00-1

Planning 

Report

Economic Impact of

Standard Reference Materials

for Sulfur in Fossil Fuels

Prepared by:

Research Triangle Institute

for

National Institute of

Standards & Technology

Program Office

Strategic Planning and

Economic Analysis Group

February 2000

U.S Department of Commerce

Technology Administration
February 2000

Economic Impact of Standard

Reference Materials for Sulfur

in Fossil Fuels

Final Report

Prepared for

Strategic Planning and Economic Analysis Group

National Institute of Standards and Technology

Bldg. 101, Room A1013

Gaithersburg, MD 20899-1060

Prepared by

Sheila A. Martin, Ph.D.

Michael P. Gallaher, Ph.D.

Alan C. O’Connor

Research Triangle Institute

Center for Economics Research

Research Triangle Park, NC 27709

RTI Project Number 7007-006
RTI Project Number

7007-006

Economic Impact of Standard

Reference Materials for Sulfur

in Fossil Fuels

Final Report

February 2000

Prepared for

Strategic Planning and Economic Analysis Group

National Institute of Standards and Technology

Bldg. 101, Room A1013

Gaithersburg, MD 20899-1060

Prepared by

Sheila A. Martin, Ph.D.

Michael P. Gallaher, Ph.D.

Alan C. O’Connor

Research Triangle Institute

Center for Economics Research

Research Triangle Park, NC 27709
iii

Acknowledgments

We wish to acknowledge Dr. Gregory C. Tassey, Dr. W. Robert

Kelly, Bruce S. MacDonald, Dr. John D. Fassett, and Ellyn S. Beary

for helpful comments and suggestions on earlier versions of this

report.
v

Contents

Executive Summary ES-1

1. Introduction 1-1

1.1 NIST’s SRM Program for Sulfur in Fossil Fuels.................... 1-3

1.2 Project Objectives and Scope............................................ 1-4

1.3 Summary of Analytical Approach and Report

Organization..................................................................... 1-6

2. Overview of Affected Industries 2-1

2.1 Sulfur Measurement Industry............................................. 2-3

2.1.1 Instrument Manufacturers ...................................... 2-3

2.1.2 Manufacturers of Certified Reference Materials ...... 2-3

2.1.3 Independent Sulfur Testing Laboratories................. 2-4

2.2 Coal Industry .................................................................... 2-5

2.2.1 Coal Cleaning and Processing................................ 2-5

2.3 Petroleum Industry............................................................ 2-6

2.3.1 Petroleum Processing and Desulfurization ............. 2-7

3. SRMs and Sulfur Measurement 3-1

3.1 Uncertainty in the Measurement of Sulfur in Fossil

Fuels ............................................................................. 3-1

3.1.1 Sources of Variability in Measurement ................... 3-2

3.1.2 Quantifying the Uncertainty of a Measurement

Process.................................................................. 3-4

3.2 Methods for Measuring Sulfur in Fossil Fuels ..................... 3-6

3.2.1 Sulfur in Coal ........................................................ 3-6
vi

3.2.2 Sulfur in Petroleum Products.................................. 3-9

3.2.3 Reference and Sulfur Measurement...................... 3-10

3.3 Impact of NIST SRMs on the Measurement of Sulfur in

Fossil Fuels ..................................................................... 3-12

3.3.1 SRM Development Process .................................. 3-12

3.3.2 History of NIST’s SRM Program for Sulfur in

Fossil Fuels.......................................................... 3-17

3.3.3 Counterfactual Scenarios ..................................... 3-23

4. Valuing Improved Sulfur Information 4-1

4.1 Sulfur Information and Economic Behavior........................ 4-1

4.1.1 Use of SRMs and Sulfur Information to

Improve R&D Efficiency ........................................ 4-3

4.1.2 Use of Sulfur SRMs to Support the Production

Process.................................................................. 4-4

4.1.3 Use of Sulfur Information to Reduce

Transactions Costs in the Purchase and Sale of

Fuels and Other Products....................................... 4-6

4.2 Hypotheses ....................................................................... 4-8

4.2.1 Impact of SRMs on the Sulfur Measurement

Industry ................................................................. 4-8

4.2.2 Impact on the Fossil Fuel Production and

Combustion Industries ......................................... 4-11

4.2.3 Impact on Regulatory Agencies and the

Environment........................................................ 4-12

4.3 Valuing Economic Outcomes .......................................... 4-12

4.3.1 Benefits of Improvements in Product Quality

(H1)..................................................................... 4-15

4.3.2 Changes in R&D Costs (H2) ................................. 4-17

4.3.3 Changes in Transactions Costs (H3) ..................... 4-18

4.3.4 Improvements in Production Efficiency (H4) ........ 4-20

4.3.5 Changes in Regulatory Penalties (H5)................... 4-23

4.3.6 Benefits to the Environment (H6) ......................... 4-23

4.4 Data Collection............................................................... 4-24

4.4.1 Data Requirements .............................................. 4-25

4.4.2 Sample Selection ................................................. 4-25

4.4.3 Data Collection Procedures ................................. 4-30
vii

5. Results 5-1

5.1 Improvements in Product Quality (H1) .............................. 5-4

5.1.1 Instrument Industry................................................ 5-4

5.1.2 CRM Industry ........................................................ 5-5

5.1.3 Laboratories........................................................... 5-6

5.2 Reductions in the Cost of R&D (H2) .................................. 5-8

5.2.1 Sulfur Measurement Industry ................................. 5-8

5.2.2 Fossil Fuel Industry ................................................ 5-8

5.3 Reductions due to Transactions Costs (H3) ........................ 5-9

5.4 Increases in Production Efficiency (H4)............................ 5-11

5.4.1 Petroleum Industry .............................................. 5-11

5.4.2 Coal Industry....................................................... 5-12

5.5 Reductions in Regulatory Penalties (H5) .......................... 5-13

5.6 Benefits to the Environment (H6) ..................................... 5-14

5.7 Industry Costs ................................................................. 5-16

5.8 NIST Expenditures........................................................... 5-17

5.9 Calculating Measures of Economic Return....................... 5-19

5.10 Conclusions .................................................................... 5-20

References R-1

Appendixes

A SRMs’ Impact on Sulfur Measurement Accuracy ................A-1

B Survey Form...................................................................... B-1

C Profiles of Affected Industries ............................................C-1
viii

Figures

Figure 1-1 Analytical Approach to Assessing the Impact of NIST’s

Technical Laboratories Sulfur in Fossil Fuel SRMs ...................... 1-7

Figure 2-1 Industries Affected by Measurement of Sulfur in Fossil Fuels....... 2-2

Figure 3-1 Bias and Precision in Test Methods ............................................ 3-4

Figure 3-2 Difference “Two” Standard Deviation Limit (d2s) ....................... 3-6

Figure 3-3 Classical Linear Calibration Model........................................... 3-11

Figure 3-4 Impact of IDMS Method on the Relative Uncertainty of NIST

SRMs for Sulfur in Fossil Fuels.................................................. 3-22

Figure 4-1 Change in Consumers’ Surplus for Products and Services

Produced with NIST SRMs ....................................................... 4-16

Figure 4-2 Impact of SRMs on Disputes due to Measurement Error............ 4-19

Figure 4-3 Impact of NIST SRMs on Buffers............................................... 4-21

Figure 4-4 Impact of NIST SRMs on Regulatory Compliance Activities ...... 4-24
ix

Tables

Table 1-1 NIST SRMs Covered by this Study .............................................. 1-5

Table 3-1 Characteristics of ASTM Testing Methods Used Most Often

for Testing Sulfur in Fossil Fuels ................................................. 3-8

Table 3-2 Trends in Confidence Intervals for Certified Values of NIST

SRMs....................................................................................... 3-18

Table 4-1 Potential Impact of SRMs on Stages of Production in the

Sulfur Measurement Supply Chain ............................................. 4-3

Table 4-2 Hypotheses About the Impact of NIST SRMs .............................. 4-9

Table 4-3 Technical and Economic Measures of the Impact of NIST

SRMs....................................................................................... 4-14

Table 4-4 Data Elements Required to Populate the Analytical Model ....... 4-26

Table 4-5 Number of Interviews by Industry Segment .............................. 4-27

Table 4-6 Companies Interviewed ........................................................... 4-28

Table 5-1 Impact of NIST SRMs ................................................................. 5-2

Table 5-2 Annual Net Benefits to Society and NIST Expenditure................. 5-3

Table 5-3 Net Present Value of Benefits Hypothesis ................................... 5-4

Table 5-4 Estimated Annual Impacts of NIST Sulfur SRMs ($1998) ............. 5-7

Table 5-5 Benefits to the Environment ($1998)......................................... 5-15

Table 5-6 Time Series of NIST Expenditures for Sulfur SRMs ($1998)........ 5-18

Table 5-7 Economic Impact of NIST SRMs............................................... 5-20
ES-1

Executive Summary

The National Institute of Standards and Technology (NIST)

promotes U.S. economic growth by working with industry to

develop and apply technology, measurements, and standards.

Through its Office of Standard Reference Materials, NIST is

authorized to certify and sell standard reference materials (SRMs)

that help users engaged in commerce or research link their

measurements to NIST. Developed by NIST’s Technical

Laboratories, SRMs are materials certified for their chemical

composition or physical properties. As emerging regulations

increase the importance of the sulfur content of fossil fuels, NIST is

expanding its SRM program to include SRMs for measuring sulfur in

the low-sulfur fuels required to meet these regulations. The

development of an SRM employs NIST’s unique expertise in

measurement. A NIST-certified SRM carries with it the full weight

and authority of NIST and the U.S. Department of Commerce. This

study estimates the economic impact of NIST SRMs for sulfur in

fossil fuels.

SRMs play a key role in the National Measurement System for

Analytical Chemistry. They serve as national primary chemical

standards and are used as calibrants and as quality assurance

materials to evaluate measurement accuracy, to intercalibrate

laboratories in a measurement program, and to provide

compatibility of measurement data (Taylor, 1993). The absence of

SRMs as primary chemical standards would weaken the entire

measurement system.

SRMs help users verify the accuracy of measurement methods or

calibrate measurement systems. NIST SRMs greatly improve

measurement accuracy by reducing the uncertainty of
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

ES-2

measurement. These improvements enhance the products and

services of the measurement industry, such as testing laboratories

and analytical equipment manufacturers. More accurate sulfur

content information also reduces the likelihood of disputes between

sellers and purchasers of fossil fuels, such as coal companies and

electric utilities. Other benefits include better production efficiency

for the petroleum industry and lower sulfur emissions to the

environment.

This study quantifies a portion of the economic benefits associated

with sulfur SRMs. Included in the measures of economic benefits

are improvements in product quality, production efficiency, and

reductions in transaction costs and sulfur dioxide emissions to the

environment. In addition, the study identifies and qualitatively

describes the impact of NIST SRMs on other less tangible areas,

such as research and development programs.

Table ES-1 presents several measures of economic benefit from

NIST’s investment in sulfur SRMs based on the impacts quantified

as part of this study. Benefit estimates are based on information

gathered from industry, and NIST expenditures were provided by

NIST’s Technical Laboratories. The net present value (NPV) of the

economic benefits beginning in 1984 is $409 million ($1998).

Measure Economic Impact

Benefit-cost ratio 113

Social rate of return 1,056%

Net present value ($1998) $409,002,097

ES.1 ROLE OF NIST SRMS

Technical issues elevate the importance of accuracy and precision

in the measurement of sulfur content. The primary environmental

concern is sulfur dioxide (SO2), which is produced from the

combustion of fuels that contain sulfur as an impurity. SO2 is

directly harmful to health when inhaled and indirectly harmful

because it generates acid rain. In addition to its detrimental impact

on the environment, sulfur content also affects the quality of

Table ES-1. Measures of

Economic Benefits from

NIST SRMs

Economic impacts reflect

benefits and costs beginning in

1984, projected through 2003.
Executive Summary

ES-3

products and processes that use fossil fuels. For example, catalysts

for low-emissions vehicles are sensitive to the sulfur content of

gasoline and diesel fuel. Similarly, the catalysts used in petroleum

processing can be “poisoned” by sulfur; sulfur affects the technical

quality of other petroleum products as well. Fuel oils used in heattreating metals or in firing glass-melting furnaces must be low in

sulfur to avoid damaging the product. The sulfur content of coke

has an impact on the quality of the steel it is used to produce.

NIST’s SRM program for sulfur in fossil fuels uses a definitive

method, developed at NIST, that virtually eliminates bias and

significantly reduces the uncertainty of the SRMs. Without the

development of the isotope dilution thermal ionization mass

spectrometry (IDMS) method, sulfur measurement in industry

would be subject to greater bias and uncertainty. Because of the

IDMS’s complexity and the skill and equipment required, it is

unlikely that any other laboratories developing certified reference

materials (CRMs) would have pursued such a sophisticated method

in the absence of NIST. Therefore, without NIST, the level of

uncertainty associated with measuring sulfur in fossil fuels would

today be similar to what it was prior to the introduction of IDMS in

the early 1980s.

Figure ES-1 illustrates the role that NIST SRMs play in the integrity

of the measurement system. SRMs, which are tied to the basic

measurement units maintained at NIST, are developed using IDMS.

Many organizations use SRMs to develop and evaluate reference

methods, to ensure the accuracy of secondary reference materials,

and to ensure accuracy in critical quality assurance applications.

Secondary reference materials and reference methods are then used

to develop and evaluate field methods to prepare working reference

materials, such as calibrants, and to perform routine quality

assurance activities. The integrity of this system is based on the

quality of NIST SRMs and their traceability to the basic

measurement units.

Many companies and individuals benefit from the measurement

improvements provided by NIST’s sulfur in fossil fuels SRMs. We

focused on those industries that make most extensive use of these

SRMs and benefit most directly from their use. These companies

use NIST SRMs in a variety of production stages, including

Without NIST, the

level of uncertainty

associated with

measuring sulfur in

fossil fuels would

today be similar to

what it was prior to

the introduction of

IDMS in the early

1980s.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

ES-4

Figure ES-1. SRMs’ Role in Measurement Accuracy

NIST SRMs play an integral role in users’ quality control programs. They are used to develop and evaluate analytical

methods, to produce secondary standards, and in quality assurance applications.

,

Basic

Measurement

Units

,,,

NIST

SRMs

,9

Reference

Methods

9

Secondary

Reference

Materials

9,

Field

Methods

,,

Definitive

Methods

é Reference Method

Development and Evaluation

é Production of High-Accuracy

Secondary Reference

Materials

é Critical Quality Assurance

Applications

é Field Method Development

and Evaluation

é Preparation of Routine

Working Reference

Materials

é Routine Internal and

External Quality Assurance

Field Applications

Source: Taylor, John K. February 1993. Standard Reference Materials: Handbook for SRM Users. NIST Special

Publication 260-100. Washington, DC: U.S Government Printing Office.
Executive Summary

ES-5

marketing, applications development, production, and quality

control. Industries include

Z the sulfur measurement industry, including manufacturers of

sulfur measurement instruments, CRMs, and independent

laboratories that conduct sulfur analysis;

Z the fossil fuels extraction and processing industry, including

coal processing, petroleum refining, and coke production;1

and

Z primary users of fossil fuels, including the electric utility

industry and the steel industry (see Figure ES-2).

NIST

Processed

Fossil Fuels

Fossil Fuel Combustion

• Electricity Generation

• Steel Industry

• Industrial Combustion

Users of Power, Steel, and

Other Goods and Services

Power and

Steel

SRMs

Sulfur Measurement

Products and Services

Fossil Fuel Extraction, Processing, and

Transportation

• Coal Processing

• Petroleum Refining

• Coke Production

Sulfur Measurement

• Instrument Manufacturers

• Manufacturers of Certified Reference

Materials

• Independent Testing Laboratories

 1Although natural gas would normally be included in this characterization, we did

not analyze the natural gas industry because NIST does not provide an SRM for

sulfur in natural gas. As described in Appendix C, this is because very little

sulfur is found in natural gas, and its measurement is not an important industry

issue.

Figure ES-2. Industries

Affected by

Measurement of Sulfur in

Fossil Fuels

Sulfur measurement is

supported by each element of

the measurement industry and is

used by each member of the

fossil fuel supply chain.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

ES-6

The potential impacts of these uses for sulfur information fall within

the three categories of infratechnology impact discussed by Tassey

(1997):

Z Infratechnologies improve the efficiency of R&D. Sulfur

SRMs reduce the cost of developing new products and

processes in the sulfur measurement industry and in the

fossil fuel industry.

Z Infratechnologies support the production process and

enhance product characteristics. Sulfur SRMs support

quality control during the manufacturing and laboratory

processes.

Z Infratechnologies reduce transactions costs. SRMs allow

these measurements to be made accurately and enable

comparability among the results, thus promoting efficient

and low-cost transactions.

Table E-2 summarizes our observations about how NIST SRMs may

support production stages for each of the three industry sectors that

we discuss. We used this general characterization of the role of

infratechnologies in the economy and the potential role of NIST

SRMs for sulfur in fossil fuels to develop hypotheses about how

NIST SRMs affect each of the affected market segments.

Table ES-2. Potential Impact of SRMs on Stages of Production in the Sulfur Measurement

Supply Chain

NIST SRMS may affect several stages of production for each industry segment.

Stage of Production

Industry Sector R&D Production Market Transactions

Sulfur Measurement Industry ✓ ✓

Fossil Fuel Processing ✓✓✓

Fossil Fuel Combustion ✓ ✓

ES.2 ANALYSIS RESULTS AND IMPACT

CATEGORIES

The first step in quantifying the benefits from NIST sulfur SRMs is to

develop a counterfactual scenario from which the benefits and
Executive Summary

ES-7

costs can be measured. Our counterfactual scenario is that, in the

absence of NIST, the level of uncertainty associated with measuring

sulfur in fossil fuels would today be similar to what it was prior to

the introduction of IDMS in the early 1980s. Based on this

counterfactual assumption, we are able to express the impact of

NIST SRMs in terms of a change in the standard error (SE) of

American Society for Testing and Materials (ASTM) sulfur

measurement tests. Using the ratio of the old standard error to the

new standard error and taking into account the percentage of

measurement error associated with sampling, we estimate that NIST

SRMs improve measurement accuracy by a factor of about 1.75 for

petroleum and 1.25 for coal. These estimates allowed us to

estimate possible economic impacts of sulfur SRMs.

We interviewed several members of each of the affected industries.

Thirty-eight interviews were conducted with technical experts at 24

companies. The interviews were conducted in two stages: scoping

interviews and technical interviews. During the scoping interviews,

we learned about sulfur-content testing, methods and practices, and

the importance of accurate sulfur-content information. We then

used this information to develop and refine the questionnaire for

the technical interviews. During the technical interviews,

respondents were asked about sulfur testing and SRMs, their

impressions of the impact of SRMs, and their use of the sulfurcontent information.

We developed six hypotheses about the impact of NIST SRMs on

industry, regulatory agencies, and the environment, and we

evaluated them using data collected from primary and secondary

sources. Table ES-3 summarizes the NPV of the benefits associated

with the six hypotheses identified in this study. Of the six

hypotheses, we were able to partially quantify the benefits for four

hypotheses. Although we found anecdotal information to support

the remaining hypotheses, little concrete evidence was available.

Therefore, the potential benefits associated with these remaining

hypotheses are discussed qualitatively, but they are not included in

the estimates of economic return. In addition, industries’ avoided

expenditures on CRMs are included in the total benefit estimates.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

ES-8

Table ES-3. Net Present Value of Benefits and Costs

NIST expenditures of approximately $3.7 million lead to benefits of approximately $409 million.

Benefitsa NIST Expendituresa

H1: Improved Product Quality $2,665,422

H2: Change in R&D Costs –

H3: Change in Transaction Costs $7,542,201

H4: Improved Production Efficiency $401,408,574

H5: Change in Regulatory Penalties –

H6: Benefits to Environment $78,449,207b

Avoided CRM Expenditures $1,043,734

NIST Investment Expenditures $3,657,834

Total NPV ($1998) $409,002,097 $3,657,834

aAll benefits and costs are expressed as NPV ($1998).

bNot included in total NPV benefits summation.

The first hypothesis about the impact of SRMs on industry was that

SRMs improve the quality of the products and services of the sulfur

measurement industry, namely sulfur analysis equipment, CRMs,

and sulfur analysis services. We were only able to quantify the

impact on sulfur analysis services. Although CRM and instrument

manufacturers said NIST SRMs affected their operations,

interviewees were unable to quantify those impacts; thus, these

areas are not included in the impact estimates in Table ES-3.

Our second hypothesis was that SRMs would reduce the cost of

R&D to the sulfur measurement industry and the fuel industry by

supporting accurate, reliable sulfur measurement. Although some

of our interviewees indicated that NIST SRMs were part of their

R&D laboratories’ quality control program, they were not able to

quantify any benefits to their R&D program from NIST SRMs.

Third, we hypothesized that NIST SRMs would reduce the cost of

fossil fuel transactions because measurements are accepted as

reliable; consequently, fewer transactions are disputed because of

measurement error. Although most of our contacts indicated that,

theoretically, better measurements would reduce the number of

disputes, in actuality disputes seldom occur and only a small

proportion of them are related to sulfur measurement problems.
Executive Summary

ES-9

We used information provided by industry to estimate the total cost

of measurement disputes and assumed that 5 percent of that figure

is the cost associated with measurement error.

Our fourth hypothesis was that NIST SRMs increase the efficiency

of fuel blending, desulfurization, and equipment operations

because the reliability of the measurement allows users to reduce

the buffer they employ to ensure compliance with technical

specifications. Petroleum refineries and coal companies are the

primary beneficiaries of this impact because better sulfur

measurement allows them to reduce the amount of desulfurization

they conduct on fuels, which provides cost savings. Avoided

desulfurization accounted for approximately 97 percent of the total

benefits used to calculate measures of economic return.

Our fifth hypothesis was that improvements in the measurement of

sulfur may reduce the incidence and quantity of penalties imposed

by regulatory agencies. Thus, improved information on the sulfur

content of products may lower the cost of production by lowering

the cost of fines. Although industry experts agreed with this

hypothesis, it was determined that fines paid by industry were in

fact transfer payments and did not represent in themselves changes

in social welfare. Thus, changes in regulatory penalties were not

included in the benefit analysis.

The final hypothesis was that SRMs reduce the total amount of

sulfur entering the environment by providing industry greater

control over the sulfur content of its fuels and by allowing

compliance officials greater authority in enforcing the regulatory

limits. These benefits are not included in the total benefits

presented in Table ES-3 or in the measures of economic return

presented in Table ES-1 because they do not directly accrue to the

sulfur measurement supply chain. As with the production

efficiency hypothesis, the benefits to the environment associated

with NIST SRMs are limited to petroleum products. With NIST

SRMs, the reproducibility interval around the target sulfur content

value is smaller, which means that batches of diesel fuel and

gasoline are released with less sulfur. Lower sulfur fuels reduce the

amount of SO2 emitted to the environment. To estimate the

economic impact, we valued the additional amount of SO2 that

would have been emitted to the environment in the absence of

NIST SRMs.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

ES-10

In the absence of NIST SRMs, industry would likely purchase

CRMs. Thus, avoided expenditures on CRMs are included as a

benefit, offsetting NIST program expenditures.

The NPV of NIST’s expenditures—including development,

production, operation, overhead, and administrative costs—is

$3,657,834. Based on the benefits we were able to quantify and

NIST expenditures, the benefit-to-cost ratio associated with

NIST/Technical Laboratories sulfur SRMs since 1984 is 113.
1-1

1 Introduction

The combustion of fossil fuels provides the majority of energy

consumed in the U.S. This inexpensive and abundant source of

energy is an integral part of the U.S. economy. Energy from fossil

fuels has been and continues to be a key contributor to U.S.

economic growth and productivity.

While the combustion of fossil fuels allows us to heat our homes,

fuel our industries, and transport people and goods, it also has a

negative effect on the quality of our environment. Sulfur dioxide

(SO2) gas and other sulfur compounds are emitted during

combustion of fossil fuels that contain sulfur. These sulfur

compounds have a detrimental effect on human health, wildlife,

agricultural productivity, and quality of life and are a major

contributor to acid rain. Sulfur compounds also reduce catalyst

efficiency, increasing nitrogen oxide (NOx) and hydrocarbon

emissions from automobile engines. These negative environmental

impacts have prompted the development of regulations that limit

sulfur compound emissions from some sources and the sulfur

content of some fuels. These regulations have evolved over time

and have become more strict with respect to both sulfur content

and sulfur compound emissions.

Sulfur in fossil fuels also affects the quality of a number of products.

For example, catalysts for low-emissions vehicles are sensitive to

the sulfur content of gasoline and diesel fuel. Similarly, the

catalysts used in petroleum processing can be “poisoned” by sulfur;

sulfur affects the technical quality of other petroleum products as

well. Fuel oils used in heat-treating metals or in firing glass-melting

furnaces must be low in sulfur to avoid damaging the product. The
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

1-2

sulfur content of coke has an impact on the quality of the steel it is

used to produce.

Because sulfur has a negative effect on both the environment and

on the quality of products, low-sulfur fuels are more desirable than

high-sulfur fuels. However, because low-sulfur fuels are scarce and

removing sulfur from fossil fuels is expensive, low-sulfur fuels are

more valuable than high-sulfur fuels. The sulfur content of fossil

fuels has become increasingly important to the value of these fuels

as environmental regulations gradually lower the sulfur content

limits for fossil fuels and restrict the emission of sulfur from fossil

fuel combustion. These regulations have encouraged the

development of technologies that remove sulfur from fossil fuels

and the design of transportation and power generation equipment

that operate on low-sulfur fuel.

Because sulfur is a key characteristic of fossil fuels and an

important factor in determining their value, information about the

sulfur content of fossil fuels is important to industry This

information is used by industry in three ways:

Z Sulfur content information is used to write and execute

fossil fuel purchase contracts. It supports the millions of

fuel transactions that occur in the U.S. every year.

Z Sulfur content information is used during fuel extraction,

blending, and processing operations to improve their

efficiency. An accurate measure of the sulfur content

allows companies to meet strict product specifications.

Z Sulfur content information is used by industry and by the

regulatory community to ensure that fuels meet sulfur

content regulations and that their combustion will not

violate an emissions permit.

The National Institute of Standards and Technology (NIST)

promotes U.S. economic growth by working with industry to

develop and apply technology, measurements, and standards.

NIST, through its Office of Standard Reference Materials, is

authorized to certify and sell standard reference materials (SRMs).

SRMs are materials certified for their chemical composition or

physical properties; they are developed by various laboratories at

NIST. SRMs help users verify the accuracy of measurement

methods or calibrate measurement systems by linking their

measurements to NIST. The development of SRMs employs NIST’s

unique experience in measurement. A NIST-certified SRM carries
Section 1 — Introduction

1-3

with it the full weight and authority of NIST and the U.S.

Department of Commerce.

Among the approximately 1,300 SRMs available from NIST, 27 are

SRMs for measuring sulfur in fossil fuels. These SRMs and the

methods used to certify them are developed by NIST’s Technical

Laboratories. As emerging regulations increase the importance of

the sulfur content of fossil fuels, NIST is expanding its suite of fossil

fuel SRMs to include SRMs for measuring sulfur in the low-sulfur

fuels that are required to meet these regulations.

To provide input to NIST’s program planning and evaluation

process, Research Triangle Institute (RTI) conducted a study to

identify, characterize, and quantitatively estimate the economic

impact of NIST’s SRMs for sulfur in fossil fuels. This report

describes the study and discusses our conclusions.

1.1 NIST’S SRM PROGRAM FOR SULFUR IN

FOSSIL FUELS

All measurements depend on standards. Chemical measurements,

such as the measurement of sulfur in fossil fuels, depend on both

physical standards and chemical standards. Although early

chemical analytical measurements depended almost entirely on

physical standards, modern techniques rely more heavily on

chemical standards. This is because most modern chemical

measurements rely on comparative techniques by which an

instrument is used to compare an unknown sample with one of

known composition (Taylor, 1993).

SRMs play a key role in the National Measurement System for

Analytical Chemistry. They serve as national primary chemical

standards and are used as calibrants and as quality assurance

materials to evaluate measurement accuracy, to intercalibrate

laboratories in a measurement program, and to provide

compatibility of measurement data (Taylor, 1993). If SRMs as

primary chemical standards did not exist, the entire national

measurement infrastructure would be weakened.

NIST’s SRM program for sulfur in fossil fuels began in 1968 with the

certification of two residual fuel oil standards, SRMs 1621 and

1622, which contain 1 and 2 percent sulfur, respectively. The
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

1-4

sulfur content for both of these SRMs was certified using a

gravimetric method similar to American Society for Testing and

Materials (ASTM) D-129 (General Bomb Method). In the early

1980s, scientists at NIST (in particular, Paulsen and Kelly [1984])

began developing an application of isotope dilution mass

spectrometry (IDMS) to the certification of sulfur in fossil fuels.

IDMS is now considered a definitive method that virtually

eliminates bias in the certified value. It has significantly reduced

the uncertainty associated with the certified values, providing a

more reliable standard for all laboratories testing the sulfur content

of fossil fuels.

Today, the importance of sulfur content measurement for fossil

fuels is growing as the U.S. Environmental Protection Agency (EPA)

continues to reduce the allowable sulfur in fuels and the auto

industry moves toward lower emissions vehicles that use catalysts

that are even more sensitive to sulfur in fuels. NIST SRMs will

continue to play an important role in the measurement system for

sulfur in fossil fuels. For example, NIST recently developed SRMs

for sulfur in reformulated gasoline (RFG). RFG is required in nine

metropolitan areas of the U.S. as part of the 1990 Clean Air Act.

Two of these SRMs are certified at very low sulfur levels, consistent

with the low sulfur content currently required in California and on

the horizon nationally. NIST will continue to issue SRMs as

industry expresses the need for standards that support the analysis

of sulfur content in ultra-low sulfur fuels.

1.2 PROJECT OBJECTIVES AND SCOPE

The objective of this project is to identify, characterize, and

quantitatively estimate the economic impact of NIST’s SRMs for

sulfur in fossil fuels on the relevant industries. We need to

understand how the sulfur content of fossil fuels affects the

economy and how information about sulfur content affects the

economic decisions of agents in the economy. By modeling those

decisions, we can quantify how the world would be different in the

absence of the NIST SRMs that improve the accuracy and precision

of these measurements.

NIST’s SRM program includes over 1,300 SRMs. For this project,

we examined only the 29 SRMs shown in Table 1-1. Each of these

SRMs supports measurement methods used to determine the sulfur

content of fossil fuels.
Section 1 — Introduction

1-5

Table 1-1. NIST SRMs Covered by this Study

This study examines the impact of 27 existing SRMs and two SRMs that were still under development in early 1999.

SRM

Number Description

First Certificate

Datea Years of Reissue

1616 Sulfur in Kerosene 2/19/88 1995

1617 Sulfur in Kerosene 2/19/88 1995

1619 Sulfur in Residual Fuel Oil, 0.7% 12/22/81 1991, 1998

1620 Sulfur in Residual Fuel Oil, 4% 12/1/79 1981, 1990

1621 Sulfur in Residual Fuel Oil, 1% 12/11/67 1980, 1981,

1986, 1991, 1996

1622 Sulfur in Residual Fuel Oil, 2% 12/11/67 1979, 1981,

1986, 1991, 1997

1623 Sulfur in Residual Fuel Oil, 0.3% 4/7/71 1981, 1990, 1996

1624 Sulfur in Distillate Fuel Oil, 0.4% 4/7/71 1981, 1990, 1997

1819 Sulfur in Lubricating Base Oil 7/17/85 1994

2294 Reformulated Fuels (nom. 11% MTBE, 35 mg/kg sulfur) 3/10/98

2295 Reformulated Fuels (nom. 15% MTBE, 300 mg/kg sulfur) 3/10/98

2296 Reformulated Fuels (nom. 13% ETBE, 35 mg/kg sulfur) 3/10/98

2297 Reformulated Fuels (nom. 10% Ethanol, 300 mg/kg sulfur) 3/10/98

2717 Sulfur in Residual Fuel Oil 10/25/90

2718 Green Petroleum Coke 7/15/99

2719 Calcined Petroleum Coke 7/15/99

2724 Sulfur in Distillate Fuel Oil, 0.04% 8/17/92 1995

1632 Trace Elements in Coal (Bituminous) 3/7/75 1978, 1998

1633 Trace Elements in Coal Fly Ash 3/7/75 1979, 1993

1635 Trace Elements in Coal (Subbituminous) 10/24/95

2682 Sulfur in Coal, 0.5% 12/14/82 1998

2683 Sulfur in Coal, 2% 12/14/82 1992, 1997

2684 Sulfur in Coal, 3% 12/14/82 1992

2685 Sulfur in Coal, 5% 12/14/82 1994

2690 Trace Elements in Coal Fly Ash 12/20/93

2691 Trace Elements in Coal Fly Ash 12/20/93

2692 Sulfur in Coal, 1% 11/15/88 1994

2775 Foundry Coke 5/12/99

2776 Furnace Coke 3/19/98

aThe first certificate date indicates the date that the certificate was issued for the first batch of this SRM. As new batches

are developed, new certificates are issued and the SRM is redesignated with an appropriate letter after the number

signifying which batch it is from. For example, SRM 1632a was the second batch of 1632; SRM 1632b was the third

batch of 1632.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

1-6

Many companies and individuals benefit from the availability of

SRMs that improve the measurement of the sulfur content of fossil

fuels. We focused on those industries that make the most extensive

use of these SRMs and benefit most directly from their use. These

industries include

Z the sulfur measurement industry, including manufacturers of

sulfur measurement instruments, certified reference

materials (CRM), and independent laboratories that conduct

sulfur analysis;

Z the fossil fuels extraction, processing, and transportation

industry, including coal processing, petroleum refining, and

coke production;1 and

Z primary users of fossil fuels, including the electric utility

industry and the steel industry. Industrial combustion also

accounts for a large percentage of the fossil fuels consumed

in the U.S. However, because of the difficulty of

characterizing the diverse set of industries that engage in

industrial combustion, we did not address industrial

combustion in this study.2

1.3 SUMMARY OF ANALYTICAL APPROACH AND

REPORT ORGANIZATION

NIST SRMs support the measurement of sulfur in fossil fuels. These

measurements are provided by a sulfur measurement industry and

support economic activity in the entire fossil fuel supply chain. To

estimate the economic impact of SRMs for sulfur in fossil fuels on

these industries, we employed a methodology that allowed us to

value the economic outcomes resulting from decisions that use the

improved information provided by NIST SRMs. Figure 1-1 provides

an overview of this method. First, we examined how NIST SRMs

affect the measurement of sulfur in fossil fuels, including the

accuracy of these estimates and the cost of conducting these tests.

Second, we evaluated how improvements in measurement quality

provided by NIST SRMs affect the behavior of people and

 1Although natural gas would normally be included in this characterization, we did

not analyze the natural gas industry because NIST does not provide an SRM for

sulfur in natural gas. As described in Section 2, this is because very little sulfur

is found in natural gas, and its measurement is not an important industry issue.

2Industrial combustion refers to the use of industrial, commercial, and institutional

(ICI) boilers whose primary use is for process heating, electrical or mechanical

power generation, and/or space heating.
Section 1 — Introduction

1-7

Figure 1-1. Analytical Approach to Assessing the Impact of NIST’s Technical Laboratories

Sulfur in Fossil Fuel SRMs

This five-step analytical approach captures the benefits and costs of NIST’s SRMs for sulfur in fossil fuels.

Step 1:

Evaluate SRM Impact

on Measurement

Accuracy and Cost

Step 2:

Identify Expected

Changes in Behavior

Due to Improved

Accuracy

Step 3:

Quantify and Value

the Economic Benefits

of Changes in

Behavior

Step 4:

Determine the Cost to NIST of

Developing SRMs for Sulfur in

Fossil Fuels and the Costs of

Transferring the Measurement

Infrastructure to Industry

Step 5:

Estimate

Measures of

Economic Return

to NIST’s

Investment in

SRMs for Sulfur in

Fossil Fuels

Benefits

Costs

companies that use sulfur content measurements. Third, we

quantified and valued the economic benefits of these changes in

behavior to provide a numerical estimate of the benefits of the NIST

SRMs. We then compared those benefits with the costs of the SRM

program and estimated measures of economic return to society’s

investment.

This report is organized into seven sections. Section 2 provides

background on the industries affected by the measurement of sulfur

in fossil fuels and contains some of the basic economic information

needed to conduct our analysis. Section 3 describes how sulfur in

fossil fuels is measured, why these measurements are subject to

error, and how NIST’s SRM program has improved the

measurement of sulfur in fossil fuels over time. Section 4 describes

our approach to valuing improvements in the accuracy of the

measurement of sulfur in fossil fuels. It explains how sulfur

information affects industry, lists our hypotheses for the study, and

describes impact measures for quantifying technical and economic

impacts. It also describes the data we used to conduct the analysis
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

1-8

and the data collection process. Section 5 describes the results of

the study, carefully reviewing the evidence to support or refute

each of the hypotheses developed in Section 4. Section 6 explains

why NIST has played, and will continue to play, such an important

role in the development of these SRMs. Section 7 offers

conclusions based on our analysis and observations about the role

of NIST SRMs in industry.
2-1

Overview of 2 Affected Industries

The combustion of fossil fuels provides 85 percent of the energy

consumed in the U.S. Each year U.S. households and industry

consume 1 billion tons of coal, 7 billion barrels of oil, and 20,000

cubic feet of natural gas (U.S. DOE, 1998a). Fossil fuels affect

virtually every sector of the U.S. economy because they provide the

power required to manufacture goods; heat and cool homes,

offices, and factories; provide services; and transport people and

goods.

Sulfur is an important factor in determining the value of fossil fuels.

Increasingly strict environmental regulations limit the sulfur content

of some fuels and also limit sulfur compound emissions that result

from its combustion. Sulfur also has a negative impact on the

quality of some products and processes. Removing sulfur from

fossil fuels is expensive, and the natural sulfur content of these fuels

is increasing.

Because sulfur is an important determinant of the value of fossil

fuels, an accurate measurement of the sulfur content of fossil fuels

and of downstream products is essential to support commerce.

These measurements also help industry demonstrate regulatory

compliance and control the quality of their products.

NIST SRMs facilitate measurements and standards throughout the

fossil fuel supply chain. The measurement industry uses NIST SRMs

to verify the quality of their instruments’ calibration, reference

materials, and measurement procedures. The fossil fuel extraction

companies and their customers use NIST SRMs similarly to verify

the quality and reliability of the measurements they make for

transactions, process control, and environmental compliance. The
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

2-2

regulatory community uses SRMs to ensure environmental

compliance by the regulated industries.

Figure 2-1 illustrates the relationships among the industries in the

supply chain. Appendix C contains profiles of the industries that

use SRMs to measure sulfur content. It describes the importance of

sulfur as a characteristic of fossil fuels; includes a profile of the

affected industries; and describes how NIST SRMs support these

industries.

NIST

Processed

Fossil Fuels

Fossil Fuel Combustion

• Electricity Generation

• Steel Industry

• Industrial Combustion

Users of Power, Steel, and

Other Goods and Services

Power and

Steel

SRMs

Sulfur Measurement

Products and Services

Fossil Fuel Extraction, Processing, and

Transportation

• Coal Processing

• Petroleum Refining

• Coke Production

Sulfur Measurement

• Instrument Manufacturers

• Manufacturers of Certified Reference

Materials

• Independent Testing Laboratories

Figure 2-1. Industries

Affected by

Measurement of Sulfur in

Fossil Fuels

Sulfur measurement is

supported by each element of

the measurement industry and is

used by each member of the

fossil fuel supply chain.
Section 2 — Overview of Affected Industries

2-3

This section provides an overview of the key industries discussed in

Appendix C. Although many industries engage in the measurement

of sulfur content, we concentrated on three sectors—sulfur

measurement industry, coal processing, and petroleum refining—

because they are primary users of SRMs for their in-house sulfur

measurement activities.1

2.1 SULFUR MEASUREMENT INDUSTRY

The industry that supports the measurement of sulfur in fossil fuels

includes the manufacturers of instruments, suppliers of CRMs, and

independent laboratories that conduct sulfur analysis.

2.1.1 Instrument Manufacturers

Determinators, spectrometers, elemental analyzers, and

chromatographers are measurement equipment used to determine

the elemental composition of organic and inorganic samples.

Manufacturers and consumers of these measurement instruments

use NIST’s sulfur SRMs to test and calibrate their equipment. These

instruments must be properly calibrated to provide quality

laboratory results. Sulfur SRMs allow technicians to test an

instrument’s accuracy and inform them of any need for

adjustments. Equipment technicians may use NIST’s sulfur SRMs

directly, or they may use NIST-traceable CRMs from a secondary

manufacturer to calibrate laboratory equipment.

2.1.2 Manufacturers of Certified Reference Materials

A certified reference material (CRM) is defined by the International

Standards Organization (ISO) as “a reference material one or more

of whose property values are certified by a technically valid

procedure, accompanied by or traceable to a certificate or other

documentation which is issued by a certifying body” (American

National Standards Institute [ANSI], 1981). CRMs are used in the

same way as NIST SRMsfor equipment calibration, development

of other standards, and quality control for analyzing sulfur in fossil

fuels. CRMs are often used in conjunction with NIST SRMs. In

many laboratories, CRMs are used on a daily basis while NIST

SRMs are used only occasionally.

 1Appendix C also contains an overview of the coke, electricity, and steel industries

and discusses sulfur measurement issues related to these industries.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

2-4

CRMs are generally prepared using NIST SRM

products (when available) and ASTM procedures.

However, none of the CRM producers duplicate the

procedures followed by NIST. NIST SRMs for sulfur

in fossil fuels are certified using a technique known

as IDMS. As explained in Section 3, IDMS is a

definitive method that virtually eliminates bias and

significantly reduces the relative uncertainty

associated with reference materials. No commercial

CRM manufacturers use IDMS; instead, they employ

ASTM methods and/or interlaboratory testing for

certification. The less rigorous process used by the

CRM manufacturers can sometimes lead to significant

differences between the accuracy and precision of

the certified values provided by NIST and those

provided by a CRM manufacturer.

2.1.3 Independent Sulfur Testing Laboratories

Independent sulfur testing laboratories fall within SIC 8734, Testing

Laboratories. In 1992, the U.S. had over 4,500 commercial testing

laboratories generating almost $5 billion in revenue and $2 billion

in payroll each year (U.S. DOC, 1994).2 A small subset of these

laboratories conducts sulfur analysis of fossil fuels. These

laboratories provide inspection, sampling, and analytical services

for fossil fuel producers and consumers.

Independent laboratories are an important link in the supply chain

affected by SRMs. Although many mines, coking plants, coal

preparation plants, utilities, and refineries have their own

laboratories for these analyses, independent laboratories are

becoming more important, particularly for contractual matters.

Third-party independent laboratory results are routinely used to

satisfy contractual requirements for buyers and sellers in the coal

industry, and this arrangement is increasing in the petroleum

industry as well. To cut costs, some firms also hire independent

laboratories rather than operate their own.

 2These figures include taxable firms only. Noncommercial research organizations

are not included.

Traceability ensures that secondary standards,

such as CRMs, can be linked to national

standards. However, the length of the pathway

from the user of a measurement back through

intermediate calibration to national standards

or fundamental constants has an important

effect on the level of uncertainty of the

measurement. With each transfer point along

the traceability pathway, the accuracy of the

measurement degrades because each

laboratory introduces its own measurement

error to the process. Furthermore, it is not

always a simple matter to interpret the

uncertainty measurements provided by

intermediate laboratories. For this reason, it is

generally presumed that a shorter traceability

pathway is preferred when uncertainty must be

minimized or when knowledge of uncertainty

is important (Garner and Rasberry, 1993).
Section 2 — Overview of Affected Industries

2-5

2.2 COAL INDUSTRY

The U.S. coal industry produces and distributes 1.1. billion short

tons of coal per year. The industry consists of a few very large

companies that produce more than 50 percent of total coal

production and many mid-size and small companies. Information

about the sulfur content of coal is very important to this industry

because the price of coal is a function of its sulfur content among

other attributes. Removing sulfur from coal is expensive, and the

sulfur content of coal determines whether an electric utility plant

that burns it can meet its regulatory emissions requirements for

SO2.

Coal is generally classified into four sulfur categories: compliance,

low sulfur, medium sulfur, and high sulfur. Compliance coal has

the lowest sulfur content—0.6 pounds per million Btus or less. It

naturally falls within federal emissions regulations and therefore

requires less cleaning before combustion. Low-sulfur coal has

between 0.61 and 1.25 pounds of sulfur per million Btus, medium

sulfur coal between 1.26 and 1.67 pounds per million Btus, and

high-sulfur coal more than 1.67 pounds per million Btus.

Coal’s sulfur content varies by the location from which it is mined.

Generally, western coal (from Colorado, North Dakota, and

Wyoming, for example) is lowest in sulfur; Appalachian coal (from

Pennsylvania, West Virginia, and Kentucky, for example) is either

low or medium sulfur; and interior coal (from Indiana, Illinois,

Ohio, for example) is medium and high sulfur.

2.2.1 Coal Cleaning and Processing

Coal processing entails the mining, cleaning, and distribution of

coal from underground and surface mines. Figure C-4 in

Appendix C provides an overview of activities, inputs, and outputs

of the coal processing industry.

Coal is extracted from two categories of mines: underground and

surface mines. Underground coal mining entails cutting a slot,

known as a kerf, at the bottom of a face; drilling holes in the face

for explosives or compressed air; blasting the coal; and loading and

hauling it out of the working area to a conveyor belt or mine cars

(Pennsylvania Department of Environmental Protection, 1999).

Surface mining refers to the removal of dirt and rock on top of a
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

2-6

coal seam so that it can be excavated, placed on conveyors, and

sent to preparation plants. Strip mining is the most popular surface

mining method in the U.S.

On-site coal preparation plants make coal more valuable through

size reduction, desulfurization, and removal of moisture and

inorganic impurities. Nearly 50 percent of the coal mined in the

U.S. passes through coal preparation plants; east of the Mississippi

River this number increases to 80 percent (Fonseca, 1995). Coal

preparations, which “clean” coal by removing impurities, may

account for 5 to 15 percent of the cost of coal production (Horton

and Bloom, 1993).

Coal preparation plants remove coal mechanically by taking

advantage of differences between the impurities and the coal’s

density. Water is used to fluidize a bed of crushed coal and its

contaminants. As the lighter coal particles float to the top, the

impurities are separated. The coal is then skimmed off the top of

the bed and dried using a combination of hot gases. Coal is also

blended to meet customer specifications. For example, high- and

low-sulfur coal can be mixed together as part of the preparation

and cleaning process to ensure the sulfur content of the delivered

coal meets sulfur levels specified in contracts.

2.3 PETROLEUM INDUSTRY

The U.S. petroleum industry supplies over 6 billion barrels of

petroleum products per year. The industry is dominated by a small

number of large, vertically integrated companies. This structure is

driven by the large capital costs associated with the petroleum

refining technology.

The main determinants of crude oil prices are sulfur content (sweet

versus sour) and API gravity (light versus heavy). High API gravity,

or light crude, is more valuable because it is used in more high-end

products when distilled and has fewer impurities. Sulfur

information allows refineries to control the sulfur content of output

streams and emissions. Both are required for regulatory

compliance

The composition of crude oil varies greatly from field to field

throughout the world. For example, Alaskan crude typically has a

low sulfur content (sweet), and South American crude typically has
Section 2 — Overview of Affected Industries

2-7

a high sulfur content (sour). Crude oil with a high sulfur content is

more expensive to refine because it is difficult to separate sulfur

compounds from pure hydrogen/carbon compounds (Leffler, 1985).

2.3.1 Petroleum Processing and Desulfurization

Petroleum refining is the physical, thermal, and chemical

separation of crude oil into its major distillation fractions, which are

then further processed through a series of separation and

conversion steps into finished petroleum products and chemical

industry feedstocks.

Sulfur is removed from petroleum products by reacting it with

hydrogen gas in the presence of a catalyst at a moderately high

temperature and pressure. This process is referred to as

hydrodesulfurization or hydrofinishing. In addition to

desulfurization of final products, sulfur recovery for sale of

elemental sulfur is also conducted for refinery process off-gas

streams as part of emissions reduction activities. The sulfur is

converted to hydrogen sulfide, which is then absorbed through

desulfurization of stack gases.

Desulfurization of petroleum output streams can be very expensive.

As part of background research for the development of its new

sulfur content in gasoline regulations, EPA developed estimates of

the cost of removing sulfur from gasoline. As shown in Table C-16

in Appendix C, for example, reducing the sulfur content of gasoline

from 330 ppm to 40 ppm costs about 1.6 cents per gallon.3

Maintaining specific sulfur levels in output streams and process offgas streams is difficult because of the varying content of sulfur in

crude oil. Accurate information about the sulfur content of the

crude oil and the output streams is essential to maintaining product

specifications and maximizing the efficiency of the processing

equipment.

 3The American Petroleum Institute (API) believes that EPA underestimated the

added cost of reducing the sulfur content of gasoline below current levels. The

trade association funded a series of studies conducted by MathPro that

estimated the cost to be 2.3 to 2.6 cents per gallon (Octane Week, 1999).

Although API’s estimates are provided in Table C-16, the economic estimates

presented in this study are based on the more conservative EPA estimates of

approximately 1 cent per gallon.
3-1

SRMs and Sulfur 3 Measurement

To assess the economic impact of SRMs on the affected industries,

we must first assess the impact of NIST SRMs on the accuracy of

sulfur content measurement. In this section, we demonstrate that

NIST SRMs are responsible for reducing the bias and improving the

precision of sulfur content measurement in industry. We quantify

the relationship between NIST SRMs and sulfur measurement

accuracy and use this relationship in the next stage of the analysis.

We begin by describing the sources of variability in measurement

and how this variability is quantified. Then we describe the ASTM

methods used most frequently to measure the sulfur content of

fossil fuels, including the role of reference materials in these

methods. We explain how bias and uncertainty in a reference

material introduce bias and uncertainty into the measurement

process. In Section 3.3, we describe the process of SRM

development and the history of the NIST SRM program for sulfur in

fossil fuels. We demonstrate the relationship between NIST’s

methodology development and the reduction in uncertainty and

bias associated with the certified values of NIST SRMs. Finally, we

conclude that, in the absence of the NIST SRM program, the

accuracy of measurements of sulfur in fossil fuels would today be

similar to what it was prior to the introduction of new NIST

methods in the early 1980s.

3.1 UNCERTAINTY IN THE MEASUREMENT OF

SULFUR IN FOSSIL FUELS

All measurements, including measurements of the sulfur content of

fossil fuels, are subject to some uncertainties. The measured value
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

3-2

of a variable is a function of both its true value and the

measurement system. The measurement system contains a number

of elements that contribute to uncertainty in measurement (Taylor,

1997; Bentley, 1983). Uncertainties of analytical measurements

must be quantified so that decision-makers can understand the

degree of reliability of the result. NIST SRMs play a role in both

reducing and quantifying the uncertainty of field laboratory

measurements.

3.1.1 Sources of Variability in Measurement

A number of factors contribute to uncertainty in measurement.

NIST defines accuracy as the closeness of a measured value to the

true value. Accuracy is a “relative” measure and includes both the

concepts of precision and bias. Precision refers to the variability of

individual results of replicate measurements. Bias is the difference

between the observed mean of those measurements and the true

mean (Taylor, 1993).

The ASTM defines the sources of variability of a measurement

method, each of which belongs to one of the following categories:1

Z the operator

Z the apparatus

Z the environment

Z the sample

Z time

The operator must interpret the test method and execute it. The

greater the clarity of the test method, the less it is open to incorrect

interpretation. Different operators (and the same operator at

different times) introduce variability into the process because of

differences in dexterity, reaction time, color sensitivity, ability to

interpolate scale readings, and so forth.

Apparatus typically allow variations in measurements due to

specification tolerances. Because no apparatus can be built that

has zero tolerance, these variations are one source of variability

between test results from different test equipment. Apparatus

calibration is also a potential source of error. An instrument that is

not calibrated correctly or is calibrated to an incorrect standard

 1This section is taken from ASTM Method E 177.
Section 3 — SRMs and Sulfur Measurement

3-3

may introduce bias into the measurement process. NIST SRMs for

sulfur in fossil fuels directly impact this potential source of bias.

The environment also contributes to measurement uncertainty.

Although test methods typically specify the standard environmental

conditions for testing, these factors cannot be controlled perfectly.

Thus, slight differences in environment yield differences in test

results.

Another source of uncertainty is sampling. A batch or lot of

material to be tested (such as a shipment of coal or tank of fuel) is

rarely perfectly uniform. Sampling methods are typically employed

to ensure that the sample is representative of the lot; however,

sampling is often (especially in the case of coal, which is typically

very heterogeneous) a large source of measurement uncertainty.

All of the above sources of uncertainty in measurement can change

over time, and this contributes to variability in measurement. For

example, the environment in a laboratory may change

systematically over time. Thus, the longer the amount of time

between different realizations of a test method, the greater the

potential variability in the results.

These sources of uncertainty suggest strategies to reduce

uncertainty in the measurement process. Variability due to the

operator can be reduced by providing clear, complete instructions

to operators regarding the proper methodology. Careful training

and quality control in the execution of the method might also

reduce the uncertainty associated with the test method.

Uncertainty due to the apparatus can be reduced by improving the

instrument’s tolerances, by more careful (or more frequent)

calibration and quality control of the instrument, or by calibration

to a more reliable standard. Calibration to a more reliable standard

and the ability to perform quality control against a known is

perhaps the primary contribution of NIST SRMs to reducing

uncertainty in measurement. They also allow the bias and

precision of a measurement process to be quantified.

Variability due to the environment can be reduced by carefully

controlling the conditions under which measurements are made.

Uncertainty due to the sample can be reduced by taking more

samples or by taking more composites of a sample.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

3-4

3.1.2 Quantifying the Uncertainty of a Measurement

Process

We can describe two aspects of uncertainty associated with a

measurement: bias and precision. These concepts are illustrated in

Figure 3-1 and discussed below.

Figure 3-1. Bias and Precision in Test Methods

Bias is the difference between the mean of a set of test results (x–) and the accepted value (x*); precision is a measure of

the dispersion of the test results.

Frequency

Without NIST

Percent Sulfur

Content

_

x

Precision

Bias

x*

The bias of a measurement process describes the relationship

between the test results from the process and an accepted reference

value. The bias of a measurement process is determined by taking

the average of a large set of test results (x–) and comparing it against

the accepted reference value. In Figure 3-1, if x* is the accepted

reference value, then the bias of the measurement system is Ix– – x*I.

If an accepted reference value is not available, the bias cannot be

established. The accepted reference value is a value that serves as

an agreed-upon reference for comparison. It may be a theoretical

or established value based on scientific principles (which is

sometimes called the “true” value), or it may be an assigned or

consensus value based on experimental work. The certified values

of a NIST SRM are universally accepted reference values.

If the bias in a test method is known, an adjustment for the bias can

be incorporated into the test method. Thus, one important benefit

One important contribution

of NIST SRMs is the

establishment of a

reference value so that the

bias of a measurement

method can be determined.

An analyst can then

compensate for the

measurement method’s

bias.
Section 3 — SRMs and Sulfur Measurement

3-5

of having an accepted reference value is the ability to assess and

adjust for the bias.

The precision of a test method refers to the closeness of agreement

among multiple test results obtained under similar conditions. The

greater the dispersion of the results, the poorer the precision. Two

different types of precision are commonly determined for a test

method. Repeatability (r) is determined by conducting the method

repeated times under similar conditions within a single laboratory,

by the same operator, with the same equipment, in the shortest

practical period of time. Reproducibility (R) is determined from the

results of tests obtained in different (independent) laboratories

under similar conditions.

Precision is often expressed as an index in the same units as the test

result. These indexes are related to the estimate of the sample

standard deviation, s, of a random set of test results. The two

indexes of precision used most commonly by the ASTM for sulfur in

fossil fuels are as follows:

Z Two Standard Deviation Limits (2s). This measure of

precision refers to an interval that expresses the dispersion

of individual test results in relation to the average value.

Ninety-five percent of individual test results from similar

labs will differ from the average value in absolute value by

less than 1.96 s. In Figure 3-1, if x– is the average of results

of an interlaboratory study, then 95 percent of individual

test results from similar labs will fall within the interval

x

– ± 1.96 s.

Z Difference “Two” Standard Deviation Limit (d2s). This

measure of precision refers to the dispersion of pairs of test

results relative to each other. In Figure 3-2, suppose x1 and

x2 are a pair of test results from laboratories similar to those

in the study. In 95 percent of all pairs, x1 and x2 will differ

in absolute value by less than 1.96 2 s.2

 2If the variance of an observation x is equal to s2, then the variance of a difference

in such observations, if they are uncorrelated, will be 2s2; Var(x1 – x2) = Var(x1)

+ Var(x2) = 2s2. Hence, the standard deviation of the difference will be 2s,

and the interval estimate to contain 95 percent of such differences will be 1.96

2s.

The standard deviation

(denoted by s) of an ASTM

method can be determined

from the stated 2s interval

by dividing the interval in

half and then dividing it by

1.96. Similarly, s can be

determined from the d2s

interval by dividing the

interval in half and then

again by 1.96 2.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

3-6

Frequency

of x2

Percent

Sulfur

d2s Interval Content

x1 x1 – 1.96 2 s x1 + 1.96 2 s

3.2 METHODS FOR MEASURING SULFUR IN

FOSSIL FUELS

Although a number of methods exist for measuring sulfur in fossil

fuels, industry relies increasingly on instrumental methods that

require the use of calibrants. The accuracy of these methods

depends a great deal on proper calibration and quality control

procedures. NIST SRMs provide a reference material that can be

used as a calibrant, a check on the true value of a calibrant, and a

quality control material for ensuring that the method is providing

accurate results.

This section provides a brief description of these methods and

describes the importance of NIST SRMs in ensuring their accuracy.

The first section reviews the most common methods for measuring

sulfur in coal. The second section reviews the most common

methods for measuring sulfur in petroleum products. The last

section describes the statistical relationship between the accuracy

of the certified value of a reference material and the accuracy of the

sulfur content measurements supported by those reference

materials.

3.2.1 Sulfur in Coal

The method used most often for measuring the sulfur content in

coal is ASTM method D 4239, Sulfur in the Analysis Sample of Coal

Figure 3-2. Difference

“Two” Standard

Deviation Limit (d2s)

Any pair of test results, X1 and

X2, will lie within the d2s

interval 95 percent of the time.
Section 3 — SRMs and Sulfur Measurement

3-7

and Coke Using High-Temperature Tube Furnace Combustion

Methods. This method actually comprises three different methods:

Z High-Temperature Combustion Method with Acid Base

Titration Detection Procedures

Z High-Temperature Combustion Method with Iodimetric

Titration Detection Procedures

Z High-Temperature Combustion Method with Infrared

Absorption Detection Procedures

Among these three methods, the most common is the last. This

method uses an infrared (IR) absorption detector to measure the

amount of sulfur dioxide present in a sample of coal that is burned

in a tube furnace. The method is based on the fact that sulfur

dioxide absorbs IR energy at a precise wavelength within the IR

spectrum. The amount of sulfur dioxide in the sample is

proportional to the change in energy at the detector. Because this

method is empirical, the apparatus must be calibrated.

The infrared detection system must be calibrated using SRMs,

reference coals, or calibrating agents with known dry-basis sulfur

values in the range of the samples to be analyzed. These SRMs,

reference coals, or calibrating agents must have precision values of

less than or equal to method repeatability.3 They must be stable

with respect to moisture and pulverized to pass 100 percent

through a 0.250 mm (no. 60) USA Sieve.

Precision and Bias

ASTM reports the precision for the IR method as both the 2s method

and the “d2s” measure described above. The precision intervals

are reported in Table 3-1. These precision statements are valid for

determining sulfur in the concentration range from 0.28 to 5.61

percent. The ASTM notes that this method has no bias if the

instrument is properly calibrated against certified reference

standards. This underscores the importance of unbiased SRMs in

using this method.

 3NIST SRMs meet this criterion. For example, the NIST SRM for sulfur in coal,

2 percent (2683b), has a 95 percent confidence interval of ±0.041 percent, or

0.082 (NIST, 1997). At 2 percent sulfur, the repeatability interval for ASTM

4239 is about the same [0.02 + 0.03(2)] = 0.08 (ASTM, 1998).
3-8

Table 3-1. Characteristics of ASTM Testing Methods Used Most Often for Testing Sulfur in Fossil Fuels The most frequently used methods for measuring sulfur in fossil fuels are instrumental methods; their accuracy depends on an unbiased calib

ASTM Method Number Title Method Summary Key Apparatus SRM Usage Bias Repeata

(r) (2s) 

D 4239a (Method C) Sulfur in the Analysis Sample of Coal and Coke Using High- Temperature Tube Furnace Combustion Methods Uses IR absorption detector to measure the amount of IR absorption from a sample of coal that is burned in a tube furnace. Relationship between sulfur content and IR absorption is established by a calibration curve. Commercially available sulfur analyzers with infrared detection systems Used for calibration and periodic calibration verification None when instrument is properly calibrated 0.02 + 0.

x– = averatwo resul

S

D 2622 Sulfur in Petroleum Products by X-Ray Spectrometry Uses an X-ray spectrograph to measure the intensity of sulfur radiation after the sample has been subjected to an X-ray beam. The relationship between radiation intensity and sulfur content is established by the calibration procedure. X-ray spectrograph Used for calibration quality control No bias when appropriate corrections are applied r 0.60 * 

0.20 * 0.05 * 

D 5453 Determination of Total

Sulfur in LightHydrocarbons, MotorFuels, and Oils byUltravioletFluorescence

Uses an ultraviolet (UV)fluorescence detector to measurethe amount of energy emitted fromcombustion gases after they havebeen exposed to UV light.Relationship between sulfurcontent and energy emission isestablished by a calibration curve.

UVfluorescencedetector

Used forcalibrationquality control

Notreportedb

0.1867(x

–

x–

 = avera

two resul

aThis ASTM method number covers three methods. This table discusses Method C, which uses infrared absorption detection procedures.bASTM reported that test results obtained on the SRM were within the repeatability of the test method.
Section 3 — SRMs and Sulfur Measurement

3-9

Before coal can be analyzed for sulfur content, it must be sampled

and prepared for analysis. Sampling and sample preparation are a

significant source of uncertainty in coal sulfur content

measurement. Two ASTM methods cover the procedures used for

sampling coal:

Z ASTM D 2234, Standard Practice for Collection of a Gross

Sample of Coal

Z ASTM D 2013, Standard Method of Preparing Coal Samples

for Analysis

As described below, one way to improve the precision of the

measurement of sulfur in fossil fuels is to increase the number of

samples taken, analyze them separately, and report the average of

the results. As described in ASTM D 2234, the control limits theory

defines the relationship between the number of samples and

precision. For example, to reduce the uncertainty by one-half

(double the precision), four times as many gross samples must be

taken. Similarly, to reduce errors to one-third (triple the precision),

nine times as many gross samples must be taken. Increasing the

number of increments in a gross sample can also increase the

measurement’s precision.

3.2.2 Sulfur in Petroleum Products

The methods used most often for measuring the sulfur content of

petroleum products are ASTM D 2622, Sulfur in Petroleum

Products by X-Ray Spectrometry, and ASTM D 5453, Determination

of Total Sulfur in Light Hydrocarbons, Motor Fuels, and Oils by

Ultraviolet (UV) Fluorescence.

D 2622 is required by EPA for verifying sulfur in diesel fuel. It is

also required by the California Air Resources Board (CARB) for

determining the sulfur content of high-sulfur fuels (exceeding 1,000

ppm). ASTM Method D 5453 is required by CARB to determine

sulfur levels in low-sulfur fuels (1 to 8,000 ppm). D 5453 is much

more sensitive than D 2622.

In ASTM D 2622, the sample is placed in an X-ray beam, and the

intensity of the sulfur radiation is measured by an X-ray

spectrograph. The calibration procedure establishes the

relationship between radiation intensity and sulfur content. The

measured intensity is then compared to the previously established

calibration curve to obtain the concentration of sulfur.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

3-10

The precision of this method is a function of the sulfur content of

the sample. As shown in Table 3-1, the repeatability and

reproducibility intervals, as a percentage of sulfur content, fall as

the sulfur content grows.

In ASTM D 5453, a sample of a hydrocarbon is oxidized to SO2.

The sample combustion gases are exposed to ultraviolet light. A

UV fluorescence detector is used to measure the light emitted by

SO2. The sulfur contained in the sample is a function of emitted

light. The calibration procedure establishes the relationship

between emitted light and sulfur content.

The precision of this method is shown in Table 3-1. As in the case

of Method D 2622, the intervals become smaller (as a percentage of

the concentration) as the concentration rises.

Both of these methods depend entirely on establishing a calibration

curve, which, in turn, depends on a reliable calibration standard. If

the calibration standard used to establish the calibration curve is

biased, then the estimate of the sulfur content will be biased as

well.

Petroleum products must also be sampled prior to analysis.

Sampling of petroleum products is not as problematic as sampling

of coal, because the product tends to be more homogeneous.

ASTM Method D 4057 addresses practices for manual sampling of

petroleum and petroleum products. Sampling crude petroleum and

residual fuel oils is generally more difficult than sampling gasoline

and distillate products because they are less homogeneous than

gasoline and distillate products.

3.2.3 Reference and Sulfur Measurement

The instrumental methods used most often to measure the sulfur

content of coal and petroleum products described above are based

on the classic linear calibration model shown in Figure 3-3. They

rely heavily on the use of standards and calibrants. As shown in the

figure, if bias exists in the calibration standard used to calibrate the

instrument this will translate to bias in the instrument’s sulfur

measurements.4

 4Bias in the calibration standard is one potential counterfactual in the absence of

NIST SRMs.
Section 3 — SRMs and Sulfur Measurement

3-11

Figure 3-3. Classical Linear Calibration Model

If bias exists in the calibration standard this will lead to bias in the estimate of the slope of the curve and bias in

estimates of the sulfur content.

y

(Instrument

Response)

x (Sulfur Content)

y = α + (β/P)x

Calibrated response curve

when x is biased

y1

x Px1 1 Px2 Px3 x2 x3

y = α + βx

Actual response curve

bias in x when y = y1 is observed

y

y3

y2

Similarly, uncertainty about the certified value of a standard

introduces uncertainty and additional bias to the measurements

taken using the standard. The variance of the mean of n

observations increases proportionately with the variance associated

with the standard. These relationships are developed formally in

Appendix A.

We can use these relationships to develop simulations of the impact

of bias and variance in a reference material on the repeatability and

reproducibility of ASTM methods. As noted above, bias in the

certified value of a reference material translates into bias in the

measurement of sulfur content. Thus, if NIST SRMs eliminate bias

in calibration standards, they also remove bias from the

measurement method.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

3-12

3.3 IMPACT OF NIST SRMS ON THE

MEASUREMENT OF SULFUR IN FOSSIL

FUELS

NIST’s SRM Program for sulfur in fossil fuels has improved the

accuracy of the measurement of sulfur in fossil fuels. NIST’s SRM

development process is designed to provide a reference material

that is unbiased and traceable to the System Internationale (SI)

units. NIST’s SRM program for sulfur in fossil fuels uses a definitive

method, developed at NIST, that virtually eliminates bias and

significantly reduces the uncertainty of the SRMs. Without the

development of this method, sulfur measurement in industry would

be subject to greater bias and uncertainty.

3.3.1 SRM Development Process

SRMs are developed in response to the measurement needs of

industry and other NIST customers. Funding for research to support

SRM development can come from NIST internal research funds,

other government agencies, as well as from industry. The

incremental costs associated with producing SRMs and maintaining

the SRM program are recovered through sales. NIST must balance

the application of its available resources versus the expressed need

and projected impact in its SRM projects prioritization process,

whether for new or renewal materials.

After identifying an SRM need, NIST conducts a careful analysis of

the necessary properties of a useful reference material. Minimum

specifications for a candidate SRM are drafted, and a material is

obtained, usually from a naturally occurring source. Then

measurements are made to evaluate the material’s compliance with

the specifications, and NIST begins the process of certifying the

SRM.

SRM Certification: Basic Principles5

In certifying SRMs, the goal at NIST is to give a true value at a

stated level of uncertainty for each property or constituent certified.

Four major considerations are involved in certifying an SRM by

NIST.

 5Much of this section is based on Taylor (1993).
Section 3 — SRMs and Sulfur Measurement

3-13

Homogeneity. It is essential that every subportion of a given lot be

the same within the overall uncertainty limits provided. This is

necessary so that each user obtains a portion that agrees with the

certified values. NIST conducts statistical assessments of the

homogeneity of the material. The degree of homogeneity

contributes to the uncertainty of the certified value.

Stability. If the material changes with time, it will eventually have

true values that no longer agree with the certified values. NIST

establishes the long-term stability of the material and includes any

critical information concerning long-term storage or special stability

requirements. In the case where this long-term stability has not

been established, the certificate provides this information (e.g.,

“long-term [greater than one year] stability of this SRM has not

been rigorously established. NIST will continue to monitor this

material and any substantive change will be reported to

purchasers”). Increasingly, SRMs are provided with expiration

dates after which their certificate is not valid.

Handling Procedures. Special procedures, such as cold storage,

drying, and other preparation may be necessary for the proper use

of the SRM. In the case of some SRMs, segregation on standing is a

potential problem. The certificate will instruct the user to shake,

rotate, stir, or otherwise reconstitute the material. Failure to do so

not only invalidates the present measurement but jeopardizes

further measurement from the same container because of the

disproportionate withdrawal of the contents.

Certified Values. The certificate must state the best possible level

of accuracy for the certification. Sometimes this factor is stated as a

tolerance interval; more often than not, it is simply given as an

estimated uncertainty. NIST tries to provide conservatively stated

uncertainties to allow for unknown systematic errors. The certified

value is not expected to deviate from the true value by more than

the uncertainty stated on the certificate. This uncertainty is more

than a precision statement and includes the systematic error of the

measurements, method imprecision, and material heterogeneity.

Certification: Hierarchy of Measurement Methods

Several techniques are especially helpful in the quest for

certification accuracy. The quality of an SRM’s assigned value is

based on the existence and application of sound measurement
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

3-14

principles and practices (May et al., 1999). Definitive, or primary,

methods (methods of highest accuracy) are most closely linked to

basic measurement units and thus reduce opportunities for error.

Agreement of several independent laboratories using the same or

different methods provides additional reason for confidence. Two

approaches are used by NIST for fossil fuel SRM certification. In

order of preference they are:

1. Single primary method approach: measurement by a

definitive or primary method of known and demonstrated

accuracy having essentially zero systematic errors. The

measurements may then be confirmed using an additional

technique.

2. Multiple independent method approach: measurement by

two or more highly reliable independent critically evaluated

methods, designated as reference methods having estimated

inaccuracies (including systematic errors) that are small

relative to the required certification accuracy.

In general, NIST uses approaches 1 or 2 to develop and certify

SRMs such as sulfur content in fossil fuels. Below, we describe the

hierarchy of measurement methods and how it is applied in the

certification of an SRM.

Primary Methods. A primary method is a method of known and

demonstrable accuracy. To understand the use of primary methods

for SRM certification, one must also understand the SI system of

units. The SI system of units includes the seven base units: mass,

length, time, electric current, thermodynamic temperature,

luminous intensity, and the amount of substance (i.e., the mole).

Using the basic equations of physics, one can describe the

approximately 50 derived units (e.g., volume, density, frequency,

and viscosity) in terms of the base units. The derived units, together

with the base units, form the basis for the other experimental

measurement parameters that are normally determined in physics

and chemistry laboratories (e.g., absorbance, nuclear cross-section,

spectral intensity, pH). It is not always possible to relate the

experimentally determined parameters to the basic units without

using extensive approximations or inexact equations. These

approximations may lead to large uncertainties in determining the

experimental parameters by introducing systematic errors.
Section 3 — SRMs and Sulfur Measurement

3-15

A primary method is one in which all significant parameters have

been related by a direct or solid chain of evidence to the base or

derived units of the SI. These definitive methods have a valid and

well-described theoretical foundation, have been experimentally

evaluated so that reported results have negligible systematic errors,

and have high levels of precision. Such methods with high

reliability give true values and are the most accurate methods

available to measure a given chemical property. They provide the

fundamental basis for accuracy in chemical analysis. All

potentially significant sources of error are evaluated explicitly for

each application and investigated matrix (May et al., 1999).

Primary methods are generally uneconomical for general use. They

usually require highly skilled personnel and are time consuming as

well as expensive to perform. An example is the use of IDMS to

determine the concentration of an element in a sample. In IDMS

the concentration of unknown samples is related directly to the

actual weights of spikes of isotopes or isotopically labeled

compounds. In terms of accuracy, the IDMS technique is powerful

because chemical manipulations are carried out on a direct weight

basis, and the mass spectrometric determinations involve isotopic

ratios rather than absolute isotope determinations, obviating the

need for instrumental corrections. Thus, systematic errors are

essentially eliminated. This technique automatically and directly

results in determining experimental parameters in terms of base

units of measurement. Examples of other definitive techniques are

gravimetry and coulometry.

Once a value has been assigned to a reference material, that

measurement is confirmed using an additional technique.

Confirmation may be accomplished using one of the following

three possibilities: a second NIST technique, interlaboratory

testing, or determination of the certified constituents in other SRMs

of similar matrix and constituent concentration (May et al., 1999).

Multitechnique Approach. Because primary methods are

sometimes not available for use in certifying SRMs, NIST may

sometimes use two or more independent critically evaluated

methods for certification. Independent means that the basic

principles used for the analysis must be entirely different. Reliable

means that the method must have been successfully used in similar

analytical situations (same concentration range, similar

Although definitive

methods are the most

accurate methods

available, they are not

economical for general use

because they require highly

skilled personnel and

specialized equipment and

are time consuming.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

3-16

interferences) as that expected in certifying the SRM. The methods

must be accompanied by a confident statement concerning the

estimated systematic errors. To use a method, the estimated

systematic errors must be small. The methods are chosen that have

significantly different sources of error and variability. This

approach is based on the rationale that the likelihood of two

independent methods being biased by the same amount and in the

same direction is small. A special kind of independent method is a

reference method. This is a method of proven accuracy, based on

testing versus a definitive method. Reference methods are generally

arrived at by consensus.

SRM Certification

The actual testing of a material to be marketed as an SRM involves

numerous stages of testing. The material must be tested to

determine its homogeneity and stability. The certification analyses

are conducted using critically evaluated methods. A statistical

analysis is conducted to determine method imprecision and method

biases, which are combined and reported as the uncertainty of the

certified values.

The homogeneity of materials is usually relatively easy to establish

once an adequate statistical sampling plan has been designed.

Thus, analysts can use highly precise, rapid instrumental techniques

such as x-ray fluorescence (XRF) or neutron activation analysis

(NAA) to evaluate material variability without being concerned

with the evaluation of systematic errors.

Materials with significant, but usable, levels of heterogeneity may

be certified as a batch, in which case the statistical tolerance limits

are given. A statement on the statistical tolerance limits includes

the average value of all samples in the batch and limits within

which most individual samples are expected to lie, with stated

confidence. Because only a small number of samples will have

been analyzed, the limits for a given percentage of samples cannot

be stated with certainty. Rather, there is only a probability that the

limits are valid. Thus, for example, it can be said with 95 percent

confidence that these statistical tolerance limits cover the true

values of 95 percent of the samples of the batch.

The final product of the certification of a NIST SRM is the SRM itself

and the certificate of analysis accompanying it. The certificate
Section 3 — SRMs and Sulfur Measurement

3-17

presents the certified valuethe best estimate of the value for a

constituent or property of the SRM. This value is usually the

arithmetic or weighted mean of the determinations made using

definitive methods, independent methods, or from interlaboratory

testing. A detailed discussion of alternative uncertainty

measurements is provided in Taylor (1993).

3.3.2 History of NIST’s SRM Program for Sulfur in Fossil

Fuels

NIST’s SRM program for sulfur in fossil fuels was motivated by

anticipated needs due to the regulation of sulfur content in residual

fuel oil. In 1967, NIST (then NBS) issued SRM 1621, Sulfur in

Residual Fuel Oil, 1 %, and 1622, Sulfur in Residual Fuel Oil 2 %.

The technical objective of the SRM work order for these two SRMs

stated that

The problem of air pollution from large industrial

organization burning residual fuel oil containing sulfur

has reached a point where legal limitations on the

sulfur content of oils is a certainty. Out of these laws

will arise considerable litigation, the outcome of

which will depend on the ability to accurately analyze

for the sulfur. The NBS sulfur in oil standard reference

materials will supply a generally accepted, accurate

standard against which the buyer and seller can check

their oil for sulfur content as well as a standard for

referee work in legal action.

The sulfur content for both of these SRMs was certified using a

gravimetric method similar to ASTM D-129 (General Bomb

Method). The relative uncertainty (95 percent confidence interval)

of the certified value was about 2 percent of the certified value in

the case of 1621, and about 0.5 percent of the certified value for

the case of 1622. In the early 1970s, NIST added SRMs for other

concentrations of residual fuel oil (SRM 1623) and also developed

an SRM for distillate fuel oil (SRM 1624). Both of these were

certified with the same gravimetric method used earlier, and the

relative uncertainties were about 1.5 and 2 percent of the certified

values, respectively.

Then NIST began the practice of using several independent

methods to certify the standards. The independent methods usually

included a gravimetric method, ion chromatography,

microcoulometry, and X ray fluorescence. As shown in Table 3-2,
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

3-18

Table 3-2. Trends in Confidence Intervals for Certified Values of NIST SRMs

The introduction of the IDMS method has improved the accuracy of measurement methods for sulfur in fossil fuels.

SRM No. and

Title/Certification

Date

Certification

Methods

Certified Value

(CV) Uncertainty

Uncertainty,

Percentage of CV

1616: Sulfur in Kerosene

1988 IDMS IC 0.0152 0.0002 1.32%

1995 IDMS 0.01462 0.00018 1.23%

1617: Sulfur in Kerosene

1988 IDMS IC 0.169 0.004 2.37%

1995 IDMS 0.17307 0.00034 0.20%

1619: Sulfur in Residual Fuel Oil

1981 GRAV IC XRF 0.719 0.007 0.97%

1991 IDMS 0.725 0.007 0.97%

1998 IDMS 0.696 0.0077 1.11%

1620: Sulfur in Residual Fuel Oil

1979 GRAV IC 4.48 0.02 0.45%

1981 GRAV IC XRF 4.504 0.01 0.22%

1990 IDMS 4.22 0.013 0.31%

1621: Sulfur in Residual Fuel Oil ~1%

1967 GRAV 1.05 0.02 1.90%

1980 GRAV IC 0.94 0.01 1.06%

1981 GRAV IC XRF 0.95 0.005 0.53%

1986 IDMS RR 1.04 0.015 1.44%

1991 IDMS 1.011 0.012 1.19%

1996 IDMS 0.948 0.0057 0.60%

1622 Sulfur in Residual Fuel Oil ~2%

1967 GRAV 2.14 0.01 0.47%

1979 IC XRF 1.96 0.04 2.04%

1981 GRAV IC XRF 1.982 0.018 0.91%

1986 IC IDMS 2.012 0.025 1.24%

1991 IDMS 2.031 0.02 0.98%

1997 IDMS 2.1468 0.0041 0.19%

1623 Sulfur in Residual Fuel Oil

1971 GRAV 0.268 0.004 1.49%

1981 GRAV IC XRF 0.24 0.003 1.25%

1990 IDMS 0.348 0.002 0.57%

1996 IDMS 0.3806 0.0024 0.63%

1624 Sulfur in Distillate Fuel Oil

1971 GRAV 0.211 0.004 1.90%

1981 GRAV IC 0.141 0.002 1.42%

1990 IDMS IC 0.332 0.003 0.90%

1997 IDMS 0.397 0.004 1.01%

(continued)
Section 3 — SRMs and Sulfur Measurement

3-19

Table 3-2. Trends in Confidence Intervals for Certified Values of NIST SRMs (continued)

SRM No. and

Title/Certification

Date

Certification

Methods

Certified Value

(CV) Uncertainty

Uncertainty,

Percentage of CV

1632 Trace Elements in Coal

1975 Sulfur not Certified

1978 Sulfur not Certified 1.64

1998 GRAV IC XRF 1.89 0.06 3.17%

1633 Trace Elements in Coal Fly Ash

1975 Sulfur not Certified

1979 Sulfur not Certified

1993 IDMS 0.2075 0.0011 0.53%

1635 Trace Elements in Coal (Subbituminous)

1978 Sulfur not Certified

1995 IDMS 0.33 0.03 9.09%

1819 Sulfur in Lubricated Base Oil

1985(I) MICRO XRF 299 8 2.68%

1985(II) MICRO XRF 1,070 40 3.74%

1985(III) MICRO XRF 2,865 70 2.44%

1985(IV) MICRO XRF 6,030 130 2.16%

1985(V) MICRO XRF 10,550 260 2.46%

1994(I) IDMS 423.5 2.2 0.52%

1994(II) IDMS 741.1 4.3 0.58%

1994(III) IDMS 4,022 17 0.42%

1994(IV) IDMS 4,689 21 0.45%

1994(V) IDMS 6,135 23 0.37%

2294 Reformulated Gasoline

1998 IDMS 4.09x10-5 0.000001 2.44%

2295 Reformulated Gasoline

1998 IDMS 0.000308 0.000002 0.65%

2296 Reformulated Gasoline

1998 IDMS 0.00004 0.0000004 1.00%

2297 Reformulated Gasoline

1998 IDMS 0.000304 0.0000015 0.49%

2682 Sulfur in Coal

1982 GRAV IC TIMS 0.47 0.03 6.38%

1998 IDMS 0.486 0.006 1.23%

2683 Sulfur in Coal

1982 IC GRAV TIMS 1.85 0.06 3.24%

1992 IDMS 1.89 0.03 1.59%

1997 IDMS 1.955 0.041 2.10%

2684 Sulfur in Coal

1982 IC GRAV TIMS 3 0.13 4.33%

1992 IDMS 3.06 0.03 0.98%

(continued)
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

3-20

Table 3-2. Trends in Confidence Intervals for Certified Values of NIST SRMs (continued)

SRM No. and

Title/Certification

Date

Certification

Methods

Certified Value

(CV) Uncertainty

Uncertainty,

Percentage of CV

2685 Sulfur in Coal

1982 IC GRAV TIMS 4.62 0.18 3.90%

1994 IDMS 4.73 0.052 1.10%

2690 Trace Elements in Coal Fly Ash

1993 GRAV COLOR XRF 0.15 0.01 6.67%

2691 Trace Elements in Coal Fly Ash

1993 GRAV COLOR XRF 0.83 0.05 6.02%

2692 Sulfur in Coal

1988 GRAV IC TIMS 1.115 0.019 1.70%

1994 IDMS 1.184 0.036 3.04%

2717 Sulfur in Residual Fuel Oil

1990 IDMS IC 3.022 0.024 0.79%

2724 Sulfur in Diesel Fuel Oil

1992 IDMS 0.0425 0.0004 0.94%

1995 IDMS 0.04304 0.00037 0.86%

2775 Sulfur in Foundry Coke

1999 IDMS 0.5816 0.0051 0.88%

2776 Sulfur in Furnace Coke

1998 IDMS 0.825 0.016 1.94%

IDMS Isotope Dilution Mass Spectrometry

IC Ion Chromatography

GRAV Gravimetry (ASTM D-120 for Petroleum; ASTM D-3177 for coal)

XRF X-ray Fluorescence

RR Round Robin

MICRO Microcoulometry

COLOR Colorimetry

aUncertainty as reported on the SRM certificates. Two times the uncertainty value give the 95 percent confidence

interval about the certified value.

NIST used several independent methods to certify SRMs from 1979

to 1981, including SRMs 1619, 1620 and 1620a, 1621a and 1621b,

1622a, 1623a, and 1624a.

In the early 1980s, NIST began developing an application of IDMS

to the certification of sulfur in fossil fuels. P.J. Paulsen and W.R.

Kelly developed a thermal ionization mass spectrometric method

that utilizes iostope dilution, referred to as ID-TIMS. Their first

paper describing the method appeared in Analytical Chemistry in

1984 (Paulsen and Kelly, 1984). For petroleum products, the first

SRMs to be certified using IDMS were 1621C and 1622C in 1986

(although the application to coal came earlier, as explained below).
Section 3 — SRMs and Sulfur Measurement

3-21

In general, NIST developed the certification statement using only

the results from the IDMS, but NIST used other independent

methods to confirm the results. Today, IDMS is considered a

definitive method that virtually eliminates bias in the certified value

and significantly reduces uncertainty.

NIST began certifying SRMs for sulfur in coal in the early 1980s

with SRM 2682, 2683, 2684, and 2685. Although 1632 and 1635

were developed earlier, the sulfur levels for these SRMs were not

certified until later. One of the earliest applications of the IDMS

method for certifying sulfur in fossil fuels was in SRMs 2682, 2683,

2684, and 2685. At this early stage, IDMS was used in conjunction

with other methods to confirm the certified value. IDMS is now

used to certify virtually all SRMs for sulfur in fossil fuels.

The application of IDMS has had a significant impact on the

uncertainty associated with SRMs. Figure 3-4 compares the relative

uncertainty for several SRMs over time. Part a shows relative

uncertainties for SRMs for residual fuel oil and lubricating base oil.

The first bar shows the relative uncertainty before the introduction

of IDMS; the second shows the relative uncertainty of the most

recently issued batches. For all petroleum products, the ratio of the

relative uncertainty for the earliest SRMs to that of the most recent

SRMs averages about 2.3.

A similar trend can be seen for the coal SRMs. The IDMS method

has improved over the years. In 1982, the relative uncertainty of

coal SRMs ranged from about 3 percent to about 6 percent. Today,

the relative uncertainties range from 1 percent of the certified value

to about 3 percent. For all coal SRMs the ratio of the relative

uncertainty for the earliest SRMs to that of the most recent SRMs is

about 1.6. Note, however, that these comparisons are more

difficult for coal than for petroleum products because the

heterogeneity of the material contributes a great deal to the SRM

uncertainty.

However, the uncertainty associated with NIST SRMs is only one

component of the total uncertainty of the sulfur measurement

methods. For example, in the analysis of coal, material

heterogeneity is the primary source of uncertainty. Interviews with

analysts at coal testing labs indicated that sample variability is
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

3-22

Figure 3-4. Impact of IDMS Method on the Relative Uncertainty of NIST SRMs for Sulfur in

Fossil Fuels

The relative uncertainty of NIST SRMs decreased with the introduction of the IDMS method.

1.9

0.47

1.49

2.68

0.6

0.19

0.63 0.52

0

1

2

3

1621 1622 1623 1819(1)

SRM/Issue Date

Relative Uncertainty (%)

1967 1996

3.24

6.38

4.33

3.9

2.1

1.23 0.98 1.1

0

1

2

3

4

5

6

7

2682 2683 2684 2685

SRM/Issue Date

Relative Uncertainty (%)

a) Petroleum Products

b) Coal

1967 1996 1971 1996 1985 1994

1982 1997 1982 1997 1982 1997 1982 1994

responsible for about 80 percent of the total uncertainty. Therefore,

a reduction of the variability associated with the SRM has a small

impact on the variability associated with the coal measurement

itself.

For petroleum, sampling is not as important an issue. Interviews

with chemists at petroleum refineries indicated that sampling error

is responsible for about 33 percent of the total error. The

uncertainty associated with NIST SRMs and instrument response

account for a larger share of the total uncertainty of the sulfur
Section 3 — SRMs and Sulfur Measurement

3-23

measurement method. Therefore, we assumed that decreases in

NIST SRMs’ uncertainty may have a greater impact on sulfur testing

in petroleum than in coal.

3.3.3 Counterfactual Scenarios

To analyze the impact of NIST’s SRM program, we must develop a

counterfactual scenario—that is, if NIST SRMs were not available,

then what would be the state of the science for measuring sulfur in

fossil fuels. For the counterfactual, we assume that, in the absence

of NIST, the level of uncertainty associated with the measurement

of sulfur in fossil fuels would today be similar to what it was prior

to the introduction of IDMS in the early 1980s.

Because of the complexity of the method and the skill and

equipment required to apply IDMS, it is unlikely that any other

laboratories developing CRMs would have pursued this method in

the absence of NIST. This hypothesis was confirmed by our

interviews with several CRM manufacturers who said that they

typically do not engage in fundamental research targeted at new

techniques for developing sulfur reference materials.

We assume that the impact associated with SRMs developed using

the IDMS method began in 1986 and will continue at least through

2003. In 1986, NIST began selling SRMs developed using the

IDSM method. However, not all benefits categories (described in

Section 4) realized economic impacts beginning in 1986. For

example, the decreased level of measurement uncertainty

associated with SRMs using the IDMS method did not affect

petroleum production until the mid-1990s when California began

regulating the sulfur content of gasoline and diesel fuels.

We assume that, in

the absence of NIST,

the level of

uncertainty

associated with the

measurement of

sulfur in fossil fuels

would today be

similar to what it

was prior to the

introduction of

IDMS in the early

1980s.
4-1

Valuing Improved 4 Sulfur Information

What is the value of improved information about the sulfur content

of fossil fuels? Economic principles define information as

“valuable” if it supports decisions that lead to improved economic

outcomes. Information is then valued by comparing the outcomes

obtained with and without the information (Preckel, Loehman, and

Kaylen, 1987).

In this section, we apply this basic definition of the value of

information to develop methods for valuing the benefits of NIST

SRMs for sulfur in fossil fuels. First, we describe how sulfur

information is used to support decisions in the fossil fuel industry.

Second, we provide a set of hypotheses and a list of technical and

economic metrics. Third, we discuss how the impact of NIST SRMs

on measurement accuracy can be combined with primary and

secondary data to test these hypotheses and value economic

impacts. The last section describes how we collected the required

data.

4.1 SULFUR INFORMATION AND ECONOMIC

BEHAVIOR

Information about the sulfur content of fossil fuels is used in a

number of industries to make decisions about product

development, pricing, resource use, and production. More

specifically, sulfur content measurements are used

Z by the sulfur measurement industry to develop and produce

sulfur measurement equipment, to prepare CRMs, and to

conduct laboratory testing;

Information is

“valuable” if it

supports decisions

that lead to

improved economic

outcomes.

Information is then

valued by

comparing the

outcomes obtained

with and without

the information

(Preckel, Loehman,

and Kaylen, 1987).
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-2

Z by the fossil fuel supply chain to determine the appropriate

price for fuels;

Z by the fossil fuel supply chain for setting operating

specifications for equipment to meet technical or regulatory

criteria;

Z by the fossil fuel supply chain for R&D aimed at developing

new products and processes, including low-sulfur fuels and

lubricants and desulfurization processes; and

Z by the fossil fuel supply chain and the regulatory

community (EPA and CARB) to verify compliance with

environmental regulations.

The potential impacts of these uses for sulfur information fall within

the three categories of infratechnology impact discussed by Tassey

(1997):

Z Infratechnologies improve the efficiency of R&D. NIST

SRMs for sulfur in fossil fuels may reduce the cost of

developing new products and processes in the sulfur

measurement industry and in the fossil fuel industry. They

allow for the calibration and testing of sulfur measurement

instruments, improve the quality of CRMs, and may improve

the efficiency of research aimed at reducing the sulfur

content of fossil fuels. SRMs allow for the replication and

verification of research results.

Z Infratechnologies support the production process and can

enhance product characteristics. NIST SRMs support the

production of the products and services of the sulfur

measurement industry by providing quality control during

the manufacturing and laboratory processes. For the

petroleum refining and coal processing industries, NIST

SRMs provide information that can improve their

production processes, their products, and their

environmental compliance. Improved sulfur information

allows these companies to adjust the sulfur content of their

inputs and outputs to more precisely meet technical and

environmental specifications. For the electric power

generation industry, higher-quality information can improve

productive efficiency as well as reduce the risk of regulatory

violations. For steel manufacturers, the quality of the steel

is driven, in part, by the sulfur content of the coke that is

used in this process; thus, more accurate information

resulting from the use of NIST SRMs improves the quality

and reliability of the product.

Infratechnologies impact

the economy by

Z improving the

efficiency of R&D,

Z supporting the

production process

and enhancing

product characteristics,

and

Z reducing transactions

costs.
Section 4 — Valuing Improved Sulfur Information

4-3

Z Infratechnologies reduce transactions costs. Each market

transaction involving a fossil fuel, from mining/drilling to

combustion, depends on information about the sulfur

content of that fuel. SRMs allow these measurements to be

made accurately and enable comparability among the

results, thus promoting efficient and low-cost transactions.

SRMs also reduce transactions costs for consumers of

instruments and CRMs. NIST traceability of these products

assures customers of the quality of these measurement

products.

Table 4-1 summarizes our observations about how NIST SRMs may

support production stages for each of the three industry sectors that

we discuss. We used this general characterization of the role of

infratechnologies in the economy and the potential role of NIST

SRMs for sulfur in fossil fuels to develop hypotheses about how

NIST SRMs affect each of the affected market segments.

Table 4-1. Potential Impact of SRMs on Stages of Production in the Sulfur Measurement

Supply Chain

NIST SRMS may affect several stages of production for each industry segment.

Stage of Production

Industry Sector R&D Production Market Transactions

Sulfur Measurement Industry ✓ ✓

Fossil Fuel Processing ✓✓✓

Fossil Fuel Combustion ✓ ✓

4.1.1 Use of SRMs and Sulfur Information to Improve R&D

Efficiency

Both the sulfur measurement industry and the fossil fuel industry

use NIST SRMs to develop new products and processes. NIST

SRMs may support R&D by providing more accurate sulfur

information. This support may decrease the cost and increase the

efficiency of R&D.

Sulfur Measurement Industry

The sulfur measurement industry, including developers of CRMs,

developers and manufacturers of sulfur measurement equipment,
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-4

and independent labs, is prominent among the customers of NIST’s

SRMs for sulfur in fossil fuels. These organizations use NIST SRMs

during the product development process to test alternative product

designs and to develop new applications for their products. The

availability of a standard for product testing may decrease the cost

and increase the efficiency of product development.

Fossil Fuel Processing Industry

Petroleum and coal companies also use SRMs to conduct R&D to

reduce the sulfur content of fuels and to improve sulfur testing

methodologies. For example, fuel companies that would like better

real-time information about the sulfur content of their products are

developing in-line sulfur testing methods. NIST’s SRMs improve

the efficiency of these R&D processes by providing a standard for

quality control and testing of new products and processes.

However, these benefits are difficult to quantify.

4.1.2 Use of Sulfur SRMs to Support the Production

Process

Sulfur content information is used throughout the sulfur

measurement industry and the fossil fuel supply chain to support

production activities. The improved information can raise the

quality of the products and services provided as well as make

production processes more efficient.

Sulfur Measurement Industry

In addition to supporting the development of sulfur testing

instruments and CRMs, SRMs support their production and the

provision of sulfur testing services. NIST SRMs may improve the

quality of these products and services because they support quality

control. Improvements in the quality of these instruments, CRMs,

and laboratory services in turn may increase their value to the

customers of these companies because of the more accurate

information they provide.

Fossil Fuel Processing Industry

The fossil fuel processing industry may use SRMs to support its fuel

blending and fuel desulfurization activities. These companies

blend coals and crudes of different characteristics, including sulfur

Improved sulfur

content information

can raise the quality

of the products and

services provided as

well as make

production

processes more

efficient.
Section 4 — Valuing Improved Sulfur Information

4-5

content, to meet contract specifications regarding sulfur content.

They may also conduct desulfurization processes for raw or final

products to meet final sulfur specifications. If information about the

sulfur content of the fuel is not accurate, the blend may be too high

or too low in sulfur content. If it is too high in sulfur content, the

buyer may not accept the shipment, or the seller may violate

environmental regulations. If the sulfur content is below product

specifications, the seller is essentially giving away product that

could have been sold.

Because of the uncertainty involved in measuring sulfur in fossil

fuels, companies may include a “buffer” in their shipments. That is,

they may ship fuel that measures lower in sulfur content than is

specified in the contract. This buffer reduces the probability that

the shipment will be rejected because it does not meet the terms of

the contract. However, buffers are expensive because low-sulfur

fuel commands a higher price than high-sulfur fuel and because

desulfurization is expensive. Reducing the amount of the buffer

may reduce the cost of meeting contract specifications.

Uncertainty about the sulfur content of finished petroleum products

also affects the companies’ decisions regarding how to ensure

environmental compliance of their finished petroleum products.

Companies may use a “buffer” similar to that used in fuel blending

and desulfurization processes described above to ensure

compliance with sulfur content regulations.

Fossil Fuel Combustion Industry

Electricity generation equipment, especially environmental control

equipment, is affected by the sulfur content of the coal that is used.

Electrostatic precipitators remove particulates (fly ash) using

electrically charged plates. The resistivity of the ash particles to the

electric charges is adversely affected if the sulfur content becomes

too high. Thus, if the sulfur content of the fuel is not known with

certainty, technical specifications of this equipment may be set

incorrectly. Process inefficiencies may result, increasing

production costs.

Unknown sulfur content can also affect productivity by forcing the

company to take action to prevent an environmental compliance

violation. If the sulfur content of the coal is higher than expected,

Accurate sulfur content

information is important to

fossil fuel producers

because they conduct

costly desulfurizaiton

processes on raw or final

products to meet

contractual obligations.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-6

the company may be alerted to a potential violation by the

information provided by the SRMs. The company may take action

by reducing the fuel input in the boiler (reducing the productivity of

the unit) or purchasing sulfur credits in emissions markets.

4.1.3 Use of Sulfur Information to Reduce Transactions

Costs in the Purchase and Sale of Fuels and Other

Products

Recall that sulfur content normally is specified as part of a purchase

contract. SRMs can reduce transactions costs between buyers and

sellers of fuels and other products by reducing the cost of acquiring

the information (such as sulfur content) needed to set prices and

finalize the transaction. The primary characteristics of fossil fuel

purchase contracts are explained below.

Sulfur Content Specifications

Coal purchase contracts generally specify a minimum and

maximum sulfur content. Most long-term contracts will specify a

range in which the coal’s sulfur content must fall. The range is

generally centered around a guaranteed value. The actual price

paid for the shipment of coal may increase or decrease if the coal’s

actual sulfur content is above or below the guaranteed value.

However, a buyer may reject a shipment if the sulfur content falls

outside the specified range. Even then, the contract is not

terminated if the seller makes reasonable assurances that it will

remedy the situation. Similar negotiations occur for crude oil.

For finished petroleum products, the primary specification that must

be met with respect to sulfur content is the sulfur limit imposed by

either EPA or, in California, the CARB. The refineries test each

batch of fuel produced. Pipeline companies may test the fuel

before transporting it and prohibit the sulfur content from exceeding

a set maximum limit related to the regulatory limit.

Pricing Based on Sulfur Content

A purchase contract for coal generally specifies a base price with

price adjustments for differences in quality or changes in market

price. A quality adjustment is almost always made for heat content

(Btu/lb). A contract may have a quality adjustment for sulfur as

long as the sulfur content is still within a specified range. For

SRMs can reduce

transactions costs

between buyers and

sellers of fuels and

other products by

reducing the cost of

acquiring the

information (such as

sulfur content)

needed to set prices

and finalize the

transaction.
Section 4 — Valuing Improved Sulfur Information

4-7

example, if the coal’s sulfur content is lower than the guaranteed

value, then the buyer pays a premium. The calculation of such a

premium or penalty differs by contract.

Coal quality and price adjustments are typically applied to

individual shipments, although some contracts will aggregate coal

quality information on the basis of multiple shipments or for a given

period. In the case of rail shipments, usually one composite sample

applies for an individual shipment, and payment is based on that

sample. In the case of truck deliveries, price and payment may be

based on the average of samples taken from shipments over a

period of time (all truck deliveries for a bimonthly or monthly

basis). For barge deliveries, the price may apply to individual barge

loads (1,500 tons each) or barge tows (nine barges or more).

The price of a crude oil shipment may be revised if the sulfur

content varies from the guaranteed value. For refined petroleum,

price is generally set for a specific type or grade of fuel, regardless

of sulfur content, as long as it meets the (regulatory and

performance) specifications. Although the price of a product might

not change, lowering the sulfur content to meet a regulatory

standard generally raises manufacturing costs.

Testing and Resolution of Disputes

Most coal contracts outline a general sampling procedure, which

includes how many splits of each sample will be taken, who is

responsible for sampling, and what procedure to follow if there is a

dispute. Most specify that the testing facility must employ ASTM

methods. The sampling plan and the testing site vary by contract.

Usually they are not specified other than to mention that these must

be carried out as agreed upon by the buyer and seller. Generally a

sample is split into three portions. The seller (or the seller’s

designated laboratory) tests one portion, the buyer (or the buyer’s

designated laboratory) tests the other, and the third is kept in case

of a dispute. In the event of a dispute, the third split is tested by an

independent laboratory. Additional costs may be incurred by both

parties to the transaction as they review the circumstances of the

dispute and examine the data provided by the independent

laboratory in comparison to their own test data.

For crude and refined petroleum, test methods are specified in

regulations and contract and product specifications. The type (not
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-8

brand) of equipment or instrumentation is usually described in the

test method. Test methods include specific procedures for

calibration. Most calibration procedures do not specify the use of

NIST SRMs. SRMs or secondary standards based on SRMs can be

used as part of a laboratory’s quality control/quality assurance

(QC/QA) program to check the test bias.

Intercompany contracts generally do not specify what happens in

the case of a dispute regarding the sulfur content of petroleum

products. In the case of EPA, an independent contractor collects

and stores retained samples. EPA decides which 10 percent of the

samples the independent laboratory must test. Results should agree

with the refinery laboratory (within the reproducibility interval). In

the case of a violation detected by EPA or CARB testing, a company

could use its QC/QA data in defense. Test data on SRMs also are

helpful in such cases.

4.2 HYPOTHESES

As described above, NIST SRMs affect each segment of the fossil

fuel measurement industry and the fossil fuel supply chain. This

section frames the discussion in Section 4.1 as a set of hypotheses

about the impact of NIST SRMs on each sector. These hypotheses

are summarized in Table 4-2.

4.2.1 Impact of SRMs on the Sulfur Measurement Industry

We expect that NIST SRMs have technical and economic impacts

on the sulfur measurement industry (Table 4-2). SRMs reduce the

cost of R&D by providing better information during the product

development process. During the production process, SRMs

improve the quality of products and services by providing better

quality control and a standard against which to calibrate

instruments. The technical impact is higher-quality equipment,

more accurate CRMs, more accurate analytical results, and less

product testing required. The hypothesized economic impact is

consumers’ higher valuation of products and services that provide

greater accuracy of sulfur content information. To the extent that

SRMs also reduce the need for product testing, they also may lower

R&D costs.

SRMs improve the

quality of products

and services by

providing better

quality control and

a standard against

which to calibrate

instruments.
Section 4 — Valuing Improved Sulfur Information

4-9

Table 4-2. Hypotheses About the Impact of NIST SRMs

NIST SRMs may reduce R&D costs, increase the value of products, reduce fuel and operating costs, reduce regulatory

penalties, and reduce sulfur emissions.

Beneficiaries/

Market Segment Uses of NIST SRMs

Technical Impacts of

Improved Information

Economic Impacts of

Improved Information

Sulfur Measurement Industry

Instrument Manufacturers Calibrate equipment and

control quality

Higher-quality equipment Increased value to

instrument users

Verify product

specifications during

product development

Less product testing

required during

development

Lower R&D costs

Manufacturers of CRMs Verify accuracy of CRMs

Calibrate equipment

More accurate CRMs Increased value to CRM

users

Verify product

specifications during

product development

Less product testing

required during

development

Lower R&D costs

Independent Laboratories Calibrate instruments

Control quality

More accurate analytical

results

Increased value to users of

services

Fossil Fuel Production and Combustion Industries

Coal Set prices and meet

contract specifications

Fewer trade disputes over

sulfur content

Lower transactions costs

Determine level of

desulfurization required

prior to sales

Less uncertainty in coal

blending process and

desulfurization processes;

less “buffer” to ensure limits

are met

Lower costs for

desulfurization; lower costs

to meet contractual

specifications

Ensure and verify

environmental compliance

of products

Fewer environmentala

compliance penalties

Reduction in number and

dollar value of regulatory

penalties

Set prices and meet

contract specifications

Fewer trade disputes over

sulfur content

Lower transactions costs

Determine level of

desulfurization required

prior to sales

Less uncertainty in fuel

blending process and

desulfurization processes;

less “buffer” to ensure limits

are met

Lower costs for

desulfurization; lower costs

to meet contractual

specifications

Petroleum Industry:

 Gasoline

 Diesel (distillate fuel oil)

 Kerosene

 Residual fuel oil

 Petroleum coke

Ensure and verify

environmental compliance

of products

Fewer environmentala

compliance penalties

Reduction in number and

dollar value of regulatory

penalties

Verify product

specifications during

development of low-sulfur

fuels and lubricants

Less product testing

required

Reduced R&D costs

(continued)
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-10

Table 4-2. Hypotheses About the Impact of NIST SRMs (continued)

Beneficiaries/

Market Segment Uses of NIST SRMs

Technical Impacts of

Improved Information

Economic Impacts of

Improved Information

Fossil Fuel Production and Combustion Industries (continued)

Coke Ensure sulfur content of

coal and coke

Fewer trade disputes over

sulfur content

Lower transactions costs

Determine level of

desulfurization required

before and after coking

Less uncertainty in coal

blending process and

desulfurization processes;

less “buffer” to ensure

technical limits are met

Lower costs for

desulfurization; may reduce

fuel costs

Determine settings for

emissions control

equipment

More efficiently operated

emissions control

equipment

Reduction in cost of

controlling emissions

Monitor and verify

environmental compliance

Fewer environmental

compliance violations

Reduction in number and

dollar value of regulatory

penalties

Electric Power Generation Ensure sulfur content of

purchased coal

Fewer trade disputes over

sulfur content

Lower transactions costs

Determine level of

desulfurization required

Less uncertainty in coal

blending process and

desulfurization processes;

less “buffer” to ensure

technical limits are met

Lower costs for

desulfurization; may reduce

fuel costs

Determine settings for

emissions control

equipment

More efficiently operated

emissions control

equipment

Reduction in generation

cost

Monitor and verify

environmental compliance

Fewer environmental

compliance violations

Reduction in number and

dollar value of regulatory

penalties

Steel Ensure sulfur content of

purchased coal and coke

Fewer trade disputes over

sulfur content

Lower transactions costs

Determine level of fuel

desulfurization required

Less uncertainty in coal

blending process and

desulfurization processes;

less “buffer” to ensure

technical limits are met

Lower costs for

desulfurization; may reduce

fuel costs

Determine level of postproduction steel

desulfurization required

Less uncertainty in steel

desulfurization process

Lower costs for steel

desulfurization

Determine settings for

emissions control

equipment

More efficiently operated

emissions control

equipment

Reduction in production

cost

Monitor and verify

environmental compliance

Fewer environmental

compliance violations

Reduction in number and

dollar value of regulatory

penalties

(continued)
Section 4 — Valuing Improved Sulfur Information

4-11

Table 4-2. Hypotheses About the Impact of NIST SRMs (continued)

Beneficiaries/

Market Segment Uses of NIST SRMs

Technical Impacts of

Improved Information

Economic Impacts of

Improved Information

Regulatory Community and Environment

Regulatory Community Determine whether

regulated community is in

compliance with

regulations

Less uncertainty and

therefore more rigorous

enforcement

Possible increased

collection of regulatory

penalties

Lower emissions Lower costs of

environmental degradation

aReductions in regulatory penalties are a transfer from regulators to companies but do not result in net benefits unless

administrative costs also fall.

4.2.2 Impact on the Fossil Fuel Production and Combustion

Industries

The fossil fuel production and combustion industries use sulfur

information to inform a number of production and consumption

decisions. Table 4-2 summarizes our hypotheses about the impact

of this information on these industries. Many of the uses, technical

impacts, and economic impacts across these industries are similar.

Setting Prices, Meeting Contract Specifications, and

Ensuring Sulfur Content of Purchased Fuels

The coal, petroleum, and coke industries each are on the selling

side (and in the case of coke, the buying side) of a fuel transaction.

They use sulfur information to set prices and to meet their contract

specifications. The purchasers of coal—the electric power and

steel industries—use sulfur information to verify the sulfur content

of what they have purchased. For each of these market

participants, accurate sulfur information can lead to fewer trade

disputes over the sulfur content of the fuel, which can lower the

transactions costs.

Fuel Blending and Desulfurization

Sulfur information can also be used to determine (1) the extent to

which fuels (including coal, crude oil, finished petroleum products,

and coke) must be processed to remove sulfur, or (2) the proper

degree of blending between high- and low-sulfur fuels. For

suppliers of fuel, the information can lead to reductions in the cost

of meeting the contractual specifications of fuel customers. To

Accurate sulfur

information can

lead to fewer trade

disputes over the

sulfur content of the

fuel, which can

lower the

transactions costs.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-12

those processing fuel for their own use, it may decrease the cost of

coal and petroleum processing.

Process Control

The electric power generation industry and the steel industry use

sulfur content information to determine the proper fuel mix and to

determine the settings required for emissions control. More

accurate information can improve the efficiency of these processes.

Environmental Compliance

Sulfur information is also used by the regulated industries to

monitor and verify their environmental compliance with sulfur

content and sulfur emissions regulations. Improvements in their

information about their compliance status may lead to fewer

violations and regulatory penalties.

4.2.3 Impact on Regulatory Agencies and the Environment

Table 4-2 also summarizes our hypotheses regarding the impact of

NIST SRMs on the regulatory agencies and the environment. EPA

and CARB use sulfur SRMs to determine whether sulfur content

regulations for gasoline and diesel fuel are being met. As the

accuracy of sulfur content measurement improves, the enforcement

of these regulations can also improve. For example, as stated

earlier, CARB regulations for sulfur content of diesel fuel and

gasoline state that enforcement will occur only if the sulfur content,

as measured by CARB, is higher than the upper-bound

reproducibility interval for the ASTM method specified in the

regulation. Thus, as the reproducibility intervals of these methods

narrow, the regulatory community can better enforce compliance

with these regulations. This enforcement can lead to lower

emissions, which reduces the economic damage to the

environment.

4.3 VALUING ECONOMIC OUTCOMES

In the previous section, six main hypotheses were described:

H1: SRMs improve the quality of the products of the sulfur

measurement industry. This quality improvement leads to

a shift in demand and an increase in customers’

willingness to pay (WTP) for these products and services.
Section 4 — Valuing Improved Sulfur Information

4-13

H2: SRMs reduce the cost of R&D in the sulfur measurement

industry and in the fuel industry by supporting accurate,

reliable sulfur measurement.

H3: SRMs reduce the cost of fossil fuel transactions because

measurements are accepted as reliable and fewer

transactions are disputed because of measurement error.

H4: SRMs improve the efficiency of a number of production

operations, including fuel blending, desulfurization, and

equipment operations because the reliability of the

measurement allows users to reduce the “buffer” they

employ to ensure compliance with technical

specifications.

H5: SRMs reduce the fines paid by industry due to

environmental noncompliance because industry and the

regulatory community have accurate and reliable sulfur

content information.

H6: SRMs reduce the total amount of sulfur entering the

environment by providing industry greater control over

the sulfur content of its fuels and by allowing compliance

officials greater authority in enforcing the regulatory

limits.

These hypotheses suggest a number of economic impact measures

for this study. Table 4-3 summarizes the technical and economic

impacts developed and quantified through our interviews with

members of the affected industries. Following the methodology

illustrated in Figure 1-1, these technical and economic metrics are

derived from the primary technical impact of NIST SRMs:

improvement in the accuracy of sulfur content measurement.

This section describes how we valued the technical and economic

impacts noted in Table 4-3. In particular, it focuses on quantifying

six types of technical and economic impacts:

Z benefits of improvements in product quality (H1);

Z changes in R&D costs (H2);

Z changes in transactions costs (H3);

Z improvements in production efficiency (including changes

in fuel costs, operating costs, and desulfurization costs)

(H4);

Z changes in regulatory penalties (H5); and

Z benefits to the environment (H6).
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-14

Table 4-3. Technical and Economic Measures of the Impact of NIST SRMs

We used a variety of technical and economic impact measures to assess the impacts of NIST SRMs.

Hypothesis

Market

Segment

Technical

Impacts

Technical

Impact Measure

Economic

Impacts

Economic

Impact Measure

H1:

Improved

Product

Quality

Sulfur testing

equipment

CRMs

Sulfur testing

services

High-quality

equipment,

CRMs, and

sulfur testing

services

Change in

repeatability

intervals or

confidence

intervals

Higher prices

commanded for

products and

services

Change in

consumers’

WTP

H2:

Change in

R&D Costs

Sulfur testing

equipment

CRMs

Less product

testing required

during

development of

equipment and

CRMs

Change in

product testing

procedures

(qualitative)

Lower R&D

costs

Change in R&D

costs

H3:

Change in

Transaction

Costs

Coal,

petroleum,

coke, steel

Fewer trade

disputes over

sulfur content

Change in the

number of trade

disputes

Lower

transactions

costs

Change in total

annual

transactions

costs

H4:

Improved

Production

Efficiency

Coal,

petroleum,

coke, electric

power, steel

More efficiency

in coal

blending,

desulfurization,

and processing

Change in the

“buffer” used to

ensure that

technical and

contractual

specifications

are met

Lower costs for

desulfurization;

lower raw fuel

costs

Change in fuel

costs; change in

desulfurization

costs

Electric power,

steel

More efficiently

operated

emissions

control

equipment

Change in total

amount of sulfur

removed per Btu

Reduction in

cost of

emissions

control

equipment

Total change in

annual

operating cost

H5:

Change in

Regulatory

Penalties

Petroleum,

electric power

Fewer

environmental

compliance

violations

Change in the

number of

violations per

year

Reduced

regulatory

penalties

Change in the

total annual cost

of regulatory

penalties

Regulatory

community

More rigorous

enforcement

Number of

enforcement

actions per

violation

Collection of

regulatory

penalties

Total annual

collection of

regulatory

penalties

H6:

Benefits to

Environment

Environment Lower emissions Total annual

emissions of

sulfur

Cost of

environmental

degradation

from sulfur

Change in the

cost of

environmental

degradation

from sulfur
Section 4 — Valuing Improved Sulfur Information

4-15

4.3.1 Benefits of Improvements in Product Quality (H1)

The value of an improvement in the quality of a good or service can

be measured by a change in the sum of producers’ and consumers’

surplus. Consumers’ surplus is a measure of the net benefit

received by consumers from the purchase of a good or service. It is

the difference between what the good or service is worth to the

buyer and what they actually pay for it (the price). Producers’

surplus is the difference between what producers receive for a good

(the price) and what it costs to produce it. The total welfare created

by a market transaction is equal to the sum of producers’ and

consumers’ surplus.

To simplify our analysis, we assumed that marginal cost is constant

and equals price. This implies that producers’ surplus is zero; all

net benefits created by a market transaction accrue to consumers.

This assumption does not affect our estimate of the total benefits of

improvements in product quality; however, it does mean that we

cannot describe the distribution of these benefits among buyers and

sellers.

The value of a good or service to any given consumer can be

quantified by his or her WTP for this good or service. WTP is an

observable measure of utility that is typically used in benefit-cost

analyses. It is a measure of the maximum dollar amount the

individual would be willing to pay for the welfare improvement we

would expect from the quality changes. Although WTP is not a

perfect surrogate for utility changes, the consensus among

economists is that WTP does provide the best available utility

surrogate (Haddix et al., 1996; Sloan, 1995; Tolley, Kenkel, and

Fabian, 1994).

In some cases, WTP is revealed in markets. When an individual

purchases a commodity in a market, the monetary sacrifice is the

price of the commodity. In such cases, price is the appropriate

WTP value of the welfare change associated with a one-unit

increase in the individual’s consumption rate of the commodity.

A demand curve is a representation of the relationship between

quantity and consumers’ WTP. Figure 4-1 demonstrates this

relationship and how it might be affected by changes in product

quality. Assume the current (with-NIST) demand curve for a CRM,

for example, is
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-16

Figure 4-1. Change in Consumers’ Surplus for Products and Services Produced with NIST

SRMs

In the absence of NIST SRMs, demand shifts downward and consumers’ surplus falls by the area a1E1E2a2.

marginal cost

(a1 - a2) (Q1 - 1⁄2(Q1 - Q2)

P

Q2

F

Q1

E2

E1

a2

a1

Q1 = a1 + bP

Q2 = a2 + bP

Price

Quantity

Q1 = a1 +bP,

where

Q is the quantity demanded,

P is price,

a is the intercept,

b is the inverse of the slope, and

subscripts indicate the with-NIST (Scenario 1) or without-NIST

(Scenario 2) demand.

Marginal cost is constant and is therefore equal to the market price.

The net benefits to all consumers who purchase the CRM are equal

to area PE1a1. Now suppose that without the NIST SRM this

demand curve would shift downward because the quality of the

CRM (e.g., accuracy of its certified value) would decline. The new

(without-NIST) demand curve would be

Q2 = a2 +bP.
Section 4 — Valuing Improved Sulfur Information

4-17

We assume that the elasticity of demand does not change. Thus, as

shown in Figure 4-1, the change in quality causes a parallel shift in

the demand curve. Consumers’ per-unit WTP for this product falls

by the amount (a1 – a2). This decline leads to a reduction in the

equilibrium quantity demanded from Q1 to Q2 and a reduction in

consumers’ surplus. In this case, the consumers’ surplus falls to

area PE2a2. The loss in consumers’ surplus is equal to a1E1a2E2.

This is the appropriate measure of the change in welfare due to the

use of NIST SRMs.

The change in consumers’ surplus (CS), using the simplifying

assumptions stated earlier (linear demand, constant marginal cost),

can be expressed as

∆ CS = (a1 – a2) * [Q1 – 1⁄2(Q1 – Q2)]

To implement our methodology for estimating the benefit of an

improvement in the quality of goods and services due to NIST

SRMs, we needed to collect variables for each good and service

that is manufactured with the assistance of NIST SRMs for sulfur in

fossil fuels. These variables are

Z annual quantities sold,

Z prices, and

Z estimates of change in consumers’ in WTP for each product.

Table 4-2 provides an example of the type of data we collected to

implement the measurement plan. As shown in Appendix B, we

designed survey questions that elicit this information. Note that we

assumed that the manufacturers of these products can estimate the

change in their customers’ WTP. Ideally, we would ask the

customers for this information; however, this population is too large

and difficult to identify to make this a reasonable task within the

resources allowed for this study.

4.3.2 Changes in R&D Costs (H2)

We hypothesized that the manufacturers of instruments and CRMs,

as well as fuel companies, benefit from accuracy in the

measurement of sulfur via reductions in the cost of R&D. To

quantify these changes, we collected and analyzed the following

information:
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-18

Z total R&D budget for industrial sector (B);

Z percentage of R&D budget allocated to sulfur-related

research (D);

Z percentage of R&D costs consumed by measurement and

testing of sulfur content (T); and

Z potential percentage increase in R&D costs due to

unavailability of NIST SRMs for sulfur in fossil fuels (M).

The decrease in R&D cost to industry is then

∆C = B * D * T * M.

4.3.3 Changes in Transactions Costs (H3)

We hypothesized that increases in the precision of the

measurement of sulfur in fossil fuels decrease the transactions costs

for buyers and sellers of fossil fuels. To quantify the extent of these

changes, we need to know

Z the number of fossil fuel transactions that take place each

year;

Z the number of transactions that currently involve some type

of dispute over the sulfur content of the fuel;

Z the impact of NIST SRMs on the number of transactions in

dispute; and

Z the cost of resolving a dispute.

From our analysis of the impact of SRMs on the repeatability of

sulfur measurements, we estimated the change in the number of

disputes. This estimate depends on the degree to which the SRM

improves the precision of the measurement of sulfur in fossil fuels.

As this precision increases, fewer shipments are disputed because

of measurement error. Our approach is illustrated in Figure 4-2.

As previously described, many fuel purchase contracts specify a

sulfur content and a range within which the shipment will be

accepted. Assume that the acceptance range is C1 to C2—that is,

the purchaser of the fuel will accept the shipment as long as the

estimated sulfur content lies [above C1 or] below C2. For

simplicity, assume that this acceptance range is equal to the

95 percent confidence interval for the measurement of sulfur in

fossil fuels, and that a NIST SRM is used for calibration and/or

quality control. These assumptions imply that if one measurement

is within the acceptance range, a second measurement will be
Section 4 — Valuing Improved Sulfur Information

4-19

Figure 4-2. Impact of SRMs on Disputes due to Measurement Error

Given a fixed acceptance range, improved measurement precision decreases the probability of rejection.

Frequency

Without NIST SRMs

Sulfur

Content

Acceptance Range

With NIST SRMs

2 C 1 C

below C1 or above C2 5 percent of the time because of

measurement error.

If we assume that sulfur measurements (x) are distributed normally

with a mean of x– and a standard error of s, then the following

relationships apply:

With-NIST SRMs:1

C1 = x– – 1.96 2 s

C2 = x– + 1.96 2 s

Prob x < C1 = 0.025 (because 0.975 is the area under the

cumulative normal curve at 1.96)

Prob x > C2 = 0.025

Total probability of rejection due to measurement error =

0.05

In the absence of NIST SRMs, we know that the confidence interval

widens because the standard error of the distribution, s’, is larger.

For petroleum products, s’—the value of the standard error without

NIST—is about 2.3 times what it is with NIST SRMs. For coal, the

 1The difference “two” standard deviation limit (d2s) is used to calculate the

acceptance interval (described in Section 3.1.2) because disputes typically

involve the comparison of pairs of test results—one by the seller and one by the

purchaser of the fossil fuel.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-20

without-NIST s is about 1.6 times what it is with NIST SRMs.2

Taking coal as an example, the following relationships hold:

s = s’/1.6

C1 = x– – 







 1.96 2s’

1.6 = x– – 1.255 2 s

Prob x < C1 = 1 – 0.8897 (area under the cumulative normal

curve at 1.225) = 0.0951

Prob x > C2 = 0.1103

Total probability of rejection due to measurement error is about

0.22

Thus, the probability that a shipment will be disputed changes from

0.05 in the with-NIST case to about 0.22 in the without-NIST case.

If the total number of transactions per year sold on the basis of

sulfur content is equal to 1 million, the number of transactions in

dispute climbs from 50,000 in the with-NIST case to 220,000 in the

without-NIST case. (This is an extreme example. The real numbers

are much smaller.)

To implement this analysis, we collected information on the

number of transactions that specify sulfur content, the percentage

that currently are disputed, and the cost of resolving a dispute.

Information about the impact of NIST SRMs on the distribution of

sulfur measurements was determined as described in Section 3.

4.3.4 Improvements in Production Efficiency (H4)

We hypothesize that by improving the quality of the measurement

of sulfur in fossil fuels NIST SRMs assist the coal, petroleum, steel,

and electric utility industries in improving the productivity of many

of their operations. These operations include fuel blending,

desulfurization, and operation of equipment. In this section, we

describe how we quantified and valued these changes in

productivity.

 2These factors represent the average ratio of SRM standard errors before and after

introducing the IDMS methodology.
Section 4 — Valuing Improved Sulfur Information

4-21

Quantifying the Economic Benefits of Improvements

in Efficiency

As described in Section 3.1.2, lack of perfect information about the

sulfur content of fuel leads to inefficiency in the production,

processing, and combustion of fossil fuels where sulfur content is a

technical or regulatory factor. The primary factor affecting

productivity is companies’ use of a “buffer” to ensure that they have

met the specification. Figure 4-3 illustrates this concept.

Figure 4-3. Impact of NIST SRMs on Buffers

Improved measurement precision may decrease the size of buffers used to ensure that technical specifications are met.

1.96 2 s

μ

Buffer

With NIST

95%

2.5% 2.5%

1.96 2 s

z

μ¢

Buffer¢

Without NIST

2.5% 2.5%

95%

s¢ > s Þ Buffer¢ > Buffer

c1¢

c1 c2

ca¢

Suppose the critical level for the sulfur content of a batch of fossil

fuel is equal to z, and that there is a penalty associated with going

over z. For this reason, sellers may intentionally target a sulfur

content that is less than z to provide some degree of assurance that

when the buyer (or regulator) measures the sulfur content it will be

below cutoff level. Let C1 to C2 be the 95 percent reproducibility

interval of the measurement method, assuming that NIST SRMs are

available. Thus, the seller is 95 percent certain that if its

measurement is μ, a second measurement will lie within that

interval.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-22

The following relationships hold:

C1 = μ – 1.96 2 s

z = C2 = μ + 1.96 2 s

For example, suppose the critical sulfur level for diesel fuel is

500 ppm and the oil company wants to be 95 percent certain that

the fuel will test at or below 500 ppm. If the reproducability

interval is equal to 50 ppm, then the oil company would set the

target value at 475 ppm to be 95 percent certain that the fuel would

test at or below 500 ppm. The buffer would be equal to 25 ppm,

about half of the reproducability interval.

Now consider the impact of a wider interval (e.g., the impact of a

wider interval due to the absence of a NIST SRM). For petroleum

products, that standard error in the absence of NIST SRMs is about

2.3 times the size it is, given the availability of NIST SRMs. This

implies the buffer increases to approximately 57 ppm and the new

target value (μ′) is equal to about 443 ppm.3

To value the impact of the change in the buffer, we must consider

the relative cost of low-sulfur versus high-sulfur fuels. For

petroleum products, we used the unit desulfurization costs of

gasoline and diesel fuel ($0.0001 per gallon to remove 1 ppm of

sulfur—see Section 4). For coal, we conducted a similar analysis;

the value of reducing the sulfur buffer is based on the unit cost of

cleaning and blending coal to remove sulfur (approximately $0.03

per ton per 0.01 percent sulfur reduction—see Section 4).

To complete the analysis, we multiplied the per-unit savings due to

the reduction of the buffer by the annual quantity of fuel subject to

each type of constraint. For example, we needed to know the

annual quantity of diesel fuels subject to the 500-ppm sulfur limit

imposed by EPA, the quantity of gasoline subject to the sulfur

limits, and the quantity of fuels subject to sulfur limits in purchase

contracts and for technical operating criteria.

 3We have simplified this example. Actually, the reproducibility interval function

changes with changes in the mean sulfur concentration.
Section 4 — Valuing Improved Sulfur Information

4-23

4.3.5 Changes in Regulatory Penalties (H5)

In addition to causing changes in the efficiency of production,

improvements in the measurement of sulfur content may reduce the

incidence and quantity of penalties imposed by the regulatory

community. As a result, NIST SRMs may reduce the expected value

of regulatory penalties for industry.

Suppose that the penalty for being over the limit on diesel fuel can

be expressed as follows:

Fine = G * (x – 500) * F

where G is the number of gallons in the batch; F represents the pergallon, per-ppm fine associated with overshooting the sulfur limit; x

is the sulfur value as measured by the regulatory authorities; and

500 is the regulatory limit in ppm. The expected value of the fine

is a function of the standard deviation associated with the

measurement, x. Because NIST SRMs reduce the standard

deviation of this measurement distribution, they decrease the

expected total loss associated with the probability of being over the

limit.

4.3.6 Benefits to the Environment (H6)

As the probability of exceeding regulatory limits for sulfur in fossil

fuels falls, emissions of sulfur to the environment may also fall.

Thus, improving the measurement of sulfur empowers regulated

industries not only to avoid regulatory penalties, but also to avoid

emitting sulfur to the environment. In addition, some regulations

specify that compliance actions can only be taken if the test results

of the regulatory authority exceed the reproducibility interval.

Thus, achieving a narrower reproducibility interval allows for

improved compliance with the regulation.

Figure 4-4 demonstrates the impact of narrowing the reproducibility

interval on regulatory compliance. Suppose the reproducibility

interval with NIST SRMs is C1 to C2. Any company whose products

test in excess of C2 is subject to regulatory enforcement and the

batch cannot be sold. However, suppose the reproducibility

interval in the absence of NIST SRMs is C1’ to C2’. This means that

the regulatory agency cannot take action unless the sulfur tests

higher than C2’. This implies that, in the absence of NIST SRMs,
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-24

Figure 4-4. Impact of NIST SRMs on Regulatory Compliance Activities

NIST SRMs may improve testing methods to prevent noncompliant fuels from entering commerce.

Frequency

Sulfur Content 2 C 1 C ¢

2 C ¢1 C

batches of fuel testing at between C2 and C2’ would be allowed to

enter commerce. To determine the impact of this change on the

environment, we gathered information on the

Z quantity of fuel currently testing outside the reproducibility

interval (greater than C2),

Z ranges of sulfur values for batches testing outside the limits,

and

Z changes in reproducibility intervals from the simulation

exercises described in Section 3.

This information allowed us to estimate an expected decrease in

sulfur emissions:

⌡⌠

C2

C2’

 f(x) (x – C2) dx

where x is the tested value of the sulfur content.

4.4 DATA COLLECTION

We hypothesized that NIST SRMs provide a variety of benefits to

industries that use SRMs and sulfur measurement products and

services. This section describes our procedures for collecting the

data required to test these hypotheses. First, we summarize the

data requirements from each industry sector. Then we discuss how
Section 4 — Valuing Improved Sulfur Information

4-25

we chose the sample of companies from among the many

companies likely to be affected by NIST SRMs. Finally, we discuss

our data collection procedures, including the procedures we used

to pretest the instruments, contact participants, and record their

responses.

4.4.1 Data Requirements

A variety of data are needed to test the hypotheses we developed

earlier in this chapter. We also developed technical and economic

impact measures and described the data that would be needed to

construct each measure. Table 4-4 summarizes these data

requirements.

The final column in Table 4-4 indicates the source of the data. We

collected items marked “secondary” from publicly available

secondary data sources. Many of these data items were available

from EPA, CARB, the American Petroleum Institute, and the Electric

Power Research Institute. When possible, we verified these data

during the interviews. For data elements for which the source is

marked “primary,” we collected these data directly from interview

participants. Appendix B contains the questionnaire used to guide

the interviews.

4.4.2 Sample Selection

We interviewed several members of each of the affected industries.

The interview contact list was developed using information and

contacts provided by our consultants, industry trade associations,

the SRM sales database, and the ASTM online directory of testing

laboratories. Table 4-5 shows the number of interviews conducted

by industry segment. Although we spoke with many of our

respondents on multiple occasions over the course of the study,

each respondent was counted as one interview. Occasionally, it

was necessary to conduct interviews with multiple contacts within

one company, because of the range of activities conducted in

different divisions of larger companies.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-26

Table 4-4. Data Elements Required to Populate the Analytical Model

The evidence required to support our six hypotheses will be collected from both primary and secondary sources.

Hypothesis Affected Industries Data Elements Source

H1 Product quantities Secondary

Product prices Secondary

Quality change Primary

Sulfur measurement industry:

Z CRM manufacturers

Z Sulfur testing equipment

manufacturers

Z Sulfur testing laboratories

Customer WTP for quality change Primary

H2 Industry R&D budget Secondary

Percentage of R&D allocated to

sulfur-related research

Primary

Percentage of R&D costs consumed

by measurement and testing of sulfur

content

Primary

Z Sulfur measurement

industry

Z Fossil fuel industry,

especially petroleum

companies

Potential percentage increase in R&D

costs due to unavailability of NIST

SRMs for sulfur in fossil fuels

Primary

H3 Annual number of transactions Secondary

Percentage specifying sulfur content Primary

Percentage of transactions currently

disputed

Primary

Z Fossil fuel extraction,

processing, and

transportation

Z Fossil fuel generation

Cost of resolving a dispute Primary

H4 Annual quantity of fuel subject to

sulfur specification

Secondary/

primary

Penalties for overshooting

specification

Secondary/

primary

Cost of undershooting Secondary/

primary

Z Fossil fuel extraction,

processing, and

transportation

Z Fossil fuel generation

Use of buffers Primary

H5 Fine structure of regulation Secondary/

primary

Quantity of fuel subject to regulation Secondary

Annual quantity of fuel exceeding

regulatory limits

Primary

Z Fossil fuel extraction,

processing, and

transportation, especially

petroleum companies

Z Fossil fuel combustion

Annual quantity of fines assessed Secondary

H6 Compliance structure of regulations Secondary/

primary

Quantity of fuel currently testing

outside compliance guidelines

Secondary/

primary

Average sulfur values for

noncompliant fuels

Primary

Z Regulatory community

(EPA, CARB)

Economic damages associated with

SO2 emissions

Secondary
Section 4 — Valuing Improved Sulfur Information

4-27

Table 4-5. Number of Interviews by Industry Segment

We interviewed several members of each affected industry segment.

Industry

Number of

Interviews

Number of

Companiesa Percentage of Industry Revenue

Sulfur Measurement Industry

Instrument manufacturers 4 4 12

CRM manufacturers 5 4 44

Independent testing laboratories 3 2 14

Fossil Fuel Extraction, Processing, and

Transportation Industry

Coal companies 5 4 10

Coke companies 0 0 0

Petroleum companies 5 3 18

Fossil Fuel Combustion Industry

Electricity generation firms 6 3 7

Steel companies 3 2 12

Regulatory Agencies 5 1

Total Interviews 38 24

aFor several larger companies, we spoke with two or more divisions.

The interviews were conducted in two stages: scoping interviews

and technical interviews. During the scoping interviews, we

learned about sulfur-content testing, methods and practices, and the

importance of accurate sulfur-content information. We then used

this information to develop and refine the questionnaire for the

technical interviews. During the technical interviews, respondents

were asked about sulfur testing and SRMs, their impressions of the

impact of SRMs, and their use of the sulfur-content information.

Sulfur Measurement Industry

We interviewed companies from each segment of the sulfur

measurement industry:

Z instrument manufacturers,

Z manufacturers of CRMs, and

Z independent testing laboratories.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-28

The companies interviewed for each of these segments represented

12, 44, and 14 percent of total industry revenue, respectively.

Table 4-6 lists the companies and organizations we interviewed.

Table 4-6. Companies Interviewed

Twenty-four companies, associations, and agencies participated in this study.

American Iron & Steel Institute MAPCO Coal

Antek Instruments Mobil Research & Development

Asoma Instruments National Mining Association

Bethlehem Steel NSI Solutions

California Air Resources Board Oxford Instruments

Carolina Power & Light RAG American

Chevron Research & Technology SPEX Certiprep

Commercial Testing & Engineering Standard Laboratories

Conoco Tennessee Valley Authority

Duke Energy Vanguard Solutions

Electric Power Research Institute VHG Labs

Interprovincial Pipeline

Leco Corporation

We spoke with four instrument manufacturers. Several criteria

were used in selecting instrument manufacturers to interview. First,

we targeted companies whose sole line of business was analytical

equipment. Second, these companies produce well-known

instruments that are used to conduct tests for sulfur in fossil fuels.

Many of our other respondents used the instruments these

companies produced in their laboratories. Finally, we included

both small and large companies in the interviews to investigate if

instrument development and manufacturing varies by company

size.

We spoke with four CRM companies. Using sales data supplied by

NIST, we generated a list of eight companies whose primary line of

business is developing reference materials traceable to NIST SRMs.

From this list we selected two small and two large companies to

interview.
Section 4 — Valuing Improved Sulfur Information

4-29

Two companies dominate the market for independent sulfur testing

for the coal industry. We spoke with one of these testing

companies in-depth and on numerous occasions. We also spoke

with the second major coal testing company (briefly) to verify that

their testing activities and procedures were similar.

Unlike the coal industry, which regularly hires independent

laboratories to conduct sulfur tests for contracts, the majority of

sulfur tests for petroleum products are conducted in-house. As

such, independent petroleum-testing laboratories were not included

in the interviews, and petroleum testing activities were investigated

during our discussion with refineries.

Fossil Fuel Extraction and Processing

This industry consists of the coal processing industry, the petroleum

refining industry, and the coke industry. We interviewed two coal

companies. These companies represent 10 percent of total coal

production. We found that the testing activities and procedures

employed by this coal processing company were basically identical

to those used by the coal testing laboratories.

We also interviewed three petroleum companies. Together, these

companies account for 18 percent of U.S. revenues from petroleum

products. Two of these companies are among the largest petroleum

companies domestically and internationally. The third company

we interviewed was a relatively smaller domestic producer. All of

the respondents worked in research, development, and technology

divisions.

We interviewed one integrated coke and steel company to obtain

information on sulfur testing associated with coke production. The

integrated coke and steel company interviewed produces and

consumes in-house 11 percent of the total amount of coke

produced domestically.

Fossil Fuel Combustion Industry

We interviewed three electricity-generating companies and one

steel company. We selected companies that varied by size and that

had purchased NIST SRMs.

From the same coke and steel company discussed earlier, we

obtained information on the use of coke (and sulfur testing) in the
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

4-30

production of steel. The steel company interviewed represents

12 percent of total national steel production. We also spoke with

this industry’s trade association, the American Iron & Steel Institute.

4.4.3 Data Collection Procedures

Our data were gathered from both primary and secondary sources.

We used an interview guide to collect information from

respondents via telephone interviews. Appendix B contains the

interview guide. These guides were customized for each industry

based on the hypotheses that we were testing for each industry.

After we field-tested these questions, we collected data from

respondents in four steps:

1. Make initial telephone contact.

2. Send respondent an overview of the project and the

interview guide.

3. Conduct telephone interview.

4. Write-up interview and contact respondent again to ask

clarifying questions if necessary.

We initially contacted a person at the target company who was

referred by NIST or our consultants. If we determined that the

initial contact was not qualified to address the issues of the survey,

we contacted another individual recommended by the first contact.

In some cases, we spoke with more than one person at a particular

company. This was often necessary given the broad scope of the

questions we asked.

We also gathered secondary information to support our analysis.

This information was collected from government information

agencies, trade associations, and industry literature.
5-1

5 Results

In Section 3, NIST’s improvements in the methodology for

measuring the sulfur content of fossil fuels and for certifying SRMs

were discussed. These improvements increased the accuracy of

available sulfur content information. In this section, we present

data that documents the social benefits and cost associated with the

use of NIST SRMs. Beginning in 1984, we quantified

approximately $409 million in net benefits to society (NPV $1998)

associated with the NIST sulfur SRMs.

The first step in quantifying the benefits from NIST sulfur SRMs, is

to develop a counterfactual scenario from which the benefits and

costs can be measured. As discussed in Section 3, our

counterfactual scenario is that in the absence of NIST, the level of

uncertainty associated with the measurement of sulfur in fossil fuels

would today be similar to what it was prior to the introduction of

IDMS in the middle 1980s. Based on this counterfactual

assumption, we are able to express the impact of NIST SRMs in

terms of a change in the standard error (SE) of sulfur measurement

tests.

Table 5-1 shows the average ratio of SRM standard errors before

and after the introduction of the IDMS methodology. Taking into

account the percentage of measurement error associated with

sampling, we determined that NIST SRMs improve measurement

accuracy by a factor of about 1.75 for petroleum and 1.25 for coal.

These factors represent the ratio of the counterfactual measurement

errors to the NIST SRM measurement errors.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

5-2

Table 5-1. Impact of NIST SRMs

Taking into account the percentage of measurement error associated with sampling, we estimate that NIST SRMs

improve measurement accuracy by a factor of about 1.75 for petroleum and 1.25 for coal.

Ratio of

Counterfactual SE

to NIST IDMS SE

Share of Measurement

Error Associated with

Sampling

Improved Measurement

Accuracy Factor

(Counterfactual/NIST)

Average for Petroleum SRMs 2.42 0.33 1.75

Average for Coal SRMs 1.60 0.85 1.25

The factors were derived by first determining the standard error,

expressed as a percentage of the confidence interval, for all batches

of SRMs. For each SRM, we developed the ratio of the standard

error before and after NIST began solely using IDMS to certify

SRMs. We then grouped the ratios by fuel type and developed two

average ratios of the counterfactual SE to the NIST IDMS SE to

represent petroleum and coal SRMs. These average ratios were

then adjusted to account for the percentage of measurement error

associated with sampling to obtain the improved measurement

accuracy factor of 1.75 for petroleum and 1.25 for coal.

Table 5-2 presents summary annual data for the total and net

benefits to society from NIST SRMs and NIST’s expenditures. The

time series begins in 1984 when the NIST Analytical Chemistry

Division received a $40,000 internal standards development award

to support research in new methods to certify SRMs. Benefits are

first realized in 1986 because this was the first year the IDMS

method was used in certifying sulfur SRMs and costs are projected

through 2003 because industry representatives indicated that the

IDMS method would remain the state-of-the-art technology in the

near future.

Table 5-3 summarizes the NPV of the benefits associated with the

six main hypotheses presented in Section 4. Of the six hypotheses,

we are able to partially quantify the benefits for four hypotheses.

Although we found anecdotal information to support the remaining

hypotheses, little concrete evidence was available. Therefore, the

potential benefits associated with these remaining hypotheses are

discussed qualitatively, but they are not included in the estimates of

economic return. In addition, industries’ avoided expenditures on

CRMs are included in the total benefit estimates.
Section 5 — Results

5-3

Table 5-2. Annual Net Benefits to Society and NIST Expenditures

Approximately $409 million in net benefits to society (NPV $1998) were quantified associated with the NIST sulfur

SRMs.

Year Total Benefits NIST Expenditures Net Benefits to Society

1984 $— $129,228

1985 $— $130,520

1986 $17,274,061 $202,231

1987 $17,964,227 $—

1988 $18,675,304 $172,496

1989 $19,120,623 $79,997

1990 $20,291,709 $436,913

1991 $20,250,116 $500,092

1992 $20,226,198 $381,976

1993 $19,510,225 $671,527

1994 $66,801,079 $577,429

1995 $68,502,832 $438,167

1996 $73,033,742 $465,349

1997 $76,610,716 $443,161

1998 $79,960,879 $427,705

1999e $83,607,231 $449,575

2000e $87,402,088 $474,604

2001e $91,393,911 $501,013

2002e $95,593,819 $528,636

2003e $100,013,611 $558,362

Total (NPV $1998) $412,659,931 $3,657,834 $409,002,097

e = estimated

In the discussion that follows, both the qualitative and quantitative

evidence that supports the analysis is discussed. We also present

information about the costs of developing and applying the

technology for developing SRMs. These costs include industry’s

costs for purchasing the SRMs and NIST’s investment in the

development and support of the analytical methods. Finally,

several measures of economic return to NIST’s investments are

presented, including a benefit-cost ratio and social rate of return.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

5-4

Table 5-3. Net Present Value of Benefits Hypothesis

Partial benefits in four of the six hypothesized categories were quantified along with avoided expenditures on CRMs.

Not all the benefits in any individual hypothesis category were captured. For example, improved product quality

benefits reflect only a subset of manufacturers in the supply chain. These benefits could not be extrapolated because of

the diverse nature of the industries represented in the supply chain.

Hypothesis NPV ($1998) of Benefit Hypothesisa

H1: Improved Product Quality $2,665,422

H2: Change in R&D Costs Not able to verify benefits

H3: Change in Transaction Costs $7,542,201

H4: Improved Production Efficiency $401,408,574

H5: Change in Regulatory Penalties Transfer—not a net benefit to society

H6: Benefits to Environment $78,449,207b

Avoided Expenditures on CRMs $1,043,734

Total Benefits (NPV $1998) $409,002,097

aBased on a 7 percent inflation adjusted social discount rate.

bNot included in total benefits summation in measures of economic return.

5.1 IMPROVEMENTS IN PRODUCT QUALITY (H1)

The first benefit hypothesis was that SRMs improve the quality of

the products and services of the sulfur measurement industry,

namely sulfur analysis equipment, CRMs, and sulfur analysis

services. This hypothesis was investigated by asking respondents in

the sulfur measurement industry

Z whether the use of NIST SRMs affects the quality of their

products,

Z whether their customers specifically request the use of NIST

SRMs in their quality control processes, and

Z whether their customers are willing to pay a premium for

products and services that are NIST-traceable.

The respondents answered this question in different ways.

5.1.1 Instrument Industry

Instrument manufacturers use NIST SRMs to conduct final tests and

calibrations on their instruments. All respondents said that, if NIST

standards were not available, they would use secondary standards,

either prepared in-house or purchased externally, to provide these

final checks. However, two of the four companies interviewed

While SRMs clearly

contribute to the quality of

sulfur analysis instruments,

CRMs, and sulfur testing

methods, this improvement

in quality is difficult to

measure.
Section 5 — Results

5-5

acknowledged that unavailability of a NIST standard to provide a

universally accepted benchmark against which to test their

instruments could affect the accuracy of their instruments, although

they were not able to quantify this difference. Another respondent

stated that he thought that in-house gravimetrically prepared

standards were sufficient to meet the company’s needs for quality

control and calibration.

Of the four companies, two said that, if they did not use NIST

SRMs, there could be an impact on customers’ willingness to pay

(WTP) for their products. Most CRM and instrument manufacturers

mentioned their use of NIST SRMs in their marketing materials.

Respondents noted that the use of NIST SRMs for quality control is

expected and that NIST SRMs are generally treated as tacit industry

standards for quality control programs. However, none of the

companies we interviewed were able to quantify the impact of not

using NIST SRMs on their customers’ purchase decisions. They

thought that the impact on customers’ WTP would be minimal,

particularly if no SRMs were available and all manufacturers used a

substitute material. Thus, we were not able to quantify any benefits

to the instrument industry from improved product quality or

subsequent WTP.

5.1.2 CRM Industry

In the market for CRMs, NIST traceability is an important issue.

Virtually all companies that manufacture or market sulfur standards

for fossil fuels claim NIST traceability. This is an important selling

point and a company trying to sell standards that are not certified as

NIST-traceable would likely lose sales if competitors were selling

NIST-traceable materials at a comparable price. We asked CRM

companies if their customers’ WTP for their products would change

if they did not have an independent national standard against

which to verify the quality of their products. Of the four companies

we interviewed, three companies were not able to quantify

potential sales if their products were not NIST-traceable. However,

one company estimated that their customers’ WTP would fall by

about 25 percent if NIST standards were not available to verify the

accuracy of their standards.

Using the formula presented in Section 4, we estimate the loss in

consumer surplus from this company’s products alone at about
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

5-6

$54,000 per year. Because the other companies we interviewed

could not quantify the potential losses in WTP, we have not

extrapolated these results to the remainder of the industry. This

particular company positions itself in the high-quality end of the

CRM market. Thus, although its customers may be willing to pay

extra for the improved quality that NIST traceability provides, this

may not be true for the customers of the other CRM companies.

5.1.3 Laboratories

Laboratories that conduct sulfur testing of coal, coke, and

petroleum products routinely use NIST SRMs as part of their quality

control program to verify the calibration of their instruments.

While commercially prepared CRMs may be adequate for these

purposes, some customers specifically request that NIST SRMs be

used for these checks. Otherwise, laboratories typically use NIST

SRMs once or twice per quarter. The customers that request NIST

SRMs to be used for all calibration checks may be willing to pay a

premium for their use in the quality control program.

One coal laboratory representative estimated the WTP premium

associated with SRMs was about 5 percent. This company

accounts for approximately 33 percent of sulfur coal testing

industry revenues, which are approximately $2,220,000. Applying

the 5 percent premium to industry coal testing revenue, we

estimate that in 1998 the change in consumer surplus was about

$313,000 for the entire coal testing industry. Table 5-4 presents the

stream of benefits estimated for each hypothesis from when the

IDMS method for sulfur was first introduced in 1986 and projected

until 2003. To project benefits into the future, we used the average

annual rate of sales growth. All data are presented in 1998 dollars.

Although we believe the change in consumer surplus for the

petroleum testing industry to be proportional to that of the coal

testing laboratories, we were unable to quantify that change.

Because of the large number of firms that provide independent

petroleum testing services and the wide range of other services they

provide, we could not get an accurate estimate of the percentage of

industry revenue generated by testing for sulfur in petroleum.

Without these data, we could not determine a reliable estimate of

the change in consumer surplus associated with using NIST SRMs

in quality control programs.
5-7

Table 5-4. Estimated Annual Impacts of NIST Sulfur SRMs ($1998)Avoided desulfurization of petroleum products and coal accounted for approximately 97 percent of total benefits.

Year H1 H2 H3

H4

Coal

H4

Gasoline

H4

Diesel H5

A

Exp

o

1986 $124,481 $— $456,456 $16,693,125 $— $— $— 1987 $128,784 $— $607,943 $17,227,500 $— $— $— 

1988 $172,429 $— $641,828 $17,818,125 $— $— $— $1989 $151,528 $— $560,105 $18,388,125 $— $— $— $1990 $206,239 $— $669,734 $19,295,625 $— $— $— $11991 $324,265 $— $1,107,586 $18,675,000 $— $— $— $11992 $376,516 $— $1,033,835 $18,703,125 $— $— $— $11993 $395,880 $— $1,183,994 $17,726,250 $— $— $— $21994 $411,862 $— $1,211,899 $19,378,125 $— $45,619,197 $— $1

1995 $349,776 $— $895,636 $19,368,750 $— $47,748,215 $— $11996 $313,815 $— $758,102 $19,948,125 $1,531,442 $50,328,686 $— $11997 $289,840 $— $770,725 $20,435,625 $1,544,854 $53,419,039 $— $11998 $313,200 $— $658,439 $20,975,625 $1,577,032 $56,286,887 $— $1

1999e $348,086 $— $730,176 $21,392,042 $1,600,361 $59,374,047 $— $12000e $386,859 $— $809,730 $21,816,727 $1,624,036 $62,588,301 $— $12001e $429,950 $— $897,951 $22,249,842 $1,648,061 $65,976,561 $— $12002e $477,841 $— $995,784 $22,691,556 $1,672,442 $69,548,247 $— $22003e $531,067 $— $1,104,276 $23,142,039 $1,697,183 $73,313,288 $— $2

Total NPV $2,665,422 $— $7,542,201 $180,186,303 $4,548,634 $216,673,636 $— $1,0

e= estimated
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

5-8

5.2 REDUCTIONS IN THE COST OF R&D (H2)

Our second hypothesis about the impact of NIST SRMs was that

SRMs would reduce the cost of R&D to the sulfur measurement

industry and the fuel industry by supporting accurate, reliable sulfur

measurement. Although some of our interviewees indicated that

NIST SRMs were part of their R&D laboratories’ quality control

program, they were not able to quantify any benefits to their R&D

program from NIST SRMs. We have no evidence to support this

hypothesis and cannot quantify any economic benefits due to

reductions in the cost of R&D attributable to NIST SRMs.

5.2.1 Sulfur Measurement Industry

The companies that develop and manufacture instruments that

measure sulfur content in fossil fuels use NIST SRMs in applications

development and to verify their prototype instruments. Although all

three of the instrument manufacturers we interviewed said that

SRMs are used in the quality control process in these R&D

laboratories, only one company stated that SRMs have any impact

on the cost of conducting R&D. Furthermore, this company

indicated that the R&D impact was minimal. The only savings the

company representative could identify was the savings in terms of

the labor required to gravimetrically prepare and verify in-house

standards if NIST standards were not available. He could not

quantify the associated cost savings.

5.2.2 Fossil Fuel Industry

The impact of NIST SRMs in the R&D sector of the fuel industry is

minimal. Most petroleum companies conduct R&D in the

development of lower sulfur fuels, but there is no evidence that

NIST SRMs reduce the cost of this research. One representative

mentioned that the primary reason that NIST SRMs are not an

important factor in R&D is because a quick turnaround time for

sulfur results is not as imperative in R&D as it is in production

operations and purchase/sales situations. Because NIST SRMs

support instrumental analytical methods that are used in

quick-turnaround situations, they are much more important in these

situations than they are in an R&D context.
Section 5 — Results

5-9

5.3 REDUCTIONS DUE TO TRANSACTIONS

COSTS (H3)

We hypothesized that NIST SRMs would reduce the cost of fossil

fuel transactions because measurements are accepted as reliable;

consequently, fewer transactions are disputed because of

measurement error. Most of our contacts indicated that,

theoretically, better measurements would reduce the number of

disputes. However, they emphasized that, in actuality, disputes

seldom occur and only a small proportion of them are related to

sulfur measurement problems. To estimate the benefits attributable

to NIST SRMs, we have to ask the question: what would be the

increase in the number of disputes if sulfur measurements were less

accurate in the absence of NIST?

To quantify this benefit, we first estimated the total cost to industry

of measurement disputes and assumed that 5 percent of these

disputes were associated with measurement error. We then used

the change in the standard deviation of sulfur content measurement

associated with and without the IDMS method to estimate the

decrease in disputes attributable to NIST SRMs.

In the coal industry, the sulfur content of coal is specified in

contracts. The acceptance levels are typically specified in pounds

sulfur per million Btu or as the sulfur percent weight of coal. The

contract generally details two sulfur specifications: a guaranteed

monthly weighted average for sulfur content and a rejection limit

sulfur content for individual shipments. For example, one industry

representative indicated that a typical contact may specify that the

average monthly sulfur content of their coal shipments cannot

exceed 2.87 percent, and that if any individual shipment tested

over 3.175 percent sulfur content, the shipment would be disputed

and could be rejected pending the resolution of the dispute.

Disputes rarely occur. One coal laboratory respondent stated that

less than 1 percent of all transactions are disputed. According to

this estimate because there are roughly six million coal shipments

each year in the United States, fewer than 60,000 shipments per

year are disputed. A coal company respondent indicated that only

“a few” shipments per year from her company are disputed. One

electric utility told us that they handled five disputes per month, or

about 120 disputes over coal shipments per year. Using the firm’s
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

5-10

share of annual electricity generation from coal, we can

conservatively estimate the number of disputes per year to be about

2,200.

To estimate the benefits attributable to NIST SRMs, we have to ask

the question, how much would this number rise if sulfur

measurements were less accurate in the absence of NIST SRMs? As

demonstrated in Section 4, if rejection criteria are constant, an

increase in the size of the standard deviation associated with sulfur

content measurement would increase the probability that a

shipment may be disputed simply due to measurement error. For

coal, the standard deviation today is only about 62 percent of what

it was before the introduction of IDMS. Thus, we assume that the

standard deviation of a sulfur measurement estimate would be 1.25

times as large without NIST SRMs as it would be with NIST SRMs.

Our model predicts that increasing the standard deviation by a

factor of 1.25 increases the dispute probability from 0.035 percent

to about 0.344 percent, meaning that about 18,800 more disputes

occur due to measurement error. One electric utility respondent

said the cost of resolving a dispute, inclusive of person-hours and

laboratory expenses, is about $700. Using these estimates, for the

coal supply chain, we estimate the cost of the additional disputes in

the absence of NIST SRMs to be $13.2 million per year.

However, most of our respondents party to coal contracts said that

usually when there is a dispute, it is because of human error. Thus,

only a handful of the disputes that occur can be attributed to

measurement error. No respondents were able to estimate the

percentage of disputes attributable to measurement error.

Assuming that 5 percent of the disputes are a result of measurement

error, we estimate that the reduction in transactions costs because

of increased measurement error is about $660,000 in 1998.

Table 5-3 presents our estimates from 1986 until 2003. The data

were weighted by the annual average percentage growth in sulfur

SRM sales to coal companies, petroleum companies, electric

utilities, and steel companies.
Section 5 — Results

5-11

5.4 INCREASES IN PRODUCTION EFFICIENCY

(H4)

Our fourth hypothesis is that NIST SRMs increase the efficiency of

fuel blending, desulfurization, and equipment operations because

the reliability of the measurement allows users to reduce the buffer

they employ to ensure compliance with technical specifications.

Information obtained during the interviews indicates that both the

petroleum industry and the coal industry are beneficiaries of this

benefit. In contrast, the interviews indicated that coke producers

and electric utilities burning coal rarely adjust their buffers to take

advantage of incremental gains in measurement accuracy because

of the difficulty and cost of physically mixing coal.

5.4.1 Petroleum Industry

Petroleum refineries use buffers in their production processes to

reduce the possibility of producing fuels that are found by

regulatory agencies to be off-specification, which carries regulatory

penalties for diesel nationally and gasoline in California. With

NIST SRMs, refineries have more accurate information about the

sulfur content of their products. The improved measurement

accuracy allows refineries to reduce the buffer between their target

sulfur content and the legal limit.

One petroleum industry respondent said that a typical refinery

operates with a buffer of about 5 percent. For on-highway diesel

fuel, which has a per-gallon sulfur content limit of 500 ppm, the

targeted sulfur content is 475 ppm. This 475 ppm target sulfur

content assures the refinery that, if the diesel fuel it produced is

tested by a regulatory agency, it will most likely not have a sulfur

content exceeding the 500 ppm critical limit.

The accuracy of NIST SRMs allow refineries to reduce their buffer,

thereby saving on desulfurization costs. In the absence of NIST

SRMs, the confidence interval around the target value widens

because the standard error is larger—about 1.75 times what it is

with NIST SRMs. Based on the approach outlined in Section 4, we

estimate that to achieve the same level of confidence without NIST

SRMs as with them, the target sulfur content would be 456.3 ppm,

rather than 475 ppm. Thus, refineries would remove an additional

18.7 ppm from each gallon of on-highway diesel fuel if they did not

have NIST SRMs. EPA estimates that the average cost of removing
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

5-12

1 ppm of sulfur from diesel and gasoline costs $0.0001 per gallon.

Our petroleum industry contacts agreed with this estimate.

In 1998, over 30 billion gallons of on-highway diesel fuel were

consumed in the United States. The cost of removing an additional

18.7 ppm sulfur from each gallon would have been approximately

$56 million. Table 5-4 presents estimates beginning in 1994

because it was the first complete year in which on-highway diesel

had a legal limit of 500 ppm. Estimates for 1999 until 2003 were

generated using the average annual percentage growth in diesel

sales from 1994 to 1998.

For gasoline, we limited our investigation to California reformulated

gasoline. Currently, California is the only state where the sulfur

content of gasoline is regulated. The regulation has been in effect

since 1996.

Elsewhere, refineries may limit the amount of sulfur in gasoline to

avoid damaging sensitive equipment, but they do not alter their

production processes to conform to a legal limit, thereby avoiding

regulatory penalties. Because these refineries alter their sulfur

content levels at their discretion, it is difficult to determine their

buffer and target sulfur content, and non-California reformulated

gasoline was not included in the benefits calculations.

California Air Resources Board (CARB) limits the sulfur content of

gasoline in California to an average of 30 ppm. Incorporating the

5 percent buffer, refineries producing gasoline for that market are

targeting a 28.50 ppm sulfur content. In the absence of NIST SRMs,

the refinery would have to revise its target limit downward to

achieve the same level of confidence that they would not be caught

off-specification. Refineries would target 27.38 ppm, removing an

additional 1.12 ppm. In 1998, California consumed over 14 billion

gallons of reformulated gasoline. If refineries had removed the

additional sulfur, the additional cost would have been $1.6 million

(see Table 5-4).

5.4.2 Coal Industry

The coal industry also uses buffers in their production process to

ensure that delivered coal meets the sulfur content specified in

contracts. Cleaning and blending of coal are used to remove sulfur

prior to shipment.
Section 5 — Results

5-13

One respondent from the coal industry estimates that coal

processors typically use a buffer of 0.05 percent sulfur content.

This buffer allows room for “spikes” in sulfur content but keeps the

running average below the contract maximum. The coal cleaning

process costs approximately $0.03 per ton per to remove

0.01 percent of sulfur.1

The accuracy of NIST SRMs allows refineries to reduce their buffer,

thereby saving on coal cleaning costs. In the absence of NIST

SRMs, the confidence interval around the target value widens

because the standard error is larger—about 1.25 times what it is

with NIST SRMs. Based on the approach outlined in Section 4, we

estimate that, to achieve the same level of confidence without NIST

SRMs as with them, the buffer would increase to 0.0625 percent

sulfur content. Thus, coal processors would need to remove an

additional 0.0125 percent sulfur from each ton of coal that they

clean. This yields a cost savings of $0.0375 per ton associated with

the increased accuracy of NIST SRMs.

It is estimated that the coal industry cleans approximately

50 percent of the 1.118 billion tons (1998) of coal mined in the

U.S.2 This yields an annual benefit of approximately $21 million in

1998 (see Table 5-4).

5.5 REDUCTIONS IN REGULATORY PENALTIES

(H5)

Our fifth hypothesis was that NIST SRMs reduce the fines paid by

industry due to environmental noncompliance because industry

and the regulatory community have accurate and reliable sulfur

content information. We hypothesized that improvements in the

measurement of sulfur may reduce the incidence and quantity of

penalties imposed by regulatory agencies.

As with coal transactions, the number of disputes between

regulatory agencies and regulated entities, such as electric utilities

and refineries, would probably rise in the absence of NIST SRMs.

 1Note that many factors influence the actual cost of removing sulfur from coal,

such as whether the sulfur is in the coal or in the rock, aerability of the sulfur

content, type of mine (underground or surface), type of cleaning process, and

raw and clean coal storage capacity.

2A large share of western coal has a low enough sulfur content that it does not

require cleaning.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

5-14

Although this may be the case, the fines paid by industry to

regulatory agencies constitute transfers payments. Therefore, we

did not quantify the increase in the number of fines in the absence

of NIST SRMs because no net social benefits are associated with

transfer payments.

5.6 BENEFITS TO THE ENVIRONMENT (H6)

Our final hypothesis was that SRMs reduce the amount of sulfur

entering the environment by providing industry greater control over

the sulfur content of its fuels and by allowing compliance officials

greater authority in enforcing the regulatory limits. Quantified

benefits to the environment are not included in the total benefits

presented in Table 5-4 or in the measures of economic return

calculated in Section 5.9. These benefits are presented separately

because they do not directly affect the sulfur measurement supply

chain. However, they are estimated and shown in Table 5-5.

As with the production efficiency hypothesis, the benefits to the

environment associated with NIST SRMs are limited to petroleum

products. With NIST SRMs, the reproducibility interval around the

target sulfur content value is smaller, which means that batches of

diesel fuel and gasoline are released with less sulfur. Lower sulfur

fuels reduce the amount of sulfur dioxide (SO2) emitted to the

environment.

Nationally, refineries produce diesel fuel with an average sulfur

content target of 475 ppm. The reproducibility interval, in terms of

ppm, is 64.32; the upper limit is the target plus half the

reproducibility interval, or 507.16 ppm. If the refinery tests the

sulfur content of the fuel and it is below this upper limit, they will

release the fuel because they are confident that their fuel falls

within the regulatory agency’s reproducibility interval around the

500 ppm legal limit. If the sulfur content exceeds the upper limit,

the refinery will reblend the fuel rather than risk the regulators

finding their product off-specification. In the absence of NIST, the

reproducibility interval increases to 112.35 ppm because the

standard error increases. The upper limit would be 531.17 ppm as

opposed to 507.16 ppm. Thus, with NIST SRMs, gasoline is

released with 24.01 ppm, or 5.06 percent, less sulfur.
Section 5 — Results

5-15

Table 5-5. Benefits to the Environment ($1998)

Increased accuracy of sulfur measurement allows compliance officials greater authority in enforcing the regulatory limits.

These benefits are not included in the measures of economic return calculated in Section 5.9 because they do not accrue

directly to the sulfur measurement supply chain.

Year H6

Gasoline

H6

Diesel

1984 $— $—

1985 $— $—

1986 $— $—

1987 $— $—

1988 $— $—

1989 $— $—

1990 $— $—

1991 $— $—

1992 $— $—

1993 $— $—

1994 $— $18,181,234

1995 $— $18,411,376

1996 $982,611 $19,101,802

1997 $997,147 $19,331,945

1998 $1,011,898 $19,792,229

1999e $1,026,868 $20,206,485

2000e $1,042,058 $20,620,741

2001e $1,057,474 $21,034,997

2002e $1,073,118 $21,449,253

2003e $1,088,993 $21,863,509

Total (NPV $1998) $2,921,050 $75,528,157

e = estimated

According to EPA, SO2 emissions from on-highway diesel fuel were

84,000 tons in 1997. Assuming a proportionate relationship

between sulfur in diesel and SO2 emissions, without NIST SRMs,

5.06 percent, or about 4,250 tons, more SO2 would have been

emitted to the environment. EPA estimates that, in the western
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

5-16

United States, the average environmental impact of a ton of SO2 to

be approximately $4,400 (1997).3

We estimate the benefits to the environment from NIST SRMs to be

$19.8 million for diesel fuel in 1998. The same analysis for

California gasoline yields approximately $1 million in benefits in

1998 (see Table 5-5). Benefits for both fuels begin in the first year

in which there is a legislated sulfur content limit. Our benefits

projections for 1999 to 2003 were based on the estimated growth

in sulfur dioxide emissions associated with those fuels (EPA,

1997b).

5.7 INDUSTRY COSTS

When measuring the benefits of NIST SRMs, it is important to also

take into account industry’s avoided expenditures on CRMs.4 It is

assumed that in the absence of NIST SRMs industry would have

been purchased commercially available CRMs to support their

sulfur measurement needs. Thus, from society’s perspective, these

avoided CRM expenditures are treated as a benefit and included in

the total benefit time series shown in Table 5-4.

CRMs are approximately 35 percent of the cost of NIST SRMs.5

Based on this percentage, we assumed that expenditures by

industry to produce CRMs would have been approximately 35

percent of NIST’s production, operations, overhead, and

administration expenditures.6 Thus, in 1998 it is estimated that

increased expenditures for CRMs in 1998 would have been

approximately $150,000 in the absence of SRMs.

 3We believe this particular estimate to be more conservative because most

estimates range from $2,000 to $13,000.

4Industry representatives said that no additional operational costs (pull costs) were

associated with using SRMs compared to using CRMs.

5Excluding the prices for isooctane and lubricating oil standards, the average price

of a NIST sulfur SRM is about $170. The pricing schedule for CRMs is based on

the number of units purchased. Assuming that customers purchase CRMs in

similar quantities as they purchase NIST SRMS, the average price is about $60.

The $60 price was determined by averaging the prices for CRMs comparable to

NIST SRMs from VHG Labs, Alpha Resources, AccuStandards, and NSI

Solutions Thus, society’s increased expenditures on sulfur CRMs is estimated to

be approximately 170/60 = 35 percent of NIST’s expenditures on sulfur SRMs.

6Research and development costs incurred by CRM manufacturers were assumed

to be sunk costs and are not included in the industry’s avoided CRM

expenditures.

Avoided expenditures on

CRMs are modeled as a

benefit and included in the

total benefit calculation
Section 5 — Results

5-17

5.8 NIST EXPENDITURES

Beginning in 1984, NIST began incurring expenditures to support

the Analytical Chemistry Division’s development and use of IDMS

sulfur SRMs. NIST expenditures are ongoing and cover SRM

development, production, operations, overhead, and administrative

costs for SRMs.

NIST’s program expenditures over time for sulfur SRMs developed

using the IDMS method are shown in Table 5-6. Expenditures were

calculated from NIST’s Standard Reference Market Transfer (SRMT)

notices. The time series was developed using the following

guidelines:

Z SRM development costs are incurred in the first year of the

time series.

Z SRM production costs are incurred in the year in which the

SRM “batch” was produced.

Z SRM operating, overhead, and administration costs are

distributed over time and are assumed to be incurred when

individual SRMs are sold.

SRM development costs: NIST’s Analytical Chemistry Division

received a $40,000 internal standards development (SD) award in

1984 to support research in new methods to certify SRMs.

Although this SD research was targeted toward certifying future

metals SRMs, the methodology was directly transferable to fossil

fuel analysis. Thus, 50 percent of this funding is ascribed to the

fossil fuel standards certification program. This investment

(adjusted for inflation) is shown in the NIST investment cost time

series shown in Table 5-6.7

SRM production costs: Production costs were obtained from the

SRMT notices and were available for 85 percent of the sulfur SRM

“batches” (including new and reissued SRMs) produced between

1984 and 1998. Average unit production costs were $56 ($1998).

Average unit production costs were used to estimate expenditures

 7Past NIST research conducted in related areas was also important to the

development of sulfur SRMs. Sulfur SRMs have benefited from previous

research in areas such as thermal ionization mass spectrometry (TIMS)

developed for nuclear standards program and atomic weight research, sample

preparation methods for TIMS, and sample preparation methods for isotope

dilution. Costs associated with related/supporting research are not included in

the NIST expenditure estimates presented in Table 5-6 used to calculate

economic returns.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

5-18

Table 5-6. Time Series of NIST Expenditures for Sulfur SRMs ($1998)

Production costs are incurred in the year in which the SRM was produced. SRM operations, overhead, and

administrative costs are distributed over time and were assumed to be incurred when SRMs are sold.

Year

SRM Development

Costs

SRM

Production

Costs

SRM Operations,

Overhead, and

Administrative Costs

Total Annual NIST

Expenditures

1984 $31,918a $97,310 $— $129,228

1985 $130,520 $— $130,520

1986 $202,231 $— $202,231

1987 $— $— $—

1988 $157,496 $15,000 $172,496

1989 $59,642 $20,354 $79,997

1990 $319,402 $117,511 $436,913

1991 $226,284 $273,809 $500,092

1992 $75,627 $306,349 $381,976

1993 $283,951 $387,576 $671,527

1994 $158,254 $419,176 $577,429

1995 $101,383 $336,784 $438,167

1996 $162,653 $302,697 $465,349

1997 $121,530 $321,631 $443,161

1998 $161,553 $266,152 $427,705

1999 $169,043 $280,532 $449,575

2000 $178,914 $295,690 $474,604

2001 $189,357 $311,656 $501,013

2002 $200,311 $328,325 $528,636

2003 $212,119 $346,243 $558,362

Total NIST Expenditures

(NPV $1998)

$31,918 $1,724,475 $1,901,442 $3,657,834

a$20,000 SD award in1984 converted to 1998 dollars.

for the remaining 15 percent SRMs, where SRMT notices

information was not available and for projected SRMs. Projected

SRM production from 1999 through 2003 was extrapolated based

on the average number of SRMs produced in the 1990s.

SRM operating, overhead, and administration costs: These costs

were also based on information obtained from SRMT notices, and

average unit cost estimates were used when SRM information was
Section 5 — Results

5-19

not available. SRM operating costs are approximately $90 per unit

and account for approximately 95 percent of the operating,

overhead, and administration category shown in column 4 of

Table 5-6.

The total NPV ($1998) of NIST expenditures, including SRM

development, production, operations, overhead, and administrative

costs, is $3.4 million.8 Production costs account for approximately

47 percent of NIST total expenditures.

5.9 CALCULATING MEASURES OF ECONOMIC

RETURN

To determine the returns from NIST’s investment in the

development and operation of the sulfur SRM program, we

compared the net benefits to industry described above with NIST

sulfur SRM expenditures. We calculated three summary measures

of the net benefits of the program: the benefit-cost ratio, the net

present value (NPV), and the social rate of return.

If Bt is the total net benefits to industry (H1 through H5 plus

avoided CRM expenditures) accrued to all beneficiaries in year t,

and Ct is the cost to NIST of the program in year t, then the benefitcost ratio for the program is given by

(B/C) = 

∑

i=0

n B(t+i)

(1+r)i

∑

i=0

n C(t+i)

(1+r)i

(5.1)

where t is the first year in which benefits or costs occur, n is the

number of years the benefits or costs occur, and r is the social rate

of discount. Because benefits and program costs may occur at

different time periods, both are expressed in present-value terms

before the ratio is calculated.

The NPV of the NIST SRMs program can be computed as

 8NIST recovers the majority of its SRM development, production, operations,

overhead, and administrative expenditures by selling SRMs to industry.

However, because we are estimating the benefits and costs of SRMs to society

(not to individual organizations or economic sectors), the selling price of SRMs

does not enter our analysis; the revenue recovered by NIST is a transfer

payment.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

5-20

NPV = ∑

i=0

n



 

B(t+i  )

(1+r)i – Ct+i

(1+r)i . (5.2)

The social rate of return is the value of r that sets NPV equal to 0 in

Eq. (5.2).

For the NIST sulfur SRM program, the following parameter values

were used to calculate economic returns:

t = 1984: first year in which NIST incurred development

costs related to sulfur SRMs

n = 19: number of years from 1984 to 2003

r = 7 percent: inflation adjusted social discount rate

As shown in Table 5-2, NIST expenditures begin in 1984. However

benefits associated with NIST sulfur SRMs are identified beginning

in 1986 with the introduction of the IDMS sulfur SRM.

The three measures of economic return are provided in Table 5-7.

The estimated net benefits to industry from the program greatly

exceed NIST’s investment costs. In addition, these estimates of

economic return may represent a lower bounds because we were

not able to quantify several identified benefit categories, whereas

all identifiable costs to industry and NIST investment costs are

included in the calculations.

Measure of Social Returna Economic Impact

Benefit-to-cost ratio 113

Net present value ($1998) $409,002,097

Social rate of return 1,056%

aBased on a 7 percent inflation adjusted social discount rate.

5.10 CONCLUSIONS

In summary, most industry representatives surveyed indicated that

NIST SRMs have decreased the level of uncertainty associated with

the measurement of sulfur in fossil fuels. In the absence of NIST

SRMs, industry would likely purchase CRMs for sulfur testing. We

found qualitative evidence that this reduction in the level of

uncertainty has led to economic benefits throughout the supply

Table 5-7. Economic

Impact of NIST SRMs

Economic impacts reflect

benefits and costs from 1984

projected through 2003.
Section 5 — Results

5-21

chain, as described in the impact hypotheses presented in this

section.

The majority of the economic benefits we were able to quantify are

associated with using SRMs in petroleum refineries’ and coal

companies’ production processes. Improved sulfur measurement

allows these industries to reduce the amount of desulfurization they

conduct on fuels, which yields substantial cost savings. Avoided

desulfurization accounted for approximately 97 percent of the total

benefits used to calculate measures of economic return.
R-1

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A-1

SRMs’ Impact on

Sulfur Measurement A Accuracy

The instrumental methods used most often to measure the sulfur

content of coal and petroleum products described above are based

on the classic linear calibration model shown in Figure A-1. They

rely heavily on the use of standards and calibrants. In this section,

we demonstrate how the bias and precision of the standard used to

calibrate the instrument contribute to uncertainty in sulfur content

measurement.

Figure A-1. Classical Linear Calibration Model

Bias in the calibration standard leads to bias in the estimate of the slope of the curve; this leads to bias in estimates of the

sulfur content.

y

(Instrument

Response)

x (Sulfur Content)

y1

x1 Px1 Px2 Px3 x2 x3

y = α + βx

Actual response curve

bias in x when y = y1 is observed

y3

y2

y = α + (β/P)x

Calibrated response curve

when x is biased
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

A-2

The instrument response curve can be described as

yi = α + βxi + εi,

where

yi is the reported value of the sulfur content for test i, and

xi is the actual (or accepted) value of the sulfur (as defined by

the standard) for test i.

If we assume that xi, the amount of sulfur in the standard, is known

with certainty, then the error term, εi, refers only to measurement

error associated with the instrument response. If we also assume

that all the other assumptions of ordinary least squares (OLS) apply,

the OLS estimator of β, β

^, is an unbiased, consistent estimator of

the slope of the calibration curve. The error εi indicates the

uncertainty associated with the measurement of a single sulfur

sample using that instrument.

This is the classic linear calibration model. We assume that this

form of the model applies. It relies on the assumption that the

calibration curve is linear, at least locally. In many cases, the

calibration is conducted at several points along the line to allow the

linearity to be tested. The issue of the appropriateness of this

assumption is discussed at length by Mandel (1984).

A.1 IMPACT OF BIAS IN THE CERTIFIED VALUE

OF THE SRM

Now suppose that the standard values of x are not known with

certainty. First, assume that xi

 ́, the certified sulfur content of the

standard, is really equal to Pxi, where xi is the actual value and P is

a given proportion that holds for all standards. Note that

P = % recovery

100 = xi

 ́

 xi 

 = relative bias + 1 = bias

true xi

+ 1.

The calibration curve gives

y = α + βx + ε

= α + β

Px′ + ε.
Appendix A — SRMs’ Impact on Sulfur Measurement Accuracy

A-3

Thus a negative bias in the SRMs (P<1) leads to an overestimate of

β, which in turn leads to negative bias in the observed

concentrations that mimics the bias in the SRMs:

x′ = y – α

β/P = P 







 y – α

β = Px.

A.2 RANDOM MEASUREMENT ERROR IN THE

CERTIFIED VALUE OF THE SRM

Now consider the impact of random measurement error associated

with xi. Putting aside the issue of bias in the calibration standard,

let us assume that there is no bias in xi (e.g., the certified value of

the standard is equal to the expected value), but that the certified

value is measured with error. In this case, two things happen:

1. The error associated with the measurement of xi introduces

additional error into estimates of yi.

2. The least squares estimate of the slope underestimates the

true value (Maddala, 1988). This is the classic errors in

variables model. The bias is equal to βλ, where λ is the

proportion of error variance in the variance of xi. This bias

occurs because the usual OLS assumption of independence

is violated (the equation error εi is correlated with the xi).

Assume that the variability of the observed instrument responses

during the calibration process can be separated into two

components:

σey

2 + β2σr

2 ,

where σey

2 is the variance associated with the instrument response,

and σr

2 is the variance associated with the SRM. Then the variance

of an observed sulfur value, X1,

Var(X) = 

σey

2

β2 + σr

2 = σex

2 + σr

2 ,

where σex

2 is the error variance translated into the x scale that

would be expected with perfect SRMs. This formula treats the

slope as a known quantity (i.e., it ignores random error in the

estimate of the slope). In practice, the two variance components

may be inseparable; that is, we may not be able to determine what

part of the variance is due to variability in the SRM.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

A-4

However, recall also that petroleum products and coal must be

sampled before analysis and that sampling introduces another

source of uncertainty. Suppose the material (coal or petroleum) is

sampled from a batch. The result of the sulfur analysis is the mean

of n observations of the sulfur content of the batch. Then the

variance of the mean of n observations (x–) is:

Var (X–) = 

( ) σs

2 + σex

2 + σr

2

n .

Note that if the samples that are taken are composites (e.g., samples

taken from a number of locations and mixed up to make a single

sample—this is common in coal sampling), then the equation is

Var (X–) = 









 σs

2

k + σex

2 + σr2

n ,

where k is the number of samples in the composite and n is the

number of composite samples. This formula assumes that the

compositing process itself has negligible error; this assumption will

tend to be violated if the physical size of the composite gets too

large (i.e., if k is “too big”) and/or if homogenization or weighing is

difficult.
B-1

B Survey Form

This appendix contains a master list of the survey questions for

primary data collection from industry. We constructed ten different

interview guidesone for each of the industries listed in Table B-1.

After we finalized the master list of questions, we developed each

interview guide by pulling the relevant sections, as shown in

Table B-1, from the master list into the guide.

Table B-1. Structure of Industry Interview Guides

We will construct each of the ten interview guides by pulling relevant sections from the master list of questions.

Industry Relevant Questionnaire Sections

Sulfur measurement industry

Instrument manufacturers 1, 2, 3, 4.1, 4.2

CRM manufacturers 1, 2, 3, 4.1, 4.2

Independent testing laboratories 1, 2, 3, 4.1, 4.2

Fossil fuel extraction, processing, and transportation industry

Coal companies 1, 2.3, 4.3, 4.4

Petroleum companies 1, 2, 3, 4.1, 4.3, 4.4

Coke companies 1, 2, 3, 4.3, 4.4

Oil pipelines 1, 2, 3, 4.3, 4.4

Fossil fuel combustion industry

Electricity generation firms 1, 2, 3, 4.3, 4,4

Steel companies 1, 2, 3, 4.2, 4.3, 4.4

Regulatory agencies 1, 2, 3, 4.3, 4.5
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

B-2

1.1 Contact Information

1.1.1 Contact name:

1.1.2 Contact address:

1.1.3 Contact phone:

1.1.4 Contact fax:

1.1.5 Contact email:

1.1.6 Date and time of interview:

1.2 Company Information

1.2.1 Company name:

1.2.2 Division and title of contact:

1.2.3 Contact background:

1.2.4 Company’s primary line of business:

1.2.5 Company’s total revenue:

1.2.6 Division revenue (if applicable)

1.2.7 List of company products and services that are supported in any way by SRMs or

sulfur testing (might have to ask this later in the interview so the interviewee

understands purpose and context of question)

Product Description Price

Annual Revenue, or Percent of Total

Revenue
Appendix B — Survey Form

B-3

2. USE OF SULFUR TESTING AND SRMS

2.1 Use of Sulfur Testing

2.1.1 Does your company conduct tests of the sulfur content of fossil fuels?

2.1.2 What fuels are tested?

2.1.3 How many tests do you conduct each day?

2.1.4 What is this information used for?

2.1.5 What ASTM methods are followed in this testing?

Check if

Used

ASTM Method

Number Description

D 4239 (Method C) Sulfur in the Analysis Sample of Coal and Coke Using

High-Temperature Tube Furnace Combustion Methods

D 2622 Sulfur in Petroleum Products by X-Ray Spectrometry

D 5453 Determination of Total Sulfur in Light Hydrocarbons,

Motor Fuels, and Oils by Ultraviolet Fluorescence

ASTM D0129 Sulfur in Petroleum Products (General Bomb Method)

ASTM D1072 Sulfur Content (Total) In Fuel Gas

ASTM D1266 Sulfur in Petroleum Products (Lamp Method)

ASTM D1275 Corrosive Sulfur in Electrical Insulating Oils

ASTM D1552 Sulfur in Petroleum Products (High Temperature

Method)

ASTM D2784 Sulfur in Liquefied Petroleum Gases by Oxy-Hydrogen

Burner/Lamp Test

ASTM D3120 Sulfur in Liquid Petroleum Products by Oxidative

Microcoulometry

ASTM D3177 Sulfur(Total)—Analysis Sample of Coal/Coke For

Ultimate Analysis

ASTM D3227 Mercaptan Sulfur in Gasoline, Kerosene

(Potentiometric Method)

ASTM D3246 Sulfur in Petroleum Gas By Oxidative Microcoulometry

ASTM D4045 Sulfur in Petroleum Products by Hydrogenolysis and

Rateometric Colorimetry
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

B-4

Check if

Used

ASTM Method

Number Description

ASTM D4294 Sulfur-Petroleum Products, by Energy-Dispersive X-ray

Fluorescence Spectroscopy

ASTM D4468 Sulfur Content (Total) in Gaseous Fuels, by

Hydrogenolysis/Rateometric Colorimetry

ASTM D4951 Additive Elements-Lubricating Oils by Inductively

Coupled Plasma Atomic Emission Spectrometry

ASTM D4952 Active Sulfur Species-Fuels/Solvents, Qualitative

Analysis by Doctor Test

ASTM D5016 Sulfur Trioxide (SO3) in Ash From Coal/Coke Using

High Temperature Tube Furnace Combustion Method

with Infrared Absorption

ASTM D5504 Sulfur Compounds—Presence in Natural Gas/Gaseous

Fuels, by Gas Chromatography/Chemiluminescence

ASTM D5623 Sulfur Compounds in Light Petroleum Liquefy Gas

Chromatography

2.1.6 What instruments do you use in these tests?

Company Model Number Description
Appendix B — Survey Form

B-5

2.2 Use of SRMs

2.2.1 What calibrants do you use with these instruments/methods?

2.2.2 Do you use NIST SRMs? (Before interview, check against NIST SRM Customer

Database.)

2.2.3 How many years have you been using NIST SRMs?

2.2.4 Which SRMs do you use? (Check against table below.)

Certificate

Date

1st Year

Used SRM Number Description

9/1/95 1616a Sulfur in Kerosene

7/1/95 1617a Sulfur in Kerosene

4/30/91 1619a Sulfur in Residual Fuel Oil, 0.7%

7/27/98 1619b Sulfur in Residual Fuel Oil, 0.7%

7/1/90 1620b Sulfur in Residual Fuel Oil, 4%

7/1/96 1621e Sulfur in Residual Fuel Oil, 1%

4/1/97 1622e Sulfur in Residual Fuel Oil, 2%

7/1/96 1623c Sulfur in Residual Fuel Oil, 0.3%

6/1/97 1624c Sulfur in Distillate Fuel Oil, 0.4%

6/1/97 1632b Trace Elements in Coal (Bituminous)

6/1/93 1633b Trace Elements in Coal Fly Ash

7/1/95 1635 Trace Elements in Coal (Subbituminous)

4/1/94 1819a Sulfur in Lubricating Base Oil

3/1/98 2294 Reformulated Fuels (nom. 11% MTBE, 35 mg/kg sulfur)

3/1/98 2295 Reformulated Fuels (nom. 15% MTBE, 300 mg/kg sulfur)

3/1/98 2296 Reformulated Fuels (nom. 13% ETBE, 35 mg/kg sulfur)

3/1/98 2297 Reformulated Fuels (nom. 10% ethanol, 300 mg/kg sulfur)

5/1/94 2682a Sulfur in Coal, 0.5%

2683a Sulfur in Coal, 2%

10/27/97 2683b Sulfur in Coal, 2%

12/1/97 2684a Sulfur in Coal, 3%

5/1/94 2685a Sulfur in Coal, 5%

12/1/93 2690 Trace Elements in Coal Fly Ash

12/1/93 2691 Trace Elements in Coal Fly Ash

9/1/94 2692a Sulfur in Coal, 1%

10/1/90 2717 Sulfur in Residual Fuel Oil
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

B-6

Certificate

Date

1st Year

Used SRM Number Description

NA 2718 Green Petroleum Coke

NA 2719 Calcined Petroleum Coke

8/1/95 2724a Sulfur in Distillate Fuel Oil, 0.04%

5/1/97 2775 Foundry Coke

3/1/98 2776 Furnace Coke

2.2.4 How do you use the NIST SRMs?

2.2.5 Do you use any secondary standards?

If Yes, which do you use? (Fill in table below.)

Company CRM Number/Name

2.2.6 How do you use the secondary standards, and how does this differ from how

you use NIST SRMs?

2.2.7 What do you view as the difference between NIST and secondary standards?

• Quality?

• Price?

• Best use?
Appendix B — Survey Form

B-7

3 IMPACT OF SRMS

3.1 Suppose NIST SRMs were not available for the uses described above. What

would you use as a substitute?

3.2 Given that you would have to substitute a different material or process, do you

think the methods you use to measure sulfur in fossil fuels would change?

• By what percentage do you think the repeatability of ASTM methods would

change?

• Do you think the level of bias would change?

4 USE OF SULFUR TESTING INFORMATION

4.1 R&D

4.1.1 Does your company conduct R&D related to sulfur content of fuels or the

development of sulfur measurement instruments and methods?

4.1.2 What is your company’s total R&D budget?

4.1.3 What percentage of your company’s total R&D budget is allocated to sulfur

testing or sulfur content issues?

4.1.4 How do NIST SRMs support this R&D?

4.1.5 In the absence of NIST SRMs, do you think your R&D costs in this area would be

higher?

• By what percentage?

• Why?

4.2 Quality of Products and Services

4.2.1 Do you use NIST SRMs for quality control or for any other reason in the

production of your products and services?

4.2.2 If NIST SRMs were not available, what changes would you make in these

processes?

4.2.3 How do you think this would affect the quality of your products?

4.2.4 Do you think your customers would value your products less if they were not

produced with the support of or traceability to NIST SRMs?

4.2.5 Given the current prices of your goods and services, by what percentage do you

think the prices your customers would be willing to pay for your goods and

services would fall?
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

B-8

4.3 Transactions Costs

4.3.1 What percentage of the transactions (sales or purchases) of fossil fuels are based

on contracts that specify sulfur content?

4.3.2 How are these contracts structured?

4.3.3 What happens if the contract specifications are not met?

• What happens if the sulfur content is too high?

• What if it is too low?

4.3.4 How often are shipments disputed due to sulfur content?

4.3.5 Are these disputes usually resolved?

4.3.6 How are they resolved?

4.3.7 How are SRMs used in the dispute settlement process?

4.3.8 What is your estimate of the cost of resolving a dispute?

• What are the most costly parts of the process?

4.3.9 How often are shipments totally rejected (i.e., no resolution of dispute)?

4.3.10 What could help to decrease the incidence of these disputes?

4.3.11 Do you think these disputes or rejections are ever caused by measurement error?

4.3.12 What percentage of disputes do you think could be avoided if the measurement

process was more accurate?

4.4 Productivity

4.4.1 What operations at your facility are affected by sulfur content?

• Fuel blending

• Desulfurization

• Boiler operations

• Emissions control

• Coking

• Others?

4.4.2 How are they affected by sulfur content?

4.4.3 What are the technical specifications regarding sulfur content of fuels for these

processes?
Appendix B — Survey Form

B-9

4.4.4 Do you feel that the information you have about sulfur content is sufficient to

ensure that you meet the technical specifications for sulfur?

4.4.5 How often are the technical specifications not met?

4.4.6 What is the impact of going over technical limits?

• What are the technical impacts?

• What are the economic impacts?

4.4.7 What is the impact of going under technical limits?

• What are the technical impacts?

• What are the economic impacts?

4.4.8 What is your strategy for ensuring that you meet the technical limits?

4.4.9 Do you use a “buffer,” i.e., shoot for some lower level to ensure that, given

measurement error, you will not test over the limit?

4.5 Regulatory Penalties

4.5.1 How are sulfur content limits monitored?

4.5.2 What is the structure of enforcing these limits?

• Under what conditions are regulatory penalties imposed?

• What is the size of the regulatory penalties?

• How many companies are fined per year, and what is the annual amount of

total fines?

4.5.3 What is the role of NIST SRMs in imposing regulatory penalties?

4.5.4 How would enforcement be affected if NIST SRMs were not available to support

the measurement process?
C-1

Profiles of C Affected Industries

This appendix provides the background required to understand the

importance of NIST SRMs to this supply chain. Section C.1

provides brief profiles of the affected industries: the sulfur

measurement industry, the fossil fuel extraction and processing

industry, and the fossil fuel combustion industry. Section C.2

describes the importance of sulfur as a characteristic of fossil fuels,

including the regulations affecting the industries that produce and

use fossil fuels in the U.S., and why these regulations increase the

importance of accurate information about the sulfur content of

fossil fuels. Section C.3 describes how NIST SRMs support these

industries, including information about who buys NIST SRMs for

sulfur in fossil fuels and how they are used.

C.1 INDUSTRY PROFILE

Many industries depend on NIST SRMs to support the measurement

of sulfur in fossil fuels. Figure C-1 provides a graphical

representation of the relationships among these industries. The

sulfur measurement industry includes manufacturers of sulfur

measurement instruments and CRMs and independent laboratories

that conduct sulfur analysis. These companies use NIST SRMs in

developing their instruments, preparing their CRMs, and providing

quality control in their sulfur measurement laboratories. They

supply instruments, reference materials, and analytical services to

the fossil fuels industry.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-2

NIST

Processed

Fossil Fuels

Fossil Fuel Combustion

• Electricity Generation

• Steel Industry

• Industrial Combustion

Users of Power, Steel, and

Other Goods and Services

Power and

Steel

SRMs

Sulfur Measurement

Products and Services

Fossil Fuel Extraction, Processing, and

Transportation

• Coal Processing

• Petroleum Refining

• Coke Production

Sulfur Measurement

• Instrument Manufacturers

• Manufacturers of Certified Reference

Materials

• Independent Testing Laboratories

The fossil fuels extraction and processing industry includes coal

processing, petroleum refining, and coke production.1 This

industry uses the sulfur measurement products and services of the

sulfur measurement industry and also uses NIST SRMs to support

their in-house sulfur measurement activities. This industry supplies

 1Although natural gas is part of the fossil fuel industry, we did not analyze the

natural gas industry because NIST does not provide an SRM for sulfur in natural

gas because very little sulfur is found in natural gas, and its measurement is not

an important industry issue.

Figure C-1. Industries

Affected by

Measurement of Sulfur in

Fossil Fuels

Sulfur measurement is

supported by each element of

the measurement industry and is

used by each member of the

fossil fuel supply chain.
Appendix C — Profiles of Affected Industries

C-3

processed fossil fuels to the industries that engage in fossil fuels

combustion.

Although many industries engage in the combustion of fossil fuels,

we concentrated on three sectors—sulfur measurment industry,

petroleum refining, and coal processing—because they are primary

users of fossil fuels. These industries use NIST SRMs for their inhouse sulfur measurement activities. Industrial combustion also

accounts for a large percentage of the fossil fuels consumed in the

U.S. However, because of the difficulty of characterizing this

diverse set of industries, we focus primarily on the electricity

industry and the steel industry in this study.2

The final link in the supply chain is the users of power, steel, and

other goods and services that are produced with fossil fuels. This

link includes essentially the entire U.S. economy. Thus, we limited

our analysis by focusing on the upstream components of the supply

chain.

Environmental regulatory agencies, including EPA and state

agencies, affect the operations of the second and third tier of

industries. They develop, monitor, and enforce sulfur content

regulations for the petroleum industry and develop, monitor, and

enforce sulfur compound emissions limits for industries engaging in

fossil fuel combustion. We discuss the role of the regulatory

community and their use of NIST SRMs in Section C.2.

C.1.1 Sulfur Measurement Industry

The industry that supports the measurement of sulfur in fossil fuels

includes the manufacturers of instruments, suppliers of CRMs, and

independent laboratories that conduct sulfur analysis.

Instrument Manufacturers

Determinators, spectrometers, elemental analyzers, and

chromatographers are measurement equipment used to determine

the elemental composition of organic and inorganic samples. Fuel

and chemical manufacturers for whom knowledge of a sample’s

sulfur content is important use these devices. For example, the

 2Industrial combustion refers to the use of industrial, commercial, and institutional

(ICI) boilers whose primary use is for process heating, electrical or mechanical

power generation, and/or space heating. Industrial boilers are used in all major

industrial sectors.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-4

petroleum industry uses sulfur analyzers to determine the sulfur

content of the fuels they produce.

Manufacturers and consumers of these measurement instruments

use NIST’s sulfur SRMs to test and calibrate their equipment. These

instruments must be properly calibrated to provide quality

laboratory results. Sulfur SRMs allow technicians to test an

instrument’s accuracy and inform them of any need for

adjustments. Equipment technicians may use NIST’s sulfur SRMs

directly, or they may use NIST-traceable CRMs from a secondary

manufacturer to calibrate laboratory equipment.

Although many companies manufacture laboratory equipment,

relatively few manufacture the type of equipment used to determine

the sulfur content of coal and petroleum products. Table C-1 lists

companies that produce these instruments at manufacturing

facilities in the U.S. Together, these companies generate over

$1 billion in revenue, although a significant percentage of this

revenue is from equipment other than sulfur analysis equipment.

Smaller firms generally produce a single product or several models

of a single product, such as a line of analyzers. Many larger firms

also manufacture other laboratory equipment, such as analyzers for

nitrogen or other elements.

Manufacturers of Certified Reference Materials

A CRM is defined by the International Standards Organization (ISO)

as “a reference material one or more of whose property values are

certified by a technically valid procedure, accompanied by or

traceable to a certificate or other documentation which is issued by

a certifying body” (American National Standards Institute [ANSI],

1981). CRMs are used in the same way as NIST SRMsfor

equipment calibration, development of other standards, and quality

control for analyzing sulfur in fossil fuels. CRMs are often used in

conjunction with NIST SRMs. In many laboratories, CRMs are used

on a daily basis while NIST SRMs are used only occasionally.

Table C-2 lists the companies that market CRMs for sulfur in fossil

fuels in the U.S. Each company’s role in the production of their

CRMs varies. Some companies produce and certify CRMs at their

own facilities and laboratories, whereas other companies produce

the standards but hire an outside laboratory to certify the sulfur
Appendix C — Profiles of Affected Industries

C-5

Table C-1. Principal Manufacturers of Sulfur Analysis Equipment

The market for sulfur analysis equipment includes a few very large firms and many smaller firms.

Company City State

Sales

($million)a Employees Yearb

Alcor Petroleum Instruments, Inc. San Antonio TX 8.00 35 1997

Amray, Inc. (KLA-Tencor) Bedford MA 20.00 185 1996

Analytical Spectral Devices Boulder CO 4c 27 1997

Antek Instruments Co. Houston TX 8.00 50 1997

Asoma Instruments, Inc. Austin TX 15.00 70 1998

Berger Instruments, Inc. Berwyn PA 1.00 35 1997

Buck Scientific, Inc. Norwalk CT 8c 30 1998

Burrell Scientific, Inc. Pittsburgh PA 4.00 18 1997

Diano Corp. Woburn MA 2.00 14 1997

Exeter Analytical, Inc. N. Chelmsford MA 1.00 5 1997

Extrel Corporation Pittsburgh PA 14.00 108 1997

Hitachi Instruments San Jose CA 77.4b 280 1997

Horiba Instruments (USA), Inc. Irvine CA 81.00 250 1997

Houston Atlas Houston TX 7.50 40 1998

Kevex Instruments Valencia CA 22.00 130 1997

Koehler Instrument Co., Inc. Bohemia NY 4.00 NA 1997

Leco Corp. St. Joseph MI 100.00 1,000 1992

Leeman Labs, Inc. Lowell MA 17c 125 1998

Nicolet Instrument Corp. Madison WI 48.00 400 1997

Noran Instruments, Inc. Middleton WI 40.00 160 1997

Oxford Instruments America, Inc. Concord MA 12d 80 1997

Preiser Scientific, Inc. St. Albans WV 8.00 40 1997

Spectro Analytical, Inc. Littleton MA 9d 22 1997

Varian, Inc. Palo Alto CA 557.8c 3,033 1998

aSales and employment data are from American Business Information, Inc., 1998. The American Business Disk

[computer file]. Omaha, NE: American Business Information (except where indicated).

bYear for which sales and employment data are applicable.

cSales and employment information for these companies is from Information Access Corporation, 1998. Business Index

[computer file]. Foster City, CA: Information Access Corporation.

dSales and employment information is from Dun & Bradstreet, 1997. D&B Million Dollar Directory: America’s Leading

Public and Private Companies. Bethlehem, PA: Dun & Bradstreet, Inc.

Source: This list of companies was compiled from various public sources on the instruments market.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-6

Table C-2. Sulfur in Fossil Fuels CRM Manufacturers’ Sales Ranges and Employment, 1999

This industry comprise small- to medium-size companies.

Company City State

Sales

($million) Employment

Absolute Standards, Inc. Hamden CT 0.90a 7

AccuStandards, Inc. New Haven CT 4.65a 50

Alpha Resources, Inc. Stevensville MI 15.00 22

Analytical Services, Inc. The Woodlands TX 0.30a 2

NSI Chemical Standards, Inc.b Durham NC 3.75 17

SPEX CertiPrep, Inc.b Metuchen NJ 10.00c NA

Vanguard Solutions, Inc. Ashland KY 0.78a 3

VHG Labs, Inc. Manchester NH 1.75 19

aDun & Bradstreet, 1999. D&B Million Dollar Directory: America’s Leading Public and Private Companies.

Bethlehem, PA: Dun & Bradstreet, Inc.

bThese companies market CRMs but outsource the preparation and certification of sulfur CRMs.

cInformation Access Corporation. 1998. Business Index [computer file]. Foster City, CA: Information Access

Corporation.

Source: American Business Information, Inc. 1998. The American Business Disk [computer file]. Omaha, NE:

American Business Information.

content. A third option for companies is to purchase standards

from another firm and then market those standards under their own

private label.

CRMs are generally prepared using NIST SRM products (when

available) and the American Society for Testing and Materials

(ASTM) procedures. However, none of the CRM producers

duplicate the procedures followed by NIST. NIST SRMs for sulfur

in fossil fuels are certified using a technique known as IDMS. As

explained in Section 3, IDMS is a definitive method that virtually

eliminates bias and significantly reduces the relative uncertainty

associated with reference materials. No commercial CRM

manufacturers use IDMS; instead, they employ ASTM methods

and/or interlaboratory testing for certification. The less rigorous

process used by the CRM manufacturers can sometimes lead to

significant differences between the accuracy and precision of the

certified values provided by NIST and those provided by a CRM

manufacturer.

Many CRM companies offer a wider variety of standards than NIST

does. They may also provide a wider variety of base materials as
Appendix C — Profiles of Affected Industries

C-7

well as a larger selection of concentrations. Those CRMs that do

have a NIST SRM counterpart usually cost less than the comparable

NIST SRM. The price difference probably reflects differences in the

cost of instruments and procedures used to certify the reference

materials and economies of scale associated with CRMs’ larger

production volume.

NIST SRMs are an important input in the CRM production process.

CRM manufacturers use NIST SRMs to verify product quality and to

certify that their products are NIST-traceable. It is possible that

CRMs would be more expensive to produce and would not be of

the same quality if NIST SRMs were not available. Many CRM

manufacturers use the fact that their products are NIST-traceable as

a key selling point.

Eight small- to medium-sized companies market CRMs for sulfur in

fossil fuels (see Table C-2). The smallest companies have annual

revenues as low as $300,000; the largest have annual revenues as

high as $15 million. As a group, these companies had combined

annual revenues of about $37 million in 1997. Only two

companies employ more than 20 people: Alpha Resources and

AccuStandards.

Independent Sulfur Testing Laboratories

Independent sulfur testing laboratories fall within SIC 8734, testing

laboratories. In 1992, the U.S. had over 4,500 commercial testing

laboratories generating almost $5 billion in revenue and $2 billion

in payroll each year (U.S. DOC, 1994).3 A small subset of these

laboratories conduct sulfur analysis of fossil fuels. These

laboratories conduct inspection, sampling, and analytical services

for fossil fuel producers and consumers.

Independent laboratories are an important link in the supply chain

affected by SRMs. Although many mines, coking plants, coal

preparation plants, utilities, and refineries have their own

laboratories for these analyses, independent laboratories are

becoming more important, particularly for contractual matters.

Third-party independent laboratory results are routinely used to

satisfy contractual requirements for buyers and sellers in the coal

 3These figures include taxable firms only. Noncommercial research organizations

are not included.

Independent laboratories

are an important link in the

supply chain because they

provide independent

testing results to satisfy

contractual requirements

for fossil fuel transactions.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-8

industry, and this arrangement is increasing in the petroleum

industry as well. To cut costs some firms also hire independent

laboratories rather than operate their own.

Independent testing laboratories offer coal and petroleum sampling

and testing services. They also offer an array of other services:

Z the running of contract laboratories;

Z coal preparation plant services: consulting on preparation

plant development, operation, equipment, washability, and

best practices;

Z power plant services: consulting on fuel combustion,

performance testing, fuel selection, materials handling,

training, and fuel switching;

Z coal and mineral round robin services: ensuring quality

laboratory results and procedures;

Z stockpile inventory services: determining the quantity and

quality of coal and coke in storage; and

Z other environmental services.

Two firms dominate the market for coal testing: Commercial

Testing and Engineering Company (CT&E), headquartered in

Lombard, IL, and Standard Laboratories (SL) of South Charleston,

WV. CT&E is a wholly owned subsidiary of SGS North America,

Inc., the North American division of the world’s largest inspection

and testing company, Société Générale de Surveillance (SGS). As

shown in Table C-3, CT&E had revenues of $57.0 million in 1997

and employed 600 professionals at more than 50 locations in the

contiguous U.S. SL’s revenues were $37.0 million in 1996. SL

employs approximately 500 people at more than 50 locations in the

U.S. and abroad. Both companies together control over 90 percent

of the contractual coal testing market (Vaninetti, 1998).

Most of the laboratories owned by SL and CT&E are located either

in coal-producing states or at main ports for imported and export

coal (see Figure C-2). Laboratories are primarily concentrated in

key coal areas, mainly West Virginia, Kentucky, Colorado, and

Wyoming. Coastal laboratories analyze samples for the coal

import-export market. For example, CT&E’s San Pedro, CA, facility

serves the ports of Long Beach, Los Angeles, and San Francisco.

The Norfolk, VA, facility serves the ports of Norfolk Southern Coal,
Appendix C — Profiles of Affected Industries

C-9

Table C-3. Sales and Employment of Major Coal Testing Laboratories

Two companies, CT&E and SL, dominate the market for coal testing services.

Company

Revenue

($million)a Employmenta Location

Commercial Testing & Engineering $57 600 Lombard, Illinois

Parent: SGS North America $400 5,900 Parsippany, New Jersey

Ultimate Parent: SGS S.A. $2,260b 28,000 Geneva, Switzerland

Standard Laboratories $37 500 South Charleston, West Virginia

aRevenue and employment data for CT&E are for 1997. Revenue and employment for SL are for 1996.

bAt current exchange rate (1.44 CHF/$).

Source: Information Access Company. 1998. Business Index [computer file]. Foster City, CA: Information Access

Corporation.

Société Générale de Surveillance Holding S.A. 1988. 1997 Annual Report. Geneva: Société Générale de

Surveillance S.A.

Figure C-2. Location of Independent Coal Testing Laboratories in the U.S.

Most of the laboratories owned by CT&E and SL are located either in coal-producing states or at main ports for imported

and exported coal.

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Location of Independent Testing Laboratories in the U.S. By State

6 to 13 (4) 4 to 6 (2) 3 to 4 (3)

2 to 3 (5) 1 to 2 (12) 0 (24)

Source: Commercial Testing & Engineering Company. 1998. “Sampling Services.” As obtained on December 2, 1998.

<http://www.comteco.com/sampleserv.htm>.

Standard Laboratories (SL). 1998. “Contract Laboratory Services—Standard Labs—Coal Test.” As obtained on

December 2, 1998. <http://www.coaltest.com/CONTLABS.htm>.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-10

Morehead City, Richmond, Baltimore, and New York, among

others. Other CT&E coastal lab cities include Charleston, Tampa,

Toledo, Tukwila (Seattle), Mobile, and Deer Park (Houston).

These companies also operate contract test laboratories on-site for

the mining industry. SL operates 30 such laboratories in the U.S.

and abroad (SL, 1998). When mines have on-site laboratories, it is

usually to test the coal for their coal preparation plants. Utilities

may have in-house laboratories to test sulfur, heating value,

moisture, and ash to ensure proper equipment operations,

regulatory compliance, and/or blending operations.

Oil companies routinely operate their own laboratories that

conduct product testing, including sulfur content testing, on

petroleum products. Unlike the coal industry, the oil industry is

more vertically integrated, with companies owning exploration

firms, pipelines, refineries, and testing laboratories. However,

independent testing laboratories for petroleum products are

becoming more important. Table C-4 shows the primary

independent petroleum testing laboratories in the U.S. Functioning

similarly to coal laboratories, independent testing laboratories

specializing in oil testing conduct tests on petroleum products and

waste oils for contractual purposes and as a part of larger

consulting projects. Firms providing petroleum testing services are

concentrated in states with large refinery capacity, such as Texas,

New Jersey, Oklahoma, and California.

C.1.2 Fossil Fuel Extraction and Processing

The combustion of fossil fuels supplies the majority of energy used

by the residential, commercial, and industrial sectors. As shown in

Figure C-3, in 1997 fossil fuels, including coal, petroleum products,

and natural gas, supplied 85 percent of U.S. energy consumption.

The U.S. is a net importer of energy products, with petroleum

products being the largest energy import. Coal is the largest source

of domestic energy production, accounting for 32 percent of

domestic Btu production.

Table C-5 provides energy consumption by sector. After processing

and refining, approximately two-thirds of fossil fuels are used

directly to produce heat and work. The remainder is used by

power plants to generate electricity that is subsequently used to

generate heat and work.
Appendix C — Profiles of Affected Industries

C-11

Table C-4. Sales and Employment of Petroleum Testing Laboratories

The 24 companies listed below test for sulfur in petroleum products.

Company

Company Revenue

($million) Employmenta

Alpha Analytical Labs., Inc. 0.75 12

American Interplex Corp. 4a NA

American Testing and Research, Inc. 1.75 19

Analysts, Inc. 15a NA

Analytical Service Consultants 0.3 NA

Aspen Research Corp. 15 120

Atlantic Petroleum Services, Inc. 1.75 20

Bennett Testing Service, Inc. 1 7

Camin Cargo Control, Inc. 5.75 120

Conam Inspection Inc. 43.1a 725

Core Laboratories (Saybolt, Inc.) 92.3b NA

Dallas Laboratories, Inc. 0.3 5

Harris Testing Laboratories, Inc. 0.3 7

Hydrocarbon Technologies Analytical Lab, Inc. 0.75 7

Inspectorate America Corp. 60b 600

Intertek Testing Services 85b 800

King Laboratories, Inc. 0.75 7

Martel Laboratories JDS, Inc. 3.75 40

Oil Science Laboratory 0.3 1

Oiltest, Inc. 2.5 51

Paragon Laboratories, Inc. 0.75 9

Quanterra Incorporated 41.7b 800

Saybolt Inc. 35 NA

SGS Control Services, Inc. (NA) 61.5b 720

aInformation Access Company. 1998. Business Index [computer file]. Foster City, CA: Information Access

Corporation.

bDun & Bradstreet, 1999. D&B Million Dollar Directory: America’s Leading Public and Private Companies.

Bethlehem, PA: Dun & Bradstreet, Inc.

Source: American Society for Testing and Measurement. 1999. 1999 Directory of Testing Laboratories.

<http://www.astm.org/labs/>. As obtained on February 16, 1999.

Company Data Source: American Business Information, Inc. 1998. The American Business Disk [computer file].

Omaha, NE: American Business Information.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-12

Figure C-3. Energy Flow, 1997 (quadrillion Btu)

Fossil fuels supply about 85 percent of U.S. energy consumption.

Total

Consumption

94.21

Total

Supply

98.78

Exported Energy

Coal 4.57

2.19

Other

2.38

Coal

23.17

Natural Gas

19.47

Crude Oil

13.57

NGPL 2.54

Nuclear 6.69

Renewables 6.93

Crude Oil

and Products

21.22

Other

3.74 Adjustments

1.50

Fossil

Fuels

80.36

Renewables 7.14

Domestic

Production

72.32

Industrial

35.67

Transportation

24.81

Residential and

Commercial

33.72

Coal

21.44

Natural Gas

22.59

Petroleum

36.31

Nuclear 6.69 Imported

Energy 24.96

Fossil

Fuels

58.75

b

c

a

d

e

f

h

i

j

c

k

aIncludes lease condensate.

bNatural gas plant liquids.

cBiofuels, conventional hydroelectric power, geothermal energy, solar energy, and wind energy.

dIncludes –0.04 quadrillion Btu hydroelectric pumped storage.

eNatural gas, coal, coal coke, and electricity.

f

Stock changes, losses, gains, miscellaneous blending components, and unaccounted for supply.

gCrude oil, petroleum products, natural gas, electricity, and coal coke.

hIncludes supplemental gaseous fuels.

i

Petroleum products, including natural gas, plant liquids, and crude oil consumed directly as fuel.

j

Includes 0.02 quadrillion Btu coal coke imports.

kIncludes, in quadrillion Btu, 0.16 net imported electricity from nonrenewable sources; -0.04 hydroelectric pumped

storage; and –0.10 ethanol blended into motor gasoline, which is accounted for in both fossil fuels and renewables.

Notes: Data are preliminary. Totals may not equal sum of components due to independent rounding.

Source: U.S. Department of Energy, Energy Information Administration. 1998a. Annual Energy Review 1997.

DOE/EIA-0384(97). Washington, DC: Department of Energy. Tables 1.1, 1.2, 1.3, 1.4, and 2.1.
Appendix C — Profiles of Affected Industries

C-13

Table C-5. End-Use Energy Consumption, 1996 (quadrillion Btu)

Energy consumption is roughly equally divided among residential and commercial, industrial, and transportation uses.

Sector Gas Coal

Petroleum

Products Electricitya

Other (Coke, Breeze,

Biofuels, Net Steam,

and Raw Materials) Lossesb Total

Residential and

Commercial

8.63 0.14 2.18 7.04 0.72 14.98 33.69

Industrial 10.39 2.42 9.07 3.52 2.63 7.48 35.51

Transportation — — 23.89 — 1.00 — 24.89

Total 19.02 2.56 35.14 10.56 4.35 22.46 94.09

aElectricity generation: 50.5 percent coal, 15.3 percent gas, 1.9 percent oil, and 32.3 percent nonfossil fuel (nuclear,

hydroelectric, and renewables).

bTotal losses are calculated as the sum of energy consumed at electric utilities to generate electricity, utility purchases of

electricity from nonutility power producers, and imported electricity, minus exported electricity and electricity

consumed by end users. Total losses are allocated to the end-use sectors in proportion to each sector’s share of total

electricity use.

Source: U.S. Department of Energy, Energy Information Administration. 1998a. Annual Energy Review, 1997.

Washington, DC: Department of Energy.

The industries accounting for the majority of fossil fuel combustion

are electrical power, petroleum, iron and steel, and trucking. As

shown in Table C-6, power plants use approximately 90 percent of

coal to generate electricity. The trucking industry consumes

approximately 65 percent of all petroleum products used in the

U.S. in the form of diesel fuel.4

National trends in coal consumption are an environmental concern

because the combustion of coal is a major source of sulfur released

to air. Table C-7 shows the trend of coal consumption from 1992

to 1997. The consumption of coal by electric utilities increased

from 1992 to 1997. However, coal consumption by electric

utilities is expected to decrease as new gas-fired generation units

are bought online and older coal units are retired.

Coal Industry

The U.S. coal industry produces and distributes 1.1. billion short

tons of coal per year. The industry consists of a few very large

companies that produce more than 5 percent of total coal

production and many mid-size and small companies. Information

about the sulfur content of coal is very important to this industry

 4The trucking industry accounts for approximately 78 percent of freight bills, and

fuel expenditures represent a large share of the trucking industry’s expenditures.

The industries

accounting for the

majority of fossil

fuel combustion are

electrical power,

petroleum, iron and

steel, and trucking.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-14

Table C-6. Fossil Fuel Combustion by Industry and Sector

Approximately 90 percent of coal is used by power plants to generate electricity.

Industry

Coal

(thousand short

tons, 1996)

Coal

(%)

Oil

(thousand

barrels, 1996)a

Oil

(%)

Natural Gas

(thousand cubic

feet, 1995)

Natural Gas

(%)

Electricity

Generation

874,681 88.9% 116,800 1.75% 3.2 16.2%

Iron and Steel

(and Coke)

31,706 3.2% 6,680b 0.10% 0.5a 2.5%

Petroleum

Refining

— — 12,050b 0.18% 0.7a 3.5%

Industrial

Combustion

70,941 7.2% 1,757,870 26.30% 7.4 37.6%

Transportation — — 4,372,700 65.42% 0 0.00%

Commercial and

Other

6,006 0.6% 3.0 15.2%

Residential 0 0.0%

427,050 6.39%

4.9 24.9%

Total 983,334 100% 6,683,150 100% 19.7 100%

aAll liquid fossil fuels, including fuel oils, diesel fuel, and gasoline.

b1994 amounts.

Sources: Coal data from U.S. Department of Energy, Energy Information Administration. 1998a. Annual Energy

Review, 1997. Washington, DC: Department of Energy.

National Mining Association. “Coal Statistics, 1992-1997.” <http://www.nma.org/coalstats.html>. As obtained on

November 18, 1998.

U.S. Department of Energy, Energy Information Administration. 1998a. Annual Energy Review, 1997. Washington,

DC: Department of Energy.

Table C-7. Coal Consumption, 1992 to 1997 (thousand short tons)

The consumption of coal by electric utilities has increased since 1992 but is expected to decrease in the near future.

1992 1993 1994 1995 1996 1997

Total Consumption 892,421 925,944 930,201 940,880 983,334 1,007,813

Electric Utilities 779,830 813,508 817,270 829,007 874,681 907,662

Coking 32,366 31,323 31,740 33,011 31,706 29,443

Other Industrial 74,042 74,892 75,179 73,055 70,941 70,702

Residential/Commercial 6,153 6,221 6,013 5,807 6,006 6,006

Source: National Mining Association. “Coal Statistics, 1992-1997.” <http://www.nma.org/coalstats.html>. As obtained

on November 18, 1998.
Appendix C — Profiles of Affected Industries

C-15

because the price of coal is a function of its sulfur content among

other attributes. Removing sulfur from coal is expensive, and the

sulfur content of coal determines whether an electric utility plant

that burns it can meet its regulatory emissions requirements for SO2.

Characteristics of Coal Supply. The U.S. Department of Energy’s

Energy Information Administration (EIA) estimates U.S. recoverable

reserves of coal to be over 270 billion short tons of varying sulfur

content. U.S. annual coal production has been increasing steadily

since the mid-1990s despite a 34 percent drop in the number of

mines. Table C-8 presents selected coal supply statistics for 1992

to 1997. Between 1992 and 1997 coal production increased more

than 9 percent to nearly 1.1 billion short tons. Western coal, which

is generally lowest in sulfur content, accounted for most of the

growth, with a 30 percent increase in production. Cost-cutting

measures and the abandonment of small mines brought the number

of mines in the U.S. down from 2,746 in 1992 to 1,810 in 1997.

Table C-8. Selected Coal Supply Statistics, 1992 to 1997

U.S. coal production increased by 9 percent during the mid-1990s despite a 34 percent drop in the number of mines.

1992 1993 1994 1995 1996 1997

Production (thousand

short tons)

997,545 945,424 1,033,504 1,032,974 1,063,856 1,089,932

Appalachian 456,565 409,718 445,370 434,861 451,868 464,737

Interior 195,659 167,174 179,858 168,526 172,848 172,290

Western 345,321 368,532 408,276 429,587 439,140 451,592

Value of Production at

Mine ($1,000)

$20,978,371 $18,766,666 $20,060,312 $19,450,900 $19,681,336 $19,801,979

Price Indicators

(avg. $/short ton)

Value at Mines $21.03 $19.85 $19.41 $18.83 $18.50 $18.19

Cost at Electric

Utility

$29.36 $28.58 $28.03 $27.01 $26.45 $26.16

Number of Mines 2,746 2,475 2,354 2,104 1,903 1,810

Underground 1,354 1,196 1,143 977 885 810

Surface 1,392 1,279 1,211 1,127 1,018 1,000

Source: U.S. Department of Energy, Energy Information Administration. 1998f. Coal Industry Annual, 1997.

Washington, DC: U.S. Department of Energy.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-16

The composition of coal varies greatly across fields. The key

properties of coal are its relative levels of carbon, hydrogen,

moisture content, heating value, and sulfur. The heating value of a

coal determines its “rank.” The rank of a particular coal is

determined largely by the fixed (or nonvolatile) carbon content.

Coals are ranked as follows from lowest to highest: lignite,

subbituminous, bituminous, and anthracite.

Other characteristics of coal, aside from heating value, also vary by

rank. Tables C-9 and C-10 summarize some of the key

characteristics of coal of different rankings. The value of coal is

primarily a function of its Btu content and moisture content.

However, sulfur content also influences the value of coal. Coal

contains up to 10 percent sulfur (by weight), which is released during

burning and oxidizes to SO2 or sulfate (SO4) in the atmosphere.

Table C-9. Composition and Heating Value of “As-Received” Coals

Anthracite and bituminous coals have the highest commercial value because of their high heating value and low

moisture content.

Composition (weight percentage)

Rank Moisture Volatile Matter Fixed Carbon Ash

Heating Value

(Btu/lb)

Anthracite 3-6 4-12 75-85 4-15 12,000-13,500

Bituminous 2-15 15-45 50-70 4-18 12,000-14,500

Subbituminous 10-25 30-45 31-55 3-12 8,000-11,000

Lignite 35-45 22-32 25-30 4-15 6,000-7,500

Source: Glasstone, Samuel. 1980. “Energy Deskbook.” National Technical Information Services, U.S. Department of

Commerce. DE82013966 (DOE/IR/05114-1).

Table C-10. Chemical Composition of Coals by Type (Moisture and Ash Free)

The sulfur content of coal ranges from 0.2 to 6 weight percent.

Weight Percentage

Rank Carbon Hydrogen Oxygen Nitrogen Sulfur

Anthracite 75-85 1.5-3.5 5.5-9 0.5-1.0 0.5-2.5

Bituminous 65-80 4.5-6.0 4.5-10 0.5-2.5 0.5-6.0

Subbituminous 57-69 5.5-6.5 15-30 0.8-1.5 0.2-2.0

Lignite 35-45 6.0-7.5 38-48 0.5-1.0 0.3-3.0

Source: Glasstone, Samuel. 1980. “Energy Deskbook.” National Technical Information Services, U.S. Department of

Commerce. DE82013966 (DOE/IR/05114-1).
Appendix C — Profiles of Affected Industries

C-17

Coal is generally classified into four sulfur categories: compliance,

low sulfur, medium sulfur, and high sulfur. Compliance coal has

the lowest sulfur content of 0.6 pounds per million Btus or less. It

naturally falls within federal emissions regulations and therefore

requires less cleaning before combustion. Low-sulfur coal has

between 0.61 and 1.25 pounds of sulfur per million Btus, medium

sulfur coal between 1.26 and 1.67 pounds per million Btus, and

high-sulfur coal more than 1.67 pounds per million Btus.

Coal’s sulfur content varies by the location from which it is mined.

Generally, western coal (from Colorado, North Dakota, and

Wyoming, for example) is lowest in sulfur; Appalachian coal (from

Pennsylvania, West Virginia, and Kentucky, for example) is either

low or medium sulfur; and interior coal (from Indiana, Illinois,

Ohio, for example) is medium and high sulfur.

Many variables affect the price of coal. The price a utility pays per

short ton of coal is a function of quantity purchased, heating value,

sulfur and ash content, distance from the mine, and the supplier’s

costs. Coal from surface mines is less expensive than coal from

underground mines because surface mines operate using less

capital and labor, all other things held equal. For a utility, the

prices paid for coals of varying sulfur content may differ

significantly precisely because so many factors affect prices (see

Table C-11). A utility may pay a higher price for higher-sulfur

content coal because that coal has a greater healthy value than a

lower-sulfur content coal. All other things held equal, however,

high-sulfur coal is less expensive than low-sulfur coal.

Coal Industry Structure. The coal industry consists of a few large

companies and many smaller companies. In 1997, the U.S. had

over 1,800 coal mines employing about 83,000 people (EIA, 1997).

Table C-12 lists the top 40 coal producers in the U.S in 1996. The

largest coal producer, Peabody Holding Co., Inc., produces

13.4 percent of total U.S. coal production. The top four companies

generate about 33 percent of total production; the top ten

companies produce about 51 percent, and the top 20 produce

about 66 percent (EIA, 1997). Many companies that own coal

mines are engaged primarily in another industry that requires a

large quantity of coal. For example, many power companies

produce coal, as do Aluminum Company of America and General

Dynamics Corporation.

Of the three primary types

of fossil fuels, coal has the

highest sulfur content by

percent weight and heat

content. It contains up to

10 percent sulfur (by

weight).
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-18

Table C-11. Average Delivered Cost of Coal by Sulfur Content and Region for Electric Utilities,

1997 ($ per short ton)

The price a utility pays per short ton is a function of quantity purchased, sulfur and ash content, distance from mine, and

the supplier’s costs.

Sulfur Content

Region Average

0.5% or

Less

More than

0.5% up

to 1.0%

More than

1.0% up

to 1.5%

More than

1.5% up

to 2.0%

More than

2.0% up

to 3.0%

More

than

3.0%

New England 43.67 50.10 43.25 43.74 43.36 40.44 —

Middle Atlantic 34.39 16.93 39.56 36.40 33.78 32.21 35.94

East North Central 27.68 23.54 33.45 30.30 29.82 25.80 29.26

West North Central 15.39 15.71 13.48 18.04 30.99 24.69 28.36

South Atlantic 36.34 26.83 38.58 37.58 33.21 37.52 27.62

East South Central 28.70 22.74 37.46 29.76 32.03 25.65 21.27

West South Central 19.69 23.12 13.58 12.42 9.49 26.32 14.10

Mountain 21.52 21.21 21.79 15.83 ———

Pacific Contiguous 25.19 21.11 26.33 ————

Pacific Noncontiguous ———————

Total 26.16 21.18 29.16 28.86 30.57 28.53 27.35

Note: Figures may not add to total because of independent rounding.

Source: U.S. Department of Energy, Energy Information Administration. 1998b. Cost and Quality of Fuels for Electric

Utility Plants 1997 Tables. Washington, DC: U.S. Department of Energy.

Coal Processing Technology. Coal processing entails the mining,

cleaning, and distribution of coal from underground and surface

mines. Figure C-4 provides an overview of activities, inputs, and

outputs of the coal processing industry.

Coal is extracted from two categories of mines: underground and

surface mines. Underground coal mining entails cutting a slot,

known as a kerf, at the bottom of a face; drilling holes in the face

for explosives or compressed air; blasting the coal; and loading and

hauling it out of the working area to a conveyor belt or mine cars.

(Pennsylvania Department of Environmental Protection, 1999).

Surface mining refers to the removal of dirt and rock on top of a

coal seam so that it can be excavated, placed on conveyors, and

sent to preparation plants. Strip mining is the most popular surface

mining method in the U.S.
Appendix C — Profiles of Affected Industries

C-19

Table C-12. Top Forty U.S. Coal Producers, 1996

While the largest coal producer controls a large percentage of the market, the coal market has many mid-size and small

producers.

Company Name

Production

(thousand short tons)

Percentage of

Total

Production

Cumulative

Percentage

Peabody Holding Co., Inc. 142,811 13.4 13.4

Cyprus AMAX Minerals Co. 74,738 7.0 20.4

Consol Energy Inc. 70,072 6.6 27.0

Kennecott Energy Co. 62,527 5.9 32.9

ARCO Coal Co. 51,013 4.8 37.7

Kerr-McGee Coal Corp. 31,350 2.9 40.6

Zeigler Coal Holding Co. 31,001 2.9 43.5

Marrowbone Development Co. 29,239 2.7 46.2

Texas Utilities Co. 28,214 2.6 48.8

A.T. Massey Coal Co. 27,327 2.6 51.4

North American Coal Corp. 26,284 2.5 53.9

Arch Mineral Corp. 30,153 1.9 55.8

Montana Power Co. 19,623 1.8 57.6

Ashland Coal Inc. 16,091 1.5 59.1

Marigold Land Co. 14,731 1.4 60.5

Pittston Coal Group 13,281 1.2 61.7

BHP Utah Minerals 13,228 1.2 62.9

Pittsburg & Midway Coal Mining Co. 19,246 1.2 64.1

Mapco Coal Inc. 12,844 1.2 65.3

Kiewit Coal Properties, Inc. 9,863 0.9 66.1

Costain Coal Inc. 9,342 0.9 67.0

The Coastal Corp. 8,932 0.8 67.8

AEP Service Corp. 8,652 0.8 68.6

Jamer River Coal Co. 8,025 0.8 69.4

Andalex Resources Inc. 7,613 0.7 70.1

Drummond Company Inc. 7,342 0.7 70.8

Rochester & Pittsburgh Coal Co. 7,315 0.7 71.5

Jim Walter Resources Inc. 7,313 0.7 72.2

U.S. Steele Mining Co., Inc. 7,169 0.7 72.9

Black Beauty Coal Co. 6,628 0.6 73.5

Teco Coal Corp. 6,615 0.6 74.1

Aluminum Company of America 8,379 0.5 74.6

Westmoreland Resources Inc. 5,111 0.5 75.1

General Dynamics Corp. 4,741 0.4 75.5

Ohio Valley Resources Inc. 4,538 0.4 75.9

Minnesota Power & Light 4,199 0.4 76.3

Hanson PLC 4,132 0.4 76.7

Lee Ranch Coal Co. 3,828 0.4 77.1

Exxon Corp. 3,689 0.3 77.4

Sun Co., Inc. 3,554 0.3 77.7

Source: U.S. Department of Energy, Energy Information Administration. 1997. Coal Industry Annual, 1996.

Washington, DC: U.S. Department of Energy.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-20

Figure C-4. Coal Processing

Coal preparation and cleaning are used to remove sulfur and other impurities.

Coal

Extraction

Coal

Preparation

and Cleaning

Coal

Transportation

Natural

Resources

Coal

Delivered to

Industry for

Combustion

Impurities and

Residual Coal

Fossil Fuels

Crushing and

Drying

On-site coal preparation plants make coal more valuable through

size reduction, desulfurization, and removal of moisture and

inorganic impurities. Nearly 50 percent of the coal mined in the

U.S. passes through coal preparation plants; east of the Mississippi

River this number increases to 80 percent (Fonseca, 1995). Coal

preparations, which “clean” coal by removing impurities, may

account for 5 to 15 percent of the cost of coal production (Horton

and Bloom, 1993).

Coal preparation plants remove coal mechanically by taking

advantage of differences between the impurities and the coal’s

density. Water is used to fluidize a bed of crushed coal and its

contaminants. As the lighter coal particles float to the top, the

impurities are separated. The coal is then skimmed off the top of

the bed and dried using a combination of hot gases. Coal is also

blended to meet customer specifications. For example, high- and

low-sulfur coal may be mixed together as part of the preparation

and cleaning process to ensure the sulfur content of the delivered

coal meets sulfur levels specified in contracts.

Petroleum Refining

The U.S. petroleum industry supplies over 6 billion barrels of

petroleum products per year. The industry is dominated by a small
Appendix C — Profiles of Affected Industries

C-21

number of large, vertically integrated companies. This structure is

driven by the large capital costs associated with the petroleum

refining technology. Sulfur information allows refineries to control

the sulfur content of output streams and emissions. Both are

required for regulatory compliance.

Characteristics of Petroleum Supply. The value of crude oil is a

function of its elemental composition, which determines the type

and grade of the final product it can be used to produce. The

hydrocarbons present in petroleum release a significant amount of

heat upon combustion and are the major determinant of

petroleum’s heating value (measured in Btu/gal or Btu/barrel).

Table C-13 contains the elemental composition ranges of typical

crude oils.

Element Weight Percentage

Carbon 82 to 87

Hydrogen 11 to 15

Nitrogen Up to about 1

Oxygen Up to about 2

Sulfur Up to about 6

Metals Up to about 0.05

Source: Glasstone, Samuel. 1980. “Energy Deskbook.” National Technical

Information Services, U.S. Department of Commerce. DE82013966

(DOE/IR/05114-1).

Petroleum is commonly classified according to its specific gravity

or by its API gravity. 5 These are both measures of density. A lower

specific gravity is equivalent to a higher value on the API scale.

Most crude petroleum oils have specific gravities in the range of

0.80 to 0.95, which corresponds to 45 to 17 degree API. Lower

specific gravity (higher API) is typically linked to a higher market

value.

 5API gravity is an arbitrary scale expressing the gravity or density of liquid

petroleum products. The higher the API gravity, the lighter the compound.

Light crudes generally exceed 38 degrees API and heavy crudes are commonly

labeled as crudes with API gravity of 22 or below. Intermediate crudes fall into

the range of 22 to 38 API gravity.

Table C-13. Approximate

Elemental Composition

Ranges of Most

Petroleum Oils

Sulfur content in crude oil

typically ranges from 1 to

2 percent. However, some

crude oil has up to 6 percent

sulfur.

The sulfur found in crude

petroleum is removed from

refined products by a

process known as

hydrodesulfurization. The

resulting hydrogen sulfide

must then be removed from

stack gasses to prevent its

release to the environment.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-22

The sulfur content is an important characteristic of crude oil. The

composition of crude oil varies greatly from field to field

throughout the world. For example, Alaskan crude typically has a

low sulfur content (sweet), and South American crude typically has

a high sulfur content (sour). Crude oil with a high sulfur content is

more expensive to refine because it is difficult to separate sulfur

compounds from pure hydrogen/carbon compounds (Leffler, 1985).

As shown in Table C-14 the main determinants of crude oil prices

are sulfur content (sweet versus sour) and API gravity (light versus

heavy). High API gravity, or light crude, is more valuable because

it is used in more high-end products when distilled and has fewer

impurities.

Table C-14. Prices and Sulfur Content for Selected Crude Streams

Crude oil prices depend on both API and sulfur content.

Crude Stream

Price (average 1997)

($/barrel)

Sulfur

(weight percentage) API

Nigrerian Bonny Light 21.21 0.13 35.4

UK Brent 20.85 0.35 37.4

Gaben Rabi-Kouanga 20.07 0.05 34.3

Mexican Olmeca 20.02 0.72 39.1

Angolan Cabinda 19.48 0.17 32.0

West Texas Intermediate 19.27 0.3 39.1

Venezuelan Furrial 18.59 1.16 27.4

Saudi Arabian Light 18.14 1.1 38.4

West Texas Sour 17.77 1.65 34.1

Saudi Arabian Medium 17.11 2.5 30.1

Canadian Bow River Heavy 16.46 2.1 24.7

California Wilmington 16.44 1.7 16.9

Mexican Mayan 15.58 3.43 22.2

Alaskan North Slope 14.84 1.0 27.0

Sources: U.S. Department of Energy, Energy Information Administration. Petroleum Marketing Monthly. 1998e.

Haverly/Chevron Assay Library. <http://www.haverly.com.chevfram.htm>.

Table C-15 lists the net production of petroleum products in 1997.

Almost 90 percent of the products generated by petroleum refining

are used as fuels (gasoline, diesel and distillate fuel oil, liquefied

petroleum gas, jet fuel, residual fuel oil, kerosene, and coke). The
Appendix C — Profiles of Affected Industries

C-23

Commodity

U.S. Annual Production

(thousand barrels)

Liquefied Refinery Gases 252,168

Finished Motor Gasoline 2,826,051

Finished Aviation Gasoline 7,248

Jet Fuel 567,295

Kerosene 23,887

Distillate Fuel Oil 1,238,041

0.05 percent sulfur and under 789,287

Greater than 0.05 percent sulfur 448,754

Residual Fuel Oil 258,290

Less than 0.31 percent sulfur 26,090

0.31 to 1.00 percent sulfur 75,334

Greater than 1.00 percent sulfur 156,866

Naphtha for Petrochemical Feedstock Use 83,569

Other Oils for Petrochemical Feedstock Use 79,539

Special Naphthas 19,191

Lubricants 8,372

Waxes 251,619

Petroleum Coke 84,294

Asphalt and Road Oil 177,019

Still Gas 241,184

Miscellaneous Products 17,501

Total 6,116,870

Source: U.S. Department of Energy, Energy Information Administration. 1998c.

Petroleum Supply Annual, Volume 1. Washington, DC: U.S. Department of

Energy.

remaining 10 percent include finished nonfuel products (solvents,

lubricating oils, greases, petroleum wax, petroleum jelly, asphalt,

and coke) and chemical industry feedstocks (naphtha, ethane,

propane, butane, ethylene, propylene, butylenes, butadiene,

benzene, toluene, and xylene). Chemical feedstocks are used as a

primary input to a number of products, including fertilizers,

pesticides, paints, waxes, thinners, solvents, cleaning fluids,

detergents, refrigerants, antifreeze, resins, sealants, insulations,

latex, rubber compounds, and plastics.

Table C-15. Production

of Petroleum Products

Most refinery products are used

as fuels such as motor gasoline

and distillate fuel oil.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-24

Petroleum Industry Structure. In the U.S., most crude oil

distillation capacity is owned by large integrated companies (EPA,

1995). Until recently, the petroleum refining industry was

categorized as oligopolistic because it was dominated by the top

four firms in the industry. Over 30 percent of the market share was

attributable to these four firms: Exxon Corp., Mobil Corp., El du

Pont de Nemours and Co., and Texaco Inc. However, the market

concentration ratios for these top firms have been marginally

decreasing in recent years (EPA, 1995). The large companies

generally have the greatest control over residual fuel sales, while

distillate sales have been decreasing for these companies in recent

years.

Petroleum Processing Technology. Petroleum refining is the

physical, thermal, and chemical separation of crude oil into its

major distillation fractions, which are then further processed

through a series of separation and conversion steps into finished

petroleum products and chemical industry feedstocks. The primary

input to the refining process is crude oil, which accounts for

92 percent of input feed.

Four primary categories of operations are implemented at a

petroleum refinery:

Z the desalting process;

Z separation processes, which are used to divide crude oil

into its major components;

Z conversion processes, which involve restructuring

petroleum molecules to convert crude oil components into

gasolines and other light fractions; and

Z petroleum treating processes, which serve the purpose of

stabilizing and upgrading petroleum products by separating

them from less desirable products and removing undesirable

elements such as sulfur (EPA, 1995).

Sulfur is removed from petroleum products by reacting it with

hydrogen gas in the presence of a catalyst at a moderately high

temperature and pressure. This process is referred to as

hydrodesulfurization or hydrofinishing. In addition to

desulfurization of final products, sulfur recovery for sale of

elemental sulfur is also conducted for refinery process off-gas

streams as part of emissions reduction activities. The sulfur is
Appendix C — Profiles of Affected Industries

C-25

converted to hydrogen sulfide, which is then absorbed through

desulfurization of stack gases.

Desulfurization of petroleum output streams can be very expensive.

As part of background research for the development of its new

sulfur content in gasoline regulations, EPA developed estimates of

the cost of removing sulfur from gasoline. As shown in Table C-16,

reducing the sulfur content of gasoline from its pre-Tier-2 levels

(about 330 ppm) to 40 ppm is about 1.6 cents per gallon.

Sulfur Level

EPA Estimate of Cost

per Gallon (cents)

API Estimate of Cost

per Gallon (cents)

150 ppm 0.7

100 ppm 1.1

40 ppm 1.6

30 ppm 1.7

2.3 to 2.6

Source: U.S. Environmental Protection Agency. April 1999. Draft RIA for Control

of Air Pollution from New Motor Vehicles: Tier 2 Motor Vehicle Emissions

Standards and Gasoline Sulfur Control Requirements.

The American Petroleum Institute (API) believes that EPA

underestimated the added cost of reducing the sulfur content of

gasoline below current levels. The trade association funded a series

of studies conducted by MathPro that estimated the cost to be 2.3

to 2.6 cents per gallon (Octane Week, 1999). Although API’s

estimates are listed in Table C-16, the economic estimates

presented in this study are based on the more conservative EPA

estimates of approximately 1 cent per gallon.

Maintaining specific sulfur levels in output streams and process offgas streams is difficult because of the varying content of sulfur in

crude oil. Accurate information about the sulfur content of the

crude oil and the output streams is essential to maintaining product

specifications and maximizing the efficiency of the processing

equipment.

Frequently, refineries specialize in crude streams with either high or

low sulfur content. Because desulfurization equipment is

expensive, a company’s high-sulfur crude refining will typically be

concentrated in a few large facilities to increase equipment

utilization and decrease costs. Large refineries are generally more

Table C-16. Cost of

Reducing the Sulfur

Content of Gasoline from

its Current Level (about

350 ppm) to Alternative

Levels

As the sulfur content of gasoline

is reduced, the incremental cost

of removing each additional

ppm of sulfur increases.

The varying content of

sulfur in crude oil makes it

difficult to maintain

specific sulfur levels in

output streams.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-26

flexible compared to small refineries in their ability to substitute

one type of crude oil input for another.

Coke Industry

Coke is metallurgical coal that has been baked into a charcoal-like

substance. This substance burns more evenly and at a higher

temperature compared to coal. Coke is primarily used as an input

for producing steel in blast furnaces at integrated iron and steel

mills (i.e., furnace coke) and as an input for gray, ductile, and

malleable iron castings in cupolas at iron foundries (i.e., foundry

coke). Therefore, the demand for coke is a derived demand that is

largely dependent on production of steel and iron castings.

The sulfur content of coke affects the production process and the

sulfur content of iron and steel and that industry’s regulatory

compliance. Low-sulfur iron and steel is more valuable than highsulfur iron and steel. Furthermore, the lower the sulfur content of

coke, the lower the emissions of sulfur compounds during the iron

and steel production process. Coke’s sulfur content is primarily

determined by the sulfur content of the coals used to produce it.

Alternatively, additional steps can be added to the production

process to reduce the amount of sulfur in coke. However, these

processes add to the cost of production; thus, facilities generally

prefer to use lower-sulfur coals to avoid additional desulfurization

processes (Zaino and Brousseau, 1983).

Characteristics of the Coke Industry. The manufacture of coke is

included under Standard Industrial Classification (SIC) code 3312—

Blast Furnaces and Steel Mills. However, coke production is a

small fraction of this industry.

Table C-17 summarizes coke industry capacity and production by

type of producer and type of coke. There are two primary types of

coke producers: integrated producers and merchant producers.

Integrated producers, which manufacture about 79 percent of all

coke, are owned by steel companies. Merchant producers, which

manufacture the remaining 21 percent of coke, sell their product to

steel manufacturers.

In 1997, the coke industry produced about 20 million short tons of

coke. About 90 percent of that coke was furnace coke to be used

in blast furnaces for steel making. The remaining 10 percent was

The sulfur content of coke

affects the quality of iron

and steel, the cost of

production, and the cost of

environmental compliance.
Appendix C — Profiles of Affected Industries

C-27

Table C-17. Summary of Coke Operations at U.S. Companies, 1997

Most furnace coke is produced by integrated producers, while foundry coke is supplied by merchant producers.

Coke Production by Type (short tons/yr)

Company Name

Number

of Coke

Plants

Total Coke

Capacity

(short tons/yr) Furnace Foundry Other Total

Integrated Producers

Acme Metals Inc. 1 500,000 493,552 0 19,988 513,540

AK Steel Corp. 2 1,429,901 1,352,986 0 0 1,352,986

Bethlehem Steel Corp. 2 2,627,000 2,420,387 0 82,848 2,503,235

Geneva Steel Co. 1 800,000 700,002 0 16,320 716,322

HMK Enterprises Inc.a 1 500,000 521,000 0 0 521,000

LTV Corp. 2 1,164,000 1,133,406 0 0 1,133,406

National Steel Corp. 2 1,526,701 1,479,387 0 0 1,479,387

USX Corp. 2 7,823,045 6,667,594 0 0 6,667,594

WHX Corp.b 1 1,247,000 1,249,501 0 36,247 1,285,748

Total Integrated Producers 14 17,617,647 16,017,815 0 155,403 16,173,218

Merchant Producers

Aloe Holding Co.c 1 514,779 354,137 0 0 354,137

Citizens Gas and Coke 1 634,931 173,470 367,798 93,936 635,204

Drummond Co. Inc.d 1 699,967 25,806 727,720 0 753,526

Erie Coke Corp. 1 214,951 0 122,139 19,013 141,152

Koppers Industries Inc. 1 372,581 358,105 0 0 358,105

McWane Inc.e 1 162,039 0 142,872 0 142,872

New Boston Coke Corp. 1 346,126 317,777 0 0 317,777

Sun Co. Inc.f 2 1,949,000 649,000 0 0 649,000

Tonawanda Coke Corp. 1 268,964 207,234 136,225 63,822 407,281

Walter Industriesg 1 451,948 268,304 131,270 33,500 433,074

Total Merchant Producers 11 5,615,286 2,353,833 1,628,024 210,271 4,192,128

Total 25 23,232,933 18,371,648 1,628,024 365,674 20,365,346

aOwns Gulf States Steel, Inc.

bOwns Wheeling-Pittsburgh Corp.

cOwns Shenango Inc.

dOwns ABC Coke.

eOwns Empire Coke.

f

Owns Indiana Harbor Coke Co. and Jewell Coke and Coal Co.

gOwns Sloss Industries Corp.

Sources: U.S. Environmental Protection Agency. 1998c. Coke Industry Responses to Information Collection Request (ICR)

Survey. Database prepared for EPA’s Office of Air Quality Planning and Standards. Research Triangle Park, NC.

Association of Iron and Steel Engineers (AISE). 1998. “1998 Directory of Iron and Steel Plants: Volume 1 Plants and

Facilities.” Pittsburgh, PA: AISE.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-28

foundry coke to be used for making iron castings. About

89 percent of furnace coke was manufactured by integrated iron

and steel facilities.

Table C-17 lists the coke-producing companies in the U.S.

Nineteen companies own a total of 25 coke plants in the U.S. The

nine integrated producers own 14 coke plants, while the ten

merchant produces own 11 coke plants. Captive consumption

currently dominates the U.S. furnace coke market. Integrated

producers account for about 87 percent of all furnace coke. In

1997, six companies produced foundry coke in the U.S. The U.S.

foundry coke market is fairly concentrated, with two companies

currently accounting for two-thirds of U.S. production—Drummond

Co. Inc., with 45 percent, and Citizens Gas and Coke, with

22.6 percent. The remaining four merchant producers each

account for between 7.5 and 8.8 percent of the market.

Coke Manufacturing Process. Coke is produced by heating

pulverized coal at high temperatures in large ovens without oxygen

for 14 to 36 hours and then cooling it with a water spray.

Figure C-5 presents the inputs, production activity, major

emissions, and product outputs for the industry.

Figure C-5. Coke Production

Sulfur emissions occur during both the coking process and the quenching process.

Mixing and

Pulverizing

Coking

(Heating)

Process

Quenching

Process

High Sulfur

Coal

Sulfur

Emissions

Combustion of Fossil

Fuels for Process

Heat

Sulfur

Emissions

Coal

Dust

Water

Low Sulfur

Coal

Furnace and

Foundry

Processes

Coke
Appendix C — Profiles of Affected Industries

C-29

Metallurgical coal is delivered to coke manufacturing plants in

railroad cars or barges. It is then transferred to mixing bins where

the various types of coal are blended based on specific

characteristics of the coal such as fluidity, ash, and sulfur content.

Lankford et al. (1985) consider the selection of coals to be the

single most important factor in establishing coke quality. The best

coals are low in ash and sulfur content and produce a structurally

strong coke. Coal blending results in improved and more

consistent coke quality, which justifies the extra expense of mixing.

The coal is pulverized and fed into the oven. The coal in the coke

oven is heated at temperatures up to 2,000 oF for 14 to 36 hours.

When subjected to such a high degree of heat in the absence of air,

the chemical compounds making up coal are unstable and the

complex organic molecules break down to yield gases and a

relatively nonvolatile carbonaceous residue (i.e., coke). At the end

of the coking cycle, doors on each end of the oven are removed,

and the incandescent coke is pushed from the oven.

During what is known as the wet quenching process, the

incandescent coke is carried to a quench tower where it is cooled

to a temperature of 200 o to 500 oF by a system of stationary water

sprays and air dried in preparation for sizing. This quenching

prevents the coke from burning up in the air. The coke is then

screened to a uniform size, which also results in some small coke

fines (or breeze) that are recovered for use as a raw material input

to blast furnaces.

C.1.3 Fuel Combustion

As explained earlier in Appendix C, the primary uses of fossil fuels

in the U.S. are the production of power by electric utilities, the

production of steel, and the production of power by industrial

boilers. This section describes the structure of the electric power

industry and the steel industry. However, we do not address

industrial combustion. Because industrial boilers are used in all

major industrial sectors, it would be very difficult for us to

characterize this diverse set of industries.

Electricity Generation

Approximately 35 percent of all U.S. fossil fuel consumption

(measured in Btus) is used to generate electricity. Electricity

Coke production involves

three basic steps:

Z mixing and pulverizing

Z coking

Z quenching
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-30

generation in 1996 consumed 88.9 percent of coal, 1.7 percent of

oil, and 16.2 percent of natural gas used in the U.S. Because of its

dependence on coal as a fuel, electricity generation accounts for

65.9 percent of SO2 released into the atmosphere. The electric

generation industry is heavily regulated because it is one of the

primary sources of SO2 emissions in the U.S.

The electric utility industry relies heavily on sulfur content

information to determine fuel mix and other operating parameters

that affect its compliance with environmental regulations.

Furthermore, many power plants are designed to burn coal of a

specific sulfur content. Burning high-sulfur coal in these plants can

lead to boiler fouling and slagging, decreased generating efficiency,

and increased maintenance costs.

Characteristics of the Electricity Generation Industry. Electric

utilities produce 88 percent of electricity generated in the U.S.

Electric utilities are typically large publicly owned entities whose

primary function is to generate and distribute electricity. Nonutility

generators account for the remaining 12 percent of electricity

generation and are comprised mainly of independent power

producers and industrial facilities engaged in self-generation and

cogeneration. Cogeneration refers to the combined production of

electricity with another form of useful energy, such as process heat

or steam.

The electric utility industry is very dependent on fossil fuels,

especially coal. Fossil fuels account for over two-thirds of net

megawatthours (MWh) generated in the U.S. (EPA, 1998c). As

shown in Table C-18, nuclear, hydroelectric, renewable, and other

fuels account for the remaining net generation. Within the fossil

fuel category, coal is used as the main energy source to generate

electricity in the utility industry, and natural gas is the main energy

source for nonutility generators. Other fossil fuels used much less

frequently to generate electricity are petroleum coke, refinery gas,

coke oven gas, blast furnace gas, and liquefied petroleum gas.

Future trends are for natural gas to increase its share of both utility

and nonutility electricity generation because of rapid technology

improvements in combined-cycle gas turbine engines.
Appendix C — Profiles of Affected Industries

C-31

Table C-18. Net Generation by Energy Source, 1996

Although most new generating units built during the past few years are gas-fired units, coal units still account for over

half of electricity generation in the U.S.

Energy

Source

Utility Generators

(million kWh)

Nonutility Generatorsa

(million kWh)

Total

(million kWh)

Fossil Fuels

Coal 1,737,453 61,424 1,798,877

Natural Gas 262,730 213,359 476,089

Petroleum 67,346 14,951 82,297

Nuclear 674,729 — 674,729

Renewable

Hydroelectric 331,058 16,555 347,613

Geothermal 5,234 10,198 15,432

Biomass 1,967 57,997 59,964

Other 13 4,303 4,316

Other — 3,744 3,744

Total 3,080,530 382,531 3,463,061

aGross generation: Approximately 60 percent of electricity produced by nonutility generators is sold to electric utilities.

Source: U.S. Department of Energy, Energy Information Administration. 1998d. Electric Power Annual, Volumes I & 2.

Washington, DC: U.S. Department of Energy.

Electricity Generation Process. Figure C-6 shows an overview of

the electricity generation process using fossil fuel. Through

controlled combustion, the Btu potential in fossil fuels is converted

into either steam or hot air, which is then used to generate

electricity.

Several generation technologies are commonly used to produce

electricity, including boilers to fire steam turbines, gas turbines,

internal combustion engines, and combined-cycle generation.

Combined-cycle generation produces electricity by passing one

source of hot gas through two separate thermal cycles, thereby

increasing efficiency by reducing waste heat.

The sulfur content of the coal determines, in part, the extent of the

processing required prior to combustion. Coal can be cleaned and

prepared to reduce sulfur content. The cleaning of coal also

increases its fuel efficiency (effective Btu content). However,

cleaning coal is a costly process and is more efficiently conducted

at the mine by using gravity concentration, flotation, or dewatering

methods. Accurate sulfur information is used to determine the

amount of precleaning and postcleaning activities required to

comply with environmental regulations.

The sulfur content of coal

affects the performance of

electricity generating

equipment, the amount of

preprocessing required, and

the level of emissions

control required to achieve

compliance.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-32

Figure C-6. Electricity Generation Process

Sulfur emissions occur during coal preprocessing and fuel combustion.

Preprocessing

Dust Control

Equipment

Coal

SO2

Emissions

Combustion

Technology to Reduce

Emissions

Steam and

Hot Air

SO2

Emissions

Combustion

Oil

End

User

Distribution

Gas

Emissions

Control

Electricity

Generation

Most petroleum used for electricity generation is refined prior to

use and shipped to the generating plant by pipeline. The fuel oils

most commonly used for electricity generation include fuel oil

numbers 4, 5, and 6 (heavy oil).

Steel Industry

The U.S. iron and steel industry (including coke) consumes

approximately 3.2 percent of the U.S. coal supply. In addition, the

iron and steel industry accounts for 2.5 percent of natural gas and

0.1 percent of oil consumption (EIA, 1998a). Most coal is

converted into coke prior to use in the steel manufacturing process.

The steel industry uses sulfur information primarily to control

product quality and also to ensure environmental compliance.

There is an inverse relationship between sulfur levels and steel

quality. Low-sulfur steels (<0.010 percent sulfur) have greater

ductility and better impact properties than steels with high sulfur

content. Low-sulfur steels are demanded by vehicle manufacturers
Appendix C — Profiles of Affected Industries

C-33

and pipe manufacturers because of their impact and corrosion

resistance, which enhances the quality of end-use products (Zaino

and Brousseau, 1983).

Characteristics of the Steel Industry. The U.S. iron and steel

industry can be separated into three distinct types of producers:

integrated mills, nonintegrated or specialty mills, and mini-mills.

Integrated iron and steel producers are companies that produce iron

from iron ore in blast furnaces. The integrated producers in the

U.S. are listed in Table C-17. Their principal commercial activity is

the production and sale of carbon steel. Integrated producers use

furnace coke in blast furnaces and either produce coke on site or

purchase it from merchant coke producers. Nonintegrated or

specialty mills do not have the necessary equipment to produce

steel from basic raw materials; instead, they purchase these inputs

in a processed form (i.e., semi-finished products) to manufacture

steel products. Mini-mills use only electric arc furnaces (EAFs) to

melt scrap steel and other materials to make steel products.

From 1980 to 1990, integrated iron and steel production in the U.S.

decreased approximately 60 percent. This decline was due to slow

growth in demand for steel, markets lost to substitute materials,

increased foreign competition, and low productivity growth

resulting from older and less-efficient capital stock. However,

while the integrated producers were contracting, the mini-mills

were more than doubling their capacity and expanding into new

markets. As a whole, the U.S. steel industry experienced a

turnaround in 1993 with shipments at their highest level since

1981. This increase was due to the strong demand from the

automotive and construction industries and the weak dollar

(making imports more expensive). As of 1997, integrated producers

accounted for roughly 55 percent of U.S. steel production, with

20 plants operating at a total steel capacity of almost 6.2 million

short tons per year (AISI, 1998; EPA, 1998a).

In 1994, iron and steel facilities consumed 1,907 trillion Btus of

energy. The vast majority of this energy, 1,119 trillion Btus, was in

the form of coke and breeze. Natural gas and electricity supply

most of the industry’s remaining energy needs.

Manufacturing Process. Steel facilities manufacture steel by

melting, alloying, and molding pig iron and steel scrap. Figure C-7
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-34

Figure C-7. Integrated Iron and Steel Production

Sulfur emissions are generated during coke production and steel production.

Coke

Production

Iron

Production

Steel Production

Coal

SO2

Emissions

SO2

Emissions

Coke

Raw Materials

Coal Steel

Products

Slag and Other

Solid By-Products

Gas and

Electricity

Iron

Slag

presents the inputs, production activity, major emissions, and

product outputs for the industry.

Raw materials used in the production process include molten or pig

iron (iron that is allowed to cool and solidify), iron and steel scrap,

foundry returns, metal turnings, alloys, carbon additives, sand, sand

additives, binders, and fluxes. Fluxes are materials that are added

to collect impurities from the metal, such as carbon compounds.

The most widely used flux is lime; other fluxes include soda ash,

fluorspar, and calcium carbide. Iron is manufactured by combining

iron ore, coke, and flux and heating the mixture at high

temperatures.

The steel-making process generally consists of combining and

melting ingredients before pouring the liquid steel into molds to be

packed and cooled. Scrap metals are cleaned and degreased with

solvents prior to being mixed with pig iron. Typically the metals

are melted in large EAFs or basic oxygen furnaces. When the

melting process is complete, the molten metal is poured directly

into molds.
Appendix C — Profiles of Affected Industries

C-35

C.2 THE IMPORTANCE OF SULFUR IN FOSSIL

FUELS

This section describes the regulatory and technical issues that make

the sulfur content of fossil fuels important. The sulfur content of a

fuel is important for two reasons: because sulfur has a detrimental

effect on the environment and because sulfur content can affect the

performance of a product or process. For both reasons, the sulfur

content of fossil fuels affects its value; thus, information about sulfur

content is essential to trade and production.

C.2.1 Environmental Regulation of Sulfur in Fossil Fuels

Because some sulfur compounds have a detrimental effect on

human health, wildlife, agricultural productivity, and quality of life,

sulfur compound emissions from some sources and sulfur content

of some fuels are regulated by EPA and by state regulatory agencies.

These regulations have evolved over time and have become more

strict with respect to both sulfur content and sulfur compound

emissions. We expect that this trend will continue, as EPA requires

greater control over sulfur compound emissions and lower sulfur

content in fossil fuels.

The primary environmental concern is sulfur dioxide (SO2), which

is produced from the combustion of fuels that contain sulfur as an

impurity. Sulfur dioxide is directly harmful to health when inhaled

and indirectly harmful because it generates acid rain.

Table C-19 shows the share of SO2 emissions by fossil fuel type.

Because of coal’s chemical composition, typically containing 2 to

6 weight percent sulfur, the mining, processing, transportation, and

combustion of coal account for 80 percent of domestic fossil fuel

SO2 emissions. In contrast, the combustion of natural gas, which

has a much lower Btu-to-sulfur ratio, generates approximately

4 percent of total domestic SO2 emissions.

Table C-20 lists SO2 emissions for the major industries directly

affected by environmental regulation. Electricity generation,

through its high consumption of coal, is the major generator of SO2

emissions, accounting for about two-thirds of these emissions.

Industrial combustion, primarily in industrial boilers, accounts for

approximately 18 percent of SO2 emissions. Reductions in

Sulfur’s detrimental impact

on the environment has led

to regulations of the sulfur

content of fossil fuels and

the sulfur emissions of

facilities burning fossil

fuels. Because sulfur is

expensive to remove, these

regulations have resulted in

a price premium for lowsulfur-content fossil fuels.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-36

Fuel SO2 (%)

Coal 80.1

Oil 15.8

Natural Gas 4.1

Total 100

Source: U.S. Environmental Protection Agency, Office of Air Quality Planning and

Standards. December 1997b. National Air Pollution Emissions Trends, 1990-

1996. Research Triangle Park, NC: U.S. Environmental Protection Agency.

Industry SO2 SO2 (%)

Electricity Generation 12,604 65.9

Iron and Steel (coke) 151 0.8

Petroleum Refining 271 1.4

Petroleum Production 89 0.5

Industrial Combustion 3,399 17.8

Others 2,599 13.4

Total 19,113 100

Note: Totals may not sum due to independent rounding.

Source: U.S. Environmental Protection Agency, Office of Air Quality Planning and

Standards. December 1997b. National Air Pollution Emissions Trends, 1990-

1996. Research Triangle Park, NC: U.S. Environmental Protection Agency.

emissions from power generation and ferrous metals processing are

projected to reduce the total amount of SO2 emissions from coal

consumption over the next decade. The projected reduction is due,

in part, to expected reductions in the use of coal by electric utilities

as new gas-fired generation units are brought on line and older coal

units are retired.

Regulations that control the emissions of sulfur to the environment

fall under two broad types: sulfur content regulations and sulfur

emissions regulations. Both types of regulations are supported by

standards that control the way in which sulfur content and sulfur

emissions are tested.

Table C-19. Sulfur

Dioxide Emissions by

Fossil Fuel Type

(thousand short tons)

The mining, processing,

transportation, and combustion

of coal account for 80 percent

of domestic fossil fuel SO2

emissions.

Table C-20. Sulfur

Dioxide Emissions by

Industry, 1996 (thousand

short tons)

Electricity generation is

responsible for about two-thirds

of SO2 emissions.
Appendix C — Profiles of Affected Industries

C-37

Sulfur Content Regulations

The Clean Air Act of 1970 authorized EPA to regulate product

quality through specific formulations of gasoline and other fuels.

The main national programs currently regulating sulfur content in

fossil fuels are the National Highway Diesel Fuel Program and the

National Ambient Air Quality Standards (NAAQS). The highway

diesel fuel program required that the sulfur content of all highway

diesel fuel be reduced from 0.5 percent (5,000 ppm) to

0.05 percent (500 ppm) by October 1, 1993. California limits the

sulfur content of diesel fuel to between 300 and 500 ppm.

Reducing SO2 emissions from gasoline was one of the primary

goals included in the 1971 NAAQS. In addition, other provisions

of the Act limited the sulfur content in residual and distillate fuel

oils used by electric utilities and industrial plants.

New federal regulation promulgated under the Clean Air Act will

limit the sulfur content of gasoline by 2004. The federal legislation,

formally proposed in May 1999, is known as “Tier 2” Emissions

Standards for Vehicles. It is based on actions taken by California to

reduce motor vehicle emissions to improve air quality. Because

low sulfur content of gasoline supports advanced emissions control

technologies, California restricts the sulfur content of gasoline to no

more than 40 ppm or, alternatively, to a quarterly average of 30

ppm with a cap of 80 ppm (EPA, 1998b). Federal regulations to be

phased in by 2004 will set similar sulfur content levels for all

gasoline sold in the U.S. Current and emerging sulfur content

regulations are an indirect result of efforts to limit automobile

emissions of SO2 as well as other pollutants.

This legislation was prompted, in part, by tremendous progress in

technology to reduce emissions from gasoline-fueled vehicles. The

emissions performance of these low emissions vehicles (LEVs) is

very sensitive to the sulfur content of gasoline. Emissions control

technology is often designed to meet the vehicle emission standards

of California, which currently has the most stringent vehicle

emission standards in the world. The vehicles are also designed to

run on the low-sulfur content gasoline sold in California. While

gasoline in California averages less than 30 ppm and is limited to

no more than 80 ppm, gasoline in the U.S. outside of California

currently averages over 330 ppm and can reach levels as high as

1,000 ppm (EPA, 1998b). This high sulfur level can significantly

Currently, the sulfur

content of fuels used by

industry and EPA for

federal vehicle certification

can differ substantially from

gasoline actually sold

nationwide. Because the

emissions performance of

LEVs is sensitive to the

sulfur content of fossil

fuels, these vehicles do not

perform as well on the road

with high-sulfur fuels as

they do during testing.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-38

reduce catalyst performance and increase the emissions of these

vehicles. Low-sulfur gasoline is needed to enable the use of

advanced emissions control technologies.

For these reasons, there was increasing momentum toward federal

sulfur content regulation. In November 1997, the American

Automobile Manufacturers Association (AAMA) and the Association

of International Automobile Manufactures (AIAM) petitioned EPA to

establish a national, year-round limit on gasoline sulfur. Their

request echoed California’s sulfur content limits. In California, the

sulfur content of gasoline must not exceed 40 ppm on an annual

average of 30 ppm. In addition, an individual gallon of gasoline

must not exceed 80 ppm. This request was based not only on its

immediate impact on the industry’s ability to meet emissions

requirements, but also on its importance for accommodating the

newest generation of automobile catalysts for LEVs and other new

vehicle technologies.

The new Tier 2 emissions standards make California emissions the

national standard. Beginning in 2004, all cars and light trucks sold

in the U.S., including sport utility vehicles, minivans, and pickup

trucks, will be equipped with advanced emissions control

technologies. The impact of these technologies and low-sulfur

gasoline will allow vehicles to be 77 to 95 percent cleaner than

they are today (EPA, 1999).

Regulation of Sulfur Emissions

EPA regulates air emissions of SO2 from a variety of sources to

reduce adverse health and environmental effects. Under the 1990

Clean Air Act Amendments, EPA developed national emissions

standards for 186 hazardous chemicals, including SO2 and sulfur

oxide (SOx). National emissions standards for hazardous air

pollutants (NESHAPs) regulations specify an emissions limit based

on what is achievable with a specific control technology and the

chemical content of the inputs to the production process. For

example, to achieve the limits, petroleum refineries using crude oils

with different levels of sulfur content may require different scrubber

technologies on the catalytic cracker’s gas flue.

As a criteria pollutant, SO2 (combined with other sulfur oxides as

SOx) is also regulated under new source review (NSR) and new

source performance standards (NSPSs). NSR requirements are

BP Amoco recently

announced that it will

begin selling low-sulfur

gasoline in 40 cities

worldwide. Currently, BP

Amoco’s Amoco Ultimate

gasoline has the industry’s

lowest sulfur content

(outside of California) at

200 ppm. BP Amoco’s

goal is to meet or exceed

the 2005 European goal of

50 ppm (News and

Observer, 1999).
Appendix C — Profiles of Affected Industries

C-39

typically conducted by state agencies. This program applies to new

facilities or expansion of existing facilities or process modifications

and requires facilities to meet lower achievable emission rate

(LAER) standards compared to existing (unchanged) facilities. SO2

also falls under NAAQS and the acid rain program.

These emissions regulations affect all industries that use fossil fuels

as a fuel input, including petroleum refineries, coke and steel

plants, utility boilers, and industrial boilers.

These regulations affect industries’ fuel choices and profitability.

For example, public utilities commissions (PUCs) may have to

approve utilities’ fuel switching and emissions technology choices,

and they define the way costs are treated in the rate base and how

electricity prices are established (Bohi, 1994). Emissions reductions

have typically been achieved by specifying pollution control

technologies for SO2 emissions sources.

Air emissions from the stack gases from coal- and oil-fired boilers

are primarily regulated through technology-based performance

standards included in state and local permits. These performance

standards commonly identify specific combustion technologies or

end-of-pipe scrubber equipment that can be applied to individual

units (referred to as sources) to demonstrate compliance. These

technologies may require coals of a specific sulfur content (EPA,

1997a).

In addition to technology-based performance standards, generating

units may also be subject to other local or regional environmental

regulations, including NAAQ standards, the Acid Rain Program,

and the Acid Rain Allowance Trading Program.

NAAQ standards do not directly affect the fossil fuel electric power

generation industry because they are not applied to individual

sources. Rather, these standards are applied to the ambient air in a

particular area. Fossil fuel electric generators may be indirectly

affected by these standards if they are located in or near an area

with nonattainment status. Generators in nonattainment areas may

be targeted for more stringent controls implemented through local

operating permits.

The Acid Rain Program was authorized by the Clean Air Act to

reduce the adverse effects of acidic deposition on natural resources,
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-40

ecosystems, materials, visibility, and public health. The principal

sources of acidic compounds are emissions of SO2 and NOx from

the combustion of fossil fuels. To support the mandated reductions

in SO2 and NOx, EPA issued regulations requiring facilities in acid

rain regions to install continuous emission monitoring systems

(CEMS). In addition, all generating units in these regions over 25

megawatts (and new units under 25 megawatts) that use fuel with

sulfur content greater than 0.05 percent by weight are required to

measure and report emissions under the Acid Rain Program (EPA,

1997a).

The Acid Rain Allowance Trading Program is an innovative

approach included in the 1990 Clean Air Act Amendments

intended to reduce the costs of compliance while meeting the same

(or improved) environmental objectives. The approach provides a

firm with the flexibility to find the most cost-effective way of

achieving compliance through trading SO2 allowances. The

trading system exploits the potential efficiency gain from equating

the marginal cost of abatement (pollution reduction) for individual

sources within a facility and across companies in a trading region

(RFF, 1996). In the year 2001, steelmakers will join electric utilities

in trading SO2 emissions allowances under Title IV of the Clean Air

Act Amendments of 1990.

The market price for SO2 allowances is one measure of the impact

of sulfur content on the value of fossil fuels. The allowance price is

primarily determined by the market availability of low-sulfur coal

and the cost of purchasing and operating emissions abatement

technologies, such as SO2 scrubbers. In June 1998, the market

price for SO2 allowances hit a record high of $190 per ton (ACA,

1998).

For facilities exceeding emissions limits (whether or not they are

inadvertent), enforcement agencies can bring legal action resulting

in fines, prison terms, or both. Individuals can be fined up to

$25,000 per day for violations and can be sentenced to a year in

prison. Corporations can be fined up to $1,000,000 for each

offense. Furthermore, repeat offenders can have fines and

sentences doubled.

Other remedies exist for facilities that cannot meet an emissions

limitation. Production rates can be reduced to reduce emissions, or

Individuals can be

fined up to $25,000

per day for

violations and can

be sentenced to a

year in prison.

Corporations can be

fined up to

$1,000,000 for each

offense.
Appendix C — Profiles of Affected Industries

C-41

agreements can be established with permitting agencies to allow

full production in exchange for emissions reductions in other

processes or for other actions acceptable to the agencies.

C.2.2 Sulfur’s Role in Product and Process Quality

In addition to its detrimental impact on the environment, sulfur

content also affects the quality of products and processes that use

fossil fuels. For example, catalysts for low-emissions vehicles are

sensitive to the sulfur content of gasoline and diesel fuel. Similarly,

the catalysts used in petroleum processing can be “poisoned” by

sulfur; sulfur affects the technical quality of other petroleum

products as well. Fuel oils used in heat-treating metals or in firing

glass-melting furnaces must be low in sulfur to avoid damaging the

product. The sulfur content of coke has an impact on the quality of

the steel it is used to produce. As explained below, these technical

issues elevate the importance of accuracy and precision in the

measurement of sulfur content.

Sulfur Impact on Vehicle Catalysts

The technology for the low emissions vehicles of the future requires

low-sulfur fuels to operate efficiently. Sulfur in gasoline increases

exhaust emissions by decreasing the efficiency of the catalysts used

in current and advanced emissions control systems. The sulfur

affects the precious metals used in the catalyst; palladium is

especially sensitive to sulfur poisoning. Similarly, metal oxides

used to manage the oxygen concentrations in the exhaust are also

affected by sulfur (Hart’s Fuel Technology & Management’s Sulfur

2000, 1998).

Sulfur in gasoline can also have a detrimental effect on emerging

engine technologies. For example, the gasoline direct-injection

(GDI) engine offers the promise of improved fuel economy,

improved engine response under variable operating conditions, and

more rapid starting. However, performance of this technology is

sensitive to the sulfur content of gasoline. New fuel cell

technologies are also sensitive to the sulfur content of gasoline.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-42

Sulfur in Other Petroleum-Based Products and in

Refinery Processing

Other petroleum-based products are sensitive to the presence of

sulfur compounds. For example, undesirable sulfur compounds in

base oils used for lubricants lead to poor performance in lubricant

products. However, sulfur is present in many of the additives

blended into the base oils to enhance performance. Base oil,

additive, and lubricant product specifications typically include

allowable sulfur levels. Hence, monitoring sulfur levels for these

products is key to quality control.

Fuel oils used in heat-treating metals or in firing glass-melting

furnaces must be low in sulfur to avoid damaging the product. In

addition, some expensive process catalysts used in petroleum and

chemical refining can be poisoned when trace amounts of sulfurbearing materials are contained in feedstocks.

Steel

Sulfur is an undesirable property in steel except for special

purposes. Sulfur with iron forms sulfide, which is soluble in the

liquid metal and has a melting point lower than the other

constituents of the iron. This phenomenon, called “hot-shortness,”

may cause weaknesses in the steel. Sulfur also increases the

shrinkage of the iron, increasing the difficulty of making accurate

castings, as well as the tendency to form cracks (which are a result

of the high shrinkage) (Lankford et al., 1985). As a result,

specifications for the maximum allowable sulfur content in various

types of steel are on the order of 0.04 to 0.05 percent.

The major source of sulfur in the steel-making process is from coal,

which is made into coke as described in Section C.1.2. Coal is

processed into coke by a process called coking, which takes place

in coke oven batteries. Coke that contains too much sulfur affects

the productivity of the steel-making process as well as the sulfur

content of the steel. Sulfur from the coke used in the blast furnace

becomes part of the slag, which is a by-product of the blast furnace

(the other product is molten iron). A good deal of the sulfur is

removed from the blast furnace with the slag, which removes other

impurities from the molten iron as well. If the coal contains too

much sulfur, the volume of slag that is generated increases,

Scientists have determined

that one factor contributing

to the demise of The

Titanic was that the steel

used in its construction had

a high sulfur content,

which caused it to be

brittle, especially under

very cold conditions

(Modern Marvels, 1999).
Appendix C — Profiles of Affected Industries

C-43

decreasing the productivity of the blast furnace. Some sulfur

remains dissolved in the iron (Lankford et al., 1985).

If the coal has too much sulfur, additional treatment is required to

remove excess sulfur from the final product. After the iron is

removed from the blast furnace, it goes through a desulfurization

process. Flux materials are added to the iron, and the sulfur is

removed in a ladle prior to charging the iron to the steel-making

furnace (Lankford et al., 1985).

C.3 USAGE OF NIST SRMS IN THE FOSSIL FUEL

INDUSTRY

As described in Section 3, NIST SRMs are used by the measurement

and fossil fuel industries to develop CRMs, to calibrate instruments,

and to check the accuracy of analytical methods. The chain of

traceability of all sulfur measurements to NIST SRMs begins with

the direct customers of NIST SRMS.

Figure C-8 shows the role that NIST SRMs play in the integrity of

the measurement system. SRMs are developed using definitive

methods that are tied to the basic measurement units maintained at

NIST. NIST definitive methods are methods involving high

precision primary techniques and have been critically evaluated for

sources of bias in each specific application. SRMS are then used to

develop and evaluate reference methods, to ensure the accuracy of

secondary reference materials, and to ensue accuracy in critical

quality assurance applications. Secondary reference materials and

reference methods are then used to develop and evaluate field

methods to prepare working reference material such as calibrants

and to perform routine quality assurance activities. The integrity of

this system is based on the quality of NIST SRMS and their

traceability, through definitive methods, to the basic measurement

units.

C.3.1 How Industry Uses NIST SRMs

SRMs play an integral role in users’ quality control programs.

Companies use SRMs in four ways: to calibrate equipment, to

develop and validate the accuracy of analytical methods, to prepare
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-44

Figure C-8. SRM Role in Measurement Accuracy

NIST SRMs play an integral role in users’ quality control programs. They are used to develop and evaluate analytical

methods, to produce secondary standards, and in quality assurance applications.

,

Basic

Measurement

Units

,,,

NIST

SRMs

,9

Reference

Methods

9

Secondary

Reference

Materials

9,

Field

Methods

,,

Definitive

Methods

é Reference Method

Development and Evaluation

é Production of High-Accuracy

Secondary Reference

Materials

é Critical Quality Assurance

Applications

é Field Method Development

and Evaluation

é Preparation of Routine

Working Reference

Materials

é Routine Internal and

External Quality Assurance

Field Applications

Source: Taylor, John K. 1993. Standard Reference Materials: Handbook for SRM Users. NIST Special Publication

260-100. Washington, DC: U.S Government Printing Office. February.
Appendix C — Profiles of Affected Industries

C-45

standards, and to set contracts and settle disputes. Figure C-9

illustrates the various points at which the sulfur content of the fuel

may be tested.

Figure C-9. Sulfur Testing Along the Coal and Oil Supply Chain

Figure C-9 illustrates the various points at which the sulfur content of the fuel may be tested.

Mines ★ Coal Washing

Plant ★

COAL

OIL

Well ★ Refinery ★

★ = Testing

Pump ★

Testing in Transit 

★

★

★ ★

Tanker

Pipeline

Steel 

Works ★

Petroleum

Coke for

Aluminum ★

Utility ★

Because SRMs are costly, firms generally use NIST-traceable

secondary reference materials for routine tasks. Companies’ use of

NIST SRMs is consistent with the model shown in Figure C-8.

Generally, firms do not use SRMs each time they calibrate their

equipment. Because SRMs are more costly than other reference

materials, firms use NIST-traceable secondary reference materials to

calibrate the equipment and perform other routine tasks. SRMs are

used to verify that the equipment is properly calibrated. This

technique allows firms to maintain traceability and quality while

keeping costs down. NIST SRMs for calibration or calibration

verification give users confidence in the precision of their

instruments and the accuracy of those instruments’ results.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-46

Properly calibrated equipment is required for accurate sulfurcontent testing and for applications development. Utilities,

petroleum companies, coal companies, and other firms need

properly calibrated equipment to ensure that the fuel they have

bought or sold meets the sulfur-content specifications detailed in

contracts. There are financial, and often regulatory, penalties for

failing to meet those specifications. Equipment manufacturers use

NIST SRMs to ensure that products are functioning properly and to

test new prototypes.

NIST SRMs are also used in the production of certified reference

materials, or CRMs. Many firms produce CRMs for in-house use or to

sell to other firms and NIST SRMs are used in the quality control and

production processes. By using NIST SRMs to calibrate equipment

and validate equipment performance, CRM manufacturers make their

products traceable to NIST. NIST traceability is a key component of a

CRM manufacturer’s credibility.

SRMs also support the analytical methods used by firms to take

measurements and develop products and services. Indeed, many

standard analytical methods call for SRMs because they are easily

obtainable and authoritative. SRMs also allow firms to more

accurately determine the bias of the methods they are using.

In addition, SRMs provide a common, independent benchmark

from which industry can develop product specifications and legally

binding contracts. Natural matrix SRMs are superior to other

reference materials because they are certified using critically

evaluated methods. SRMs lend credibility and legal defensibility to

measurements.

When disputes over measurement accuracy arise between firms,

SRMs are used as a referee material. For example, if a firm

purchases a sulfur analyzer and later complains that instrument is

not functioning properly, the manufacturer will validate the

accuracy of the instrument’s measurements using NIST SRMs.

Generally, fuel contracts will explicitly state that in the event of a

dispute over a fuel’s sulfur content or the precision of an instrument

that ASTM methods and NIST SRMs will be used to referee the

dispute settlement.

Regulatory agencies use SRMs to support their quality control

programs, which in turn play an important role in regulatory
Appendix C — Profiles of Affected Industries

C-47

enforcement. To reduce the possibility of being out of compliance

with environmental regulations, regulators and industry prefer to

use the same standards and methods.

Regulators use SRMs to verify the calibration of their laboratory

instruments with NIST SRMs. Like industry, regulators use NISTtraceable CRMs, which they may have purchased or prepared inhouse, to calibrate equipment. The more expensive NIST SRMs are

used at regular intervals to ensure the equipment is functioning

properly.

NIST’s SRM program supports the reproducibility and accuracy of

the ASTM methods used to determine compliance by providing an

authoritative primary standard. If SRMs were not available, greater

uncertainty might occur regarding whether a plant was in

compliance. Disagreements between a company and the

regulatory agency regarding whether a plant was in compliance

might result should a primary standard not be available.

C.3.2 SRM Customers

Table C-21 classifies the customers of the NIST SRMs under study

for the past 9 years and shows the number of units purchased by

each class of customers. From 1982 to early 1999, 2,954 different

organizations purchased 45,673 units of sulfur fossil fuel SRMs.

Each level of the supply chain shown in Figure C-1 is represented

among NIST’s customers. As one would expect, among the largest

group of customers are members of the sulfur measurement industry

and members of the fuel extraction and processing industries.

Public utilities are also important customers.

NIST SRMs are also purchased by users not specifically shown in

Figure C-1. These companies include other U.S. industrial

customers, such as cement and stone manufacturers, chemicals

manufacturers, paper and allied products companies, and waste

management companies. These companies could be using NIST

SRMs to support sulfur measurements required for compliance with

environmental regulations on industrial boilers. U.S. federal, state,

and local governments also purchase NIST SRMs for environmental

compliance purposes, and a number of foreign companies,

universities, laboratories, and governments also purchase NIST

SRMs for sulfur in fossil fuels.
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-48

Table C-21. Customers of NIST SRMs for Sulfur in Fossil Fuels Since 1982

Customers of NIST fossil fuel SRMs include members of each level of the supply chain, as well as a substantial number

of government and private users from other countries.

Industry

Number of

Customers

Number of Units

Purchased

Measurement Industry

Instrument Manufacturers 92 2,300

Reference Material Manufacturers 8 109

Laboratories, Consultants, and Universities 776 12,838

Fossil Fuel Extraction, Processing, and Transportation

Fossil Fuel Extraction and Processing 455 12,191

Fuel Transportation and Export 95 903

Fossil Fuel Combustion

Utilities and Utility Services 152 5,648

Steel Industry 33 301

Other U.S. Industrial Customers 358 3,501

Other SRM Users

U.S. Federal, State, and Local Governments 212 1,265

Foreign Governments 77 542

Foreign Laboratories, Consultants, and Universities 233 1,312

Foreign Manufacturers 407 4,481

Unclassified 56 282

Total 2,954 45,673

Source: SRM purchase data provided by NIST’s SRM program.

Table C-22 shows the number of customers by SRM and the total

number of units purchased by SRM and customer type. The

number of units of NIST SRMs purchased is lower for industry

segments that are farther down the supply chain. This suggests that,

while sulfur measurements at the top of the supply chain are often

supported by NIST SRMs, downstream elements of the supply chain

rely more heavily on secondary reference materials, which may, in

turn, be supported by NIST SRMs.
Appendix C 

— Profiles of Affected Industries

C-49

Table C-22. SRM Purchases by SRM, 1982 to Early 1999Industries farther down the supply chain use fewer NIST SRMs.

Number of Purchases by Sector

SRM Description

First

Certification

Date

Number

of

Batchesa

Number

of

Customers

Measurement

Industry

Fuel Extraction,

Processing, and

Transportation

Fuel

Combustion

Other SRM

Users Unclassified Total

1616 Sulfur in Kerosene 2/19/88 2 442 442 658 102 212 2 1,4161617 Sulfur in Kerosene 2/19/88 2 423 471 620 74 171 0 1,3361619 Sulfur in Residual Fuel Oil, 0.7% 12/22/81 3 647 1,230 898 509 574 14 3,2251620 Sulfur in Residual Fuel Oil, 4% 12/1/79 2 597 833 518 222 391 11 1,9751621 Sulfur in Residual Fuel Oil, 1% 12/11/67 4 847 1,242 1,044 500 622 15 3,4231622 Sulfur in Residual Fuel Oil, 2% 12/11/67 4 825 1,209 1,080 412 598 14 3,3131623 Sulfur in Residual Fuel Oil, 0.3% 4/7/71 3 652 742 620 299 354 10 2,0751624 Sulfur in Distillate Fuel Oil, 0.4% 4/7/71 3 643 496 786 247 396 10 1,9351632 Trace Elements in Coal (Bituminous) 3/7/75 2 561 765 308 654 698 6 2,431

1633 Trace Elements in Coal Fly Ash 3/7/75 2 1,033 794 152 364 1,484 33 2,8271635 Trace Elements in Coal

(Subbituminous)

10/24/95 1 120 47 16 70 100 2 235

1819 Sulfur in Lubricating Base Oil 7/17/85 2 193 87 97 80 90 3 3572294 Reformulated Fuels (nom. 11%

MTBE, 35 mg/kg sulfur)

3/10/98 1 6 3 17 0 0 0 20

2295 Reformulated Fuels (nom. 15%

MTBE, 300 mg/kg sulfur)

3/10/98 1 3 1 6 0 0 0 7

(continued)
Economic Impact of Standard Reference Materials for Sulfur in Fossil Fuels

C-50 Table C-22. SRM Purchases by SRM, 1982 to Early 1999 (continued)

Number of Purchases by Sector

SRM Description

First

Certification

Date

Number

of

Batchesa

Number

of

Customers

Measurement

Industry

Fuel Extraction,

Processing, and

Transportation

Fuel

Combustion

Other SRM

Users Unclassified Total

2296 Reformulated Fuels (nom. 13% ETBE,

35 mg/kg sulfur)

3/10/98 1 2 1 1 0 0 0 2

2297 Reformulated Fuels (nom. 10%

Ethanol, 300 mg/kg sulfur)

3/10/98 1 2 1 1 0 0 0 2

2682 Sulfur in Coal, 0.5% 12/14/82 2 473 702 864 818 286 6 2,6762683 Sulfur in Coal, 2% 12/14/82 3 508 1,370 1,215 1,637 223 12 4,4572684 Sulfur in Coal, 3% 12/14/82 2 427 1,663 1,170 1,410 182 122 4,5472685 Sulfur in Coal, 5% 12/14/82 2 397 914 606 838 167 16 2,5412690 Trace Elements in Coal Fly Ash 12/20/93 1 183 109 21 59 203 2 3942691 Trace Elements in Coal Fly Ash 12/20/93 1 212 121 71 122 209 1 5242692 Sulfur in Coal, 1% 11/15/88 2 288 1,059 478 679 281 0 2,4972717 Sulfur in Residual Fuel Oil 10/25/90 1 299 378 346 107 185 2 1,0182724 Sulfur in Distillate Fuel Oil, 0.04% 8/17/92 2 391 560 1,440 229 171 1 2,4012775 Foundry Coke 5/12/99 1 14 6 7 17 3 0 332776 Furnace Coke 3/19/98 1 4 1 4 1 0 0 6

Totals 52 10,192 15,247 13,044 9,450 7,600 282 45,673

aNumber of batches that were sold between 1982 and early 1999.

Source: Based on data provided by NIST’s SRM program.