigation Systems, 2015
Market Variable 50-100 hp 101-600 hp
Quantity (units) 272 707
Price ($/unit) $42,247 $75,815
Sources: U.S. Environmental Protection Agency. 2004. Final Regulatory Analysis: Control of Emissions from
Nonroad Diesel Engines. EPA 420-R-04-007. Available from
.
Sorrels, Larry, EPA, e-mail to Ruth Mead, ERG and Katherine Heller and Brooks Depro, RTI
International. CI engine population by NAICS. April 20, 2005.
4-7
-------
Next, we can use "hat" notation to transform Eq. (4.3) to proportional changes and rearrange
terms:
where
4 = *,P (4-4)
Qs = percentage change in the quantity of market supply,
Qs = market elasticity of supply, and
p = percentage change in market price.
By using this approach, we have taken the elasticity definition and turned it into a linear
behavioral equation that characterizes market supply in the three diesel equipment markets.
To introduce the cost of controls associated with the regulatory program, we assume the per-
unit cost (c) leads to a proportional shift in the marginal cost of production. Under the
assumption of perfect competition (price equals marginal cost), we can approximate this shift
at the initial equilibrium point as follows:
MC =
MC,
c
Pe
(4.5)
4,3.2 Market Demand
We can specify a demand equation for each diesel engine equipment market as
follows:
where
(4.6)
a =
percentage change in the quantity of market demand,
market elasticity of demand, and
percentage change in market price.
4-8
-------
4.3.3 Equilibrium Solution
Lastly, we specify the market equilibrium conditions in three diesel equipment
markets. In response to the exogenous increase in production costs, the new equilibrium
satisfies the condition that the change in supply equals the change in demand:
6 - 6 (4-7)
tj - ^-d
We now have three linear equations in three unknowns (p ,Qd, and Qs ), and we can solve
for the proportional price change in terms of the elasticity parameters (es and r|d) and the
proportional change in marginal cost:
p = -^-MC. (4.8)
?%
Given this solution, we can solve for the proportional change in market quantity using the
demand equation.
4.4 Results
The model projects the NSPS will increase prices from 2 to 9.4 percent (see Table 4-
3). Generator set and welding equipment markets experience the highest relative change in
baseline price (9.4 percent). Domestic production declines by small amounts (less than 0.5
percent) because the (absolute) elasticity of demand for the final product or service that uses
affected equipment and the cost share of equipment in production of these goods and
services is small.
The national compliance cost estimates are often used to approximate the social cost
of the rule. The engineering analysis estimated annualized costs of $57.1 million. In cases
where the engineering costs of compliance are used to estimate social cost, the burden of the
regulation is typically measured as falling solely on the affected producers, who experience a
profit loss exactly equal to these cost estimates. Thus, the entire loss is a change in producer
surplus with no change (by assumption) in consumer surplus, because no change in market
price is estimated. This is typically referred to as a "full-cost absorption" scenario in which
all factors of production are assumed to be fixed and firms are unable to adjust their output
levels when faced with additional costs.
4-9
-------
Table 4-3. Summary of Economic Impacts: 2015
Market-Level Impacts
Generator Sets and Welders
Pumps and Compressors
Irrigation Systems
Change in Consumer Surplus
Change in Producer Surplus
Recordkeeping costs not addressed in market model
Change in Total Surplus
% Change in
9.4%
3.7%
2.0%
-$37.629
-$0.436
-$19.009
-$57.074
Price % Change
-0.
-0.
-0.
Welfare Impacts
in Quantity
40%
02%
01%
In contrast, EPA's economic analysis builds on the engineering cost analysis and
incorporates economic theory related to producer and consumer behavior to estimate changes
in market conditions. Owners of affected plants are economic agents that can make
adjustments, such as changing production rates or altering input mixes, that will generally
affect the market environment in which they operate. As producers change their production
levels in response to a regulation, consumers are typically faced with changes in prices that
cause them to alter the quantity that they are willing to purchase. These changes in price and
output from the market-level impacts are used to estimate the total surplus losses/gains for
two types of stakeholders: chemical consumers and owners of chemical plants.
The numerical simulation suggests the changes in price and quantity are relatively
small; thus, the economic approach and engineering cost approach yield approximately the
same estimate of the total change in surplus ($57.1 million). However, the advantage of the
economic approach is that it illustrates how the costs flow through the economic system and
identifies transitory impacts on stakeholders. As shown in Table 4-3, equipment consumers
unambiguously see reductions in surplus as the result of higher prices and reduced
consumption ($37.6 million). The monitoring, recordkeeping, recording, and reporting costs
in 2015 total $20.2 million. They include $2.06 million for prime engines (included in the
model) and $19.009 million for initial notification ($5,768), certification ($845,000), and
recording hours of nonemergency operation of emergency engines ($18.158 million). The
$19.0 million in costs are largely borne by emergency engine operators and thus are not
included in the model; instead, they are entered as a line item in the calculation of social
costs of the rule (see Table 4-3).
4-10
-------
Table 4-4 presents detailed economic impact estimates for generator and welder
equipment. Prices are projected to increase from 6.3 percent to 10.3 percent across the
horsepower ranges, and quantities sold are projected to decline by less than 0.5 percent. For
this segment of the industry, purchasers of the generator and welder equipment are projected
to incur three-quarters of the social costs ($28.9 million), while producers of the generator
and welder equipment are projected to lose less than $0.5 million.
Table 4-4. Detailed Results for Generator and Welder Equipment: 2015
HP Range
51-75hp
76-100 hp
101-175 hp
>176 hp
Market-Level
% Change in Price %
6.3%
9.4%
8.9%
10.3%
Impacts
Change in Quantity
-0.27%
-0.40%
-0.37%
-0.43%
Welfare Impacts
Change in Consumer Surplus
Change in Producer Surplus
Change in Total Surplus
-$28.949
-$0.417
-$29.366
Table 4-5 presents detailed economic impact estimates for pump and compressor
equipment. Prices are projected to increase from 2.4 percent to 4.9 percent across the
horsepower ranges, and quantities sold are projected to decline by less than 0.03 percent. For
this segment of the industry, purchasers of the pump and compressor equipment are
projected to incur the majority of the social costs ($7.4 million), while producers of the pump
and compressor equipment are projected to lose $0.02 million.
Table 4-6 presents detailed economic impact estimates for irrigation equipment.
Prices are projected to increase from 2.0 percent to 2.2 percent across the horsepower ranges,
and quantities sold are projected to decline by 0.01 percent. Like the other two segments of
the industry, purchasers of the irrigation equipment are projected to incur the majority of the
4-11
-------
Table 4-5. Detailed Results for Pump and Compressor Equipment: 2015
HP Range
51-75hp
76-100 hp
101-175 hp
>176 hp
Market-Level
% Change in Price %
3.3%
4.9%
4.7%
2.4%
Impacts
Change in Quantity
-0.02%
-0.03%
-0.03%
-0.01%
Welfare Impacts
Change in Consumer Surplus
Change in Producer Surplus
Change in Total Surplus
-$7.376
-$0.016
-$7.391
Table 4-6. Detailed Results for Irrigation Equipment: 2015
Market-Level Impacts
HP Range
% Change in Price % Change in Quantity
51-100 hp
101-600 hp
2.2%
2.0%
-0.01%
-0.01%
Welfare Impacts
Change in Consumer Surplus
Change in Producer Surplus
Change in Total Surplus
$ (1.305)
$ (0.002)
$ (1.307)
social costs ($1.3 million), while producers of the irrigation equipment are projected to lose
less than $0.01 million.
The NSPS will reduce emissions of SO2 by requiring the use of lower-sulfur fuel. In
the baseline year of analysis (2015), new stationary CI equipment subject to the NSPS will
be required to use ULSD fuel (i.e., must consume fuel meeting a 15 ppm sulfur standard). In
the absence of regulation, these engines might still have been using high-sulfur fuel. As a
result of regulation, demand for ULSD fuel will increase and demand for high-sulfur No. 2
distillate will decline relative to an unregulated baseline. Estimated demand for low-sulfur
4-12
-------
diesel fuel in 2015 is 63.2 billion gallons. This number includes demand for diesel fuels used
in highway, nonroad, locomotive, and marine categories (see Table 4-7). Estimated prime
engine fuel demand in 2015 is 1.73 billion gallons; therefore, the expected increase in
demand for low-sulfur diesel fuel equals 2.74 percent. On the other hand, decrease in
demand for high-sulfur diesel fuel will be a substantial share of the remaining production of
high-sulfur diesel fuel. Estimated 2015 high-sulfur fuel production is 7.538 billion gallons,
and the ratio of prime engine fuel demand to high-sulfur fuel supply equals 22.94 percent
(see Table 4-7).
Table 4-7. Shift of Diesel Fuel Supply and Demand Quantities in 2015 (billion gallons)
Estimated Demand for Estimated Supply for High-
Fuel Use Category Low-Sulfur Diesel Fuel" Sulfur Diesel Fuel"
Highway
Nonroad
Locomotive
Marine
Heating oil
47.58
10.34
3.13
2.16
7.54
Total 63.21 7.54
Estimated stationary prime-engine fuel 1.73 1.73
demand15
Ratio 2.74% 22.94%
"From Table 7.1.4-13, pi-61, Final Reg Supp Doc.
bE-mail from Larry Sorrels to ERG and RTI, "Analysis of availability of ultra low sulfur diesel." June 7, 2005.
4-13
-------
SECTION 5
SMALL BUSINESS IMPACT ANALYSIS
This regulatory action will potentially affect the economic welfare of owners of
facilities that will own or operate new CI internal combustion engines. The ownership of
these facilities ultimately is in the hands of private individuals who may be owners/operators
that directly conduct the business of the firm (i.e., single proprietorships or partnerships) or,
more commonly, investors or stockholders that employ others to conduct the business of the
firm on their behalf (i.e., privately held or publicly traded corporations). The individuals or
agents that manage these facilities have the capacity to conduct business transactions and
make business decisions that affect the facility. The legal and financial responsibility for
compliance with a regulatory action ultimately rests with these agents; however, the owners
must bear the financial consequences of the decisions. Environmental regulations like this
rule potentially affect all businesses, large and small, but small businesses may have special
problems in complying with such regulations, because they may have less specialized
environmental expertise or limited access to capital for investing in compliance equipment.
The Regulatory Flexibility Act (RFA) of 1980 requires that special consideration be
given to small entities affected by federal regulation. The RFA was amended in 1996 by the
Small Business Regulatory Enforcement Fairness Act (SBREFA) to strengthen the RFA's
analytical and procedural requirements. Prior to enactment of SBREFA, EPA exceeded the
requirements of the RFA by requiring the preparation of a regulatory flexibility analysis for
every rule that would have any impact, no matter how minor, on any number, no matter how
few, of small entities. Under SBREFA, however, the Agency decided to implement the RFA
as written and that a regulatory flexibility analysis will be required only for rules that will
have a significant impact on a substantial number of small entities (SISNOSE). In practical
terms, the amount of analysis of small entities' impacts has not changed, for SBREFA
required EPA to increase involvement of small entity stakeholders in the rulemaking process.
Thus, the Agency has made additional efforts to consider small entity impacts as part of the
rulemaking process.
5-1
-------
5.1 Description of Small Entities Affected
Small entities include small businesses, small organizations, and small governmental
jurisdictions. For purposes of assessing the impacts of the CINSPS, a small entity is defined
as
a small business whose parent company has fewer than 1 ,000 employees (for
NAICS 335312 [Motor and Generator Manufacturing]) or 500 employees (for
NAICS 33391 1 [Pump and Pumping Equipment Manufacturing], NAICS 333912
[Air and Gas Compressor Manufacturing], and NAICS 333992 [Welding and
Soldering Equipment Manufacturing]);
a small governmental jurisdiction that is a government of a city, county, town,
school district, or special district with a population of fewer than 50,000; and
a small organization that is any not-for-profit enterprise, which is independently
owned and operated and is not dominant in its field.
5.2 Small Business Screening Analysis
In the next step of the analysis, we assessed how the regulatory program may
influence the profitability of ultimate parent companies by comparing pollution control costs
to total sales. To do this, we divided an ultimate parent company's total annual compliance
cost by its reported revenue (see the following equation):
- (5-1)
LTACC
CSR =
ra,
where
CSR = cost-to-sales ratio,
TACC = total annualized compliance costs,
i = indexes the number of affected plants owned by company j,
n = number of affected plants, and
TRj = total revenue from all operations of ultimate parent company j.
This method assumes the affected a company cannot shift pollution control costs to
consumers (in the form of higher market prices). Instead, the company experiences a one-for-
one reduction in profits.
5-2
-------
To identify sales and employment characteristics of affected parent companies, we
used a company database developed for small business analysis of the Clean Air Nonroad
Diesel Rule (EPA, 2004). Since the rule does not affect all companies included in the
database, the analysis only includes companies that produced the following types of
equipment segments:
pumps and compressors (Pump and Pumping Equipment Manufacturing [NAICS
333911] or Air and Gas Compressor Manufacturing [NAICS 333912]) and
welders and generators (Motor and Generator Manufacturing [NAICS 335312] or
Welding and Soldering Equipment Manufacturing [NAICS 333992]).
The statistics included in the database come from PSR and other publicly available resources
such as the following:
Business & Company Resource Center. A single database for company pro files,
company brand information, rankings, investment reports, company histories,
chronologies, full-text articles, investment reports, industry overviews, and
financial and trade association data. http://www.gale.com/servlet/Item
DetailServlet?region=9&imprint=000&titleCode=GAL49&type=l&id=115085.
Hoover's Online. This electronic database is an excellent source of information
on U.S. public and private companies. Users can search for companies byname,
ticker symbol, or keyword. It provides corporate ownership, sales, net income,
and employment. Links are also provided to the company's Web site and those of
top competitors (if available), SEC filings in EDGAR Online, investor research
reports, and news and commentary, http://www.hoovers.com/.
ReferenceUSA. The ReferenceUSA database contains, in module format, detailed
information on more than 12 million U.S. businesses. Information is compiled
from the following public sources: more than 5,600 Yellow Page and Business
White Page telephone directories; annual reports, 10-Ks, and other Securities and
Exchange Commission (SEC) information; Continuing Medical Education (CME)
directories; federal, state, provincial, and municipal government data; Chamber of
Commerce information; leading business magazines, trade publications,
newsletters, major newspapers, industry and specialty directories; and postal
service information, including both U.S. and Canadian National Change of
Address updates. One disadvantage of this database is that it only reports sales
and employment ranges. For this analysis, we developed a point estimate for these
values (typically the median), http://www.referenceusa.com/.
5-3
-------
Dun & Bradstreet's Million Dollar Directory. The D&B Million Dollar
Directory provides information on over 1,260,000 U.S. leading public and private
businesses. Company information includes industry information with up to 24
individual eight-digit Standard Industrial Classification (SIC) codes, size criteria
(employees and annual sales), type of ownership, and principal executives and
biographies, http://www.dnb.com/ dbproducts/ description/
0,2867,2-223-1012-0-223-142-177-l,OO.html.
We identified 60 small companies and 44 large companies with sales data. Using the
data, we found 62 companies manufacture products that are included in the Pump and
Pumping Equipment Manufacturing (NAICS 333911) or Air and Gas Compressor
Manufacturing (NAICS 333912) industries, and 30 companies manufacture products
included in the Motor and Generator Manufacturing (NAICS 335312) or Welding and
Soldering Equipment Manufacturing (NAICS 333992) industries. The remaining 12
companies manufacture equipment in both PSR segments.
The results of the screening analysis, presented in Table 5-1, show that two small
firms have estimated CSRs between 1 percent and 3 percent of sales and one firm has a CSR
greater than 3 percent. The remaining 57 small firms have estimated CSRs below 1 percent.
The average (median) CSR for small firms is 0.3 percent (0.1 percent), and the average and
median CSR for all large firms with data is less than 0.02 percent (0.003 percent).
Table 5-1. Summary Statistics for SBREFA Screening Analysis
Companies with Parent Sales Data
Compliance costs are < 1% of sales
Compliance costs are > 1 to 3% of sales
Compliance costs are > 3% of sales
Cost-to-Sales Ratios (%)
Average
Median
Maximum
Minimum
Small
Number Share (%)
60 100%
57 95%
2 3%
1 2%
0.3%
0.1%
4.7%
0.0%
Large
Number
44
44
0.0192%
0.0025%
0.2%
0.0%
Share (%)
100%
100%
0%
0%
5.3 Assessment
The RFA generally requires an agency to prepare a regulatory flexibility analysis of
any rule subject to notice and comment rulemaking requirements under the Administrative
5-4
-------
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. Small entities include
small businesses, small organizations, and small governmental jurisdictions. The economic
impacts of the NSPS are expected to be insignificant, and the Agency has determined that
there is no significant impact (economic) on a substantial number of small entities (or
SISNOSE).
5-5
-------
SECTION 6
HUMAN HEALTH BENEFITS OF EMISSION REDUCTIONS
6.1 Calculation of Human Health Benefits
For the purposes of estimating the benefits of reducing emissions from stationary
diesel compression ignition engines through this rulemaking, EPA is using the approach and
methodology laid out in EPA's 2004 economic analysis supporting the regulation of
emissions from nonroad diesel engines (Final Regulatory Impact Analysis (PJA): Control of
Emissions from Nonroad Diesel Engines, May 2004). We chose this analysis as the basis
since most of the elements in that rule are similar to those covered here. Both the engine
type, the controls applied, and the pollutants reduced are similar to those covered by the
Nonroad Diesel engine rule. In addition, EPA believes that these types of engines are
broadly distributed across the country similar in distribution to nonroad diesel engines.
Figure 6-1 shows the distribution of these engines by State.
6-1
-------
Fjguie 6-1: Noioroad Engine sin the U.S. hy State
140.000
120,000
100.000
80,000
60.000
40,000
20,000
.-, n
n H
nllll
State
6-2
-------
These four factors lead us to believe is appropriate to use the benefits transfer
approach and values in the Nonroad Diesel engine rule regulatory impacts analysis (RIA) for
estimating the benefits of this rule. The benefits transfer method used to estimate benefits
for the final Nonroad Diesel engine rule is similar to that used to estimate benefits in the
analysis of the Large Si/Recreational Vehicles standards (see U.S. EPA 2002, Docket A-
2000-01, Document VB-4). The methodology is laid out in Chapter 9 of the Nonroad Diesel
engine RIA.
EPA did not perform an air quality modeling assessment of the emission reductions
resulting from the installation of controls on these engines due to time and resources
constraints and the limited value of that analysis for the purposes of developing the
regulatory approach. This limited EPA's ability to perform a benefits analysis for this
rulemaking since our benefits model requires either air quality modeling or monitoring data.
However, as mentioned above, the similarities of the engines being regulated under this
rulemaking and those in the Nonroad Diesel rulemaking allow us to use the benefit per ton
values derived from the Nonroad Diesel RIA in this analysis.
To develop the estimate of the benefits of the emission reductions from this
rulemaking, we used dollar benefits per ton of emissions reduced estimates for each pollutant
based on the results of the benefits analysis in the Nonroad diesel RIA. We then multiply
this by the number of tons of each pollutant reduced to get the overall benefits value. These
results are summarized in Table 6-1 below. It is important to note that the dollar benefits per
ton estimates used here reflect specific geographic patterns of emissions reductions and
specific air quality and benefits modeling assumptions. Use of these $/ton values to estimate
benefits associated with different emission control programs (e.g. for reducing emissions
from large stationary sources like EGUs) may lead to higher or lower benefit estimates than
if benefits were calculated based on direct air quality modeling. Great care should be taken
in applying these estimates to emission reductions occurring in any specific location, as these
are all based on national or broad regional emission reduction programs and therefore
6-3
-------
represent average benefits per ton over the entire U.S. The benefits per ton for emission
reductions in specific locations may be very different than the national average.
Table 6-1: Estimate of Monetized Benefits in 2015 ($2000)* Presuming CI Engines are
Spatially Distributed Similar to Nonroad Engines
Pollutant
NOx
SOx
Direct PM
Total health
benefits
$ benefits/ton
$8,000
$23,000
$300,000**
Amount of
emissions reduced
(tons)
35,000
9,300
2,900
Monetized benefits
$280 million
$220 million
$860 million
$1.36 billion
* The results in the table are presented assuming a discount rate of three percent. Assuming
a discount rate of seven percent reduces the total benefits to $1.28 billion.
** This $/ton value is higher than that found in other EPA rulemakings such as the heavy
duty onroad engines. This reflects the fact that nonroad engines, such as construction
equipment, are frequently located in highly populated urban areas and thus more people
benefit per ton of emissions reduced.
6.2 Characterization of Uncertainty in the Benefits Estimates
In any complex analysis, there are likely to be many sources of uncertainty. Many
inputs are used to derive the final estimate of economic benefits, including emission
inventories, air quality models (with their associated parameters and inputs), epidemiological
estimates of C-R functions, estimates of values, population estimates, income estimates, and
estimates of the future state of the world (i.e., regulations, technology, and human behavior).
For some parameters or inputs it maybe possible to provide a statistical representation of the
underlying uncertainty distribution. For other parameters or inputs, the necessary information
is not available.
6-4
-------
In addition to uncertainty, the annual benefit estimates presented in this analysis are
also inherently variable due to the truly random processes that govern pollutant emissions
and ambient air quality in a given year. Factors such as hours of equipment use and weather
display constant variability regardless of our ability to accurately measure them. As such,
the estimates of annual benefits should be viewed as representative of the magnitude of
benefits expected, rather than the actual benefits that would occur every year. In addition, as
with all benefits transfer applications, the benefits per ton for specific emissions tons reduced
will be dependent on the geographic location of those emissions reductions and the relative
atmospheric conditions compared to the geographic distribution of nonroad diesel engines
and the atmospheric conditions assumed in the Nonroad Diesel analysis. Specifically, the
transfer method we used leads to an average benefit per ton that is based on the average
population exposed to emissions from nonroad engines. If populations exposed to ambient
pollution resulting from emissions from CI engines are less dense than the average
population exposed to ambient pollution resulting from nonroad engines, then the benefits
per ton associated with those emissions will be lower than that derived from the Nonroad
rule. Likewise, if populations exposed are more dense than those exposed to ambient
pollution from Nonroad engines, then benefits per ton will be higher.
Above we present a primary estimate of the total benefits, based on our interpretation
of the best available scientific literature and methods and supported by the SAB-HES and the
NAS (NRC, 2002). The benefits estimates are subject to a number of assumptions and
uncertainties. For example, key assumptions underlying the primary estimate for the
premature mortality which accounts for 90 percent of the total benefits we were able to
quantify include the following:
(1) Inhalation of fine particles is causally associated with premature death at concentrations
near those experienced by most Americans on a daily basis. Although biological
mechanisms for this effect have not yet been definitively established, the weight of the
available epidemiological evidence supports an assumption of causality.
6-5
-------
(2) All fine particles, regardless of their chemical composition, are equally potent in causing
premature mortality. This is an important assumption, because PM produced via transported
precursors emitted from EGUs may differ significantly from direct PM released from diesel
engines and other industrial sources, but no clear scientific grounds exist for supporting
differential effects estimates by particle type.
(3) The impact function for fine particles is approximately linear within the range of ambient
concentrations under consideration. Thus, the estimates include health benefits from
reducing fine particles in areas with varied concentrations of PM, including both regions that
are in attainment with fine particle standard and those that do not meet the standard.
(4) The forecasts for future emissions and associated air quality modeling are valid.
Although recognizing the difficulties, assumptions, and inherent uncertainties in the overall
enterprise, these analyses are based on peer-reviewed scientific literature and up-to-date
assessment tools, and we believe the results are highly useful in assessing this rule.
The recent NAS report (NAS 2002) on estimating public health benefits of air
pollution regulations recommended that EPA begin to move the assessment of uncertainties
from its ancillary analyses into its primary analyses by conducting probabilistic, multiple-
source uncertainty analyses. As part of a collaboration between EPA's Office of Air and
Radiation (OAR) and the Office of Management and Budget (OMB) on the Nonroad Diesel
Rule, we conducted a pilot expert elicitation intended to more fully characterize uncertainty
in the estimate of mortality resulting from exposure to PM. The final expert elicitation is
expected to be finished and peer reviewed this Fall.
For this RIA we did not go through the detailed uncertainty assessment used in the
Regulatory Impact Analysis for the Clean Air Interstate Rule (CAIR RIA) (March 2005)
because we lack the necessary air quality input data to run the benefits model. However, the
results of the Monte Carlo analyses of the health and welfare benefits presented in Appendix
B of that RIA can provide some evidence of the uncertainty surrounding the benefits results
presented in this analysis.
6-6
-------
6.3 General Approach
In our recent assessment of the Clean Air Interstate Rule (CAIR) we describe our
progress toward improving our approach of characterizing the uncertainties in our economic
benefits estimates, with particular emphasis on the concentration response (C-R) function
relating premature mortality to exposures to ambient PM2.5. We presented two approaches
to generating probabilistic distributions designed to illustrate the potential influence of some
aspects of the uncertainty in the C-R function in a PM benefits analysis. The first approach
generated a probabilistic estimate of statistical uncertainty based on standard errors reported
in the underlying studies used in the benefit modeling framework. The second approach
used the results from the pilot expert elicitation designed to characterize certain aspects of
uncertainty in the ambient PM2.5/mortality relationship.
In addition to the two approaches to characterize uncertainty for PM mortality, we
incorporated information on uncertainties of other endpoints in the benefits model. We did
not attempt to assign probabilities to all of the uncertain parameters in the model because of
a lack of resources and reliable methods. We simply generate estimates of the distributions
of dollar benefits for PM health effects and for total dollar benefits. For non-mortality
endpoints, we provide a likelihood distribution for the total benefits estimate, based solely on
the statistical uncertainty surrounding the estimated C-R functions and the assumed
distributions around the unit values.
Our estimate of the likelihood distribution for total benefits should be viewed as
incomplete because of the wide range of sources of uncertainty that we have not
incorporated. The 5th and 95th percentile points of our estimate are based on statistical
error, and cross-study variability provides some insight into how uncertain our estimate is
with regard to those sources of uncertainty. However, it does not capture other sources of
uncertainty regarding other inputs to the model, including emissions, air quality, baseline
population incidence, projected exposures, or the model itself, including aspects of the health
science not captured in the studies, such as the likelihood that PM is causally related to
premature mortality and other serious health effects. Thus, a likelihood description based on
6-7
-------
the standard error would provide a misleading picture about the overall uncertainty in the
estimates.
Both the uncertainty about the incidence changes4 and uncertainty about unit dollar
values can be characterized by distributions. Each "likelihood distribution" characterizes our
beliefs about what the true value of an unknown variable (e.g., the true change in incidence
of a given health effect in relation to PM exposure) is likely to be, based on the available
information from relevant studies.5 Unlike a sampling distribution (which describes the
possible values that an estimator of an unknown variable might take on), this likelihood
distribution describes our beliefs about what values the unknown variable itself might be.
Such likelihood distributions can be constructed for each underlying unknown variable (such
as a particular pollutant coefficient for a particular location) or for a function of several
underlying unknown variables (such as the total dollar benefit of a regulation). In either
case, a likelihood distribution is a characterization of our beliefs about what the unknown
variable (or the function of unknown variables) is likely to be, based on all the available
relevant information. A likelihood description based on such distributions is typically
expressed as the interval from the 5th percentile point of the likelihood distribution to the
95th percentile point. If all uncertainty had been included, this range would be the "credible
range" within which we believe the true value is likely to lie with 90 percent probability.
6.4 Monte-Carlo Based Uncertainty Analysis
The uncertainty about the total dollar benefit associated with any single endpoint
combines the uncertainties from these two sources (the C-R relationship and the valuation)
Because this is a national analysis in which, for each endpoint, a single C-R function is applied everywhere,
there are two sources of uncertainty about incidence: statistical uncertainty (due to sampling error) about
the true value of the pollutant coefficient in the location where the C-R function was estimated and
uncertainty about how well any given pollutant coefficient approximates 6*.
Although such a "likelihood distribution" is not formally a Bayesian posterior distribution, it is very similar in
concept and function (see, for example, the discussion of the Bayesian approach in Kennedy (1990), pp.
168-172).
-------
and is estimated with a Monte Carlo method. In each iteration of the Monte Carlo procedure,
a value is randomly drawn from the incidence distribution, another value is randomly drawn
from the unit dollar value distribution; the total dollar benefit for that iteration is the product
of the two.6 When this is repeated for many (e.g., thousands of) iterations, the distribution of
total dollar benefits associated with the endpoint is generated.
Using this Monte Carlo procedure, a distribution of dollar benefits can be generated
for each endpoint. As the number of Monte Carlo draws gets larger and larger, the Monte
Carlo-generated distribution becomes a better and better approximation of a joint likelihood
distribution (for the considered parameters) making up the total monetary benefits for the
endpoint. After endpoint-specific distributions are generated, the same Monte Carlo
procedure can then be used to combine the dollar benefits from different (nonoverlapping)
endpoints to generate a distribution of total dollar benefits.
The estimate of total benefits may be thought of as the end result of a sequential
process in which, at each step, the estimate of benefits from an additional source is added.
Each time an estimate of dollar benefits from anew source (e.g., a new health endpoint) is
added to the previous estimate of total dollar benefits, the estimated total dollar benefits
increases. However, our bounding or likelihood description of where the true total value lies
also increases as we add more sources. The physical effects estimated in this analysis are
assumed to occur independently. It is possible that, for any given pollution level, there is
some correlation between the occurrence of physical effects, due to say avoidance behavior
or common causal pathways and treatments (e.g., stroke, some kidney disease, and heart
attack are related to treatable blood pressure). Estimating accurately any such correlation,
however, is beyond the scope of this analysis, and instead it is simply assumed that the
physical effects occur independently.
For the CAIR RIA, we conducted two different Monte Carlo analyses, one based on
the distribution of reductions in premature mortality characterized by the mean effect
This method assumes that the incidence change and the unit dollar value for an endpoint are stochastically
independent.
6-9
-------
estimate and standard error from the epidemiology study of PM-associated mortality
associated with the primary estimate (Pope et al, 2002), and one based on the results from a
pilot expert elicitation project (lEc, 2004). In both analyses, the distributions of all other
health endpoints are characterized by the reported mean and standard deviations from the
epidemiology literature. Distributions for unit dollar values are based on reported ranges or
distributions of values in the economics literature and are summarized in Table B-l of
Appendix B of the CAIR RIA. Summary results of the Monte Carlo analyses based on the
Pope et al. (2002) distribution and based on the pilot expert elicitation are presented in the
next section.
6.5 Results of the CAIR RIA Monte Carlo Analyses
Results of the Monte Carlo simulations are presented in Table 6-2. The table
provides the estimated means of the distributions and the estimated 5th and 95th percentiles
of the distributions. The contribution of mortality to the mean benefits and to both the 5th
and 95th percentiles of total benefits is substantial, with mortality accounting for 93 percent
of the mean estimate, and even the 5th percentile of mortality benefits dominating the 95th
percentile of all other benefit categories. Thus, the choice of value and the shape for
likelihood distribution for VSL should be examined closely and is key information to provide
to decision makers for any decision involving this variable.
Table 6-2: Results of Monte Carlo Uncertainty Assessment from CAIR RIA
Statistical
uncertainty based
approach
Expert
elicitation
uncertainty based
approach
5th percentile
$26 Billion
$3 Billion
mean
$100 Billion
$74 Billion
95th
percentile
$210 Billion
$240 Billion
6-10
-------
For the statistical based approach, the 95th percentile of total benefits is
approximately twice the mean, while the 5 th percentile is approximately one-fourth of the
mean. The overall range from 5th to 95th represents about one order of magnitude. For the
expert elicitation based approach, the 95th percentile of total benefits is approximately three
times the mean, while the 5 th percentile is approximately one-twentieth of the mean. The
overall range from 5th to 95th is somewhat wider than that of the statistical based approach.
Prior to taking the next step and applying these results to the benefits estimates from
this rulemaking, it is important to note that there are numerous caveats and limitations
associated these uncertainty approaches which are not reflected in this write-up. Readers are
strongly encouraged to review the detailed discussion in Appendix B of the CAIR RIA for a
detailed discussion of these approaches.
As a means of assessing the uncertainty associated with the estimate of the monetized
benefits of this rulemaking we applied the ratios from the above table to the benefit estimates
presented earlier. Thus, to estimate the 5th percentile of the statistical uncertainty based
approach we multiplied the ratio of the 5th percentile to the mean (26/100) by the estimated
benefits of this rule ($1.36 Billion). Using these values as a guide, we assumed that the
distribution of values for this rulemaking would be similar. Table 6-3 summarizes the
results.
6-11
-------
Table 6-3: Estimated Monetized Health Benefits Compared to Two Approaches for
Estimating the Uncertainty Range
Estimated monetized
benefits**
Statistical uncertainty
based approach
Expert elicitation
uncertainty based
approach
5th percentile
NC*
$360 Million
$68 Million
mean
$1.36 Billion
NC*
NC*
95th percentile
NC*
$2.85 Billion
$4.4 Billion
* NC - Not Calculated
** 3 percent discount rate
6.6 Benefits By Engine Size Category
We analyzed the distribution of monetized benefits across engine size categories.
This analysis assumes that the average $ benefits per ton based on the Nonroad Diesel RIA
analysis is representative of the average benefits that would accrue to reductions in emissions
for each individual engine size category. This introduces additional uncertainty in the
analysis. As such, this analysis should be viewed as providing the most information when
used in a relative sense, e.g., comparing relative magnitudes across categories, rather than in
an absolute sense, as little confidence should be placed on the specific estimates of benefits
for any one category of engine size. As with all benefits transfer applications, the benefits
per ton for any specific grouping of engine sizes will be dependent on the geographic
location of those engines and the relative atmospheric conditions compared to the geographic
distribution of nonroad diesel engines and the atmospheric conditions assumed in the
Nonroad Diesel analysis.
6-12
-------
The results of this analysis shown below in Table 6-4 suggest that there are net
benefits for every engine size category. In addition, the benefit-cost ratio exceeds 8 for all
engine size categories, although the benefit-cost ratios tend to be larger for the larger engine
size categories. It should be noted that the impacts listed in Table 6-4 are associated with
prime engines. We believe that emergency engines, which make up about 80 percent of the
engines covered by this rule, will have minimal incremental costs and benefits. We assume
that emergency engines will be compliant with certain non-road diesel requirements, thereby
meeting the requirements of this rule.
6-13
-------
Table 6-4. Benefits of Emission Reductions in 2015 by Engine Size Category
Engine
Size(hp)
50-75
75-100
100-175
175-300
300-600
600-750
750-1200
1200-
3000
>3000
Emission
Reductions by
Pollutant (tons)
PM2.5
64
324
498
738
497
101
187
399
62
NOx
-
1620
2780
5044
3345
673
1069
20421
3210
SO2
270
542
1184
1983
1437
372
997
2116
351
Benefits
(3%, million
2000$)
25.3
112.0
181.0
275.4
187.8
40.0
80.9
210.5
33.3
Benefit
s (7%, million
2000$)
23.8
114.8
186.5
288.6
196.2
41.6
82.4
315. .3
49.8
Annualize
d Costs
(2000$)
2.9
6.5
11.0
12.5
6.7
1.2
3.8
10.8
1.6
Net
Benefits
3%
22.4
105.5
170.0
262.9
181.0
38.8
77.1
199.7
31.7
Net
Benefits
7%
21.0
108.4
175.5
276.0
189.5
40.4
78.6
304.5
48.1
Benefits/
Costs
3%
8.8
17.3
16.5
22.0
27.9
32.5
21.2
19.4
20.3
Benefits/
Costs
7%
8.3
17.8
17.0
23.0
29.2
33.8
21.6
29.1
30.3
6-14
-------
6.7 Benefit-Cost Comparison
Recall that the costs of this rulemaking are estimated to be $57 million in 2015.
Regardless of the uncertainty characterization approach used, the benefits of this rule exceed
the costs, even when the cost is compared to the 5th percentile estimate of the expert
elicitation approach. Thus, EPA believes that the benefits of this rulemaking will exceed the
costs. The reader should refer to the CAIR RIA for a full detailed discussion of the
uncertainties considered in EPA's benefit analyses.
6-15
-------
REFERENCES
California Air Resources Board (CARB). 2003. Staff Report: Initial Statement of Reasons for
Proposed Rulemaking Airborne Toxic Control Measure for Stationary
Compression-Ignition Engines. Available from . Last updated November 16, 2004.
Fullerton, D, and G. Metcalf. March 2002. "Tax Incidence." NBER Working Paper 8829.
. Obtained in November 2004.
Guerra, Z., Office of Transportation and Technology, U.S. Environmental Protection
Agency. 2005. Memorandum: "Price Database for New Non-Road Equipment."
Hicks, J.R. 1963. The Theory of Wages. 2nd Ed. New York: St. Martin's Press.
Hoover's Online. 2005. Available from .
Industrial Economics, Incorporated (lEc). 2004. Expert Judgment Assessment of the
Relationship Between PM2.5 Exposure and Mortality." Available at
www. epa. go v/ttn/ecas/benefits .html.
Layard, P., and A. Walters. 1978. Microeconomic Theory. New York: McGraw-Hill.
Mas-Colell, A., M. Whinston, and J. Green. 1995. Microeconomic Theory. New York:
Oxford University Press.
National Research Council (NRC). 2002. Estimating the Public Health Benefits of
Proposed Air Pollution Regulations. Washington, DC: The National Academies
Press.
Parise, T., Alpha-Gamma Technologies, Inc. 2005a. Memorandum: "Cost Impacts
Associated with NSPS for Stationary CI ICE."
Parise, T., Alpha-Gamma Technologies, Inc. 2005b. Memorandum: "Emission Reduction
Associated with NSPS for Stationary CI ICE."
Pope, C.A., III, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K. Ito, and G.D. Thurston.
2002. "Lung Cancer, Cardiopulmonary Mortality, and Long-Term Exposure to Fine
R-l
-------
Particulate Air Pollution." Journal of the American Medical Association 287:1132-
1141.
Power Systems Registry (PSR). 2004. OELink. .
Rhein Associates. 2002. The Future of Diesel Engines, Fifth Edition. Rhein Associates:
Canton, MI.
Sorrels, Larry, EPA, e-mail to Ruth Mead, ERG and Katherine Heller and Brooks Depro,
RTI International. CI engine population by NAICS. April 20, 2005.
U.S. Bureau of Economic Analysis. 2002. 1997 Benchmark Input-Output Accounts: Detailed
Make Table, Use Table and Direct Requirements Table. Tables 4 and 5.
U.S. Bureau of the Census. 2004a. "Farm Machinery and Equipment Manufacturing: 2002."
2002 Economic Census Manufacturing Industry Series. EC02-311-333111(RV).
Washington, DC: U.S. Bureau of the Census. Table 1.
U.S. Bureau of the Census. 2004b. "Motor and Generator Manufacturing: 2002." 2002
Economic Census Manufacturing Industry Series. EC02-311-335312(RV).
Washington, DC: U.S. Bureau of the Census. Table 1.
U.S. Bureau of the Census. 2004c. "Pump and Pumping Equipment Manufacturing: 2002."
2002 Economic Census Manufacturing Industry Series. EC02-311-333911(RV).
Washington, DC: U.S. Bureau of the Census. Table 1.
U.S. Bureau of the Census. 2004d. "Welding and Soldering Equipment Manufacturing:
2002." 2002 Economic Census Manufacturing Industry Series. EC02-311-
333992(RV). Washington, DC: U.S. Bureau of the Census. Table 1.
U.S. Department of Agriculture, National Agricultural Statistics Service. 2004. "Farm
Production Expenditures 2003 Summary." Washington, DC: USDA-NASS.
U.S. Environmental Protection Agency (EPA). 2000. Guidelines for Preparing Economic
Analyses. EPA-240-R-00-003. Washington, DC: EPA.
U.S. Environmental Protection Agency (EPA). 2002. Final Regulatory Support Document
for the Large Industrial Spark-Ignition Engines, Recreational Marine Vessels, and
Recreational Vehicles. EPA420-R-02-022. Available from
http://www.epa.gov/otaq/regs/nonroad/2002/cleanrec-final.htmffchapter.
R-l
-------
U.S. Environmental Protection Agency (EPA). 2004. Final Regulatory Analysis: Control of
Emissions from Nonroad Diesel Engines. EPA420-R-04-007. Available from
.
U.S. Environmental Protection Agency (EPA). 2005. Regulatory Impact Analysis for the
Final Clean Air Interstate Rule. EPA/452-R-05-002. Available from
http://www.epa. gov/cair/pdfs/finaltech08 .pdf.
Viscusi, W.K., J.M. Vernon, and J.E. Harrington. 1992. Economics of Regulation and
Antitrust. Lexington, MA: B.C. Heath and Co.
Vives, X. 1987. "Small Income Effects: A Marshallian Theory of Consumer Surplus and
Downward Sloping Demand. "Review of Economic Studies 54:87-103.
R-2
-------
-------
-------
United States Office of Air Quality Planning and Standards Publication No. EPA-452/R-06-003
Environmental Protection Health and Enviromental Impacts Division June 2006
Agency Research Triangle Park, NC
------- |